T. Nir, S. Thomopoulos, J. Villalon-Reina, A. Zavaliangos-Petropulu, E. Dennis, Robert I. Reid, M. Bernstein, B. Borowski, C. Jack, M. Weiner, N. Jahanshad, P. Thompson
{"title":"多壳扩散MRI测量脑老化:与ADNI3的初步比较","authors":"T. Nir, S. Thomopoulos, J. Villalon-Reina, A. Zavaliangos-Petropulu, E. Dennis, Robert I. Reid, M. Bernstein, B. Borowski, C. Jack, M. Weiner, N. Jahanshad, P. Thompson","doi":"10.1109/ISBI.2019.8759486","DOIUrl":null,"url":null,"abstract":"The Alzheimer’s Disease Neuroimaging Initiative (phase 3; ADNI3) is collecting multisite diffusion MRI (dMRI) data using protocols optimized for different scanner vendors, including one multi-shell protocol, to better understand disease effects. Here, we analyzed multi-shell scans from 56 ADNI3 participants (age: $74.3 \\pm 7.5$ yrs; 17F/49M). We evaluated whether multi-shell dMRI measures computed from neurite orientation dispersion and density imaging (NODDI) and diffusion kurtosis imaging (DKI) differentiated people with mild cognitive impairment from healthy controls with higher sensitivity than standard diffusion tensor imaging (DTI) measures. We also assessed the effects of various multi-shell derived dMRI samples on the sensitivity of DTI measures. While we did not identify large differences in effect sizes among tensor-based, NODDI, or DKI measures, we did detect greater effect sizes from DTI measures estimated using multi-shell data converted to single-shell HARDI compared to those fit using the subset of $48 b=1000s /$mm $^{2}$ volumes, typical of DTI.","PeriodicalId":119935,"journal":{"name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Multi-Shell Diffusion MRI Measures of Brain Aging: A Preliminary Comparison From ADNI3\",\"authors\":\"T. Nir, S. Thomopoulos, J. Villalon-Reina, A. Zavaliangos-Petropulu, E. Dennis, Robert I. Reid, M. Bernstein, B. Borowski, C. Jack, M. Weiner, N. Jahanshad, P. Thompson\",\"doi\":\"10.1109/ISBI.2019.8759486\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Alzheimer’s Disease Neuroimaging Initiative (phase 3; ADNI3) is collecting multisite diffusion MRI (dMRI) data using protocols optimized for different scanner vendors, including one multi-shell protocol, to better understand disease effects. Here, we analyzed multi-shell scans from 56 ADNI3 participants (age: $74.3 \\\\pm 7.5$ yrs; 17F/49M). We evaluated whether multi-shell dMRI measures computed from neurite orientation dispersion and density imaging (NODDI) and diffusion kurtosis imaging (DKI) differentiated people with mild cognitive impairment from healthy controls with higher sensitivity than standard diffusion tensor imaging (DTI) measures. We also assessed the effects of various multi-shell derived dMRI samples on the sensitivity of DTI measures. While we did not identify large differences in effect sizes among tensor-based, NODDI, or DKI measures, we did detect greater effect sizes from DTI measures estimated using multi-shell data converted to single-shell HARDI compared to those fit using the subset of $48 b=1000s /$mm $^{2}$ volumes, typical of DTI.\",\"PeriodicalId\":119935,\"journal\":{\"name\":\"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISBI.2019.8759486\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2019.8759486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
阿尔茨海默病神经影像学倡议(第3期;ADNI3)正在使用针对不同扫描仪供应商优化的协议(包括一个多外壳协议)收集多位点扩散MRI (dMRI)数据,以更好地了解疾病影响。在这里,我们分析了来自56名ADNI3参与者(年龄:74.3美元/ pm 7.5美元/年;17 f / 49米)。我们评估了由神经突定向弥散和密度成像(NODDI)和弥散峰度成像(DKI)计算的多壳dMRI测量是否能以比标准弥散张量成像(DTI)测量更高的灵敏度将轻度认知障碍患者与健康对照区分开来。我们还评估了各种多壳衍生的dMRI样品对DTI测量灵敏度的影响。虽然我们没有发现基于张量、NODDI或DKI测量之间的效应大小差异很大,但我们确实发现,与使用典型DTI的$48 b=1000s /$mm $^{2}$体积子集拟合的DTI测量相比,使用转换为单壳HARDI的多壳数据估计的DTI测量的效应大小更大。
Multi-Shell Diffusion MRI Measures of Brain Aging: A Preliminary Comparison From ADNI3
The Alzheimer’s Disease Neuroimaging Initiative (phase 3; ADNI3) is collecting multisite diffusion MRI (dMRI) data using protocols optimized for different scanner vendors, including one multi-shell protocol, to better understand disease effects. Here, we analyzed multi-shell scans from 56 ADNI3 participants (age: $74.3 \pm 7.5$ yrs; 17F/49M). We evaluated whether multi-shell dMRI measures computed from neurite orientation dispersion and density imaging (NODDI) and diffusion kurtosis imaging (DKI) differentiated people with mild cognitive impairment from healthy controls with higher sensitivity than standard diffusion tensor imaging (DTI) measures. We also assessed the effects of various multi-shell derived dMRI samples on the sensitivity of DTI measures. While we did not identify large differences in effect sizes among tensor-based, NODDI, or DKI measures, we did detect greater effect sizes from DTI measures estimated using multi-shell data converted to single-shell HARDI compared to those fit using the subset of $48 b=1000s /$mm $^{2}$ volumes, typical of DTI.