Cancer predisposition syndromes (CPSs) are a group of inherited disorders that significantly increase the risk of developing various cancers, ranging from infancy through adulthood. CPSs account for about 10% of the pediatric cancers, and they represent a major cause of morbidity and mortality in affected children. The inheritance pattern and the variable penetrance influence the age of onset and the clinical course, resulting in substantial variation in presentation, even within a single family. Early recognition of CPSs is crucial, as timely diagnosis allows for health surveillance, preventive interventions, and genetic counselling for patients and their families. Guidelines and surveillance programs have been developed to identify at-risk patients and coordinate long-term care. This review focuses on the most common CPSs associated with pediatric cancers, with particular emphasis on the involvement of the head and neck region. For each syndrome, we provide a background summary including its genetics and clinical manifestations, followed by a detailed description of characteristic head and neck imaging findings. Illustrative case examples are then presented to demonstrate the spectrum of clinical and imaging features. It highlights imaging features to assist providers reading these studies in the early identification of all possible pathological manifestations in these syndromes. Key CPSs covered include retinoblastoma, Li-Fraumeni syndrome, neurofibromatosis type 1, DICER1 syndrome, rhabdoid tumor predisposition syndrome, Gorlin-Goltz syndrome, hereditary paraganglioma-pheochromocytoma syndrome, constitutional mismatch repair deficiency syndrome, and neuroblastoma predisposition syndrome.
Previous studies have identified hemispheric asymmetries in cerebral blood flow and volume, favoring the left hemisphere. Accordingly, we hypothesized that arteries on the left side of the circle of Willis (CoW) are larger than on the right. We compared artery diameters between the hemispheres. Cranial time-of-flight magnetic resonance angiography scans of 1052 participants from a population-based cohort were assessed. Diameters of major CoW arteries (> 1.2 mm) were measured using a semiautomatic tool (mean ± standard deviation) and compared between the left and right hemisphere using a paired-samples t-test. As the posterior communicating arteries (Pcom) are often small and non-normally distributed, they were measured manually, categorized as "present" (≥ 1 mm) or "aplastic/hypoplastic" (< 1 mm), and compared using odds ratios (OR) with 95% confidence intervals (CI). The A2 segment of the anterior cerebral artery was smaller on the left than on the right (1.97 ± 0.21 mm vs. 2.01 ± 0.22 mm; p < 0.001), while the vertebral artery (2.36 ± 0.44 mm vs. 2.25 ± 0.41 mm; p < 0.001) and P1 segment of the posterior cerebral artery (2.01 ± 0.28 mm vs. 1.98 ± 0.29 mm; p = 0.001) were larger on the left. The Pcom was less frequently present on the left (26.7%) than on the right (33.4%; OR 0.73, 95% CI 0.60-0.88). No left-right differences were found for the A1 segment, M1 segment of the middle cerebral artery, and internal carotid artery. We found that some vessels were larger in the left hemisphere, whereas others were smaller. Future studies should investigate underlying mechanisms driving these specific asymmetries.
Several studies have demonstrated the amelioration of refractory migraines with middle meningeal artery (MMA) intra-arterial lidocaine infusion, but the durability beyond 1 month is not well studied, and the angiographic dose response of lidocaine infusion was not previously evaluated. We aimed to assess the efficacy of middle meningeal artery lidocaine infusion in the treatment of refractory migraines at a 3-month follow-up. We quantified the response to intra-arterial lidocaine infusion (maximum dose of 150 mg) in patients with refractory migraine using the Migraine Disability Assessment (MIDAS) evaluated pre- and posttreatment. At 3 months, We determined the MIDAS score changes, the proportion of responders (≥50% MIDAS reduction), the proportion of patients with "no disability" (MIDAS Grade 1), and the cessation of opioid medication for headache management measured at the last known follow-up. An angiographic dose response was quantified. Eight patients were included in our analysis (mean age of 49.1 ± 13.2 years; 87.5% were women). The cohort comprised equal numbers of unilateral and bilateral MMA lidocaine infusions (4 each), with doses titrated from 50 to 150 mg per procedure. At 3 months posttreatment, the mean MIDAS score improved from 86.3 ± 40.1 to 23.5 ± 26.8 (p = 0.001, paired t-test), and 62.5% of the patients showed 50% MIDAS score reduction. The disability pre-treatment was classified as "severe disability" in all patients, and 50% achieved "no disability" (MIDAS Grade 1) at 3 months posttreatment. No adverse events were reported in any of the procedures. At last known follow-up of a median period of 9.8 months [range 4-21 months], three out of the four patients who were on opioid medication pre-treatment discontinued their opioid medications following MMA lidocaine infusion. Intra-arterial lidocaine infusion was associated with sustained improvement at 3 months posttreatment in 50% of patients with refractory migraines.
Cerebral collateral circulation is a critical determinant of infarct evolution, therapeutic response, and clinical outcomes in patients with acute ischemic stroke. While the concept of "time is brain" has traditionally guided reperfusion therapy, recent evidence-particularly from trials like DAWN and DEFUSE 3-suggests that collateral status more accurately determines the rate of infarct progression and the extent of salvageable tissue. This comprehensive review synthesizes advances in neuroimaging modalities for evaluating cerebral collaterals, emphasizing their role in refining stroke diagnosis, guiding patient selection, and informing personalized treatment strategies. Structural approaches such as multiphase and dynamic CT angiography, alongside perfusion-based parameters (e.g., cerebral blood volume, hypoperfusion intensity ratio, and Tmax delay maps), are examined. Cortical venous outflow, assessed via the cortical vein opacification score, emerges as an independent predictor of outcome, complementing arterial grading. Susceptibility-weighted imaging, arterial spin labeling, and metabolic and molecular techniques (e.g., PET imaging of inflammation and vascular remodeling) offer functional insights beyond traditional angiography. Biomarkers such as matrix metalloproteinase-9, integrin αvβ3, and translocator protein-targeted PET ligands are discussed in relation to collateral vessel dynamics. Finally, we explore the integration of genetically informed brain atlases, spatial transcriptomics, and imaging-genomic platforms for high-resolution collateral phenotyping. Although promising, these modalities face challenges related to heterogeneity, limited validation, and the lack of standardization. A biologically informed, multimodal, and automated imaging paradigm may herald a new era of precision stroke medicine.
Task-based functional MRI (fMRI) can identify spatial and temporal brain configurations of blood-oxygen-level-dependent (BOLD) activity for dissociable cognitive functions. Evidence for the discriminability of spatial/temporal/functional combinations (i.e., cognitive modes) can be achieved through the dissociation of task-based BOLD signal changes following whole-brain dimension reduction. A double dissociation can be achieved by task-induced BOLD-change activation of mode A in condition A but not B, and vice versa for activation in mode B. In this study, we analyzed the Coherence-Semantic task from the Midnight Scan Club dataset to test for a double dissociation of Focus on Visual Features (FoVF) from Language (LAN) modes. The Coherence-Semantic task involved 10 healthy participants scanned over 10 sessions on a 3-Tesla MRI scanner. The task included (1) identifying coherent or random movements of dots (Coherence condition) and (2) identifying a noun versus a verb (Semantic condition). fMRI data were analyzed by combining finite impulse response multivariate multiple regression with whole-brain dimensionality reduction. The dissociations were evaluated at the level of subject-specific task-induced BOLD changes using repeated-measures ANOVAs comparing the Coherence and Semantic conditions. A double dissociation was observed: FoVF showed task-induced increases in BOLD activation during the Coherence condition, with no significant task-related activation during the Semantic condition, and vice versa for LAN. The default mode (DM) also showed task-related deactivation in both conditions. This double dissociation provides evidence for the temporal and functional discriminability of FoVF and LAN, contributing to evidence supporting the discriminability of cognitive modes detectable by fMRI.
Stroke is a leading cause of epilepsy, especially in older adults. The SeLECT score remains the standard among post-stroke epilepsy (PSE) prediction tools. However, its broader validation is limited by the need to manually extract neuroimaging predictors (cortical and middle cerebral artery [MCA] involvement). Unlike the CAVE score, SeLECT did not evaluate acute stroke volume, which can now be quantified automatically. We aimed to determine whether stroke volume independently predicts PSE and compare its predictive contribution to SeLECT's neuroimaging variables. SeLECT variables were manually extracted. Diffusion-weighted imaging volume was quantified using a validated convolutional neural network. Cox proportional hazards models for time to PSE were built by adding stroke volume (per 10 mL) and then removing cortical and/or MCA involvement. For each model, we analyzed variable significance, discrimination, and calibration. Among 221 patients, 35 (15.8%) developed PSE. In our cohort, the original SeLECT score and the refit model had a C-index of 0.669 and 0.642, respectively. Adding stroke volume resulted in a C-index of 0.656. Retaining volume while removing cortical and MCA involvement resulted in C-indices of 0.664 and 0.668, respectively. Keeping stroke volume and removing both variables increased the C-index to 0.679. Calibration was good for all models. Stroke volume in crease by 10 mL was an independent predictor of 12% increased PSE risk across all models. Acute stroke volume is an independent PSE predictor. Stroke volume offered comparable discrimination to the neuroimaging components of the SeLECT score, supporting its use as a scalable and automated alternative.
To determine the diagnostic accuracy of median nerve ultrasound in suspected cases of carpal tunnel syndrome (CTS) in a prospective, real-world study. This prospective study was carried out over one year at Roy Neuro Care Centre, Ranchi, Jharkhand, India. The clinical, electrophysiologic, and ultrasonographic findings in suspected cases of CTS were collected. A history and physical examination consistent with CTS were considered the gold standard for diagnosis. A total of 134 patients with symptoms suggestive of CTS were enrolled, and both wrists were examined. The diagnostic accuracy of various ultrasound parameters including maximum cross-sectional area (CSA) of the median nerve in the tunnel, difference between CSA at the level of the pronator quadratus compared to the carpal tunnel, and wrist-to-forearm ratio were evaluated by individual, parallel, and serial testing strategies using optimal cut-off values determined by the Youden Index. Parallel testing provided the highest sensitivity, making it suitable for screening, whereas serial testing produced the highest overall accuracy. Median nerve ultrasound is an accurate diagnostic tool for CTS in a real-world setting.
Chimeric antigen receptor-engineered T-cell (CAR-T) therapy in hematological malignancies may be associated with severe complications, as Cytokine Release Syndrome (CRS) and Immune effector Cell-Associated Neurotoxicity Syndrome (ICANS). The aim of the study is to investigate MRI-derived macrostructural and microstructural features potentially able to identify patients at higher ICANS risk. Forty-two patients treated with CAR-T from October 2020 to June 2025 performed brain MRIs before CAR-T administration, including diffusion-weighted imaging. A general linear model was used to compare patients who developed ICANS, CRS, or neither at baseline in terms of MRI macro- and microstructural features. A binary logistic regression analysis was performed to evaluate the role of microstructural features in predicting the risk of developing ICANS. Mean age 59.2 ± 13 years, 59.5% male; 21 (50%) patients received tisagenlecleucel, 21 (50%), axicabtagene ciloleucel or brexucabtagene autoleucel; 14 (33%) and 31 (73.8%) patients developed ICANS and CRS, respectively. At baseline MRI, fluid-attenuated inversion recovery (FLAIR) white matter (WM) hyperintensities were detected in 41/42 (97.6%). No significant differences between patients who developed ICANS, CRS and neither both were observed in terms of FLAIR hyperintensities nor total brain volume at baseline. Fractional anisotropy extracted from FLAIR hyperintensities and WM areas without macroscopic abnormalities was a predictor of ICANS in the logistic regression model (p = 0.03 and 0.02, respectively). FLAIR hyperintensities and brain volume prior to CAR-T were not informative, whereas the severity of WM microstructural (axonal) damage predicted ICANS risk. Greater axonal damage was associated with a higher likelihood of ICANS.
Amygdala dysfunction is implicated in major depressive disorder. Despite wide acknowledgement of its heterogeneity, the amygdala is predominantly considered as a single entity and functional connectivity investigations have reported findings using standard or low spatial resolution functional MRI data. This study compared the capabilities of two high spatial resolution acquisition strategies, the gold standard 2D and a novel 3D, in identifying amygdala functional connectivity to other brain regions at a subregional level. Resting state fMRI data were acquired at 3T in 10 healthy controls using both versions of a Gradient-Echo Echo Planar Imaging (GRE-EPI) sequence. Whole brain voxel-wise functional connectivity measures were calculated using the whole amygdala and six subregional seed regions-of-interest; left and right basolateral, centromedial and superficial. The 3D data identified multiple stronger bilateral connections between both centromedial subregions, most notably to subcortical structures including brainstem and hippocampus, as well as intra-amygdala subregional connections. The 2D data displayed stronger connections to several cortical regions. Whole amygdala and subregional FC results differed. This study identified underutilized capability in current fMRI acquisition techniques at 3T. 2D GRE-EPI sequences optimized for high spatial resolution with voxel volumes of 15.6 mm3 capably demonstrate functional connectivity patterns of the amygdala at a subregional level, allowing interrogation of heterogeneous amygdala function at a more granular level. The novel 3D acquisition with voxel volumes of 8 mm3 showed promise in outperforming its 2D counterpart in identifying amygdala subregional connections to other subcortical structures that are traditionally difficult to image well.
Automated detection of focal cortical dysplasia (FCD) requires large volumes of voxelwise-lesion-delineated MRI data, which are difficult to acquire. This study aims to generate synthetic MRI data exhibiting FCD, assess its realism, and evaluate its impact on automated FCD detection-particularly in reducing the need for manual annotations. T1-weighted (T1w) and T2-weighted-fluid-attenuated inversion recovery (FLAIR) MRI scans from 131 FCD patients and 90 healthy controls from multiple (3) sites were retrospectively studied. Synthetic MRIs were generated by conditioning a generative network on binary FCD mask. Two neuroradiologists identified real images from a random set of 14 real and 14 synthetic scans. Three nnU-Net models were trained to detect FCD using (i) real-only (35-FCD/35-controls), (ii) real (35-FCD/35-controls) + synthetic augmentation, and (iii) expanded real data (70-FCD/70 controls). Experts showed limited ability to distinguish real from synthetic images, with classification accuracy of 60% for T1w and 70% for FLAIR (inter-rater agreement κ = 0.86). Augmenting automated FCD detection with synthetic data increased sensitivity by 8.14% (p = 0.12) and improved model confidence at true lesion sites (0.83 ± 0.11 to 0.89 ± 0.12; p = 0.02). The expanded real-data model further improved sensitivity to 73.8% (p < 0.001) and confidence to 0.90 ± 0.14 (p = 0.01). Conditional generative networks can generate realistic synthetic FCD-MRIs, reducing labeled data needs by ∼20% while maintaining equivalent sensitivity. Equivalent amounts of real data, when available, remain more effective than synthetic augmentation.
Neurodegeneration with brain iron accumulation (NBIA) refers to a group of rare genetic disorders characterized by abnormal iron deposition in the basal ganglia and brainstem due to impaired iron homeostasis. Disease severity and manifestations vary according to the underlying genetic mutation and age of presentation; however, most subtypes share progressive neurological features such as dystonia, Parkinsonism, spasticity, cognitive decline, and intellectual disability. In this review, we first outline the physiological role of iron in the central nervous system, emphasizing its importance for neurotransmitter synthesis, myelination, and mitochondrial metabolism, and discuss how disruption of homeostatic mechanisms may lead to ferroptosis and neuronal injury. We then explore the role of neuroimaging in the diagnosis of NBIA, with a focus on MRI as the modality of choice. Finally, we provide an overview of the clinical and imaging features of the major NBIA subtypes, highlighting both shared characteristics and distinctive patterns. Covered NBIA include primary disorders of iron metabolism, such as neuroferritinopathy and aceruloplasminemia, and secondary disorders with disrupted iron regulation, including Pantothenate Kinase-Associated Neurodegeneration, Phospholipase A2 Group VI-Associated Neurodegeneration, Mitochondrial Membrane Protein-Associated Neurodegeneration, Beta-Propeller Protein-Associated Neurodegeneration, Fatty Acid Hydroxylase-Associated Neurodegeneration, Coenzyme A Synthetase Protein-Associated Neurodegeneration, Woodhouse-Sakati syndrome, and Kufor-Rakeb Disease. By integrating genetics, pathophysiology, and imaging, this review aims to improve recognition of NBIA and support comprehensive clinical management.
Small fiber neuropathy (SFN) is a neuropathic disorder that is associated with chronic pain. While most SFN cases are idiopathic, SFN can also have hereditary causes. For example, rare SCN9A gene mutations can impair the NaV1.7 sodium channel, which leads to dorsal root ganglion neuron hyperexcitability, causing SFN. Although chronic pain may induce cerebral changes, the specific structural brain alterations in SCN9A-associated SFN (SFN-SCN9A) remain insufficiently characterized. Therefore, potential alterations in the structural brain network of idiopathic SFN and SFN-SCN9A were explored. Ten SFN-SCN9A patients, 20 idiopathic SFN patients, and 20 controls were included. All participants underwent 3-Tesla diffusion MRI (66 gradient directions, b-value = 1200 s/mm2), and the brain network was quantified using nodal importance, which describes the influence of a group of regions on the whole network. The nodal importance of pain-associated regions (postcentral gyrus, insular cortex, anterior cingulate cortex, and thalamus) was increased in SFN-SCN9A patients compared to controls (β = 0.43, p = 0.02) and idiopathic SFN patients (β = 0.43, p = 0.02). Moreover, higher self-reported pain was associated with higher nodal importance of pain-associated regions in the SFN-SCN9A group (r = 0.67, p = 0.03), while this effect was not observed in the idiopathic SFN patients (r = -0.22, p = 0.34). As self-reported pain did not differ between the SFN groups, it is likely specific to the SCN9A-mutation and not to differences in pain intensity. Combined, these results suggest the potential involvement of a distinct structural pathway related to pain processing in SFN-SCN9A.
Socioeconomic determinants of health impact childhood development and adult health outcomes. One key aspect is the physical environment and neighborhood where children live and grow. Emerging evidence suggests that neighborhood deprivation, often measured by the Area Deprivation Index (ADI), may influence neurodevelopment, but longitudinal and multimodal neuroimaging analyses remain limited. We examined the association between childhood neighborhoods and brain white matter (WM) microstructural integrity using a large, demographically representative cohort from the Adolescent Brain Cognitive Development Study. We analyzed the relationship between ADI and MRI metrics of WM microstructural integrity and resting-state funtional magnetic resonance imaging (rs-fMRI) connectivity in children with data at baseline (mean age of 9.9 years) and follow-up (mean age 12.0 years), with a sample size of n = 2615. Children living in poorer neighborhoods (higher ADI) showed lower brain WM microstructural integrity at baseline and follow-up, even after adjusting for age, sex, race/ethnicity, head size, body mass index, parental education, and income levels. This reduced microstructure was seen in critical tracts, such as the superior longitudinal fasciculus, corpus callosum, and the uncinate. Additionally, baseline and follow-up rs-fMRI analysis revealed that children living in poorer neighborhoods had decreased connectivity within the retrosplenial-temporal network and between higher-order networks, such as the cingulo-opercular network. These findings highlight the influence of neighborhood socioeconomic disadvantage on both WM microstructural integrity and functional brain connectivity in the preadolescent brain. Children from more deprived neighborhoods showed reduced integrity in key WM tracts and disrupted connectivity within and between higher-order networks.
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White matter lesions are common imaging biomarkers associated with aging and neurodegenerative diseases, yet their underlying pathology remains unclear due to limitations in imaging-based characterization. We aim to develop and validate a comprehensive workflow enabling precise MRI-guided histological sampling of white matter lesions to bridge neuroimaging and neuropathology. We established a workflow integrating agar-sucrose brain embedding, ultrahigh field 7 Tesla (7T) MRI acquisition, reusable three-dimensional (3D) printed cutting guides, and semiautomated MRI-blockface alignment. Left hemispheric postmortem brains were stabilized in the embedding medium and scanned using optimized MRI protocols. Coronal sectioning was guided by standardized 3D-printed cutting guides, and knife traces were digitally matched to MRI planes. White matter lesions were segmented on MRI and aligned for histopathological sampling. The workflow enabled reproducible brain sectioning, minimized imaging artifacts, and achieved precise spatial alignment between MRI and histology. For demonstration, detailed results from two representative brains were presented in this article. Consistent, high-resolution MRI data facilitated accurate lesion detection and sampling. The use of standardized cutting guides and alignment protocols reduced variability and improved efficiency. Our cost-effective, scalable workflow reliably linked neuroimaging findings with histological analysis, enhancing the understanding of white matter lesion pathology. This framework held significant potential for advancing translational research in aging and neurodegenerative diseases.
Diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) has emerged as a promising noninvasive method for evaluating water motion that may reflect glymphatic system function. However, the reliability of DTI-ALPS measurements across different region-of-interest (ROI) selection methods remains underinvestigated. This study aimed to assess the interrater reliability among three neuroradiologists in native space and compare DTI-ALPS indices derived from ROIs placed in subjects' native space versus standardized Montreal Neurological Institute (MNI) space. DTI-ALPS indices from 16 healthy subjects were calculated from both left and right hemispheres using two ROI placement approaches: (1) native space ROIs manually placed by three neuroradiologists, and (2) standardized ROIs in MNI space based on the fractional anisotropy template. Interrater reliability was assessed using intraclass correlation coefficients (ICCs). The proportion of ROI overlaps among the three neuroradiologists was also evaluated. Differences between native and MNI space measurements were evaluated using related-samples Friedman's analysis with post hoc pairwise comparisons. Interrater reliability for native space ROI placement was moderate for left-sided DTI-ALPS indices (ICC = 0.599) and good for right-sided DTI-ALPS indices (ICC = 0.807). Spatial overlap analysis revealed poor Dice similarity coefficients across all ROI types (range: 0.047-0.312), with right association ROIs showing higher spatial consistency. Significant differences were found between native and MNI space measurements for left-sided DTI-ALPS indices (p = 0.002) but not for right-sided DTI-ALPS indices (p = 0.913). These findings highlight the importance of standardized ROI selection approaches for clinical applications of DTI-ALPS.
Synthetic (Sy) MRI is a clinically approved technique providing quantitative MRI measures based on T1-weighted, T2-weighted, and proton density relaxometry. MRI sequences are often acquired after contrast injection with gadolinium (Gd) to assess active lesions in persons with multiple sclerosis (PwMS), affecting relaxation time. We aimed to assess the influence of Gd on the SyMRI-based volumetrics in PwMS. We enrolled 106 PwMS and 15 controls who performed pre-/post-contrast brain SyMRI on a 3T scanner. We evaluated mean change in brain parenchymal fraction (BPF), white matter (WM), grey matter (GM), myelin (Myl), non-aqueous component (NAC), excess parenchymal water (EPW), and T1 enhancement (T1E) using paired sample t-test for pre-/post-Gd volumes and independent sample t-test for comparison between groups. The mean age was 40.9 and 39.9 years with 69% and 87% females in MS and controls, respectively. Compared to native volumetrics, Gd caused a significant observed volume increase (p < 0.001) in BPF 1.05 ± 0.3%, WM 2.8 ± 0.99%, Myl 1.42 ± 0.39%, NAC 1.04 ± 0.23%, and EPW 0.6 ± 0.4% and decrease in GM -3.05 ± 1.34% in MS. Similar change was seen in controls: BPF 0.99 ± 0.21%, WM 2.94 ± 0.93%, Myl 1.35 ± 0.37%, NAC 0.99 ± 0.22%, EPW 0.47 ± 0.29%, and GM -2.89 ± 1.18%. The change in T1E was 0.05 ± 0.12% in MS (p < 0.001) and 0.02 ± 0.25% (p = 0.76) in controls. The number of contrast-enhancing lesions correlated with T1E (r = 0.348, p < 0.003). There was a consistent pattern of volume changes in PwMS and controls, except for T1E, where the contrast could have affected the results in PwMS. Therefore, combining pre- and post-contrast metrics in longitudinal studies should be interpreted with caution.
Facial nerve (CN VII) diffusion MR tractography is considered as a useful adjunct in pre-operative planning prior to vestibular schwannoma (VS) resection, especially in larger (Koos Grade III/IV) tumors. Since 2016, several systematic reviews have investigated the clinical value of CN VII tractography in VS, and all reported a "success rate" of at least 87% for predicting the pre-operative CN VII position. Yet in clinical practice, CN VII tractography has not yet been widely adopted into routine clinical practice. We suspected that underlying methodology and reporting metrics for existing tractography algorithms may be overestimating success rate. This motivated us to revisit the literature from a different perspective to unravel the caveats and nuances behind this technology. We screened all published works on PubMed related to pre-operative CN VII tractography in VS. Twenty-two studies were reviewed in detail. We observed a strikingly high heterogeneity in tractography protocols in all domains of the tractography acquisition and analysis pipeline across studies. These findings suggest that the reliability and reproducibility of CN VII tractography in large VS has been overestimated. We believe that employing standardized reporting metrics, including sensitivity, true predictive value, and false discovery rate, would increase the transparency of benchmarking over other commonly reported metrics ("success rate" or "concordance rate"). In addition, ongoing research should aim to systematically investigate and improve each step in the acquisition and analysis pipeline for CN VII tractography in VS.
Hemodynamic impairment may contribute to stroke risk and cognitive decline in asymptomatic internal carotid artery stenosis (ICAS). Therefore, multimodal MRI-based quantification of hemodynamic impairment could inform improved treatment decisions. While gross interhemispheric hemodynamic imbalances have been reported in ICAS, identifying more spatially resolved patterns of disease-related alterations may be promising to harness the full potential of hemodynamic MRI. In this feasibility study, we investigated the spatial topography of ICAS-related impairments by applying scaled subprofile model principal component analysis (SSM-PCA) to cerebral blood flow (CBF), relative oxygen extraction fraction (rOEF), and oxygen extraction capacity (OEFmax) data of 21 unilateral ICAS patients and 25 healthy controls (HC). We found spatially extended, partly overlapping disease-related patterns for CBF and OEFmax, but not rOEF. CBF (area under the curve [AUC] = 0.95) but not OEFmax (AUC = 0.72) SSM-PCA scores distinguished ICAS patients and HC better than interhemispheric lateralizations (AUC = 0.75/0.73). SSM-PCA scores were only partly explained by interhemispheric lateralization (R2 = -0.27/0.38), indicating complementary information. Critically, ICAS patients with higher OEFmax SSM-PCA scores (z ≥ 1) demonstrated higher stenotic degrees and lower cognitive performance (p < 0.05) without differing in interhemispheric lateralization (p > 0.05). We demonstrated the feasibility of SSM-PCA in ICAS and obtained novel insights into complex hemodynamic impairment patterns and their association with cognitive function.