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

Overview

Journal Phenomics

Publisher Springer

Date 2025 Mar 10

PMID 40061820

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

Affiliations

Soon will be listed here.

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.

References

Hundley W, Bluemke D, Finn J, Flamm S, Fogel M, Friedrich M . ACCF/ACR/AHA/NASCI/SCMR 2010 expert consensus document on cardiovascular magnetic resonance: a report of the American College of Cardiology Foundation Task Force on Expert Consensus Documents. J Am Coll Cardiol. 2010; 55(23):2614-62. PMC: 3042771. DOI: 10.1016/j.jacc.2009.11.011. View

Anand S, Tu J, Awadalla P, Black S, Boileau C, Busseuil D . Rationale, design, and methods for Canadian alliance for healthy hearts and minds cohort study (CAHHM) - a Pan Canadian cohort study. BMC Public Health. 2016; 16:650. PMC: 4963999. DOI: 10.1186/s12889-016-3310-8. View

Bamberg F, Kauczor H, Weckbach S, Schlett C, Forsting M, Ladd S . Whole-Body MR Imaging in the German National Cohort: Rationale, Design, and Technical Background. Radiology. 2015; 277(1):206-20. DOI: 10.1148/radiol.2015142272. View

Li X, Morgan P, Ashburner J, Smith J, Rorden C . The first step for neuroimaging data analysis: DICOM to NIfTI conversion. J Neurosci Methods. 2016; 264:47-56. DOI: 10.1016/j.jneumeth.2016.03.001. View

Wang C, Li Y, Lv J, Jin J, Hu X, Kuang X . Recommendation for Cardiac Magnetic Resonance Imaging-Based Phenotypic Study: Imaging Part. Phenomics. 2022; 1(4):151-170. PMC: 8318053. DOI: 10.1007/s43657-021-00018-x. View

Hegedus P, von Stackelberg O, Neumann C, Selder S, Werner N, Erdmann P . How to report incidental findings from population whole-body MRI: view of participants of the German National Cohort. Eur Radiol. 2019; 29(11):5873-5878. DOI: 10.1007/s00330-019-06077-z. View

Bild D, Bluemke D, Burke G, Detrano R, Diez Roux A, Folsom A . Multi-Ethnic Study of Atherosclerosis: objectives and design. Am J Epidemiol. 2002; 156(9):871-81. DOI: 10.1093/aje/kwf113. View

Isensee F, Jaeger P, Kohl S, Petersen J, Maier-Hein K . nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods. 2020; 18(2):203-211. DOI: 10.1038/s41592-020-01008-z. View

van Griethuysen J, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V . Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Res. 2017; 77(21):e104-e107. PMC: 5672828. DOI: 10.1158/0008-5472.CAN-17-0339. View

10.

Petersen S, Matthews P, Bamberg F, Bluemke D, Francis J, Friedrich M . Imaging in population science: cardiovascular magnetic resonance in 100,000 participants of UK Biobank - rationale, challenges and approaches. J Cardiovasc Magn Reson. 2013; 15:46. PMC: 3668194. DOI: 10.1186/1532-429X-15-46. View

11.

Bai W, Suzuki H, Huang J, Francis C, Wang S, Tarroni G . A population-based phenome-wide association study of cardiac and aortic structure and function. Nat Med. 2020; 26(10):1654-1662. PMC: 7613250. DOI: 10.1038/s41591-020-1009-y. View

12.

Petersen S, Matthews P, Francis J, Robson M, Zemrak F, Boubertakh R . UK Biobank's cardiovascular magnetic resonance protocol. J Cardiovasc Magn Reson. 2016; 18:8. PMC: 4736703. DOI: 10.1186/s12968-016-0227-4. View

13.

McKay A, Wilman H, Dennis A, Kelly M, Gyngell M, Neubauer S . Measurement of liver iron by magnetic resonance imaging in the UK Biobank population. PLoS One. 2018; 13(12):e0209340. PMC: 6303057. DOI: 10.1371/journal.pone.0209340. View

14.

Littlejohns T, Holliday J, Gibson L, Garratt S, Oesingmann N, Alfaro-Almagro F . The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions. Nat Commun. 2020; 11(1):2624. PMC: 7250878. DOI: 10.1038/s41467-020-15948-9. View

15.

Raisi-Estabragh Z, Harvey N, Neubauer S, Petersen S . Cardiovascular magnetic resonance imaging in the UK Biobank: a major international health research resource. Eur Heart J Cardiovasc Imaging. 2020; 22(3):251-258. PMC: 7899275. DOI: 10.1093/ehjci/jeaa297. View

16.

Kramer C, Barkhausen J, Flamm S, Kim R, Nagel E . Standardized cardiovascular magnetic resonance imaging (CMR) protocols, society for cardiovascular magnetic resonance: board of trustees task force on standardized protocols. J Cardiovasc Magn Reson. 2008; 10:35. PMC: 2467420. DOI: 10.1186/1532-429X-10-35. View

17.

Hegenscheid K, Kuhn J, Volzke H, Biffar R, Hosten N, Puls R . Whole-body magnetic resonance imaging of healthy volunteers: pilot study results from the population-based SHIP study. Rofo. 2009; 181(8):748-59. DOI: 10.1055/s-0028-1109510. View

18.

Hegenscheid K, Seipel R, Schmidt C, Volzke H, Kuhn J, Biffar R . Potentially relevant incidental findings on research whole-body MRI in the general adult population: frequencies and management. Eur Radiol. 2012; 23(3):816-26. DOI: 10.1007/s00330-012-2636-6. View

19.

Victor R, Haley R, Willett D, Peshock R, Vaeth P, Leonard D . The Dallas Heart Study: a population-based probability sample for the multidisciplinary study of ethnic differences in cardiovascular health. Am J Cardiol. 2004; 93(12):1473-80. DOI: 10.1016/j.amjcard.2004.02.058. View

20.

Cerqueira M, Weissman N, Dilsizian V, Jacobs A, Kaul S, Laskey W . Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. Circulation. 2002; 105(4):539-42. DOI: 10.1161/hc0402.102975. View