期刊
INVESTIGATIVE RADIOLOGY
卷 55, 期 9, 页码 601-616出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/RLI.0000000000000666
关键词
quantitative imaging; quantitative imaging biomarker alliance; standardization; diffusion-weighted imaging; synthetic MRI; magnetic resonance fingerprinting; chest CT; radiomics; artificial intelligence; deep learning
资金
- AMED [JP19lk1010025h9902]
- JSPS KAKENHI [19K17150, 19K17177, 18H02772, JP16H06280]
- Health, Labour and Welfare Policy Research Grants for Research on Region Medical
- Promotion and Mutual AidCorporation for Private Schools of Japan
- Grants-in-Aid for Scientific Research [18H02772, 19K17177, 19K17150] Funding Source: KAKEN
Radiological images have been assessed qualitatively in most clinical settings by the expert eyes of radiologists and other clinicians. On the other hand, quantification of radiological images has the potential to detect early disease that may be difficult to detect with human eyes, complement or replace biopsy, and provide clear differentiation of disease stage. Further, objective assessment by quantification is a prerequisite of personalized/precision medicine. This review article aims to summarize and discuss how the variability of quantitative values derived from radiological images are induced by a number of factors and how these variabilities are mitigated and standardization of the quantitative values are achieved. We discuss the variabilities of specific biomarkers derived from magnetic resonance imaging and computed tomography, and focus on diffusion-weighted imaging, relaxometry, lung density evaluation, and computer-aided computed tomography volumetry. We also review the sources of variability and current efforts of standardization of the rapidly evolving techniques, which include radiomics and artificial intelligence.
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