AJNR. American journal of neuroradiology最新文献

Background and purpose: The study of T2-weighted hyperintense lesions resulting from autoimmune inflammatory injury and associated volumes within the CNS remains fundamental to the diagnosis and disease surveillance of MS. We investigated the dynamic changes of individual T2-weighted hyperintense MS lesions on MRI and hypothesized that variations may be present below the threshold of visual perception when evaluating longitudinal data.

Materials and methods: A retrospective study was performed of people with MS, incorporating data from 3 consecutive MRI time points acquired within a single academic center. All included MRI studies lacked formal imaging interpretations of newly enlarging or contracting T2-weighted hyperintensities. Well-defined, noncoalescing, individual T2-weighted hyperintense lesions were targeted. A total of 8-12 lesions were randomly selected in a blinded fashion at MRI time point 1 and 3D lesion volumes were followed over MRI time points 2 and 3. The impact of treatment on lesion expansion and relationship to brain MRI advancement, patient-reported progression of disease, and physician-identified progression was also studied.

Results: The study cohort comprised 115 people (81 (70.4%) women; mean disease duration of 9.36 years [standard deviation: 7.72 years]) who were primarily White (79.1%). A total of 1426 focal T2-weighted hyperintense MS lesions were identified on MRI time point 1 and longitudinally followed over MRI time points 2 and 3. In the evaluation of raw changes in individual T2-weighted hyperintense lesion volumes from MRI time point 1 to MRI time point 2, a similar number of individuals were observed with predominantly expanding (49/115; 42.6%) or contracting (51/115; 44.3%) lesions. However, most lesions expanded in volume (48/115; 41.7%) versus those that contracted (45/115; 39.1%) when evaluating MRI time point 3 to time point 1. Those individuals not on active treatment had a 67.15% reduction in the odds of more individual lesions predominantly contracting in volume relative to those on low-efficacy disease modifying therapy treatment (95% CI = [-83.89% to -33.01%], P = .0008) and 74.02% reduction relative to high-efficacy treatment individuals (95% CI = [-87.37% to -46.56%], P < .0001).

Conclusions: Dynamic changes in T2-weighted hyperintense lesions are abundant, occurring below the threshold of visual perception and are present more frequently in untreated individuals.

Background and purpose: Granulomatosis with polyangiitis (GPA) and eosinophilic granulomatosis with polyangiitis (EGPA) are the most common causes of chronic sinusitis from systemic granulomatous diseases. While both are small- to medium-sized vasculitis with necrotizing granulomas, they have different clinical courses and prognoses. High-density sinus opacification has been reported in allergic fungal sinusitis with eosinophilic infiltrates. Given that EGPA also has eosinophilic tissue infiltrates, we evaluated the differences in sinus CT findings, focusing on the sinus secretion attenuation between patients with GPA and EGPA, along with other previously described findings.

Materials and methods: This study included 31 patients with GPA and 22 patients with EGPA who underwent sinus CT. The attenuation of secretions within the paranasal sinuses was visually assessed, and the Hounsfield unit (HU) of the highest-density portions within each sinus was measured. Lund-Mackay scores (LMS), bony destruction, sclerotic wall changes, adjacent organ involvement, and nasal polyps were evaluated and compared between patients with GPA and EGPA. Multiple logistic regression analyses were conducted to determine which factors independently discriminated GPA from EGPA, and the diagnostic ability to differentiate between these 2 diseases was evaluated by using a receiver operating characteristic curve analysis.

Results: More patients in the GPA group showed bony destructions, bone sclerosis, and involvement of organs adjacent to paranasal sinuses than in the EGPA group (P = .006, 0.048, and 0.035, respectively). The EGPA group had higher LMS and more nasal polyps than the GPA group (P = .078 and 0.333, respectively). More patients in the EGPA group showed internal high-density opacification than in the GPA group, and patients with EGPA had higher mean HUs (both P < .0001). The presence of high-density opacification or mean HUs independently distinguished GPA from EGPA (OR, 53.67 and 1.07; 95% CI, 4.07-708.03 and 1.02-1.13, respectively) and showed a greater ability to discriminate between these diseases compared with other findings.

Conclusions: Patients with EGPA had more high-density sinus opacification and higher mean HU on sinus CT than the patients with GPA. In addition to the previously reported CT findings, such as bony destruction, bone sclerosis, and adjacent organ involvement, evaluating secretion attenuation can assist in distinguishing between GPA and EGPA.

Dextromethorphan toxicity in young children (especially those 4 years of age or younger) can have an extremely poor prognosis if untreated. However, if timely recognized and optimally managed, it can have a good clinical outcome despite a profound initial insult. We present 3 pediatric cases (younger than 5 years of age) with sudden unresponsiveness following ingestion of cough medications containing dextromethorphan. All these children showed cytotoxic edema in the cerebellar hemispheres on MR of the brain, with diffusion-restricting foci in the supratentorial white matter in 2 patients. These features resemble the recently described acute opioid toxidrome in children, pediatric opioid use-associated neurotoxicity with cerebellar edema (POUNCE). Hence, we named this entity dextromethorphan-associated neurotoxicity with cerebellar edema (DANCE) to increase the awareness of dextromethorphan toxicity in young children and the need to promptly recognize it to initiate optimal management.

Background and purpose: Prior investigations have noted the presence of peritumoral hyperintense signal (a "halo") around vestibular schwannomas on postcontrast 3D T2 FLAIR images. This study evaluated this phenomenon in a cohort of patients undergoing stereotactic radiosurgery.

Materials and methods: A retrospective review was completed of consecutive patients with presumed vestibular schwannomas undergoing stereotactic radiosurgery. Tumor size, location, presence or absence of a peritumoral halo, and halo thickness were recorded. Images were reviewed for presence and size of peritumoral hyperintense signal on postcontrast 3D T2 FLAIR images before and after treatment.

Results: Twenty-six patients were included in this study, 14 of which were female (54.0%). Average age was 62±12 years. Prior to treatment, a post-contrast 3D T2 FLAIR hyperintense peritumoral halo was seen in 85% of patients, averaging 0.8±0.4 mm in thickness. There was a higher incidence of peritumoral halo in post treatment patients (96%) than pre-treatment patients (85%) (p=0.017) with a mean follow up period of 1.2 years (SD, 0.35) from 11/12/2019 to 9/5/2023. The average halo thickness was also larger in posttreatment patients (average=1.4±0.4 mm) compared to pre-treatment patients (0.8±0.4 mm) (p<0.001). Average tumoral size did not significantly change following treatment (p=0.10).

Conclusions: Vestibular schwannomas treated with stereotactic radiosurgery are more likely to have a peritumoral halo on post-contrast 3D T2 FLAIR images, with larger halo size as compared to pre-treatment studies. Further study with a larger tumor cohort and longer follow-up will be necessary to determine if these findings are predictive of subsequent tumor shrinkage.

Abbreviations: VSs = vestibular schwannomas; SRS = stereotactic radiosurgery; CPA = cerebellopontine angle; IAC = internal auditory canal.

Amyloid-targeting therapy has recently become widely available in the U.S. for the treatment of patients with symptomatic mild Alzheimer's disease (AD). At present, there are no biomarkers that have been clinical validated to assess treatment response in routine clinical practice; longitudinal amyloid PET could play a role but is not cost effective. This report presents a case series of six patients with AD, whose amyloid positivity was confirmed by PET or CSF biomarkers, who underwent baseline and longitudinal arterial spin-labeling magnetic resonance imaging (ASL-MR) as part of FDA-mandated, clinical standard-of-care, non-contrast MR monitoring to assess for amyloid-related imaging abnormalities (ARIA). We and others have previously reported that ASL-MR can screen for neurodegenerative disease, as a proxy for FDG-PET, and can be easily added on as a cost-effective, repeatable method to monitor post-therapy changes. This series highlights varied cerebral blood flow (CBF) changes in response to lecanemab therapy. For instance, Cases 1, 3, and 5 showed increased CBF after multiple infusions, with subjective cognitive improvement in Case 1 and improved MoCA scores in Case 3. Case 2 showed improved CBF initially before the 5^th infusion, but this returned to baseline on the subsequent study, with no cognitive improvement over the course of therapy. Cases 4 and 6 have demonstrated no significant changes in regional CBF thus far on therapy, with cognitive decline in Case 4. This case series underscores the potential utility of ASL-MR as an adjunct sequence to current imaging protocols to monitor treatment response to anti-amyloid therapy.ABBREVIATIONS: ASL-MR= arterial spin-labeling magnetic resonance imaging; MRI= magnetic resonance imaging; CBF= cerebral blood flow; AD= Alzheimer's disease; PET= positron emission tomography; CSF= cerebrospinal fluid; FDG= fluorodeoxyglucose.

Background and purpose: To train and evaluate an open-source generative adversarial networks (GANs) to create synthetic lumbar spine MRI STIR volumes from T1 and T2 sequences, providing a proof-of-concept that could allow for faster MRI examinations.

Materials and methods: 1817 MRI examinations with sagittal T1, T2, and STIR sequences were accumulated and randomly divided into training, validation, and test sets. GANs were trained to create synthetic STIR volumes using the T1 and T2 volumes as inputs, optimized using the validation set, then applied to the test set. Acquired and synthetic test set volumes were independently evaluated in a blinded, randomized fashion by three radiologists specializing in musculoskeletal imaging and neuroradiology. Readers assessed image quality, motion artifacts, perceived likelihood of the volume being acquired or synthetic, and presence of 7 pathologies.

Results: The optimal model leveraged a customized loss function that accentuated foreground pixels, achieving a structural similarity imaging metric (SSIM) of 0.842, mean absolute error (MAE) of 0.028, and peak signal to noise ratio (PSNR) of 26.367. Radiologists could distinguish synthetic from acquired volumes; however, the synthetic volumes were of equal or better quality in 77% of test patients and demonstrated equivalent or decreased motion artifacts in 78% of test patients. For common pathologies, the synthetic volumes had high positive predictive value (75-100%) but lower sensitivity (0-67%).

Conclusions: This work links objective computer vision performance metrics and subject clinical evaluation of synthetic spine MRIs using open-source and reproducible methodologies. High-quality synthetic volumes are generated, reproducing many important pathologies, demonstrating a potential means for expediting imaging protocols.

Abbreviations: AI = Artificial Intelligence; GANs = general adversarial networks; aqSTIR = acquired STIR volume; sSTIR = synthetically generated STIR volume; SSIM = structural similarity imaging metric; PSNR = peak signal to noise ratio; MAE = mean absolute error.

Background and purpose: Magnetic Resonance Imaging is widely used to assess disease burden in multiple sclerosis (MS). This study aimed to evaluate the effectiveness of a commercially available k-nearest neighbors (k-NN) software in quantifying white matter lesion (WML) burden in MS. We compared the software's WML quantification to expert radiologists' assessments.

Materials and methods: We retrospectively reviewed brain MRI examinations of adult MS patients and of adult patients without MS and with a normal brain MRI referred from the neurology clinic. MRI images were processed using an AI-powered, cloud-based k-NN software, which generated a DICOM lesion distribution map and a report of WML count and volume in four brain regions (periventricular, deep, juxtacortical, and infratentorial white matter). Two blinded radiologists performed semi-quantitative assessments of WM lesion load and lesion segmentation accuracy. Additionally, four blinded neuroradiologists independently reviewed the data to determine if MRI findings supported an MS diagnosis. Results were considered significant when p < 0.05.

Results: The study included 32 MS patients (35.4 years ± 9.1) and 19 patients without MS (33.5 years ± 12.1). The k-NN software demonstrated 94.1% and 84.3% accuracy in differentiating MS from non-MS subjects based respectively on WML count and WML volume, compared to radiologists' accuracy of 90.2% to 94.1%. Lesion segmentation was more accurate for the deep WM and infratentorial regions than for the juxtacortical region (both p <0.001).

Conclusions: k-NN-derived WML volume and WML count provide valuable quantitative metrics of disease burden in MS. AI-powered post-processing software may enhance the interpretation of brain MRIs in MS patientsABBREVIATIONS: MS = multiple sclerosis; k-NN＝k-Nearest Neighbors; WML＝white matter lesion; MPRAGE = Magnetization-Prepared Rapid Acquisition Gradient Echo; SPACE = Sampling Perfection with Application-optimized Contrasts using a Different Flip Angle Evolution; EDSS = Expanded Disability Status Scale.

Background and purpose: Epilepsy, a globally prevalent neurological disorder, necessitates precise identification of the epileptogenic zone (EZ) for effective surgical management. While the individual utilities of FDG PET and FMZ PET have been demonstrated, their combined efficacy in localizing the epileptogenic zone remains underexplored. We aim to improve the non-invasive prediction of epileptogenic zone (EZ) in temporal lobe epilepsy (TLE) by combining FDG PET and FMZ PET with statistical feature extraction and machine learning.

Materials and methods: This study included 20 drug-resistant unilateral TLE patients (14 mesial TLE, 6 lateral TLE), and two control groups (N=29 for FDG, N=20 for FMZ). EZ of each patient was confirmed by post-surgical pathology, and one-year follow-up, while propagation zone (PZ) and non-involved zone (NIZ) were derived from the epileptogenicity index based on presurgical stereo-encephalography (SEEG) monitoring. Whole brain PET scans were obtained with dual tracers [¹⁸F]FDG and [¹⁸F]FMZ on separate days, from which standard uptake value ratio (SUVR) was calculated by global mean scaling. Low-order statistical parameters of SUVRs and t-maps derived against control groups were extracted. Additionally, fused FDG and FMZ features were created using arithmetic operations. Spearman correlation was used to investigate the associations between FDG and FMZ, while multiple linear regression analysis was used to explore the interaction effects of imaging features in predicting epileptogenicity. Crafted imaging features were used to train logistic regression models to predict EZ, whose performance was evaluated using 10-fold cross-validation at ROI-level, and leave-one-patient-out cross-validation at patient-level.

Results: FDG SUVR significantly decreased in EZ and PZ compared to NIZ, while FMZ SUVR in EZ significantly differed from PZ. Interaction effects were found between FDG and FMZ in their prediction of epileptogenicity. Fusion of FDG and FMZ provided the best prediction model with an area under the curve (AUC) of 0.86 [0.84-0.87] for EZ vs. NIZ and an AUC of 0.79 [0.77-0.81] for EZ vs. PZ, eliminating 100% false positives in 50% of patients, and ≥80% FPs in 90% patients at patient level.

Conclusions: Combined FDG and FMZ offer a promising avenue for non-invasive localization of the epileptogenic zone in TLE, potentially refining surgical planning.

Abbreviations: AUC = Area under the curve; EI = Epileptogenicity index; EZ = Epileptogenic zone; FMZ = Flumazenil; GABAA = Gammaaminobutyric acid type A; NIZ = Not-involved zone; PZ = Propagation zone; SEEG = Stereo-electroencephalography; SUVR = Standard uptake value ratio; TLE = Temporal lobe epilepsy.