BACKGROUND AND PURPOSE: Peripheral nerve disorders caused by benign and malignant primary nerve sheath tumors, infiltration or compression of nerves by metastatic disease, and postradiation neuritis demonstrate overlapping features on conventional MR imaging but require vastly different therapeutic approaches. We characterize and compare diffusivities of peripheral nerve lesions in patients undergoing MR neurography for peripheral neuropathy or brachial or lumbosacral plexopathy. MATERIALS AND METHODS: Twenty-three patients, referred for MR neurography at our institution between 2003 and 2009 for a peripheral mononeuropathy or brachial or lumbosacral plexopathy and whose examinations included DWI, received a definitive diagnosis, based on biopsy results or clinical and imaging follow-up, for a masslike or infiltrative peripheral nerve or plexus lesion suspicious for tumor. Mean ADC values were determined within each lesion and compared across 3 groups (benign lesions, malignant lesions, and postradiation changes). RESULTS: Both ANOVA and Kruskal-Wallis tests demonstrated a statistically significant difference in ADC values across the 3 groups (P = .000023, P = .00056, respectively). Post hoc pair-wise comparisons showed that the ADC within malignant tumors differed significantly from that within benign tumors and postradiation changes. ADC within benign tumors and postradiation changes did not differ significantly from each other. CONCLUSIONS: DWI may be highly effective for the differentiation of benign from malignant peripheral nerve masslike or infiltrative lesions.

Objective: To assess the prevalence and clinical implications of variant sciatic nerve anatomy in relation to the piriformis muscle on magnetic resonance neurography (MRN), in patients with lumbosacral neuropathic symptoms. Materials and Methods: In this retrospective single-center study, 254 sciatic nerves, from 127 patients with clinical and imaging findings compatible with extra-spinal sciatica on MRN between 2003 and 2013, were evaluated for the presence and type of variant sciatic nerves, split sciatic nerve, abnormal T2-signal hyperintensity, asymmetric piriformis size and increased nerve caliber, and summarized using descriptive statistics. Two-tailed chi-square tests were performed to compare the anatomical variant type and clinical symptoms between imaging and clinical characteristics. Results: Sixty-four variant sciatic nerves were identified with an equal number of right and left variants. Bilateral variants were noted in 15 cases. Abnormal T2-signal hyperintensity was seen significantly more often in variant compared to conventional anatomy (40/64 vs. 82/190; p = 0.01). A sciatic nerve split was seen significantly more often in variant compared to conventional anatomy (56/64 vs. 20/190; p < 0.0001). Increased nerve caliber, abnormal T2-signal hyperintensity, and asymmetric piriformis size were significantly associated with the clinically symptomatic side compared to the asymptomatic side (98:2, 98:2, and 97:3, respectively; p < 0.0001 for all). Clinical symptoms were correlated with variant compared to conventional sciatic nerve anatomy (64% vs. 46%; p = 0.01). Conclusion: Variant sciatic nerve anatomy, in relation to the piriformis muscle, is frequently identified with MRN and is more likely to be associated with nerve signal changes and symptomatology.

Background/Objectives: This study aimed to create a pipeline for standardized data extraction from lumbar-spine MRI radiology reports using a large language model (LLM) and assess the agreement of the extracted data with research-grade semi-quantitative scoring. Methods: We included a subset of data from a multi-site NIH-funded cohort study of chronic low back pain (cLBP) participants. After initial prompt development, a secure application programming interface (API) deployment of OpenAIs GPT-4 was used to extract different classes of pathology from the clinical radiology report. Unsupervised UMAP and agglomerative clustering of the pathology terms’ embeddings provided insight into model comprehension for optimized prompt design. Model extraction was benchmarked against human extraction (gold standard) with F1 scores and false-positive and false-negative rates (FPR/FNR). Then, an expert MSK radiologist provided comprehensive research-grade scores of the images, and agreement with report-extracted data was calculated using Cohen’s kappa. Results: Data from 230 patients with cLBP were included (mean age 53.2 years, 54% women). The overall model performance for extracting data from clinical reports was excellent, with a mean F1 score of 0.96 across pathologies. The mean FPR was marginally higher than the FNR (5.1% vs. 3.0%). Agreement with comprehensive scoring was moderate (kappa 0.424), and the underreporting of lateral recess stenosis (FNR 63.6%) and overreporting of disc pathology (FPR 42.7%) were noted. Conclusions: LLMs can accurately extract highly detailed information on lumbar spine imaging pathologies from radiology reports. Moderate agreement between the LLM and comprehensive scores underscores the need for less subjective, machine-based data extraction from imaging.