Molecular Imaging Methodology Group

The major research area is PET quantification, including the development and evaluation of PET instrumentation, image reconstruction and tracer kinetic modelling. The latter also includes the validation and clinical implementation of new PET radiotracers. In addition, we pursue the development and clinical evaluation of data-driven analysis of PET neuroreceptor imaging and focus on response measurement and criteria in oncology PET.

Ronald Boellaard

We are a renowned research team in oncology PET quantification, harmonization and standardization. Ronald Boellaard (https://orcid.org/0000-0002-0313-5686) is the founder and scientific lead of the European program for harmonization of PET system performance (EANM/EARL). The research team is involved and performs several research projects on the use of radiomics, machine learning and deep learning for prognosis and treatment outcome prediction (see also petralymphoma.org). Finally, the team focusses on methodological research using the large axial field of view PET/CT, the so-called total body PET/CT. The team has strong collaborations with several clinical departments, such as hematology, medical oncology, cardiology, rheumatology and neurology. The team is also member of various international committees and consortia.

    Group members

    Group members:

    • Prof. dr. Ronald Boellaard
    • Dr. Maqsood Yaqub
    • Dr. Marc Huisman
    • Dr. Sandeep Golla
    • Mrs Marijke den Hollander

    PhD students:

    • Maria Ferrandez-Ferrandez
    • Anouk Nijman
    • Charlotte Smith
    • Konstantinos Vrakidis
    • Jessica Wijngaarden
    • Wouter van der Heijden
    • Hanna Saadani
    • Bart de Vries
    • Hayel Tuncel

    Research coworkers/data managers

    • Lisa Verweij
    • Sanne Wiegers
    • Cemile Karga
    • Nienke Gerards
    • Annelies Bes

                Key publications

                FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0.
                Boellaard R, Delgado-Bolton R, Oyen WJ, Giammarile F, Tatsch K, Eschner W, Verzijlbergen FJ, Barrington SF, Pike LC, Weber WA, Stroobants S, Delbeke D, Donohoe KJ, Holbrook S, Graham MM, Testanera G, Hoekstra OS, Zijlstra J, Visser E, Hoekstra CJ, Pruim J, Willemsen A, Arends B, Kotzerke J, Bockisch A, Beyer T, Chiti A, Krause BJ; European Association of Nuclear Medicine (EANM).Eur J Nucl Med Mol Imaging. 2015 Feb;42(2):328-54. doi: 10.1007/s00259-014-2961-x. Epub 2014 Dec 2

                The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping.
                Zwanenburg A, Vallières M, Abdalah MA, Aerts HJWL, Andrearczyk V, Apte A, Ashrafinia S, Bakas S, Beukinga RJ,Boellaard R, Bogowicz M, Boldrini L, Buvat I, Cook GJR, Davatzikos C, Depeursinge A, Desseroit MC, Dinapoli N, Dinh CV, Echegaray S, El Naqa I, Fedorov AY, Gatta R, Gillies RJ, Goh V, Götz M, Guckenberger M, Ha SM, Hatt M, Isensee F, Lambin P, Leger S, Leijenaar RTH, Lenkowicz J, Lippert F, Losnegård A, Maier-Hein KH, Morin O, Müller H, Napel S, Nioche C, Orlhac F, Pati S, Pfaehler EAG, Rahmim A, Rao AUK, Scherer J, Siddique MM, Sijtsema NM, Socarras Fernandez J, Spezi E, Steenbakkers RJHM, Tanadini-Lang S, Thorwarth D, Troost EGC, Upadhaya T, Valentini V, van Dijk LV, van Griethuysen J, van Velden FHP, Whybra P, Richter C, Löck S.Radiology. 2020 May;295(2):328-338. doi: 10.1148/radiol.2020191145. Epub 2020 Mar 10

                An artificial intelligence method using FDG PET to predict treatment outcome in diffuse large B cell lymphoma patients.
                Ferrández MC, Golla SSV, Eertink JJ, de Vries BM, Lugtenburg PJ, Wiegers SE, Zwezerijnen GJC, Pieplenbosch S, Kurch L, Hüttmann A, Hanoun C, Dührsen U, de Vet HCW; PETRA; Zijlstra JM,Boellaard R.Sci Rep. 2023 Aug 12;13(1):13111. doi: 10.1038/s41598-023-40218-1

                Mitigating SUV uncertainties using total body PET imaging.
                Smith CLC, Zwezerijnen GJC, den Hollander ME, Weijland J, Yaqub M,Boellaard R.Eur J Nucl Med Mol Imaging. 2024 Mar;51(4):1070-1078. doi: 10.1007/s00259-023-06503-x. Epub 2023

                Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE Guidelines).
                Jha AK, Bradshaw TJ, Buvat I, Hatt M, Kc P, Liu C, Obuchowski NF, Saboury B, Slomka PJ, Sunderland JJ, Wahl RL, Yu Z, Zuehlsdorff S, Rahmim A,Boellaard R.J Nucl Med. 2022 Sep;63(9):1288-1299. doi: 10.2967/jnumed.121.263239. Epub 2022 May 26

                Awards:

                • Award for contributions to the PET center of excellence of the Society of Nuclear Medicine and Molecular Imaging, 2012, 2013.
                • Esteemed investigator award (2013) for significant contributions to the development of the FDG PET/CT quantitative imaging biomarkers initiative (QIBA) profile by the Radiological Society of Northern America.
                • Most cited paper award of the European Journal of Nuclear Medicine and Molecular Imaging, paper entitled “FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0”, 2014.
                • American Association of Physicist in Medicine (AAPM) award. AAPM, 2017.
                • Presidential recognition award for scientific contribution to the field of Nuclear Medicine. Society of Nuclear Medicine and Molecular Imaging, 2022.
                • Edward J. Hoffman memorial award for significant contribution to harmonisation and quantification of PET imaging and Nuclear Medicine. Society of Nuclear Medicine and Molecular Imaging, 2023.
                • Society of Nuclear Medicine and Molecular Imaging AI Task Force Award for exceptional leadership and contributions, 2024.

                Contact

                Prof.dr. Ronald Boellaard
                Radiology and Nuclear Medicine
                r.boellaard@amsterdamumc.nl

                Keywords

                Quantitative PET imaging | image analysis | kinetic modelling | artificial intelligence | imaging biomarkers | EARL/EANM