{
  "abstract": "Background\n\nTo determine intermodal agreement of AI-derived volumetric body composition metrics between [18 F]FDG-PET/CT-derived low-dose CT and whole-body MRI (wb-MRI).Methods\n\nWe retrospectively analyzed same-day whole-body low-dose CT, obtained from [¹⁸F]FDG-PET/CT, and wb-MRI from consecutive multiple myeloma patients from the prospective GMMG-HD7- and GMMG-HD8-/DSMM-XIX-trials. An automated deep learning pipeline based on the TotalSegmentator model, and its MRI variant were used to segment skeletal muscle (SM), subcutaneous- (SAT) and abdominal visceral adipose tissue (VAT) from CT and MRI, respectively. Volumetric measures and single-slice estimates were derived. Agreement between CT- and MRI-based metrics was assessed using Pearson r, intraclass correlation coefficients (ICC), and Bland-Altman analyses.Results\n\nForty-two multiple myeloma patients with same-day PET/CT and wb-MRI were included. For AI-based volumetric body composition metrics, CT and MRI demonstrated high agreement (ICC > 0.95) across all SM, SAT and VAT. However, Bland-Altmann plots revealed systematic modality-related differences between MRI and CT: both SM (bias: -2582 ml, p < 0.0001) and VAT (bias: -211 ml, p < 0.0001) were significantly lower when extracted from MRI compared to CT, while for SAT, the difference was not statistically significant (bias: -263 ml, p = 0.1629). For AI-based single slice analysis, agreement remained high for SAT and VAT (ICC > 0.97), while being lower for SM (ICC 0.87). Bland-Altman plots showed that SM was systematically and significantly lower when obtained from MRI than from CT (bias: -18.4cm², p < 0.0001).Conclusions\n\nAutomated body composition measures from (PET-)CT and wb-MRI are highly concordant but show consistent intermodal biases that should be considered when pooling multimodal data or applying modality-agnostic thresholds.Clinical trial number\n\nNot applicable.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Radiology, German Cancer Research Centre (DKFZ), Im Neuenheimer Feld 280, Heidelberg, 69120 , Germany. julius.holzschuh@dkfz.de.",
    "Department of Radiology, German Cancer Research Centre (DKFZ), Im Neuenheimer Feld 280, Heidelberg, 69120 , Germany.",
    "Faculty of Medicine and University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, Cologne, Germany.",
    "German-Speaking Myeloma Multicenter Group (GMMG), Heidelberg University Hospital, Heidelberg, 69120, Germany.",
    "Department of Internal Medicine V, Hematology, Oncology and Rheumatology, Medical Faculty Heidelberg, Heidelberg Myeloma Center, Heidelberg University Hospital, Heidelberg, 69120, Germany.",
    "Clinical Cooperation Unit Nuclear Medicine, German Cancer Research Centre (DKFZ), Heidelberg, Germany.",
    "Department of Medical Oncology, National Center for Tumor Diseases (NCT), Heidelberg University Hospital, Heidelberg, 69120, Germany."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 18,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Julius C Holzschuh"
    },
    {
      "affs": [
        1
      ],
      "name": "Lukas T Rotkopf"
    },
    {
      "affs": [
        1
      ],
      "name": "Christian Neelsen"
    },
    {
      "affs": [
        2
      ],
      "name": "Fabian Bauer"
    },
    {
      "affs": [
        1
      ],
      "name": "Kevin S Zhang"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Ekaterina Menis"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Marina Hajiyianni"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Elias Karl Mai"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Niels Weinhold"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Lukas John"
    },
    {
      "affs": [
        5
      ],
      "name": "Christos Sachpekidis"
    },
    {
      "affs": [
        5
      ],
      "name": "Antonia Dimitrakopoulou-Strauss",
      "orcid": "0000-0003-0338-9472"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Marc-Steffen Raab"
    },
    {
      "affs": [
        3,
        4,
        6
      ],
      "name": "Hartmut Goldschmidt"
    },
    {
      "affs": [
        1
      ],
      "name": "Johann Jende"
    },
    {
      "affs": [
        1
      ],
      "name": "Stefan Delorme"
    },
    {
      "affs": [
        1
      ],
      "name": "Heinz-Peter Schlemmer"
    },
    {
      "affs": [
        1,
        5
      ],
      "name": "Markus Wennmann"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bg41vdwwcjsdn.bib",
  "cited_by": 0,
  "doi": "10.1186/s40644-026-01134-5",
  "fulltext_url": "https://europepmc.org/articles/PMC13700498",
  "id": "bg41vdwwcjsdn",
  "issns": [
    "1740-5025",
    "1470-7330"
  ],
  "landing_url": "https://europepmc.org/article/MED/42928255",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
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      "openalex",
      "2737|Body Composition Measurement Techniques"
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  "openalex": "W7223263368",
  "pdf_url": "https://europepmc.org/articles/PMC13700498?pdf=render",
  "pmcid": "PMC13700498",
  "pmid": "42928255",
  "published": "2026-10-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bg41vdwwcjsdn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:18Z",
      "native_id": "MED:42928255",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42928255"
    }
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  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2737|Body Composition Measurement Techniques",
      "subfield": "physiology"
    }
  ],
  "title": "AI-based automated body composition analysis from whole-body MRI and (PET-) CT: an intermodal comparison from same-day examinations.",
  "title_text": "AI-based automated body composition analysis from whole-body MRI and (PET-) CT: an intermodal comparison from same-day examinations.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:21:18Z",
  "url": "https://research.draconitic.com/paper/bg41vdwwcjsdn",
  "venue": "Cancer imaging : the official publication of the International Cancer Imaging Society",
  "versions": []
}