Deformable medical image registration is a fundamental task in medical image analysis. While deep learning-based methods have demonstrated superior accuracy and computational efficiency compared to traditional techniques, they often overlook the critical role of regularization in ensuring robustness and anatomical plausibility. We propose DARE (Deformable Adaptive Regularization Estimator), a novel registration framework that dynamically adjusts elastic regularization based on the gradient norm of the deformation field. Our approach integrates strain and shear energy terms, which are adaptively modulated to balance stability and flexibility. To ensure physically realistic transformations, DARE includes a folding-prevention mechanism that penalizes regions with negative deformation Jacobian. This strategy mitigates non-physical artifacts such as folding, avoids over-smoothing, and improves both registration accuracy and anatomical plausibility

PURPOSE Accurate target volume delineation is critical for effective stereotactic radiotherapy (SRT) of brain metastases. This study systematically investigates how MRI sequence selection and the time elapsed after contrast agent (CA) administration affect the apparent metastases volumes, with the goal of optimizing MRI protocols for radiation therapy planning. MATERIALS AND METHODS A total of 49 patients with 414 brain metastases were included and randomized into 6 groups with varying imaging sequences (MPRAGE, SPACE, and VIBE) and timepoints after CA administration. Lesions smaller than 0.03 cm3 were excluded due to resolution limitations. Lesion volumes were independently assessed by radiology and radiation oncology specialists, and mean values were analyzed. The effects of MRI sequence and time delay on lesion volume were evaluated using t tests, ANOVA, and multiple linear regression. RESULTS Both MRI sequence and CA timing significantly influenced measured volumes. On average, SPACE volumes were 20% larger than MPRAGE, and VIBE volumes were 10% larger than SPACE, independent of timing. Lesion volumes increased progressively with time after CA administration at rates of 0.63%, 0.58%, and 0.36% per minute for MPRAGE, SPACE, and VIBE, respectively. Smaller lesions (<1 cm3) showed greater relative intersequence differences, primarily due to variations in visible lesion borders. CONCLUSIONS Both MRI sequence choice and imaging time after CA administration significantly affect the apparent volume of brain metastases in SRT planning. Although SPACE and VIBE sequences enhance small lesion detection, they may also increase border blurring and inter-rater variability. Standardizing protocols to account for these factors is essential for improving delineation accuracy, reducing toxicity risk, and optimizing SRT outcomes.

Occlusive cervical artery dissection (CeAD) is associated with worse patient outcome. The net clinical benefit of acute revascularization measures has to be weighed against the likelihood of spontaneous recanalization. Our aim was to assess the hitherto un-addressed impact of spontaneous recanalization on stroke risk in patients with occlusive CeAD. MRI verified CeAD patients with initially occlusive CeAD within cohort study that did not undergo acute revascularization measures were assessed. Follow-up data derived from clinical routine and study specific assessments. Outcomes of interest were occurrence of (i) recanalization and (ii) ischemic stroke upstream of CeAD-related occlusion. Adjusted logistic regression analysis addressed the impact of recanalization on said outcomes. 97/328 (29.6%) patients had occlusive CeAD and did not undergo acute revascularization treatment. Upon follow-up, 56/97 (57.7%) showed spontaneous recanalization of initially occlusive CeAD. Female sex (OR 0.41[0.18, 0.97]; P = 0.043) and internal carotid artery dissection (OR 0.33[0.14, 0.78]; P = 0.012) were the only factors independently associated with recanalization. Within a median follow-up of 8.2 (1.58, 12.8) years, a total of 18/97 (18.6%) patients suffered ischemic stroke upstream of the initially CeAD-affected vessel. After adjusting for confounders, spontaneous recanalization was independently associated with lower rates of cerebral ischemia upon follow-up (OR 0.28[0.09, 0.90]; P = 0.032), most notably also independent of type of antithrombotic treatment. Spontaneous recanalization in occlusive CeAD is associated with lower rates of stroke upon follow-up. These results indicate that persistent CeAD-related occlusion remains a risk-factor for recurrent ischemic events, thus calling for future trials addressing optimal medical treatment. N/A. Lukas Mayer-Suess.

Background: Comorbid personality disorders (PDs) in patients with anorexia nervosa (AN) are associated with increased psychopathology, higher suicide risk, and poorer treatment response and outcomes. This study aimed to examine associations between gray matter (GM) volume and PDs in female adolescents with AN before and after short-term psychotherapeutic and nutritional therapy. Methods: Eighteen female adolescents with acute AN, mean age 15.9 years, underwent 3T magnetic resonance imaging before and after weight restoration. The average interval between scans was 2.6 months. Structural brain changes were analyzed using voxel-based morphometry. PDs were assessed using the Structured Clinical Interview for DSM-IV Axis II Disorders (SCID II) and the Assessment of Identity Development Questionnaire. Results: SCID-II total scores showed significant positive associations with GM volume in the mid-cingulate cortex at both time points and in the left superior parietal–occipital lobule at baseline. The histrionic subscale correlated with GM volume in the thalamus bilaterally and the left superior parietal–occipital lobule in both assessments, as well as with the mid-cingulate cortex at follow-up. Borderline and antisocial subscales were associated with GM volume in the thalamus bilaterally at baseline and in the right mid-cingulate cortex at follow-up. Conclusions: PDs in female adolescent patients with AN may be specifically related to GM alterations in the thalamus, cingulate, and parieto-occipital regions, which are present during acute illness and persist after weight restoration therapy.

There are differing results in recent literature concerning aneurysmal wall enhancement (AWE) after endovascular treatment (ET) of intracranial aneurysms (IAs). The aim of this retrospective study is to investigate if the presence of AWE of unruptured treated IAs via stent-assisted coiling (SAC) is associated with higher reperfusion rates. The clinical courses of 58 patients with IAs after ET via SAC were examined over the timespan of up to 5 years, assessing for AWE in T1 SPACE FS and T1 SE FS blood suppression sequences after contrast administration, events of reperfusion and need for retreatment. 58 patients were included (23 with AWE, 35 without). 18 of 23 patients (78.3%) with AWE showed reperfusion after treatment, compared to 15 of 35 patients (42.9%) without AWE. Reperfusion rates were significantly higher in patients with AWE, compared to those without AWE (p = 0.0139) also after propensity score matching (p = 0.0456). In patients with unruptured IAs treated exclusively with SAC, AWE on follow-up MRI was significantly associated with higher reperfusion rates. AWE may serve as an early imaging biomarker of post-treatment instability.

The analysis of carotid arteries, particularly plaques, in multi-sequence Magnetic Resonance Imaging (MRI) data is crucial for assessing the risk of atherosclerosis and ischemic stroke. In order to evaluate metrics and radiomic features, quantifying the state of atherosclerosis, accurate segmentation is important. However, the complex morphology of plaques and the scarcity of labeled data poses significant challenges. In this work, we address these problems and propose a semi-supervised deep learning-based approach designed to effectively integrate multi-sequence MRI data for the segmentation of carotid artery vessel wall and plaque. The proposed algorithm consists of two networks: a coarse localization model identifies the region of interest guided by some prior knowledge on the position and number of carotid arteries, followed by a fine segmentation model for precise delineation of vessel walls and plaques. To effectively integrate complementary information across different MRI sequences, we investigate different fusion strategies and introduce a multi-level multi-sequence version of U-Net architecture. To address the challenges of limited labeled data and the complexity of carotid artery MRI, we propose a semi-supervised approach that enforces consistency under various input transformations. Our approach is evaluated on 52 patients with arteriosclerosis, each with five MRI sequences. Comprehensive experiments demonstrate the effectiveness of our approach and emphasize the role of fusion point selection in U-Net-based architectures. To validate the accuracy of our results, we also include an expert-based assessment of model performance. Our findings highlight the potential of fusion strategies and semi-supervised learning for improving carotid artery segmentation in data-limited MRI applications.

Background/Objectives: In consideration of the significance of the pursuit of training-induced neuroplastic changes in the stroke population, who are reliant on neurorehabilitation treatment for the restoration of neuronal function, the objectives of this trial were to investigate fMRI paradigms for acute stroke patients with ataxic symptoms, to follow up on changes in motor function and balance due to recovery and rehabilitation, and to investigate the different effects of two treatment methods on neuronal plasticity. Methods: Therefore, fMRI-paradigms foot tapping and the motor imagery (MI) of a balancing task (tandem walking) were employed. Results: The paradigms investigated were suitable for ataxic stroke patients to monitor changes in neuroplasticity while revealing increased activity in the primary motor cortex (M1) and the cerebellum over 3 months of treatment. Furthermore, analysis of the more complex balance task revealed augmented activation of association areas due to training. Coordination exercises, constituting a specific treatment of ataxic symptoms, indicate more consolidated brain activations, corresponding to a faster motor learning process. Activation within Brodmann Area 7 has been prominent among all paradigms, indicating a special importance of this region for coordinative functions. Conclusions: Further studies are needed to confirm our results in larger patient groups. Clinical Trial Registration: German Clinical Trials Registry (drks.de). Identifier: DRKS00020825. Registered 16.07.2020.

Background/Objectives: Large language models (LLMs), such as ChatGPT, have emerged as potential clinical support tools to enhance precision in personalized patient care, but their reliability in radiological image interpretation remains uncertain. The primary aim of our study was to evaluate the diagnostic accuracy of ChatGPT-4o in interpreting chest X-rays (CXRs) and abdominal X-rays (AXRs) by comparing its performance to expert radiology findings, whilst secondary aims were diagnostic confidence and patient safety. Methods: A total of 500 X-rays, including 257 CXR (51.4%) and 243 AXR (48.5%), were analyzed. Diagnoses made by ChatGPT-4o were compared to expert interpretations. Confidence scores (1–4) were assigned and responses were evaluated for patient safety. Results: ChatGPT-4o correctly identified 345 of 500 (69%) pathologies (95% CI: 64.81–72.9). For AXRs 175 of 243 (72.02%) pathologies were correctly diagnosed (95% CI: 66.06–77.28), while for CXRs 170 of 257 (66.15%) were accurate (95% CI: 60.16–71.66). The highest detection rates among CXRs were observed for pulmonary edema, tumor, pneumonia, pleural effusion, cardiomegaly, and emphysema, and lower rates were observed for pneumothorax, rib fractures, and enlarged mediastinum. AXR performance was highest for intestinal obstruction and foreign bodies, and weaker for pneumoperitoneum, renal calculi, and diverticulitis. Confidence scores were higher for AXRs (mean 3.45 ± 1.1) than CXRs (mean 2.48 ± 1.45). All responses (100%) were considered to be safe for the patient. Interobserver agreement was high (kappa = 0.920), and reliability (second prompt) was moderate (kappa = 0.750). Conclusions: ChatGPT-4o demonstrated moderate accuracy for the interpretation of X-rays, being higher for AXRs compared to CXRs. Improvements are required for its use as efficient clinical support tool.

Background: The accidental puncture of the supra-aortal arteries during central venous catheterization is a rare but potentially life-threatening complication. Traditional management often requires open surgical repair, which is associated with significant morbidity. This study evaluates an endovascular approach for managing such cases using an Angio-Seal™ vascular closure device (Terumo Medical Corporation, Somerset, NJ, USA). Methods: Between January 2010 and December 2024, 47 patients with misplaced catheters in supra-aortal arteries were treated at our institution. Of these, 37 cases involving subclavian artery catheter misplacements were managed using a standardized algorithm and form the focus of this study. Additional interventions, such as stent graft placement or balloon inflation, were performed as needed. Results: Primary technical success was achieved in 86.5% of cases. Four patients required stentgrafts and one balloon inflation for persistent extravasations. One patient developed a small subclavian pseudoaneurysm, which resolved spontaneously. Primary assisted technical success and clinical success rates were both 100%. Conclusions: This study demonstrates the efficacy and safety of our minimally invasive endovascular approach for managing subclavian artery catheter misplacements. With a high success rate, low complication rate, and the avoidance of open surgery, this algorithm offers a promising alternative for treating this rare but serious complication of central venous catheterization.

Background: Blunt traumatic aortic injury (BTAI) is the second most common cause of death following blunt trauma, and it can affect people of all ages. The aim of this study was to evaluate age-related differences in outcomes among patients undergoing thoracic endovascular aortic repair (TEVAR) for BTAI. Methods: All patients treated with TEVAR for BTAI at a tertiary care center in Europe between 2005 and 2023 were included in this study. All clinical and imaging data were collected and analyzed retrospectively. Results: A total of 70 patients with a median age of 43 years were included, and 89% were male. Older patients had significantly higher American Society of Anesthesiologists (ASA) physical status classification scores (p < 0.001) compared to younger patients. All age groups (<18, 18–40, 41–65, and >65) exhibited low to borderline low initial hemoglobin levels with a further decline over time (p = 0.063, p < 0.001, p < 0.001, and p = 0.018, respectively). Age groups were comparable regarding injury mechanism, Injury Severity Score (ISS), concomitant injuries and postoperative complications. The age-independent ISS showed a moderate to strong correlation to the length of intensive care unit stay (r = 0.594, p < 0.001). Total in-hospital mortality was 6% and none was from aortic-related complications. There was a generally high rate of loss of follow-up (59%). Conclusions: Although older patients presented worse ASA scores in comparison to younger patients, no significant differences regarding postoperative morbidity/mortality were noted. These findings imply that patient age and preinjury physical status might not substantially influence outcomes when treating BTAI with TEVAR.

Introduction The increasing prevalence of Alzheimer’s disease (AD) has created an urgent need for rapid and cost-effective methods to diagnose and monitor people at all stages of the disease. Progressive memory impairment and hippocampal atrophy are key features of the most common so-called typical variant of AD. However, studies evaluating detailed cognitive measures combined with region of interest (ROI)-based imaging markers of progression over the long term in the AD dementia (ADD) stage are rare. Method We conducted a retrospective longitudinal follow-up study in patients with mild to moderate ADD (aged 60-92 years). They underwent magnetic resonance imaging (MRI; 3 Tesla, MPRAGE) as well as clinical and neuropsychological examination (Consortium to Establish a Registry for Alzheimer’s Disease [CERAD] -Plus test battery) at baseline and at least one follow-up visit. ROI-based brain structural analysis of baseline MRIs was performed using the Computational Anatomy Toolbox (CAT) 12. Clinical dementia progression (progression index [PI]) was measured by the annual decline in the Mini Mental State Examination (MMSE) scores. MRI, demographic, and neuropsychological data were included in univariate and multiple linear regression models to predict the PI. Results 104 ADD patients (age 63 to 90 years, 73% female, mean MMSE score 22.63 ± 3.77, mean follow-up 4.27 ± 2.15 years) and 32 age- and gender-matched cognitively intact controls were included. The pattern of gray matter (GM) atrophy and the cognitive profile were consistent with the amnestic/typical variant of ADD in all patients. Deficits in word list learning together with temporal lobe GM atrophy had the highest predictive value for rapid cognitive decline in the multiple linear regression model, accounting for 25.4% of the PI variance. Discussion Our results show that temporal atrophy together with deficits in the encoding of verbal material, rather than in immediate or delayed recall, is highly predictive for rapid cognitive decline in patients with mild to moderate amnestic/typical ADD. These findings point to the relevance of combining detailed cognitive and automated structural imaging analyses to predict clinical progression in patients with ADD.

Background Pharmacological treatment options for patients with dementia owing to Alzheimer's disease are limited to symptomatic therapy. Recently, the US Food and Drug Administration approved the monoclonal antibody lecanemab for the treatment of amyloid-positive patients with mild cognitive impairment (MCI) and early Alzheimer´s dementia. European approval is expected in 2024. Data on the applicability and eligibility for treatment with anti-amyloid monoclonal antibodies outside of a study population are lacking. Aims This study examined eligibility criteria for lecanemab in a real-world memory clinic population between 1 January 2022 and 31 July 2023. Method We conducted a retrospective, single-centre study applying the clinical trial eligibility criteria for lecanemab to out-patients of a specialised psychiatric memory clinic. Eligibility for anti-amyloid treatment was assessed following the phase 3 inclusion and exclusion criteria and the published recommendations for lecanemab. Results The study population consisted of 587 out-patients. Two-thirds were diagnosed with Alzheimer's disease (probable or possible Alzheimer's disease dementia in 43.6% of cases, n = 256) or MCI (23%, n = 135), and 33.4% (n = 196) were diagnosed with dementia or neurocognitive disorder owing to another aetiology. Applying all lecanemab eligibility criteria, 11 (4.3%) patients with dementia and two (1.5%) patients with MCI would have been eligible for treatment with this compound, whereas 13 dementia (5.1%) and 14 (10.4%) MCI patients met clinical inclusion criteria, but had no available amyloid status. Conclusions Even in a memory clinic with a good infrastructure and sufficient facilities for dementia diagnostics, most patients do not meet the eligibility criteria for treatment with lecanemab.

Background: A better understanding of the peritumoral stroma changes due to tumour invasion using non-invasive diagnostic methods may improve the differentiation between benign and malignant breast lesions. This study aimed to assess the correlation between breast lesion differentiation and intra- and peritumoral shear-wave elastography (SWE) gradients. Methods: A total of 135 patients with newly diagnosed breast lesions were included. Intratumoral, subsurface, and three consecutive peritumoral SWE value measurements (with three repetitions) were performed. Intratumoral, interface, and peritumoral gradients (Gradient 1 and Gradient 2) were calculated using averaged SWE values. Statistical analysis included descriptive statistics and an ordinary one-way ANOVA to compare overall and individual gradients among Breast Imaging-Reporting and Data System (BI-RADS) 2, 3, and 5 groups. Results: Malignant tumours showed higher average SWE velocity values at the tumour centre (BI-RADS 2/3: 4.1 ± 1.8 m/s vs. BI-RADS 5: 4.9 ± 2.0 m/s, p = 0.04) and the first peritumoral area (BI-RADS 2/3: 3.4 ± 1.8 m/s vs. BI-RADS 5: 4.3 ± 1.8 m/s, p = 0.003). No significant difference was found between intratumoral gradients (0.03 ± 0.32 m/s vs. 0.0 ± 0.28 m/s; p > 0.999) or gradients across the tumour–tissue interface (−0.17 ± 0.18 m/s vs. −0.13 ± 0.35 m/s; p = 0.202). However, the first peritumoral gradient (−0.16 ± 0.24 m/s vs. −0.35 ± 0.31 m/s; p < 0.0001) and the second peritumoral gradient (−0.11 ± 0.18 m/s vs. −0.22 ± 0.28 m/s; p = 0.037) were significantly steeper in malignant tumours. The AUC was best for PTG1 (0.7358) and PTG2 (0.7039). A threshold value for peritumoral SWI PT1 above 3.76 m/s and for PTG1 below −0.238 m/s·mm−1 indicated malignancy in 90.6% of cases. Conclusions: Evaluating the peritumoral SWE gradient may improve the diagnostic pre-test probability, as malignant tumours showed a significantly steeper curve of the elasticity values in the peritumoral stroma compared to the linear regression with a relatively flat curve of benign lesions.