整合标准癫痫方案、ASL-灌注、MP2RAGE/EDGE 和 MELD-FCD 分类器检测细微致痫病灶:3 特斯拉 MRI 试验研究。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-10-23 DOI:10.1007/s00234-024-03488-8
Luigi Vincenzo Pastore, Sniya Valsa Sudhakar, Kshitij Mankad, Enrico De Vita, Asthik Biswas, Martin M Tisdall, Aswin Chari, Matteo Figini, M Zubair Tahir, Sophie Adler, Friederike Moeller, J Helen Cross, Suresh Pujar, Konrad Wagstyl, Mathilde Ripart, Ulrike Löbel, Luigi Cirillo, Felice D'Arco
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引用次数: 0

摘要

背景:局灶性癫痫患儿的皮质发育畸形(MCDs)给诊断带来了巨大挑战,精确的放射学诊断对于手术规划至关重要。新的磁共振成像序列和人工智能(AI)算法的使用被认为在这方面大有可为,但目前还缺乏评估每种诊断技术相对贡献的研究:本研究使用专用的 "EPI-MCD MR 方案",在 3 特斯拉磁共振成像扫描仪上对以前磁共振成像呈阴性的局灶性癫痫患者进行了评估。评估的磁共振成像序列包括三维 FLAIR、三维 T1 MPRAGE、T2 Turbo Spin Echo (TSE)、三维 T1 MP2RAGE 和动脉自旋标记 (ASL)。两名儿科神经放射专家对每个序列的病灶定位和扩展情况进行评分。我们还评估了 MELD-FCD AI 分类器识别病理结果的性能。我们仅纳入了随后经组织学和/或sEEG确诊为MCD的患者:结果:三维 FLAIR 序列在检测致痫病灶方面显示出最高的收益率,三维 T1 MPRAGE、T2 TSE 和三维 T1 MP2RAGE 序列显示出中等到较低的收益率。ASL 的作用最小。MELD-FCD分类器的真阳性率为69.2%。在一个病例中,MELD发现了一个被神经放射科医生忽视的皮质发育不良的微小区域,从而改变了对患者的治疗:结论:三维 FLAIR 序列对基于 MRI 的细微致痫病灶诊断最为有效,在定位和扩展方面优于其他序列。这项试验研究强调了仔细评估附加序列价值的重要性。
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Integrating standard epilepsy protocol, ASL-perfusion, MP2RAGE/EDGE and the MELD-FCD classifier in the detection of subtle epileptogenic lesions: a 3 Tesla MRI pilot study.

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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