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Current Medical Imaging

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ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

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Review Article

Distinguishing Intramedullary Spinal Cord Neoplasms from Non-Neoplastic Conditions by Analyzing the Classic Signs on MRI in the Era of AI

Author(s): Ernest Junrui Lim*, Natalie Wei Lyn Leong and Chi Long Ho

Volume 18, Issue 8, 2022

Published on: 07 March, 2022

Article ID: e021221198486 Pages: 11

DOI: 10.2174/1573405617666211202102235

Price: $65

Abstract

Intramedullary lesions can be challenging to diagnose, given the wide range of possible pathologies. Each lesion has unique clinical and imaging features, which are best evaluated using magnetic resonance imaging. Radiological imaging is unique with rich, descriptive patterns and classic signs-which are often metaphorical. In this review, we present a collection of classic MRI signs, ranging from neoplastic to non-neoplastic lesions, within the spinal cord. The Differential Diagnosis (DD) of intramedullary lesions can be narrowed down by careful analysis of the classic signs and patterns of involvement in the spinal cord. Furthermore, the signs are illustrated memorably with emphasis on the pathophysiology, mimics, and pitfalls. Artificial Intelligence (AI) algorithms, particularly deep learning, have made remarkable progress in image recognition tasks. The classic signs and related illustrations can enhance a pattern recognition approach in diagnostic radiology. Deep learning can potentially be designed to distinguish neoplastic from non-neoplastic processes by pattern recognition of the classic MRI signs.

Keywords: Frosting sign, intramedullary lesion, posterior vertebral scalloping , rim and flame sign, scalpel, snake-eyes sign.

Graphical Abstract

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