Cauda equina involvement in Susac's syndrome.

Susac's syndrome is a rare autoimmune microangiopathy characterized by the clinical triad of encephalopathy, branch retinal artery occlusions, and sensorineural hearing loss. In many cases, the clinical triad is not fully present at the onset of symptoms. MRI studies often show characteristic punched out lesions of the central fibers of the corpus callosum, and leptomeningeal enhancement and deep gray matter lesions may also be seen. Here we present a case of Susac's syndrome in a middle aged man with the unique clinical finding of cauda equina syndrome and spinal MRI showing diffuse lumbosacral nerve root enhancement. Biopsy specimens of the brain, leptomeninges, and skin showed evidence of a pauci-immune endotheliopathy, consistent with pathology described in previous cases of Susac's syndrome. This case is important not only because it expands the clinical features of Susac's syndrome but also because it clarifies the mechanism of a disorder of the endothelium, an important target for many disorders of the nervous system.

Diffuse cauda equina enhancement in a middle aged male with Susac syndrome and symptomatic cauda equina syndrome.

Susac syndrome is a rare neurologic disorder first described by Susac et al. in 1979. Clinically, Susac syndrome consists of a triad including encephalopathy, branch retinal artery occlusions and sensorineural hearing loss. All three components of the triad usually do not present at the same time, thus delaying time to diagnosis. MRI studies often show characteristic punched out lesions of the central fibers of the corpus callosum. Intracranial leptomeningeal enhancement may be seen, however, cauda equina involvement has not been described to our knowledge. We present a case of Susac syndrome in a middle-aged male with symptoms of cauda equina syndrome, and spinal MRI showing diffuse enhancement of the nerve roots of the cauda equina.

Comparison of four prediction models to discriminate benign from malignant vertebral compression fractures according to MRI feature analysis.

OBJECTIVE: The purpose of this study was to identify a set of significant predictors, predominantly based on MRI features and limited demographic data, for differentiating benign from malignant vertebral compression fractures (VCFs) and to compare the diagnostic value of four different types of prediction models. MATERIALS AND METHODS: The cohort included 101 subjects (mean age, 64 years; range, 22-89 years; 39.6% were men) with 128 VCFs, 84 (65.6%) of which were proven to be malignant by biopsy or follow-up imaging. A set of 36 predictors (34 MRI features, age, and sex) was acquired for each VCF retrospectively. RESULTS: Univariate analysis and initial variable screening selected 14 moderately significant predictors. All four model types performed similarly in overall discrimination power. The median area under the curve for each model type was 0.872 for logistic regression, 0.781 for classification tree, 0.760 for support vector machine, and 0.730 for neural network, but no significant difference was found between any two model types by Student t test. Five predictors for the logistic regression model were statistically significant (p < 0.01). Focal paraspinal mass and depositlike appearance of pedicle involvement were positively correlated with VCF malignancy. Age, other compression deformities without bone marrow edema, and intravertebral fluid collection or fluid signal were negatively correlated with VCF malignancy. CONCLUSION: It is possible to estimate the malignancy risk of VCF by using a small number of MRI features and patient age. The diagnostic performance of models selected by logistic regression, support vector machine, neural network, and classification tree was similar.

Research synthesis: what is the diagnostic performance of magnetic resonance imaging to discriminate benign from malignant vertebral compression fractures? Systematic review and meta-analysis.

STUDY DESIGN: This study is a research synthesis of the published literature evaluating the performance of magnetic resonance imaging (MRI) for differentiation of malignant from benign vertebral compression fractures (VCFs). OBJECTIVE: Perform a systematic review and meta-analysis to summarize and combine the published data on MRI for discriminating malignant from benign VCFs. SUMMARY OF BACKGROUND DATA: The differentiation between benign and malignant VCFs in the spine is a challenging problem confronting spine practitioners. METHODS: MEDLINE, EMBASE, and other databases were searched by 2 independent reviewers to identify studies that reported the performance of MRI for discriminating malignant from benign VCF. Included studies were assessed for described MRI features and study quality. The sensitivity, specificity, and diagnostic odds ratio (OR) of each feature were pooled with a random-effects model weighted by the inverse of the variance of each individual estimate. RESULTS: A total of 31 studies with 1685 subjects met the selection criteria. All the studies focused on describing specific features rather than overall diagnostic performance. Signal intensity ratio on opposed phase (chemical shift) imaging 0.8 or more (OR = 164), apparent diffusion coefficient on echo planar diffusion-weighted images 1.5 × 10(-3) mm2/s or less with b value 500 s/mm2 (OR = 130), presence of other noncharacteristic vertebral lesions (OR = 55), presence of paraspinal mass (OR = 33), involvement of posterior element (OR = 28), involvement of pedicle (OR = 24), complete replacement of normal bone marrow in VCF (OR = 19), presence of epidural mass (OR = 13), and diffuse convexity of posterior vertebral border (OR = 10) were associated with malignant VCFs, whereas coexisting healed benign VCF (OR = 0.006), presence of "fluid sign" (OR = 0.08), presence of focal posterior vertebral border convexity/retropulsion (OR = 0.08), and band-like shape of abnormal signal (OR = 0.07) were associated with benign VCFs. CONCLUSION: Several specific MRI features using signal intensity characteristics, morphological characteristics, quantitative techniques, and findings at other levels can be useful for distinguishing benign from malignant VCFs and can serve as inputs for a prediction model. Observer performance reliability has not been adequately assessed.