Augustin C. Ogier

Purpose: To develop, optimize, and characterize a respiratory motion‐resolved free‐running isotropic 3D carotid vessel wall T ₁ mapping technique named CARISMAT1C. Methods: An inversion‐recovery gradient‐echo free‐running pulse sequence with interleaved double flip‐angle (2FA) was implemented, and an extended‐phase‐graph dictionary was used to map the T ₁ relaxation time. In a phantom, the T ₁ accuracy was compared to that of a single‐flip‐angle (1FA) variant, the inversion‐recovery spin‐echo reference, and clinical routine MOLLI, while the T ₁ precision of several phyllotaxis‐based radial trajectories was compared. The most precise sequence was used in 11 healthy volunteers (25 ± 3Y, 3F). A synthetic 3D gray‐blood image was reconstructed from the source images and used to delineate the internal, external, and common carotid arteries. T ₁ values across artery sections were compared to those of MOLLI. Results: In the phantom, the 2FA variant had higher T ₁ agreement with the IR‐SE reference than 1FA or MOLLI. The top‐to‐bottom phyllotaxis trajectory with golden‐step shuffling was the most precise and was retained for in vivo scans. End‐expiratory carotid vessel wall T ₁ values (1185 ± 42 ms) were similar to those obtained with MOLLI (1162 ± 84 ms, p = 0.37) and showed less intersubject variability and high interscan repeatability. No significant differences were found across arterial segments in the vessel wall T ₁ values. Conclusion: CARISMAT1C had high T ₁ accuracy in phantoms and high T ₁ precision in vivo in different sections of the carotid artery tree.

Le déploiement de méthodes d’anatomie computationnelle demeure limité pour l'exploration des organes à tissus mous, notamment dans le cadre des deux contextes applicatifs abordés dans cette thèse que sont l'étude des troubles du plancher pelvien et des maladies neuromusculaires via l'imagerie par résonance magnétique (IRM). Dans ces domaines, l'étape de segmentation est essentielle pour la caractérisation des altérations physiologiques au sein des organes d'intérêt. Le manque de méthodes automatiques robustes freine les recherches cliniques sur de larges populations. La première contribution de cette thèse a été le développement d'une approche de segmentation supervisée basée sur des méthodes de propagation par recalage difféomorphique d'images afin de simplifier la segmentation de séries d'images présentant une continuité d'informations entre ses images successives. En réduisant considérablement l'implication manuelle d'un opérateur et en fournissant un résultat robuste et précis, cette méthode a été validée pour la segmentation des muscles squelettiques ainsi que de la vessie dans des contextes pathologiques. Dans le versant musculaire de cette thèse, notre méthode a également été étendue pour le suivi longitudinal des patients et a directement été appliqué dans plusieurs études cliniques afin de caractériser différentes maladies neuromusculaires via des scores issus de l'IRM quantitative. Dans le contexte des troubles de la statique pelvienne, l'association de notre approche de segmentation avec des méthodes avancées d'imagerie dynamique et de recalage de points a permis la première visualisation dynamique 3D d'organes pelviens pendant un exercice de charge

Purpose: To develop and evaluate a free-breathing 2D radial joint T₁-T₂ mapping technique for the kidneys at 3T, and to assess the impact of navigator gating parameters on mapping precision and accuracy. Methods: The PARMANav sequence (PArametric Radial MApping with Navigator gating) was implemented for renal imaging, using 25 single-shot radial gradient echo acquisitions with five repeated magnetization preparations and lung-liver navigator gating to avoid through-plane motion. Virtual compressed coil and compressed sensing with spatial and contrast regularization was used for image reconstruction, followed by a model-based registration. An acquisition-specific joint T₁-T₂ dictionary was generated using extended phase graph simulations. T ₁ and T ₂ accuracies were quantified in a phantom study versus gold standard spin-echo-based sequences. The influence of the navigator acceptance window width (NAWW) and navigator rejection on T ₁ and T ₂ precision were established in 10 healthy volunteers and were compared to routine T ₁ and T ₂ mapping. Three patients were scanned to demonstrate clinical feasibility. Results: In the phantom, PARMANav T ₁ and T ₂ values showed high accuracy with the gold standard T ₁ and T ₂ values and were insensitive to rejected navigators (< 5% variation for T ₁ and T ₂ ). As expected from previous studies, in-vivo renal PARMANav T ₁ and T ₂ values were higher than routine values but showed lower variability, both per subject and between subjects: in the cortex PARMANav T ₁ =1601±48ms/T ₂ =90.8±5.0ms vs routine T ₁ =1307±108ms/T ₂ =73.3±8.0ms, while in the medulla PARMANav T ₁ =2044±82ms/T ₂ =90.3±5.4ms and routine T ₁ =1560±122ms/T ₂ =67.6±5.8ms. No T ₁ or T ₂ trend was observed for the different NAWW. Feasibility was demonstrated in patients, where high-quality maps were obtained. Conclusion: PARMANav allows for precise and accurate joint T ₁ -T ₂ mapping of the kidneys without requiring breath holding. Through-plane motion artifacts were avoided with a navigator, which did not impact the accuracy or precision of the resulting maps.

Background Free-running (FR) cardiac MRI enables free-breathing ECG-free fully dynamic 5D (3D spatial+cardiac+respiration dimensions) imaging but poses significant challenges for clinical integration due to the volume and complexity of image analysis. Existing segmentation methods are tailored to 2D cine or static 3D acquisitions and cannot leverage the unique spatial-temporal wealth of FR data. Purpose To develop and validate a deep learning (DL)-based segmentation framework for isotropic 3D+cardiac cycle FR cardiac MRI that enables accurate, fast, and clinically meaningful anatomical and functional analysis. Methods Free-running, contrast-free bSSFP acquisitions at 1.5T and contrast-enhanced GRE acquisitions at 3T were used to reconstruct motion-resolved 5D datasets. From these, the end-expiratory respiratory phase was retained to yield fully isotropic 4D datasets. Automatic propagation of a limited set of manual segmentations was used to segment the left and right ventricular blood pool (LVB, RVB) and left ventricular myocardium (LVM) on reformatted short-axis (SAX) end-systolic (ES) and end-diastolic (ED) images. These were used to train a 3D nnU-Net model. Validation was performed using geometric metrics (Dice similarity coefficient [DSC], relative volume difference [RVD]), clinical metrics (ED and ES volumes, ejection fraction [EF]), and physiological consistency metrics (systole–diastole LVM volume mismatch and LV–RV stroke volume agreement). To assess the robustness and flexibility of the approach, we evaluated multiple additional DL training configurations such as using 4D propagation-based data augmentation to incorporate all cardiac phases into training. Results The main proposed method achieved automatic segmentation within a minute, delivering high geometric accuracy and consistency (DSC: 0.94 ± 0.01 [LVB], 0.86 ± 0.02 [LVM], 0.92 ± 0.01 [RVB]; RVD: 2.7%, 5.8%, 4.5%). Clinical LV metrics showed excellent agreement (ICC > 0.98 for EDV/ESV/EF, bias < 2 mL for EDV/ESV, < 1% for EF), while RV metrics remained clinically reliable (ICC > 0.93 for EDV/ESV/EF, bias < 1 mL for EDV/ESV, < 1% for EF) but exhibited wider limits of agreement. Training on all cardiac phases improved temporal coherence, reducing LVM volume mismatch from 4.0% to 2.6%. Conclusion This study validates a DL-based method for fast and accurate segmentation of whole-heart free-running 4D cardiac MRI. Robust performance across diverse protocols and evaluation with complementary metrics that match state-of-the-art benchmarks supports its integration into clinical and research workflows, helping to overcome a key barrier to the broader adoption of free-running imaging.

Purpose: To implement a navigator‐gated free‐breathing 2D radial joint T ₁ –T ₂ mapping technique for the myocardium at 3T, and to characterize the impact of the navigator rejection on the precision and accuracy of the T ₁ and T ₂ maps. Methods: The proposed technique, named PARMANav (for PArametric Radial Mapping with Navigator gating), collects 25 lung–liver navigator‐gated electrocardiogram (ECG)‐triggered single‐shot radial gradient‐recalled echo (GRE) images with five magnetization preparations. Source images were reconstructed using compressed sensing. Extended‐phase‐graph simulations were used to generate an acquisition‐specific joint T ₁ –T ₂ dictionary. The impact of the number of rejected navigators on the relaxation times was assessed in numerical simulations. The influence of the navigator acceptance window width (NAWW) and heart rate on the relaxation times was assessed in phantom studies, 10 healthy volunteers, and 3 patients. The relaxation times were compared to routine T ₁ and T ₂ mapping values. Results: The numerical simulations showed negligible dependence on the number of rejected navigators (1 –T ₂ variation). In the phantom, PARMANav T ₁ –T ₂ values were stable across heart rates: the T ₁ –T ₂ coefficient of variation (CoV) was 1 –T ₂ values were higher than routine values (T ₁ = 1331 ± 53 ms, T ₂ = 46.1 ± 2.5 ms vs. T ₁ = 1095 ± 81 ms, T ₂ = 38.7 ± 2.9 ms, p < 0.001), while the PARMANav T ₂ CoV was significantly reduced. No myocardial T ₁ –T ₂ values or CoV trend was observed for the different NAWW. Feasibility in patients was demonstrated, where high‐quality maps were obtained. Conclusion: PARMANav allows for precise and accurate joint T ₁ –T ₂ mapping without requiring breath holding. Through‐plane motion artifacts were avoided with a navigator that did not impact the accuracy or precision of the resulting maps.

Background Heart failure (HF) is a life-threatening syndrome with significant morbidity and mortality. While evidence-based drug treatments have effectively reduced morbidity and mortality in HF with reduced ejection fraction (HFrEF), few therapies have been demonstrated to improve outcomes in HF with preserved ejection fraction (HFpEF). The multifaceted clinical presentation is one of the main reasons why the current understanding of HFpEF remains limited. This may be caused by the existence of several HFpEF disease subtypes that each need different treatments. There is therefore an unmet need for a holistic approach that combines comprehensive imaging with metabolomic, transcriptomic and genomic mapping to subtype HFpEF patients. Methodology This prospective multi-center observational cohort study will include 500 consecutive patients with actual or recent hospitalization for treatment of HF with preserved ejection fraction at two Swiss university hospitals, along with 50 age-matched HFrEF patients and 50 age-matched healthy controls. Diagnosis of heart failure is based on clinical signs and symptoms and subgrouping HF patients is based on the left-ventricular ejection fraction. In addition to routine clinical workup, participants undergo genomic, transcriptomic, and metabolomic analyses, while the anatomy, composition, and function of the heart are quantified by comprehensive echocardiography and magnetic resonance imaging (MRI). Quantitative MRI is also applied to characterize the kidney. The primary outcome is a composite of one-year cardiovascular mortality or rehospitalization. Machine learning (ML) based multi-modal clustering will be employed to identify distinct HFpEF subtypes in the holistic data. The clinical importance of these subtypes shall be evaluated based on their association with the primary outcome. Discussion The integration of comprehensive MRI with extensive genomic and metabolomic profiling in this study will result in an unprecedented panoramic view of HFpEF and should enable us to distinguish functional subgroups of HFpEF patients. This approach has the potential to provide unprecedented insights on HFpEF disease and should provide a basis for personalized therapies. Beyond this, identifying HFpEF subtypes with specific molecular and structural characteristics could lead to new targeted pharmacological interventions, with the potential to improve patient outcomes. Clinical trial number: not applicable.

Purpose: To optimize and characterize an interrupted 5D free‐running framework at 3 T for detailed cardiac function assessment without the use of breath holding or contrast agents. Methods: A free‐running 3D radial gradient echo sequence was periodically interrupted with a preparation and a recovery module to optimize native blood‐to‐myocardium contrast at 3 T. Lipid signal was suppressed using a numerically optimized water‐excitation RF pulse to reduce lipid streaking artifacts and to improve overall image quality. Optimal acquisition parameters were established for a 5‐min scan time using extended phase graph simulations. A compressed sensing‐based reconstruction incorporating cardiac and respiratory inter‐bin deformation fields was employed to generate 5D images of the whole heart. The sharpness and contrast between the left ventricular blood pool and myocardium, along with the functional measurements of the left ventricle from the 5D datasets, were compared to routine 2D cine imaging in 16 healthy volunteers and three patients referred for clinically indicated CMR. Results: The proposed method resulted in lower contrast vs. and sharpness vs. , but enabled similar left‐ventricle ejection fraction assessment , limits of , intraclass correlation with high reproducibility compared to 2D cine. Conclusion: The proposed contrast‐free, interrupted free‐running 5D imaging provides left ventricular functional assessments comparable to 2D cine at 3 T, while offering an improved patient experience through shorter scan times and free breathing.

Introduction and Aims: Mitochondrial myopathies are rare genetic disorders for which no effective treatment exists. We previously showed that the pharmacological cyclophilin inhibitor cyclosporine A (CsA) extends the lifespan of fast‐twitch skeletal muscle‐specific mitochondrial transcription factor A knockout (Tfam KO) mice, lacking the ability to transcribe mitochondrial DNA and displaying lethal mitochondrial myopathy. Our present aim was to assess whether the positive effect of CsA was associated with improved in vivo mitochondrial energy production.Methods: Mice were treated with CsA for 4 weeks, beginning at 12 weeks (i.e., before the terminal disease phase). Hindlimb plantar flexor muscles were fatigued by 80 contractions (40 Hz, 1.5 s on, 6 s off) while measuring force and energy metabolism using phosphorus‐31 magnetic resonance spectroscopy.Results: Force decreased at similar rates in Tfam KO mice with and without the CsA treatment, reaching 50% of the baseline value after ~14 ± 1 contractions, which was faster than in control mice (25 ± 1 contractions). Phosphocreatine (PCr) decreased to ~10% of the control concentration in Tfam KO mice, independent of the treatment, which was larger than the ~20% observed in control mice. The time constant of PCr recovery was higher in untreated Tfam KO than that in control muscle (+100%) and similar in untreated and CsA‐treated Tfam KO mice.Discussion: The results do not support improved mitochondrial energy production as a mechanism underlying the prolonged lifespan of Tfam KO mitochondrial myopathy mice treated with CsA. Thus, other mechanisms must be involved, such as the previously observed CsA‐mediated protection against excessive mitochondrial Ca²⁺ accumulation.

Purpose: To compare two blind source separation (BSS) techniques to principal component analysis and the electrocardiogram for the identification of cardiac triggers in self‐gated free‐running 5D whole‐heart MRI. To ascertain the precision and robustness of the techniques, they were compared in three different noise and contrast regimes.Methods: The repeated superior–inferior (SI) projections of a 3D radial trajectory were used to extract the physiological signals in three cardiac MRI cohorts: (1) 9 healthy volunteers without contrast agent injection at 1.5T, (2) 30 ferumoxytol‐injected congenital heart disease patients at 1.5T, and (3) 12 gadobutrol‐injected patients with suspected coronary artery disease at 3T. Self‐gated cardiac triggers were extracted with the three algorithms (principal component analysis [PCA], second‐order blind identification [SOBI], and independent component analysis [ICA]) and the difference with the electrocardiogram triggers was calculated. PCA and SOBI triggers were retained for image reconstruction. The image sharpness was ascertained on whole‐heart 5D images obtained with PCA and SOBI and compared among the three cohorts.Results: SOBI resulted in smaller trigger differences in Cohorts 1 and 3 compared to PCA (p < 0.01) and in all cohorts compared to ICA (p < 0.04). In Cohorts 1 and 3, the sharpness increased significantly in the reconstructed images when using SOBI instead of PCA (p < 0.03), but not in Cohort 2 (p = 0.4).Conclusion: We have shown that SOBI results in more precisely extracted self‐gated triggers than PCA and ICA. The validation across three diverse cohorts demonstrates the robustness of the method against acquisition variability.