Background and Purpose: Radiologically isolated syndrome(RIS) describes asymptomatic individuals with incidental radiologic abnormalities suggestive of multiple sclerosis(MS). Recent studies demonstrate that >40%of white matter lesions(WMLs) in MS(and often substantially more) have visible central veins on MRI. This “central vein sign”(CVS) reflects perivenous inflammatory demyelination and can assist in differentiating MS from other white matter disorders. We therefore hypothesized that >40% of WMLs in RIS cases would show the CVS. Materials and Methods: 20 participants diagnosed with RIS after evaluation by a neurologist were recruited. We performed 3.0T MRI of the brain and cervical spinal cord. WMLs were analyzed for the CVS. Results: Of 391 total WMLs, 292(75%) demonstrated the CVS(CVS+). The median proportion of CVS+lesions per case was 87%(range:29-100%). When the “40% rule” that has been proposed to distinguish MS from other disorders was applied, 18 RIS cases(90%) had ≥40%CVS+lesions(range:55-100%). Two cases(10%) had <40%CVS+lesions(29% and 31%). When the simpler “rule of 6” was applied, 19 cases(95%) met these criteria. In multivariable models, the number of spinal cord and infratentorial lesions was associated with a higher proportion of CVS+lesions(p=0.002, p=0.06, respectively). Conclusions: The vast majority of RIS cases had a high proportion of CVS+lesions, suggesting that lesions in these individuals reflect perivenous inflammatory demyelination. Moreover, we found correlations between the proportion of CVS+lesions and spinal cord lesions, a known risk factor for RIS developing MS. These findings raise the possibility, testable prospectively, that the CVS may have prognostic value in distinguishing RIS cases at risk of developing clinical MS from those with WMLs of other etiology.

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Machine learning (ML) holds great promise in transforming healthcare. While published studies have shown the utility of ML models in interpreting medical imaging examinations, these are often evaluated under laboratory settings. The importance of real world evaluation is best illustrated by case studies that have documented successes and failures in the translation of these models into clinical environments. A key prerequisite for the clinical adoption of these technologies is demonstrating generalizable ML model performance under real world circumstances. The purpose of this study was to demonstrate that ML model generalizability is achievable in medical imaging with the detection of intracranial hemorrhage (ICH) on non-contrast computed tomography (CT) scans serving as the use case. An ML model was trained using 21,784 scans from the RSNA Intracranial Hemorrhage CT dataset while generalizability was evaluated using an external validation dataset obtained from our busy trauma and neurosurgical center. This real world external validation dataset consisted of every unenhanced head CT scan (n = 5965) performed in our emergency department in 2019 without exclusion. The model demonstrated an AUC of 98.4%, sensitivity of 98.8%, and specificity of 98.0%, on the test dataset. On external validation, the model demonstrated an AUC of 95.4%, sensitivity of 91.3%, and specificity of 94.1%. Evaluating the ML model using a real world external validation dataset that is temporally and geographically distinct from the training dataset indicates that ML generalizability is achievable in medical imaging applications.

Primary central nervous system vasculitis (PCNSV) is a poorly understood neuroinflammatory disease of the CNS affecting the intracranial vasculature. Although PCNSV classically manifests as a multifocal beaded narrowing of the intracranial vessels, some patients may not have angiographic abnormalities. A rare subset of patients with PCNSV present with masslike brain lesions mimicking a neoplasm. In this article, we retrospectively review 10 biopsy-confirmed cases of tumefactive PCNSV (t-PCNSV). All cases of t-PCNSV in our series that underwent CTA or MRA were found to have normal large and medium-sized vessels. T-PCNSV had a variable MR imaging appearance with most cases showing cortical/subcortical enhancing masslike lesion (70%), often with microhemorrhages (80%). Diffusion restriction was absent in all lesions. In summary, normal vascular imaging does not exclude the diagnosis of t-PCNSV. Advanced imaging techniques including MR perfusion and MR spectroscopy failed to demonstrate specific findings for t-PCNSV but assisted in excluding neoplasm in the differential diagnosis. Biopsy remains mandatory for definitive diagnosis.ABBREVIATIONS: PCNSV ¼ primary central nervous system vasculitis; t-PCNSV ¼ tumefactive PCNSV; ABRA ¼ amyloidb -associated angiitis; CAA-RI ¼ cerebral amyloid angiopathy-related inflammation; ESR ¼ erythrocyte sedimentation rate; MRP ¼ MR perfusion; CRP ¼ C-reactive protein; PCR ¼ polymerase chain reaction; VWI ¼ vessel wall imaging; PCNSL ¼ primary CNS lymphoma P rimary central nervous system vasculitis (PCNSV) is a poorly understood neuroinflammatory disease involving intracranial vessels. [1][2][3][4][5] The typical radiologic manifestation of PCNSV is multifocal beading of the large and medium-sized intracranial vessels. An underrecognized and rarer subset of PCNSV, approximately 5%-29%, can present with "masslike" or "tumefactive" lesions mimicking a neoplasm. 3,4,[6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] To date, imaging features of tumefactive PCNSV (t-PCNSV) have not been well described and definitive diagnosis can only be made confidently on histopathology. [5][6][7][8][9][10] In this article, we performed a retrospective review of 10 histopathologically proved cases of t-PCNSV and analyzed pertinent imaging features with histopathologic correlation. CASE SERIES Case SelectionWe performed a retrospective pathology data base search by using the keywords "brain biopsy" and "vasculitis" in histopathology reports from July 2010-December 2018 at a single institution. Exclusion criteria included patients with histopathology findings of amyloid-beta (Ab )-associated angiitis (ABRA) or cerebral amyloid angiopathy-related inflammation (CAA-RI), and infectious CNS vasculitis. Finally, we identified 6 patients who had a final diagnosis of t-PCNSV from this institution. The other 4 patients with t-PCNSV were collected from the imaging and histopathology archives of the contributing authors from 2 other institutions.All 10 patients presented with masslike brain...

Objective: The central vein sign (CVS) and “paramagnetic rim lesions” (PRL) are emerging imaging biomarkers in multiple sclerosis (MS) reflecting perivenular demyelination and chronic, smoldering inflammation. The objective of this study was to assess relationships between cognitive impairment (CI) and the CVS and PRL in radiologically isolated syndrome (RIS). Methods: Twenty-seven adults with RIS underwent 3.0 T MRI of the brain and cervical spinal cord (SC) and cognitive assessment using the minimal assessment of cognitive function in MS battery. The CVS and PRL were assessed in white-matter lesions (WMLs) on T2*-weighted segmented echo-planar magnitude and phase images. Multivariable linear regression evaluated relationships between CI and MRI measures. Results: Global CI was present in 9 (33%) participants with processing speed and visual memory most frequently affected. Most participants (93%) had ⩾ 40% CVS + WML (a threshold distinguishing MS from other WM disorders); 63% demonstrated PRL. Linear regression revealed that CVS + WML predicted performance on verbal memory( β =-0.024, p = 0.03) while PRL predicted performance on verbal memory ( β = -0.040, p = 0.04) and processing speed ( β = -0.039, p = 0.03). Conclusions: CI is common in RIS and is associated with markers of perivenular demyelination and chronic inflammation in WML, such as CVS + WML and PRL. A prospective follow-up of this cohort will ascertain the importance of CI, CVS, and PRL as risk factors for conversion from RIS to MS.

Cortical and sulcal hyperintensity on gadolinium-enhanced FLAIR is a transient observation in the arterial territory exposed to iodinated contrast medium during endovascular treatment of intracranial aneurysms. Cortical and sulcal hyperintensity on gadolinium-enhanced FLAIR is significantly associated with procedural time, and the frequency of angiographic runs suggesting a potential technical influence on the breakdown of the BBB, but no reported adverse clinical outcome or association with both iodinated contrast medium volume and DWI lesions was found. Recognition of cortical and sulcal hyperintensity on gadolinium-enhanced FLAIR as a benign incidental finding is vital to avoid unnecessary investigation.

Fractures of the cervical spine are a medical emergency and may lead to permanent paralysis and even death. Accurate diagnosis in patients with suspected fractures by computed tomography (CT) is critical to patient management. In this paper, we propose a deep convolutional neural network (DCNN) with a bidirectional long-short term memory (BLSTM) layer for the automated detection of cervical spine fractures in CT axial images. We used an annotated dataset of 3,666 CT scans (729 positive and 2,937 negative cases) to train and validate the model. The validation results show a classification accuracy of 70.92% and 79.18% on the balanced (104 positive and 104 negative cases) and imbalanced (104 positive and 419 negative cases) test datasets, respectively.

Background: The spinal cord (SC) is highly relevant to disability in multiple sclerosis (MS), but few studies have evaluated longitudinal changes in quantitative spinal cord magnetic resonance imaging (SC-MRI). Objectives: The aim of this study was to characterize the relationships between 5-year changes in SC-MRI with disability in MS. Methods: In total, 75 MS patients underwent 3 T SC-MRI and clinical assessment (expanded disability status scale (EDSS) and MS functional composite (MSFC)) at baseline, 2 and 5 years. SC-cross-sectional area (CSA) and diffusion-tensor indices (fractional anisotropy (FA), mean, perpendicular, parallel diffusivity (MD, λ⊥, λ||) and magnetization transfer ratio (MTR)) were extracted at C3–C4. Mixed-effects regression incorporating subject-specific slopes assessed longitudinal change in SC-MRI measures. Results: SC-CSA and MTR decreased ( p = 0.009, p = 0.03) over 5.1 years. There were moderate correlations between 2- and 5-year subject-specific slopes of SC-MRI indices and follow-up EDSS scores (Pearson’s r with FA = −0.23 ( p < 0.001); MD = 0.31 ( p < 0.001); λ⊥ = 0.34 ( p < 0.001); λ|| = −0.12 ( p = 0.05), MTR = −0.37 ( p < 0.001); SC-CSA = −0.47 ( p < 0.001) at 5 years); MSFC showed similar trends. The 2- and 5-year subject-specific slopes were robustly correlated ( r = 0.93–0.97 for FA, λ⊥, SC-CSA and MTR, all ps < 0.001). Conclusion: In MS, certain quantitative SC-MRI indices change over 5 years, reflecting ongoing tissue changes. Subject-specific trajectories of SC-MRI index change at 2 and 5 years are strongly correlated and highly relevant to follow-up disability. These findings suggest that individual dynamics of change should be accounted for when interpreting longitudinal SC-MRI measures and that measuring short-term change is predictive of long-term clinical disability.