Клиническая интеграция МРТ мозга и шнура улучшает дифференциальное диагностирование множественных склерозов.
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Rocca Maria A, Ratzinger Sophia, Preziosa Paolo, Meani Alessandro, Gueye Mor, Vezzulli Paolo, Pagani Elisabetta, Esposito Federica, Giordano Antonino, Colombo Bruno, Falini Andrea, Filippi Massimo
Аннотация
Оригинал публикации
Clinical integration of brain and cord MRI features improves differential diagnosis of multiple sclerosis.
OBJECTIVE: To explore the role of brain and spinal cord MRI features in differentiating patients with suspected central nervous system (CNS) inflammatory diseases.
MATERIAL AND METHODS: Prospective data from 125 patients undergoing diagnostic evaluation, including 1.5 T brain and spinal cord MRI scans from February 2021 and March 2024 were analyzed. The cohort comprised 91 patients with multiple sclerosis (MS), 15 with other inflammatory neurological diseases (OIND), and 19 with non-inflammatory neurological diseases (NIND). Brain and spinal cord lesion topographies and morphological features were evaluated to identify MRI features discriminating MS from OIND and NIND.
RESULTS: Random forest analysis identified key MRI features supporting MS diagnosis over OIND: absence of longitudinally extensive transverse myelitis (relative importance [RI] = 100%), presence of ≥ 1 Dawson's finger (RI = 55.3%), ≥ 1 cortical lesion (RI = 42.6%), and ≥ 1 brain T2-hyperintense white matter (WM) lesion (RI = 36.4%). After excluding the presence of ≥ 1 brain T2-hyperintense WM lesion, fulfilling ≥ 2 of the 3 selected criteria distinguished MS from OIND patients with a sensitivity of 0.59 and a specificity of 0.80. For distinguishing MS from NIND, relevant MRI features included ≥ 1 T2-hyperintense spinal cord lesion (RI = 100.0%), ≥ 1 Dawson's finger (RI = 84.3%), ≥ 1 cortical lesion (RI = 61.4%), ≥ 1 cerebellar peduncle lesion (RI = 52.2%) and ≥ 3 central vein sign-positive lesions (RI = 27.8%). Fulfilling ≥ 2 of the 5 selected criteria identified MS patients with a sensitivity of 0.64 and a specificity of 0.84.
CONCLUSION: Integrating specific MRI features in the diagnostic work-up of patients with suspected CNS inflammatory disease improves differentiation between MS, OIND, and NIND, reducing the risk of misdiagnosis.