Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics.

Journal: Investigative radiology
PMID: 37222527

Abstract

OBJECTIVES: In multiple myeloma and its precursor stages, plasma cell infiltration (PCI) and cytogenetic aberrations are important for staging, risk stratification, and response assessment. However, invasive bone marrow (BM) biopsies cannot be performed frequently and multifocally to assess the spatially heterogenous tumor tissue. Therefore, the goal of this study was to establish an automated framework to predict local BM biopsy results from magnetic resonance imaging (MRI).

Authors

  • Markus Wennmann
    From the Division of Radiology, German Cancer Research Center (DKFZ).
  • Wenlong Ming
  • Fabian Bauer
  • Jiri Chmelik
    Faculty of Electrical Engineering and Communication, Department of Biomedical Engineering, Brno University of Technology, Brno, Technicka 3082/12, 616 00, Czechia. Electronic address: chmelikj@feec.vutbr.cz.
  • André Klein
    Medical Image Computing, German Cancer Research Center.
  • Charlotte Uhlenbrock
  • Martin Grözinger
    From the Divisions of Radiology.
  • Kim-Celine Kahl
    Medical Image Computing, German Cancer Research Center (DKFZ).
  • Tobias Nonnenmacher
    Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg.
  • Manuel Debic
    Diagnostic and Interventional Radiology.
  • Thomas Hielscher
    Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Heidi Thierjung
    From the Division of Radiology, German Cancer Research Center (DKFZ).
  • Lukas T Rotkopf
    Department of Radiology, German Cancer Research Centre, Heidelberg, Germany.
  • Nikolas Stanczyk
  • Sandra Sauer
    Department of Medicine V, Multiple Myeloma Section, University Hospital Heidelberg.
  • Anna Jauch
    Institute of Human Genetics.
  • Michael Götz
    Medical Image Analysis, Division Medical Image Computing, DKFZ Heidelberg, Germany; National Center for Tumor Diseases (NCT), Heidelberg, Germany. Electronic address: m.goetz@dkfz-heidelberg.de.
  • Felix T Kurz
    Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.
  • Kai Schlamp
  • Marius Horger
    Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076 Tübingen, Germany. Electronic address: marius.horger@med.uni-tuebingen.de.
  • Saif Afat
    Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany.
  • Britta Besemer
  • Martin Hoffmann
  • Johannes Hoffend
  • Doris Kraemer
    Department of Hematology and Oncology, St.-Josefs-Hospital, Hagen, Germany.
  • Ullrich Graeven
  • Adrian Ringelstein
  • David Bonekamp
    From the Department of Radiology (D.B., P.S., J.P.R., P.K., K.Y., M.F., H.P.S.), Division of Medical Image Computing (S.K., M.G., N.G., K.H.M.H.), Division of Statistics (M.W.), and Department of Medical Physics (T.A.K., F.D.), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany (D.B., H.P.S., K.H.M.H.); and Departments of Urology (J.P.R., B.H., M.H., B.A.H.) and Neuroradiology (P.K.), University of Heidelberg Medical Center, Heidelberg, Germany.
  • Jens Kleesiek
    AG Computational Radiology, Abteilung Radiologie, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Deutschland. j.kleesiek@dkfz-heidelberg.de.
  • Ralf O Floca
  • Jens Hillengass
    Department of Medicine, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY.
  • Elias K Mai
  • Niels Weinhold
    Department of Medicine V, Multiple Myeloma Section, University Hospital Heidelberg.
  • Tim F Weber
    Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany. Tim.Weber@med.uni-heidelberg.de.
  • Hartmut Goldschmidt
  • Heinz-Peter Schlemmer
    From the Department of Radiology (D.B., P.S., J.P.R., P.K., K.Y., M.F., H.P.S.), Division of Medical Image Computing (S.K., M.G., N.G., K.H.M.H.), Division of Statistics (M.W.), and Department of Medical Physics (T.A.K., F.D.), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany (D.B., H.P.S., K.H.M.H.); and Departments of Urology (J.P.R., B.H., M.H., B.A.H.) and Neuroradiology (P.K.), University of Heidelberg Medical Center, Heidelberg, Germany.
  • Klaus Maier-Hein
    Medical Image Analysis, Division Medical Image Computing, DKFZ Heidelberg, Germany.
  • Stefan Delorme
    From the Divisions of Radiology.
  • Peter Neher
    Division of Medical Image Computing (MIC), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120 Heidelberg, Germany. Electronic address: p.neher@dkfz.de.

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