VaTEST III : validation of 8 potential super-earths from TESS data

Funding: The ULiege’s contribution to SPECULOOS has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) (grant Agreement n◦ 336480/SPECULOOS). This research is in part funded by the European Union’s Horizon 2020 research and innovation programme (grants agreements n◦ 803193/BEBOP), and from the Science and Technology Facilities Council (STFC; grant n◦ ST/S00193X/1, and ST/W000385/1).NASA’s all-sky survey mission, the Transiting Exoplanet Survey Satellite (TESS), is specifically engineered to detect exoplanets that transit bright stars. Thus far, TESS has successfully identified approximately 400 transiting exoplanets, in addition to roughly 6 000 candidate exoplanets pending confirmation. In this study, we present the results of our ongoing project, the Validation of Transiting Exoplanets using Statistical Tools (VaTEST). Our dedicated effort is focused on the confirmation and characterisation of new exoplanets through the application of statistical validation tools. Through a combination of ground-based telescope data, high-resolution imaging, and the utilisation of the statistical validation tool known as TRICERATOPS, we have successfully discovered eight potential super-Earths. These planets bear the designations: TOI-238b (1.61 +0.09−0.10 R ⊕ ), TOI-771b (1.42 +0.11−0.09 R ⊕ ), TOI-871b (1.66 +0.11−0.11 R ⊕ ), TOI-1467b (1.83 +0.16−0.15 R ⊕ ), TOI-1739b (1.69 +0.10−0.08 R ⊕ ), TOI-2068b (1.82 +0.16−0.15 R ⊕ ), TOI-4559b (1.42 +0.13−0.11 R ⊕ ), and TOI-5799b (1.62 +0.19−0.13 R ⊕ ). Among all these planets, six of them fall within the region known as ‘keystone planets’, which makes them particularly interesting for study. Based on the location of TOI-771b and TOI-4559b below the radius valley we characterised them as likely super-Earths, though radial velocity mass measurements for these planets will provide more details about their characterisation. It is noteworthy that planets within the size range investigated herein are absent from our own solar system, making their study crucial for gaining insights into the evolutionary stages between Earth and Neptune.Peer reviewe

A large sub-Neptune transiting the thick-disk M4 V TOI-2406

We thank the anonymous referee for their corrections and help in improving the paper. We warmly thank the entire technical staff of the Observatorio Astronomico Nacional at San Pedro Martir in Mexico for their unfailing support to SAINT-EX operations, namely: E. Cadena, T. Calvario, E. Colorado, B. Garcia, G. Guisa, A. Franco, L. Figueroa, B. Hernandez, J. Herrera, E. Lopez, E. Lugo, B. Martinez, J. M. Nunez, J. L. Ochoa, M. Pereyra, F. Quiroz, T. Verdugo, I. Zavala. B.V.R. thanks the Heising-Simons Foundation for support. Y.G.M.C acknowledges support from UNAM-PAPIIT IG-101321. B.-O. D. acknowledges support from the Swiss National Science Foundation (PP00P2-163967 and PP00P2-190080). R.B. acknowledges the support from the Swiss National Science Foundation under grant P2BEP2_195285. M.N.G. acknowledges support from MIT's Kavli Institute as a Juan Carlos Torres Fellow. A.H.M.J.T acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement nffi 803193/BEBOP), from the MERAC foundation, and from the Science and Technology Facilities Council (STFC; grant nffi ST/S00193X/1). T.D. acknowledges support from MIT's Kavli Institute as a Kavli postdoctoral fellow Part of this work received support from the National Centre for Competence in Research PlanetS, supported by the Swiss National Science Foundation (SNSF). The research leading to these results has received funding from the ARC grant for Concerted Research Actions, financed by the Wallonia-Brussels Federation. TRAPPIST is funded by the Belgian Fund for Scientific Research (Fond National de la Recherche Scientifique, FNRS) under the grant FRFC 2.5.594.09.F, with the participation of the Swiss National Science Fundation (SNF). M.G. and E.J. are F.R.S.-FNRS Senior Research Associate. This publication benefits from the support of the French Community of Belgium in the context of the FRIA Doctoral Grant awarded to MT. We acknowledge the use of public TESS data from pipelines at the TESS Science Office and at the TESS Science Processing Operations Center. We acknowledge the use of public TESS Alert data from pipelines at the TESS Science Office and at the TESS Science Processing Operations Center. Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center for the production of the SPOC data products. Funding for the TESS mission is provided by NASA's Science Mission Directorate. This research has made use of the Exoplanet Follow-up Observation Program website, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. This paper includes data collected by the TESS mission that are publicly available from the Mikulski Archive for Space Telescopes (MAST). We thank the TESS GI program G03274 PI, Ryan Cloutier, for proposing the target of this work for 2-min-cadence observations in Sector 30. This work is based upon observations carried out at the Observatorio Astronomico Nacional on the Sierra de San Pedro Martir (OAN-SPM), Baja California, Mexico. This work makes use of observations from the LCOGT network. Part of the LCOGT telescope time was granted by NOIRLab through the Mid-Scale Innovations Program (MSIP). MSIP is funded by NSF. This work includes data collected at the Vatican Advanced Technology Telescope (VATT) on Mt. Graham. This paper includes data taken on the EDEN telescope network. We acknowledge support from the Earths in Other Solar Systems Project (EOS) and Alien Earths (grant numbers NNX15AD94G and 80NSSC21K0593), sponsored by NASA. Some of the observations in the paper made use of the High-Resolution Imaging instrument Zorro (Gemini program GS-2020B-LP-105). Zorro was funded by the NASA Exoplanet Exploration Program and built at the NASA Ames Research Center by Steve B. Howell, Nic Scott, Elliott P. Horch, and Emmett Quigley. Zorro was mounted on the Gemini South telescope of the international Gemini Observatory, a program of NSF's OIR Lab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. on behalf of the Gemini partnership: the National Science Foundation (United States), National Research Council (Canada), Agencia Nacional de Investigacion y Desarrollo (Chile), Ministerio de Ciencia, Tecnologia e Innovacion (Argentina), Ministerio da Ciencia, Tecnologia, Inovacoes e Comunicacoes (Brazil), and Korea Astronomy and Space Science Institute (Republic of Korea). This research has made use of the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. This work made use of the following Python packages: astropy (Astropy Collaboration 2013, 2018), lightkurve (Lightkurve Collaboration 2018), matplotlib (Hunter 2007), pandas (Wes McKinney 2010), seaborn (Waskom & The Seaborn Development team 2021), scipy (Virtanen et al. 2020) and numpy (Harris et al. 2020).Context. Large sub-Neptunes are uncommon around the coolest stars in the Galaxy and are rarer still around those that are metal-poor. However, owing to the large planet-to-star radius ratio, these planets are highly suitable for atmospheric study via transmission spectroscopy in the infrared, such as with JWST. Aims. Here we report the discovery and validation of a sub-Neptune orbiting the thick-disk, mid-M dwarf star TOI-2406. The star's low metallicity and the relatively large size and short period of the planet make TOI-2406 b an unusual outcome of planet formation, and its characterisation provides an important observational constraint for formation models. Methods. We first infer properties of the host star by analysing the star's near-infrared spectrum, spectral energy distribution, and Gaia parallax. We use multi-band photometry to confirm that the transit event is on-target and achromatic, and we statistically validate the TESS signal as a transiting exoplanet. We then determine physical properties of the planet through global transit modelling of the TESS and ground-based time-series data. Results. We determine the host to be a metal-poor M4 V star, located at a distance of 56 pc, with properties T-eff = 3100 +/- 75 K, M-* = 0.162 +/- 0.008M(circle dot), R-* = 0.202 +/- 0.011R(circle dot), and [Fe/H] = -0.38 +/- 0.07, and a member of the thick disk. The planet is a relatively large sub-Neptune for the M-dwarf planet population, with R-p = 2.94 +/- 0.17R(circle plus) and P= 3.077 d, producing transits of 2% depth. We note the orbit has a non-zero eccentricity to 3 sigma, prompting questions about the dynamical history of the system. Conclusions. This system is an interesting outcome of planet formation and presents a benchmark for large-planet formation around metal-poor, low-mass stars. The system warrants further study, in particular radial velocity follow-up to determine the planet mass and constrain possible bound companions. Furthermore, TOI-2406 b is a good target for future atmospheric study through transmission spectroscopy. Although the planet's mass remains to be constrained, we estimate the S/N using amass-radius relationship, ranking the system fifth in the population of large sub-Neptunes, with TOI-2406 b having a much lower equilibrium temperature than other spectroscopically accessible members of this population.Heising-Simons FoundationPrograma de Apoyo a Proyectos de Investigacion e Innovacion Tecnologica (PAPIIT)Universidad Nacional Autonoma de Mexico IG-101321Swiss National Science Foundation (SNSF)European Commission PP00P2-163967 PP00P2-190080 P2BEP2_195285MIT's Kavli Institute as a Juan Carlos Torres FellowEuropean Research Council (ERC) nffi 803193/BEBOPMERAC foundationUK Research & Innovation (UKRI)Science & Technology Facilities Council (STFC)Science and Technology Development Fund (STDF) nffi ST/S00193X/1MIT's Kavli Institute as a Kavli postdoctoral fellowSwiss National Science Foundation (SNSF)Australian Research CouncilFonds de la Recherche Scientifique - FNRS FRFC 2.5.594.09.FSwiss National Science Foundation (SNSF)French Community of Belgium in the context of the FRIA Doctoral GrantNASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research CenterNASA's Science Mission DirectorateNational Aeronautics and Space Administration under the Exoplanet Exploration ProgramTESS GI program G03274National Science Foundation (NSF)Earths in Other Solar Systems Project (EOS)Alien Earths - NASA NNX15AD94G 80NSSC21K0593High-Resolution Imaging instrument Zorro (Gemini program) GS-2020B-LP-105NASA Exoplanet Exploration ProgramNational Aeronautics & Space Administration (NASA)National Science Foundation (NSF

Migration and Evolution of giant ExoPlanets (MEEP) I: Nine Newly Confirmed Hot Jupiters from the TESS Mission

Hot Jupiters were many of the first exoplanets discovered in the 1990s, but in the decades since their discovery, the mysteries surrounding their origins remain. Here, we present nine new hot Jupiters (TOI-1855 b, TOI-2107 b, TOI-2368 b, TOI-3321 b, TOI-3894 b, TOI-3919 b, TOI-4153 b, TOI-5232 b, and TOI-5301 b) discovered by NASA's TESS mission and confirmed using ground-based imaging and spectroscopy. These discoveries are the first in a series of papers named the Migration and Evolution of giant ExoPlanets (MEEP) survey and are part of an ongoing effort to build a complete sample of hot Jupiters orbiting FGK stars, with a limiting Gaia $G$-band magnitude of 12.5. This effort aims to use homogeneous detection and analysis techniques to generate a set of precisely measured stellar and planetary properties that is ripe for statistical analysis. The nine planets presented in this work occupy a range of masses (0.55 Jupiter masses (M$_{\rm{J}}$) $<$ M$_{\rm{P}}$ $<$ 3.88 M$_{\rm{J}}$) and sizes (0.967 Jupiter radii (R$_{\rm{J}}$) $<$ R$_{\rm{P}}$ $<$ 1.438 R$_{\rm{J}}$) and orbit stars that range in temperature from 5360 K $<$ Teff $<$ 6860 K with Gaia $G$-band magnitudes ranging from 11.1 to 12.7. Two of the planets in our sample have detectable orbital eccentricity: TOI-3919 b ($e = 0.259^{+0.033}_{-0.036}$) and TOI-5301 b ($e = 0.33^{+0.11}_{-0.10}$). These eccentric planets join a growing sample of eccentric hot Jupiters that are consistent with high-eccentricity tidal migration, one of the three most prominent theories explaining hot Jupiter formation and evolution.Comment: 35 pages, 7 tables, and 14 figures. Submitted to AAS Journals on 2023 Dec 2

Identification of the top TESS objects of interest for atmospheric characterization of transiting exoplanets with JWST

Funding: Funding for the TESS mission is provided by NASA's Science Mission Directorate. This work makes use of observations from the LCOGT network. Part of the LCOGT telescope time was granted by NOIRLab through the Mid-Scale Innovations Program (MSIP). MSIP is funded by NSF. This paper is based on observations made with the MuSCAT3 instrument, developed by the Astrobiology Center and under financial support by JSPS KAKENHI (grant No. JP18H05439) and JST PRESTO (grant No. JPMJPR1775), at Faulkes Telescope North on Maui, HI, operated by the Las Cumbres Observatory. This paper makes use of data from the MEarth Project, which is a collaboration between Harvard University and the Smithsonian Astrophysical Observatory. The MEarth Project acknowledges funding from the David and Lucile Packard Fellowship for Science and Engineering, the National Science Foundation under grant Nos. AST-0807690, AST-1109468, AST-1616624 and AST-1004488 (Alan T. Waterman Award), the National Aeronautics and Space Administration under grant No. 80NSSC18K0476 issued through the XRP Program, and the John Templeton Foundation. C.M. would like to gratefully acknowledge the entire Dragonfly Telephoto Array team, and Bob Abraham in particular, for allowing their telescope bright time to be put to use observing exoplanets. B.J.H. acknowledges support from the Future Investigators in NASA Earth and Space Science and Technology (FINESST) program (grant No. 80NSSC20K1551) and support by NASA under grant No. 80GSFC21M0002. K.A.C. and C.N.W. acknowledge support from the TESS mission via subaward s3449 from MIT. D.R.C. and C.A.C. acknowledge support from NASA through the XRP grant No. 18-2XRP18_2-0007. C.A.C. acknowledges that this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). S.Z. and A.B. acknowledge support from the Israel Ministry of Science and Technology (grant No. 3-18143). The research leading to these results has received funding from the ARC grant for Concerted Research Actions, financed by the Wallonia-Brussels Federation. TRAPPIST is funded by the Belgian Fund for Scientific Research (Fond National de la Recherche Scientifique, FNRS) under the grant No. PDR T.0120.21. The postdoctoral fellowship of K.B. is funded by F.R.S.-FNRS grant No. T.0109.20 and by the Francqui Foundation. H.P.O.'s contribution has been carried out within the framework of the NCCR PlanetS supported by the Swiss National Science Foundation under grant Nos. 51NF40_182901 and 51NF40_205606. F.J.P. acknowledges financial support from the grant No. CEX2021-001131-S funded by MCIN/AEI/ 10.13039/501100011033. A.J. acknowledges support from ANID—Millennium Science Initiative—ICN12_009 and from FONDECYT project 1210718. Z.L.D. acknowledges the MIT Presidential Fellowship and that this material is based upon work supported by the National Science Foundation Graduate Research Fellowship under grant No. 1745302. P.R. acknowledges support from the National Science Foundation grant No. 1952545. This work is partly supported by JSPS KAKENHI grant Nos. JP17H04574, JP18H05439, JP21K20376; JST CREST grant No. JPMJCR1761; and Astrobiology Center SATELLITE Research project AB022006. This publication benefits from the support of the French Community of Belgium in the context of the FRIA Doctoral Grant awarded to M.T. D.D. acknowledges support from TESS Guest Investigator Program grant Nos. 80NSSC22K1353, 80NSSC22K0185, and 80NSSC23K0769. A.B. acknowledges the support of M.V. Lomonosov Moscow State University Program of Development. T.D. was supported in part by the McDonnell Center for the Space Sciences. V.K. acknowledges support from the youth scientific laboratory project, topic FEUZ-2020-0038.JWST has ushered in an era of unprecedented ability to characterize exoplanetary atmospheres. While there are over 5000 confirmed planets, more than 4000 Transiting Exoplanet Survey Satellite (TESS) planet candidates are still unconfirmed and many of the best planets for atmospheric characterization may remain to be identified. We present a sample of TESS planets and planet candidates that we identify as “best-in-class” for transmission and emission spectroscopy with JWST. These targets are sorted into bins across equilibrium temperature Teq and planetary radius Rp and are ranked by a transmission and an emission spectroscopy metric (TSM and ESM, respectively) within each bin. We perform cuts for expected signal size and stellar brightness to remove suboptimal targets for JWST. Of the 194 targets in the resulting sample, 103 are unconfirmed TESS planet candidates, also known as TESS Objects of Interest (TOIs). We perform vetting and statistical validation analyses on these 103 targets to determine which are likely planets and which are likely false positives, incorporating ground-based follow-up from the TESS Follow-up Observation Program to aid the vetting and validation process. We statistically validate 18 TOIs, marginally validate 31 TOIs to varying levels of confidence, deem 29 TOIs likely false positives, and leave the dispositions for four TOIs as inconclusive. Twenty-one of the 103 TOIs were confirmed independently over the course of our analysis. We intend for this work to serve as a community resource and motivate formal confirmation and mass measurements of each validated planet. We encourage more detailed analysis of individual targets by the community.Peer reviewe

TESS discovery of a sub-Neptune orbiting a mid-M dwarf TOI-2136

peer reviewedWe present the discovery of TOI-2136b, a sub-Neptune planet transiting every 7.85 days a nearby M4.5V-type star, identified through photometric measurements from the TESS mission. The host star is located $33$ pc away with a radius of $R_{\ast} = 0.34\pm0.02\ R_{\odot}$, a mass of $0.34\pm0.02\ M_{\odot}$ and an effective temperature of $\rm 3342\pm100\ K$. We estimate its stellar rotation period to be $75\pm5$ days based on archival long-term photometry. We confirm and characterize the planet based on a series of ground-based multi-wavelength photometry, high-angular-resolution imaging observations, and precise radial velocities from CFHT/SPIRou. Our joint analysis reveals that the planet has a radius of $2.19\pm0.17\ R_{\oplus}$, and a mass measurement of $6.4\pm2.4\ M_{\oplus}$. The mass and radius of TOI2136b is consistent with a broad range of compositions, from water-ice to gas-dominated worlds. TOI-2136b falls close to the radius valley for low-mass stars predicted by the thermally driven atmospheric mass loss models, making it an interesting target for future studies of its interior structure and atmospheric properties

Image processing and simulation of perfusion MRI images for the prediction of the ischemic lesion evolution in stroke

L'Accident Vasculaire Cérébral (AVC) - pathologie résultant d'une perturbation de l'apport sanguin dans le cerveau - est un problème de santé publique majeur, représentant la troisième cause de mortalité dans les pays industrialisés. Afin d'améliorer la prise en charge des patients atteints d'un AVC, il est important de posséder des méthodes efficaces pour l'identification des patients éligibles aux différentes thérapies et pour l'évaluation du rapport bénéfice/risque associé à ces thérapies. Dans ce contexte, l'Imagerie par Résonance Magnétique (IRM) dynamique de perfusion par contraste de susceptibilité, une modalité d'imagerie utile pour apprécier l'état de la perfusion cérébrale, peut aider à identifier les tissus à risque de s'infarcir. Cependant, l'intégralité de la chaîne de traitement, de l'acquisition à l'analyse et l'interprétation de l'IRM de perfusion demeure complexe et plusieurs limitations restent encore à surmonter. Durant ces travaux de thèse, nous contribuons à l'amélioration de la chaîne de traitement de l'IRM de perfusion, avec comme objectif final, l'obtention d'une meilleure prédiction de l'évolution de la lésion ischémique dans l'AVC. Dans une première partie, nous travaillons principalement sur l'étape de déconvolution des signaux temporels, une des étapes clefs à l'amélioration de l'IRM de perfusion. Cette étape consiste en la résolution d'un problème inverse mal-posé, et permet le calcul de paramètres hémodynamiques qui sont des biomarqueurs importants pour la classification de l'état final des tissus dans l'AVC. Afin de comparer de façon objective les performances des différents algorithmes de déconvolution existants et d'en valider des nouveaux, il est nécessaire d'avoir accès à une information sur la vérité terrain après déconvolution. Dans ce but, nous avons développé un simulateur numérique pour l'IRM de perfusion, avec une vérité terrain générée automatiquement. Ce simulateur est utilisé pour démontrer la faisabilité d'une automatisation du réglage des paramètres de régularisation, et établir la robustesse d'un algorithme de déconvolution avec régularisation spatio-temporelle d'introduction récente. Nous proposons également un nouvel algorithme de déconvolution globalement convergent. Enfin, la première partie de ces travaux se termine avec une discussion sur une autre étape de la chaîne de traitement en IRM de perfusion, à savoir, la normalisation des cartes de paramètres hémodynamiques extraites des images déconvoluéesStroke – a neurological deficit resulting from blood supply perturbations in the brain – is a major public health issue, representing the third cause of death in industrialized countries. There is a need to improve the identification of patients eligible to the different therapies, as well as the evaluation of the benefit-risk ratio for the patients. In this context, perfusion Dynamic Susceptibility Contrast (DSC)-MRI, a prominent imaging modality for the assessment of cerebral perfusion, can help to identify the tissues at risk of infarction from the benign oligaemia. However, the entire pipeline from the acquisition to the analysis and interpretation of a DSC-MRI remains complex and some limitations are still to be overcome. During this PhD work, we contribute to improving the DSC-MRI processing pipeline with the ultimate objective of ameliorating the prediction of the ischemic lesion evolution in stroke. In a first part, we primarily work on the step of temporal signal deconvolution, one of the steps key to the improvement of DSC-MRI. This step consists in the resolution of an inverse ill-posed problem and allows the computation of hemodynamic parameters which are important biomarkers for tissue fate classification in stroke. In order to compare objectively the performances of existing deconvolution algorithms and to validate new ones, it is necessary to have access to information on the ground truth after deconvolution. To this end, we developed a numerical simulator of DSC MRI with automatically generated ground truth. This simulator is used to demonstrate the feasability of a full automation of regularization parameters tuning and to establish the robustness of a recent deconvolution algorithm with spatio-temporal regularization. We then propose a new globally convergent deconvolution algorithm. Then, this first part ends with a discussion on another processing step in the DSC-MRI pipeline, the normalisation of the hemodynamic parameters maps extracted from the deconvolved images. In a second part, we work on the prediction of the evolution of the tissue state from longitudinal MRI data. We first demonstrate the interest of modeling longitudinal MRI studies in stroke as a communication channel where information theory provides useful tools to identify the hemodynamic parameters maps carrying the highest predictive information, determine the spatial observation scales providing the optimal predictivity for tissue classification as well as estimate the impact of noise in prediction studies. We then demonstrate the interest of injecting shape descriptors of the ischemic lesion in acute stage in a linear regression model for the prediction of the final infarct volume. We finally propose a classifier of tissue fate based on local binary pattern for the encoding of the spatio-temporal evolution of the perfusion MRI signal

Traitement et simulation d’images d’IRM de perfusion pour la prédiction de l’évolution de la lésion ischémique dans l’accident vasculaire cérébral

Stroke – a neurological deficit resulting from blood supply perturbations in the brain – is a major public health issue, representing the third cause of death in industrialized countries. There is a need to improve the identification of patients eligible to the different therapies, as well as the evaluation of the benefit-risk ratio for the patients. In this context, perfusion Dynamic Susceptibility Contrast (DSC)-MRI, a prominent imaging modality for the assessment of cerebral perfusion, can help to identify the tissues at risk of infarction from the benign oligaemia. However, the entire pipeline from the acquisition to the analysis and interpretation of a DSC-MRI remains complex and some limitations are still to be overcome. During this PhD work, we contribute to improving the DSC-MRI processing pipeline with the ultimate objective of ameliorating the prediction of the ischemic lesion evolution in stroke. In a first part, we primarily work on the step of temporal signal deconvolution, one of the steps key to the improvement of DSC-MRI. This step consists in the resolution of an inverse ill-posed problem and allows the computation of hemodynamic parameters which are important biomarkers for tissue fate classification in stroke. In order to compare objectively the performances of existing deconvolution algorithms and to validate new ones, it is necessary to have access to information on the ground truth after deconvolution. To this end, we developed a numerical simulator of DSC MRI with automatically generated ground truth. This simulator is used to demonstrate the feasability of a full automation of regularization parameters tuning and to establish the robustness of a recent deconvolution algorithm with spatio-temporal regularization. We then propose a new globally convergent deconvolution algorithm. Then, this first part ends with a discussion on another processing step in the DSC-MRI pipeline, the normalisation of the hemodynamic parameters maps extracted from the deconvolved images. In a second part, we work on the prediction of the evolution of the tissue state from longitudinal MRI data. We first demonstrate the interest of modeling longitudinal MRI studies in stroke as a communication channel where information theory provides useful tools to identify the hemodynamic parameters maps carrying the highest predictive information, determine the spatial observation scales providing the optimal predictivity for tissue classification as well as estimate the impact of noise in prediction studies. We then demonstrate the interest of injecting shape descriptors of the ischemic lesion in acute stage in a linear regression model for the prediction of the final infarct volume. We finally propose a classifier of tissue fate based on local binary pattern for the encoding of the spatio-temporal evolution of the perfusion MRI signalsL'Accident Vasculaire Cérébral (AVC) - pathologie résultant d'une perturbation de l'apport sanguin dans le cerveau - est un problème de santé publique majeur, représentant la troisième cause de mortalité dans les pays industrialisés. Afin d'améliorer la prise en charge des patients atteints d'un AVC, il est important de posséder des méthodes efficaces pour l'identification des patients éligibles aux différentes thérapies et pour l'évaluation du rapport bénéfice/risque associé à ces thérapies. Dans ce contexte, l'Imagerie par Résonance Magnétique (IRM) dynamique de perfusion par contraste de susceptibilité, une modalité d'imagerie utile pour apprécier l'état de la perfusion cérébrale, peut aider à identifier les tissus à risque de s'infarcir. Cependant, l'intégralité de la chaîne de traitement, de l'acquisition à l'analyse et l'interprétation de l'IRM de perfusion demeure complexe et plusieurs limitations restent encore à surmonter. Durant ces travaux de thèse, nous contribuons à l'amélioration de la chaîne de traitement de l'IRM de perfusion, avec comme objectif final, l'obtention d'une meilleure prédiction de l'évolution de la lésion ischémique dans l'AVC. Dans une première partie, nous travaillons principalement sur l'étape de déconvolution des signaux temporels, une des étapes clefs à l'amélioration de l'IRM de perfusion. Cette étape consiste en la résolution d'un problème inverse mal-posé, et permet le calcul de paramètres hémodynamiques qui sont des biomarqueurs importants pour la classification de l'état final des tissus dans l'AVC. Afin de comparer de façon objective les performances des différents algorithmes de déconvolution existants et d'en valider des nouveaux, il est nécessaire d'avoir accès à une information sur la vérité terrain après déconvolution. Dans ce but, nous avons développé un simulateur numérique pour l'IRM de perfusion, avec une vérité terrain générée automatiquement. Ce simulateur est utilisé pour démontrer la faisabilité d'une automatisation du réglage des paramètres de régularisation, et établir la robustesse d'un algorithme de déconvolution avec régularisation spatio-temporelle d'introduction récente. Nous proposons également un nouvel algorithme de déconvolution globalement convergent. Enfin, la première partie de ces travaux se termine avec une discussion sur une autre étape de la chaîne de traitement en IRM de perfusion, à savoir, la normalisation des cartes de paramètres hémodynamiques extraites des images déconvoluée

An unsupervised spatio-temporal regularization for perfusion MRI deconvolution in acute stroke

International audienceWe consider the ill-posed inverse problem encountered in perfusion magnetic resonance imaging (MRI) analysis due to the necessity of eliminating, via a deconvolution process, the imprint of the arterial input function on the MR signals. Until recently, this deconvolution process was realized independently voxel by voxel with a sole temporal regularization despite the knowledge that the ischemic lesion in acute stroke can reasonably be considered piecewise continuous. A new promising algorithm incorporating a spatial regularization to avoid spurious spatial artifacts and preserve the shape of the lesion was introduced [1]. So far, the optimization of the spatio-temporal regularization parameters of the deconvolution algorithm was supervised. In this communication, we evaluate the potential of the L-hypersurface method in selecting the spatio-temporal regularization parameters in an unsupervised way and discuss the possibility of automating this method. This is demonstrated quantitatively with an in silico approach using digital phantoms simulated with realistic lesion shapes

Multicomponent and Longitudinal Imaging Seen as a Communication Channel—An Application to Stroke

International audienceIn longitudinal medical studies, multicomponent images of the tissues, acquired at a given stage of a disease, are used to provide information on the fate of the tissues. We propose a quantification of the predictive value of multicomponent images using information theory. To this end, we revisit the predictive information introduced for monodimensional time series and extend it to multicomponent images. The interest of this theoretical approach is illustrated on multicomponent magnetic resonance images acquired on stroke patients at acute and late stages, for which we propose an original and realistic model of noise together with a spatial encoding for the images. We address therefrom very practical questions such as the impact of noise on the predictability, the optimal choice of an observation scale and the predictability gain brought by the addition of imaging components

Interest of non-negativity constraint in perfusion DSC-MRI deconvolution for acute stroke

International audienceWe develop a globally convergent deconvolution algorithm for perfusion dynamic susceptibility contrast MRI applied to stroke. This algorithm includes, in addition to temporal and spatial regularization terms, a non-negativity constraint. Experiments on real data show performance improvements with the non-negativity constraint in the temporal regularization context