Ryu Dong-Woo, Hong Yun Jeong, Cho Jung Hee, Kwak Kichang, Lee Jong-Min, Shim Yong S, Youn Young Chul, Yang Dong Won
Department of Neurology, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea.
Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea.
Brain Imaging Behav. 2022 Oct;16(5):2086-2096. doi: 10.1007/s11682-022-00678-x. Epub 2022 Jun 13.
A quantitative analysis of brain volume can assist in the diagnosis of Alzheimer's disease (AD) which is ususally accompanied by brain atrophy. With an automated analysis program Quick Brain Volumetry (QBraVo) developed for volumetric measurements, we measured regional volumes and ratios to evaluate their performance in discriminating AD dementia (ADD) and mild cognitive impairment (MCI) patients from normal controls (NC). Validation of QBraVo was based on intra-rater and inter-rater reliability with a manual measurement. The regional volumes and ratios to total intracranial volume (TIV) and to total brain volume (TBV) or total cerebrospinal fluid volume (TCV) were compared among subjects. The regional volume to total cerebellar volume ratio named Standardized Atrophy Volume Ratio (SAVR) was calculated to compare brain atrophy. Diagnostic performances to distinguish among NC, MCI, and ADD were compared between MMSE, SAVR, and the predictive model. In total, 56 NCs, 44 MCI, and 45 ADD patients were enrolled. The average run time of QBraVo was 5 min 36 seconds. Intra-rater reliability was 0.999. Inter-rater reliability was high for TBV, TCV, and TIV (R = 0.97, 0.89 and 0.93, respectively). The medial temporal SAVR showed the highest performance for discriminating ADD from NC (AUC = 0.808, diagnostic accuracy = 80.2%). The predictive model using both MMSE and medial temporal SAVR improved the diagnostic performance for MCI in NC (AUC = 0.844, diagnostic accuracy = 79%). Our results demonstrated QBraVo is a fast and accurate method to measure brain volume. The regional volume calculated as SAVR could help to diagnose ADD and MCI and increase diagnostic accuracy for MCI.
脑容量的定量分析有助于阿尔茨海默病(AD)的诊断,该病通常伴有脑萎缩。借助为容积测量开发的自动分析程序快速脑容积测定法(QBraVo),我们测量了区域容积和比率,以评估其在区分AD痴呆(ADD)、轻度认知障碍(MCI)患者与正常对照(NC)方面的性能。QBraVo的验证基于与手动测量的评分者内和评分者间可靠性。比较了受试者之间各区域容积以及与总颅内体积(TIV)、总脑体积(TBV)或总脑脊液体积(TCV)的比率。计算了区域容积与小脑总体积的比率,即标准化萎缩体积比率(SAVR),以比较脑萎缩情况。比较了简易精神状态检查表(MMSE)、SAVR和预测模型在区分NC、MCI和ADD方面的诊断性能。总共纳入了56名NC、44名MCI和45名ADD患者。QBraVo的平均运行时间为5分36秒。评分者内可靠性为0.999。TBV、TCV和TIV的评分者间可靠性较高(R分别为0.97、0.89和0.93)。内侧颞叶SAVR在区分ADD与NC方面表现最佳(曲线下面积[AUC]=0.808,诊断准确率=80.2%)。同时使用MMSE和内侧颞叶SAVR的预测模型提高了在NC中对MCI的诊断性能(AUC=0.844,诊断准确率=79%)。我们的结果表明,QBraVo是一种快速准确的脑容量测量方法。计算为SAVR的区域容积有助于诊断ADD和MCI,并提高对MCI的诊断准确率。