Investigation of ComBat Harmonization on Radiomic and Deep Features from Multi-Center Abdominal MRI Data.

Autor: Jia W; Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 7009, Cincinnati, OH, 45229, USA.; Department of Environmental and Public Health, Division of Biostatistics and Bioinformatics, University of Cincinnati, Cincinnati College of Medicine, Cincinnati, OH, USA., Li H; Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 7009, Cincinnati, OH, 45229, USA.; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA., Ali R; Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 7009, Cincinnati, OH, 45229, USA., Shanbhogue KP; Department of Radiology, New York University Langone Health, New York, NY, USA., Masch WR; Department of Radiology, University of Michigan, Michigan Medicine, Ann Arbor, MI, USA., Aslam A; Department of Radiology, University of Michigan, Michigan Medicine, Ann Arbor, MI, USA., Harris DT; Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, Emergency Medicine, University of Wisconsin, Madison, WI, USA., Reeder SB; Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, Emergency Medicine, University of Wisconsin, Madison, WI, USA., Dillman JR; Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 7009, Cincinnati, OH, 45229, USA.; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA., He L; Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 7009, Cincinnati, OH, 45229, USA. lili.he@cchmc.org.; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA. lili.he@cchmc.org.; Computer Science, Biomedical Engineering, Biomedical Informatics, University of Cincinnati, Cincinnati, OH, USA. lili.he@cchmc.org.
Jazyk: angličtina
Zdroj: Journal of imaging informatics in medicine [J Imaging Inform Med] 2024 Sep 16. Date of Electronic Publication: 2024 Sep 16.
DOI: 10.1007/s10278-024-01253-0
Abstrakt: ComBat harmonization has been developed to remove non-biological variations for data in multi-center research applying artificial intelligence (AI). We investigated the effectiveness of ComBat harmonization on radiomic and deep features extracted from large, multi-center abdominal MRI data. A retrospective study was conducted on T2-weighted (T2W) abdominal MRI data retrieved from individual patients with suspected or known chronic liver disease at three study sites. MRI data were acquired using systems from three manufacturers and two field strengths. Radiomic features and deep features were extracted using the PyRadiomics pipeline and a Swin Transformer. ComBat was used to harmonize radiomic and deep features across different manufacturers and field strengths. Student's t-test, ANOVA test, and Cohen's F score were applied to assess the difference in individual features before and after ComBat harmonization. Between two field strengths, 76.7%, 52.9%, and 26.7% of radiomic features, and 89.0%, 56.5%, and 0.1% of deep features from three manufacturers were significantly different. Among the three manufacturers, 90.1% and 75.0% of radiomic features and 89.3% and 84.1% of deep features from two field strengths were significantly different. After ComBat harmonization, there were no significant differences in radiomic and deep features among manufacturers or field strengths based on t-tests or ANOVA tests. Reduced Cohen's F scores were consistently observed after ComBat harmonization. ComBat harmonization effectively harmonizes radiomic and deep features by removing the non-biological variations due to system manufacturers and/or field strengths in large multi-center clinical abdominal MRI datasets.
(© 2024. The Author(s).)
Databáze: MEDLINE
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