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Importance Approaches are needed to stratify individuals in early psychosis stages beyond positive symptom severity to investigate specificity related to affective and normative variation and to validate solutions with premorbid, longitudinal, and genetic risk measures. Objective To use machine learning techniques to cluster, compare, and combine subgroup solutions using clinical and brain structural imaging data from early psychosis and depression stages. Design, Setting, and Participants A multisite, naturalistic, longitudinal cohort study (10 sites in 5 European countries; including major follow-up intervals at 9 and 18 months) with a referred patient sample of those with clinical high risk for psychosis (CHR-P), recent-onset psychosis (ROP), recent-onset depression (ROD), and healthy controls were recruited between February 1, 2014, to July 1, 2019. Data were analyzed between January 2020 and January 2022. Main Outcomes and Measures A nonnegative matrix factorization technique separately decomposed clinical (287 variables) and parcellated brain structural volume (204 gray, white, and cerebrospinal fluid regions) data across CHR-P, ROP, ROD, and healthy controls study groups. Stability criteria determined cluster number using nested cross-validation. Validation targets were compared across subgroup solutions (premorbid, longitudinal, and schizophrenia polygenic risk scores). Multiclass supervised machine learning produced a transferable solution to the validation sample. Results There were a total of 749 individuals in the discovery group and 610 individuals in the validation group. Individuals included those with CHR-P (n = 287), ROP (n = 323), ROD (n = 285), and healthy controls (n = 464), The mean (SD) age was 25.1 (5.9) years, and 702 (51.7%) were female. A clinical 4-dimensional solution separated individuals based on positive symptoms, negative symptoms, depression, and functioning, demonstrating associations with all validation targets. Brain clustering revealed a subgroup with distributed brain volume reductions associated with negative symptoms, reduced performance IQ, and increased schizophrenia polygenic risk scores. Multilevel results distinguished between normative and illness-related brain differences. Subgroup results were largely validated in the external sample. Conclusions and Relevance The results of this longitudinal cohort study provide stratifications beyond the expression of positive symptoms that cut across illness stages and diagnoses. Clinical results suggest the importance of negative symptoms, depression, and functioning. Brain results suggest substantial overlap across illness stages and normative variation, which may highlight a vulnerability signature independent from specific presentations. Premorbid, longitudinal, and genetic risk validation suggested clinical importance of the subgroups to preventive treatments.

International audience; Black Blood Fast Spin Echo imaging of the heart is usually performed during mid-diastolic rest. This is a direct consequence of the long inversion time required to suppress the blood signal, which is constrained by the T(1) of the blood, and of the heart rate. To overcome these constraints, and to acquire black blood images in the end-systolic rest period, a new approach is introduced aiming at adaptively predicting the best time to prepare and acquire MR signals. It is based on a RR interval prediction algorithm and on a cardiac cycle model. The proposed method was applied to 14 healthy volunteers and is compared to a simple alternative method using a fixed delay and to the standard black blood imaging method for imaging in the mid-diastolic rest period. Results show that the proposed method offers an increased robustness in terms of trigger delay error and image quality compared to the tested simple alternative. Also, it has been shown by qualitative analysis done by an experienced observer that the right ventricle, especially the thin right ventricle free wall, is better depicted with our method than with the standard mid-diastolic rest acquisition.

Magnetic resonance imaging (MRI) is a valuable tool for the clinical diagnosis for brain imaging as well as cardiac and abdominal imaging. In cardiac MRI, there are two challenging issues: the non reproducibility of cardiac cycles and respiratory motion. Morphological cardiac MRI is generally performed with a pulse sequence composed of a long preparation, to cancel the blood signal and thus enhance the contrast of the myocardium, and the acquisition itself. These acquisitions are performed during the mid-diastolic rest (relaxation period of the heart) to satisfy constraints to cancel the blood signal and to avoid problems linked to the cardiac non reproducibility because the mid-diastolic rest is long. Consequently, to acquire images in end-systolic rest (when the heart is fully contracted) while taking into account constraints to cancel the blood signal is not straight forward due to cardiac non reproducibility because the end-systolic rest is short. To overcome these limitations and to acquire images in end-systolic rest, a new adaptive method is introduced that allows to optimally placing acquisition windows while taking constraint for the cancellation of the blood signal into account. This method was applied to measure and compare transverse relaxation time (T2) between end-systolic and mid-diastolic rests. For prospective respiratory motion correction, the crucial point is to estimate motion in real-time without perturbing MR signal used for imaging. In order to solve this issue, a new method is introduced aiming at estimating motion parameters in real-time based on physiological signals such as respiratory bellows and ECG. This method is evaluated and results show its interest and its reliability regarding motion estimation errors. A reconstructions algorithm is also used in order to perform cardiac imaging during the end-systolic rest in free breathing and to use different kind of respiratory motion sensors such as MR signals. Hence, during this research work, several adaptive method were developed to get a better management of motion and to take into account specificity of each patient. These works open the way of fully functional adaptive magnetic resonance imaging in a clinical situation; L'imagerie par résonance magnétique (IRM) est un outil remarquable pour le diagnostic clinique, aussi bien pour l'imagerie cérébrale que pour l'imagerie cardiaque et abdominale. En IRM cardiaque, deux problèmes sont récurrents : la non reproductibilité des cycles cardiaques et le mouvement respiratoire. L'IRM cardiaque morphologique est généralement faite avec une séquence composée d'une préparation longue, visant à annuler le signal du sang pour accentuer le contraste au niveau du myocarde, et de l?acquisition à proprement parler. Ces acquisitions sont généralement faites en mésodiastole (phase de relaxation passive du coeur) ce qui permet de satisfaire les contraintes liées à l'annulation du sang et d'éviter les problèmes liés aux non reproductibilités des cycles cardiaques car la mésodiastole est longue. Il est donc difficile de satisfaire les contraintes liées à l?annulation du sang pour faire les acquisitions en télésystole (phase où le coeur est contracté) à cause des non reproductibilités cardiaques car la télésystole est courte. Afin de passer outre ces limitations et de pouvoir acquérir ces mêmes images morphologiques en télésystole, nous proposons une nouvelle méthode adaptative qui permet à la fois de placer la fenêtre d'acquisition de manière optimale et de satisfaire les contraintes liées à l'annulation du sang. Une application de cette méthode a également été mise en place pour estimer et comparer les temps de relaxation transversale (T2) entre télésystole et mésodiastole. Pour la gestion prospective du mouvement respiratoire, le point crucial est d'estimer les mouvements en temps réel en perturbant au minimum les signaux de résonance magnétique. Pour ce faire nous proposons une méthode basée sur l'estimation paramétrique des mouvements en temps réel à partir des signaux physiologiques disponibles (ceintures respiratoires et ECG). Cette méthode a été testée et les résultats montrent son intérêt et sa fiabilité par rapport aux erreurs faites au niveau du mouvement. Une méthode de reconstruction incluant les mouvements a également été utilisée pendant ces travaux afin de faire de l'imagerie en télésystole en respiration libre et d'utiliser d'autres types de capteurs respiratoires comme certains signaux de résonance magnétique. Ainsi pendant ces travaux, des méthodes adaptatives ont été mises en place afin de mieux gérer le mouvement et de prendre en compte les spécificités de chaque patient. Ces travaux ouvrent la voie de l'imagerie par résonance magnétique adaptative pleinement fonctionnelle dans un contexte clinique

Magnetic resonance imaging (MRI) is a valuable tool for the clinical diagnosis for brain imaging as well as cardiac and abdominal imaging. In cardiac MRI, there are two challenging issues: the non reproducibility of cardiac cycles and respiratory motion. Morphological cardiac MRI is generally performed with a pulse sequence composed of a long preparation, to cancel the blood signal and thus enhance the contrast of the myocardium, and the acquisition itself. These acquisitions are performed during the mid-diastolic rest (relaxation period of the heart) to satisfy constraints to cancel the blood signal and to avoid problems linked to the cardiac non reproducibility because the mid-diastolic rest is long. Consequently, to acquire images in end-systolic rest (when the heart is fully contracted) while taking into account constraints to cancel the blood signal is not straight forward due to cardiac non reproducibility because the end-systolic rest is short. To overcome these limitations and to acquire images in end-systolic rest, a new adaptive method is introduced that allows to optimally placing acquisition windows while taking constraint for the cancellation of the blood signal into account. This method was applied to measure and compare transverse relaxation time (T2) between end-systolic and mid-diastolic rests. For prospective respiratory motion correction, the crucial point is to estimate motion in real-time without perturbing MR signal used for imaging. In order to solve this issue, a new method is introduced aiming at estimating motion parameters in real-time based on physiological signals such as respiratory bellows and ECG. This method is evaluated and results show its interest and its reliability regarding motion estimation errors. A reconstructions algorithm is also used in order to perform cardiac imaging during the end-systolic rest in free breathing and to use different kind of respiratory motion sensors such as MR signals. Hence, during this research work, several adaptive method were developed to get a better management of motion and to take into account specificity of each patient. These works open the way of fully functional adaptive magnetic resonance imaging in a clinical situation, L'imagerie par résonance magnétique (IRM) est un outil remarquable pour le diagnostic clinique, aussi bien pour l'imagerie cérébrale que pour l'imagerie cardiaque et abdominale. En IRM cardiaque, deux problèmes sont récurrents : la non reproductibilité des cycles cardiaques et le mouvement respiratoire. L'IRM cardiaque morphologique est généralement faite avec une séquence composée d'une préparation longue, visant à annuler le signal du sang pour accentuer le contraste au niveau du myocarde, et de l?acquisition à proprement parler. Ces acquisitions sont généralement faites en mésodiastole (phase de relaxation passive du coeur) ce qui permet de satisfaire les contraintes liées à l'annulation du sang et d'éviter les problèmes liés aux non reproductibilités des cycles cardiaques car la mésodiastole est longue. Il est donc difficile de satisfaire les contraintes liées à l?annulation du sang pour faire les acquisitions en télésystole (phase où le coeur est contracté) à cause des non reproductibilités cardiaques car la télésystole est courte. Afin de passer outre ces limitations et de pouvoir acquérir ces mêmes images morphologiques en télésystole, nous proposons une nouvelle méthode adaptative qui permet à la fois de placer la fenêtre d'acquisition de manière optimale et de satisfaire les contraintes liées à l'annulation du sang. Une application de cette méthode a également été mise en place pour estimer et comparer les temps de relaxation transversale (T2) entre télésystole et mésodiastole. Pour la gestion prospective du mouvement respiratoire, le point crucial est d'estimer les mouvements en temps réel en perturbant au minimum les signaux de résonance magnétique. Pour ce faire nous proposons une méthode basée sur l'estimation paramétrique des mouvements en temps réel à partir des signaux physiologiques disponibles (ceintures respiratoires et ECG). Cette méthode a été testée et les résultats montrent son intérêt et sa fiabilité par rapport aux erreurs faites au niveau du mouvement. Une méthode de reconstruction incluant les mouvements a également été utilisée pendant ces travaux afin de faire de l'imagerie en télésystole en respiration libre et d'utiliser d'autres types de capteurs respiratoires comme certains signaux de résonance magnétique. Ainsi pendant ces travaux, des méthodes adaptatives ont été mises en place afin de mieux gérer le mouvement et de prendre en compte les spécificités de chaque patient. Ces travaux ouvrent la voie de l'imagerie par résonance magnétique adaptative pleinement fonctionnelle dans un contexte clinique

International audience; In cardiac MR imaging, the Double Inversion Recovery Fast Spin Echo (DIR-FSE) sequence [1] (also called “black blood”) enables to suppress the blood signal for an accurate depiction of the myocardium. The inversion time (TI) required to suppress the blood signal is constrained by the T1 of the blood and the repetition time [2]. Since the T1 of the blood is long, the TI should also be long. Usually, the detection of an R-wave is used to trigger the sequence. Consequently, the Trigger Delay (TD), the time between an R-wave and the next echo train, is the same as TI and the acquisition is performed during the mid- diastolic rest. The problem is that the TD is constrained by TI whereas it should only be used to select the cardiac phase to acquire. Moreover, the optimum TI does not necessarily match the mid-diastolic, nor end-systolic cardiac rest period . To overcome these limitations, two methods are proposed to acquire black blood images during the end-systolic rest.