Alexander V. Ortiz , Jarrod J. Eisma , Dann Martin , Andre H. Lagrange , Cari Motuzas , William Nobis , Bassel W. Abou-Khalil , Victoria L. Morgan , Jonah Fox
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Improving our ability to accurately detect TEs by MRI is an important step in improving surgical outcomes in patients with drug-resistant epilepsy. We performed a review on existing imaging modalities for detecting TEs and report on our attempt to use a voxel-based morphometry (VBM) algorithm to detect TEs in T1-weighted MRIs of 81 patients from a database comprised of 25 patients with confirmed encephaloceles and 56 controls. Our program's sensitivity and specificity were compared to those of two neuroradiologists and two epileptologists using visualization during surgery as the gold standard. On average, the neuroradiologists and epileptologists had sensitivities of 41 % and 58 % and specificities of 81 % and 60 % while our VBM-based approach had sensitivities and specificities ranging from 11 % to 50 % and 0.2 % to 17 %, respectively. 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引用次数: 0
摘要
颞叶脑瘤(TEs)是大脑实质通过中颅窝底的结构性缺损疝出。颞叶脑疝是一种比较常见的、但最近才发现的导致耐药性癫痫的潜在原因。不受控制的癫痫会对长期健康造成许多负面影响,包括增加死亡风险。手术是治疗耐药性癫痫的最有效方法。预测手术成功的最重要因素之一是在成像中发现异常。然而,TE 难以检测,在神经影像学研究中经常被忽视。提高磁共振成像准确检测 TE 的能力是改善耐药癫痫患者手术效果的重要一步。我们对现有的检测 TE 的成像模式进行了回顾,并报告了我们尝试使用基于体素形态测量(VBM)算法检测 T1 加权 MRI 中 81 例患者的 TE 的结果,该数据库由 25 例确诊脑瘤患者和 56 例对照患者组成。我们将程序的灵敏度和特异性与两位神经放射科医生和两位癫痫科医生的灵敏度和特异性进行了比较,前者使用手术中的可视化作为金标准。平均而言,神经放射学专家和癫痫专家的灵敏度分别为 41 % 和 58 %,特异性分别为 81 % 和 60 %,而我们基于 VBM 的方法的灵敏度和特异性分别为 11 % 至 50 % 和 0.2 % 至 17 %。这项研究概述了用于检测 TE 的不同成像模式,并强调了经验丰富的医生和尖端计算方法在检测 TE 方面遇到的困难。我们的研究结果表明,基于 VBM 的方法有可能用于提高临床医生检测 TE 的能力,从而促进手术规划,通过更有针对性的定位来改善手术效果,并改善继发于 TE 的耐药性癫痫患者的长期健康和福祉。
Detection challenges of temporal encephaloceles in epilepsy: A retrospective analysis
Temporal encephaloceles (TEs) are herniations of cerebral parenchyma through structural defects in the floor of the middle cranial fossa. They are a relatively common, but only relatively recently identified potential cause of drug-resistant epilepsy. Uncontrolled epilepsy is associated with many negative long term health consequences including a heightened risk of death. The most effective treatment for drug-resistant epilepsy is surgery. One of the most predictive factors associated with successful surgery is identification of an abnormality on imaging. However, TEs can be difficult to detect and are often overlooked on neuroimaging studies. Improving our ability to accurately detect TEs by MRI is an important step in improving surgical outcomes in patients with drug-resistant epilepsy. We performed a review on existing imaging modalities for detecting TEs and report on our attempt to use a voxel-based morphometry (VBM) algorithm to detect TEs in T1-weighted MRIs of 81 patients from a database comprised of 25 patients with confirmed encephaloceles and 56 controls. Our program's sensitivity and specificity were compared to those of two neuroradiologists and two epileptologists using visualization during surgery as the gold standard. On average, the neuroradiologists and epileptologists had sensitivities of 41 % and 58 % and specificities of 81 % and 60 % while our VBM-based approach had sensitivities and specificities ranging from 11 % to 50 % and 0.2 % to 17 %, respectively. This work provides an overview of the different imaging modalities utilized in the detection of TEs and highlights the difficulties associated with their detection for both experienced physicians and cutting-edge computational methods. Our findings suggest that VBM-based methods could potentially be used to enhance clinicians' ability to detect TEs thereby facilitating surgical planning, improving surgical outcomes by allowing for more specific targeting, and bettering the long-term health and well-being of patients with drug-resistant epilepsy secondary to TEs.
期刊介绍:
Magnetic Resonance Imaging (MRI) is the first international multidisciplinary journal encompassing physical, life, and clinical science investigations as they relate to the development and use of magnetic resonance imaging. MRI is dedicated to both basic research, technological innovation and applications, providing a single forum for communication among radiologists, physicists, chemists, biochemists, biologists, engineers, internists, pathologists, physiologists, computer scientists, and mathematicians.