弥散张量成像诊断创伤性脑损伤的验证

Micah Daniel Vinet , Alexander Samir Ayoub , Russell Chow , Joseph C. Wu
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引用次数: 0

摘要

背景和目的随着准确诊断创伤性脑损伤(TBI)对标准化方法的需求日益增加,弥散张量成像(DTI)作为一种辅助方法提供了很好的诊断结果,但仍未得到充分利用。本研究的目的是验证 DTI 与统计参数映射 (SPM) 在创伤性脑损伤 (TBI) 中的应用,支持将其用作诊断工具。对 42 名对照组患者(平均年龄为 34.1 岁;年龄范围为 19 - 58 岁;28 名男性和 13 名女性)进行了认知障碍和神经异常筛查(n = 41)。将临床诊断为创伤性脑损伤的 18 名患者(第一组:平均年龄 41.8 岁;年龄范围 23 - 70 岁;男性 9 人,女性 9 人;第二组:平均年龄 45.7 岁;年龄范围 23 - 68 岁;男性 9 人,女性 9 人)(n = 36)汇集在一起。使用 3 特斯拉核磁共振成像扫描仪采集 DTI 图像。使用 SPM 对 DTI 图像进行基于体素的 t 检验分析,将每个人与常模对照组进行比较,生成每个对照组和每个 TBI 患者的 z 图。测试统计的范围为 p 值(0.001-0.05)和群集范围值(0、30、60、65、70、75)。受试者工作特征曲线下面积(AUCROC)用于验证诊断能力。对所有 p 值和范围阈值进行 AUCROC 分析。结果和结论在两个队列中指定的 p 值范围和聚类范围阈值范围内,最大 AUCROC 为 1.000。较高的 AUCROC 支持对所提出的方法进行验证,并支持将弥散张量成像和 SPM 用作创伤性脑损伤的辅助诊断工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validation of diffusion tensor imaging for diagnosis of traumatic brain injury

Background and Purpose

With an increased need for standardized methodology in accurate diagnosis of Traumatic Brain Injury (TBI), Diffusion Tensor Imaging (DTI) has provided promising diagnostic results as an adjunct modality yet remains underutilized. The purpose of this study was to validate the use of DTI with Statistical Parametric Mapping (SPM) for Traumatic Brain Injury (TBI) supporting its use as a diagnostic tool.

Materials and Methods

This study was retrospective and compared controls to patients clinically diagnosed with TBI. Forty-two controls (mean age = 34.1; range, 19 - 58; 28 Males and 13 Females) were screened (n = 41) for cognitive impairment and neurological abnormality. Two cohorts, each of eighteen patients (first cohort: mean age, 41.8; range, 23 - 70; 9 Males and 9 Females; second cohort: mean age, 45.7; range, 23 - 68; 9 Males and 9 Females) clinically diagnosed with TBI (n = 36) were pooled. DTI image acquisition was obtained using a 3 Tesla MRI scanner. DTI images were analyzed through voxel-based t-tests using SPM comparing each individual to the normative control group to generate z-maps for each individual control and each individual patient with a TBI. Test statistics were ranged for p-values (0.001-0.05) and cluster extent values (0, 30, 60, 65, 70, 75). Area Underneath A Receiver Operating Characteristic Curve (AUCROC) was used to validate diagnostic capability. AUCROC analysis was conducted on all sets of p-value and extent threshold values. Significance of results was determined by examining the AUCROC values.

Results and Conclusions

A maximal AUCROC of 1.000 was obtained across the p-value range and cluster extent thresholding values specified across the two cohorts. The high AUCROC supports validation of the methodology presented and the use of diffusion tensor imaging and SPM as an adjunct diagnostic tool for TBI.

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来源期刊
Neuroscience informatics
Neuroscience informatics Surgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology
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