Olivier Couture

Vincent Hingot

Baptiste Heiles

Pauline Muleki-Seya

Mickael Tanter

Ultrasound localization microscopy and superresolution: a state-of-the-art

), the kidney and in tumors. In the clinic, ULM is bound to improve drastically our vision of the microvasculature, which could revolutionize the diagnosis of cancer, arteriosclerosis, stroke and diabetes, among others. Figure 1: Ultrasound Localization Microscopy of the living rat brain (reconstructed from data in [1])

Ultrasound imaging: Lower frequency means more penetration

Science is guided by our quest for studying and understanding the invisible. Through history, the invention of instruments to distinguish objects that are too small or hidden to the naked eye has lead to new understanding of matter and life. Optical microscopy, for instance, was invented four centuries ago and has been essential to the discovery of cellular processes and pathogens, thus indirectly saving hundreds of millions of lives. It benefits from a spatial resolution, the capacity to distinguish close objects, in the hundreds of nanometers. It is only limited by its wavelength by diffraction. However, optical microscopy is generally bound to shallow specimen due to its lack of penetration. When applied to human health, these microscopes remain the gold-standard for the diagnosis of many diseases, such as cancer, through histopathology.

The opacity of the human body to light, nonetheless, has justified the invention of imaging modalities that can observe the organs of interest through several centimeters of tissue. X-ray, ultrasound, magnetic resonance imaging (MRI), positron emission tomography (PET), and computed tomography (CT) are now common household names, each applied differently due to their respective trade-offs between resolution, contrast source, penetration, sensitivity, frame-rate, full-body nature, cost, availability, etc. Nevertheless, none of these medical imaging techniques has approached the resolution of optical microscopy in depth, either because of a fundamental compromise due to diffraction, as in ultrasound imaging, or through a more complex consideration such as radiation dose, acquisition time or mean free particle path.

More than seventy years after its birth [START_REF] Chilowsky | Procédés et appareils pour la production de signaux sousmarins dirigés et pour la localisation à distance d'obstacles sous-marins[END_REF] [3] [START_REF] Newman | The history of ultrasound[END_REF], ultrasound imaging remains a key modality for observing the heart, liver, kidneys, breast, testis, prostate, thyroid, muscles, vascular structures and the human foetus. Helped with its excellent spatial resolution (few hundred microns) and time resolution (tens of frames per second), conventional ultrasound provides a window in soft tissue that guides diagnosis, prognosis and interventions in hospitals throughout the world [START_REF] Cobbold | Foundations of Biomedical Ultrasound[END_REF]. For physiological imaging, standard B-mode images can be overlaid with pulsed-Doppler which provides maps of blood vessels with flows beyond a few cm/s. Doppler is a key component of most ultrasound exams today, as it yields information on the organs function, and not just their anatomy.

As conventional Doppler ultrasound relies on the rapid displacement of red blood cells to detect them with respect to tissue, slow flow remained difficult to observe. The discovery of ultrasound contrast agents by Gramiak and Shah [START_REF] Gramiak | Ultrasound Cardiography: Contrast Studies in Anatomy and Function[END_REF] allowed the indirect observation of the smallest vessels through the detection of intravascular microbubbles. Even in relatively small concentrations (in the order of 1 per 10 5 red blood cells), injected bubbles of air or perfluorocarbon a few microns in size increase the intensity of blood vessels by more than a factor of a hundred. This is due to impedance mismatch between blood and gas, but also by the resonance of these natural oscillators [START_REF] Leighton | The acoustic bubble[END_REF]. Moreover, microbubbles oscillation can become nonlinear at clinically-relevant acoustic pressure range, helping their detection with respect to mostly linear tissue [START_REF] Mulvana | Characterization of contrast agent microbubbles for ultrasound imaging and therapy research[END_REF]. When a certain threshold is attained, these contrast agents can also be disrupted by ultrasound, enabling differential imaging. In fact, ultrasound is so sensitive to pockets of gas that single microbubbles can be detected [START_REF] Klibanov | Detection of Individual Microbubbles of Ultrasound Contrast Agents: Imaging of Free-Floating and Targeted Bubbles[END_REF]. Microbubbles greatly enhance the perfusion of liver tumor [START_REF] Brannigan | Blood flow patterns in focal liver lesions at microbubble-enhanced US[END_REF], prostate tumor [START_REF] Wijkstra | Contrast specific imaging in the detection and localization of prostate cancer[END_REF] or myocardium [START_REF] Lepper | Myocardial contrast echocardiography[END_REF] in clinical settings.

Beyond microbubbles, research in ultrasound imaging is undergoing a paradigm shift with the availability of the ultrafast programmable ultrasound scanner. By using plane-wave emissions rather than line-by-line pulse-echo, frame rates were increased from 50 Hz to 20,000 Hz giving access to rapid phenomena [START_REF] Tanter | Ultrafast imaging in biomedical ultrasound[END_REF]. The concept of ultrafast ultrasound, denominated and initiated in the 1970's [START_REF] Bruneel | Ultrafast echotomographic system using optical processing of ultrasonic signals[END_REF], [START_REF] Delannoy | Acoustical image reconstruction in parallel-processing analog electronic systems[END_REF], has found its first clinical application with transient elastography [START_REF] Sandrin | Time-resolved pulsed elastography with ultrafast ultrasonic imaging[END_REF]and Shear Wave Elastography [START_REF] Tanter | Ultrafast compound imaging for 2-D motion vector estimation: Application to transient elastography[END_REF] which demonstrated that the elasticity of tissue can be mapped and quantified indepth to help the diagnosis of breast cancer [START_REF] Tanter | Quantitative Assessment of Breast Lesion Viscoelasticity: Initial Clinical Results Using Supersonic Shear Imaging[END_REF] and liver fibrosis [START_REF] Bavu | Noninvasive In Vivo Liver Fibrosis Evaluation Using Supersonic Shear Imaging: A Clinical Study on 113 Hepatitis C Virus Patients[END_REF], for example. The accumulation of thousands of ultrasound images at ultrafast frame rates also allows the observation of slow processes, such as blood flow in the mm/s range [START_REF] Bercoff | Ultrafast compound doppler imaging: Providing full blood flow characterization[END_REF]. This is due to the increased amount of data and to the possibility to use more efficient filters on long ensembles of images such as singular value decomposition [START_REF] Demené | Spatiotemporal Clutter Filtering of Ultrafast Ultrasound Data Highly Increases Doppler and fUltrasound Sensitivity[END_REF] in order to unambiguously discriminate tissue motion and very slow blood flows. This increase of sensitivity by more than an order of magnitude gives new information on blood flow in various organs, including newborn brains [START_REF] Demené | Ultrafast Doppler reveals the mapping of cerebral vascular resistivity in neonates[END_REF]. It opened an entirely new field with functional ultrasound [START_REF] Macé | Functional ultrasound imaging of the brain[END_REF] [START_REF] Deffieux | Functional ultrasound neuroimaging: a review of the preclinical and clinical state of the art[END_REF], which can map the neuronal brain activation of free-moving animals [START_REF] Sieu | EEG and functional ultrasound imaging in mobile rats[END_REF][26], human newborns [START_REF] Demene | Functional ultrasound imaging of brain activity in human newborns[END_REF] and during brain surgery in adults [START_REF] Imbault | Intraoperative Functional Ultrasound Imaging of Human Brain Activity[END_REF]. The combination of ultrafast imaging and microbubbles was also shown to be fruitful since it reduces microbubble disruption for an enhanced contrast [START_REF] Couture | Ultrafast Imaging of Ultrasound Contrast Agents[END_REF], [START_REF] Couture | Ultrasound Contrast Plane Wave Imaging[END_REF]. Moreover, Doppler sequences can be easily interleaved with ultrafast nonlinear pulses [START_REF] Tremblay-Darveau | Combined perfusion and doppler imaging using plane-wave nonlinear detection and microbubble contrast agents[END_REF]. It also permitted transcranial ultrasound functional imaging [START_REF] Errico | Transcranial functional ultrasound imaging of the brain using microbubble-enhanced ultrasensitive Doppler[END_REF]. Moreover, it can provides a higher contrast-to-tissue ratio than nonlinear methods even in a clinical setting for microbubbles moving faster than a few mm/s [START_REF] Desailly | Contrast enhanced ultrasound by real-time spatiotemporal filtering of ultrafast images[END_REF]. We shall see below that it can do much more.

Beyond frame rates, the introduction of software-based ultrasound scanners has opened new possibilities in ultrasound research laboratories, allowing the rapid introduction and in-vivo testing of new sequences. Rather than modifying the electronic hardware, we can now rapidly modify parameters of emission, reception and beamforming to yield new types of contrast, a freedom that MRI-scientists have enjoyed for many years now. With the help of the ultrafast programmable ultrasound scanner, we expect the blossoming of many ultrasound-based techniques in the near future [34][35], [START_REF] Fink | Time-Reversal Acoustics in Biomedical Engineering[END_REF].

However, even at 20,000 frames per second, ultrasound imaging remains bound to diffraction due to its undulatory nature and is confined by the compromise between penetration and resolution. For instance, cardiac imaging performed at 3 MHz to achieve a penetration of 15 cm will be limited to a 1mm resolution in practical conditions [Figure 2]. It can be improved through harmonic imaging [START_REF] Tranquart | Clinical Use of Ultrasound Tissue Harmonic Imaging[END_REF], but resolution remains bound to the submillimetric regime. Indeed, the resolution of ultrasound is defined by diffraction, which eliminates, in the far-field, aspects that are smaller than approximately a half-wavelength. For instance, the lateral resolution is linked to the full-width at half-maximum of the point-spread function [START_REF] Cobbold | Foundations of Biomedical Ultrasound[END_REF]: FWHM=1.4 ʎ F/D, where ʎ is the wavelength, F is the focal length and D is the aperture. Knowing that the attenuation of ultrasound in tissue also depends on frequency, with a relationship of f 1 to 2 (where ʎ =c/f, where c is the speed of sound and f is the frequency), it is clear that a better resolved image will be generally achievable at a shallower depth. Therefore, the resonance frequency of the piezoelectric crystal, the choice of the probe and, sometimes, the electronics, is bound by this compromise between resolution and penetration, restricting the options for radiologists and researchers alike.

A better resolved ultrasound

Several approaches have been proposed to improve the resolution of ultrasound imaging. Increasing the frequency is the most direct possibility [START_REF] Lockwood | Beyond 30 MHz[END_REF]. Exploiting scanners using pulses beyond 15 MHz for high-frequency ultrasound gives access to resolution below 100 microns. But, for a 100 dB dynamic range, the maximum imaging depth is about 300 wavelengths, which limits penetration to 30mm at 15 MHz and 10 mm at 35 MHz [START_REF] Foster | A New 15-50 MHz Array-Based Micro-Ultrasound Scanner for Preclinical Imaging[END_REF]. High-frequency ultrasound is now widespread in animal models and can be used to observe implanted tumors [START_REF] Goertz | High-frequency Doppler ultrasound monitors the effects of antivascular therapy on tumor blood flow[END_REF], cardiac imaging [START_REF] Sun | A high-frame rate high-frequency ultrasonic system for cardiac imaging in mice[END_REF], fetal development [START_REF] Turnbull | In vivo ultrasound biomicroscopy in developmental biology[END_REF], and many other applications. In human applications, it can be used for intravascular ultrasound with the exploitation of a catheter-based ultrasonic probe [START_REF] Potkin | Coronary artery imaging with intravascular high-frequency ultrasound[END_REF].

An important step toward higher resolutions was achieved with the development of ultrasound angiography [START_REF] Gessner | Acoustic angiography: A new imaging modality for assessing microvasculature architecture[END_REF], [START_REF] Shelton | Quantification of microvascular tortuosity during tumor evolution using acoustic angiography[END_REF]. This technique uses the very high ultraharmonics (10th harmonic or higher) emitted by microbubbles after insonification at relatively low frequencies (2.25 MHz for example) to reconstruct images of vessels. This means that the propagation length at the highest frequency is halved, improving the compromise between resolution and penetration. This technique, which required dual-transducer technology, was applied to the imaging of subcutaneous tumor models.

Nevertheless, ultrasound angiography and high-frequency ultrasound remain limited to the diffractionlimit as they simply exploit shorter wavelengths to create images. In this review, we shall define super-resolution ultrasound as a technique that surpasses the classical limit of diffraction for imaging and allows the detection and separation of subwavelength features. In general, the separability of two objects or structures distant by less than half of the minimum wavelength is considered an appropriate criteria for super-resolution.

The diffraction-limit is applicable in the far-field and an elegant way to bypass this compromise is to perform imaging in the near-field. Less than a few wavelengths away from a probe, evanescent waves allow the observation of structures that are in the order of the distance between the instrument and the object [START_REF] Shekhawat | Applied physics: Nanoscale imaging of buried structures via scanning near-field ultrasound holography[END_REF]. This subtend ultrasound microscopy, where the acoustical waves is generated and detected within a micrometer or less from the sample. It can map acoustical contrast, linked to the density and compressibility of objects at a nanometric scale. However, in medical imaging, organs are often at hundreds of wavelengths from the probe and near-field super-resolution techniques are difficult to apply.

Another way to achieve super-resolution for other contrasts such as optical absorption, shear modulus, or dielectric permittivity is to exploit the interactions between ultrasound and other waves of different nature. In this approach, called multi-wave imaging [START_REF] Fink | Multiwave imaging and super resolution[END_REF], ultrasound is often used to improve the conventional resolution provided by other types of waves; optical waves in photo-acoustics, shear waves in elastography or electromagnetic waves in acousto-electric imaging. For practical reasons, we will restrict this review to the single use of ultrasonic waves for far-field imaging.

The development of metamaterials have also introduced new ideas around super-resolution by allowing super-focusing in the near field of resonant heterogeneities with electromagnetic waves [START_REF] Lerosey | Focusing beyond the diffraction limit with far-field time reversal[END_REF].

The idea is inspired by Pendry's "perfect lens" with doubly-negative material [START_REF] Pendry | Negative refraction makes a perfect lens[END_REF]. In ultrasound, such materials known as phononic crystals were shown to achieve resolutions close to ʎ/3, which is better than the diffraction-limit [51][52].

Closer to the concept of localization, super-resolution ultrasound was also shown to be achievable when a limited number of scatterers are present in the observed medium [53][54]. Through a combination of maximum-likelihood and multiple signal characterization (MUSIC) and decomposition of the time-reversal operator (DORT), Prada and Thomas [START_REF] Prada | Experimental subwavelength localization of scatterers by decomposition of the time reversal operator interpreted as a covariance matrix[END_REF] were able to demonstrate experimentally subwavelength localization of scatterers when the number of these scatterers was smaller than the number of array elements. In particular, they were able to separate two point-like scatterers ʎ/3 apart in the far-field. It required several realizations, beyond the number of scatterers to be separated. Unfortunately, from an acoustic point of view, the nature of biological tissues inherently corresponds to a random distribution of millions of spatially unresolved Rayleigh scatterers (the socalled "speckle noise") whose number is orders of magnitude larger than the limited number of independent ultrasonic transmitters composing an ultrasonic imaging scanner. Thus, all these methods were unlikely to be achievable in a fully-developed speckle in ultrasound imaging as the scatterers are considered innumerable. However, a very interesting insight from these researchers was that super-resolution is possible in ultrasound imaging if a restricted number of scatterers is detectable.

Other approaches to achieve a form of super-resolution exploit strongly conditioned a priori information on the object or the insonification pattern. For instance, Clement et al. [START_REF] Clement | Superresolution ultrasound imaging using backprojected reconstruction[END_REF] described an experiment where known single wires could be measured with a thickness much smaller than the wavelength. An approach exploiting the Moiré effect from multiple ultrasonic beam was also introduced as acoustical structured illumination by Ilovitsch et al. [START_REF] Ilovitsh | Acoustical structured illumination for super-resolution ultrasound imaging[END_REF]. With multiple emissions of shifted patterns, they were able to improve the resolution of the image by a factor of 2. However, it requires a precise a priori calculation of the phase of the propagating field.

Hence, the field of super-resolution ultrasound is several decades old [START_REF] Ikeda | Super-resolution imaging system using waves with a limited frequency bandwidth[END_REF][59] and its development remained sparse until recently due to the incapacity of ultrasonic waves to separate the signature of millions of randomly distributed scatterers and without a strong a priori information. It took a revolutionary development in the field of optics, an undulatory close-kin to ultrasound, to create a new excitement for super-resolution ultrasound, namely localization microscopy.

An optical res/volution

Even with the introduction of these various approaches to breach the diffraction-limit, the applicable resolution of ultrasound imaging remained, until recently, desperately wavelength-like. This situation has also plagued optical microscopy in the past, which has also seen numerous examples of nearfield approaches [START_REF] Betzig | Near-Field Optics: Microscopy, Spectroscopy, and Surface Modification beyond the Diffraction Limit[END_REF], metamaterials concept [START_REF] Lu | Hyperlenses and metalenses for far-field super-resolution imaging[END_REF], structured illumination [START_REF] Gustafsson | Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy[END_REF][60] and other processes to defeat their diffraction-limit of a few hundred nanometers. This state-of-affair was revolutionized by optical localization microscopy [START_REF] Betzig | Imaging intracellular fluorescent proteins at nanometer resolution[END_REF] whose implications and applications created sufficient ripple for the 2014 Chemistry Nobel Prize to be awarded to Eric Betzig, Stefan Hell and William E. Moerner [START_REF] Möckl | Super-resolved Fluorescence Microscopy: Nobel Prize in Chemistry 2014 for Eric[END_REF].

Biological applications of optical microscopy rely heavily on fluorescent tiny beacons within the observed object [START_REF] Udenfriend | Fluorescence Assay in Biology and Medicine[END_REF], which are used to label every aspect of molecular pathways, antibodies, genetic materials, etc. Reporter genes inducing the production of fluorescent proteins have revolutionized genetics, also yielding a Nobel prize in 2008 [START_REF] Chalfie | Green fluorescent protein as a marker for gene expression[END_REF]. As demonstrated by Moerner and Kador [START_REF] Moerner | Optical detection and spectroscopy of single molecules in a solid[END_REF] and Betzig and Chichester [START_REF] Betzig | Single molecules observed by near-field scanning optical microscopy[END_REF], optical microscopes are sufficiently sensitive to detect single fluorescent labels.

The nonlinear response of certain fluorescent labels can allow the restriction of the focal spot within a fraction of the wavelength, such as in the STED technique (Stimulated emission depletion [START_REF] Hell | Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy[END_REF]).

This technique which exploits the selective deactivation of fluorophores within a doughnut-shape surrounding the observation spot can achieve resolutions in the order of tens of nanometer [START_REF] Hell | Far-field optical nanoscopy[END_REF]. Even with the necessary beam scanning, it can achieve up to 200 frames per second in optimal conditions [START_REF] Lauterbach | Dynamic imaging of colloidalcrystal nanostructures at 200 frames per second[END_REF].

The stochastic blinking of fluorescent labels observed over large numbers of frames can also be used to increase resolution. In PALM (photoactivated localization microscopy [START_REF] Betzig | Imaging intracellular fluorescent proteins at nanometer resolution[END_REF],à), FPALM (fluorescence photoactivation localization microscopy [START_REF] Hess | Ultra-high resolution imaging by fluorescence photoactivation localization microscopy[END_REF]) or STORM (stochastic optical reconstruction microscopy [START_REF] Rust | Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)[END_REF]), fluorescent labels switch between bright and dark states, making it such that only a subset of them are observable in each image [START_REF] Huang | Breaking the diffraction barrier: Super-resolution imaging of cells[END_REF]. Due to the limited number of sources in each image, the responses of the fluorescent labels do not interfere with each others. Consequently, it is possible to deconvolve the point-spread-function of the system from the image and determine the centroid of the sources with a localization precision much higher than the wavelength [START_REF] Deschout | Precisely and accurately localizing single emitters in fluorescence microscopy[END_REF]. FPALM, PALM and STORM exploit this blinking to accumulate the localization of point sources over thousands of images to recreate a super-resolved image. Betzig et al. [START_REF] Betzig | Imaging intracellular fluorescent proteins at nanometer resolution[END_REF] demonstrated that the error on the fitted position is dependent on "the standard deviation of a Gaussian approximating the true PSF" and inversely correlated to the square-root of the number of detected photons from the source. More than 10,000 photons can be collected from single sources, yielding a potential resolution of 1 nm for a wavelength of a few hundred nanometers! In practical situations, the resolution is within tens of nanometers, which is already an order of magnitude better than the wavelength. However, accumulation time and damaging fluence can be detrimental.

In general, photoactivated localization microscopy requires several conditions [START_REF] Von Diezmann | Three-Dimensional Localization of Single Molecules for Super-Resolution Imaging and Single-Particle Tracking[END_REF]:

a. Sensitivity: A sensitivity allowing the detection of labels that are much smaller than the wavelength (1/1000) b. Localization: The positioning of these labels with a precision better than the diffraction limit.

c. Video recording:

Multi-frame acquisition at a relatively high frame rate.

d. Isolated sources in a spatiotemporal referential:

A switchable label to restrict their local concentration at a specific time point in order to ensure the possibility of localizing them.

For FPALM, these conditions were achieved with switchable fluorescent labels and video cameras connected to the optical microscope.

Super-resolution optical fluctuation imaging (SOFI) also exploits the blinking of fluorescent sources and a video-recording to increase the resolution of optical microscopy [START_REF] Dertinger | Fast, background-free, 3D superresolution optical fluctuation imaging (SOFI)[END_REF]. However, it relies on the higher-order statistics of temporal fluctuations rather than localizing individual sources. Because the spatial distribution of cumulants from the image series narrows as the order of cumulants increases, a superior resolution can be attained. This technique is significantly more rapid than photoactivated localization microscopy and it requires less fluence. However, it yields a limited improvement of the resolution dependent on the square-root of the cumulant order and noise can become detrimental in imaging applications beyond the second-order [START_REF] Geissbuehler | Comparison between SOFI and STORM[END_REF].

As demonstrated by the attribution of the Nobel Prize, the field of optics and its biological applications benefited enormously from the development of super-resolution microscopy [START_REF] Sengupta | Superresolution imaging of biological systems using photoactivated localization microscopy[END_REF]. Biological processes at the scale of the nanometers, such as adhesion dynamics [START_REF] Shroff | Live-cell photoactivated localization microscopy of nanoscale adhesion dynamics[END_REF], single-molecule trajectories [START_REF] Manley | High-density mapping of single-molecule trajectories with photoactivated localization microscopy[END_REF] or microtubules organization [START_REF] Shtengel | Interferometric fluorescent super-resolution microscopy resolves 3D cellular ultrastructure[END_REF] are now accessible.

Ultrasonic replication

Within 5 years after Betzig's paper [START_REF] Betzig | Imaging intracellular fluorescent proteins at nanometer resolution[END_REF], our team proposed to apply equivalent approaches to exploit localization microscopy in ultrasound [START_REF] Couture | Microbubble ultrasound superlocalization imaging (MUSLI)[END_REF], [START_REF] Couture | Method and device for ultrasound imaging[END_REF]. The suggested idea was to use ultrasound contrast agents as the punctual sources and ultrafast imaging of their disruption or movement as the necessary state fluctuation in the backscattered signals. Indeed, the important idea that ultrafast differential imaging was able to catch very transient fluctuations had recently been demonstrated for the estimation of the fast dissolution dynamics of microbubbles after disruption in [START_REF] Couture | Ultrafast Imaging of Ultrasound Contrast Agents[END_REF] and for the estimation of the in vivo cavitation threshold by tracking the appearance of a single cavitation bubble in the brain [START_REF] Gateau | Combined passive detection and ultrafast active imaging of cavitation events induced by short pulses of high-intensity ultrasound[END_REF]. For ULM, the general principle is to emit an ultrasonic pulse in a medium that contains microbubbles and collect the received echo. In the matrix of radio-frequency (RF) data acquired by each channel (number of samples x number of elements), single echoes of microbubbles propagating at a constant speed of sound (c) are represented by hyperbolas described by the time-offlight to arrive at each transducer element. If this echo is unique, a simple fit can provide the position of the microbubbles with a much higher resolution than the wavelength. Even if the echo is beamformed by a clinical scanner, a process that converts the hyperbola on RF channel data into a point in an image, the centroid of the microbubble can be defined very precisely for stand-alone sources. As in optics, the question is never if wave-based imaging methods can precisely localize individual sources, but rather how to obtain these punctual sources in the first place!

As we have seen, methods initiated decades before, such as MUSIC, could already claim the name of super-resolution ultrasound but for a very limited number of scatterers which does not correspond to the configuration of biomedical ultrasound. The innovation can be rather seen as the introduction of ultrasound localization microscopy (ULM), a direct pendant to photoactivated localization microscopy, leading to super-resolution in configurations where millions of scatterers are present. ULM can mirror the conditions for photoactivated localization microscopy adapted from von Diezmann [START_REF] Von Diezmann | Three-Dimensional Localization of Single Molecules for Super-Resolution Imaging and Single-Particle Tracking[END_REF] and some are even more favorable in acoustics than in optics: a) Sensitivity: The sensitivity of ultrasound to its contrast agents, microbubbles, is extremely high as it was already described that single microbubbles a few microns in diameter (ʎ / 100) can be imaged with a clinical scanner [START_REF] Klibanov | Detection of Individual Microbubbles of Ultrasound Contrast Agents: Imaging of Free-Floating and Targeted Bubbles[END_REF]. This is due to their impedance mismatch, resonance in the MHz-range and nonlinearities. Contrary to optical agents, they can be detected at several cm depth in tissue, making them a clinically relevant contrast modality. These isolated microbubbles are often seen at the beginning and end of the injected boluses in the clinic. The tracks of individual bubbles could even be superposed to create Maximum Intensity Projection images, which remained however diffraction-limited [START_REF] Wilson | Contrast-enhanced ultrasound: What is the evidence and what are the obstacles?[END_REF]. Initially, it may appear restricting to use blood-pool microbubbles s as the labels for ultrasound super-resolution. However, a vast number of diseases involves the microvasculature, such as cardio and cerebrovascular diseases, cancer and diabetes. Currently, hundreds of thousand of contrast enhanced ultrasound scans are performed every year, in addition to the millions of Doppler exams.

b) Localization: Because ultrasonic waves remain coherent when propagating into tissue and that our acquisition systems are sensitive to phase, minute decorrelations much smaller than the wavelength (ʎ /100 or less) can be observed with an ultrasound scanner. This sensitivity to small changes is exploited in Doppler imaging [START_REF] Evans | Doppler ultrasound: physics, instrumentation and signal processing[END_REF], but also by displacement measurements [START_REF] Walker | A Fundamental Limit on Delay Estimation Using Partially Correlated Speckle Signals[END_REF] and transient elastography which can detect vectorial displacements in the range of microns at kHz frame rates [START_REF] Tanter | Ultrafast compound imaging for 2-D motion vector estimation: Application to transient elastography[END_REF]. Moreover, the response of ultrasound images to a single isolated point is well-behaved and well-known (point-spread function [START_REF] Cobbold | Foundations of Biomedical Ultrasound[END_REF]). Ultrasound can be refocused even through highly aberrating [START_REF] Fink | Time-Reversal Acoustics in Biomedical Engineering[END_REF][89], multiply scattering [START_REF] Tourin | Dynamic time reversal of randomly backscattered acoustic waves[END_REF] and even non-linear media [START_REF] Couture | Suppression of tissue harmonics for pulse-inversion contrast imaging using time reversal[END_REF]. From the response of a single isolated microbubble, we can thus pinpoint its centroid with a resolution much greater than the wavelength, as it was demonstrated for other strong scatterers with DORT and MUSIC [START_REF] Prada | Experimental subwavelength localization of scatterers by decomposition of the time reversal operator interpreted as a covariance matrix[END_REF].

c) Video recording: Conventional ultrasound is already the fastest clinical imaging modality with frame-rates around 50 frames per second. In "M-mode" (single line imaging), phenomena in the timescale of the pulse-echo (less than 100 microseconds) can also be detected over a single line. Ultrafast imaging pushed these frame rates by a few order of magnitude by producing entire frames within one pulse-echo (up to 20,000 frames per second for shallow tissue). Planar [START_REF] Montaldo | Coherent plane-wave compounding for very high frame rate ultrasonography and transient elastography[END_REF] or volumetric [START_REF] Provost | 3D ultrafast ultrasound imaging in vivo[END_REF] compounding have allowed a direct trade-off between image quality and frame rates. The exponential development of RAM and graphical processing units, also permits the accumulation and beamforming of millions of images within one acquisition. Far beyond just a technological leap, such ultrafast frame rates are key for ultrasound localization microscopy as tiny in vivo tissue motion or even physiological tissue pulsatility occurring at tens of micrometers and millisecond ranges can destroy our ability to produce microscopic images if uncorrected.

d) Isolated sources in a spatiotemporal referential:

The principle of localization microscopy is that sources are isolated in each individual image. For localization to work precisely, isolated sources such as microbubbles need be separated by a wavelength or more. Indeed, in a single image, the PSF of two microbubbles should not be superposed by more than 50% in order to fulfill the Rayleigh criteria and avoid the bias in the localization of their respective centroid (figure 2). One of the main questions of the current developments in super-resolution ultrasound is the method by which microbubbles are separated. The most straightforward answer consists of using a very limited concentration of microbubbles. Indeed, when injected at standard concentration [a few hundred million bubbles in a human] at the peak of the bolus, several microbubbles are present in each pixel at clinical frequencies making them impossible to distinguish. Drastically reducing the concentrations leads to a separability between individual microbubbles which can then be individually localized. In the case of large microbubble clouds (high concentration), ultrafast imaging solves the problem of individual bubble separation by detecting their transient individual signatures from the decorrelation of successive ultrasonic backscattered signals. This decorrelation can be due to movement or disruption. However, with the advent of tracking methods, the disruption of microbubbles is detrimental and low MI pulses should rather be used to observe microbubbles as they individually flow through microvessels.

With the exception of ultrasonic transposition of SOFI [START_REF] Bar-Zion | Fast Vascular Ultrasound Imaging with Enhanced Spatial Resolution and Background Rejection[END_REF], which will be discussed below, ultrasonic super-resolution techniques introduced recently for in-vivo imaging are ultrasound localization Finally, our group generalized the initial work on ultrafast ultrasound localization microscopy in 3D by using a 1.5D array to reconstruct the super-resolved position of microbubbles in the axial, lateral but also elevation directions (figure 3b [START_REF] Desailly | Sono-activated ultrasound localization microscopy[END_REF]). Ultrafast imaging was still implemented and decorrelation through differential filters was exploited to separate microbubbles present in high concentrations. The technique allowed, at a frequency of 1.75 MHz (ʎ =850 microns), the reconstruction of a branching vascular network in a microfuidics phantom with channels as small as 40 microns (/20).

Within these five initial studies, most of the elements of ultrasound localization microscopy were already in place. In general, such acquisitions follow these steps (figure 4): 1) An injection of a contrast agent at a low (~10 6 microbubbles injected) or a high concentration (~10 8 microbubbles) 2) A video acquisition of 100s to 100,000 B-mode with or without contrast-specific pulse sequences, at conventional or ultrafast frame rate 3) A motion correction algorithm 4) A filtering step highlighting distinct individual microbubbles on each image 5) The localization of the centroid of each of the microbubble echo in the RF field or on beamformed images. Thousands to tens of millions of microbubbles can be localized over a cineloop 6) The tracking of the localized points to define the paths of microbubbles in microvessels 7) The visualization of the accumulation of individually localized microbubbles, their density or their calculated velocities. Each of these steps were optimized by various groups, several trade-offs were discovered and numerous strategies were introduced to circumvent them. However, it is important to note that the resulting resolutions have varied drastically between groups, even if they all claimed to defeat the diffraction limit. In some cases, authors have shown an improvement by more than one order of magnitude, others have achieved a small gain with respect to the half-wavelength limits and for others it suffices to supplant the FWHM=1.4 ʎF/D. In the end, resulting images can only be compared on the basis of the subwavelength structures that can be detected and separated. For instance, channels much closer than the wavelength can be shown to be separated with ULM [START_REF] O'reilly | A super-resolution ultrasound method for brain vascular mapping[END_REF][95] [START_REF] Desailly | Sono-activated ultrasound localization microscopy[END_REF]. Further down the tracking process, the vectorial information obtained from ULM can be used to determine the statistical significance of the difference between the velocities in two sub pixels in order to determine the ultimate resolution [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF].

The following developments in 2015 involved the technology transfer to the in-vivo setting (more in the dedicated section below), but continuing work on the optimization of ULM remained important. It was essential, for instance, to theoretically predict the maximum resolution achievable by this technique and under what conditions. This lower bound is defined by the localization precision of each microbubble and it is linked to the minimal temporal delay which can be estimated between similar echoes, the so-called Cramer-Rao lower-bound [START_REF] Walker | A Fundamental Limit on Delay Estimation Using Partially Correlated Speckle Signals[END_REF]. The theoretical resolution limit achievable in ULM was given in Errico et al. [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF] and shown to present nice analogies with the resolution limit in optical localization microscopy. This theoretical resolution limit was demonstrated and validated experimentally by Desailly et al. [START_REF] Desailly | Resolution limits of ultrafast ultrasound localization microscopy[END_REF]. The process of localization on the hyperboloid echoes in the RF channel data or determining the centroid on beamformed data are similar as they relate to the fitting of the time-of-flight equation with respect to the localization of the source and of the transducers. However, the equivalency between the localization in the RF space and the beamformed space might be affected by nonlinear processing such as the correction of outliers and phase jumps in the fitting of the microbubble echo. A recent article by Song et al. [START_REF] Song | Sampling Quantization in Super-Resolution Ultrasound Microvessel Imaging[END_REF] have described the influence of the spatial sampling of the beamforming on the localization error.

In the far-field, Desailly et al. showed that the achievable resolution was (eq1) in the lateral, (eq2) in the axial resolution where is the standard deviation of the position of the echo-time on each channel RF line, n is the number of transducer elements, c the speed of sound z 0 the depth and L the size of the array. This shift depends on the pulse bandwidth, the pulse centre frequency, the SNR and finally the temporal jitter between electronic channels of the scanner whose classical values (2 to 6 ns) sets an intrinsic limit to some µm resolution. Interestingly, these equations relate very well to the maximum resolution in FPALM which is highly dependent on s, the standard deviation of a Gaussian approximating the true PSL and N, the total number of detected photons. In practice, the model predicted an axial resolution of approximately 2 micrometers at 7 MHz. An interesting coincidence is that this limitation correspond approximatively to the size of the microbubble, linking the geometric confinement of the microbubble to the ultrasound capacity at localizing them.

eq.1:

eq.2: eq.3:

Apart from the precision of localization, the first question in ULM is often how to distinguish the microbubbles from surrounding tissue, which was thoroughly studied in the field of contrastenhanced ultrasound [START_REF] Burns | Microbubble contrast for radiological imaging: 1. Principles[END_REF]. For instance, Viessmann et al. [START_REF] Viessmann | Acoustic super-resolution with ultrasound and microbubbles[END_REF] used harmonic imaging to highlight microbubbles in their channels. A similar harmonic technique was also used by O'Reilly [START_REF] O'reilly | A super-resolution ultrasound method for brain vascular mapping[END_REF]. Couture et al. [START_REF] Couture | Microbubble ultrasound superlocalization imaging (MUSLI)[END_REF] initially exploited slow-time filtering on large stacks of ultrafast images to highlight disruption or motion of the microbubbles. This approach was improved by using singular value decomposition (SVD) of ultrafast data introduced initially for Doppler imaging [START_REF] Demené | Spatiotemporal Clutter Filtering of Ultrafast Ultrasound Data Highly Increases Doppler and fUltrasound Sensitivity[END_REF] and applied here for ULM [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF]. Such spatiotemporal filters based on SVD of ultrafast data can surpass nonlinear sequences even in clinical settings for slowly moving microbubbles (minimum 2 mm/s microbubble velocity in [START_REF] Desailly | Contrast enhanced ultrasound by real-time spatiotemporal filtering of ultrafast images[END_REF]). Further development by Ghosh et al. [START_REF] Ghosh | Toward optimization of in vivo super-resolution ultrasound imaging using size-selected microbubble contrast agents[END_REF] and Lin et al. [START_REF] Lin | Optimizing Sensitivity of Ultrasound Contrast-Enhanced Super-Resolution Imaging by Tailoring Size Distribution of Microbubble Contrast Agent[END_REF] has shown that selecting a population of larger microbubbles improves the signal-to-noise ratio of individualized microbubbles. Finally, nonlocal means filtering was introduced by Song et al. [START_REF] Song | Improved Super-Resolution Ultrasound Microvessel Imaging with Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking[END_REF].

The second question, and possibly the most important, is the separation of microbubbles from each other. Indeed, the echoes from two microbubbles that are closer than a few wavelengths in a specific image will interfere, making the corresponding centroids of each microbubble indistinguishable or shifted. Consequently, only a limited number of microbubbles can be detected in each image to avoid such overlapping. For instance, in our brain experiments, we tend to localize around 100 microbubbles per ultrafast image. This limits contributes to the fundamental trade-off between the attained super-resolution and the acquisition time as the number of microbubble events determines the smallest vessels that can be reconstructed. Couture et al. [START_REF] Couture | Microbubble ultrasound superlocalization imaging (MUSLI)[END_REF] initially proposed slow-time filtering of ultrafast data to extract microbubbles based on their motion or disruption. This approach was further improved by using singular value decomposition [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF]. It is used to separate microbubbles from the surrounding tissue, the choice of the singular value threshold leading to an efficient extraction of microbubbles from tissue signature to the price of the exclusion of microbubbles that are too close from each other's. In London [START_REF] Viessmann | Acoustic super-resolution with ultrasound and microbubbles[END_REF], [START_REF] Christensen-Jeffries | In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles[END_REF], low concentrations of microbubbles were injected to guarantee that the echoes of multiple agents would not interfere. Such a solution, leading to longer acquisitions times or a lower number of detected microbubbles was also preferred in Toronto by O'Reilly et al. [START_REF] O'reilly | A super-resolution ultrasound method for brain vascular mapping[END_REF]. However, their acquisition system relied on passive beamforming methods with a maximum attainable frame rate of 2 kHz at their imaging depth.

Along with the separation of microbubbles from tissue (contrast-to-tissue ratio CTR) and the separation of microbubbles from each others, the signal-to-noise ratio of an individual microbubble is a key element. Indeed, the resolution of an ULM image is determined by the localization precision of independent microbubbles. On the radio-frequency channel data, the microbubble echo appears, in time, as a hyperbola. The contrast for the detection of each pulse with respect of noise and tissue determines how accurately the fitting procedures can be applied on the maxima of the envelope or on the zero-crossing on each echo. In the end, it determines the maximum resolution of ULM. Because the beamformed data is often more readily available, a centroid detection procedure is applied, relying on local maxima search, convolution or weighted-average approaches as in photoactivated localization microscopy [START_REF] Henriques | QuickPALM: 3D real-time photoactivation nanoscopy image processing in ImageJ[END_REF].

Christensen-Jeffries demonstrated in-vitro that the delayed response of the microbubbles had to be taken into account when localizing microbubbles [START_REF] Christensen-Jeffries | Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging[END_REF]. Indeed, because of their resonant nature, microbubbles do not scatter identically to the initial emitted pulse and tend to ring for a long period with respect to tissue. They proposed to use the signal onset as a reference because the exploitation of a gaussian fitting method could lead to hundreds of microns in error. This is particularly important in the resonant regime of the contrast agent.

Since the super-resolved ULM images are reconstructed point-by-point, their resolution is preconditioned by the total number of microbubbles detected. Here, the distinction between the localization precision, introduced above, and the separability of the observable features is essential. Indeed, a blood vessel cannot be reconstructed with a single microbubble detection, even with a 1 picometer localization precision. A vessel needs several microbubbles events to be reconstructed and this number increases with the number of super-resolved pixels it encompasses. Smaller pixels require more microbubble events. For instance, in Errico et al. [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF], the image was formed with close to 10 millions super-resolved pixels. Considering that vessels are present in a great number of these pixels and that microbubble events are often superfluous in the same pixel, it took more than one million microbubble events to reconstruct a single image. Moreover, one should bear in mind vascular physiology as smaller vessels need much more time to be filled with microbubbles [START_REF] Prinzen | Blood flow distributions by microsphere deposition methods[END_REF] and, irrespective of the localization method, should require a longer acquisition time to be reconstructed [START_REF] Dencks | Determination of adequate measurement times for super-resolution characterization of tumor vascularization[END_REF][1]. In the end, rather than the localization precision, the capacity of the imaging system to distinguish blood vessels much smaller than the wavelength represents a better measurement for resolution.

Because a single microbubble can reconstruct several pixels through its tracking during displacement trajectories, ultrasound microbubble tracking is a technique that can vastly improve the quality of images and modify its visualization. It was used initially in Errico et al. [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF] and in Christensen-Jeffries et al. [START_REF] Christensen-Jeffries | In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles[END_REF] to determine the velocity vector of individual microbubbles. Microbubbles flowing in blood vessels follow a smooth continuous track which can be reconstructed from a selected number of samples in the slow time. These samples are the localization of an individual microbubble in each image. The most basic algorithm of tracking is the closest-neighbor detector where a track is constructed iteratively by searching for the closest microbubble in the next image. A series of parameters are important such as the maximum distance a microbubble can propagate between two images, the intensity threshold to include or exclude the next microbubble, the criteria's to initiate and the criteria's to terminate a track. More refined tracking algorithms were introduced such as Markov chain combined with Monte Carlo approaches [START_REF] Opacic | Super-Resolution Ultrasound Bubble Tracking for Preclinical and Clinical Multiparametric Tumor Characterization[END_REF][112] or involving Hungarian assignment [105][113].

The Hungarian assignment resolution implies linear operations on the cost matrix of the problem to solve the assignment problem of dimension n with an order of n 3 time complexity instead of an order of n! time complexity with a conventional brute-force approach. As the number of particles is large in high frame rate acquisitions, this method is particularly efficient to assign the particles together. It was extensively used in transportation analysis [START_REF] Munkres | Algorithms for the Assignment and Transportation Problems[END_REF].

As in pulsed Doppler, the sampling rate necessary to reconstruct a track depends on the velocity of the microbubble. A higher velocity should require a higher frame rate. For slow flow, a higher number of samples improves the tracking, as it simply adds more point to the curve fitting. However, the required sampling rate depends additionally on the distance between different microbubbles and the tracking algorithm. In other words, when comparing two successive ultrasonic images, can the ambiguity between a single and fast moving bubble, and two distinct bubbles be solved? Distinguishing the path of two neighboring microbubbles is made easier when the respective tracks are appropriately sampled in time. In our view, this is an important argument in favor of ultrafast imaging for ultrasound localization in addition to the improved speckle denoising.

Tracking is also a filter that can distinguish microbubbles from noise. Indeed, electronic noise does not follow a traceable path. Isolated points or very short tracks can be excluded from the image to improve the contrast between vessels and the surrounding bubble-less extravascular space.

Nevertheless, the main contribution of tracking is the possibility to create velocity maps. By determining the displacement of a microbubble between two images, a velocity vector can be created with a high dynamic range. Indeed, a millisecond sampling of a motion with a spatial resolution of 10 micrometers can yield velocities in the range of 0.1 mm/s to 10 mm/s and even more if the microbubbles are sparse. Moreover, the tracking in ultrasound localization imaging have much smaller dependence on direction than Doppler, which dominantly highlights axial displacements.

One of the strengths of ultrasound imaging is its temporal resolution which makes it such that motion can be exploited by the radiologists to assess the function of an organ such as the heart. However, motion is also a source of artefacts, particularly in ULM which requires long acquisitions to observe minute vessels. These vessels can be much smaller than the average displacements during a handheld scan. Several techniques have been used to reduce motion in the context of superresolution. Christensen-Jeffries clamped a mouse ear with plates [START_REF] Christensen-Jeffries | In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles[END_REF]. Errico et al. used a stereotactic frame to stabilize the brain [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF]. Lin et al. [START_REF] Lin | 3-D ultrasound localization microscopy for identifying microvascular morphology features of tumor angiogenesis at a resolution beyond the diffraction limit of conventional ultrasound[END_REF] excluded images where excessive motion due to breathing was present.

Motion can also be partly corrected using the cineloop where microbubbles are detected. Indeed, the phase-dependence of ultrasound echoes opens the possibility to use precise subwavelength motion detection algorithms, much like interferometry in optics. For instance, in shear wave elastography, micrometric displacement can be detected in the B-mode images even though the compression waves have wavelength hundreds of times larger. For ULM, Hingot et al. [START_REF] Hingot | Subwavelength motion-correction for ultrafast ultrasound localization microscopy[END_REF] (figure 5) gave a proof of concept using a very simple speckle tracking approach based on phase-correlation between successive ultrafast images to correct for planar motion. Such a method could correct motion in the hundreds of microns in both directions in a brain without strict mechanical stabilization. However, the main contribution of this article was the demonstration that the microbubble signal had to be removed from the images before motion-correction as they can create false displacements by tens of micrometers. Similarly, Foiret et al. [START_REF] Foiret | Ultrasound localization microscopy to image and assess microvasculature in a rat kidney[END_REF] have implemented their motion correction from the B-mode images while extracting their microbubbles from Contrast Pulse Sequence (CPS). They were able to achieve correction of the kidney motion by several hundred microns in a free-breathing rat, adding a rotational component to the algorithm. Song et al. [START_REF] Song | Improved Super-Resolution Ultrasound Microvessel Imaging with Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking[END_REF] also exploited phase-correlation rigid motion correction to align the kidney images in a free-breathing rabbit. Unfortunately, out-of-plane motions remain impossible to correct appropriately as the information is absent. Further development in 3D ULM will become essential for the generalization of the technique. A very important debate in the ULM community is the frame rate necessary to create super-resolved images. Indeed, subwavelength resolutions were obtained both with ultrafast frame rates (500Hz and up [START_REF] Couture | Microbubble ultrasound superlocalization imaging (MUSLI)[END_REF], [START_REF] Desailly | Sono-activated ultrasound localization microscopy[END_REF], [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF], [START_REF] Lin | 3-D ultrasound localization microscopy for identifying microvascular morphology features of tumor angiogenesis at a resolution beyond the diffraction limit of conventional ultrasound[END_REF]- [START_REF] Foiret | Ultrasound localization microscopy to image and assess microvasculature in a rat kidney[END_REF]) and conventional frame rates (around 30Hz [START_REF] Viessmann | Acoustic super-resolution with ultrasound and microbubbles[END_REF], [START_REF] O'reilly | A super-resolution ultrasound method for brain vascular mapping[END_REF], [START_REF] Christensen-Jeffries | In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles[END_REF], [START_REF] Opacic | Super-Resolution Ultrasound Bubble Tracking for Preclinical and Clinical Multiparametric Tumor Characterization[END_REF], [START_REF] Ackermann | Detection and tracking of multiple microbubbles in ultrasound B-mode images[END_REF], [START_REF] Christensen-Jeffries | 3-D in Vitro Acoustic Super-Resolution and Super-Resolved Velocity Mapping Using Microbubbles[END_REF], [119][111]). Is ultrafast imaging at kHz frame rates really necessary for ULM? Especially since most available clinical scanners have yet to attain high frame rates, reducing the potential impact of the method in patient imaging. Opacic et al. [START_REF] Opacic | Super-Resolution Ultrasound Bubble Tracking for Preclinical and Clinical Multiparametric Tumor Characterization[END_REF] propose to exploit ULM tracking at conventional frame rates to reconstruct super-resolved vessels. Not only were they able to track microbubbles in vessels with a short acquisitions of 40s (2000 images), but they were also able to extract parameters such as median distance between vessels, flow direction entropy and other parameters that appear to change between tumor types in-vivo. These parameters could become very relevant in cancer diagnosis. Discussions following the presentation of these results included the claim that ultrafast imaging could oversample the problem in time and that slow moving microbubbles do not need to be localized more than few tens of time per second if tracking is properly implemented.

In our view, the question comes back to the definition of resolution, which is not the precision of localization of a single microbubble, but rather the separability of the microscopic features in an organ. According to the precision of localization, single tracks can be precise at the micrometer level. However, if only a very small fraction of microvessels are reconstructed at the smallest scale, then the image does not accurately depict the real vasculature. In some applications, a small sample of the microvasculature might be all it takes for diagnostically-relevant information to be obtained, but in other applications a large fraction of the vessels will need to be reconstructed. In the latter case, millions of microbubble events are necessary and ultrafast imaging is likely to be required if experimentalists wish to be home for dinner.

In the end, many of these acoustical parameters depend strongly on the ultrasonic system, clinical or research, and on the ultrasonic probe. In most embodiments, linear arrays at various frequencies were exploited to perform ultrasound localization. However, O'Reilly and Hynynen [START_REF] O'reilly | A super-resolution ultrasound method for brain vascular mapping[END_REF] conceived their super-resolution experiment with a hemispherical 3D ultrasonic array to reconstruct the microbubble position in 3D. Desailly et al. [START_REF] Desailly | Sono-activated ultrasound localization microscopy[END_REF] used parallel probes to achieve super-resolution in lateral, axial and the elevation direction. Christensen-Jeffries et al. [START_REF] Christensen-Jeffries | Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging[END_REF] rather proposed for the probes to be placed perpendicularly to attain an isotropic resolution in the three dimensions. Nevertheless, this method restricted the field of view to the confocal line between the two planes.

Through these technological developments, a series of new trade-offs were discovered in ultrasound localization microscopy which went beyond the classical resolution vs penetration conundrum. Spatial resolution has been increased by two orders of magnitude, but it now depends on the timeresolution, number of microbubbles, signal-to-noise-ratio, tracking algorithm, probe geometry, vessel size and many more parameters. These various parameters, shown in table 1, should therefore be described in future publications for each trade-off to be appropriately compared. Moreover, endpoint results such as localization precision and separability should be stated. These parameters will drastically affect the use of ultrasound localization microscopy in its preclinical and clinical applications.

Important parameters

Signal-to-noise ratio

Ultrasonic SOFI

Super-resolution optical fluctuation imaging, or SOFI, is not a localization technique per se, as it rather exploits the stochastic fluctuations in pixels to reduce the size of the pointspread function. However, as in ULM, its adaptation for ultrasound by the Technion group [START_REF] Bar-Zion | Super-Resolution Ultrasound Imaging of Vascular Structures with High Temporal Resolution[END_REF][94], exploits ultrafast imaging and microbubbles to improve resolution and it should be described in this review. In optics, SOFI uses smaller image stacks than other super-resolution techniques such as FPALM and STED since it does not require the localization of individual emitters [START_REF] Dertinger | Fast, background-free, 3D superresolution optical fluctuation imaging (SOFI)[END_REF]. Instead, it exploits the fact that the point-spread function of the images can be reduced by the properties of the cumulants in the slow-time direction. Indeed, the PSF is reduced by the square root of the order of the cumulant used. Although emitters are not localized, the technique still requires that some sources cycle between two distinguishable states. However, this process rapidly introduces noise artefacts and is usually restricted to lower order cumulants, leading to an improvement of resolution limited to a typical factor of 2. It is drastically lower than the improvement by FPALM, but it is faster by orders of magnitude and generally reduces the total fluence which damages cells in optical microscopy.

The approach taken by Bar Zion et al. [START_REF] Bar-Zion | Fast Vascular Ultrasound Imaging with Enhanced Spatial Resolution and Background Rejection[END_REF] is very similar to SOFI. In one study, they performed ultrafast imaging on VX-2 tumor xenograph in white rabbit model while injecting microbubbles. The various cumulants of the image stacks were exploited to recreate images showing some improvements in the vessel details. With a factor of 2 gain with respect to the resolution-limit of the system for a 1000 frames acquisition, the results appear close to the images obtained without contrast agents using ultrafast Doppler and an inverse filter [START_REF] Demené | 4D microvascular imaging based on ultrafast Doppler tomography[END_REF] . A more freshly-fished approach based on SOFI in the case of sparse acquisitions, called SUSHI, was also proposed recently [START_REF] Van Sloun | Sparsity-driven super-resolution in clinical contrast-enhanced ultrasound[END_REF]. It was recently applied for the microvasculature imaging of the human prostate.

As SOFI is based on second order statistics fluctuations rather than localization, it does not allow microscopic resolutions and should be compared in our opinion with concurrent approaches used in clinics, such as ultrafast power Doppler imaging [START_REF] Demené | Spatiotemporal Clutter Filtering of Ultrafast Ultrasound Data Highly Increases Doppler and fUltrasound Sensitivity[END_REF] or Superb Microvascular Imaging [START_REF] Zhan | Superb Microvascular Imaging -A new vascular detecting ultrasonographic technique for avascular breast masses: A preliminary study[END_REF] rather than with localization microscopy. The deconvolution of single events corresponding to individual microbubbles were described in conventional [START_REF] Siepmann | Imaging tumor vascularity by tracing single microbubbles[END_REF] and ultrafast [START_REF] Couture | Microbubble ultrasound superlocalization imaging (MUSLI)[END_REF] imaging of murine tumor models. However, we would have to wait until 2015 for a proper subwavelength reconstruction of in-vivo vasculature to be performed by two independent teams. The work of Christensen-Jeffries pursued the initial quest of their group to exploit a conventional scanner and low concentration of microbubbles to reveal the microvasculature of the ear [figure 6a [START_REF] Christensen-Jeffries | In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles[END_REF]]. They showed that they could visualize vessels down to 20 micrometers and confirmed their measurements with optical imaging of the same vessels. Although the total acquisition time was difficult to assess from the article, with a frame rate of 25 Hz, the maximum injected volume of 200 µL at their maximum infusion rate could be reached between 40 to 1000 minutes, an acquisition time difficult to sustain from practical clinical applications.

In-vivo applications of ultrasound localization microscopy

In parallel, Errico et al. [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF]also pursued their initial idea to exploit ultrafast differential imaging for ultrasound localization microscopy to explore the rat brain with a resolution of 8 um (figure 6b). The acquisition was done in 3 minutes with a single bolus for each plane and several millions microbubble events were highlighted. This resolution of 8 µm was measured through statistical separability of the smallest pixels achievable with velocity tracking. Indeed, both groups [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF], [START_REF] Christensen-Jeffries | In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles[END_REF] introduced tracking of individual microbubbles to improve super-resolution imaging. This has become an essential component of super-resolution as it provides velocity measurements of individual microbubbles through time. The localization being done in the micrometer spatial resolution and millisecond time scale in the case of ultrafast ULM, the precision on the velocity vector is very high and Errico et al. achieved a flow velocity dynamic range from less than 1mm/s to several cm/s. Further studies on the brain [START_REF] Hingot | Incompressible perfusion time of microbubbles drives the fundamental compromise between spatial resolution and acquisition time in ultrasound localization microscopy[END_REF] have confirmed that the maximum resolution is dependent on the number of microbubbles that are observed. The smallest vessels, such as capillaries, being only sparsely populated with microbubbles, the acquisition time increases when the super-resolved pixels and the vessels get smaller. Even though detecting a vessel of 100 µm can be performed in the hundreds of milliseconds, vessels of 5 micrometers in diameter takes several minutes to be described in their majority. In fact, in many applications where time resolution is more important than spatial resolution, ultrafast Doppler imaging [START_REF] Bercoff | Ultrafast compound doppler imaging: Providing full blood flow characterization[END_REF] may remain a better approach for microvascular imaging [figure 7a] as it does not require microbubbles. Microbubbles will remain important when perfusion down to the capillary level is needed. In any case, ultrafast Doppler should always be performed on the same dataset in comparison. For practical clinical use, ULM should move beyond a simple description of the morphology of the microvasculature and allow the extraction of relevant biomarkers. Recent advances in the field are opening such applications. For instance, Lin et al. [START_REF] Lin | 3-D ultrasound localization microscopy for identifying microvascular morphology features of tumor angiogenesis at a resolution beyond the diffraction limit of conventional ultrasound[END_REF](figure 6c) described the microvessels in subcutaneous tumor in rats by performing ultrafast ULM over several planes. The vessels were between 25 microns and 175 microns (wavelength = 330 microns). Moreover, the authors also described the tortuosity of the vessels at the microscopic scale and they showed an elevation in the tumor with respect to normal tissue. This is the first step in the direct description of the effect of angiogenesis on the conformation of microvessels for which ultrasound only provided indirect measurements until today, through reperfusion enhancement [START_REF] Wei | Quantification of myocardial blood flow with ultrasound-induced destruction of microbubbles administered as a constant venous infusion[END_REF].

Opacic et al. [START_REF] Opacic | Super-Resolution Ultrasound Bubble Tracking for Preclinical and Clinical Multiparametric Tumor Characterization[END_REF], exploiting ULM tracking at conventional frame rates, also established new parameters for tumor characterization through microvessel imaging. They compared three different tumor types in mice, which were expected to display a diversity of vascular density (A431, MLS and A546).They showed that they could extract biomarkers such as flow direction entropy and distances to the closest vessel, which differed in a statistically significant fashion between the different tumor types.

Ghosh et al. [START_REF] Ghosh | Monitoring early tumor response to vascular targeted therapy using super-resolution ultrasound imaging[END_REF] described the use of ULM with a clinical ultrasound scanner to monitor the effect of an angiogenesis inhibiting drug. They showed that the detected microvasculature was reduced by up to 60 % within two hours after the injection of Avastin versus 26% in the control tumor (likely due to experimental conditions). The same group [START_REF] Ghosh | Super-resolution ultrasound imaging of the microvasculature in skeletal muscle: A new tool in diabetes research[END_REF] also described the use of ULM techniques to map the microvasculature in skeletal muscle of diabetic mice. Using various parameters, such as peak microbubble count, they showed the impaired microvascular response of obese animals to insulin, showing the potential of ULM to assess peripheral vascular damages in type-2 diabetes.

Foiret et al. [START_REF] Foiret | Ultrasound localization microscopy to image and assess microvasculature in a rat kidney[END_REF] depicted the microvasculature of the rat kidney with ultrafast CPS mode. Nonlinear sequences and plane-wave imaging for microbubbles detection are far from being contradictory. It was even demonstrated that, at appropriate depth, it has a higher CTR and lower disruption than nonlinear sequences at conventional frame rates [START_REF] Couture | Ultrafast Imaging of Ultrasound Contrast Agents[END_REF], [START_REF] Couture | Ultrasound Contrast Plane Wave Imaging[END_REF]. Beyond describing the microvascular anatomy of the kidney, Foiret et al. also suggested that microbubbles which were constrained in small vessels would have a longer persistence.

Finally, Luke et al. [START_REF] Luke | Super-Resolution Ultrasound Imaging in Vivo with Transient Laser-Activated Nanodroplets[END_REF] have proposed to generalize ULM to vaporized nanodroplets. They showed the laser vaporization and the localization of the resulting microbubbles in the mouse brain. Acoustic droplet vaporization could probably also be used [START_REF] Sheeran | Formulation and acoustic studies of a new phase-shift agent for diagnostic and therapeutic ultrasound[END_REF], [START_REF] Hingot | Subwavelength far-field ultrasound targeted drug-delivery[END_REF]. In general, these nanodroplets tend to last longer and also penetrates tumours through the enhanced permeation and retention effect. Consequently, biological mechanisms other than intravascular flow could be explored through ultrasound localization microscopy.

These various applications of ULM, in the brain [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF], in superficial vessels [START_REF] Christensen-Jeffries | In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles[END_REF], in tumors [START_REF] Lin | 3-D ultrasound localization microscopy for identifying microvascular morphology features of tumor angiogenesis at a resolution beyond the diffraction limit of conventional ultrasound[END_REF], [START_REF] Ghosh | Monitoring early tumor response to vascular targeted therapy using super-resolution ultrasound imaging[END_REF], in the kidney [START_REF] Foiret | Ultrasound localization microscopy to image and assess microvasculature in a rat kidney[END_REF], are still at their infancy but show a pivotal evolution of the field. Indeed, initially, microvessels were used to demonstrate ULM as an imaging technique and displayed the anatomy of the microvasculature. More recent studies are showing that ULM can be used to extract useful information from these images such as the tortuosity of vessels, their mutual distances or the stability of microbubbles in small vessels. Considering the evolution within the last seven years since its introduction, it probably has many tricks still to show.

Perspectives

With many independent groups working on the subject and energetic exchanges in international ultrasonic symposia, ULM is gaining momentum in research. In our view, there are still many developments and major discoveries to come.

The technological development is still a dynamic aspect of the field. Fundamental limits can be expanded by improving the separation of microbubbles from tissue and from each other's. Indeed, the localization precision determines the ultimate attainable resolution. Improving SNR and CTR can both contribute in bettering the precision below a few microns as most authors currently describe the limit to be. However, as microbubbles are purely intravascular, a resolution in the nanometer range might not be particularly relevant for most applications. Nevertheless, it can be used for new approaches such as physically distinguishing bound microbubbles from flowing microbubbles. In fact, one should envision ULM as deep microscopy and many applications currently limited to confocal or two-photon microscopy are now opened to ultrasound. It would vastly improve molecular imaging and allow the description of many new biological parameters at the micron scale.

One of the proximal goals for the field of ultrasound localization would be the validation of its accuracy. To date, in-vitro demonstrations were concerned with precision, or the reproducibility of the localization within a confined vessel. In-vivo, the quality of the super-resolved images is often evaluated through the self-coherence of the vessel branching pattern. In limited cases, a direct optical confirmation was possible [START_REF] Christensen-Jeffries | In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles[END_REF] or the resolution was directly obtained from statistical variance of the measured blood velocity between subpixels [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF]. But to establish the accuracy of ULM, it is necessary to compare it to established microscopy techniques such as confocal or two-photons microscopy.

The physics of microbubble oscillation has been a major subject of study in the last 20 years [START_REF] Jong | Acoustic Properties of Ultrasound Contrast Agents[END_REF]. Currently, the localization of microbubble centroids remains very simplistic in this regard. Only Christensen-Jeffries et al. [START_REF] Christensen-Jeffries | Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging[END_REF] have taken into account the resonance phenomena linked to microbubbles. Resonance, nonlinearities, disruption and dedicated sequences should be used to improve the localization process. Using microbubble physics, ULM could even be used to probe the surrounding medium as it was suggested briefly by Foiret et al. [START_REF] Foiret | Ultrasound localization microscopy to image and assess microvasculature in a rat kidney[END_REF]. Indeed, the localization of individual microbubbles could be used as an equivalent of an atomic force microscope in-vivo. For instance, the micrometric motion induced by radiation force or other forces could be measured to assess the vessel elasticity or other mechanisms [START_REF] Koruk | Acoustic particle palpation for measuring tissue elasticity[END_REF].

Beyond punctual localization, microbubble tracking should be the target of additional developments. Tracking improves drastically the images, under the condition that single microbubbles can be identified appropriately on each passing frame. Currently, this depends on the frame rate, the microbubble concentration and the tracking algorithm. The latter can benefit from the all the developments in optical tracking and artificial intelligence. If a person can be followed in a crowd through video cameras, so should microbubbles in an organ! However, we have to keep in mind that the concentration of microbubbles cannot be increased indefinitely as very close microbubbles affect not only the tracking specificity, but also the localization process itself.

The requirement for tracking also imposes a general reduction in acoustic pressure to allow for microbubbles to remain intact over hundreds of images. In general, because of the exploitation of nonlinear sequences, microbubble are used in a pressure range between the linear regime and the disruption regime. The disruption regime is stochastic, some microbubbles can disrupt after hundreds of pulses at a pressure deemed below the disruption threshold. For instance, we previously observed loss of 25% of the microbubble signal after 100 plane-wave images at 40 kPa peak-negative pressure at 7.5 MHz [START_REF] Couture | Ultrasound Contrast Plane Wave Imaging[END_REF]. It is thus necessary to reduce imaging pressure to obtain long tracks, which excludes the use of several nonlinear sequences. Further improvements in linear detection of microbubbles might be important [START_REF] Desailly | Contrast enhanced ultrasound by real-time spatiotemporal filtering of ultrafast images[END_REF].

ULM with other agents than microbubbles could open avenues other than microvascular imaging. Indeed, the localization of the vaporization of droplets [START_REF] Hingot | Subwavelength far-field ultrasound targeted drug-delivery[END_REF] would allow for the observation of extravascular contrast agents, accumulated, for example, by the Enhanced-Permeability and Retention effect. ULM could map the interstitial environment and even determine the intratumoral conditions through the slow displacement of resulting microbubbles. The exhilarating development of ultrasonic reporter genes [START_REF] Bourdeau | Acoustic reporter genes for noninvasive imaging of microorganisms in mammalian hosts[END_REF] could also be applied in ULM. Rather than tracking microbubbles, it would be possible to track cells that express the genes for the production of nanovesicles.

But, one of the main development in ULM will probably be its generalization to 3D imaging using 2D arrays. Indeed, we are facing many limitations linked to planar imaging. First, there is a clear asymmetry between the few micron resolution we can obtain in the axial-lateral plane versus the elevation resolution limited by diffraction from a physical lense on the probe. Consequently, vessels in the elevation are projected in the plane and can be blurred. Moreover, the plane thickness is difficult to determine precisely, as an off-plane but highly scattering microbubble could appear as an in-plane poorly scattering object. Tracking is also not possible in the third dimension. Moreover, ULM is very sensitive to motion and its correction cannot be obtained in a direction without spatial sampling. Finally, plane-by-plane super-resolution is impractical due to the acquisition time of each plane which corresponds to the duration of the injected bolus (few minutes). Currently, multiple boluses or constant infusion is thus necessary to have a pseudo-3D super-resolved ultrasound image. Early work on 3D super-resolution imaging [97][96] have attempted to solve these various issues, but we are still waiting for the entire characterization of an organ with volumetric ultrasound super-resolution. 3D imaging will allow for an isotropic super-resolution, with isotropic motion correction and a complete characterization of vectorial flow. Moreover, we should be able to obtain a full volume in a time similar to that of a single plane in the current situation. Indeed, a 2D array should be capable of distinguishing many more microbubbles per acquired volume than a 1D array can detect in a single image. Obviously, 3D ULM will create massive amount of data, but Moore's law should take care of this limitation in due time. Moreover, localization is the ultimate data compression tool as a Gigabitsized stack of frames can be compacted into a kilobit-sized list of microbubble positions and timing.

Beyond technological advances, many new applications of ULM are likely to appear in the near future. Both in animals, for model characterization, and in human for diagnosis and monitoring. One of the conclusion of the work of Lin et al. [START_REF] Lin | 3-D ultrasound localization microscopy for identifying microvascular morphology features of tumor angiogenesis at a resolution beyond the diffraction limit of conventional ultrasound[END_REF] and Opacic et al. [START_REF] Opacic | Super-Resolution Ultrasound Bubble Tracking for Preclinical and Clinical Multiparametric Tumor Characterization[END_REF] is that ULM provides direct access to quantifiable microvascular parameters, which were only accessible indirectly in the past through reperfusion imaging. In fact, ULM might even replace disruption-reperfusion imaging as it provides more detailed information on the microvasculature. The vascular organization of tumors might give a clear contrast with surrounding healthy tissue, especially in highly organized organs such as the kidney, the liver and the brain. With appropriate motion correction and 3D imaging, the heart could even become accessible to ULM, providing a new characterization for coronary arteries.

In general, ULM is less a microvascular imaging method, than a technique to challenge the compromise between resolution and penetration. In many situations, the observation of capillaries or microarterioles should not be necessary. It suffices to breach a resolution limit imposed by the depth of an organ or the presence of a bone interface to yield interesting new information. For instance, deep-seated tumor in the liver could be explored at a resolution below 100 microns with a conventional bolus of microbubbles (several hundred millions). However, it might be necessary to combine motion-tracking and breath-holding. In transcranial imaging, the resolution could no longer be limited to about 1mm, which is defined by the low frequencies (<2 MHz) that can penetrate the skull.

In the brain, ULM could also be combined with blood brain barrier opening [START_REF] Mcdannold | Blood-Brain Barrier Disruption Induced by Focused Ultrasound and Circulating Preformed Microbubbles Appears to Be Characterized by the Mechanical Index[END_REF] to yield a better localization of the vascular effect of the microbubble oscillation. Indeed, the effective microbubbles could be imaged while they induce a mechanical stress on the vascular wall. The same approach would also help the characterization and the mapping of the sonoporation effect [START_REF] Bouakaz | Sonoporation: Concept and mechanisms[END_REF]. In fact, ULM could become a key aspect of theranostics for monitoring. Recent advances have demonstrated that ultrasonic therapy itself could be performed with a subwavelength resolution [START_REF] Hingot | Subwavelength far-field ultrasound targeted drug-delivery[END_REF].

Finally, the future of ULM is linked to its various in-vivo applications and manufacturers of clinical scanners should be associated for further developments. Ultrasound localization microscopy opens a new window on microvasculature which could not be observed before because it was either too small or too deep. Considering that most of the main killers involve the smallest blood vessels (cardiovascular diseases, stroke, cancer, diabetes), there should be no lack of applications.

Conclusion

Ultrasound localization microscopy is the younger cousin of optical localization microscopy. While the latter has been crowned with success in laboratories, the former remains in its infancy but shows an enormous potential for clinical applications. ULM already demonstrated some technical prowess, such as the visualization of the microvasculature, in depth, at a resolution which is a tenth of the wavelength of the ultrasound in the brain, in tumors and in the kidney. The various ongoing developments will extend its applicability to the microvasculature in all organs in animals, but especially in humans. ULM should become a diagnosis modality which will provide information on the biological processes at a micrometric scale deep within tissue. founded Cardiawave, a spin-off company developing non-invasive therapeutic approaches for cardiology. In 2016, he co-founded Iconeus, a spin-off company which develops and commercializes the first prototypes for functional ultrasound neuroimaging. Amongst other responsabilities, Prof. Tanter is an Associate Editor of the IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL, and a member of the Technical Program Committee of the IEEE International Ultrasonics Symposium and the Administrative Committee of the IEEE UFFC Society. He has received multiple international scientific distinctions, including the Grand Prize of the French Foundation for Medical Research in 2016, the Roberts Prize of Physics in Medicine and Biology for the best paper of the year 2015, the Honored Lecture of the Radiology Society of North America in 2012. He has also been awarded with the prestigious European Research Council (ERC) Advanced Grant in 2013 to develop functional ultrasound imaging and its applications.

Figure 2 :

 2 Figure 2: (Left) Compromise between resolution, defined by the wavelength, and ultrasound penetration. The half-energy distance correspond to a loss of 3dB in liver tissue (attenuation ≈ 0.5 dB/cm/MHz, extrapolated linearly from [38]). (Right) Separability of two sources (dotted lines), 0.1 mm apart, using acoustic pulses emitted at various wavelengths (60% bandwidth). The sources are indistinguishable when they are closer than a half-wavelength.

Figure 3 :

 3 Figure 3: First examples of in-vitro ultrasound localization microscopy a) Ultrafast localization of microbubbles in a liquid and in a tube [© 2011 IEEE. Reprinted, with permission, from [83]] b) 3D ULM in microfluidics channels [Reproduced from [97]with the permission of AIP Publishing] c) 3D low-concentration microbubble localization in a tube [Reproduced from [96] by permissions of Wiley company, all rights reserved] d) Planar low-concentration nonlinear localization of microbubbles in two tubes [Reproduced from [95], © Institute of Physics and Engineering in Medicine. Reproduced by permission of IOP Publishing. All rights reserved]

Figure 4 :

 4 Figure 4: General steps for ultrasound localization microscopy. 1) 100's to 100,000's of images or radio-frequency channel matrices are acquired and stacked 2) Slow-time filtering or low concentration allow the separation of particles/microbubbles 3) The centroids of the hyperbolas or the focal spots created by the microbubble are localized. 4) The localization of microbubbles are assigned to tracks to determine the velocity vector 5) The resulting tracks through the movie are accumulated in one image. In parallel, motion is tracked in the cineloop and used to correct microbubble localization.

Figure 5 :

 5 Figure 5: ULM of the rat brain without (left) and with motion correction (right) based on phasecorrelation of the ultrafast images [Reproduced from [116]by permission of Elsevier, all rights reserved]

Figure 6 :

 6 Figure 6: Initial in-vivo studies in ultrasound localization microscopy A) Mouse ear [© 2015 IEEE. Reprinted, with permission, from [106]]] B) Rat brain [99]C) Implanted tumor [115]]

Figure 7 :

 7 Figure 7: Ultrafast Doppler (A) and ultrafast ultrasound localization microscopy (B) of the rat renal cortex. Ultrasound localization microscopy of the rat kidney from [117](C, cropped from original under Creative Commons Attribution 4.0 International License) and of the rabbit kidney from [105](D [© 2017 IEEE. Reprinted, with permission, from Song et al. 2018])

  VINCENT HINGOT Vincent Hingot graduated from ESPCI in 2016, a French engineering school located in Paris, majoring in technologies for health. He started his PhD in Institute Langevin shortly after to work on medical ultrasound with Mickael Tanter and Olivier Couture. Following the work of Claudia Errico and Marine Bézagu, he worked on exploiting different interactions between ultrasound and contrast agents for imaging and therapy. He focused mainly on ultrafast Ultrasound Localization Microscopy (uULM) and its application to the study of different vascular pathologies, together with the development of new techniques for ultrasound mediated drug delivery and its application to the delivery of anti-cancerous agents. BAPTISTE HEILES Baptiste Heiles was born in France in 1990. He received a Master of Science in General and Civil Engineering from Ecole Normale Superieure Paris Saclay in 2013, the agrégation de Sciences Industrielles in 2014, and a Master of Research in Fluid Mechanics and Heat Transfers from Ecole Centrale de Paris in 2015. Following the work of Yann Desailly and Claudia Errico, he works on exploiting contrast agents for imaging. He focuses on implementing Ultrasound Localization Microscopy (uULM) in volumetric imaging as well as improving ULM in conventional 2D imaging. PAULINE MULEKI-SEYA Pauline Muleki-Seya received her M.S. degree in Acoustics from the University of Le Mans in 2011, and her Ph.D. degree in Acoustics from the University of Lyon in 2014. In 2015-2016 and in 2016-2017, she was a Postdoctoral Fellow at the Laboratory of Mechanics and Acoustics in Marseille and in the Bioacoustics Research Laboratory from the Department of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign, respectively, conducting research on quantitative ultrasound techniques on soft tissues. Since 2017, she is a Postdoctoral Fellow at Institut Langevin in Paris. Her research interests include quantitative ultrasound techniques, ultrasound tissue and microvasculature characterization and sonoporation. MICKAEL TANTER Inserm/P. Delapierre Mickael Tanter received an engineering degree in 1994 from Supelec and the Ph.D. degree in physics in 1999 from the Paris 7 University. Prof. Tanter is a research professor at Inserm (Institut National de la Santé Et de la Recherche Médicale) and the director of the team Inserm U979 "Physics for Medicine" (Inserm/CNRS/ESPCI Paris, Paris, France). Since 2016, he is also the director of the first Inserm ART (Technological Research Accelerator), dedicated to biomedical ultrasound, and created by Inserm to foster the translation of the laboratory's innovation into prototypes for biomedical research. Prof. Tanter co-invented several major innovations in biomedical ultrasound, including transient elastography, ultrafast ultrasound, functional ultrasound imaging of brain activity, ultrasound localization microscopy. He is the recipient of 40 international patents and the author of more than 220 peer-reviewed papers and book chapters. In 2006, he cofounded Supersonic Imagine, Aix-en-Provence, France, with M. Fink, J. Souquet, and C. Cohen-Bacrie, which is an innovative French company positioned in the field of medical ultrasound imaging and therapy. In 2014, he co-

Table 1 :

 1 Parameters affecting the resolution of ultrasound localization microscopy. In our opinion, these parameters and endpoints should be clearly displayed in further publications both in-vitro and in-vivo to guarantee proper comparisons.

	Contrast-to-tissue ratio
	Contrast mechanism (linear / nonlinear)
	Frame rate
	Number of frame
	Temporal jitter between electronic channels
	Concentration of microbubbles
	Infusion / bolus
	Bubble-to-bubble separation approach
	Frequency
	Acquisition time
	Number of microbubbles
	Tracking algorithm
	Track length
	Data load
	Perfusion characteristics of the organ (vessel density, blood flow)
	Endpoints:
	Localization precision of individual microbubbles
	Detectability of subwavelength structures
	Separability of subwavelength features
	Statistics concerning velocity profiles

Acknowledgments

This work was supported principally by Agence Nationale de la Recherche, within the project ANR Tremplin. This work was supported by LABEX WIFI (Laboratory of Excellence ANR-10-LABX-24) within the French Program "Investments for the Future" under reference ANR-10-IDEX-0001-02 PSL*. Thanks to Jean Provost for fruitful discussions.

microscopy methods. In our view, to prevent confusion with MUSIC, near-field methods, structured illumination, or higher order statistics fluctuations based methods, the technique should be described generally as Ultrasound localization microscopy (ULM) rather than Super-resolution Ultrasound. Indeed, localization is the key concept required to reach at least one or two orders of magnitude improvement of the ultrasonic resolution compared to the wavelength and leading to microscopic resolution. Resulting images can be referred as super-resolved but the method is based on localization.

Technical developments in ultrasound localization microscopy

Initially, ultrasound localization microscopy has been described in-vitro in microvessel phantoms [START_REF] Couture | Microbubble ultrasound superlocalization imaging (MUSLI)[END_REF], [START_REF] Viessmann | Acoustic super-resolution with ultrasound and microbubbles[END_REF][96] [START_REF] Desailly | Sono-activated ultrasound localization microscopy[END_REF]. In the initial demonstration of ultrafast ultrasound localization microscopy, Couture et al. [START_REF] Couture | Microbubble ultrasound superlocalization imaging (MUSLI)[END_REF] described the error in the localization of large floating isolated microbubbles with ultrafast imaging, and showed a ʎ /250 resolution in the axial direction. Secondly, it showed the precise localization of microbubbles contrast agents in PDMS microchannels, which demonstrated a clear reduction in the apparent size of tube (figure 3a). Finally, Couture et al. observed individual microbubble events linked to the decorrelation of contrast agents during contrast imaging of implanted tumors with an ultrafast scanner. This study used the fitting of the individual microbubble echo on channel RF-data to localize the microbubbles. Fitting of hyperboloid echoes on the RF data allows the exclusion of outliers and phase-jump which cannot be retrieved from beamformed images.

In parallel to this first demonstration of ultrasound localization microscopy, Siepmann et al. [START_REF] Siepmann | Imaging tumor vascularity by tracing single microbubbles[END_REF] described a centroid detection of dilute microbubbles for the improvement of maximum intensity projection images. They demonstrated this strategy in tumor mouse models mapped with a highfrequency ultrasonic scanner. More than a super-resolution technique, they describe their strategy to determine precisely the local microbubble density, which could give additional information on tumor perfusion. They exploited motion correction and foresaw improvement through tracking in their discussion.

Following these initial studies, the year 2013 saw the publication of three founding articles on ultrasound localization microscopy by independent groups. Viessman et al. [START_REF] Viessmann | Acoustic super-resolution with ultrasound and microbubbles[END_REF] performed localization microscopy of microtubes in 2D using a conventional scanner showing that two touching 200 micrometers vessels could be distinguished with the method (figure 3d). They discriminated microbubbles from each others through the dilution of the microbubbles. The authors exploited nonlinear imaging to extract microbubbles from tissue, using a clinically-applied mode (CHI: contrast harmonic imaging). The wavelength of the received echo was approximately 300 microns, but the authors obtained a localization precision down to 2 microns using a brass wire.

A 3D super-resolution approach was presented by O'Reilly et al. using a hemispherical array used in therapeutic ultrasound (figure 3c) [START_REF] O'reilly | A super-resolution ultrasound method for brain vascular mapping[END_REF]. This application appears particularly promising in the context of the development of blood brain barrier opening techniques exploiting microbubbles. They also showed that the localization of individual microbubbles can map microtubes behind the skull. The separation of microbubbles was also performed through the dilution of the contrast agent.