TY - GEN
T1 - Determination of reproducible radiomic features for diagnosis of fatty liver disease in a crab-eating macaque model
AU - Wang, Hui
AU - Solomon, Jeffrey
AU - Reza, Syed
AU - Yang, Hee-Jeong
AU - Crozier, Ian
AU - Sayre, Philip J.
AU - Chu, Winston T.
AU - Lee, Byeong-Yeul
AU - Mani, Venkatesh
AU - Friedrich, Thomas C.
AU - O'Connor, David H.
AU - Mulder, Willem J. M.
AU - Worwa, Gabriella
AU - Kuhn, Jens H.
AU - Calcagno, Claudia
AU - Castro, Marcelo A.
N1 - Funding Information: This work was supported in part through Laulima Government Solutions, LLC, prime contract with the U.S. National Institute of Allergy and Infectious Diseases (NIAID) under Contract No. HHSN272201800013C and Kelly Services’ contract with NIAID under Contract No. 75N93019D00027. H.W., M.A.C., H-J.Y., P.J.S., B-Y.L., and G.W. performed this work as employees of Laulima Government Solutions, LLC. J.H.K. and C.C. performed this work as employees of Tunnell Government Services (TGS), a subcontractor of Laulima Government Solutions, LLC, under Contract No. HHSN272201800013C. V.M. performed this work as an employee of Kelly Services under Contract No. 75N93019D00027 with NIAID (Task Order No. 75N93021F00010). This work was also supported in part with federal funds from the National Institutes of Health (NIH) National Cancer Institute (NCI), under Contract No. 75N910D00024, Task Order No. 75N91019F00130, with Leidos Biomedical Research, Inc. I.C. and J.S. performed this work as employees of Leidos Biomedical Research, Inc. as supported by the Clinical Monitoring Research Program Directorate, Frederick National Lab for Cancer Research, sponsored by NCI. This project was also partially funded by the NIH Clinical Center Radiology and Imaging Sciences Center for Infectious Disease Imaging (CIDI), Clinical Center, NIH (S.R. and W.T.C.). The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Department of Health and Human Services or of the institutions and companies affiliated with the authors, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. The study protocol was reviewed and approved by the NIH NIAID Division of Clinical Research (DCR) Integrated Research Facility at Fort Detrick (IRF-Frederick) Animal Care and Use Committee in compliance with all applicable federal regulations governing the protection of animals and research. Publisher Copyright: © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2023
Y1 - 2023
N2 - Evaluation of the intra-subject reproducibility of radiomic features is pivotal but challenging because it requires multiple replicate measurements, typically lacking in the clinical setting. Radiomics analysis based on computed tomography (CT) has been increasingly used to characterize liver malignancies and liver diffusive diseases. However, radiomic features are greatly affected by scanning parameters and reconstruction kernels, among other factors. In this study, we examined the effects of diets, reconstruction kernels, and liver-to-spleen normalization on the intra-subject reproducibility of radiomic features. The final goal of this work is to create a framework that may help identify reproducible radiomics features suitable for further diagnosis and grading of fatty liver disease in nonhuman primates using radiomics analysis. As a first step, the identification of reproducible features is essential. To accomplish this aim, we retrospectively analyzed serial CT images from two groups of crab-eating macaques, fed a normal or atherogenic diet. Serial CT examinations resulted in 45 high-resolution scans. From each scan, two CT images were reconstructed using a standard B kernel and a bone-enhanced D kernel, with and without normalization relative to the spleen. Radiomic features were extracted from six regions in the liver parenchyma. Intra-subject variability showed that many features are fully reproducible regardless of liver disease status whereas others are significantly different in a limited number of tests. Features significantly different between the normal and atherogenic diet groups were also investigated. Reproducible features were listed, with normalized images having more reproducible features.
AB - Evaluation of the intra-subject reproducibility of radiomic features is pivotal but challenging because it requires multiple replicate measurements, typically lacking in the clinical setting. Radiomics analysis based on computed tomography (CT) has been increasingly used to characterize liver malignancies and liver diffusive diseases. However, radiomic features are greatly affected by scanning parameters and reconstruction kernels, among other factors. In this study, we examined the effects of diets, reconstruction kernels, and liver-to-spleen normalization on the intra-subject reproducibility of radiomic features. The final goal of this work is to create a framework that may help identify reproducible radiomics features suitable for further diagnosis and grading of fatty liver disease in nonhuman primates using radiomics analysis. As a first step, the identification of reproducible features is essential. To accomplish this aim, we retrospectively analyzed serial CT images from two groups of crab-eating macaques, fed a normal or atherogenic diet. Serial CT examinations resulted in 45 high-resolution scans. From each scan, two CT images were reconstructed using a standard B kernel and a bone-enhanced D kernel, with and without normalization relative to the spleen. Radiomic features were extracted from six regions in the liver parenchyma. Intra-subject variability showed that many features are fully reproducible regardless of liver disease status whereas others are significantly different in a limited number of tests. Features significantly different between the normal and atherogenic diet groups were also investigated. Reproducible features were listed, with normalized images having more reproducible features.
KW - computed tomography
KW - image reconstruction
KW - non-alcoholic fatty liver disease
KW - radiomics
KW - reproducibility
UR - http://www.scopus.com/inward/record.url?scp=85160914582&partnerID=8YFLogxK
U2 - https://doi.org/10.1117/12.2647632
DO - https://doi.org/10.1117/12.2647632
M3 - Conference contribution
VL - 12468
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2023
A2 - Gimi, Barjor S.
A2 - Krol, Andrzej
PB - SPIE
T2 - Medical Imaging 2023: Biomedical Applications in Molecular, Structural, and Functional Imaging
Y2 - 19 February 2023 through 22 February 2023
ER -