MRI techniques for detecting focal cortical dysplasia: A systematic review

MRI is the cornerstone for detecting and characterising focal cortical dysplasia (FCD), a leading cause of drug-resistant epilepsy. Accurate identification of FCD is critical, as MRI-positive patients have markedly better surgical and clinical outcomes. However, lesion detection can be challenging, particularly in subtle or MRI-negative cases, and a range of MRI techniques has been developed to improve diagnostic performance.

PubMed, Embase, Scopus, and Web of Science were searched up to April 2025. Diagnostic accuracy studies comparing MRI findings with histopathology or multidisciplinary consensus were retained. 68 studies satisfied eligibility; data extraction was performed, and risk of bias was assessed with QUADAS-2. Marked methodological and outcome heterogeneity precluded meta-analysis, so results were synthesised narratively.

Conventional 1.5T/3T protocols incorporating 3D-T1 and FLAIR were reported to identify most type II lesions, with sensitivities of 50-91 %. At 7T, additional lesions, due partially to the characteristic "black-line" sign, were detected. Quantitative or specialised sequences and post-processing approaches enhanced detection in MRI-negative or type I/III cohorts. Across all patients, machine-learning classifiers yielded sensitivities of 74-93 % but exhibited wide-ranging specificities (34-100 %).

Based on these findings, a tiered diagnostic pathway is recommended: initial evaluation with standard MRI followed, when clinical suspicion persists, by high-field imaging and advanced quantitative or computational methods. Standard MRI detects most type II lesions, but advanced imaging and computational methods improve detection in MRI-negative or subtle cases; real-world implementation requires access, expertise, and standardised validation. Key limitations of the review were study heterogeneity, single-reviewer processes, and lack of consecutively case-sampled studies. The field would benefit from a multi-centre benchmark dataset of operated, histologically confirmed, seizure-free FCD patients, enabling fair head-to-head evaluation of detection methods.