Charbel Tannoury

Victor Merupo

Giuseppe Di Gioia

Vanessa Avramovic

David Troadec

Jean-François Lampin

Guillaume Ducournau

Steffen Breuer

Björn Globisch

Stefano Barbieri

Giuseppe Di Gioia

J-F Lampin

Robert B Kohlhaas

Emilien Peytavit
email: emilien.peytavit@iemn.fr

Photonic THz

teaching and research institutions in France or abroad, or from public or private research centers.

Introduction

Frequency mixers are an essential component of RF and THz systems. For example, heterodyne receivers using Schottky diode mixers pumped by local oscillators based on multiplier chain, have opened the way to THz sensors with fW-power-level sensitivity working at room temperature [START_REF] Schlecht | Schottky Diode Based 1.2 THz Receivers Operating at Room-Temperature and below for Planetary Atmospheric Sounding[END_REF][START_REF] Siegel | Terahertz Technology[END_REF] . Besides these promising developments based on all-electronic devices and driven largely by applications in astronomy, earth and planetary science [START_REF] Siegel | THz Instruments for Space[END_REF] , numerous studies on THz sources and detectors using photonic techniques have been performed during last years in the wake of the continuous improvement of near-infrared lasers sources at wavelengths between 780 and 1550 nm. Today, laser-driven sources and detectors are a key This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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10.1063/5.0153046 components of commercial THz spectrometers [START_REF] Liebermeister | Ultra-Fast, High-Bandwidth Coherent Cw THz Spectrometer for Non-Destructive Testing[END_REF][START_REF] Roggenbuck | Coherent Broadband Continuous-Wave Terahertz Spectroscopy on Solid-State Samples[END_REF] and have enabled the race to high data rates in THz wireless communications by bridging the gap between optical fibers and wireless communications technologies [START_REF] Nagatsuma | Advances in Terahertz Communications Accelerated by Photonics[END_REF] .

Photonic-based detection of continuous THz waves is also based on frequency mixing since, as illustrated in Figure 1a, the THz input wave is down-converted to an intermediate frequency f IF in a photoconductor illuminated by an optical signal modulated at a frequency f L0 such that f IF = |f L0f THz |. More precisely, in the case of commercial THz spectrometers, the scheme is called homodyne detection [START_REF] Verghese | Generation and Detection of Coherent Terahertz Waves Using Two Photomixers[END_REF] , since the same optical beat note of two slightly detuned laser lines is used for generating and detecting THz radiation, implying f THz = f LO . Optoelectronic mixers using a laser-based local oscillator (LLO) have indeed numerous advantages as compared to existing all-electronics technologies. First, the LLO frequency is widely tunable up to a few THz due to the huge bandwidth in the optical-domain. This paves the way for the development of THz-frequency-band spectrum analyzers with applications in high-resolution THz spectroscopy or electrical characterization of analog devices for 5G/6G communications systems. In addition, the LLO-signal is compatible with standard optical fibers, which are lightweight and immune to electromagnetic interference. This is particularly advantageous for antenna arrays, which require the distribution of the LLO signal to each individual antenna.

The same considerations are valid for integrated THz antenna arrays, which could be realized by on-chip photonic circuits. To take advantage of the low-cost, reliable and efficient telecomfiber components, 1550 nm need to be used as the operating wavelength. At the same time, several challenges remain to be addressed to exploit the full potential of photonic-assisted instruments for RF/THz applications. The first one is the development of LLOs whose frequency stability and noise approach that of electronic sources while remaining largely tunable [START_REF] Loas | Dual-Frequency 780-Nm Ti:Sa Laser for High Spectral Purity Tunable CW THz Generation[END_REF][START_REF] Rolland | Narrow Linewidth Tunable THz Signal Radiated by Photomixing: Coupling a Unitravelling Carrier Photodiode and a Two-Axis Dual-Frequency Laser[END_REF][START_REF] Latkowski | Analysis of a Narrowband Terahertz Signal Generated by a Unitravelling Carrier Photodiode Coupled with a Dual-Mode Semiconductor Fabry-Ṕrot Laser[END_REF][START_REF] Hallal | Frequency Stabilization of a Laser Tunable over 1 THz in an All Fibered System[END_REF][START_REF] Ito | Broadband-Frequency-Tunable Sub-Terahertz Wave Generation Using an Optical Comb, AWGs, Optical Switches[END_REF][START_REF] Tetsumoto | GHz Wave Generation Based on a Kerr Microresonator Frequency Comb Stabilized to a Low Noise Microwave Reference[END_REF] . The second challenge lies in increasing the performance of optoelectronic mixers working at 1550 nm in terms of conversion loss and noise temperature, to become competitive with electronic solutions. Hitherto, photoconductors used as heterodyne or homodyne detectors in THz systems are based on planar, interdigitated electrode capacitors patterned on low-carrier lifetime materials. Photoconductors suitable for optical excitation at telecom wavelengths are typically made of low temperature grown-InGaAs/InAlAs MQWs [START_REF] Göbel | Telecom Technology Based Continuous Wave Terahertz Photomixing System with 105 Decibel Signal-to-Noise Ratio and 35 Terahertz Bandwidth[END_REF] or Fe-doped InGaAs layers [START_REF] Mohandas | Generation of Continuous Wave Terahertz Frequency Radiation from Metal-Organic Chemical Vapour Deposition Grown Fe-Doped InGaAs and InGaAsP[END_REF][START_REF] Deumer | Continuous Wave Terahertz Receivers with 4.5 THz Bandwidth and 112dB Dynamic Range[END_REF] . The advantage of planar electrodes is their intrinsically low electrical capacitance allowing for efficient operation up to a few THz. Unfortunately, these electrodes come with a large conversion loss of ~50 -60 dB [START_REF] Harter | Wireless THz Link with Optoelectronic Transmitter and Receiver[END_REF]18 , which is far away from the This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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10.1063/5.0153046 best electronic mixers whose conversion loss can be as low as 12 dB 1 when they are integrated in a waveguide and operate in a reduced frequency bandwidth.

In this work, we present the design, fabrication and characterization of an ultrafast photoconductor embedded in a plasmonic microcavity designed for 1550-nm operation. This design improves the photoconductance and conversion efficiency by reducing the electrode spacing while maintaining high optical absorption and carrier collection efficiency. The photoconductor is based on a high-dark-resistivity and sub-picosecond-carrier-lifetime irondoped InGaAs layer. With this design, we demonstrate conversion losses lower than ~30 dB for frequencies up to 320 GHz. An ultrafast photoconductor illuminated by a light modulated at frequency 𝜔 𝐿0 can be modeled as a parametric conductance 𝐺(𝑡) = 𝐺 0 + 𝐺 1 cos(𝜔 𝐿𝑂 𝑡), since the charge carrier density in the device is driven by the intensity of the optical pump [START_REF] Coleman | Mixing and Detection of Coherent Light[END_REF] . Here, G 0 and G 1 are the average and modulated parts of the photoconductance, respectively. In addition, since the frequency response of the photoconductor is governed by the carrier lifetime , 𝐺 1 = (𝐺 0 -𝐺 𝑑𝑎𝑟𝑘 )/√1 + (𝜔 𝐿𝑂 𝜏) 2 20 with the dark conductivity G dark . This parametric photoconductance generates mixing frequency terms at 𝑛𝜔 𝐿𝑂 ± 𝜔 𝑇𝐻𝑧 , 𝑛 being a positive integer, when biased by an input THz signal at frequency 𝜔 𝑇𝐻𝑧 . As shown in the Supplementary Material, the Ultrafast Photoconductor

Results

Optoelectronic mixing by a photoconductor: design rules and minimum conversion loss.

! "# ! $$% ! &' ( a) b) ) = + &' ( + "#
This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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conversion loss 𝐿 = 𝑃 𝑇𝐻𝑧 𝑃 𝐼𝐹 ⁄ between the incident THz power and the IF output power at 𝜔 𝐼𝐹 = |𝜔 𝐿𝑂 -𝜔 𝑇𝐻𝑧 | can be expressed by:

𝐿 ≈ (1 + (𝜔 𝐿𝑂 𝜏) 2 ) (1 + 2𝐺 0 𝑅 𝐿 ) 4 (1 -𝐺 𝑑𝑎𝑟𝑘 𝐺 0 ⁄ ) 2 (𝐺 0 𝑅 𝐿 ) 2 (1)
where 𝑅 𝐿 , the input impedance of the IF receiver, is assumed to be equal to the source impedance. As expected, it can be seen from ( 1) that the carrier lifetime sets the frequency band of the mixer and minimizing the ratio 𝐺 𝑑𝑎𝑟𝑘 /𝐺 0 is essential in order to minimize the conversion loss. For 1550-nm-operation, photoconductors based on iron-doped InGaAs photoconductive material, which shows both sub-picosecond carrier lifetime and high dark resistivity [START_REF] Deumer | Continuous Wave Terahertz Receivers with 4.5 THz Bandwidth and 112dB Dynamic Range[END_REF] (> 1 k.cm), are likely to fulfill these requirements. In the best-case scenario, i.e.

𝜔 𝐿𝑂 𝜏 ≪ 1 and 𝐺 𝑑𝑎𝑟𝑘 ≪ 𝐺 0 , a minimum conversion loss 𝐿 𝑚𝑖𝑛 ≈18 dB is achieved at 1/𝐺 0 ≈ 2𝑅 𝐿 as seen in Figure 1b. It could reach 𝐿 𝑚𝑖𝑛 ≈ 12 dB if IF and THz filters were added on each side of the photoconductance. If 𝑅 𝐿 = 50 Ω, 𝐿 𝑚𝑖𝑛 is obtained when 𝐺 0 =10 mS, a value 25times larger than for state-of-the-art planar photoconductors. Please note that this is still much larger than the theoretical limit in conversion loss of 3.9 dB reached with an ideal resistive mixer (𝐺 𝑜𝑛 ≈ +∞) with matching loads working in pulsed mode at 𝜔 𝐿𝑂 and 50 % duty cycle [START_REF] Kelly | Fundamental Limits on Conversion Loss of Double Sideband Resistive Mixers[END_REF] . It is also still well above state-of-the-art electronic mixers which offer conversion loss around 12 dB up to 1 THz thanks to a careful electromagnetic design of IF and THz filters, which leads to a reduced tuning bandwidth around 10% [START_REF] Schlecht | Schottky Diode Based 1.2 THz Receivers Operating at Room-Temperature and below for Planetary Atmospheric Sounding[END_REF] . . For an improved electric field distribution both photoconductor thickness (t) and electrode spacing (L) should be similar and above ~1 µm. However, for a low-carrier lifetime photoconductor the responsivity is proportional to the photoconductive gain 𝜏/𝜏 𝑡𝑟 . [START_REF] Peytavit | Fundamentals of Terahertz Devices and Applications[END_REF]22 . Here, 𝜏 is the carrier lifetime, 𝜏 𝑡𝑟 the transit-time. Thus, a photoconductor with µm-wide electrode spacing would exhibit a low responsivity and hence low photoconductance, if its carrier lifetime is below 1 ps and its transit time is longer than 10 ps (v sat 10 5 cm/s). That is, it can be shown that the photoconductance (G 0 ) of a low-carrier lifetime photoconductor (assuming a 1D geometry) illuminated by an optical beam of power P 0 is equal to 22 :

InGaAs:Fe-based plasmonic cavity photoconductors for efficient optoelectronic mixing

𝐺 0 = 𝐴 𝐼𝑛𝐺𝑎𝐴𝑠 𝑞µ ℎ𝑣 𝜏 𝐿 2 𝑃 0 (2)
Eq. ( 2) shows that a reduction of the electrode spacing increases the photoconductance if the absorption in the InGaAs layer 𝐴 𝐼𝑛𝐺𝑎𝐴𝑠 is kept constant since it increases the carrier density.

The capacitance of the photoconductor should also be as low as possible in order to reach THz frequencies. Hence, we define:

𝐹 = 𝐴 𝐼𝑛𝐺𝑎𝐴𝑠 1 𝑆𝐿 𝑞µ𝜏 𝜀 𝑟 ℎ𝑣 (3)
as a suitable figure of merit to benchmark the efficiency of photoconductive THz receivers.

Here, 𝐹 is the ratio of the photoconductance per unit of optical power 𝐺 0 𝑃 0 ⁄ and the electrical capacitance (assuming that 1/𝐺 0 remains larger than the load resistance 𝑅 𝐿 ~50 Ω). For simplicity, the photoconductor is modeled as a parallel plate capacitor with relative dielectric constant  r ( r = 13.9 in InGaAs) and area S. That is, equation (3) shows that reducing the inter- electrode spacing without diminishing the absorption efficiency is a straightforward way to increase 𝐹 for a given photoconductive material and active area.

In order to assess the validity of this model, we have investigated photoconductors based on InGaAs:Fe layer embedded in a plasmonic microcavity, as shown schematically in Fig. 2b, with metallic layers acting as bias electrodes and plasmonic waveguide at the same time. The top This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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electrode is nanostructured to form a grating to achieve efficient coupling of 1550-nm light into the cavity and low parasitic serial resistance [START_REF] Billet | Ultra-Thin InGaAs-MSM Photodetectors for THz Optoelectronics Applications[END_REF][START_REF] Billet | Sub-Sampling of RF and THz Waves Using LT-GaAs Photoconductors under 1550 Nm Light Excitation[END_REF] . The bottom electrode consists of a buried gold layer. Figure 3a shows a map of the calculated absorption efficiency at 1550-nm-wavelength for a plasmonic microcavity photoconductor (PMP) as a function of the grating period and the InGaAs layer thickness t (more details can be found in the Methods section). For short grating periods p below 0.4 µm the absorption efficiency as a function of InGaAs thickness shows narrow absorption peaks related to Fabry-Pérot (FP) resonances. For grating periods longer than the wavelength in InGaAs (𝜆 𝐼𝑛𝐺𝑎𝐴𝑠 ≈ 430 nm), the structure of the absorption efficiency becomes more complex due to diffraction effects. At p≈ 𝜆 𝐼𝑛𝐺𝑎𝐴𝑠 , the grating can be seen as a coupler of the incident light to the first asymmetric mode of the plasmon slot waveguide [START_REF] Dionne | Plasmon Slot Waveguides: Towards Chip-Scale Propagation with Subwavelength-Scale Localization[END_REF] leading to a slight dependence on the InGaAs thickness. At p≈430 nm and t≈200 nm, we can observe an anti-crossing in the absorption map induced by the coupling between these two resonances. Figure 3b depicts the absorption efficiency versus InGaAs thickness at a fixed grating period in the two regimes. Close to the anti-crossing area (p = 415 nm), a very wide absorption peak (FWHM >250 nm) is achieved with a maximum above 80% at 250 nm InGaAsthickness. For the Fabry-Pérot regime, a narrow peak reaching 75% at t 160 nm with 60 nm-FWHM is predicted. Thus, for microtechnological processing, a very fine control of the InGaAs As a comparison, we have also calculated the absorption efficiency of a FP cavity with a top mirror consisting of 20-nm of gold covered by a 160-nm-thick silicon nitride (SiN) antireflecting (AR) layer, as previously developed for low-temperature-grown GaAs photoconductors operating at 780 nm [START_REF] Peytavit | Milliwatt-Level Output Power in the Sub-Terahertz Range Generated by Photomixing in a GaAs Photoconductor[END_REF] . In addition to a much larger sheet resistivity, it is shown in Figure 3b (the lowest sub-figure) that the top mirror leads to a lower and narrower absorption efficiency peak. This can be explained by its larger optical losses and its higher reflectance (~60%) despite an optimized SiN AR coating, which prevents achievement of critical coupling condition. Therefore, we decided to disregard this design and move forward with the design of the plasmonic microcavities. This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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image. Figure 4b compares the measured photoresponse as a function of excitation wavelength, which is proportional to the absorption efficiency, (right y-axis) with the calculated absorption efficiency (left y-axis). For the calculation, the parameters as measured by SEM (and shown in Figure 4a) were taken as the input. We observe very good qualitative agreement between measurement and calculation. Figure 4c summarizes the dependencies of the peak absorption efficiency on the geometrical parameters of the plasmonic cavity. In this absorption regime, grating period and layer thickness have a significant and similar impact on the absorption. It is would even be possible to counterbalance one with the other during processing.

Conversion loss measurement up to 320 GHz

The PMPs are integrated with a coplanar waveguide with contact pads allowing on-wafer characterization. After fabrication, the PMPs were characterized up to 325 GHz. Figure 5 shows SEM views of a typical device integrated in series to a 50-Ohm-coplanar waveguide ended by contact pads with dimensions adapted to the coplanar waveguides used for input and output coupling.

Figure 6a summarizes the I-V characterization of devices with 4-µm-diameter gratingelectrodes with and without illumination. It can be noticed that they are not perfectly symmetric with respect to zero bias because of the vertical structure. For optoelectronic mixing applications, this can be easily cancelled by the addition of a small dc bias. When the photoconductor is biased by the THz signal, only the part of the I-V curve around zero is used.

In this case the photoconductor can effectively be modeled as a perfect resistor which can be switched from R off = 280 k to R on = 300 , when illuminated by an optical power of 70 mW. This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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From Eq. 1, a conversion loss of around 20.5 dB is expected if R on =300 . This is in good agreement with the measured conversion loss vs frequency plotted in Figure 6b for devices with top electrode diameter between d = 2 to d = 6 µm. The best devices achieve around 22 dB conversion loss at the lower frequencies and around 30 dB at 320 GHz. In comparison, fully packaged state of the art photomixers with integrated antenna show conversion loss of ~50 dB at 100 GHz and 60 dB around 300 GHz [START_REF] Harter | Wireless THz Link with Optoelectronic Transmitter and Receiver[END_REF] . It can be seen that the conversion loss is not completely flat even for devices with the smallest diameter devices, whose RC frequency cutoff should be well beyond 300 GHz (1800 GHz for d=2 assuming R=50 Ohm). However, it is worth noting that the device with d=6 µm and f RC = 200 GHz shows, as expected, a larger increase of the conversion losses. We can also see some ripples because of the mismatch between the coplanar probes and the devices. Fig. 6c shows the dynamic range of the detector obtained by sweeping the input power from -60 dBm to 10 dBm. We achieve around 70 dB of dynamic range limited by the experimental set-up. Fig. 6d shows an IF spectrum showing a SNR around 50 dB, despite a very large RBW limited by the laser stability. This shows the superiority of the PMP as a THz mixer in comparison to a photodiode as Ref. [START_REF] Rouvalis | Millimeter-Wave Optoelectronic Mixers Based on Uni-Traveling Carrier Photodiodes[END_REF] reports similar SNR values despite a RBW of 100 Hz, which was possible by using an optical beatnote locked to a RF synthesizer.

Discussion

The measured conversion loss at frequencies below 70 GHz is in good agreement with the basic model developed in this study. A model allowing the quantitative estimation of the frequency dependent conversion loss would require more extensive work, but it is clear that the cut-off frequency related to the carrier lifetime and the impedance mismatch (due to the electrical capacitance of the device) have the largest impact. In addition, the measured carrier lifetime of the material may not represent the actual carrier lifetime during device operation. This is because the lifetime is deduced from differential transmission measurements, a pumpprobe measurement using fs-optical pulses. In contrast, during device operation the photoconductor is illuminated continuously by the optical intensity beating generated by two cw-laser lines. Thus, this carrier lifetime may be quite different due to saturation effects. In our case, the carrier lifetime which should be around 100 fs, resulting in a cut off frequency above 1 THz. However, if the actual lifetime during device operation was around 1 ps instead, This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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10.1063/5.0153046 10 we would obtain a cut-off frequency around 160 GHz, for example. These differences in the measured vs. actual carrier lifetime could explain the increasing conversion loss for higher frequencies for the smallest devices, which exhibit a very low capacitance and high RC cut-off frequency. In addition, developing an accurate electrical model of our conversion lossmeasurements is quite difficult, since, as seen before, it will require the perfect knowledge of the source and load impedances on both IF and THz bands. It is not the case, except in the lowest frequency band, since the impedances of the probes and waveguides are known only in their operating frequency band. This could explain the observed ripples and the higher conversion loss for higher frequencies as measured in our experiments. This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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Conclusion

We presented an optoelectronic photomixer based on an ultrafast, MBE-grown InGaAs:Fe layer embedded in a plasmonic microcavity. With this photomixer, we demonstrate a conversion loss as low as ~30 dB up to 325 GHz. That is, we expect significantly lower conversion loss than for state-of-the-art photomixers with integrated antenna based on a bulk photoconductive layer, once the PMPs are package. We expect similar improvements beyond 1 THz for the smallest size photomixers (when integrated with a THz antenna), since these devices show RC-related cut-off frequencies reaching 1.8 THz. Further improvements are achievable and will require optimization of the photoconductive material properties as well as better control of the electrical circuit's terminations in both the THz and IF frequency ranges. Overall, the presented plasmonic microcavity photoconductors achieve a very low conversion loss of ~30 dB at 320 GHz. This renders these devices extremely promising for application in high-data rate THz communications, in cw-THz spectrometers and in photonicsenabled THz spectrum analyzers.

Methods

Material growth: For epitaxy, a gas-source molecular beam epitaxy system by Riber was used.

The Fe-doped InGaAs layer was grown lattice matched to a semi-insulating, Fe-doped indium phosphide substrate.

Device Fabrication: The fabrication of the plasmonic microcavity photodetectors begins with the realization of a buried metal layer acting as the bottom mirror and bottom contact metallization. This is obtained by transferring the epi-layers onto a 2"-diameter high-resistivity (>5 k.cm) silicon wafer using a Au-Au thermo-compression bonding technique detailed in Ref. [START_REF] Peytavit | Wide-Band Continuous-Wave Terahertz Source with a Vertically Integrated Photomixer[END_REF] , followed by the wet etching of the InP substrate. Next, the Au (300 nm) nanogrid top contact metallization is realized through e-beam lithography, followed by e-beam evaporation and lift-off. The epi-layers are subsequently dry-etched by ICP using the top metal layer as etch-mask. The ground metal layer is finally dry-etched by an Ar + ion-beam around the PMP's down to the silicon substrate (Fig. 5). To electrically connect the nanogrid to the 50  coplanar line, suspended Ti/Au (20 nm/600 nm) wire-bridges are finally fabricated by a two-step e-beam lithography process. To this end, a first resist layer is used as support after deposition, e-beam lithography and reflow, followed by a second one to define the wires by This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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10.1063/5.0153046 standard lift-off process. The same process is used to realize the air-bridge connecting the 2D array to the 50  coplanar line.

Optical simulation of the plasmonic microcavity photoconductor

The numerical simulations are carried out to calculate the absorption efficiency of the PMPs.

We define the absorption efficiency as the ratio of the absorbed power in the InGaAs-layer to the incident opitcal power, as a function of the nanogrid period p, aperture width a, and cavity thickness t. The cavity is considered as a 2D structure infinitely periodic along one dimension and infinitely long on the other one (see Fig. 2(b)). The system is illuminated under normal incidence with a plane wave polarized orthogonally to the nanogrid electrodes (shown in Fig. 2b.). Frequency-dependent dielectric functions have been taken from Ref. [START_REF] Seifert | Revised Refractive Index and Absorption of In_1-XGa_xAs_yP_1-y Lattice-Matched to InP in Transparent and Absorption IR-Region[END_REF] (In 53 Ga 47 As) and Ref. [START_REF] Arsenin | Optical Constants and Structural Properties of Thin Gold Films[END_REF] (Au).

Photoresponse spectrum measurement.

Photoresponse spectrum of the PMP's was conducted by illuminating a test structure of 20x20 µm 2 area by an external-cavity laser (Yenista Tunics) by using a lensed optical fiber of mode field diameter (MFD) equal to 3 µm. Photoresponse data are directly extracted from the photocurrent measured by a sourcemeter (Keithley 2612A) at a bias voltage of 4 V and 4.2 mW of incident power under TM polarization.

Conversion Loss measurement:

A schematic of the photomixing measurement set-up is shown in Fig. S3 (Supplementary Material). The optical beatnote is generated by spatially overlapping the emission of two fiber-

Fig. 1

 1 Fig. 1 Details of the optoelectronic heterodyne THz receiver. (a) SEM image illustrating the down-conversion of an incoming THz frequency signal (purple) by mixing with a laser-based local oscillator (red) in a photoconductor. The output of the mixing process it the IF-signal (blue). (b) Conversion loss vs photoresistance of the photomixer calculated by using Eq. 1.

Fig. 2 h

 2 Fig. 2 Schematic of the plasmonic microcavity photoconductor. (a) State-of-the-art, planar, interdigitatedelectrode photoconductor. L is the electrode spacing and t denotes the thickness of the photosensitive layer.

Fig. 3 .

 3 Fig. 3. (a) Absorption efficiency map of a plasmonic microcavity photoconductor calculated at 1550 nm by rigorous coupled wave analysis (RCWA) as a function of the grating period p and InGaAs thickness t with grating thickness: h=300 nm and slit width a=0.3p. (b) Absorption efficiency vs InGaAs thickness with, from top to bottom panel, p=415 nm, p=300 nm and in the case of a top mirror consisting of 20-nm-thick gold layer cover by a 160-nm-thick Silicon nitride layer. We observe maximum absorption efficiency of 0.82 for p=415 nm (topmost sub-figure) and an InGaAs-thickness of 0.25 µm.

  InGaAsThis is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.PLEASE CITE THIS ARTICLE AS DOI:10.1063/5.0153046 layer thickness would be needed -which requires a careful calibration of the growth rates during epitaxy. At the same time, a much narrower spectral absorption bandwidth is calculated for the Fabry-Pérot regime (see figureS2) in comparison to the p = 415 nm case.

Fig. 4 .

 4 Fig. 4. a) SEM view of a FIB-cut cross section of a plasmonic microcavity photoconductor. The measurement uncertainty is around 5 nm. It is worth to notice that the layer above the grating is a Platinum-coating deposited within the FIB chamber and only aimed at protecting the sample from the ion milling. (b) Calculated absorption efficiency using the geometrical parameters measured by SEM and the measured photoresponse obtained from the same device. The scale for the responsivity was chosen to achieve the best visual fit. (c) Relative variation of the absorption efficiency when each parameter is varied around its optimum value, which are p = 465 nm, a = 208 nm; t = 217 nm and h = 377 nm.

Figure 4a shows a

  Figure4ashows a scanning electron micrograph of a FIB-cut cross section of a fully processed plasmonic microcavity photoconductor for a set of experimental parameters leading to large absorption around 1550 nm. The buried Au mirror, the InGaAs:Fe absorber and the grating coupler can be clearly seen. The spatial dimensions of the design are indicated in the SEM

Fig. 5 .

 5 Fig. 5.a) SEM view of a plasmonic microcavity photoconductor integrated in series to a coplanar waveguide. b) Close-up of the device showing the top grating electrode, the InGaAs:Fe-layer and the buried back reflector. As can be seen, the absorber is only 5 µm in diameter.

Fig. 6 .

 6 Fig. 6. a) Photocurrent of a 4-µm-diameter device vs applied bias voltage for several optical power levels. Around V b =0 V, R off /R on  10 3 when P opt = 70 mW b) Measured conversion loss vs frequency up to 325 GHz for devices with top electrodes diameters of d = 2, 3, 4 and 6 µm. The IF frequency was set to 𝒇 𝑰𝑭 =1 GHz and the THz power was 𝑷 𝑻𝑯𝒛 =-40 dBm. c) Experimental dynamic range at 𝒇 𝑻𝑯𝒛 = 100 GHz (P opt = 35 mW) shown by a 4-µm-diameter device. The measurement was limited by the experimental set-up: the resolution bandwidth of the spectrum analyzer was RBW= 3 MHz because of the low spectral stability of the DFB lasers. It results in a noise floor around -70 dBm. On the other side, the maximum THz power was limited to 𝑷 𝑻𝑯𝒛 ≈ 10 dBm. d) IF spectrum recorded by using a 4-µm-diameter device with and without a 100-GHz frequency input signal of 10-dBm-amplitude. Without a THz input signal, the measurement is limited by the noise floor of the spectrum analyzer (RBW=3 MHz).

  Photoresponse (Exp.)

AKNOWLEDGEMENTS

This work was supported by Hauts de France Regional Council (CPER "Wavetech",Start-AIRR ASPIR), RENATECH (French Network of Major Technology Centres), and French National Research Agency (Project BIRD,TIGER,PEPR Electronics)

In all cases, the mixing signal generated at the intermediate frequency f IF is outcoupled by a 0 -67 GHz coplanar probe and sent after amplification through a bias-T to a spectrum analyzer (SA). The measured power levels, P IF and P THz , are corrected for losses induced by the coplanar probes and by the waveguides and coaxial cables. They reach 1.5 dB for the IF power, 1.4 dB around 100 GHz and ~4 dB at 300 GHz for the THz power. At each THz frequency, the beating frequency is adjusted to ensure f IF =1 GHz.

SUPPLEMENTARY MATERIALS

The supporting information includes a circuit model of the optoelectronic mixing in a photoconductor, additional simulation data of the absorption efficiency of the plasmonic microcavity photoconductors and a schematic of the experimental set-up.

AUTHOR DECLARATIONS

Conflict of Interest

The authors have no conflicts to disclose.


domain: sdv info

text:
Arthur Longuefosse

Julien Raoult

Ilyes Benlala

Baudouin Denis De Senneville

Thomas Benkert

Julie Macey

Stéphanie Bui

Patrick Berger

Gilbert Ferretti

Jean-Yves Gaubert

Renan Liberge

Antoine Hutt

Baptiste Morel

François Laurent

Fabien Baldacci

Gaël Dournes

Generating high-resolution synthetic CT from lung MRI with ultrashort echo-times: initial evaluation in cystic fibrosis

Keywords: CF, cystic fibrosis UTE-MRI, ultrashort echo time MRI PFT, pulmonary function test GAN, generalized adversarial networks ICC, intraclass correlation coefficient

Synthetic CTs generated by AI from lung MRI with ultrashort echo times had better image quality than the original MR images and showed strong agreement with real CTs for the depiction of Cystic Fibrosis-related pulmonary alterations.

Key Results:

1. In this retrospective study, synthetic CT images produced by Generative Adversarial Networks using lung MRI with ultrashort echo-times (UTE-MRI) from patients with Cystic Fibrosis (CF) had a higher contrast-to-noise ratio than MR images, a lower noise level than CT, and the lowest level of artifacts among all 3 image types (P≤.001).

2. Almost perfect concordance was observed between real and synthetic CT images for the assessment of CF-related pulmonary structural alterations (ICC, ≥ 0.92).

INTRODUCTION

CT is the standard of reference for morphological imaging of the lung, owing to its excellent spatial resolution and contrast between air and intrapulmonary structures. However, CT imaging is based on ionizing radiations, which may raise concerns in chronic conditions when repeated imaging is needed [START_REF] Hatabu | Expanding Applications of Pulmonary MRI in the Clinical Evaluation of Lung Disorders: Fleischner Society Position Paper[END_REF]. Alternatively, lung MRI is a radiation-free imaging modality, but it remains a technical challenge owing to such things as the low proton density of this tissue, magnetic susceptibility artifacts, and respiratory motions. Lung MRI with ultrashort echo-times (UTE-MRI) (2,3) represents a recent breakthrough which helps with catching up the very fast decay of the lung MR signal and reducing susceptibility artefacts. As UTE-MRI does not require a contrast material injection or inhalation, it could be used to evaluate Cystic Fibrosis (CF) in the lungs of children, a population for which a radiation-free examination would be desirable. Indeed, previous studies have consistently demonstrated a better depiction of structural alterations with UTE-MRI than with conventional T1-weighted MR sequences [START_REF] Dournes | Lung morphology assessment of cystic fibrosis using MRI with ultra-short echo time at submillimeter spatial resolution[END_REF][START_REF] Renz | Ultrashort echo time MRI of the lung in children and adolescents: comparison with non-enhanced computed tomography and standard post-contrast T1w MRI sequences[END_REF]. Furthermore, several international position papers have recently agreed on the clinical use of proton MRI in the longitudinal follow-up of patients with CF, with the introduction of UTE-MRI [START_REF] Hatabu | Expanding Applications of Pulmonary MRI in the Clinical Evaluation of Lung Disorders: Fleischner Society Position Paper[END_REF][START_REF] Dournes | The Clinical Use of Lung MRI in Cystic Fibrosis: What, Now[END_REF][START_REF] Ciet | State-of-the-art review of lung imaging in cystic fibrosis with recommendations for pulmonologists and radiologists from the "iMAging managEment of cySTic fibROsis" (MAESTRO) consortium[END_REF]. However, UTE-MRI imaging quality remains inferior to that of CT. It displays a different imaging texture than the standard of reference CT, has a lower contrast than CT [START_REF] Renz | Ultrashort echo time MRI of the lung in children and adolescents: comparison with non-enhanced computed tomography and standard post-contrast T1w MRI sequences[END_REF] and features specific artifacts such as blurring or motions [START_REF] Papp | Lung parenchyma and structure visualisation in paediatric chest MRI: a comparison of different short and ultra-short echo time protocols[END_REF], questioning its clinical adoption without adept readers [START_REF] Gräfe | Pediatric MR lung imaging with 3D ultrashort-TE in free breathing: Are we past the conventional T2 sequence?[END_REF][START_REF] Gross | ATS Core Curriculum 2021. Pediatric Pulmonary Medicine: Pulmonary Infections[END_REF][START_REF] Tiddens | Paediatric lung imaging: the times they are a-changin[END_REF]. Indeed, there is a need for training to decipher CT semantic from UTE-MRI with confidence.

Nevertheless, artificial intelligence (AI) is currently changing the landscape of imaging tools available. Recently, deep learning with generative adversarial networks (GAN) have been developed and provides a framework for estimating generative models. Amongst the potential applications of GAN [START_REF] Yi | Generative adversarial network in medical imaging: A review[END_REF], there is a possibility of MR-to-CT translations. Lung MRI signal intensity conversion into CT-like attenuation values have been reported, demonstrating an interest in radiotherapy planning with PET-MRI [START_REF] Lenkowicz | A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases[END_REF][START_REF] Baydoun | Dixon-based thorax synthetic CT generation using Generative Adversarial Network[END_REF]. However, the feasibility of GAN to get high-resolution morphological imaging from lung UTE-MRI, that would reach CT-like quality, has not been evaluated yet. Moreover, the clinical impact of GAN for improving MRI-based evaluations of structural alterations in CF is unknown.

The aim of this study was to generate synthetic CTs from UTE using GAN and compare the image quality and clinical applicability of these synthetic images to their corresponding UTE-MRI and real CT scans.

MATERIAL AND METHODS

Study Sample

This feasibility AI study was retrospective and involved two different datasets [START_REF] Park | Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction[END_REF], collected between January 2018 and December 2022.

For model development and test, data were retrieved from medical records at the University Hospital of Bordeaux. Inclusion criteria were: 1) an age ≥ 8 years, 2) a diagnosis of CF determined by genetic testing and/or sweat chloride tests, 3) availability of non-contrastenhanced CT, MRI and PFT performed on the same day during an annual examination [START_REF]Mucoviscidose protocole national de diagnostic et de soins pour une maladie rare[END_REF].

Exclusion criteria were any contraindication to complete lung MRI. All patients and/or their parents provided written informed consent according to the local Ethics committee (CHUBX2020RE0267). The data were randomly split 75%/25% using Research Randomizer® into a training and test datasets. As a first-attempt study, an arbitrary minimum of 25 patients was calculated to assess a concordance in CF scorings > 0.6, with a risk alpha of 0.05 and a power of 90%.

For external validation [START_REF] Park | Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction[END_REF], 13 geographically distinct Institutions were screened amongst a multicenter trial (ClinicalTrials.gov: NCT03357562). Five of them conferred their agreement for an ancillary analysis of their prospectively collected data (Figure 1). Inclusion and exclusion criteria were the same as those for the training and test datasets, however, PFT data were not collected.

Imaging Protocols

MRI was performed with a 1.5 Tesla unit (MAGNETOM Aera, Siemens Healthcare), except for one center where MRI was done on a 3T scanner (MAGNETOM Skyra, Siemens Healthcare). In all centers, the UTE-MRI Spiral Volume Interpolated Breathold Examination (VIBE) sequence was implemented for evaluation [START_REF] Dournes | 3D ultrashort echo time MRI of the lung using stack-of-spirals and spherical k-Space coverages: Evaluation in healthy volunteers and parenchymal diseases[END_REF] (Supplemental Method E1). The basic sequence parameters were TR/TE/flip angle=4.1ms/0.07ms/5°; slice thickness=1mm; pixel size=1x1mm; acquisition time from 6 to 8 minutes with a prospective respiratory gating at end normal expiration. No contrast agent or sedation was used (Supplemental Method E1).

CT scans were done on 4 machine brands from two main manufacturers, i.e. GE and Siemens Healthineers. In all centers, patients were instructed to hold their breath at functional residual capacity (end normal expiration) [START_REF] Dournes | 3D ultrashort echo time MRI of the lung using stack-of-spirals and spherical k-Space coverages: Evaluation in healthy volunteers and parenchymal diseases[END_REF][START_REF] Loeve | Cystic fibrosis: are volumetric ultra-low-dose expiratory CT scans sufficient for monitoring related lung disease?[END_REF]. CTDIvol ranged from 0.6 to 7.5 mGy and Dose Length Product from 13 to 260 mGy.cm (Supplemental Table E1).

Generation of Synthetic CT using GAN

The general GAN principle is described and illustrated in Figure 2. 2D GAN architecture was set up with Semantic Image Synthesis with Spatially-Adaptive Normalization (SPADE) (https://github.com/alexandonian/contrastive-feature-loss) [START_REF] Park | Semantic Image Synthesis with Spatially-Adaptive Normalization[END_REF]. Details of the framework to generate synthetic CT from UTE-MRI using the Training dataset (Supplemental Tables E1-E2) are provided in Supplemental Method E2 [START_REF] Park | Semantic Image Synthesis with Spatially-Adaptive Normalization[END_REF][START_REF] De Senneville | EVolution: an edge-based variational method for non-rigid multi-modal image registration[END_REF][START_REF] Hofmanninger | Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem[END_REF][START_REF] Andonian | Contrastive Feature Loss for Image Prediction[END_REF][START_REF] Kingma | A Method for Stochastic Optimization[END_REF].

Evaluation of image quality

All examinations from the Test and External datasets were anonymized and randomly assigned for evaluation. For quality assessment, a reader with 4 years (J.R.) and 10 years (G.D.) of experience in chest imaging made the evaluations according to previously published methods [START_REF] Dournes | Quiet Submillimeter MR Imaging of the Lung Is Feasible with a PETRA Sequence at 1.5 T[END_REF][START_REF] Symons | Feasibility of Dose-reduced Chest CT with Photon-counting Detectors: Initial Results in Humans[END_REF][START_REF] Ohno | Pulmonary high-resolution ultrashort TE MR imaging: Comparison with thin-section standard-and low-dose computed tomography for the assessment of pulmonary parenchyma diseases[END_REF][START_REF] Darçot | Lung MRI assessment with high-frequency noninvasive ventilation at 3 T[END_REF].Quantitative assessment of apparent contrast-to-noise ratio, signal-to-noise ratio(2,3) and noise [START_REF] Symons | Feasibility of Dose-reduced Chest CT with Photon-counting Detectors: Initial Results in Humans[END_REF] were measured. Qualitative analysis was done [START_REF] Ohno | Pulmonary high-resolution ultrashort TE MR imaging: Comparison with thin-section standard-and low-dose computed tomography for the assessment of pulmonary parenchyma diseases[END_REF][START_REF] Darçot | Lung MRI assessment with high-frequency noninvasive ventilation at 3 T[END_REF] by assessing a total visibility score (range 0-30); total sharpness score (range 0-24); and total artefact score (range 0-45) (Supplemental Method E3-E4; Supplemental Tables E3).

Evaluation of CF structural alterations at the segmental level

At the segmental level, the presence of structural alterations was assessed using a binary scale (0, absent; 1, present) by G.D. (Supplemental Methods E5), i.e. peribronchial thickening, bronchiectasis, mucus plugs, bronchiolar impactions, collapse/consolidation, emphysema, bulla, and sacculation/abscess [START_REF] Hansell | Fleischner Society: glossary of terms for thoracic imaging[END_REF].

Concordance and reproducibility to assess the Bhalla score.

The clinical validity of synthetic CT was assessed using the original version of the Bhalla score [START_REF] Bhalla | Cystic fibrosis: scoring system with thin-section CT[END_REF]. The scoring system represents the severity of CF structural alterations and ranges from 0 to 25 (Supplemental Method E6, Supplemental Table E4). The junior reader (J.R.) had used the Bhalla score with CT but not MRI, while the senior reader (G.D.) had experience using the Bhalla score in both CT and MRI [START_REF] Dournes | 3D ultrashort echo time MRI of the lung using stack-of-spirals and spherical k-Space coverages: Evaluation in healthy volunteers and parenchymal diseases[END_REF]. Bhalla scores were determined independently, twice, by each reader for UTE-MRI, Synthetic CT, and CT. The Bhalla scores from the senior's CT first reading session were used as the reference standard.

Statistical analysis

Statistical analysis was carried out by P.B. ( [START_REF] Landis | The measurement of observer agreement for categorical data[END_REF][START_REF] Fleiss | The Equivalence of Weighted Kappa and the Intraclass Correlation Coefficient as Measures of Reliability[END_REF]. The relationship between Bhalla scores and PFT were assessed using Pearson correlation.

RESULTS

Study Population

A total of 110 consecutive CF patients completed both lung CT and UTE-MRI during their annual follow-up. All patients met the criteria of this study and thus none were excluded (Figure 1). Of these 110 patients, 82 (75%) were randomly assigned to the training dataset (mean age, 21 years ± 11 [SD]; 42 males, 40 females) and a total of 33 002 paired MR and CT slices were used to train the GAN algorithm (Supplemental Table E2). The test cohort included 28/110 (25%) CF patients of which 16 were male and 12 were female. The mean age in the test dataset was 18 years ± 11 with an age range of 8 to 50 years old. The mean Bhalla score for the test dataset was 16.6 ± 5.3. Additional patient characteristics are presented in Table 1.

From the 5 external Institutions who participated in this AI study, 46 CF patients who completed both lung CT and UTE-MRI on the same day were included in our external dataset. The mean age of patients in the external dataset was 20 years ± 11 and the mean CT Bhalla score was 12.6 ± 2.5 (Table 1).

Evaluation of image quality

Quantitative assessment of image quality.

In the test cohort, no difference was observed in the Signal-to-noise ratio between all imaging modalities (P = 0.63). Conversely, the median Contrast-to-noise ratio for synthetic CT images was 303 [221,382] compared to a median of 9.3 [6.6, 35] for UTE-MRI (P < .001). However, the overall noise was higher in real CT compared to MRI (median, 42 [32, 50] vs 26 [START_REF] Andonian | Contrastive Feature Loss for Image Prediction[END_REF][START_REF] Fleiss | The Equivalence of Weighted Kappa and the Intraclass Correlation Coefficient as Measures of Reliability[END_REF], respectively; P < .001) (Table 2, Supplemental Table E5, Figure 3).

Qualitative assessment of image quality

UTE-MRI had lower qualitative scores in regard to the blurring of contours (median score, 10.5 [START_REF] Gräfe | Pediatric MR lung imaging with 3D ultrashort-TE in free breathing: Are we past the conventional T2 sequence?[END_REF][START_REF] Yi | Generative adversarial network in medical imaging: A review[END_REF]) compared to real CT (median, 22 18, 24]) or synthetic CT (median score, 22 [START_REF] Loeve | Cystic fibrosis: are volumetric ultra-low-dose expiratory CT scans sufficient for monitoring related lung disease?[END_REF][START_REF] Symons | Feasibility of Dose-reduced Chest CT with Photon-counting Detectors: Initial Results in Humans[END_REF]; p < .001)). Synthetic CT had the lowest total artifact score (median score, 0 [0, 0]; P < .001) (Table 2). Beam hardening artifacts were noticed only on CT, in 17/28 (60%) patients.

Only UTE-MRI displayed slight-to-moderate motion artifacts in 14/28 (50%) patients with imperfect respiratory synchronization (Supplemental Table E6, Figure 4),

Confirmatory results in the external dataset

In the External dataset, the median Contrast-to-noise ratio for synthetic CT images was 364 [258,448], without significant difference with Test dataset (p = 0.22). Using MRI, a slight aliasing that did not overlap with the lung area was noticed in 1 female (Figure 4). As compared to the Test dataset, no significant difference in External dataset's imaging quality results was noticed, such as total sharpness score (median score, 22 [START_REF] De Senneville | EVolution: an edge-based variational method for non-rigid multi-modal image registration[END_REF][START_REF] Symons | Feasibility of Dose-reduced Chest CT with Photon-counting Detectors: Initial Results in Humans[END_REF]; P = 0.62) or total artefact score (median score, 0 [0, 0]; P = 0.43) (Supplemental Tables E7-E8).

Evaluation of CF structural alterations at the segmental level

There were 504 lung segments assessed among the 28 CF patients in the test dataset. A better agreement was observed between CT and Synthetic CT than between CT and UTE for the structural alterations bronchiectasis (CT vs synthetic CT κ = 0.91, CT vs UTE-MRI κ = 0.70), wall thickening (CT vs synthetic CT κ = 0.89, CT vs UTE-MRI κ = 0.70), and mucus plugs (CT vs synthetic CT κ = 0.98, CT vs UTE-MRI κ = 0.91), without overlap in 95% confidence intervals (Table 3). Additionally, fewer false negative structural alterations were observed on Synthetic CT (Supplemental Table E8). For instance, 55/252 (21%) lung segments with bronchiectasis were missed on UTE-MRI in the test cohort, although 16/252 (6%) lung segments with were missed on Synthetic CT. Moreover, fewer false positive structural alterations were observed on synthetic CT (Supplemental Table E8). For instance, on UTE-MRI there were 12/132 (9%) lung segments with a false positive depiction of mucus plugs compared to 1/132(0.7%) lung segment with a false positive on synthetic CT. There were 828 lung segments assessed among the 46 CF patients in the external dataset, and agreement regarding structural alterations was better between CT and Synthetic CT compared to CT and UTE for instance regarding bronchiectasis (κ = 0.97 and κ = 0.79, respectively) (Table 3). Furthermore, a reduction in both false positive and false negative depictions of structural alterations such as severe (Figure 4) or mild (Figure 5) bronchiectasis was observed on Synthetic CT (Table 3, Supplemental Table E9).

Bhalla score concordance between readers and correlation with pulmonary function tests.

For the junior reader, the UTE-MRI Bhalla score showed substantial concordance with the real CT reference Bhalla score (ICC, 0.70) in the test dataset. Alternatively, the concordance of the Synthetic CT or real CT Bhalla scores with the reference CT Bhalla score were excellent (ICC, 0.92 and ICC, 0.93, respectively).

In the external dataset, substantial concordance was observed between UTE Bhalla scores assigned by the junior reader and the real CT reference Bhalla score (ICC, 0.77), and an almost perfect concordance between Synthetic CT and real CT reference Bhalla scores (ICC, 0.93) (Table 4, Figure 5). For the senior reader, there was excellent concordance between both UTE (ICC, 0.95) and Synthetic CT (ICC, 0.97) Bhalla scores and the real CT reference Bhalla score.

Synthetic CT, and UTE-MRI Bhalla scores assessed by the senior reader demonstrated positive correlations with Forced Expiratory Volume in 1 second percentage predict (FEV1%p) (r = 0.62, P < .001; r = 0.62, P < .001; r = 0.60, P < .001; respectively) and FEV1/Forced Vital Capacity (FVC) (r = 0.52, P = .005; r = 0.53, P = .004; r = 0.45, P = .01; respectively). However, UTE Bhalla scores determined by the junior reader alone did not correlate with the obstructive pattern, assessed by the FEV1/FVC ratio (r = 0.33; P = .08) (Supplemental Table E10).

The intra-observer reproducibility of UTE, Synthetic CT or CT evaluations was almost perfect for the junior reader (ICC ≥ 0.90) and the senior reader (ICC ≥ 0.98) (Supplemental Table E11).

DISCUSSION

Lung MRI with ultrashort echo times (UTE-MRI) is a recent breakthrough for morphological MR imaging. However, its imaging quality is still inferior to CT. The aim of the study was to improve UTE-MRI quality by using post-processing with Generative Adversarial Networks (GAN). The results showed that the median contrast-to-noise ratio for synthetic CT was 303 [221,382], higher than that of UTE-MRI (median, 9.3 [6.6, 35]; P < .001). Compared to the other images, synthetic CT had the lowest level of artifacts (median score, 0 [0, 0] P ≤ .001),

The concordance between Bhalla scores for synthetic and real CTs was almost perfect for both a senior reader (ICC, 0.99) and a junior reader without any experience in UTE-MRI scoring (ICC, 0. 92). Finally, Synthetic CT Bhalla scores correlated with pulmonary function tests such as forced expiratory volume in 1 second percentage predicted (r, 0.62; p < .001).

To the best of our knowledge, this study is the first to report the use of GAN for generating high-resolution CT-like morphological imaging from lung UTE-MRI. Previous lung MRI studies with GAN have focused on converting the MRI signal into CT-like attenuation values to enable correcting the metabolic information of PET-MRI from low resolution images [START_REF] Lenkowicz | A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases[END_REF][START_REF] Baydoun | Dixon-based thorax synthetic CT generation using Generative Adversarial Network[END_REF]. Indeed, those evaluations were not done with UTE-MRI, and the resolution was of 3 mm slice thickness at best. Thus, an evaluation of morphological information was not reported.

Herein, GAN was able to generate 3D isotropic synthetic lung CT with a millimetric resolution. Also, we found that heterogeneously distributed MRI artifacts, such as slight-tomoderate motion artifacts, were removed after GAN processing. Of note, AI appeared able to correct them without affecting the global imaging features. Conversely, we found that some structural alterations that were visually missed by the expert reader on UTE alone were depicted on Synthetic CT. Those features were consistently confirmed as true positives on corresponding CT. Generation of synthetic CT images by GAN did not introduce additional false positive findings in both our test and external dataset.

In this study, CT scans protocols were not uniform, questioning the results whether only CT at high doses may have been used. Nevertheless, the study was retrospective, and the reduction of CT doses has been shown to not alter the CT morphological information in CF (31). In addition, the resulting GAN model was not dependent on a single manufacturer or kernel, and the integrated GAN model showed good generalizability, with similar imaging quality results between a Test and External datasets (P ≥ 0.12).

In addition, the clinical robustness and applicability of the method were evaluated through the assessment of the Bhalla score. The concordance of the Bhalla score assigned to Synthetic CT and real CT was almost perfect according to both an expert (ICC, 0.99) and a non-expert reader (ICC, 0.92). Of note, the non-expert reader had a lower concordance by using UTE alone (ICC, 0.70). These findings were constant across a Test dataset and an external dataset of CF patients' examinations from geographically distinct Institutions [START_REF] Park | Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction[END_REF]. Also, these ICC values were comparable to those reported in the literature with CT, showing ICC of 0.96 [0.92, 0.98] to assess the Bhalla score using CT (31).

Therefore, synthetic CT appeared to enhance the applicability of lung MRI in the clinical setting. It may open the door to a new era of lung imaging without continuing dependence upon ionizing radiation, which may be applicable to diseases beyond CF, and perhaps beyond the chest. Also, these initial results may pave the way for more standardization of MRI examinations and translating CT methods of evaluation to MRI [START_REF] Ciet | State-of-the-art review of lung imaging in cystic fibrosis with recommendations for pulmonologists and radiologists from the "iMAging managEment of cySTic fibROsis" (MAESTRO) consortium[END_REF]32). One could discuss that CT is also being revolutionized by emerging evolutions for reducing radiation dose while maintaining image quality (33). Nevertheless, MRI has no ionizing radiation. Also, synthetic CT could enhance MRI as a "one-stop-shop" ionizing radiation-free examination, with possibility to combine high resolution morphology to functional information (34,35) in a reasonable acquisition time of less than 15 minutes [START_REF] Dournes | The Clinical Use of Lung MRI in Cystic Fibrosis: What, Now[END_REF]. Next studies may address the relative contribution of these techniques in the future.

The study had several limitations. First, the study was retrospective, and a larger prospective study involving several junior and senior readers should be done to assess the clinical robustness further. Second, a single scoring system was evaluated, and other scoring methods may be worth evaluating for larger applications. Third, the technique was based on 2D algorithms, and there may be ways for improvements such as 3D algorithms. Fourth, MRI is inferior to CT in terms of cost and acquisition time. Fifth, the multicenter study was done by using a single MR sequence scheme and the generalizability to other UTE or ZTE sequence schemes remains to be explored.

CONCLUSION

Synthetic CTs showed almost perfect concordance with CTs for the depiction of CF-related pulmonary alterations and had better image quality than lung MRI with ultrashort echo-times. Note: Evaluation of lung structural alterations according to the senior reader with CT as reference.

Ernst

Legends: UTE-MRI = lung MRI with ultrashort echo-times, CI = confidence interval, NA=not applicable. Note: Ref_CT corresponds to the evaluation of lung structural alterations according to the senior reader on real computed tomography.

UTE-MRI = lung MRI with ultrashort echo-times, ICC = intraclass correlation coefficient, CI = confidence interval, NA = not applicable. 3D isotropic millimetre imaging was used for human lung imaging because of the presence of fine structures such as bronchi and vessels. For this, a field-of-view (FOV) of (320x320mm)

was used to cover the entire lung in the native coronal plane. A matrix resolution of 320x320 was used to reach a millimetre pixel resolution. The slice thickness was adapted to FOV size and matrix size to get an isotropic voxel dimension of (1x1x1mm). The number of slices had to be adapted to the patient size and ranged typically from 200 to 240. Patients were positioned in the supine position with arms along the body. To prevent aliasing due to the Cartesian sampling in the slice direction, imaging was performed in the coronal plane, covering the entire chest. The basic sequence parameters were as follows: TR/TE/flip angle=4.1ms/0.07ms/5°(4). The acquisition was performed during free breathing. To reduce respiratory-related artifacts, prospective gating was applied. For this purpose, navigator pulses were inserted into the sequence, from which the respiratory signal is extracted during scanning at functional residual capacity (end normal expiration). Once sufficient data was acquired in the end-expiratory state using a tolerance window of 40%, the scan stops automatically, and the collected data is used to reconstruct corresponding images. Acquisition time, therefore, depends on the respiratory pattern of the patient and ranged from 6 to 8 minutes. No injection of contrast agent or inhalation was used.

Methods E2. Generative Adversarial Networks framework.

To generate synthetic CT from lung MRI with ultrashort echo-times (UTE-MRI), a Training pipeline was implemented. To achieve high-resolution morphological imaging, CTs reconstructed with high frequency and pulmonary kernels were used for Training (Supplemental Table E2). Thus, all CT and MR 2D slices were first resampled in the axial axis on a common grid with a voxel size of 0.6×0.6×0.6mm 3 , and aligned each other using the EVolution algorithm [START_REF] Park | Semantic Image Synthesis with Spatially-Adaptive Normalization[END_REF]. To speed up calculations and guide training, an automatic lung segmentation of the registered 2D CT images was computed using the U-net R-231 convolutional network [START_REF] De Senneville | EVolution: an edge-based variational method for non-rigid multi-modal image registration[END_REF]. Since the lung MRI signal is not calibrated, CT intensities were Apparent signal-to-noise ratio and apparent contrast-to-noise ratio were expressed as percentages and calculated as follows (1,2):

Signal-to-noise ratio = S lung / S air ) x 100 (%)

Contrast-to-noise ratio = (S lung -S airway ) / S vessel x 100 (%).

Moreover, the standard deviation of air within the large tracheo-bronchial tree was chosen as a measurement of overall noise [START_REF] Symons | Feasibility of Dose-reduced Chest CT with Photon-counting Detectors: Initial Results in Humans[END_REF]. Herein, three ROIs of were drawn within the mid portion of the trachea, the right mainstem and left mainstem bronchi, and averaged to get a single mean standard deviation value.

Supplemental Table E11 provides information on the inter observer reproducibility of independent measurements. Also, the junior reader assessed the evaluation twice to provide additional analysis of intra-observer reproducibility. Per each lung, a qualitative score of imaging quality according to a scale adapted from Ohno et al [START_REF] Symons | Feasibility of Dose-reduced Chest CT with Photon-counting Detectors: Initial Results in Humans[END_REF] was performed on axial imaging slices at three levels: upper lung (above the cross of the aorta), mid lung (between the cross of the aorta and the superior pulmonary veins) and inferior lung (below the superior pulmonary veins). Moreover, the central lung was defined as the two third internal part of the lung, and the peripheral lung was defined as the third external part of the lung. For CT scans, a parenchymal windowing was chosen, with a width of 1500 HU and a level of -450 HU.

Methods

The visibility of central airways and central vessels was scored as follows: 0 = no depiction; 1 = depicted at segmental level; 2 = depicted at subsegmental level; 3 = depicted at subsubsegmental level; 4 = depicted beyond sub-subsegmental level. The visibility of peripheral airways and peripheral vessels was scored as follows: 0 = not visible; 1 = visible. Then, the total visibility score was calculated as the sum of central and peripheral scorings across the three upper, mid, and inferior lung levels. In the same regions, the sharpness of vessels and airways was score as follows: 0 = blurred; 1 = intermediate; 2 = sharp. Then, the total sharpness score was calculated as the sum of central and peripheral scorings across the three upper, mid, and inferior lung levels (Supplemental Table E3).

Finally, five artifacts were considered for analysis: beam hardening, motion, aliasing, shadowing, and streaks artifacts. The severity of these artifacts was scored between 0 and 3 as follows: 0 = no artifact; 1 = slight artefact without blurring of anatomical structures; 2 = moderate artefact with blurring of anatomical structures; 3 = severe artefact with no normal structure recognizable. No distinction was done between the central and peripheral lung herein. Thus, the total artefact score was calculated as the sum of scorings across three upper, mid, and inferior lung levels. (Supplemental Table E3).

Therefore, the (minimum to maximum) range of total visibility, sharpness, and artifact scores were (0 to 30), (0 to 24) and (0 to 45), respectively.

Supplemental Table E11 provides information on the inter observer reproducibility of independent evaluations. Also, the junior reader assessed the evaluation twice to provide additional analysis of intra-observer reproducibility.

Methods E5. Evaluation of CF structural alterations at the segmental level

To assess whether UTE-MRI and Synthetic CT may provide similar structural CF-related information to real CT, a senior reader with 10 years of experience in chest imaging (G.D.) and a published experience in both chest CT and MRI of cystic fibrosis completed the segmental analyses. For this task, the junior reader was left out of the evaluation, to keep him as naïve as possible from CF scoring with UTE. All UTE-MRI, Synthetic CT and CT datasets were anonymized and analyzed in random order, blinded from any clinical data. Multiplanar reformations were allowed. At the segmental level, the presence or absence of structural alterations was assessed using a binary scale (0= absent, 1=present).

Structural alterations were those necessary to complete the Bhalla scoring system (25) (see Supplemental Table E1) i.e., peribronchial thickening, bronchiectasis, mucus plugs, bronchiolar impactions with the tree-in-bud pattern, collapse/consolidation, emphysema, bulla, and sacculation/abscess. Definitions of structural abnormalities were those of the Fleishner Glossary of terms [START_REF] Darçot | Lung MRI assessment with high-frequency noninvasive ventilation at 3 T[END_REF].

Methods E6. Evaluation of the Bhalla score.

Structural alterations were evaluated according to the original version of the standard Bhalla scoring system (25) (see Supplemental Table E4). Lung structural abnormalities, i.e., peribronchial thickening, bronchiectasis, mucus plugs, bronchiolar impactions with the treein-bud pattern, collapse/consolidation, emphysema, bulla, and sacculation/abscess.

Definitions of structural abnormalities were those of the Fleishner Glossary of terms [START_REF] Darçot | Lung MRI assessment with high-frequency noninvasive ventilation at 3 T[END_REF].

According to the scoring system, bronchiectasis and peribronchial thickening were assigned a severity score as follows:

-Bronchiectasis severity: Absent (0), luminal diameter slightly greater than the diameter of the adjacent vessel (Mild (1)), luminal diameter 2-3× the adjacent vessel (Moderate (2)), luminal diameter > 3× the adjacent vessel (Severe (3)).

-Peribronchial thickening severity: Absent (0), wall thickness equal to the diameter of adjacent vessel (Mild (1)), wall thickness 2× the adjacent vessel (Moderate (2)), wall thickness > 2× the adjacent vessel (Severe (3)).

The bronchial generation involved by bronchiectasis or mucus impactions was scored as follows: Absent (0); up to the 4 th generation (1); up to the fifth generation (2); up to the 6 th generation and above (3).

Then, the score is calculated as follows: Total Bhalla score = 25 -(sum of scorings).

The evaluations were performed independently by GD and JR, twice, to assess the intra and interobserver reproducibility (Supplemental Table E10).

SUPPLEMENTAL TABLES.

Figure 1 .

 1 Figure 1. Study flow chart.

Figure 2 .

 2 Figure 2. Generative Adversarial Network (GAN) principle.

Figure 3 .

 3 Figure 3. Example images of the lung in a 12-year-old female with Cystic Fibrosis from the test dataset. The contrast-to-noise ratio was 8.5 on (A) Lung MRI with ultrashort echo-times (UTE-MRI), whereas it was 227 on ((B) synthetic CT images generated by AI from UTE-MRI and 226 on (C) real CT examination with a clearer delineation of structural alterations, such as small bronchiolar impactions (white arrowhead) in the right lower lobe. the total sharpness score of the (B) synthetic CT was 22, better than (A) UTE-MRI for which it was equal to 14 and looks more like the (C) corresponding real CT scan for which it was equal to 22. On (C) low-dose CT image, note the presence of diffuse beam hardening artifacts due to the presence of the rib cage, some of them being indicated by white arrows.

Figure 4 .

 4 Figure 4. Example images of the lung in a 21-year-old male with Cystic Fibrosis from the external validation dataset. On (A) lung MRI with ultrashort echo-times (UTE-MRI), there are motion artifacts on the right side (white arrows). These artifacts were not observed on (B) synthetic CT images generated by AI from UTE-MRI, without affecting the rest of the reconstructed image. Bronchiectasis of the left lower lobe (white arrowheads) was visually missed on (A) UTE-MRI leading to a false negative depiction of bronchiectasis, but clearer on (B) synthetic CT and confirmed on the (C) corresponding real CT scan.

Figure 5 .

 5 Figure 5. Example images of the lung in a 20-year-old female with Cystic Fibrosis from the external validation dataset. On (A) Lung MRI with ultrashort echo-times (UTE-MRI), aliasing of the mammary glands (white arrows) is visible partially outside the field-of-view due to the Cartesian k-space sampling in the anteroposterior axis of UTE-MRI. The aliasing artifacts were visible in the posterior extrapulmonary subcutaneous fat and did not impair the lung area on (A) UTE-MRI and were still noticeable on (B) synthetic CT images generated by AI from UTE-MRI. Note the presence of mild bronchiectasis in the left upper lobe (white arrowheads), with a conspicuous delineation on (B) synthetic CT and (C) corresponding real CT.

Figure 6 .

 6 Figure 6. Example images of the lung in a 15-year-old male with Cystic Fibrosis from the external validation dataset. (A, C, E) show synthetic CT images generated by AI from lung MRI with ultrashort echo-times and (B, D, F) show corresponding real CT. (A, B) Axial, (C, D) coronal, and (E, F) sagittal reformations are possible owing to the 3D isotropic voxel at millimeter resolution. The Bhalla score was scored as 12 on both examinations.

  then cropped to[-1000; 2000] HU and rescaled to [-1; 1]. Thus, MR intensity values were normalized using zero mean and unit variance. Herein, signal intensity values were cropped to[-3σ; 3σ] to remove outliers, σ being the standard deviation of signal intensities, and rescale them to [-1; 1]. Then, GAN architecture was set up with Semantic Image Synthesis with Spatially-Adaptive Normalization (SPADE)[START_REF] Hofmanninger | Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem[END_REF]. In SPADE, the learned affine parameters need to be spatially adaptive, which means that different scaling and bias are computed according to the semantic information learned during training. Using this method, previous experiments demonstrated the advantage of the SPADE method regarding both visual fidelity and alignment with input layouts[START_REF] Hofmanninger | Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem[END_REF]. Moreover, the loss function was defined as a combination of feature-matching, perceptual, and contrastive (https://github.com/alexandonian/contrastive-feature-loss)[START_REF] Andonian | Contrastive Feature Loss for Image Prediction[END_REF]. We use the Adam optimizer (23), a batch size of 1, a learning rate of 0.0001 and ReLU activation for the generator, and a learning rate of 0.0004 and LeakyReLU activation for the discriminator. The training process included 100 epochs and lasted around 400 hours on a 12GB NVIDIA RTX 2080 Ti. Finally, generating Synthetic CT from UTE with a trained model required around thirty seconds on one single GPU. Methods E3. Quantitative assessment of imaging quality Two readers with 4 years (J.R.) and 10 years (G.D.) of experience in chest imaging made the qualitative evaluation of imaging quality independently, and the mean of evaluations was chosen as the final result. All native UTE, CT and Synthetic CT data sets were anonymized, analyzed in random order, blinded from any clinical characteristics. Regions of Interest (ROIs) of the same shape (circle) and size (56 mm 2 ) were drawn by G.D. and J.R. in the axial plane by using 3D Slicer 4.11, an open-source software. Region-ofinterest (ROIs) were placed within the trachea, the right and left main bronchi and their signal values were averaged to calculate S air . ROIs were placed within the pulmonary trunk, the right and left main pulmonary arteries and their signal values were averaged to calculate S vessel .Three axial sections were selected at the level of the crossing of the aorta, the carina and the inferior pulmonary veins. ROIs were placed at each location in the anterior part and posterior part of the right and left lung, at least 2 cm from the lung periphery and by careful avoidance of vessels. Data in the resulting 12 ROIs were averaged to calculate S lung .

  E4. Qualitative assessment of imaging quality. Two readers with 4 years (J.R.) and 10 years (G.D.) of experience in chest imaging made the qualitative evaluation of imaging quality independently Multiplanar reformations were allowed. All UTE, Synthetic CT and CT datasets were anonymized, analyzed in random order, blinded from any clinical characteristics. Then, J.R. and G.D. discussed the imaging data together during the same sessions. A third reader with 8 years of experience (I.B.) in thoracic imaging was consulted to reach a final qualitative value.

Table 1 .

 1 CW, Basten IA, Ilsen B, et al. Pulmonary disease in cystic fibrosis: assessment with chest CT at chest radiography dose levels. . Veldhoen S, Heidenreich JF, Metz C, et al. Three-dimensional Ultrashort Echotime Magnetic Resonance Imaging for Combined Morphologic and Ventilation Imaging in Pediatric Patients With Pulmonary Disease. J Thorac Imaging 2021;36(1):43-51. doi: 10.1097/RTI.0000000000000537. Patient characteristics. Data are mean ± standard deviation for continuous data and number of patients with percentages in parentheses for categorical data. BMI = body mass index, FEV1 = forced expiratory volume in 1 second, FVC = forced vital capacity, RV = residual volume, TLC = total lung capacity, NA = not applicable.

	Radiology 2014;273(2):597-605. doi:

34. Wielpütz MO, Puderbach

M, Kopp-Schneider A, et al. Magnetic resonance imaging detects changes in structure and perfusion, and response to therapy in early cystic fibrosis lung disease. Am J Respir Crit Care Med 2014;189(8):956-965. doi: 10.1164/rccm.201309-1659OC. 35

Table 2 . Quantitative and qualitative assessment of image quality.

 2 For quantitative and qualitative analysis, data are medians with [interquartile range]. Overall comparison of medians was assessed with Friedman test and post hoc Dunn's test. * indicates a p-value ≤ .001 between CT and Synthetic CT, ** indicates a p-value ≤ .001 between UTE-MRI and Synthetic CT and † indicates a p-value ≤ .001 between UTE-MRI and CT.

	Test dataset (n=28 patients)	UTE-MRI			Synthetic CT	CT		p-value
	Quantitative analysis
	Contrast-to-noise ratio	9.3 **, †	[6.6, 35]	303	[221, 382]	247	[210, 323]	<0.001
	Signal-to-noise-ratio	88	[87, 91]	88	[84, 92]	88	[86, 91]	0.63
	Overall Noise	22	[18, 31]	26	[22, 30]	42 *, †	[32, 50]	<0.001
	Qualitative analysis
	Total visibility score	27 **, †	[24, 29]	29	[27, 30]	29	[27, 30]	<0.001
	Total sharpness score	10.5 **, †	[9, 12]	22	[18, 24]	22	[18, 24]	<0.001
	Total artifact score	0.5 **	[0, 1]	0	[0, 0]	1 *	[0, 1]	<0.001
	External dataset	UTE-MRI			Synthetic CT	CT		p-value
	(n=46 patients)
	Quantitative analysis
	Contrast-to-noise ratio	13 **, †	[7, 20]	364	[258, 448]	245	[155, 324]	<0.001
	Signal-to-noise ratio	90	[88, 93]	90	[88, 92]	90	[87, 92]	0.75
	Overall Noise	21.5	[14, 45]	23	[18, 28]	39 *, †	[20, 46]	0.002
	Qualitative analysis
	Total visibility score	28 **, †	[26, 29]	29	[28, 30]	29	[28, 30]	<0.001
	Total sharpness score	11 **, †	[9, 18]	22	[20, 24]	22	[18, 24]	<0.001
	Total artifacts score	1 **	[0, 3]	0	[0, 0]	0.5*	[0, 1]	<0.001

Note: The (minimum to maximum) range of visibility, sharpness, and artifact total scores are (0 to 30), (0 to 24) and (0 to 45), respectively.

Table 3 . Strength of Agreement between reader evaluations of structural alterations at a segmental level.

 3

	Test dataset		CT vs UTE-MRI	CT vs Synthetic CT
	(n=504 segments in 28 patients)		κw	95% CI	κw	95% CI
	Peribronchial thickening
	Present	277 (54.9%)	0.70	[0.64, 0.77]	0.89	[0.85,0.93]
	Bronchiectasis
	Present	252 (50%)	0.76	[0.71, 0.82]	0.91	[0.88, 0.95]
	Central mucus
	Present	131 (25.9%)	0.91	[0.87, 0.95]	0.98	[0.97,1.00]
	Peripheral mucus
	Present	179 (35.5%)	0.90	[0.86, 0.94]	0.98	[0.96, 0.99]
	Collapse/Consolidation
	Present	12 (2.3%)	0.90	[0.77, 1.00]	>0.99	NA
	Emphysema
	Present	0 (0%)	NA	NA	NA	NA
	Sacculation/Abscess
	Present	3 (0.5%)	>0.99	NA	>0.99	NA
	Bulla
	Present	0 (0%)	NA	NA	NA	NA
	External dataset		CT vs UTE-MRI	CT vs Synthetic CT
	(n=828 segments in 46 patients)		κw	95% CI	κw	95% CI
	Peribronchial thickening
	Present	703 (84.9%)	0.81	[0.76, 0.87]	0.94	[0.91, 0.97]
	Bronchiectasis
	Present	677 (81.2%)	0.79	[0.74, 0.84]	0.97	[0.95, 0.99]
	Central mucus
	Present	491 (59.2%)	0.86	[0.82, 0.89]	0.94	[0.91, 0.96]
	Peripheral mucus

Table 4 . Assessment of Concordance between Bhalla scores assigned to each image type by a junior or senior reader.

 4

		Test dataset (n=28 patients)	External daataset (n=46 patients)
		Ref_CT vs. UTE-MRI	Ref_CT vs. Synthetic CT	Ref_CT vs. CT	Ref_CT vs. UTE-MRI	Ref_CT vs. Synthetic CT	Ref_CT vs. CT
	Junior reader
	ICC	0.70	0.92	0.93	0.77	0.93	0.93
	[95% CI]	[0.45, 0.84]	[0.83; 0.96]	[0.85; 0.97]	[0.60; 0.87]	[0.88; 0.96]	[0.88; 0.96]
	Senior reader
	ICC	0.96	0.99	NA	0.95	0.97	NA
	[95% CI]	[0.93; 0.98]	[0.99; 0.99]	NA	[0.92; 0.97]	[0.94; 0.98]	NA

Table E1 . CT characteristics in Training, Test and External datasets.

 E1

	Groups	Machine Brand	Kernel	kV	mAs	Slice thickness (mm)	CTDIvol (mGy)	DLP (mGy.cm)
	Training	GE Revolution® (Site1, n=62)	LUNG (n=51); I50f3 (n=9) ; BI57d3 (n=2)
		Somatom Definition 64® (Site1, n=4)	B70f (n=2); B50f (n=1) ; I50f3 (n=1)	(80-120) (9-2195)	(0.625-1.25)	(0.8-6)	(15-250)
		Somatom Force® (Site1, n=16)	BI57d3 (n=10); BI57d5 (n=3); LUNG (n=3)
	Test	GE Revolution® (Site1, n=10)	LUNG (n=9); BI57d3 (n=1)
		Somatom Definition 64® (Site1, n=1)	B50f (n=1)	(80-140)	(9-808)	(0.625-1)	(0.6-7)	(13-245)
		Somatom Force® (Site1, n=17)	BI57d3 (n=2); BI57d5 (n=15)
	External validation	GE Revolution® (Site2, n=6; Site3, n=8 ;)	LUNG (n=14)
		GE OptimaCT660® (Site 4, n=11; Site2, n=3)	LUNG (n=14)	(70-150) (9-1610)	(0.625-1.25)	(0.8-7.5)	(16-260)
		Somatom Definition 64®
		(Site5, n=11; Site6, n=3)

Table E8 . Comparison of imaging quality between the Test dataset and External dataset.

 E8 : data are median with [interquartile range] for qualitative and quantitative measurements. Comparison of independent medians are done with the Mann-Whitney test.

		Test dataset (n = 28)	External dataset (n = 46)	p-value
	Quantitative analysis
	UTE-MRI
	Contrast-to-noise ratio	9.3	[6.6, 35]	13	[7, 20]	0.81
	Signal-to-noise ratio	88	[87, 91]	90	[88, 93]	0.10
	Overall noise	22	[18, 31]	21.5	[14, 45]	0.67
	Synthetic CT
	Contrast-to-noise ratio	303	[221, 382]	364	[258, 448]	0.22
	Signal-to-noise ratio	88	[84, 92]	90	[88, 92]	0.35
	Overall noise	26	[22, 30]	23	[18, 28]	0.12
	CT
	Contrast-to-noise ratio	247	[210, 323]	245	[155, 324]	0.29
	Signal-to-noise ratio	88	[86, 91]	90	[87, 92]	0.14
	Overall noise	42	[32, 50]	39	[20, 46]	0.08
	Qualitative analysis
	UTE-MRI
	Total visibility score	27	[24, 29]	28	[26, 29]	0.10
	Total sharpness score	10.5	[9, 12]	11	[9, 18]	0.32
	Total artefact score	0.5	[0, 1]	1	[0, 3]	0.03
	Synthetic CT
	Total visibility score	29	[27, 30]	29	[28, 30]	0.74
	Total sharpness score	22	[18, 24]	22	[20, 24]	0.62
	Total artefact score	0	[0, 0]	0	[0, 0]	0.43
	CT
	Total visibility score	29	[27, 30]	29	[28, 30]	0.90
	Total sharpness score	22	[18, 24]	22	[18, 24]	0.35
	Total artefact score	1	[0, 1]	0.5	[0, 1]	0.83

Note

Legends: UTE-MRI=lung MRI with ultrashort echo times

Acknowledgement.

This study was conducted in the framework of the University of Bordeaux's IdEx "Investments for the Future" program RRI "IMPACT" which received financial support from the French government.

The authors would like to thank Mrs Rkia Achkir and Dr Solenn Toupin for their technical support.

Note: * for visibility scoring in the central lung, the scores were as follows: 0 = no depiction; 1 = depicted at segmental level; 2 = depicted at subsegmental level; 3 = depicted at subsubsegmental level; 4 = depicted beyond sub-subsegmental level. Then, the total sharpness score was calculated as the sum of central and peripheral scorings across the three upper, mid, and inferior lung levels (Supplemental Table E).

** for visibility scoring in the peripheral lung, the scores were as follows: 0 = not visible; 1 = visible. † for sharpness scorings in the central and peripheral lung, the scores were as follows: 0 = blurred; 1 = intermediate; 2 = sharp. ‡ for artefact scorings, the scores were as follows: 0 = no artifact; 1 = slight artefact without blurring of anatomical structures; 2 = moderate artefact with blurring of anatomical structures; 3 = severe artefact with no normal structure recognizable. When present, bronchiectasis and peribronchial thickening were assigned a severity score as follows:

Bronchiectasis severity: Absent (0), luminal diameter slightly greater than diameter of adjacent vessel (Mild (1)), luminal diameter 2-3× the adjacent vessel (Moderate (2)), liminal diameter > 3× the adjacent vessel (Severe (3)).

Peribronchial thickening severity: Absent (0), wall thickness equal to the diameter of adjacent vessel (Mild (1)), wall thickness 2× the adjacent vessel (Moderate (2)), wall thickness > 2× the adjacent vessel (Severe (3)).

The authors acknowledge that other versions of the Bhalla score have been proposed in the literature, out of the scope of this study. Note: data are absolute number of segments with or without a given structural alteration, according to the senior reader, with CT as reference.

Legends: UTE-MRI=lung MRI with ultrashort echo-times; CT=real computed tomography; TP=true positive depiction; TN=true negative depiction; FP=false positive depiction; FN=false negative depiction; WT=peribronchial wall thickening; BD=bronchial dilatation; MPc=central mucus plugging; MPp=peripheral mucus pluggning with a "tree-in-bud" appearance; Cons=collapse/consolidation; Emph=emphysema; Sacc=Sacculation/Abscess. Note: data are intraclass correlation coefficients with 95% confidence interval (CI). The range of the total visibility score, sharpness score and artefact score were (0 -30), (0 -24) and (0 -35), respectively.

ICC inter = intraclass correlation coefficient of inter-observer reproducibility; ICC intra = intraclass correlation coefficient of intra-observer reproducibility; UTE-MRI = lung MRI with ultrashort echo times.