Fabien Lotte
email: fabien.lotte@inria.fr

Camille Jeunet
email: camille.jeunet@inria.fr

Towards Improved BCI based on Human Learning Principles

Although EEG-based BCI are very promising for numerous applications, they mostly remain prototypes not used outside laboratories, due to their low reliability. Poor BCI performances are partly due to imperfect EEG signal processing algorithms but also to the user, who may not be able to produce reliable EEG patterns. This paper presents some of our current work that aims at addressing the latter, i.e., at guiding users to learn BCI control mastery. First, this paper identifies some theoretical (based on human learning psychology models) and practical limitations of current standard BCI training approaches and thus the need for alternative ones. To try to address these limitations, we conducted a study to explore what kind of users can use a BCI and why, and will present the main results. We also present new feedback types we designed to help users to learn BCI control skills more efficiently.

I. INTRODUCTION

ElectroEncephaloGraphy (EEG)-based Brain-Computer Interfaces (BCI) make computer control possible without any physical activity [START_REF] Wolpaw | Brain-computer interfaces: principles and practice[END_REF]. As such, they have promised to revolutionize many application areas, including assistive devices or human-computer interaction [START_REF] Wolpaw | Brain-computer interfaces: principles and practice[END_REF]. Despite this promising potential, such revolutions have not been delivered yet, and BCI are still barely used outside laboratories [START_REF] Wolpaw | Brain-computer interfaces: principles and practice[END_REF]. This is mainly due to the substantial lack of reliability of current BCI [START_REF] Wolpaw | Brain-computer interfaces: principles and practice[END_REF]. In particular, BCI often inaccurately recognize the users' mental commands [START_REF] Blankertz | Neurophysiological predictor of SMR-based BCI performance[END_REF] whereas roughly 20% of BCI users cannot control the system at all (the so-called BCI illiteracy/deficiency) [START_REF] Allison | Could anyone use a BCI?[END_REF].

To operate a BCI, the user has to produce EEG patterns, typically using mental imagery tasks 1 , which the machine has to recognize by using signal processing. So far, to address the reliability issue of BCI, most research efforts have been focused on EEG signal processing only [START_REF] Allison | Could anyone use a BCI?[END_REF]. Thus, the reliability issue of BCI is unlikely to be solved by focusing on signal processing alone. Indeed, BCI control is known to be a skill that needs to be learned and mastered by the user [START_REF] Wolpaw | Brain-computer interfaces: principles and practice[END_REF]. This means that 1) the BCI performances of a user become better with practice and thus that 2) the user needs to learn how to produce stable, clear and distinct brain activity patterns to successfully control a BCI. With poor user BCI control skills, even the best signal processing algorithms will fail to recognize the user's mental commands. Unfortunately, how to train users to BCI control has been rather scarcely studied so far. Thus, the best way to train users to master BCI control skills is still unknown [1][3].

This paper aims at convincing the reader that changing BCI design to enable their users to master BCI control skills is a very promising direction to improve BCI reliability. Indeed, this paper first identifies the theoretical and practical limitations of current standard BCI training protocols, which may explain, at least in part, the current high rate of BCI illiteracy/deficiency and their overall modest performance. It then presents our ongoing work towards improving these training protocols. It notably presents some results about what kind of users can use mental imagery-based BCI and why. It also introduces new feedback types and new training environments targeted at improving the user's understanding of BCI use as well as his/her motivation to learn the BCI skill.

II. THEORETICAL AND PRACTICAL LIMITATIONS OF CURRENT BCI TRAINING APPROACHES

BCI control being a skill, it has to be mastered by the BCI user [START_REF] Neuper | Brain-Computer Interfaces[END_REF]. Typically, standard BCI training is performed by asking the user to control an object on screen by modulating his/her brain activity in a specific way (e.g., using Motor Imagery (MI)). The feedback provided to the user about his/her task performance is thus generally a uni-modal (generally visual) feedback indicating the mental task recognized by the classifier together with the confidence in this recognition and is represented by an extending bar or a moving cursor [START_REF] Neuper | Brain-Computer Interfaces[END_REF]. The user is generally trained following a synchronous protocol, i.e., the user is required to do specific tasks (e.g., left hand MI) in specific time periods only. The same protocol is usually repeated until the user has learned the BCI skill, i.e., until he/she has achieved a given classification accuracy.

A. Theoretical limitations

Unfortunately, such standard training approaches satisfy very few of the guidelines provided by human learning and instructional design principles to ensure an efficient learning of a skill [START_REF] Lotte | Flaws in current human training protocols for spontaneous brain-computer interfaces: lessons learned from instructional design[END_REF]. For instance, a typical BCI training session provides only corrective feedback (indicating whether the learner performed the task correctly), using fixed and somewhat boring training tasks identically repeated until the user has learned the BCI skill, with these training tasks being provided in a synchronous way. In contrast, human learning and instructional design principles recommend to provide an explanatory feedback (indicating what was right or wrong about the task performed by the user) that is goal-oriented (i.e., indicating a gap between the current performance and the desired level of performance). The feedback could also benefit from multimodality and an engaging and challenging environment with adaptive difficulty [START_REF] Lotte | Flaws in current human training protocols for spontaneous brain-computer interfaces: lessons learned from instructional design[END_REF]. In short, current standard BCI training approaches are theoretically suboptimal, and are unlikely to enable efficient learning of the BCI skill.

Moreover, according to Keller [START_REF] Keller | An integrative theory of motivation, volition, and performance[END_REF], it is necessary to consider the user's motivational and cognitive state to ensure he/she can learn and perform efficiently, irrespectively of the task. Indeed, according to Keller's theory, optimizing motivational factors -Attention (triggering a person's curiosity), Relevance (the compliance with a person's motives or values), Confidence (the expectancy for success), and Satisfaction (by intrinsic and extrinsic rewards) -leads to more user efforts and thereby a better performance. Additionally, considering the cognitive factors -the limited user's working memory capacity (requiring to minimize the amount of skill-unrelated information), the way information is actively processed by him/her (requiring to make relevant information salient) and the existing knowledge in his/her long-term memory (requiring to relate the to-be-learned skill to existing knowledge) -leads to a more efficient skill acquisition. Again, these different factors are typically not considered in BCI training protocols, or only very few of them, leading to theoretically suboptimal training protocols [START_REF] Mühl | Which factors drive successful BCI skill learning?[END_REF].

B. Practical limitations

The limitations mentioned above are only theoretical limitations though and one may wonder whether they translate into actual practical limitations. Indeed, those standard training protocols still enabled many users to gain control of a BCI system. It would therefore be interesting to study what the impact of current BCI training protocols on BCI performance and illiteracy/deficiency is. Unfortunately, there are many reasons why a given user may not gain BCI control: poor EEG signal-to-noise ratio, non-stationarity of the signals or nonaccess to the relevant brain signals due to the way the cortical neurons of the user are oriented, among many others. As such, a failure to use the BCI may have many possible causes related to EEG signals but not to the training protocol. Therefore, to work around these issues, we proposed to study standard BCI training protocols without EEG signals, i.e., without a BCI [START_REF] Jeunet | How well can we learn with standard bci training approaches? a pilot study[END_REF]. In particular, we studied how people could learn to do two simple motor tasks using the same training tasks and feedback as those given to MI BCI users (see Figure 1). More precisely, we asked subjects to learn to draw on a graphic tablet a triangle and a circle (the correct size, angles and speed of drawing of these two shapes being unknown to the subject) that can be recognized by the system, using a synchronous training protocol and an extending bar as feedback, like for MI-based BCI training. Our results show that most subjects (out of N=20 subjects) improved with this feedback and practice (i.e., the shapes they draw are increasingly more accurately recognized by the system), but that 15% of them completely fail to learn how to draw the correct shapes, despite the simplicity of the motor tasks. This suggests that part of BCI illiteracy/deficiency is likely due to the training protocols currently used.

C. Alternative approaches

Fortunately, some groups have explored alternative BCI training protocols, which satisfy some of the guidelines about efficient human learning [START_REF] Lotte | Flaws in current human training protocols for spontaneous brain-computer interfaces: lessons learned from instructional design[END_REF]. For instance, [START_REF] Hwang | Neurofeedback-based motor imagery training for brain-computer interface (BCI)[END_REF] showed that a Fig. 1. A user learning to perform simple motor tasks, using a pen to draw on a graphic tablet, with the same feedback as used for MI BCI training.

richer feedback, based on a 2D topography of cortical activation could increase MI-based BCI performances. Using BCI with game-like feedback environments also led to increased BCI performances [START_REF] Lotte | Combining BCI with Virtual Reality: Towards new applications and improved BCI[END_REF]. Some studies showed that biased feedback (i.e., making the user believe he/she did better than what he/she actually did) or positive feedback only (i.e., only providing feedback when the task was performed correctly) can improve performances, at least for new or inexperienced BCI users [START_REF] Kübler | Braincomputer communication: self-regulation of slow cortical potentials for verbal communication[END_REF] [START_REF] Barbero-Jimenez | Biased feedback in braincomputer interfaces[END_REF]. Finally, some groups have also successfully explored progressive BCI training tasks [START_REF] Mcfarland | Electroencephalographic (EEG) control of three-dimensional movement[END_REF] [START_REF] Vidaurre | Towards a cure for BCI illiteracy[END_REF]. These works further confirm that improving BCI training protocols can improve BCI performance. Unfortunately, such alternative training protocols are typically not used by the BCI community and still satisfy only a small subset of the guidelines from human learning, and many recommendations are yet to be explored. In the following sections we present our ongoing work to design BCI training protocols satisfying such guidelines.

III. UNDERSTANDING WHO CAN USE CURRENT BCI AND

WHY

BCI deficiency and more generally the huge variability in users' ability to control a MI-BCI led to some studies looking for psychological [START_REF] Hammer | Psychological predictors of smr-bci performance[END_REF] and neurophysiological [START_REF] Blankertz | Neurophysiological predictor of SMR-based BCI performance[END_REF] predictors of MI-BCI performance. However, most of them are based on one-session (i.e., one day) experiments only, while several sessions are required to learn to master a BCI. Moreover, these studies only consider MI while other mental imagery tasks have been shown to be more efficient [START_REF] Friedrich | Whatever works: A systematic user-centered training protocol to optimize brain-computer interfacing individually[END_REF]. Thus, in order to address these limitations, we looked for predictors based on data collected over 6 sessions (i.e., over 6 days) during which participants had to learn to perform 3 mental imagery tasks: mental rotation, left-hand motor imagery and mental subtraction [START_REF] Friedrich | Whatever works: A systematic user-centered training protocol to optimize brain-computer interfacing individually[END_REF]. Our results (N=18) show that 1) performances are strongly correlated with users' spatial abilities and 2) we can reliably predict these performances using a model including different psychological factors (like abstractedness, self-reliance or tension). These results are very encouraging as they could lead to reflexions about 1) exercises to improve users' spatial abilities and 2) solutions to take into account users' cognitive and personality profiles in BCI training approaches [START_REF] Jeunet | Determining personality and cognitive profiles to predict mental imagerybased bci performance[END_REF].

IV. NEW FEEDBACK AND EEG VISUALIZATION TOOLS

As mentioned above, to ensure an efficient learning, the provided feedback should be explanatory, engaging and take benefit from multimodality [START_REF] Lotte | Flaws in current human training protocols for spontaneous brain-computer interfaces: lessons learned from instructional design[END_REF]. This section reports on the design and evaluation of such kinds of BCI feedback.

A. Multi-user feedback

Making a learning task more engaging and motivating can be achieved by challenging the learner [START_REF] Lotte | Flaws in current human training protocols for spontaneous brain-computer interfaces: lessons learned from instructional design[END_REF], and setting the learning task in a social context [START_REF] Zajonc | Social facilitation[END_REF]. We therefore explored MI-based BCI training in a multi-user context, with multi-user feedback [START_REF] Bonnet | Two brains, one game: Design and evaluation of a multi-user BCI video game based on motor imagery[END_REF]. We proposed a BCI game in which users had to push a ball towards a targeted goal located on the left or right of the screen, by imagining left or right hand movements respectively. Users could play the game with another BCI user, the ball moving according to the sum of the BCI outputs from the two users. Users were provided with their own feedback (the classifier output for their EEG signals) as well as the combined output, i.e., the sum of classifier outputs from both users. The game could be in a collaborative version, the two users having to push the ball in the same direction, or in a competitive version, the two users having to push the ball in opposite directions (see Figure 2). In an evaluation study in which we compared a single player version of the game, to the multiplayer collaborative version of it, we observed that the multiplayer version could improve BCI performances for a specific category of users. In particular, for each pair of users, the user who was the best at BCI had significantly increased classification performances as compared to the single player version of the game, while the classification accuracy for the other user did not change. This suggests that such a multiuser feedback and environment could increase BCI reliability for some users.

B. Multimodality

As mentioned above, most training protocols involve visual feedback. Yet, both theoretical [START_REF] Lotte | Flaws in current human training protocols for spontaneous brain-computer interfaces: lessons learned from instructional design[END_REF] and practical [START_REF] Leeb | Freeing the visual channel by exploiting vibrotactile bci feedback[END_REF] evidences argue for the use of other sensori-modalities that could be more adapted to BCI-based applications. Among these modalities, the tactile channel seems to be a good candidate as it is often not overtaxed in interaction contexts, contrary to the visual and auditory ones. Furthermore, increasing motivation, for instance by creating more appealing training environments, has also been shown to be efficient to increase users' performances [START_REF] Lotte | Flaws in current human training protocols for spontaneous brain-computer interfaces: lessons learned from instructional design[END_REF]. However, the combination of these two parameters (tactile feedback and appealing environments) had never been tested in a BCI training protocol. Thus, our study [START_REF] Jeunet | Tactile feedback for motor-imagery based bci[END_REF] aimed at comparing a standard visual feedback with an equivalent tactile feedback in an appealing training environment containing visual distractors (to mimic an interaction context in which the visual channel is overtaxed). Users had to learn to perform motor-imagery tasks as well as a counting task, and received either a visual or vibrotactile feedback (see Figure 3). Our main result (N=18) is the fact that people receiving tactile feedback perform significantly better (in MI and counting task). Such results should encourage the BCI community to replace standard BCI protocols by more motivating training environment and multimodal feedback, as visual feedback may not be adapted to visual interaction applications.

C. Explanatory feedback

Another desired property of a good training feedback, is to be explanatory. In other words, the feedback should provide enough information so that the user can understand what mental imagery strategies lead to correctly recognized mental commands, and why. With this objective in mind, we designed two new real-time brain activity visualization tools, the Mind-Mirror and Teegi (see Figure 4), that can be used as explanatory BCI feedback. 1) Mind-Mirror: The Mind-Mirror enables its users to visualize their own brain activity in real-time, in their own head [START_REF] Mercier-Ganady | The mind-mirror: See your brain in action in your head using eeg and augmented reality[END_REF]. It uses augmented reality and head-tracking to overlay a representation of an active brain on top of the user's head, seen in a semi-reflective screen (see Figure 4, left). This gives the illusion that the user can see his/her own brain in his head, in a mirror, in activity, the EEG power from different channels being represented in real-time on the surface of the brain. The Mind-Mirror was tested as a feedback to train users to control an attention-based BCI in which the user had to perform concentration or relaxation tasks to control two different commands. The Mind-Mirror was compared to a classical gauge feedback for the same task. Results showed that users found the Mind-Mirror to be indeed an engaging and innovative visualization tool. In terms of performance however, it was not better than the classical gauge feedback. This suggests that selecting and visually enhancing the relevant information is probably necessary to ease the user perception and understanding of his/her own brain activity.

2) Teegi: Teegi is a tangible EEG interface, designed to enable users that are naive with EEG to get to know more about how EEG works, in an accessible and engaging way [START_REF] Frey | Teegi: tangible eeg interface[END_REF]. As with the Mind-Mirror, Teegi enables users to visualize their own brain activity in real-time (See Figure 4, right). Contrary to the former, Teegi is based on educational design principles to ease the user understanding of brain activity. In particular, it is based on a tangible system, the user's brain activity being projected on the head of a puppet (with a friendly and humanoid appearance), that can be easily manipulated, to favor exploration. EEG signals can also be filtered to reveal some specific EEG phenomenons (e.g., sensorimotor rhythms), hence enhancing the relevant EEG signals. Teegi was so far explored only for scientific outreach and education, to help users to know more about the brain and EEG -with success. In the future, we plan to use it as an explanatory BCI feedback.

V. CONCLUSION

In this paper we argued that, in order to bring BCI reliability to the next level, it is necessary to study further how users can learn to gain BCI control. We notably showed that current standard BCI training approaches have many limitations, both theoretical, since they do not satisfy guidelines from human learning theories, and practical, since they may fail to teach people simple motor tasks. To better identify how to improve BCI training protocols, we tried to design a model relating the personality and cognitive profile of the user to his/her mental imagery BCI performances, obtained with standard protocols. We notably showed that BCI performances are correlated to the user's abstractedness, self-reliance, tension and ability in mental rotation, thus providing us with specific insights about what to improve and how. To ensure that BCI training protocols are more in line with guidelines from human learning theories, we also proposed new feedback types. We notably showed that both multi-user feedback and multimodality (exploiting vibrotactile feedback) can improve BCI performances. We are also exploring new ways to display EEG activity to BCI users, to help them understand their EEG patterns, for which we proposed the Mind-Mirror and Teegi augmented reality-based visualization tools.

In the longer term, it would be necessary to build a comprehensive training framework to teach anyone to gain BCI control. An interesting approach to do so would be to design an Intelligent Tutoring System (ITS) [START_REF] Nkambou | Advances in intelligent tutoring systems[END_REF]. Indeed, such systems would allow to determine each user's profile, and then propose a training protocol adapted to this profile. Moreover, it could be improved by adapting in real time the training protocol to the emotional, motivational and cognitive states of the user in order to optimize the learning phase (i.e. make it more pleasant, more efficient and faster). We hope the BCI community will join these research efforts, in order to reach much more reliable BCI systems, and thus broaden the application areas for these technologies.

Fig. 2 .

 2 Fig. 2. Two users competing in a Motor Imagery-based BCI game.

Fig. 3 .

 3 Fig. 3. Illustration of the combination of an appealing training environment and a vibrotactile feedback provided on the palm of the hand using an array of vibrators (right, compared to a standard visual feedback, left)

Fig. 4 .

 4 Fig. 4. Left: the Mind Mirror, Right: Teegi, two new real-time visualization tools of the user's own brain activity, based on augmented reality.

Note that BCI based on Event Related Potentials are not considered in this paper as they involve very little or no human training[START_REF] Wolpaw | Brain-computer interfaces: principles and practice[END_REF]


Cyril Szopa

Michel Cabane

Patrice Coll

David Coscia

Arnaud Buch

Samuel Teinturier

Rafael Navarro-Gonzalez

Jean-Pierre Goutail

Christophe Montaron

Jean-Baptiste Rigal

Gas-Chromatographic analysis of Mars soil samples with the SAM instrument onboard Curiosity -the 180 first sols

come   L'archive ouverte pluridisciplinaire

Gas-Chromatographic analysis of Mars soil samples with the SAM instrument onboard Curiosity -the 180 first sols C. Szopa (1), M. Cabane (1), P. Coll (2), D. Coscia (1), A. Buch (3), S. Teinturier (2), R. Navarro-Gonzalez (4), J-P. Goutail (1), C. Montaron (1), J-B. Rigal (1), J-J. Correia (1), V. Guerrini (1), P. Poinsignon (1), M-S. Clerc (1), M. Meftah (1), L. Soldani (2), F. Mettetal (2), M. Jerôme (2), C. Philippon (2), A. Galic (5), J. Sablairolles (6), S. Triqueneaux (7), D. Chazot (7), B. Toffolo (8), F.Y. Rakoto (8), A. Gaboriaud (9), P. Mahaffy (10)

Abstract

Amongst the SAM suite of instruments [1], SAM-GC (Gas Chromatograph) is devoted to identify and quantify volatiles evolved from the thermal/chemical treatment of any soil sample collected by the Curiosity rover. The first soil samples analyzed with SAM were composed of sand collected at the Rocknest site, when the second site analyzed was a basin called "Yellowkive Bay". For their analysis, these samples were submitted to a pyrolysis at temperatures reaching about 900°C. For SAM-GC and GCMS analyses, different fractions of pyrolysates were collected at different temperature in the ambient-900°C range in order to discriminate potential different volatile fractions present in the solid sample.

With the aim to search for potential organic molecules outgassed from the samples, a SAM-GC analytical channel composed of thermal-desorption injector and a MXT-CLP chromatographic column was used as it was designed for the separation of a wide range of volatile organic molecules. This channel is also equipped with a thermal conductivity detector (TCD) capable to detect the most abundant species (with abundances down to approximately 10-10 mol). It is thus complementary to the mass spectrometer detection for quantification of such species as this last instrument has not a linear response in this domain of high abundance, whereas it is significantly more sensitive than the TCD.

The results obtained with this instrument first show that the performances of SAM-GC are representative of those obtained during calibrations of the instrument in laboratory, as well as they are repeatable. Hence, the instrument performs nominally, making it the first GCMS running successfully on Mars since the Viking missions. Moreover, the complementarity of GC towards MS is also shown, either by allowing the quantification of the major species detected (as water), or by providing a chromatographic signal well resolved temporally which can be used to improve the QMS signal treatment.

In the frame of research of organics, the SAM-GC analyses contribute to the identification of several methyl-chlorohydrocarbons, and of HCN in the gases evolved from the solid sample. These detections strongly support the presence of perchlorates in the Rocknest soil. Since perchlorates have been detected with Phoenix lander [2] and then recently with Curiosity, the re-interpretation of the Viking data have to be seen under a new angle [3]. The nondetection of PAHs is also interesting to notice, when it is known that micrometeorites containing PAHs still bring this organic material to the Mars surface today. This lack of detection defines an upper limit on the content of PAHs in the martian soil at the sites studied by Curiosity, but it could also be indicative of the presence of chemical mechanisms that process this type of material at the surface.

Fig 1 .

 1 Fig 1. Curiosity at Rocknest Sandpile, in front of sampling sites.

  and the MSL Science team cyril.szopa@latmos.ipsl.fr (1) LATMOS, Univ. Pierre et Marie Curie, Univ. Versailles Saint-Quentin & CNRS, 75005 Paris, France, (2) LISA, Univ. Air Liquide Advanced Technologies, 38360 Sassenage, France. (8) ATERMES, 78180 Montigny-le-Bretonneux, France. (9) CNES, 31000 Toulouse, France. (10) NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA.

	Paris-Est Créteil, Univ. Denis Diderot & CNRS 94010 Créteil, France (3) Ecole Centrale Paris, 92295 Chatenay-Malabry,
	France. (4) Universidad Nacional Autónoma de México, México, D.F. 04510, Mexico (5) Bureau Veritas then BTP, France.
	(6) COMAT, 31000 Toulouse France. (7)

Acknowledgements SAM-GC team acknowledges support from the French Space Agency (CNES), French National Programme of Planetology (PNP), National French Council (CNRS), Pierre Simon Laplace Institute, Institut Universitaire de France (IUF) and ESEP Labex


Reading Today Clivaz

Jérôme Meizoz

François Vallotton

éd Joseph Verheyden

Lire

The editors, together with the publisher (Presses polytechniques et universitaires romandes), attempted to innovate in the way they published the book. Three elements are available: a printed book, an extended ebook version and videos of the interventions that are still available both on the Lausanne University's website and on iTunes U. The articulation between written and oral versions of some papers allows the reader to have several ways of reading and listening to the book, in accordance with its subject (this review focuses on the extended ebook version). However it is regrettable that the extended ebook sometimes lacks a bit of cohesion and coherence. The third to fifth parts are notably poorly articulated, mixing chronology and themes -where a clear choice for a thematic organization would have been more understandable.

The colloquium, as said in the introduction written by the book's editors (Claire Clivaz, François Vallotton and Joseph Verheyden), was organized (and the book written) in a triple context: the current technological revolution and the changes that come with it; the rise of the Digital Humanities including the creation of dedicated centers mainly in Anglo-Saxon countries; the integration of digital resources and platforms within universities for both their teaching and research activities.

The book is divided into six parts (Reading and literacies: history and representations / From Ancient Manuscripts to the Digital Edition / Antiquity, Literacies and Digital Culture / Early Christianity, Literacies and Digital Culture / Written Culture and Digital Technologies in Modern History and Literature / Tools and Concepts in Digital Culture). What those six titles suggest, is confirmed by Claire Clivaz's first chapter about a Common Era 2.0 -which is to be considered as the book's matrix. It defines the two great and interesting aspects of this publication: how the digital age questions the previous era (the Common Era) in modifying some of its textual traditions, considered previously as fixed and irrevocable; how the digital era helps us rediscover reading and writing modes of Antiquity.

The first part is centered on the book or its various forms (the novel), its evolution in the digital era and the act of reading books. Christian Vandendorpe addresses the consequences of the migration of reading from print to screen on the future of the novel as a literary genre, answering for instance some criticism by Nicholas Carr of fragmented reading. He describes how, in the past, the novel adapted to various challenges. Confronting the novel with the incessant digital flow, Vanderdorpe suggests that the novel should find an appropriate digital platform that integrates multimedia documents and the web 2.0 participatory and collaborative dimensions. This should give a new and active role to the reader. Frédéric Kaplan's chapter on the evolution of the book (How Books will Become Machines) is based on the use of the theory of evolution for technological systems. Analyzing how technologies such as encyclopedias and books can evolve towards mechanization, he observes that books are resisting this evolution (contrary to encyclopedias), but could survive only if they become "closed" applications and concludes on the fact that our cognitive skills can be shaped differently depending on how the book evolves. The question, here, is how to experiment to find new applications for complex discourses.

Philippe Kaenel questions the dialogue between text and pictures since Antiquity, the role of visual culture and the notion of "literacy". David Bouvier reminds us that Christianity transformed the book into an idealized object, while we are also the heirs of Plato's views on text, at a time (Ancient Greece) where there was no reason to believe in the book's ideal. Holt Parker explains What is it that Philologists Do Exactly? -reminding us that philologists question how the authors expect readers to read the work.

Jean-Yves Mollier's chapter on Lire, une pratique constamment remise en cause is an excellent conclusion to the first part. Answering the frequent criticisms about the end of the paper and the "book's civilization" because of the appearance of screens, Mollier argues that the act of reading, reserved before to clerics, has always been contested and, especially the access of masses to reading. Analyzing the role of reading online, including during the 2011 Arab Spring, he concludes that literature is the only part of reading that is endangered. In fact, the many forms of reading today, will probably lead to the rise of new and creative forms of fiction.

The second part of the book is dedicated to the notion of edition, from ancient manuscripts to the digital edition. Based on his experience, François Bovon explains the different steps from catalogue research to the establishment of a critical edition and notes that Ancient Manuscripts are entering into their third age -which is also the digital age: an age of digitization and preservation, that facilitates access to them. Taking the example of the Qumran manuscripts, David Hamidović (both in French and English) shows one of the possibilities opened by the digital age for the study of ancient texts. Through the use of graphic software, he wishes to complete some lost parts of those texts and to study the ways scribes were writing. Exploring new possibilities for ancient texts is also fundamental in Mary Ebbott's and Leonard Muellner's chapters about Homeric epics: the fluidity and multidimensional quality of digital documents and tools are in fact, very well suited to the Iliad's edition. This potential of digital tools will radically change the way we do research, argues Ulrich Schmid, based on the experience of the edition of the New Testament, where the reader becomes a producer of the edition. The last two chapters of this part investigate the bridges between Christian and Arabic documents, showing some possible investigations into post-colonial studies opened by Digital Humanities, and, also, the limits of our Latincentered digital tools. This investigation emphasizes too, the question of the scholar's place in our world. The book's third part -Antiquity, Literacies and Digital Culture -is more centered on research practices in the digital age and on the (non-Christian) Antiquity, though it partly harmonizes with the second one. Thomas J. Kraus investigates how digital practices help find new research subjects. Mathild Cambron-Goulet shows how Greek philosophers were at the same time criticizing writing and practicing a reading in community, linked to their oral tradition. MarieClaire Beaulieu, Francesco Mambrini & J. Matthew Harrington -Toward a Digital Editio Princeps: Using Digital Technologies to Create a More Complete Scholarly Edition in the Classics -allow us to see what tomorrow's book will be: multimodal, interactive, multidimensional, multimedia. Some of their questions on the future of books are linked to Frédéric Kaplan's considerations. Alexandra Trachsel -Collecting Fragments Today: What Status Will a Fragment Have in the Era of Digital Philology? -considers three steps in the ways fragments were transmitted to us: creation of libraries, the Renaissance and, today, the digital era. Floris Bernard -Byzantine Books Epigrams: From Manuscripts to a Digital Database -shows how a text can be transformed into a database and why -in this case to understand a whole historical moment and its practices.

The fourth part is about ancient Christianity and its specificity: the hybridity of oral and writing traditions. The fifth part -Writing Culture and Digital Technologies in Modern History and Literature -is focused on a more recent period. Sandrine Baume investigates the notion of transparency and its detractors -an interesting thought for our times of fear of a generalized transparency of our private lives. In studying writing and reading practices in modern religious orders, Fabienne Henryot gives us an interesting historical insight about how writing is a way to impose an orthodoxy / social order and a common tradition. Luis Pablo Núñez's chapter -The Impact of the Digital Era on Dictionaries and Encyclopedias -brings us back to the digital era and its advantages when it comes to a digital edition of dictionaries and encyclopedias, with the possibilities of mixing several editions and many ways of reading them. Here, again, he goes back to some of Kaplan's considerations. The following chapter about ARQUIBANC (Elena Cantarell Barella) is, in a way, a more traditional digital humanities paper. It is still a very notable contribution, as it is centered on the preservation of very hard to preserve archivespersonal ones. Eliza Deac -From Paper to Web Constellations: Between Stéphane Mallarmé's Un coup de Dés and Stephanie Strickland's V: Vniverse -explains the many mutations of poetry along the technological evolutions. She points out the usage of the specificities of each medium by poets. Nelleke Moser -Collecting Quotes, Connecting People: Towards a Diachronic Approach to Appropriating and Sharing Literature -interrogates the usefulness of sharing and annotating texts and text fragments. This part, although made up of very interesting chapters, is probably the most incoherent in the book, unfortunately.

The sixth part -Tools and Concepts in Digital Culture -is more typically DH-oriented, with presentations of tools, such as the chapters on The Project of a "Thesaurus Linguae Arabicae": linguistic and computational issues (Cristina Solimando & Giuliano Lancioni) or Alberto Roncaccia & Davide Picca's piece on Interrogation Programme & SuperSenses Extraction : IPSE, une base de données ouvertes et flexible. Lukas Rosenthaler's focus on VRE -Virtual Research Environments: A New Approach for Dealing with Digitized Sources in Research in Arts and Humanities -is an interesting one, based on the JISC definition: SALSAH, the VRE described here, was conceptualized as an answer to the lack of tools to handle and analyse the consequent masses of digitized archives. Tobias Schweizer -Development of a Topographical Transcription Method -shows a practical use of the SALSAH framework. Thomas Naef -New Testament Textual Criticism Bibliographical Data -focuses on the BiBil (Biblical Bibliography of Lausanne) and the New Testament Textual Criticism (NTTC) projects. Christelle Cocco -Catégorisation automatique de propositions textuelles en types de discours -presents a statistical method rather than a tool, in the field of speech analysis. She is linking morphosyntaxic categories with types of speech and texts annotated by experts -though those links are yet hard to interpret. Solange Ghernaouti-Hélie & René Berger -Techno sacré, cyberespace et protéisme numérique: répondre autrement aux interrogations profondes de l'humain -sketch what could be a philosophy of the digital age. This chapter could have been included in the first part. They question our capacity to handle computing and the Internet in order to get out of a sheer economic view of the digital age. They acknowledge the possibility of a happy merging between Humanity and machines, reminding us but being distinct (because more poetic) from transhumanism. This chapter, and the book that inspired it (René Berger et Solange Ghernaouti-Hélié, Technocivilisation: pour une philosophie du numérique, Presses polytechniques et universitaires romandes, Lausanne, 2010), could be read in parallel to Milad Doueihi's Pour un humanisme numérique (Paris: publie.net, 2012). The last chapter of the book (Fabien Nobilio -Le livre cosmique. Des Confessions de saint Augustin au culte de l'Internet), which sounds a bit like a conclusion, draws a parallel between saint Augustin's way of considering silent reading, focused on self-consciousness, and today's need for transparency, a need which is very much linked to the Internet. In linking literacy (the use of a tool) and the symbolic dimension of the tool (whether the book or the Internet), Nobilio questions our capacity to use our knowledge as a path to freedom. In the end, Nobilio's question on whether the Internet will be an incarnation of a celestial book or the opposite is a very pertinent one -are we not at a crossroads between the network as a spy on our whole lives or as a way to achieve a better Humanity?

For the readers who will read this book in its entirety -and particularly for the historian who wrote this review -there is one regret: two parts of our history appear as more or less dark ages. The XIXth century appears in this book -and notably in Clivaz's Common Era 2.0 -as an evil period of normalization of the book and reading practices. The Middle Ages -though sometimes lightly coveredappear, by their almost complete absence also as a Dark Age. But they are not. As we are in the Digital humanities field, let us considerFranco Moretti: what motivated Moretti to theorize distant reading is the focus of the literary studies on "big novels" in the XVIIIth and the XIXth centuries. What Moretti says is, in fact, that those centuries -their literature -is not that well known. And this literature is probably more liquid, more mobile, less normalized that we think it is. Even for very well-known authors like Balzac, the articulation between novels published in newspapers in installments and the later publication of the novel as a book is not as fixed as the image of the XIXth century depicted in Lire demain.

This book is very rich and everybody interested or researching about reading in the digital age should read it. Everyone in the field of Digital Humanities has potential interest in it. In the end, I have a single question: why "Reading Tomorrow"? Is this book not about "Reading today"?

  Giovanni B. Bazzana investigates how a text is socially produced, through examples from the apocalyptic genre. Joseph Verheyden -Read, Write and Correct: The Scribe and the Perfect Textdiscusses the mythical status of the Codex Sinaiticus. Simon Butticaz reminds us that the letters of Paul are the result of a society based on the oral tradition and illiteracy. Corinne Egasse -Le papyrus Oxyrhynque 840 et Jean 13: du manuscrit mutilé à l'eau purifianteinvestigates a specific text very closely. Benjamin Bertho -Tradition orale et culture écrite: les Oracles sibyllins chez Théophile d'Antioche et dans la littérature chrétienne -is an example of hybridity between orality and writing.


Lyès Mellal

Karim Belharet

David Folio

Antoine Ferreira
email: antoine.ferreira@ensi-bourges.fr

Optimal Structure of Particles-based Superparamagnetic Microrobots Application to MRI guided Targeted Drug Therapy

Keywords: Targeted drug delivery, Magnetic steering, Superparamagnetic microrobot, Optimal design SPIO particles 30µm

This paper presents an optimal design strategy for therapeutic magnetic micro carriers (TMMC) guided in real time by a magnetic resonance imaging (MRI) system. As aggregates of TMMCs must be formed to carry the most amount of drug and magnetic actuation capability, different clustering agglomerations could be arranged. Nevertheless, its difficult to predict the hydrodynamic behavior of any arbitrary-shaped object due to the nonlinear hydrodynamic effects. Indeed, the drag effect is related not only to the properties of the bolus but also to its interaction with the fluid viscosity, the freestream velocity and the container geometry. In this work, we propose a mathematical framework to optimize the TMMC aggregates to improve the steering efficiency in experimental endovascular conditions. The proposed analysis is carried out on various sizes and geometries of microcarrier: spherical, ellipsoid-like and chain-like of microsphere structures. We analyze the magnetophoretic behavior of such designs to exhibit the optimal configuration. Based on the optimal design of the boluses, experimental investigations were carried out in mm-sized fluidic artery phantoms to demonstrate the steerability of the magnetic bolus using a proof-of-concept setup. The experiments demonstrate the steerability of the magnetic bolus under different velocity, shear-stress and trajectory constraints with a laminar viscous fluidic environment. Preliminary experiments with a MRI system confirms the feasibility of the steering of these TMMCs in hepatic artery microchannel phantom.

Introduction

Microrobots for targeted therapy by navigating in the cardiovascular system are a prolific research area for novel minimally invasive surgery procedures (Nelson et al 2010). Among proposed approaches, magnetic targeting is one of the most advanced methods that attempts to concentrate navigable micro [START_REF] Fusco | An integrated microrobotic platform for on-demand, targeted therapeutic interventions[END_REF] to nano-entities, such as therapeutic magnetic microcarriers (TMMC) in a targeted site by applying external magnetic fields (Pouponneau et al 2011(Pouponneau et al , 2014)). The magnetic targeting of deep tissues is highly challenging and is not used in clinical practice [START_REF] Alexiou | Cancer therapy with drug loaded magnetic nanoparticles-magnetic drug targeting[END_REF]. A new approach based on upgrading a typical clinical magnetic resonant imaging (MRI) scanner with adequate steering coils, referred as magnetic resonance navigation (MRN), has been proposed to guide TMMCs in deep tissues and keep the systemic carrier distribution under control (Pouponneau et al 2014). In order to benefit both from a large motive force in the macrovasculature and from a possible break-up in the microvasculature (to avoid undesired thrombosis and to improve the targeting), a promising approach is to consider aggregates. Such aggregates of TMMC are binded either by a biodegradable ligand (Morgan et al 2011;[START_REF] Korin | Shear-activated nanotherapeutics for drug targeting to obstructed[END_REF] or by self-assembly properties (Vartholomeos and Mavroidis 2012). Already, polymer particles embedding doxorubicin as a therapeutic agent were successfully synthesized and steered in a rabbit liver using a 400 mT/m unidirectional gradient coil (Pouponneau et al 2011). However, usually several milliliters of TMMCs need to be injected in order to reach the required therapeutic drug dose. Therefore, navigation of such agents requires the injection of consecutive boluses (also referred as magnetic microrobot throughout the text) that will be serially steered from the injection site to the target location before to break-up into nanometer constituents, as shown in Fig. 1. Reliable navigation of such agents leads to know precisely the number, size, shape and steering properties of the boluses to be injected with respect to the release location, the targeted site and accessibility.

Bolus break-up

Fig. 1 Schematic representation of the magnetic resonance navigation of boluses in the cardiovascular networks. The magnetic microrobots are released from a catheter in the arterial networks. By correctly applying magnetic gradients ∇b, the injected boluses follow a pre-planned path and navigate only toward the disease site (tumor, stenosis, etc.) preserving healthy tissues The image zoom illustrates a cross section of the self-assembled magnetic bolus loaded with drug and SPIO particles.

For this purpose, different designs of magnetic microrobots have been proposed in the literature (Nelson et al 2010). First, biologically inspired magnetic microswimmers using helical propulsion (Zhang et al 2010) or beating flagella [START_REF] Dreyfus | Microscopic artificial swimmers[END_REF][START_REF] Evans | Propulsion by passive filaments and active flagella near boundaries[END_REF] have been designed. However, it has been shown that such propulsion schemes are mainly efficient in arterioles or capillaries where the Reynolds number (R e ) remains small [START_REF] Arcese | Endovascular magnetically guided robots: Navigation modeling and optimization[END_REF]. Another magnetic actuation, referred as bead pulling, has demonstrated its efficiency experimentally in the carotid artery of a living pig (Martel et al 2007) and rabbit liver (Pouponneau et al 2011).

Especially, this study aims to investigate the design of magnetic microrobots that are intended to be released from a catheter in the arterial system. The bolus is formed by aggregation of TMMCs that comprise superparamagnetic iron oxide (SPIO) particles and drug, as illustrated in Fig. 1.. The MRI uniform magnetic field (e.g. b 0 ≥ 1.5 T) ensures the saturation magnetization (m sat ) of SPIO materials (Pouponneau et al 2011). A relatively large aggregation could form clots in the small arteries or conversely, a very small one would be dragged away by the systemic circulation. Thus, the aggregation size and shape of the bolus is the main key factor for successful and efficient propulsion within the arteries. In the literature, spherical geometries has been mainly considered as magnetic microcarriers. As aggregates of TMMCs must be formed to carry the most amount of drug and magnetic actuation capability, different clustering agglomerations could be arranged. Nevertheless, its difficult to predict the hydrodynamic behavior of any arbitrary-shaped object. Indeed, the drag effect is related not only to the properties of the bolus but also to its interaction with the fluid viscosity, the free-stream velocity, and the container geometry. Therefore, in this work, spherical, ellipsoid-like and chain-like of microsphere structures are mainly considered. We analyze the magnetophoretic behavior of such designs to exhibit the optimal configuration. Based on the optimal design of the bolus, experimental investigations are carried out in mm-sized fluidic artery phantoms to demonstrate the steerability of the magnetic bolus using a proof-of-concept setup. Secondly, preliminary MRN experiments using a clinical MRI scanner validate the feasibility of the proposed approach. The experimental results show the possibility to perform magnetic aggregation and mechanical break-up of boluses constituted of hundreds of SPIO particles of radius r p = 4.5 µm.

Backgrounds

The use of therapeutic magnetic microrobots for targeted drug delivery aims to release high, localized concentrations of drug to specific sites through the selective application of a magnetic field. In particular, magnetic resonant navigation (MRN)-based microrobotic systems are considered here, since they require mainly a software upgrade of common magnetic resonant imaging (MRI) scanners. Moreover, to achieve efficient magnetic targeting, the microrobot has to navigate through the vascular network facing different values of vessel diameters, blood flow velocities, Reynolds numbers, among others. Classically, the dynamic model of a magnetic microrobot within the vasculature could be expresses as:

mv = f m + f Vasc (1) J ω = t m + t Vasc (2)
where v and ω are the linear and angular velocities of the microrobot; m its mass ; J is the momentum of inertia; f m and t m are the controlled magnetic force and torque; f Vasc and t Vasc denote the external vascular forces and torques interactions, and take into account the dominant particle forces and particle-fluid coupling. Different cardiovascular dynamic behaviors could be considered in the above model, such as the hydrodynamic viscous drag, inertia, electrostatic, van der Waals, or contact forces (expressions of these forces are described in [START_REF] Arcese | Endovascular magnetically guided robots: Navigation modeling and optimization[END_REF]). Especially, when the microrobot navigates close to the vessel centerline, it has been shown that the most dominant cardiovascular force is the hydrodynamic drag force f d induced by the blood flow [START_REF] Arcese | Endovascular magnetically guided robots: Navigation modeling and optimization[END_REF][START_REF] Belharet | Simulation and planning of a magnetically actuated microrobot navigating in the arteries[END_REF].

Magnetic Actuation

The basic principle of magnetic actuation is to manipulate a magnetic field b to induce a magnetic force (f m ) and torque (t m ) on the magnetized material:

f m = V m (m • ∇)b (3) t m = V m (m × b) (4)
with V m the volume of the magnetic material; m = (m x , m y , m z ) T the microrobot's magnetization; b = (b x , b y , b z ) T the magnetic field and ∇ the gradient operator. When using ferromagnetic or superparamagnetic material, the magnetic moment m tends to be aligned along the external applied magnetic field b 0 . Therefore, to actuate a magnetic microrobot, the magnetic field has to change spatially (e.g. thanks to a gradient field) or temporally, such as using rotating or oscillating field. Based on this consideration, different magnetic actuation schemes could be considered to manipulate the microrobot such as helical propulsion (Zhang et al 2010), beating flagella [START_REF] Dreyfus | Microscopic artificial swimmers[END_REF][START_REF] Evans | Propulsion by passive filaments and active flagella near boundaries[END_REF], or bead pulling [START_REF] Floyd | Two-dimensional contact and noncontact micromanipulation in liquid using an untethered mobile magnetic microrobot[END_REF]. Usually, the magnetic microrobot has to be released from the catheter within the arteries (e.g., about 10 to 0.5 mm of radii). From such vessel size, [START_REF] Arcese | Endovascular magnetically guided robots: Navigation modeling and optimization[END_REF] have demonstrated that bead pulling is the optimal actuation scheme. Actually, the other propulsion schemes, especially helical swimmers, provide sufficient actuation capabilities only from the arterioles size (i.e., below ∼ 50 µm). Considering bead pulling within an MRI device, the strong uniform magnetic field (b 0 = 3 T) tends to align the magnetization moment m with b 0 . Thus, the orientation of the microrobot is maintained due to the magnetic torque t m .

Hydrodynamic Drag Force

Classically, the hydrodynamic behavior of a magnetic microrobot are modeled using the Navier-Stokes equation. Assuming that the blood flow is incompressible, the drag force (f d ) and torque (t d ) on an arbitrary particle is expressed in the general case as follows [START_REF] Happel | Low Reynolds Number Hydrodynamics: With Special Applications to Particulate Media, 3rd edn. Mechanics of Fluids and Transport Processes[END_REF]:

f d t d = - A B B T C v ω , (5)
with v the linear velocity, and ω the angular velocity of the microrobot with respect to the fluid flow. The resistance matrix defined by A, B and C, is a symmetric matrix function of the properties of the flow and of the microrobot. In particular, these parameters have some symmetric properties related to the microrobot geometry. For instance, if the body shape has three orthogonal symmetric planes (such as spheroid, cuboid, or chain-like structures), we get B = 0. In addition, as the orientation of the microrobot within a MRI scanner is fixed due to the uniform field b 0 , there are no rotational motion and ω = 0. Thus the hydrodynamic behavior induces mainly a drag force that could be approximated by:

f d = - 1 2 ρ f A C d • v v (6)
where ρ f is the fluid density; A is the microrobot hydrodynamic reference area; v is the motion of the microrobot relative to the fluid flow; and C d is the dimensionless drag coefficient which is classically related to the Reynolds number R e (White and Corfield 1991), which is defined by:

R e = aρ f v η f (7)
with η f the fluid viscosity, and a the characteristic length of the microrobot.

Hydrodynamic Behavior of Spherical Microrobot

First, the hydrodynamic behavior of spherical particles has been deeply validated by many numerical and experimental studies on the drag force (Maccoll 1928;[START_REF] Davies | The aerodynamics of golf balls[END_REF]. For instance, for low Reynolds number (that is R e 1), we get:

C d,Stoke = 24 R e , (8)
which leads to the well-known Stokes' drag force in a creeping flow. Thus, for a spherical microrobot with a radius r, the Eq. ( 6) becomes:

f d,Stoke = -6πη f r 2 v (9)
This approximation is usually adequate in arterioles or capillaries, but remains inaccurate in arteries where the Reynolds number is in the range of R e ∼ 0.5-500. A more accurate expression of the drag coefficient for a spherical body with a Reynolds number lower than R e < 2.5 × 10 5 has been proposed by White and Corfield (1991):

C d∞ = 24 R e + 6 1 + √ R e + 0.4 (10)
Furthermore, the above Stoke's approximation (9) also neglects the wall effect β . In endovascular applications the effect of the blood vessel walls on the drag force has to be accounted. The effect of the bounding walls is defined in terms of a wall correction factor which measures the relative change in the drag force f d with respect to the equivalent drag force f d∞ in unbounded environment. Therefore, this wall effect correction is usually defined as the ratio between the velocity v in a bounded medium and the velocity v ∞ in an infinite fluid, β ≡ v/v ∞ . Numerous studies have shown that this wall factor is mainly a function of the sphere-to-tube radius ratio, λ = r/R v , assuming that the cylindrical vessel is sufficiently long to neglect the end effects. Especially, it is admitted that the wall correction depends only on λ at both very low and high Reynolds number, whereas at the intermediate transition regime, the factor β is a function of both λ and R e parameters [START_REF] Chhabra | A note on wall effect on the terminal falling velocity of a sphere in quiescent newtonian media in cylindrical tubes[END_REF]. For a spherical device in Stoke's flow the [START_REF] Haberman | Motion of rigid and fluid spheres in stationary and moving liquids inside cylindrical tubes[END_REF] expression is the most reliable for λ ≤ 0.9:

β (λ ) = 1 -2.1050λ + 2.0865λ 3 -1.7068λ 5 + 0.72603λ 6 1 -0.75857λ 5 ( 11
)
with λ = r/R v , where r and R define the spherical microrobot and vessel radius respectively. For intermediate Reynold number in the range 0.01 < R e < 10000, the [START_REF] Kehlenbeck | Empirical relationships for the terminal settling velocity of spheres in cylindrical columns[END_REF] correlation could be recommended up to λ = 0.85:

β (λ , R e ) = 1 -λ p 1 + λ λ 0 p ( 12
)
where both p and λ 0 are function of R e as follows:

λ 0 = 0.283 + 0.0492R e 0.

Hydrodynamic Behavior of Non-Spherical Microrobot

Secondly, the drag force experienced by a non-spherical object has been also considered for spheroids, cylinders, chainlike of spheres, or cuboids [START_REF] Kasper | Measurements of viscous drag on cylinders and chains of spheres with aspect ratios between 2 and 50[END_REF]Madhav and Chhabra 1995;[START_REF] Filippov | Drag and torque on clusters of n arbitrary spheres at low reynolds number[END_REF]. The main idea is to consider that the drag force experienced by a non-spherical microrobot acts in the direction of the velocity v, and could be related to the equivalent spherical drag force, that is:

f d∞ = κ f • f ds∞ (r e ) (16)
where κ f is the dimensionless dynamic shape factor which is related to the microrobot geometry; and f ds∞ (r e ) is the equivalent drag force computed for a spherical device with the equivalent volume sphere radius r e in unbounded environment. This radius r e is defined as the radius of a sphere equal in volume to the non-spherical microrobot. Furthermore, the wall effect play a crucial role in the drag phenomena acting on non-spherical object. Efforts have been made to experimentally and numerically determine this drag correction factor for different object and channel shapes [START_REF] Happel | Low Reynolds Number Hydrodynamics: With Special Applications to Particulate Media, 3rd edn. Mechanics of Fluids and Transport Processes[END_REF][START_REF] Kasper | Measurements of viscous drag on cylinders and chains of spheres with aspect ratios between 2 and 50[END_REF]Unnikrishnan and Chhabra 1991;[START_REF] Kishore | Wall effects on flow and drag phenomena of spheroid particles at moderate reynolds numbers[END_REF]. By analogy with spherical device, the wall correction is related to the object size-to-tube radius ratio (λ ), the Reynolds number (R e ), and the microrobot aspect ration (σ ). Commonly, the wall factor β is related to the Faxén's correction [START_REF] Happel | Low Reynolds Number Hydrodynamics: With Special Applications to Particulate Media, 3rd edn. Mechanics of Fluids and Transport Processes[END_REF], and could be expressed in the general form as:

β (λ , R e , σ ) = 1 -f (λ , R e , σ ) (17)
where f is a function of the ratio λ = a/R v , with a a characteristic length of the object and R v the radius of the channel.

3 Materials and Methods

Microrobot Design

To cope with the external vascular forces f Vasc = f d , we consider in this study a microrobot that is based either on a spherical or an aggregate of therapeutic magnetic microcarriers (TMMC). Each TMMC comprises superparamagnetic iron oxide (SPIO) particles and a drug load, as illustrated in Fig. 2.

The magnetic volume of a TMMC is then a fraction of the total volume, that is V m = τ m V . Although the saturation magnetization of SPIO particles is not optimal (e.g., m sat ∼ 30-60 emu/g), it is still acceptable with the advantage to being widely used clinically (Laurent et al 2008). However, to be used as therapeutic agents, their very low value of magnetic material results in very high gradient fields that limit their application with MRI-guided delivery. To increase the effective volume V m of magnetic material, novel approaches use selfassembled aggregates (dipole-dipole interactions) of magnetic nanoparticles (MNPs) (Vartholomeos and Mavroidis 2012) or biodegradable polymer (Pouponneau et al 2011) to form large bolus of aggregates. We consider here three different structures: i) a single spherical TMMC (Fig. 2-a

Magnetic Microrobot in Viscous Flow

The flow and drag phenomena spherical microrobot in viscous flow has been well investigated (Maccoll 1928;[START_REF] Davies | The aerodynamics of golf balls[END_REF][START_REF] Haberman | Motion of rigid and fluid spheres in stationary and moving liquids inside cylindrical tubes[END_REF][START_REF] Kehlenbeck | Empirical relationships for the terminal settling velocity of spheres in cylindrical columns[END_REF], and could be directly obtained using Eqs. ( 6), ( 10) and ( 11) or (12). Usually, the hydrodynamic behavior of a non-spherical microrobot is related to its equivalent spherical drag force (16) through the dynamic shape factor κ f . As experiments cannot be conducted on objects with a wide range of shapes in different orientations, a predictable model of the dynamic shape factor is required.

In the case of a longitudinally elliptic body of circular cross section (named prolate spheroid hereafter), the dimensionless shape correction depends on the direction of the movement. If the motion of a prolate ellipsoid is transverse to its major axis (i.e., direction v ⊥ in Fig. 2), the following approximation is proposed [START_REF] Kasper | Measurements of viscous drag on cylinders and chains of spheres with aspect ratios between 2 and 50[END_REF]:

e κ ⊥ = 8 3 (σ 2 -1) (2σ 2 -3) √ σ 2 -1 ln σ + √ σ 2 -1 + σ (18)
with σ = a b the aspect ratio of the prolate spheroid, where a is the major axis and b is the minor axis of the ellipsoid (cf. Fig. 2-b). For a motion along the direction of the major axis (i.e., direction v // in Fig. 2), the dynamic shape factor is given by [START_REF] Kasper | Measurements of viscous drag on cylinders and chains of spheres with aspect ratios between 2 and 50[END_REF]:

e κ // = 4 3 (σ 2 -1) (2σ 2 -1) √ σ 2 -1 ln σ + √ σ 2 -1 -σ (19)
For chains of N-spheres, [START_REF] Geller | Boundary element method calculations of the mobility of nonspherical particles1. linear chains[END_REF] have experimentally investigated the dynamic shape factor, and have proposed the following formula:

c κ ⊥ = 4 3 N 2/3 log(2N) + 0.26269 + 0.38185 log 2 (2N) (20) c κ // = 2 3 N 2/3 log(2N) -1.00401 + 0.906526 log 2 (2N) (21)
where the subscript ⊥ and // denote a motion perpendicular, and parallel respectively, to the major axis of a straight chain of N-spheres (see Fig. 2-c).

Remark 1 Let us notice that the above dynamic shape factors are defined for all aspect ratio σ > 1 for ellipsoidal design, or N > 1 for chain-like structure. If σ = 1 or N = 1, in both cases we get a spherical object leading to κ f = 1.

Furthermore, when exposed to an external magnetic field b 0 , the magnetic microrobot acquires a magnetic dipole moment. Therefore, a non-spherical microrobot get its major axis aligned along the field b 0 direction, as illustrated in Fig. 3. As the controlled magnetic gradient ∇b defines the motion direction v, an angular deviation θ could occur. Thus, it influences the dynamic shape factor, and the above perpendicular and parallel factors could be seen as extrema values. The computation of the dynamic shape factor κ θ for an angular deviation θ between the minor axis and the moving direction (see Fig. 3) is then given by [START_REF] Kasper | Measurements of viscous drag on cylinders and chains of spheres with aspect ratios between 2 and 50[END_REF]:

1 κ θ = 1 κ ⊥ + 1 κ // - 1 κ ⊥ sin 2 θ (22)
As mentioned earlier, the wall effects have to be taken into account. The wall correction factor for prolate spheroids falling in the v // direction has been first investigated at very low Reynolds number by [START_REF] Happel | Low Reynolds Number Hydrodynamics: With Special Applications to Particulate Media, 3rd edn. Mechanics of Fluids and Transport Processes[END_REF]:

e β // (λ , σ ) = 1-e κ // λ σ 1/3 2.105 + 0.758λ 2 σ 2 + 1.329λ 2 θ ϕ θ ϕ (m a jo r a x is ) Vessel wall b 0 ∇b Vessel axis f d f d (m in o r a x is ) v v
Fig. 3 Magnetic microrobot in vessel-like environment. (23) with the aspect ration σ = a/b where a and b denote the major and minor axes of the ellipsoid. However, no wall correction for orthogonal motion v ⊥ are proposed. For prolate spheroids falling in intermediate Reynolds number in the range 1 ≤ R e ≤ 200 [START_REF] Kishore | Wall effects on flow and drag phenomena of spheroid particles at moderate reynolds numbers[END_REF] have proposed the following drag coefficient that embed the dynamic shape factor and the wall effect:

C d = 12 R e 1.81 + λ 0.79 + λ 4.16 1 + 0.304R e 0.685 σ 1.1 + 0.15R e -0.5 σ 3.3 + 2.1σ 0.4 (24)
The above drag coefficient is defined for parallel motion with σ = b/a, and orthogonal motion with σ = a/b. In contrast, few works have addressed the wall effect for chain-like structures. Commonly, researchers use the spheroid approximation. Particularly, in parallel orientation, spheroidal model appears adequate to approximate a straight chain structure, when λ 1. Based on Happel and Brenner (1983) studies, [START_REF] Kasper | Measurements of viscous drag on cylinders and chains of spheres with aspect ratios between 2 and 50[END_REF] have proposed from their experimental results dedicated to chain-like structures of N-spheres in Stoke's flow the following first-order approximations:

c β // (λ , σ = N) = 1 -2.105 e κ // λ σ 1/3 (25) c β ⊥ (λ , σ = N) = 1 -0.76 λ σ 0.7 (26)
with σ = N the number of spheres. Tabulated values from series of experiments of the dynamic shape factor and wall effect of chain-like structure up to N = 30 are also proposed in [START_REF] Kasper | Measurements of viscous drag on cylinders and chains of spheres with aspect ratios between 2 and 50[END_REF]. Fig. 4 shows the evolution of the drag forces f d for spherical, spheroid-like and chain-like superparamagnetic microrobots. The structures are composed by TMMC aggregates (radius r 0 = 100 µm) navigating in a vessel of radius R v = 750 µm. The left curves illustrate the drag behavior for a parallel motion along the vessel axis, while the right curves present the results for an orthogonal motion. As expected, the microrobotic shape plays a great role on its hydrodynamic behavior supporting the fact that the choice of the appropriated model is important for design optimization. When navigating in parallel, the ellipsoid-like and chain-like designs clearly provides less drag force than the equivalent sphere. Especially, the ellipsoidal profile is the most efficient in such case. It should be noticed that for non-spherical microrobots, the hydrodynamic force is preponderant in an orthogonal motion rather than in a parallel motion due to the fact that the non-spherical shape presents a higher resistance to the flow. However, the chain-like microrobot seems to provide less drag in perpendicular direction than a spheroid design. It can be explained by that assumption that the flow can pass at intersections between the spheres reducing significantly the drag resistance. Finally, let us recall that only limited data is available for λ > 0.9 and aspect ratio in the range of 0.25 < σ < 30. Thus extreme caution must be exercised in using any of the available correlation under these conditions. In particular, the model of [START_REF] Kasper | Measurements of viscous drag on cylinders and chains of spheres with aspect ratios between 2 and 50[END_REF] for chains of N-spheres structure provides significant correlation only up to λ ≈ 0.5 in creeping flow.

MRI Actuation

A clinical MRI is used to achieve the propulsion of the magnetic microrobot using the existing gradient coils of the scanner. These coils system is a set of electromagnetic coils, which allows the generation of magnetic gradients in the three-dimensional (3D) space within the MRI bore. We assume that the strong uniform magnetic field b 0 = 3 T of the MRI is sufficient to ensure the magnetization saturation m sat = (0, 0, m sat ) T of the embedded magnetic material. Furthermore, the uniform magnetic field b 0 tends to align the magnetization moment m with b 0 . Thus, the orientation of the microrobot is maintained thanks to the magnetic torque t m . The Eq. ( 3) can be then simplified as:

  f m x f m y f m z   = V m • m sat     ∂ B x ∂ z ∂ B y ∂ z ∂ B z ∂ z     (27)
Obviously, the optimization of the magnetic propulsion capability is then related to the available magnetic volume (V m ) and magnetization saturation (m sat ), together with the magnetic gradient strength (∇b). However, there are different technological constraints that actually limit the magnetic actuation. First, the limitations of the actuators are set here to ∇b sat = 45 mT/m, which is consistent with the maximum magnetic gradients that are available in clinical MRI scanners. Furthermore, superparamagnetic iron oxide (SPIO) particles are currently extensively investigated as magnetic material for biomedical applications due to their excellent biocompatibility and reactive surface that can be readily modified with therapeutic molecules (Laurent et al 2008;Pouponneau et al 2011). Hence, after the break up of the bolus and the drug release, the SPIO particles would be safely spread through the systemic circulation, and naturally removed by the body. Moreover, SPIO particles magnetization saturation m sat commonly span the 30-60 emu/g range, lower than the bulk iron-oxide value (∼ 100 emu/g). To improve the magnetic propulsion, one solution is then to increase the effective magnetic volume V m . Therefore, aggregates of TMMCs must be considered to maximize the magnetic force.

Magnetic Microrobot for MRI-aided Optimal Drug Delivery

This work aims to optimize the design of a magnetic microrobot that has to be released from the (small) arteries for targeted drug delivery using an MRI scanner. To transport the therapeutic agent, the microrobot comprises an agglomerate of TMMCs. In particular, to be consistent with the experiments, we consider hereafter that the magnetic parts of the TMMC are superparamagnetic iron oxide (SPIO) particles (BioMag BM547, Bang Laboratories, Inc.) with a saturation magnetization of m sat,3T = 58 emu/g under a magnetic field b 0 = 3 T (Mathieu and Martel 2009). To optimize the drug delivery, the total volume V of the microrobot should be maximized to provide a sufficient magnetic force f m , and drug load to the targeted area. Nevertheless, this objective leads to increase the drag force f d , and the risk of unwanted embolization. Especially, to control efficiently the microrobot, the driving force f m have to overcome the external drag force f d . This design optimization is then related to the dimensionless magnetophoretic number

C mt = f m

Spherical Magnetic Microrobot

The design optimization of spherical magnetic microrobots have been investigated from arteries to capillaries previously in [START_REF] Arcese | Endovascular magnetically guided robots: Navigation modeling and optimization[END_REF]. In their studies the authors have considered the optimization of the design together with the trajectory, and thus fixed the magnetization rate to τ m = 45%. Here, we aim to consider the optimal structure that allows carrying the maximum drug load to the targeted area. Fig. 5 shows the evolution of the magnetophoretic number C mt for different spherical magnetic microrobot sizes that navigate in a small artery of 1.5 mm size (cf. Tab. 1). The best ratio is given for a C mt = 1.96 with a radius of r e = 285.5 µm with a full magnetization rate of τ m = 100%. Moreover, this result exhibits that to control efficiently such spherical design, the equivalent radius r e must be within 127.8 µm and 481.9 µm range. For a spherical microcarrier in this range (C mt = 1) the minimal magnetization rate τ m = 51.06% is provided for a radius r e = 269.3 µm leading to a drug load of V d = 0.04 mm 3 . As shown in Fig. 6, the optimum drug load of 0.098 mm 3 is obtained for a radius of r e = 415.8 µm and τ m = 67.3%. However, for optimal delivery the size of the microrobot must be between 30% to 60% of the vessel size in small arteries [START_REF] Arcese | Endovascular magnetically guided robots: Navigation modeling and optimization[END_REF]. Therefore, to ensure efficient magnetic controllability and drug load to deep location in the human body, the spherical microrobot is usable mainly in small arteries (about R v 175 µm vessel size).

Non-Spherical Magnetic Microrobot

To the authors' knowledge, no studies have been investigated concerning the optimization of non-spherical bead pulling design for targeted drug delivery. Fig. 7 presents the evolution of the C mt ratio as a function of the equivalent radius r e and the magnetization rate τ m for different microrobot structures. Specifically, these results consider ellipsoid (Fig. 7a and7c) and chain-like (Fig. 7b and7d) microrobots composed of TMMC aggregates. In the following, we consider TMMCs of radius r 0 = 100 µm. The considered ellipsoid design has a fixed minor radius b = r 0 while its major axis a is increased with the equivalent volume sphere radius r e . Therefore, for a given equivalent radius r e each magnetic microrobot has the same magnetic volume, and thus is propelled with the same magnetic force f m (27). As expected, non-spherical microrobots are more efficient in parallel direction rather than following a perpendicular motion. In terms of steering performances, the simulation results demonstrate better performance for chain-like structures compared to prolatelike structures. Obviously spheroids are not able to provide steering capability (C mt < 1) in orthogonal motion. For the same equivalent volume, the reference surface of chain-like structures are greater than those of spheroids, but the former offers less drag resistance to the flow due to stream leakage at sphere contact. Fig. 8 compares the corresponding amount of drug volume carried by different microrobot structure when the ratio is settled to C mt = 1. Once again, the chain-like geometry provides the optimal drug load as spheroid cannot be controlled properly in orthogonal motion. In small artery (radius R v = 750 µm), only chain of up to 7-TMMCs of radius r 0 = 100 µm could be used in direction perpendicular to the vessel axis. Therefore, a maximal drug volume of 0.0107 mm 3 could be transported. In practice, such structures appear to be difficult to control properly without creating unwanted embolies at vessel bifurcations. Obviously, the best choice would be to navigate in vessels with a diameter close to the TMMC size. However, it would increase drastically wall effects and surface interactions (e.g., electrostatic, van der Waals, or contact microforces) which have been not addressed here. To overcome this limitation, a solution is to reduce the size of the TMMC radius r 0 . Fig. 9a illustrates the variation of the number of TMMCs in a chainlike agglomeration in orthogonal direction for maximum drug load. A minimum radius of r 0 = 60 µm with at least 12microspheres could be magnetically steered in small artery of radius R v = 750 µm. Below r 0 < 60 µm there are not enough magnetic material to propel efficiently the microrobot in perpendicular direction. At the other end, for maximal values r 0 > 140 µm, the drug load reaches a saturation level rapidly with only two TMMCs (Fig. 9b). The optimal number of TMMCs, and then the drug load capability, can be freely chosen wrt. the minimal vessel size of the targeted area.

Discussions

Actually, drug treatments utilize a manually operated syringe and single-lumen microcatheter to release the TMMC aggregates into the hepatic arterial supply with the intent of targeting downstream tumor sites. From the design point of view, the TMMCs has first to overcome the hepatic artery blood flow (37 mL/min) with a minimum transient time. The simulation results show that in such a case the chains of microspheres aggregation provides the most efficient magnetophoretic ratio C mt = f m f d and drug load capability, particularly when its major axis is aligned along the vessel axis. Due to the magnetic chain-like aggregation of TMMCs, the magnetic volume to steer is drastically increased thereby reducing the transit time. These results are in full agreement with those experienced by (Pouponneau et al 2009) with a MRI scanner. We found also that when navigating perpendicular to the vessel axis, such aggregates could have lengths exceeding the radius R v in smaller vessel (e.g., in arterioles or capillaries). The main problem foreseen is unwanted embolies. However, the simulations demonstrate that the conjunction of the endovascular shear-stress with the wall contact effects could induce a sufficient force to break-up the dipole-dipole interaction forces between the TMMCs allowing releasing the drug into arterioles and capillaries. As the small vessels are feeding the tumor, the drug delivery close to the targeted site seems feasible. Furthermore, the conducted optimal design analysis has mainly focused on the C mt = 1 case. Indeed, this magnetophoretic ratio leads to provide the maximum amount of drug while offering sufficient magnetic volume to counteract the arterial blood flow. On the other hand, the optimal value C mt ≥ 1 is only required to navigate against the hepatic blood flow. Such situations usually occur mainly in the vicinity of the first hepatic arterial bifurcation, and become less mandatory as the microrobot navigates in deeper locations. Therefore, one can slightly under evaluate the magnetic microrobot size.

Results and Discussions

In this section, we demonstrate experimentally the steerability of TMMC aggregates composed of SPIO particles in different operating conditions. First, a steering Maxwell-Helmholtz coil system is developed as a proof-of-concept before to be used with a clinical MRI scanner.

Proof of Concept Validation

Experimental Setup Description

To validate experimentally the findings of model simulations, an experimental setup has been specifically developed by Aeon Scientific™ and is depicted in Fig. 10a. The system consists of three nested sets of Maxwell coils and one nested set of Helmholtz coils presented in Table 2. Such arrangement helps to generate magnetic gradient field in x-, y-, and z-axis direction in the workspace. Magnetic gradient forces will thus be exerted on the magnetic microrobot that is placed inside a Y-channel of the microfluidic chip (cf. Fig. 10b). This microchannel chip imitates a hepatic artery bifurcation, i.e. mother branch R v1 = 2.5 mm and daughter branch R v2 = 750 µm. To imitates the blood flow, this vascular phantom is filled with a viscous fluid that is made of 50% glycerolwater mixture providing a viscosity of η f = 6 mPa • s and density of ρ f = 1130 kg/m 3 . The navigable bolus was synthesized with gel and superparamagnetic iron oxide (SPIO) particles (BioMag BM547, Bang Laboratories, Inc.) in a mixer before to be injected. By controlling the concentration of SPIO particles, we can design boluses with different magnetic rate τ m . Then, droplets containing SPIO particles are injected through a controlled syringe pump in the injection input via a flexible microcatheter. Fig. 11 depicts an example of obtained ellipsoidal-like aggregates of TMMC (Fig. 11a) and a chain-like aggregation (Fig. 11b). TMMC depicted here has the following characteristics: an average radius of about 250 µm; gel profile replacing the sustained release of drug; and an aspect ratio greater than 0.9. Such value of aspect ratio leads to a dynamic shape factor that remains close to 1. Homogeneous magnetic flux densities and gradients of up to 300 mT and 350 mT/m, respectively, can be generated in the workspace of 20 mm × 20 mm. The Helmholtz coils corresponds to the x-axis to magnetize the SPIO microparticles with low remnant magnetization values.

The system is set up on an CCD high-resolution miniature microscope camera (TIMM 400, Nanosensor) providing up to 26 mm × 20 mm field of view. The motion of magnetic microcarrier is measured by real-time processing of the video images acquired by the microscope camera using Labview computer program.

Experimental Validation

Successful targeting of magnetic microrobot at deep-seated lesions can be accomplished by steering the optimized boluses of SPIO particles through successive blood-vessel branches toward the lesion. The experimental platform can be used to determine the magnetic gradients that maximize the steering efficiency with a minimum of SPIO particles dispersion. This section describes the results of the proof of concept experiments that were conducted for validation purposes of the navigability of magnetic microrobot in a Y-channel microfluidic chip mimicking the hepatic arterial system. Fig. 12 shows the CFD simulation (ANSYS©Fluent software) of the Y-shaped microfluidic device. This result helps to verify the laminar flow conditions when the microcatheter tip is inserted in the main vessel channel.

Microaggregates of SPIO particles with polymeric solutions demonstrate stability in aqueous liquid due to their hydrophobicity. As shown in Fig. 13a, the bolus of aggregates of particles keeps its shape when navigating far from the vessel's walls. To measure the amount of particles lost during navigation, we analyzed the volume of the bolus through image processing techniques for different velocity values. rier release less than 7% of its volume of particles. It can be seen in Fig. 13a that for relatively large vessels (small-artery of R = 2.5 mm of radius), the influence of the near-field surface forces such as the shear-stress (τ) and the electrostatic forces does not play a great role in the break-up of the aggregate. The ratio λ = r/R v1 between the bolus radii and the vessel radii is very small (λ = 0.1). The condition is verified when the distance between the micro-carrier and the vessel's wall (δ 1 ) is superior to the bolus diameter. As shown in Fig. 13b, when the microcarrier enters in one daughter branch, the ratio λ is close to 0.33 that increases greatly the influence of shear-stress forces close to the wall's vessel. Moreover, when the microrobot enter in the daughter branch it has a spherical shape. While the shear stress is increasing, the shape became more ellipsoidal-like. Hence, the form of the magnetic microrobot evolves during the navigation in smaller vessel. Fig. 15 illustrates the influence of the vessel's wall on the bolus volume. We defined the non-dimensional value (S/S 0 ) as the ratio between the magnetic microrobot volume and the SPIO particle volume. The standard ratio is settled at S/S 0 = 57. One can see that for values less than δ = 350 µm, the near-field surface forces dominates until to break-up the aggregate totally. The value highlighted in red corresponds to the specific case of the snapshots of Fig. 13b.

We see clearly that when the bolus is exposed to mechanical forces that overcome the attractive forces holding the microparticles together, such as hemodynamic shear stresses, the aggregate break apart. To determine the shear-sensitivity of the microparticle deployment mechanism, we estimated from calculation the shear-stress for a cylindrical vessel as:

τ w = -η f Q (R v -δ ) R 3 v (28)
with Q the volumetric flow rate and δ the distance to the wall. The experimental results given in Fig. 16 demonstrates the great influence of the shear-stress mechanism on the break-up of the aggregate that produce repulsive forces and counteract the small magnetic dipole-dipole forces. Finally, Fig. 17

Preliminary MRI-aided Experiments

A clinical MRI scanner has been used to evaluate the relevance of the model simulation. The MRI system used here is a standard Magnetom Verio 3T (Siemens, Germany) scanner (see Fig. 18). As the MRI platform is still in used for clinical consultations, the system hardware has not been modified. However, the Siemens software environment has been upgraded. Specifically, a dedicated magnetic resonance navigation (MRN) architecture has been developed and embedded in the Siemens Integrated Development Environment for MR Applications (IDEA). The MRN architecture comprises novel MR-Imaging sequences, MR-Tracking algorithms, navigation planning and magnetic control strategies [START_REF] Folio | Mri magnetic signature imaging, tracking and navigation for targeted micro/nano-capsule therapeutics[END_REF]. An external vision system is added to observe the evolution of the bolus.

To evaluate the capability to use magnetic bolus within a clinical MRI scanner, preliminary experiments have been conducted. To this aim, a magnetic microrobot were placed in an acrylic box filled with water inside the MRI bore, as shown in Fig. 18. The acrylic box allows ensuring that no magnetic material escapes into the system. Hence, the microrobot has to follow a simple planned path, as shown in Fig. 19. The motion of magnetic microrobot is measured by real-time processing of the MRI data using a dedicated MR-tracking algorithm from a fast low single shot (FLASH) sequences. Especially, the insertion of magnetic material into the MRI field of view implies some distortion in the MR-data, and leads to magnetic susceptibility artifact formation, as illustrated in Fig. 19a. The choice of FLASH sequences allows offering a MR-tracking providing a standard deviation of 0.1mm at 0.053 mm in the x and y direction respectively [START_REF] Folio | Mri magnetic signature imaging, tracking and navigation for targeted micro/nano-capsule therapeutics[END_REF]. In clinical practice the focus is usually on avoiding such artifacts to produce correct representation of anatomical structures. In contrast, in this study, susceptibility artifacts induced bythe particles-based superparamagnetic aggregates are exploited to localize the microrobot. Therefore, despite the strong artifact formation, the MRN architecture is able to drive the magnetic microrobot along the planned path (see Fig. 19). The results illustrate that an MRI device is able to control efficiently a bolus of aggregates.

To assess the microrobot navigation capabilities in hepatic artery bifurcation phantom, a spherical aggregate of TMMCs with a radius of r 0 = 250 µm is injected into the mother channel. An average flow rate of Q = 12 mL/s has been generated using a pulsatile pump, and a gradient perpendicular to the flow switched to assist choosing a branch. For the sake of simplicity, a pre-planned isotropic navigation path is decomposed into two waypoints: one located at the bifurcation neighborhood, and the second at the end of the lower branch. Fig. 20 illustrates the obtained results. These results show that despite the size of the spherical aggregate our MRN framework allows tracking in real-time its position thanks to its significant magnetic susceptibility artifacts. Similar results have been obtained for chain-like and ellipsoid-like TMMC aggregates illustrated in Fig. 11. The experiments demonstrate that the use of magnetic gradient values limited to mT/m20 were sufficient to control the TMMC aggregates within a pulsatile flow of 12 mL/s.

Conclusion

The paper described an optimal design strategy for magnetic targeting of therapeutic drugs using magnetic SPIO particles aggregates. To propel these aggregations through the arteries (∼ 5 mm) and small arteries (∼ 500 µm) down to the thinner blood vessels to reach deep location in the human body requires important magnetic gradients leading to large boluses of agglomerates. To maximize the effect of the treatment and minimize adverse effects on the patient, different structures of magnetic microrobot have been addressed. As magnetic bead pulling actuation is the most efficient propulsion scheme in arteries, spherical, ellipsoidal-like and chain-like agglomerations of TMMC are investigated and compared. It appears that chain-like structures provide the most efficient agglomerations to carry the most amount of drug. The preliminary experimental results demonstrate the relevance to use SPIO particles for targeted therapy. The experiments show that the bolus shape evolves during the navigation from spherical to ellipsoidal-like to chain-like structures, before to be break-up close to the targeted site.

Fig. 2

 2 Fig. 2 Magnetic microrobot: (a) single spherical TMMC, (b) ellipsoidlike aggregation and (c) chain-like agglomerate of TMMC.

Fig. 4

 4 Fig. 4 Hydrodynamic drag forces f d for spherical, spheroid-like and chain-like superparamagnetic microrobots composed of TMMC aggregates as function of the bolus volume. The second abscissa shows the shape ratio σ = b/a = 1/N (left) and σ = a/b = N (right). Dimensions: TMMC radius r 0 = 100 µm, vessel radius R v = 750 µm.

Fig. 5

 5 Fig. 5 Magnetophoretic number C mt = fm f d ratio as function of equivalent spherical radius r e and magnetization rate τ m for spherical magnetic microrobots.

Fig. 6

 6 Fig. 6 Evaluation of magnetization rate τ m (a) and drug load (b) as function of the radius for a magnetophoretic number C mt = 1 for spherical magnetic microrobots.

Fig. 7

 7 Fig. 7 Comparison of magnetophoretic number C mt = f m /f d for an ellipsoidal (a)-(c) and a chain-like (b)-(d) microrobots in parallel (a)-(b) and perpendicular (c)-(d) motions.

Fig. 8 Fig. 9

 89 Fig. 8 Drug volume as function of the equivalent radius r e when C mt = 1 with TMMC of radius r 0 = 100 µm.

Fig. 10

 10 Fig. 10 Experimental proof of concept setup: (a) 3D Maxwell-Helmholtz coils setup; and (b) Y-shaped microfluidic arterial bifurcation chip.

Fig. 11

 11 Fig.11Navigable bolus being made of hundreds SPIO microparticles being embedded with the therapeutic load. The optimized structure is 75% of magnetic material and 25% of drug.

Fig. 12

 12 Fig. 12 Computational fluid dynamics simulation of a microcatheter delivering bolus of aggregates of magnetic microparticles in a Y-shaped microfluidic channel. As shown, the parabolic profile of laminar flow prevails in the mother and daughter vessels.

  (a) shows a microfluidic vascular stenosis model demonstrating how large bolus of aggregates should remain intact in pre-stenotic region (daughter vessel), but then break-up into microparticles when they flow through a constriction (60% lumen occlusion) and can accumulate in endothelial cells lining the bottom of the channel. As shown in experiments (Fig.17

  (a)) and in simulation using discrete particle modeling software (Fig.17

  (b)), shear-induced release of drug-coated microparticles could break-up back into its micrometer constituents, which are then driven by the blood flow into the thinner blood vessel toward the stenosis.

Fig. 13 Fig. 14 Fig. 15

 131415 Fig. 13 Magnetic bolus navigation experiments in microfluidic Y-shaped channels: (a) the mother channel of radius R v = 2.5 mm; (b) the daughter channel of radius R v = 750 µm.

Fig. 16

 16 Fig. 16 Evolution of the aggregate volume wrt. the shear-stress.

Fig. 17

 17 Fig. 17 Navigation of a bolus of aggregates in a daughter channel of radius 750 µm toward a microfluidic vascular stenosis model of radius 250 µm. (a) navigation of a magnetic bolus of radius r 0 = 250 µm in a stenosis vascular phantom and breaking in multiple clots due to shear-stresses; and (b) computational simulations using Discrete Particle Modeling software.

Fig. 18

 18 Fig.18The clinical Siemens Mangetom Verio 3T MRI scanner with the square acrylic box filled with water that contains bolus of aggregates.

Table 1

 1 Simulations parameters

	Blood viscosity	η f	6 mPa • s
	Small artery size	R v	0.75 mm
	Flow velocity	v	20 mm/s
	SPIO magnetization saturation m sat,3T Magnetic gradient magnitude ∇b	58 emu/g 45 mT/m

Table 2

 2 Platform coils.

	Coil Axis Radius (mm) Turns	Config.
	z	34	45	Maxwell
	y	51	58	Maxwell
	x	72	80	Maxwell
	x	68	91	Helmholtz