A Protocol for Body MRI/CT and Extraction of Imaging-Derived Phenotypes (IDPs) from the China Phenobank Project.

IF 3.7 Q2 GENETICS & HEREDITY

Phenomics (Cham, Switzerland) Pub Date : 2024-08-27 eCollection Date: 2024-12-01 DOI:10.1007/s43657-023-00141-x

Chengyan Wang, Shuo Wang, Sha Hua, Ruokun Li, Yan Li, Zhang Shi, Kai Feng, Lizhen Lan, Meng Liu, Xutong Kuang, Xueqin Xia, Shihai Zhao, Xiaodan Ye, Jianhua Jin, Jing Li, Bin Yang, Ming-Hua Zheng, Weibo Chen, Ying-Hua Chu, Juan Hu, Xiahai Zhuang, Xiaolong Qi, Wenjia Bai, He Wang, Jingchun Luo, Mei Tian

{"title":"A Protocol for Body MRI/CT and Extraction of Imaging-Derived Phenotypes (IDPs) from the China Phenobank Project.","authors":"Chengyan Wang, Shuo Wang, Sha Hua, Ruokun Li, Yan Li, Zhang Shi, Kai Feng, Lizhen Lan, Meng Liu, Xutong Kuang, Xueqin Xia, Shihai Zhao, Xiaodan Ye, Jianhua Jin, Jing Li, Bin Yang, Ming-Hua Zheng, Weibo Chen, Ying-Hua Chu, Juan Hu, Xiahai Zhuang, Xiaolong Qi, Wenjia Bai, He Wang, Jingchun Luo, Mei Tian","doi":"10.1007/s43657-023-00141-x","DOIUrl":null,"url":null,"abstract":"<p><p>Currently, standard protocols for body imaging and corresponding image processing pipelines in population-based cohort studies are unavailable, limiting the applications of body imaging. Based on the China Phenobank Project (CHPP), the present study described a body imaging protocol for multiple organs, including cardiac structures, liver, spleen, pancreas, kidneys, lung, prostate, and uterus, and the corresponding image processing pipelines promoted its development. Briefly, the body imaging protocol comprised a 40-min cardiac magnetic resonance imaging (MRI) scan, a 5-min computed tomography (CT) scan, a 20-min abdominal MRI scan, and a 10-min pelvic MRI scan. The recommended image processing pipeline utilized deep learning segmentation models to facilitate the analysis of large amount of data. This study aimed to provide a reference for planning studies based on the CHPP platform.</p>","PeriodicalId":74435,"journal":{"name":"Phenomics (Cham, Switzerland)","volume":"4 6","pages":"594-616"},"PeriodicalIF":3.7000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11889319/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Phenomics (Cham, Switzerland)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s43657-023-00141-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}

引用次数: 0

Abstract

Currently, standard protocols for body imaging and corresponding image processing pipelines in population-based cohort studies are unavailable, limiting the applications of body imaging. Based on the China Phenobank Project (CHPP), the present study described a body imaging protocol for multiple organs, including cardiac structures, liver, spleen, pancreas, kidneys, lung, prostate, and uterus, and the corresponding image processing pipelines promoted its development. Briefly, the body imaging protocol comprised a 40-min cardiac magnetic resonance imaging (MRI) scan, a 5-min computed tomography (CT) scan, a 20-min abdominal MRI scan, and a 10-min pelvic MRI scan. The recommended image processing pipeline utilized deep learning segmentation models to facilitate the analysis of large amount of data. This study aimed to provide a reference for planning studies based on the CHPP platform.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Phenomics (Cham, Switzerland)

自引率

0.00%

发文量