Cramer, Justin

BACKGROUND AND OBJECTIVES: The artery of Davidoff and Schechter (ADS) is a dural branch of the posterior cerebral artery, supplying the falcotentorial junction. It is not commonly depicted on angiography due to its small size; thus, its visibility is usually indicative of a pathology, such as a dural arteriovenous fistula (DAVF). Recognizing the ADS as a feeder could be vital in enhancing management success, and understanding its anatomy is important for preventing complications during embolization or microsurgery. We present a scoping review of DAVFs fed by the ADS followed by an illustrative case report encountered at our institution. METHODS: An extensive literature review was conducted using PubMed, Embase, Web of Science, Scopus, and Cochrane databases. The search included the keywords: “Davidoff,” “Schechter,” “Davidoff and Schechter,” “dural branch,” “tentorial branch,” “medial branch,” and “meningeal branch,” in combination with “arteriovenous fistula,” “posterior cerebral artery,” and “superior cerebellar artery.” Only articles published in English or Spanish were included, with no restriction on publication date. Case reports and series were further screened based on best relevance. Data extraction and synthesis were performed in accordance with Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. RESULTS: A total of 16 articles describing 32 cases of DAVFs supplied by the ADS were identified. The most common onset was headache (43.8%), followed by altered mental status (21.2%). Most DAVFs were classified as high grade based on Borden/Cognard scales. Transarterial embolization was the most used treatment (81.3%), achieving complete occlusion in 76.9% of cases. Among patients with complete occlusion, approximately half experienced full resolution of symptoms. In a mean follow-up of 27.4 months (IQR: 30), 2 cases reported complications due to reflux of the embolic agent. CONCLUSION: A comprehensive understanding of the ADS's angioarchitecture is essential to take full advantage of this artery's features in the treatment, mitigating potential complications and optimizing patient outcomes.

Introduction: Emerging evidence highlights the increased white matter hyperintensity (WMH) burden in APOE4 homozygotes, the greatest genetic risk factor for late-onset Alzheimer's disease (AD). The link between WMH and cerebral amyloid-beta (Aβ) accumulation remains unclear, especially in presymptomatic AD phases. We aimed to determine whether WMH burden (global or regional) mediates the association between APOE4 homozygosity and amyloid-PET Aβ deposition in a population of subjects with intact cognition. Methods: WMH were segmented using a deep learning model applied to T1 and T2-FLAIR MRI scans from 49 cognitively intact individuals older than 50. The global and regional (periventricular, lobar, basal ganglia, infratentorial) WMH volumes were adjusted for total intracranial volume and log-transformed to normalize distribution. Amyloid-PET cerebral Aβ burden was quantified in centiloid units; individuals with centiloid > 20 were classified as Aβ-positive. To examine our mediation hypothesis, we tested three pathways using logistic and linear regression models: 1) Path a, the association between APOE4 and global or regional WMH volumes (outcome); 2) Path b, the association between WMH volumes and Aβ positivity (outcome); 3) Path c (total) and c' (direct) effects of APOE4on Aβ positivity (outcome), before and after adjusting for WMH volumes. All models incorporated age and vascular risk factors (hypertension, diabetes, hypercholesterolemia, cigarette smoking). Results: We included 11 APOE4 homozygotes, of whom 7 were Aβ-positive and 38 non-carriers (35 3/3 and 3 3/2) (6 Aβ-positive). Compared to APOE4 non-carriers, APOE4 homozygotes had significantly greater WMH volumes in the posterior periventricular region only (p= 0.0453) (path a). Homozygotes were significantly more likely to be Aβ-positive compared to non-carriers (total effect, path c p=0.0019). This association remained significant after adjusting for WMH (direct effect, path c'= 0.0027). However, neither global (p=0.72) nor posterior periventricular (p=0.84) WMH volumes predicted Aβ positivity (path b) (Figure). Conclusions: In our cohort of cognitively normal individuals including preclinical AD, neither global nor regional WMH burden mediated the relationship between APOE4 homozygosity and Aβ positivity. Larger studies are needed to further evaluate the mechanistic relationship between WMH and neurodegeneration in APOE4 carriers.

ABSTRACT Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) can reduce seizures in patients with drug-resistant epilepsy. However, seizure freedom is rare, and there is no early response biomarker to predict long-term seizure suppression. To evaluate a short-term biomarker of therapeutic response to DBS, we studied 18-minute trials of ANT stimulation in patients with drug-resistant epilepsy undergoing intracranial electroencephalography. We compared a standard high-frequency periodic versus a non-periodic pulse pattern. We found that short-term ANT stimulation within the clinically used amplitude range preferentially altered the first 150 ms of anterograde ANT to anterior cingulate and superior frontal connectivity. Non-periodic ANT stimulation selectively modified early cortico-cortical evoked potentials more than periodic stimulation, and these changes were driven by the response phase. These pattern-specific changes in connectivity between the ANT and spatially restricted cortical areas suggest differing mechanisms and are a promising biomarker for patients being treated with ANT-DBS.

Purpose White matter hyperintensity (WMH) is associated with heterogeneous pathologies. In neurodegeneration, the prevailing hypothesis is that WMH primarily reflects vascular pathology, exerting an additive effect in AD. Alternatively, a subset of WMH may arise secondary to AD‐related pathophysiology. APOE4 genotype, the greatest genetic risk factor for late‐onset AD, impacts the blood‐brain barrier and WMH burden. Herein, we investigate the association between regional WMH burden and APOE4 allelic dosage in cognitively normal individuals. Methods We used deep learning to automatically segment WMH from T2‐FLAIR MRI from 154 cognitively intact individuals older than 50. We mapped WMH to 4 specific brain regions (lobar, periventricular, basal ganglia and infratentorial, further parcellated into sub‐regions, Table 1) using atlas‐based registration and FastSurfer. WMH volumes were adjusted for total intracranial volume and normalized using log transformation. The APOE4 groups were compared for WMH burden using linear regression, controlling for age and vascular risk factors (hypertension, diabetes, hypercholesterolemia, cigarette smoking). For brain regions where more than 20% of participants had no WMH, a two‐part hurdle model was applied. Results We included 13 APOE4 homozygotes, 50 heterozygotes (ε4/ ε3) and 91 non‐carriers. Compared to non‐carriers, APOEε4 homozygotes exhibited significantly greater WMH burden in the whole brain, periventricular (posterior) and lobar regions (Figure 1a). Homozygotes exhibited a significantly greater WMH burden in the whole brain and posterior periventricular region, when compared to heterozygotes (Figure 1b). No significant whole‐brain or region‐specific differences were observed between heterozygotes and non‐carriers (Figure 1c). Conclusion In cognitively intact individuals at risk for AD, APOE4 homozygosity is associated with significantly greater WMH burden, particularly in the posterior periventricular space, after controlling for age and vascular risk factors. The relationship between regional‐specific WMH burden and neurodegeneration warrants further investigation. image image

Abstract BACKGROUND Volumetric analysis of brain metastatic lesions is of great relevance in neuro-oncology. Since manual annotation of a lesion is a laborious and time-consuming task, utilizing artificial intelligence (AI) tools for automated segmentation of brain metastases has shown promising potential, but published algorithms are not incorporated into clinical practice because of poor generalizability across institutions. Large publicly available and well-annotated datasets from across the world are critical for further clinical translation. MATERIAL AND METHODS The Brain Tumor Segmentation - Metastases (BraTS-METS) 2025 Lighthouse Challenge provides a competitive environment where scientists from various disciplines can benchmark their AI-based algorithms for automatic segmentation of pre- and post-treatment brain metastases on a well-curated publicly available brain metastasis dataset comprising 1,778 multiparametric brain MRI cases. Each case consists of T1-weighed, T1 post-contrast and FLAIR sequences. The cases were retrospectively obtained from 8 institutions in the USA and overseas, and underwent 3D nnU-Net pre-segmentation, followed by manual refinements performed by medical students and neuroradiologists, and a final approval by two independent board-certified neuroradiologists. A testing dataset was prepared through four rounds of annotation: two completed ‘from scratch’ and two following 3D nnU-Net pre-segmentation, all conducted by two independent neuroradiologists, with the segmentation process screen recorded for future analysis. This allowed us to establish inter- and intra-rater variability in brain metastases segmentation and create a reference standard dataset that will be publicly available after the conclusion of the challenge. The model performance of the participating teams in the challenge will be assessed via the following metrics: Dice Similarity Coefficient (DSC), Normalized Surface Distance (NSD), sensitivity, and precision of the model. RESULTS A multi-annotator testing dataset of 75 MRI cases of brain metastases and 300 segmentations (150 created ‘from scratch’ and 150 from 3D nnU-Net pre-segmentations of the cases) was developed as a new reference standard. The mean intra- and inter-rater DSC for the segmentations ‘from scratch’ were 0.68 and 0.59, respectively. The mean intra- and inter-rater DSC for the segmentations built upon 3D nnU-Net pre-segmentations were 0.88 and 0.77, respectively. CONCLUSION The BraTS-METS 2025 Lighthouse Challenge is a key initiative designed to advance the use of AI to improve characterization of brain metastases by providing algorithms for automatic segmentation of all lesions and peritumoral edema that are measured against a novel reference standard based on rigorous multi-annotator brain MRI segmentations.

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well- annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied environments and providing the tools for future development of personalized volumetric reports to patients undergoing BM treatment.

Introduction: Although primarily supplied by the vertebrobasilar system, the hippocampus is partially supplied by ipsilateral carotid artery branches through the anterior choroidal artery or a prominent posterior communicating artery. We report a patient with acute hippocampus infarction likely due to symptomatic ipsilateral tandem carotid stenosis and discuss acute vascular-mediated hippocampal injury. Case Report: An 80-year-old female with obesity, dyslipidemia, hypertension, alcohol use disorder, history of breast cancer on letrozole, and traumatic brain injury was brought into our emergency department for 24 hours of confusion. On examination, she exhibited limited registration, recall, and executive dysfunction with otherwise normal language, visuo-spatial orientation, and praxis. Brain MRI showed a small area of diffusion restriction in the anterior right hippocampus with matched FLAIR hyperintensity, consistent with acute infarction. Computed tomography angiogram head and neck showed 90% stenosis of the proximal right internal carotid artery (ICA), <50% narrowing of the proximal left ICA, and moderate bilateral narrowing of the paraclinoid ICAs, all due to calcific atheromatous plaques. The etiology of the hippocampal infarction was suspected embolism from the ipsilateral severe carotid stenosis. Planning for right cervical carotid revascularization ensued. Conclusion: This case highlights the dual hippocampal vascular supply and that hippocampal embolic infarcts could be a sign of a symptomatic severe carotid artery stenosis that may require urgent revascularization for stroke secondary prevention.

Hippocampal segmentation is essential in neuroimaging for evaluating conditions like Alzheimer’s dementia and mesial temporal sclerosis, where small volume changes can significantly impact normative percentiles. However, inaccurate segmentation is common due to the inclusion of non-hippocampal structures such as choroid plexus and cerebrospinal fluid (CSF), leading to volumetric overestimation and confounding of functional analyses. Current methods of assessment largely rely on virtual or manual ground truth labels, which can fail to capture these inaccuracies. To address this shortcoming, this study introduces a more direct voxel intensity-based method of segmentation assessment. Using paired precontrast and postcontrast T1-weighted MRIs, hippocampal segmentations were refined by adding marginal gray matter and removing marginal CSF and enhancement to determine a total required correction volume. Six segmentation algorithms—e2dhipseg, HippMapp3r, hippodeep, AssemblyNet, FastSurfer, and QuickNat—were implemented and compared. HippMapp3r and e2dhipseg, followed closely by hippodeep, exhibited the least total correction volumes, indicating superior accuracy. Dedicated hippocampal segmentation algorithms outperformed whole-brain methods.