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    Insights into imaging. 2022 Oct 4. doi: 10.1186/s13244-022-01287-4. pii: 10.1186/s13244-022-01287-4
    Standardised lesion segmentation for imaging biomarker quantitation: a consensus recommendation from ESR and EORTC.
    deSouza NM1,  van der Lugt A2,  Deroose CM3,  Alberich-Bayarri A4,  Bidaut L5,  Fournier L6,  Costaridou L7,  Oprea-Lager DE8,  Kotter E9,  Smits M10,  Mayerhoefer ME11,  Boellaard R12,  Caroli A13,  de Geus-Oei LF14,  Kunz WG15,  Oei EH16,  Lecouvet F17,  Franca M18,  Loewe C19,  Lopci E20,  Caramella C21,  Persson A22,  Golay X23,  Dewey M24,  O'Connor JPB25,  deGraaf P26,  Gatidis S27,  Zahlmann G28
    Author information
    1Division of Radiotherapy and Imaging, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, UK. nandita.deSouza@icr.ac.uk.
    2Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
    3Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium.
    4Quantitative Imaging Biomarkers in Medicine (QUIBIM), Valencia, Spain.
    5College of Science, University of Lincoln, Lincoln, Lincoln, LN6 7TS, UK.
    6INSERM, Radiology Department, AP-HP, Hopital Europeen Georges Pompidou, Université de Paris, PARCC, 75015, Paris, France.
    7School of Medicine, University of Patras, University Campus, Rio, 26 500, Patras, Greece.
    8Department of Radiology and Nuclear Medicine, Amsterdam, UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
    9Department of Radiology, University Medical Center Freiburg, Freiburg, Germany.
    10Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
    11Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
    12Department of Radiology and Nuclear Medicine, Amsterdam, UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
    13Department of Biomedical Engineering, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy.
    14Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
    15Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
    16Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
    17Department of Radiology, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint Luc, Université Catholique de Louvain (UCLouvain), 10 Avenue Hippocrate, 1200, Brussels, Belgium.
    18Department of Radiology, Centro Hospitalar Universitário do Porto, Instituto de Ciências Biomédicas de Abel Salazar, University of Porto, Porto, Portugal.
    19Division of Cardiovascular and Interventional Radiology, Department for Bioimaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
    20Nuclear Medicine, IRCCS - Humanitas Research Hospital, via Manzoni 56, Rozzano, MI, Italy.
    21Radiology Department, Hôpital Marie Lannelongue, Institut d'Oncologie Thoracique, Université Paris-Saclay, Le Plessis-Robinson, France.
    22Department of Radiology, and Department of Health, Medicine and Caring Sciences, Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
    23Queen Square Institute of Neurology, University College London, London, UK.
    24Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany.
    25Division of Radiotherapy and Imaging, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, UK.
    26Department of Radiology and Nuclear Medicine, Amsterdam, UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
    27Department of Radiology, University of Tubingen, Tübingen, Germany.
    28Radiological Society of North America (RSNA), Oak Brook, IL, USA.
    Abstract

    BACKGROUND: Lesion/tissue segmentation on digital medical images enables biomarker extraction, image-guided therapy delivery, treatment response measurement, and training/validation for developing artificial intelligence algorithms and workflows. To ensure data reproducibility, criteria for standardised segmentation are critical but currently unavailable.

    METHODS: A modified Delphi process initiated by the European Imaging Biomarker Alliance (EIBALL) of the European Society of Radiology (ESR) and the European Organisation for Research and Treatment of Cancer (EORTC) Imaging Group was undertaken. Three multidisciplinary task forces addressed modality and image acquisition, segmentation methodology itself, and standards and logistics. Devised survey questions were fed via a facilitator to expert participants. The 58 respondents to Round 1 were invited to participate in Rounds 2-4. Subsequent rounds were informed by responses of previous rounds.

    RESULTS/CONCLUSIONS: Items with ≥ 75% consensus are considered a recommendation. These include system performance certification, thresholds for image signal-to-noise, contrast-to-noise and tumour-to-background ratios, spatial resolution, and artefact levels. Direct, iterative, and machine or deep learning reconstruction methods, use of a mixture of CE marked and verified research tools were agreed and use of specified reference standards and validation processes considered essential. Operator training and refreshment were considered mandatory for clinical trials and clinical research. Items with a 60-74% agreement require reporting (site-specific accreditation for clinical research, minimal pixel number within lesion segmented, use of post-reconstruction algorithms, operator training refreshment for clinical practice). Items with ≤ 60% agreement are outside current recommendations for segmentation (frequency of system performance tests, use of only CE-marked tools, board certification of operators, frequency of operator refresher training). Recommendations by anatomical area are also specified.


    © 2022. The Author(s).

    KEYWORDS: Modality-specific, Organ-specific, Region of interest, Segmentation and standardisation, mDelphi

    Publikations ID: 36194301
    Quelle: öffnen
     
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