[Cardiac sarcoidosis: a diagnostic and therapeutic challenge]. / Sarcoïdose cardiaque : un défi diagnostique et thérapeutique.

The diagnosis of cardiac sarcoidosis, particularly in its isolated cardiac form, represents a major challenge due to non-specific symptoms and the limited sensitivity and specificity of basic cardiac investigations. MRI and metabolic PET-CT are important elements in the diagnostic process. Corticosteroids remain the cornerstone for the treatment of the inflammatory phase, in association with biological agents and steroid-sparing therapies. The goal is to limit the progression of fibrosis, which is a source of malignant arrhythmias and heart failure. The indication for implantation of a cardiac defibrillator must be carefully evaluated to reduce the risk of sudden death. Multidisciplinary collaboration is essential for optimal care.

Le diagnostic de sarcoïdose cardiaque, en particulier dans sa forme cardiaque isolée, représente un défi majeur en raison de symptômes aspécifiques et d'une sensibilité et spécificité limitées des explorations cardiologiques de base. L'IRM et le PET-CT métabolique sont devenus des éléments essentiels dans le processus diagnostique. Les corticostéroïdes restent la pierre angulaire du traitement dans la phase inflammatoire, parallèlement aux agents biologiques et aux thérapies d'épargne cortisonique. L'objectif est d'éviter la progression vers la fibrose, source d'arythmies malignes et d'insuffisance cardiaque. L'indication à l'implantation d'un défibrillateur cardiaque doit être soigneusement évaluée afin de réduire le risque de mort subite. Une collaboration multidisciplinaire est essentielle afin d'assurer une prise en charge optimale.

Behavior problems 7 years after severe childhood traumatic brain injury: Results of the Traumatisme Grave de L'Enfant study.

PURPOSE/OBJECTIVE: To investigate the occurrence of behavioral problems 7 years after severe pediatric traumatic brain injury (TBI), and their evolution from 3 months to 7 years postinjury. METHOD/DESIGN: Thirty-four participants, 38% girls, M (SD) age at injury 7.6 (4.7) years, age at assessment 15 (4.6) years, underwent comprehensive assessments 7 years after severe TBI from March 2014 to March 2016 and were matched to a control group by age, gender, and parental education. A subgroup of 20 participants had available behavioral assessments at 3, 12, and 24 months postinjury. Internalizing, externalizing, and total behavioral problems were assessed with self- and parent reports of the Achenbach's Behavioral Checklist. Additional data included sociodemographic background, initial injury severity, and specific outcomes assessed concurrently 7 years postinjury. RESULTS: Compared to controls: (a) a significant proportion of participants with severe TBI fell above the clinical cutoff for self- (42%) and parent-reported (36%) externalizing problems, but not for self- (33%) or parent-reported (45%) internalizing problems; (b) withdrawn/depressed, intrusive behavior, and somatic complaints were significantly higher in self-reports; and (c) rule-breaking behavior, attention, and social problems were significantly higher in parent reports. Parent-reported internalizing problems were associated with older age at injury, whereas externalizing problems correlated with greater injury severity and concurrent levels of greater overall disability, lower intellectual ability, and poorer family functioning. In multiple hierarchical regression analyses, overall disability and worse family functioning significantly predicted externalizing problems. Parent-reported internalizing and externalizing problems persisted over time. CONCLUSIONS/IMPLICATIONS: These results highlight the importance of long-term follow-up and individualized behavioral interventions for children who sustained severe TBI. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Identification of Cellular Protein Targets of a Half-Sandwich Iridium(III) Complex Reveals Its Dual Mechanism of Action via Both Electrophilic and Oxidative Stresses.

Identification of intracellular targets of anticancer drug candidates provides key information on their mechanism of action. Exploiting the ability of the anticancer (C∧N)-chelated half-sandwich iridium(III) complexes to covalently bind proteins, click chemistry with a bioorthogonal azido probe was used to localize a phenyloxazoline-chelated iridium complex within cells and profile its interactome at the proteome-wide scale. Proteins involved in protein folding and actin cytoskeleton regulation were identified as high-affinity targets. Upon iridium complex treatment, the folding activity of Heat Shock Protein HSP90 was inhibited in vitro and major cytoskeleton disorganization was observed. A wide array of imaging and biochemical methods validated selected targets and provided a multiscale overview of the effects of this complex on live human cells. We demonstrate that it behaves as a dual agent, inducing both electrophilic and oxidative stresses in cells that account for its cytotoxicity. The proposed methodological workflow can open innovative avenues in metallodrug discovery.

Pericardiectomy and Mechanical Mitro-Aortic Valve Replacement in a Young Patient With Erdheim-Chester Disease.

Erdheim-Chester disease is a rare histiocytosis that primarily affects the skeletal system, but cardiovascular manifestations occur in 75% of cases and are associated with a poor prognosis. Given the small number of cases, the evolution and management of the disease are uncertain. Therefore, it is important to report and share Erdheim-Chester cases. This report presents the case of a young patient with constrictive pericarditis and mitral valve regurgitation resulting from Erdheim-Chester disease.

Long-term burden of informal caregiver 7-years after severe childhood traumatic brain injury in the traumatisme grave de l'Enfant (TGE) study.

OBJECTIVE: To investigate reported burden by the Primary Family Caregiver (PFC) 7-years after severe pediatric traumatic brain injury in the TGE (Traumatisme Grave de l'Enfant) longitudinal study. METHODS: Subjective burden was estimated with the Zarit Burden Inventory (ZBI) in 36 PFC (parents), who rated their own health status (Medical Outcome Study Short Form-12), family functioning and their child's level of care and needs (Pediatric/Adult Care And Needs Scale [PCANS/CANS]). Data collection included: child and PFC sociodemographic characteristics, injury-related factors, 'objective' (e.g. overall level of disability: Glasgow Outcome Scale - Extended, GOS-E/GOS-E-Peds) and 'subjective' outcomes (e.g. participation, behavior, executive functions, quality of life and fatigue). RESULTS: 25% of PFC reported mild-moderate burden, and 19% moderate-severe burden. Higher burden correlated with worse outcomes in all 'subjective' PFC-rated outcomes, and with self-reported participation. The ZBI correlated strongly with CANS/PCANS and GOS-E/GOS-E-Peds. Overall level of disability and PFC-reported executive functioning explained 62% of the ZBI variance. For equal levels of disability, burden was higher when PFC reported a 'negative' picture of their child. CONCLUSION: Significant PFC-reported burden 7-years post-injury was associated with overall disability and 'subjective' PFC-rated outcomes. Factors influencing parental burden in the long term should be identified and psychological support implemented over time.

Anatomy-based correction of kidney PVE on [Formula: see text] SPECT images.

BACKGROUND: In peptide receptor radionuclide therapy (PRRT), accurate quantification of kidney activity on post-treatment SPECT images paves the way for patient-specific treatment. Due to the limited spatial resolution of SPECT images, the partial volume effect (PVE) is a significant source of quantitative bias. In this study, we aimed to evaluate the performance and robustness of anatomy-based partial volume correction (PVC) algorithms to recover the accurate activity concentration of realistic kidney geometries on [Formula: see text]Lu SPECT images recorded under clinical conditions. METHODS: Based on the CT scan data from patients, three sets of fillable kidneys with surface-to-volume (S:V) ratios ranging from 1.5 to 2.8 cm-1, were 3D printed and attached in a IEC phantom. Quantitative [Formula: see text]Lu SPECT/CT acquisitions were performed on a GE Discovery NM CT 870 DR camera for the three modified IEC phantoms and for 6 different Target-To-Background ratios (TBRs: 2, 4, 6, 8, 10, 12). Two region-based (GTM and Labbé) and five voxel-based (GTM + MTC, Labbé + MTC, GTM + RBV, Labbé + RBV and IY) methods were evaluated with this data set. Additionally, the robustness of PVC methods to Point Spread Function (PSF) discrepancies, registration mismatches and background heterogeneity was evaluated. RESULTS: Without PVC, the average kidney RCs across all TBRs ranged from 0.66 ± 0.05 (smallest kidney) to 0.80 ± 0.03 (largest kidney). For a TBR of 12, all anatomy-based method were able to recover the kidneys activity concentration with an error < 6%. All methods result in a comparable decline in RC restoration with decreasing TBR. The Labbé method was the most robust against PSF and registration mismatches but was also the most sensitive to background heterogeneity. Among the voxel-based methods, MTC images were less uniform than RBV and IY images at the outer edge of high uptake areas (kidneys and spheres). CONCLUSION: Anatomy-based PVE correction allows for accurate SPECT quantification of the [Formula: see text]Lu activity concentration with realistic kidney geometries. Combined with recent progress in deep-learning algorithms for automatic anatomic segmentation of whole-body CT, these methods could be of particular interest for a fully automated OAR dosimetry pipeline with PVE correction.

Repeated Stereotactic Radiotherapy for Local Brain Metastases Failure or Distant Brain Recurrent: A Retrospective Study of 184 Patients.

BACKGROUND: The main advantages of stereotactic radiotherapy (SRT) are to delay whole-brain radiotherapy (WBRT) and to deliver ablative doses. Despite this efficacy, the risk of distant brain metastases (BM) one year after SRT ranges from 26% to 77% and 20 to 40% of patients required salvage treatment. The role and consequences of reirradiation remain unclear, particularly in terms of survival. The objective was to study overall survival (OS) and neurological death-free survival (NDFS) and to specify the prognostic factors of long-term survival. METHODS: we retrospectively reviewed the data of patients treated between 2010 and 2020 with at least two courses of SRT without previous WBRT. RESULTS: In total, 184 patients were treated for 915 BMs with two-to-six SRT sessions. Additional SRT sessions were provided for local (5.6%) or distant (94.4%) BM recurrence. The median number of BMs treated per SRT was one with a median of four BMs in total. The mean time between the two SRT sessions was 8.9 months (95%CI 7.7-10.1) and there was no significant difference in the delay between the two sessions. The 6-, 12- and 24-month NDFS rates were 97%, 82% and 52%, respectively. The 6-, 12- and 24-month OS rates were 91%, 70% and 38%, respectively. OS was statistically related to the number of SRT sessions (HR = 0.48; p < 0.01), recursive partitioning analysis (HR = 1.84; p = 0.01), salvage WBRT (HR = 0.48; p = 0.01) and brain metastasis velocity (high: HR = 13.83; p < 0.01; intermediate: HR = 4.93; p < 0.01). CONCLUSIONS: Lung cancer and melanoma were associated with a lower NDFS compared to breast cancer. A low KPS, a low number of SRT sessions, synchronous extracerebral metastases, synchronous BMs, extracerebral progression at SRT1, a high BMV grade, no WBRT and local recurrence were also associated with a lower NDFS. A high KPS at SRT1 and low BMV grade are prognostic factors for better OS, regardless of the number of BM recurrence events.

Retrospective Analysis of Responders and Impaired Patients with Knee Osteoarthritis Treated with Two Consecutive Injections of Very Pure Platelet-Rich Plasma (PRP).

OBJECTIVES: To assess the effectiveness of two consecutive intraarticular injections of PRP to treat knee osteoarthritis (KOA), discriminating between responders and impaired patients. METHODS: This retrospective study included 73 consecutive patients who were referred for two intra-articular PRP injections (one week apart) for treating symptomatic moderate/severe KOA. Biological characterization of the PRP, including platelets, leukocytes and erythrocytes, was evaluated. Patient's subjective symptoms were recorded before the treatment and 1 year after the second injection using pain VAS and WOMAC scores. Responders were defined by an improvement of 10 points on WOMAC. RESULTS: At a 1-year follow up, we found 36 (49.3%) patients who fulfilled the criteria of responders, and 21 (28.8%) patients were impaired. A statistically and clinically significant global improvement of -29.2 ± 14.3 (p < 0.001) points in WOMAC score was observed 1 year after treatment in the responder group, with a higher response rate in patients with KL 2 (57.7%) compared to KL IV (28.6%). The percentage of patients with KL IV was higher in the impaired group (48.0%) compared to the responders (16.6%). As expected, the evaluation of the functionality of the knee in the impaired group indicates that it significantly worsened after one year from treatment (p = 0.027). However, the average pain score remained stable with no significant differences after 1 year (p = 0.843). No clinical complications or severe adverse events after the PRP injections were reported. CONCLUSION: The present study suggests that two intra-articular injections of 10 mL of very pure PRP provide pain and functional improvement in symptomatic KOA.

Machine learning-based prediction of in-hospital death for patients with takotsubo syndrome: The InterTAK-ML model.

AIMS: Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine learning (ML)-based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles. METHODS AND RESULTS: A ridge logistic regression-based ML model for predicting in-hospital death was developed on 3482 TTS patients from the International Takotsubo (InterTAK) Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). Thirty-one clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the curve (AUC), sensitivity and specificity. As secondary endpoint, a K-medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the 10 most relevant features emerging from the main model. The overall incidence of in-hospital death was 5.2%. The InterTAK-ML model showed an AUC of 0.89 (0.85-0.92), a sensitivity of 0.85 (0.78-0.95) and a specificity of 0.76 (0.74-0.79) in the internal validation cohort and an AUC of 0.82 (0.73-0.91), a sensitivity of 0.74 (0.61-0.87) and a specificity of 0.79 (0.77-0.81) in the external cohort for in-hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in-hospital death (28.8% vs. 15.5% vs. 5.4% vs. 1.0.8% vs. 0.5%) which were consistent also in the external cohort. CONCLUSION: A ML-based approach for the identification of TTS patients at risk of adverse short-term prognosis is feasible and effective. The InterTAK-ML model showed unprecedented discriminative capability for the prediction of in-hospital death.

An Explainable MRI-Radiomic Quantum Neural Network to Differentiate Between Large Brain Metastases and High-Grade Glioma Using Quantum Annealing for Feature Selection.

Solitary large brain metastases (LBM) and high-grade gliomas (HGG) are sometimes hard to differentiate on MRI. The management differs significantly between these two entities, and non-invasive methods that help differentiate between them are eagerly needed to avoid potentially morbid biopsies and surgical procedures. We explore herein the performance and interpretability of an MRI-radiomics variational quantum neural network (QNN) using a quantum-annealing mutual-information (MI) feature selection approach. We retrospectively included 423 patients with HGG and LBM (> 2 cm) who had a contrast-enhanced T1-weighted (CE-T1) MRI between 2012 and 2019. After exclusion, 72 HGG and 129 LBM were kept. Tumors were manually segmented, and a 5-mm peri-tumoral ring was created. MRI images were pre-processed, and 1813 radiomic features were extracted. A set of best features based on MI was selected. MI and conditional-MI were embedded into a quadratic unconstrained binary optimization (QUBO) formulation that was mapped to an Ising-model and submitted to D'Wave's quantum annealer to solve for the best combination of 10 features. The 10 selected features were embedded into a 2-qubits QNN using PennyLane library. The model was evaluated for balanced-accuracy (bACC) and area under the receiver operating characteristic curve (ROC-AUC) on the test set. The model performance was benchmarked against two classical models: dense neural networks (DNN) and extreme gradient boosting (XGB). Shapley values were calculated to interpret sample-wise predictions on the test set. The best 10-feature combination included 6 tumor and 4 ring features. For QNN, DNN, and XGB, respectively, training ROC-AUC was 0.86, 0.95, and 0.94; test ROC-AUC was 0.76, 0.75, and 0.79; and test bACC was 0.74, 0.73, and 0.72. The two most influential features were tumor Laplacian-of-Gaussian-GLRLM-Entropy and sphericity. We developed an accurate interpretable QNN model with quantum-informed feature selection to differentiate between LBM and HGG on CE-T1 brain MRI. The model performance is comparable to state-of-the-art classical models.

Combined lactic acidosis and ketoacidosis in a female diabetic patient with severe heart failure.

SGLT2i are now recommended in a wide spectrum of indications including type 2 diabetes (T2DM), heart failure, and chronic kidney disease. This medication class is now available in combination with metformin, which is still a fundamental treatment in patients with T2DM. Despite excellent proven safety profile for both drugs, the expanding use of these agents in clinical practice may lead to an increased incidence of rare side effects, like metformin-associated lactic acidosis (MALA) and euglycemic diabetic ketoacidosis (EDKA), which can be life-threatening. A 58-year-old woman with T2DM and severe heart failure treated by metformin and empagliflozin developed progressive EDKA triggered by fasting that was also complicated by severe acute renal failure and MALA. She was successfully treated with intermittent hemodialysis. This case report highlights the importance of the recognition of rare, but very serious adverse effects due to combined metformin and SGLT2i therapy.

Physical activity matters for everyone's health, but individuals with multimorbidity benefit more.

Multimorbidity, defined as the presence of two or more chronic conditions, is increasingly prevalent and is a major contributor to ill health in old age. Physical activity (PA) is a key protective factor for health and individuals with multimorbidity could particularly benefit from engaging in PA. However, direct evidence that PA has greater health benefits in people with multimorbidity is lacking. The objective of the present study was to investigate whether the associations between PA and health were more pronounced in individuals with (vs. without) multimorbidity. We used data from 121,875 adults aged 50 to 96 years (mean age = 67 ± 10 years, 55% women) enrolled in the Survey of Health, Ageing and Retirement in Europe (SHARE). Multimorbidity and PA were self-reported. Health indicators were assessed using tests and validated scales. Variables were measured up to seven times over a 15-year period. Confounder-adjusted linear mixed-effects models were used to investigate the moderating role of multimorbidity on the associations of PA with the levels and trajectories of health indicators across aging. Results showed that multimorbidity was associated with declines in physical, cognitive, and mental health, as well as poorer general health. Conversely, PA was positively associated with these health indicators. We found a significant interaction between multimorbidity and PA, revealing that positive associations between PA and health indicators were strengthened in people with multimorbidity - although this stronger association became less pronounced in advanced age. These findings suggest that the protective role of PA for multiple health indicators is enhanced in individuals with multimorbidity.

Age-related decrease in functional mobility score when performing a locomotor task in an immersive environment.

In recent years, immersive virtual reality technology has emerged in the field of health. Its use could allow the assessment of the motor behavior of individuals in adaptable and reproducible immersive environments, simulating real situations. This study aimed to assess the effect of an immersive scenario on functional mobility during a simple locomotor task according to age. Sixty young adults and 60 older volunteers, who were autonomous and without cognitive and neurological impairment participated. A locomotor task based on the "Timed Up and Go" task was performed in real and virtual conditions. A functional mobility score was calculated by combining the time and the number of steps used and compared between young and older people. Results showed that correlations between time and the number of steps were the same in VR and real conditions, but the locomotor performance decreased significantly in VR for both populations. Additionally, older people exhibited a more reduced locomotor performance in a virtual environment than young adults, thereby their functional mobility score decreased more to complete the task, reflecting the adoption of a more secure locomotion strategy often related to the fear of falling, with an increase in time and number of steps to support balance. The major difference between reality and VR is the visual immersion with an HMD, and visual information is more important in the sensory integration of older people. Therefore, the reduction in visual field and lack of visual exproprioceptive information about the body segments in the virtual environment could explain these results. Finally, the effect of immersion in a virtual scenario on mobility exists for both populations but is accentuated by the aging process and is therefore age dependent.

Contour-guided deep learning based deformable image registration for dose monitoring during CBCT-guided radiotherapy of prostate cancer.

PURPOSE: To evaluate deep learning (DL)-based deformable image registration (DIR) for dose accumulation during radiotherapy of prostate cancer patients. METHODS AND MATERIALS: Data including 341 CBCTs (209 daily, 132 weekly) and 23 planning CTs from 23 patients was retrospectively analyzed. Anatomical deformation during treatment was estimated using free-form deformation (FFD) method from Elastix and DL-based VoxelMorph approaches. The VoxelMorph method was investigated using anatomical scans (VMorph_Sc) or label images (VMorph_Msk), or the combination of both (VMorph_Sc_Msk). Accumulated doses were compared with the planning dose. RESULTS: The DSC ranges, averaged for prostate, rectum and bladder, were 0.60-0.71, 0.67-0.79, 0.93-0.98, and 0.89-0.96 for the FFD, VMorph_Sc, VMorph_Msk, and VMorph_Sc_Msk methods, respectively. When including both anatomical and label images, VoxelMorph estimated more complex deformations resulting in heterogeneous determinant of Jacobian and higher percentage of deformation vector field (DVF) folding (up to a mean value of 1.90% in the prostate). Large differences were observed between DL-based methods regarding estimation of the accumulated dose, showing systematic overdosage and underdosage of the bladder and rectum, respectively. The difference between planned mean dose and accumulated mean dose with VMorph_Sc_Msk reached a median value of +6.3 Gy for the bladder and -5.1 Gy for the rectum. CONCLUSION: The estimation of the deformations using DL-based approach is feasible for male pelvic anatomy but requires the inclusion of anatomical contours to improve organ correspondence. High variability in the estimation of the accumulated dose depending on the deformable strategy suggests further investigation of DL-based techniques before clinical deployment.

ECMELLA as a bridge to heart transplantation in refractory ventricular fibrillation: A case report.

Background: Extracorporeal membrane oxygenation (ECMO) is an effective cardiorespiratory support technique in refractory cardiac arrest (CA). In patients under veno-arterial ECMO, the use of an Impella device, a microaxial pump inserted percutaneously, is a valuable strategy through a left ventricular unloading approach. ECMELLA, a combination of ECMO with Impella, seems to be a promising method to support end-organ perfusion while unloading the left ventricle. Case summary: The present case report describes the clinical course of a patient with ischemic and dilated cardiomyopathy who presented with refractory ventricular fibrillation (VF) leading to CA in the late postmyocardial infarction (MI) period, and who was successfully treated with ECMO and IMPELLA as a bridge to heart transplantation. Discussion: In the case of CA on VF refractory to conventional resuscitation maneuvers, early extracorporeal cardiopulmonary resuscitation (ECPR) associated with an Impella seems to be the best strategy. It provides organ perfusion, left ventricular unloading, and ability for neurological evaluation and VF catheter ablation before allowing heart transplantation. It is the treatment of choice in cases of end-stage ischaemic cardiomyopathy and recurrent malignant arrhythmias.

Detecting and quantifying spatial misalignment between longitudinal kilovoltage computed tomography (kVCT) scans of the head and neck by using convolutional neural networks (CNNs).

BACKGROUND: Adaptive radiotherapy (ART) aims to address anatomical modifications appearing during the treatment of patients by modifying the planning treatment according to the daily positioning image. Clinical implementation of ART relies on the quality of the deformable image registration (DIR) algorithms included in the ART workflow. To translate ART into clinical practice, automatic DIR assessment is needed. OBJECTIVE: This article aims to estimate spatial misalignment between two head and neck kilovoltage computed tomography (kVCT) images by using two convolutional neural networks (CNNs). METHODS: The first CNN quantifies misalignments between 0 mm and 15 mm and the second CNN detects and classifies misalignments into two classes (poor alignment and good alignment). Both networks take pairs of patches of 33x33x33 mm3 as inputs and use only the image intensity information. The training dataset was built by deforming kVCT images with basis splines (B-splines) to simulate DIR error maps. The test dataset was built using 2500 landmarks, consisting of hard and soft landmark tissues annotated by 6 clinicians at 10 locations. RESULTS: The quantification CNN reaches a mean error of 1.26 mm (± 1.75 mm) on the landmark set which, depending on the location, has annotation errors between 1 mm and 2 mm. The errors obtained for the quantification network fit the computed interoperator error. The classification network achieves an overall accuracy of 79.32%, and although the classification network overdetects poor alignments, it performs well (i.e., it achieves a rate of 90.4%) in detecting poor alignments when given one. CONCLUSION: The performances of the networks indicate the feasibility of using CNNs for an agnostic and generic approach to misalignment quantification and detection.

Image Processing Pitfalls in Vendor Adaptive Radiotherapy Software with Tomotherapy-like Systems: Feedback from Clinical Case Reports.

BACKGROUND: Adaptive radiotherapy (ART) has the potential to reduce the toxicities of radiotherapy and improve overall survival by considering variations in the patient's anatomy during the course of treatment. ART's first commercial solutions are now implemented in clinical radiotherapy departments. However, before they can be used safely with real patients, these solutions must be rigorously evaluated to precisely determine the limits of their use. METHODS: In this paper, we evaluated an offline ART vendor system in 50 patients treated on tomotherapy- like systems for six months. Illustrated by numerous examples of head and neck, thoracic and abdominopelvic localizations, two limitations of image processing used in the ART workflow have been highlighted: deformable image registration (DIR) accuracy and the way the limited field of view (FOV) is compensated. This feedback from clinical experience makes it possible to identify topics of image processing research with strong clinical interest. RESULTS: Current DIR method accuracy may be too weak for some clinical ART applications, and their improvement remains highly important, especially for multimodality registration. Improvements in contour propagation methods also remain crucial today. We showed that there is a need for the development of automatic DIR accuracy quantification methods to help streamline the ART process. Finally, the limited FOV of the onboard images may induce dose calculation errors, highlighting the need to develop new FOV extension methods. CONCLUSION: We have evaluated a vendor ART system, but some image processing pitfalls, such as DIR accuracy and the limited FOV of the onboard images, make its implementation into clinical practice difficult for the moment.