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Effects of Computed Tomography Technical Parameters on Body-Composition Analysis

    • The Catholic University of Korea Eunpyeong St. Mary’s Hospital

    Research output: Contribution to journalReview articlepeer-review

    4 Scopus citations

    Abstract

    Body-composition analysis (BCA) is gaining increasing clinical importance, because abnormalities in muscle and fat distribution are closely associated with patient outcomes for various diseases. Although several methods for assessing body composition are available, including bioelectrical impedance analysis, dual-energy X-ray absorptiometry, and magnetic resonance imaging, computed tomography (CT) has emerged as the most widely used imaging modality owing to its accuracy, accessibility, and artificial intelligence-driven automated analytical capabilities. CT-based BCA enables the precise quantification of skeletal muscle and adipose tissues, but its measurements can be influenced by various technical factors, such as the contrast phase, tube current and voltage, slice thickness, reconstruction algorithm, and scanner type. These parameters particularly affect attenuation-based metrics such as muscle density. Recent technological advancements, such as iterative reconstruction, dual-energy CT, and photon-counting CT, have resulted in new capabilities but may further introduce variability. This review summarizes the effects of CT parameters on BCA results and underscores the need for awareness and consistency when performing CT-based BCA. A better understanding of these factors may improve measurement reproducibility and support broader clinical and research applications.

    Original languageEnglish
    Pages (from-to)1157-1171
    Number of pages15
    JournalKorean Journal of Radiology
    Volume26
    Issue number12
    DOIs
    StatePublished - Dec 2025

    Bibliographical note

    Publisher Copyright:
    © 2025 The Korean Society of Radiology.

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Body-composition analysis
    • CT acquisition parameters
    • CT reconstruction techniques
    • Obesity
    • Sarcopenia

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