Pastore Luigi Vincenzo, Sudhakar Sniya Valsa, Mankad Kshitij, De Vita Enrico, Biswas Asthik, Tisdall Martin M, Chari Aswin, Figini Matteo, Tahir M Zubair, Adler Sophie, Moeller Friederike, Cross J Helen, Pujar Suresh, Wagstyl Konrad, Ripart Mathilde, Löbel Ulrike, Cirillo Luigi, D'Arco Felice
Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, 40138, Italy.
Neuroradiology Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Ospedale Bellaria, Bologna, Italy.
Neuroradiology. 2025 Mar;67(3):665-675. doi: 10.1007/s00234-024-03488-8. Epub 2024 Oct 23.
Malformations of cortical development (MCDs) in children with focal epilepsy pose significant diagnostic challenges, and a precise radiological diagnosis is crucial for surgical planning. New MRI sequences and the use of artificial intelligence (AI) algorithms are considered very promising in this regard, yet studies evaluating the relative contribution of each diagnostic technique are lacking.
The study was conducted using a dedicated "EPI-MCD MR protocol" with a 3 Tesla MRI scanner in patients with focal epilepsy and previously negative MRI. MRI sequences evaluated included 3D FLAIR, 3D T1 MPRAGE, T2 Turbo Spin Echo (TSE), 3D T1 MP2RAGE, and Arterial Spin Labelling (ASL). Two paediatric neuroradiologists scored each sequence for localisation and extension of the lesion. The MELD-FCD AI classifier's performance in identifying pathological findings was also assessed. We only included patients where a diagnosis of MCD was subsequently confirmed on histology and/or sEEG.
The 3D FLAIR sequence showed the highest yield in detecting epileptogenic lesions, with 3D T1 MPRAGE, T2 TSE, and 3D T1 MP2RAGE sequences showing moderate to low yield. ASL was the least useful. The MELD-FCD classifier achieved a 69.2% true positive rate. In one case, MELD identified a subtle area of cortical dysplasia overlooked by the neuroradiologists, changing the management of the patient.
The 3D FLAIR sequence is the most effective in the MRI-based diagnosis of subtle epileptogenic lesions, outperforming other sequences in localisation and extension. This pilot study emphasizes the importance of careful assessment of the value of additional sequences.
局灶性癫痫患儿的皮质发育畸形(MCDs)带来了重大的诊断挑战,精确的放射学诊断对于手术规划至关重要。新型MRI序列及人工智能(AI)算法的应用在这方面被认为非常有前景,但缺乏评估每种诊断技术相对贡献的研究。
本研究对患有局灶性癫痫且之前MRI检查为阴性的患者,使用配备3特斯拉MRI扫描仪的专用“EPI-MCD MR方案”进行。评估的MRI序列包括3D FLAIR、3D T1 MPRAGE、T2快速自旋回波(TSE)、3D T1 MP2RAGE和动脉自旋标记(ASL)。两名儿科神经放射科医生对每个序列的病变定位和范围进行评分。还评估了MELD-FCD AI分类器在识别病理结果方面的性能。我们仅纳入了随后经组织学和/或立体脑电图(sEEG)确诊为MCD的患者。
3D FLAIR序列在检测致痫性病变方面的阳性率最高,3D T1 MPRAGE、T2 TSE和3D T1 MP2RAGE序列的阳性率为中度至低度。ASL最无用。MELD-FCD分类器的真阳性率为69.2%。在1例病例中,MELD识别出神经放射科医生忽略的一个细微的皮质发育异常区域,改变了患者的治疗方案。
3D FLAIR序列在基于MRI诊断细微致痫性病变方面最有效,在病变定位和范围方面优于其他序列。这项初步研究强调了仔细评估附加序列价值的重要性。