Citations

Abstract Introduction Quantitative interpretation of pediatric brain [ 18 F]-FDG PET is limited by the lack of age-matched normative reference databases, despite substantial developmental variation in cerebral glucose metabolism. This study aimed to construct a large-scale normative pediatric [ 18 F]-FDG PET database and develop an age-specific z-score mapping framework for quantitative evaluation of pediatric epilepsy. Method Pediatric brain PET data were retrospectively derived from clinically acquired whole-body or dedicated [ 18 F]-FDG PET examinations in participants 0–19 years of age without neurologic disease or visible brain abnormalities. A total of 417 PET scans from 341 participants were stratified into five developmental age groups: infancy, early childhood, middle childhood/school age, adolescence, and late adolescence. SUVR maps were generated using whole-brain atlas and brainstem reference regions. Voxel-wise t-test analyses were performed to characterize age- and sex-related metabolic differences. Age-specific voxel-wise mean and standard deviation maps were generated from the normative cohort and used to calculate age-matched hypometabolic z-score maps in 14 pediatric patients with epilepsy. The resulting abnormalities were qualitatively evaluated for concordance with epileptogenic findings identified on clinical MRI and/or PET by expert image review. Results Voxel-wise analyses demonstrated prominent age-dependent SUVR differences, particularly between infancy and older age groups. With whole-brain atlas normalization, older children showed progressively higher relative SUVR in cortical and cerebellar gray matter regions, whereas infancy showed relatively higher SUVR in the occipital cortex, white matter, thalamus, and brainstem. Brainstem normalization produced distinct developmental patterns, emphasizing higher white matter SUVR in infancy and broader gray matter differences in older groups. Sex-related differences were limited and regionally specific. Whole-brain atlas normalization showed lower variability than brainstem normalization and was selected for z-score mapping. In representative epilepsy cases, age-matched z-score maps identified focal or regional hypometabolism corresponding to malformations of cortical development, focal cortical dysplasia, mesial temporal sclerosis, nonlesional MRI cases, remote insult, tumor-related abnormalities, and Sturge-Weber syndrome. Discussion A large-scale normative pediatric [18F]-FDG PET database can support developmentally appropriate quantitative interpretation of pediatric brain PET. Age-matched z-score mapping may complement visual assessment by highlighting abnormal cerebral glucose metabolism in pediatric epilepsy, although findings should be interpreted with MRI, EEG, seizure semiology, and other presurgical data.

Dynamic gadopiclenol-enhanced nodal and pedal MR lymphangiography was safe, with no adverse events, and feasible for imaging peripheral and central conducting lymphatic anatomy.

Background/Objectives: Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluation. However, current automated approaches for lesion detection and segmentation are typically designed for specific MRI contrasts or acquisition sites, limiting their generalizability in real-world clinical settings where imaging protocols vary widely. This work proposes a robust multi-site, multi-contrast segmentation framework for spinal cord lesions. Methods: The segmentation model was trained and evaluated on a large-scale dataset comprising 4428 annotated images from 1849 persons with MS across 23 imaging centers, encompassing six MRI contrasts (T1w, T2w, T2*w, PSIR, STIR, and UNIT1) acquired at 1.5 tesla (T), 3 T, and 7 T. Results: Likert-type assessment performed by neuroradiologist ratings demonstrated superior generalization of the model compared to existing contrast-specific pipelines ( p < 0.01). Additional experiments evaluated robustness across spinal levels, acquisition resolutions, binarization thresholds, and quantitative evaluation on external labeled datasets. Conclusions: The proposed model can achieve accurate and reliable spinal cord MS lesion segmentation across heterogeneous MRI data, addressing a key barrier to clinical translation. The model is available in the Spinal Cord Toolbox v7.2 and higher. Code repository: https://github.com/ivadomed/seg-sc-ms-lesion-multicontrast

Abstract BACKGROUND Patients with primary brain tumors often have very complex histories, but an accurate understanding of their care timeline is critical to provide the best care possible. Extracting pertinent facts from the medical record can be time consuming and frustrating. We sought to apply generative AI large language models (LLM) to this problem in order to supply providers with concise, accurate, and focused data including graphs and tables. METHODS After evaluating multiple LLMs, GEMINI 2.5 Pro was selected. Prompt engineering was iteratively refined across a range of patients to generate concise outputs using tables, graphs, and prose to describe timing of chemoradiation, tumor markers, procedures, and trends in MRI results. The model inferred BT-RADS scores from the MRI report prose. Using a 5-point Likert scale, neuroradiologists assessed the AI-output both prospectively and retrospectively comparing it to the medical record. LLM’s compared AI summaries to source material. RESULTS Six neuroradiologists each ranked 25 prospective patient outputs as accurate (82%/16%/1%), useful (94%/6%/0%), trustworthy (86%/13%/1%), and satisfactory (86%/10%/1%) for Likert ratings of highly agree/agree/neutral, respectively. No responses were disagree or highly disagree. Interobserver agreement was high (Gwent AC2 &gt; 0.95). The LLM evaluation of referenced portions of the record determined &gt; 85% of summary statements were supported by source documents. While users estimated time savings of a 1-10 minutes per case, they felt the greater benefit was having more organized data presented efficiently. CONCLUSIONS AI summaries of the medical record of complex patients with primary brain tumors give providers an accurate, well-organized display of the pertinent facts necessary for high quality care and save time in chart review. These summaries, which are generated early each morning, have been found to be helpful and are now being incorporated into our clinical practice and multidisciplinary tumor board.

Abstract Temporal lobe epilepsy is a common neurological disease characterized by recurrent seizures that often originate within limbic networks involving amygdala and hippocampus. The limbic network is involved in crucial physiologic functions involving memory, emotion and sleep. Temporal lobe epilepsy is frequently drug-resistant, and people often experience comorbidities related to memory, mood and sleep. Deep brain stimulation targeting the anterior nucleus of the thalamus (ANT-DBS) is an established therapy for temporal lobe epilepsy. However, the optimal stimulation parameters and their impact on memory, mood and sleep comorbidities remain unclear. We used an investigational brain sensing-stimulation implanted device to accurately track seizures, interictal epileptiform spikes (IES), and memory, mood and sleep comorbidities in five ambulatory subjects. Wireless streaming of limbic network local field potentials (LFPs) and subject behaviour were captured on a mobile device integrated with a cloud environment. Automated algorithms applied to the continuous LFPs were used to accurately cataloged seizures, IES and sleep-wake brain state. Memory and mood assessments were remotely administered to densely sample cognitive and behavioural response during ANT-DBS in ambulatory subjects living in their natural home environment. We evaluated the effect of continuous low-frequency and duty cycle high-frequency ANT-DBS on epileptiform activity and memory, mood and sleep comorbidities. Both low-frequency and high-frequency ANT-DBS paradigms reduced seizures. However, continuous low-frequency ANT-DBS showed greater reductions in IES, electrographic seizures and better sleep and memory outcomes. These results highlight the potential of synchronized brain sensing and dense behavioural tracking during ANT-DBS for optimizing neuromodulation therapy. While studies with larger patient numbers are needed to validate the benefits of low-frequency ANT-DBS, these findings are potentially translatable to individuals currently implanted with ANT-DBS systems.

Abstract Spinal cord disease is important in most people with multiple sclerosis, but assessment remains less emphasized in patient care, basic and clinical research and therapeutic trials. The North American Imaging in Multiple Sclerosis Spinal Cord Interest Group was formed to determine and present the contemporary landscape of multiple sclerosis spinal cord evaluation, further existing and advanced spinal cord imaging techniques, and foster collaborative work. Important themes arose: (i) multiple sclerosis spinal cord lesions (differential diagnosis, association with clinical course); (ii) spinal cord radiological–pathological associations; (iii) ‘critical’ spinal cord lesions; (iv) multiple sclerosis topographical model; (v) spinal cord atrophy; and (vi) automated and special imaging techniques. Distinguishing multiple sclerosis from other myelopathic aetiology is increasingly refined by imaging and serological studies. Post-mortem spinal cord findings and MRI pathological correlative studies demonstrate MRI’s high sensitivity in detecting microstructural demyelination and axonal loss. Spinal leptomeninges include immune inflammatory infiltrates, some in B-cell lymphoid-like structures. ‘Critical’ demyelinating lesions along spinal cord corticospinal tracts are anatomically consistent with and may be disproportionately associated with motor progression. Multiple sclerosis topographical model implicates the spinal cord as an area where threshold impairment associates with multiple sclerosis disability. Progressive spinal cord atrophy and ‘silent’ multiple sclerosis progression may be emerging as an important multiple sclerosis prognostic biomarker. Manual atrophy assessment is complicated by rater bias, while automation (e.g. Spinal Cord Toolbox), and artificial intelligence may reduce this. Collaborative research by the North American Imaging in Multiple Sclerosis and similar groups with experts combining distinct strengths is key to advancing assessment and treatment of people with multiple sclerosis spinal cord disease.

CT myelography has been traditionally used to evaluate post-operative paraspinal fluid collections to discern CSF leaking into a pseudomeningocele versus a contained seroma. Rather than performing a lumbar puncture and injecting intrathecal contrast for myelography, we present the first report of direct contrast injection into a post-operative paraspinal pseudomeningocele for CSF leak confirmation and localization. This is a simple procedure that has several advantages over a conventional CT myelogram for the evaluation of post-operative paraspinal fluid collections.

Functional magnetic resonance imaging (fMRI) with blood oxygen level-dependent (BOLD) technique is useful for preoperative mapping of brain functional networks in tumor patients, providing reliable in vivo detection of eloquent cortex to help reduce the risk of postsurgical morbidity. BOLD task-based fMRI (tb-fMRI) is the most often used noninvasive method that can reliably map cortical networks, including those associated with sensorimotor, language, and visual functions. BOLD resting-state fMRI (rs-fMRI) is emerging as a promising ancillary tool for visualization of diverse functional networks. Although fMRI is a powerful tool that can be used as an adjunct for brain tumor surgery planning, it has some constraints that should be taken into consideration for proper clinical interpretation. BOLD fMRI interpretation may be limited by neurovascular uncoupling (NVU) induced by brain tumors. Cerebrovascular reactivity (CVR) mapping obtained using breath-hold methods is an effective method for evaluating NVU potential.

AbstractObjectiveTo evaluate the magnetic resonance (MR) image artifact and image distortion associated with the two transcutaneous bone conduction implants currently available in the United States.Study DesignCadaveric study.MethodsTwo cadaveric head specimens (1 male, 1 female) were unilaterally implanted according to manufacturer guidelines and underwent MR imaging (General Electric and Siemens 1.5 T scanners) under the following device conditions: (1) no device, (2) Cochlear Osia with magnet and headwrap, (3) Cochlear Osia without magnet, and (4) MED‐EL Bonebridge with magnet. Maximum metal mitigation techniques were employed in all conditions, and identical sequences were obtained. Blinded image scoring (diagnostic vs nondiagnostic image) was performed by experienced neuroradiologists according to anatomical subsites.ResultsAll device conditions produced artifact and image distortion. The Osia with magnet produced diagnostic T1‐ and T2‐weighted images of the ipsilateral temporal bone, however, non‐echo planar imaging diffusion‐weighted imaging (DWI) was nondiagnostic. The Osia without magnet scanned on the Siemens MR imaging demonstrated the least amount of artifact and was the only condition that allowed for diagnostic imaging of the ipsilateral temporal bone on DWI. The Bonebridge produced a large area of artifact and distortion with the involvement of the ipsilateral and contralateral temporal bones.ConclusionIn summary, of the three device conditions (Osia with magnet, Osia without magnet, and Bonebridge), Osia without magnet offered the least amount of artifact and distortion and was the only condition in which diagnostic DWI was available for the middle ear and mastoid regions on the Siemens MR imaging scanner.