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1. Technical Note

Author

Frank Verhaegen, Salim Si-Mohamed, Ilaria Rinaldi, Juan F. P. J. Abascal, Isabel P. Almeida, Françoise Peyrin, Guillaume Landry, Katia Parodi, Simon Rit, Fabian Dörringer, Philippe Douek, Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU), Service de Radiologie et IRM [CHU Lyon], Hospices Civils de Lyon (HCL), Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Imagerie Tomographique et Radiothérapie, European Synchrotron Radiation Facility (ESRF), Maastricht Radiation Oncology Clinic (MAASTRO), Maastricht University [Maastricht], Institut de Physique Nucléaire de Lyon (IPNL), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy, Promovendi ODB, and Radiotherapie

Subjects
Organs at Risk, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, PREDICTION, relative stopping power, BEAM, dual-energy CT, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, ATTENUATION, dual layer CT, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Neoplasms, Image Processing, Computer-Assisted, proton therapy, Lung, ComputingMilieux_MISCELLANEOUS, Physics, NUMBERS, Phantoms, Imaging, Detector, Radiotherapy Dosage, General Medicine, ENERGY CT, synchrotron CT, SINGLE, 030220 oncology & carcinogenesis, Calibration, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Scanner, Mean squared error, Electrons, Imaging phantom, 03 medical and health sciences, Optics, RATIO, Humans, HEAD, Proton therapy, mono‐energetic imaging, business.industry, Radiotherapy Planning, Computer-Assisted, Attenuation, Water, dual-layer CT, monoenergetic imaging, Radiotherapy, Intensity-Modulated, Tomography, X-Ray Computed, business, Synchrotrons, Effective atomic number, ELECTRON-DENSITY, dual energy CT
Abstract

PurposeThe objective of this technical note was to investigate the accuracy of proton stopping power relative to water (RSP) estimation using a novel dual-layer, dual-energy computed tomography (DL-DECT) scanner for potential use in proton therapy planning. DL-DECT allows dual-energy reconstruction from scans acquired at a single x-ray tube voltage V by using two-layered detectors.MethodsSets of calibration and evaluation inserts were scanned at a DL-DECT scanner in a custom phantom with variable diameter D (0 to 150mm) at V of 120 and 140kV. Inserts were additionally scanned at a synchrotron computed tomography facility to obtain comparative linear attenuation coefficients for energies from 50 to 100keV, and reference RSP was obtained using a carbon ion beam and variable water column. DL-DECT monoenergetic (mono-E) reconstructions were employed to obtain RSP by adapting the Yang-Saito-Landry (YSL) method. The method was compared to reference RSP via the root mean square error (RMSE) over insert mean values obtained from volumetric regions of interest. The accuracy of intermediate quantities such as the relative electron density (RED), effective atomic number (EAN), and the mono-E was additionally evaluated.ResultsThe lung inserts showed higher errors for all quantities and we report RMSE excluding them. RMSE for from DL-DECT mono-E was below 1.9%. For the evaluation inserts at D=150mm and V=140kV, RED RMSE was 1.0%, while for EAN it was 2.9%. RSP RMSE was below 0.8% for all D and V, which did not strongly affect the results.ConclusionsIn this investigation of RSP accuracy from DL-DECT, we have shown that RMSE below 1% can be achieved. It was possible to adapt the YSL method for DL-DECT and intermediate quantities RED and EAN had comparable accuracy to previous publications.

Published
2019

2. A framework based on hidden Markov trees for multimodal PET/CT image co-segmentation

Author

Dimitris Visvikis, Wojciech Pieczynski, Mathieu Hatt, Philippe Lambin, Didier Benoit, Houda Hanzouli-Ben Salah, Jerome Lapuyade-Lahorgue, Emmanuel Monfrini, Julien Bert, Angela van Baardwijk, Laboratoire de Traitement de l'Information Medicale (LaTIM), Institut National de la Santé et de la Recherche Médicale (INSERM)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO), Maastricht Radiation Oncology Clinic (MAASTRO), Maastricht University [Maastricht], Traitement de l'Information Pour Images et Communications (TIPIC-SAMOVAR), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Centre National de la Recherche Scientifique (CNRS), RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy, Radiotherapie, Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut Brestois Santé Agro Matière (IBSAM)

Subjects
QUANTITATION, Computer science, CELL LUNG-CANCER, Bayesian inference, Wavelet Analysis, Image processing, [SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicine, computed tomography (CT), computer.software_genre, TRACER UPTAKE, CLASSIFICATION, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Wavelet, Voxel, Positron Emission Tomography Computed Tomography, Image Processing, Computer-Assisted, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, medicine, Humans, Segmentation, F-18-FDG PET, RECONSTRUCTION, positron emission tomography (PET), BRAIN, Hidden Markov model, PET-CT, medicine.diagnostic_test, business.industry, segmentation, Pattern recognition, General Medicine, Image segmentation, CT IMAGES, Markov Chains, Contourlet, wavelet and contourlet analysis, TUMOR DELINEATION, MODEL, Positron emission tomography, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], 030220 oncology & carcinogenesis, Artificial intelligence, business, Nuclear medicine, computer, hidden Markov trees (HMT)
Abstract

PurposeThe purpose of this study was to investigate the use of a probabilistic quad-tree graph (hidden Markov tree, HMT) to provide fast computation, robustness and an interpretational framework for multimodality image processing and to evaluate this framework for single gross tumor target (GTV) delineation from both positron emission tomography (PET) and computed tomography (CT) images.MethodsWe exploited joint statistical dependencies between hidden states to handle the data stack using multi-observation, multi-resolution of HMT and Bayesian inference. This framework was applied to segmentation of lung tumors in PET/CT datasets taking into consideration simultaneously the CT and the PET image information. PET and CT images were considered using either the original voxels intensities, or after wavelet/contourlet enhancement. The Dice similarity coefficient (DSC), sensitivity (SE), positive predictive value (PPV) were used to assess the performance of the proposed approach on one simulated and 15 clinical PET/CT datasets of non-small cell lung cancer (NSCLC) cases. The surrogate of truth was a statistical consensus (obtained with the Simultaneous Truth and Performance Level Estimation algorithm) of three manual delineations performed by experts on fused PET/CT images. The proposed framework was applied to PET-only, CT-only and PET/CT datasets, and were compared to standard and improved fuzzy c-means (FCM) multimodal implementations.ResultsA high agreement with the consensus of manual delineations was observed when using both PET and CT images. Contourlet-based HMT led to the best results with a DSC of 0.92 0.11 compared to 0.89 +/- 0.13 and 0.90 +/- 0.12 for Intensity-based HMT and Wavelet-based HMT, respectively. Considering PET or CT only in the HMT led to much lower accuracy. Standard and improved FCM led to comparatively lower accuracy than HMT, even when considering multimodal implementations.ConclusionsWe evaluated the accuracy of the proposed HMT-based framework for PET/CT image segmentation. The proposed method reached good accuracy, especially with pre-processing in the contourlet domain.

Published
2017

3. ESTRO ACROP: Technology for precision small animal radiotherapy research: Optimal use and challenges

Author

Kirsten Lauber, Kevin M. Prise, Ludwig Dubois, Robert A. Weersink, Frank Verhaegen, Boris Vojnovic, Stefano Gianolini, Mark A. Hill, David Sarrut, Jan J. Wilkens, Dietmar Georg, Christian P. Karger, Christian Vanhove, Daniela Thorwarth, Maastricht Radiation Oncology Clinic (MAASTRO), Maastricht University [Maastricht], Medical Software Solutions GmbH, Medical Research Council - MRC (Oxford, UK), University of Oxford [Oxford], Department of Medical Physics in Radiation Oncology, German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), National Center for Radiation Research in Oncology, Heidelberg Institute for Radiation Oncology, Department of Radiation Oncology [Munich], Ludwig-Maximilians-Universität München (LMU), Centre for Cancer Research and Cell Biology, Queen's University [Belfast] (QUB), Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Section for Biomedical Physics, University Hospital Tübingen, Universiteit Gent = Ghent University [Belgium] (UGENT), Princess Margaret Hospital, University of Toronto, Klinikums rechts der Isar, Division of Medical Radiation Physics, Medizinische Universität Wien = Medical University of Vienna, Rayet, Béatrice, University of Oxford, National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Universiteit Gent = Ghent University (UGENT), RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy, Radiotherapie, and RS: GROW - R2 - Basic and Translational Cancer Biology

Subjects
Computer science, medicine.medical_treatment, Advisory committee, Normal tissue, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, MICRO-CT, Image guided, RADIATION RESEARCH PLATFORM, 030218 nuclear medicine & medical imaging, TISSUE SEGMENTATION, PRECLINICAL RESEARCH, 0302 clinical medicine, Small animal, Radiation treatment planning, BIOLUMINESCENCE TOMOGRAPHY, DIFFUSE OPTICAL TOMOGRAPHY, Hematology, DOSE CALCULATIONS, Precision, 3. Good health, ddc, Oncology, 030220 oncology & carcinogenesis, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Radiation response, medicine.medical_specialty, Technology and Engineering, CONFORMAL RADIOTHERAPY, Image registration, [SDV.CAN]Life Sciences [q-bio]/Cancer, RELATIVE BIOLOGICAL EFFECTIVENESS, 03 medical and health sciences, [SDV.CAN] Life Sciences [q-bio]/Cancer, Radiation oncology, medicine, Journal Article, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Animals, Radiology, Nuclear Medicine and imaging, Medical physics, [PHYS.PHYS.PHYS-MED-PH] Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Radiotherapy, Radiotherapy Planning, Computer-Assisted, Neoplasms, Experimental, Radiation therapy, Disease Models, Animal, Irradiation, IMAGE QUALITY, Radiotherapy, Image-Guided
Abstract

Many radiotherapy research centers have recently installed novel research platforms enabling the investigation of the radiation response of tumors and normal tissues in small animal models, possibly in combination with other treatment modalities. Many more research institutes are expected to follow in the coming years. These novel platforms are capable of mimicking human radiotherapy more closely than older technology. To facilitate the optimal use of these novel integrated precision irradiators and various small animal imaging devices, and to maximize the impact of the associated research, the ESTRO committee on coordinating guidelines ACROP (Advisory Committee in Radiation Oncology Practice) has commissioned a report to review the state of the art of the technology used in this new field of research, and to issue recommendations. This report discusses the combination of precision irradiation systems, small animal imaging (CT, MRI, PET, SPECT, bioluminescence) systems, image registration, treatment planning, and data processing. It also provides guidelines for reporting on studies. (C) 2017 The Authors. Published by Elsevier Ireland Ltd. Radiotherapy and Oncology 126 (2018) 471-478 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Published
2018

4. PRC1 Prevents Replication Stress during Chondrogenic Transit Amplification

Author

Donald A. M. Surtel, Frans Kruitz, Juliette Salvaing, Peggy Prickaerts, Jan Willem Voncken, Lars M. T. Eijssen, Vivian E. H. Dahlmans, Tim J. M. Welting, Michiel E. Adriaens, Miguel Vidal, Yoshihiro Takihara, Bradly G. Wouters, Frank Spaapen, Hendrik G. Stunnenberg, Roel Kuijer, Hendrik Marks, Consejo Superior de Investigaciones Científicas (España), European Molecular Biology Laboratory, Ministerio de Economía y Competitividad (España), Comunidad de Madrid, Netherlands Organization for Scientific Research, Reumafonds, Transnational University of Limburg, Department of Molecular Genetics, Maastricht University Medical Center, Department of Bioinformatics, Maastricht University Medical Center (BiGCaT), Maastricht Centre for Systems Biology, Maastricht University Medical Center (MaCSBio), Department of Orthopedic Research, Maastricht University Medical Center, Physiologie cellulaire et végétale (LPCV), Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut de Recherche Interdisciplinaire de Grenoble (IRIG), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), University Medical Center Groningen [Groningen] (UMCG), Stem Cell Biology, Research Institute for Radiation Biology and Medicine, Centre for Molecular Life Sciences (NCMLS), Department of Molecular Biology, Radboud university [Nijmegen], Departments of Laboratory Medicine, Pathobiology & Radiation Oncology, Maastricht Radiation Oncology Clinic (MAASTRO), Maastricht University [Maastricht], Centro de Investigaciones Biologicas, Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut de Recherche Interdisciplinaire de Grenoble (IRIG), Radboud University [Nijmegen], Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)-Institut de Recherche Interdisciplinaire de Grenoble (IRIG), Radiotherapie, Psychiatrie & Neuropsychologie, RS: MHeNs - R3 - Neuroscience, Bioinformatica, Maastricht Centre for Systems Biology, RS: FHML MaCSBio, RS: FSE MaCSBio, Orthopedie, MUMC+: MA Orthopedie (9), RS: CAPHRI - R3 - Functioning, Participating and Rehabilitation, Promovendi ODB, Molecular Genetics, and RS: GROW - R2 - Basic and Translational Cancer Biology

Subjects
senescence, DNA damage, Health, Toxicology and Mutagenesis, [SDV]Life Sciences [q-bio], lcsh:Medicine, polycomb, topoisomerase, transit amplification, chromatin, DNA replication, transcription, chondrogenesis, differentiation, hypertrophy, macromolecular substances, Biochemistry, Genetics and Molecular Biology (miscellaneous), Biochemistry, 03 medical and health sciences, 0302 clinical medicine, Transcription (biology), Genetics, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, lcsh:QH301-705.5, 030304 developmental biology, 0303 health sciences, biology, Topoisomerase, lcsh:R, Geminin, Chondrogenesis, 3. Good health, Cell biology, Chromatin, lcsh:Biology (General), BMI1, 030220 oncology & carcinogenesis, biology.protein
Abstract

Transit amplification (TA), a state of combined, rapid proliferative expansion and differentiation of stem cell-descendants, remains poorly defined at the molecular level. The Polycomb Repressive Complex 1 (PRC1) protein BMI1 has been localized to TA compartments, yet its exact role in TA is unclear. PRC1 proteins control gene expression, cell proliferation and DNA-damage repair. Coordination of such DNA-templated activities during TA is predicted to be crucial to support DNA replication and differentiation-associated transcriptional programming. We here examined whether chondrogenesis provides a relevant biological context for synchronized coordination of these chromatin-based tasks by BMI1. Taking advantage of a prominently featuring TA-phase during chondrogenesis in vitro and in vivo, we here report that TA is completely dependent on intact PRC1 function. BMI1-depleted chondrogenic progenitors rapidly accumulate double strand DNA breaks during DNA replication, present massive non-H3K27me3-directed transcriptional deregulation and fail to undergo chondrogenic TA. Genome-wide accumulation of Topoisomerase 2α and Geminin suggests a model in which PRC1 synchronizes replication and transcription during rapid chondrogenic progenitor expansion. Our combined data reveals for the first time a vital cell-autonomous role for PRC1 during chondrogenesis. We provide evidence that chondrocyte hyper-replication and hypertrophy represent a unique example of programmed senescence in vivo. These findings provide new perspectives on PRC1 function in development and disease., The authors received financial support from the European Molecular Biology Organization (Germany; www.embl.de) ASTF5-2009 (F.S.) and the René Vogels foundation (F.S.); grant BFU2010-18146 (MINECO, MV) and Oncocycle program S2010/BMD2470 (Comunidad de Madrid, MV); the Dutch Science Organization (ZonMW-NWO; www.NWO.nl) VIDI grant 864.12.007 (H.M.); VIDI grant 016.046.362 (J.W.V.); Netherlands Reuma foundation (The Netherlands; www.ruemafonds.nl) grant LLP14 (J.W.V., L. van Rhijn, Maastricht, The Netherlands) and a transnational University of Limburg grant (J.W.V., B.W.G.).

Published
2017

5. Investigating deformable image registration and scatter correction for CBCT-based dose calculation in adaptive IMPT

Author

Kurz, Christopher, Kamp, Florian, Park, Yang-Kyun, Zöllner, Christoph, Rit, Simon, Hansen, David, Podesta, Mark, Sharp, Gregory C, Li, Minglun, Reiner, Michael, Hofmaier, Jan, Neppl, Sebastian, Thieke, Christian, Nijhuis, Reinoud, Ganswindt, Ute, Belka, Claus, Winey, Brian, Parodi, Katia, Landry, Guillaume, Promovendi ODB, Radiotherapie, RS: GROW - School for Oncology and Reproduction, RS: FHML non-thematic output, RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy, Department of Radiation Oncology [Munich], Ludwig-Maximilians-Universität München (LMU), Department of Medical Physics, Department of Radiation Oncology [Boston], Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Oncology, Aarhus University Hospital, Maastricht Radiation Oncology Clinic (MAASTRO), Maastricht University [Maastricht], Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Cone beam computed tomography, [SDV.CAN]Life Sciences [q-bio]/Cancer, respiratory system, equipment and supplies, Medical image reconstruction, stomatognathic system, adaptive radiotherapy, Dosimetry, cone-beam CT, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, proton therapy, Protons, Cancer
Abstract

International audience; Purpose:This work aims at investigating intensity corrected cone-beam x-ray computed tomography (CBCT) images for accurate dose calculation in adaptive intensity modulated proton therapy (IMPT) for prostate and head and neck (H&N) cancer. A deformable image registration (DIR)-based method and a scatter correction approach using the image data obtained from DIR as prior are characterized and compared on the basis of the same clinical patient cohort for the first time.Methods:Planning CT (pCT) and daily CBCT data (reconstructed images and measured projections) of four H&N and four prostate cancer patients have been considered in this study. A previously validated Morphons algorithm was used for DIR of the planning CT to the current CBCT image, yielding a so-called virtual CT (vCT). For the first time, this approach was translated from H&N to prostate cancer cases in the scope of proton therapy. The warped pCT images were also used as prior for scatter correction of the CBCT projections for both tumor sites. Single field uniform dose and IMPT (only for H&N cases) treatment plans have been generated with a research version of a commercial planning system. Dose calculations on vCT and scatter corrected CBCT (CBCT cor) were compared by means of the proton range and a gamma-index analysis. For the H&N cases, an additional diagnostic replanning CT (rpCT) acquired within three days of the CBCT served as additional reference. For the prostate patients, a comprehensive contour comparison of CBCT and vCT, using a trained physician’s delineation, was performed.Results:A high agreement of vCT and CBCT cor was found in terms of the proton range and gamma-index analysis. For all patients and indications between 95% and 100% of the proton dose profiles in beam’s eye view showed a range agreement of better than 3 mm. The pass rate in a (2%,2 mm) gamma-comparison was between 96% and 100%. For H&N patients, an equivalent agreement of vCT and CBCT cor to the reference rpCT was observed. However, for the prostate cases, an insufficient accuracy of the vCT contours retrieved from DIR was found, while the CBCT cor contours showed very high agreement to the contours delineated on the raw CBCT.Conclusions:For H&N patients, no considerable differences of vCT and CBCT cor were found. For prostate cases, despite the high dosimetric agreement, the DIR yields incorrect contours, probably due to the more pronounced anatomical changes in the abdomen and the reduced soft-tissue contrast in the CBCT. Using the vCT as prior, these inaccuracies can be overcome and images suitable for accurate delineation and dose calculation in CBCT-based adaptive IMPT can be retrieved from scatter correction of the CBCT projections.

Published
2016

6. Impact of thoracic radiotherapy timing in limited-stage small-cell lung cancer: usefulness of the individual patient data meta-analysis†

Author

Béranger Lueza, Lesley Seymour, C. Le Pechoux, Minoru Takada, Allan Price, S. Spiro, M. Pijls-Johannesma, M. O'Brien, Anne-Sophie Veillard, N. Murray, Nevin Murray, M. Takada, Taro Shibata, James Lovato, H. Choy, David H. Johnson, W. Blackstock, Jeffrey Crawford, Cécile Le Péchoux, Donald H. Johnson, J.P. Pignon, D.V. Skarlos, Jean-Pierre Pignon, William Blackstock, Mary O’Brien, Anne Sophie Veillard, Dirk Karel Maria De Ruysscher, Hak Choy, Baktiar Hasan, X. Wang, Bernard Lebeau, Urania Dafni, E. Paris, Suzanne E. Dahlberg, B. Lebeau, Madelon Pijls-Johannesma, Sylvie Chevret, Xiaofei Wang, Dirk De Ruysscher, L. Seymour, R. Arriagada, Emmanuelle Paris, Dimosthenis Skarlos, Allan Hackshaw, P. Baas, A. Price, Stephen G. Spiro, Rodrigo Arriagada, Paul Baas, Maastricht Radiation Oncology Clinic (MAASTRO), Maastricht University [Maastricht], Service de biostatistique et d'épidémiologie (SBE), Direction de la recherche clinique [Gustave Roussy], Institut Gustave Roussy (IGR)-Institut Gustave Roussy (IGR), Plateforme Ligue nationale contre le cancer de méta-analyse en oncologie [Villejuif], Institut Gustave Roussy (IGR), Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Département de radiothérapie [Gustave Roussy], Université Paris-Sud - Paris 11 (UP11), UT Southwestern University School of Medicine, EORTC Data Center, British Columbia Cancer Agency, University College London Hospitals (UCLH), Alliance Data and Statistical Center, Duke University [Durham], Osaka Prefectural Habikino Hospital, Hôpital St Antoine, Wake Forest University, Second Department of Medical Oncology, Metropolitan Hospital N. Faliro, The Netherlands Cancer Institute, Department of Radiation Oncology, University of Texas Southwestern Medical Center [Dallas], Cancer Research UK Edinburgh Centre [Edinburgh, UK], University of Edinburgh-MRC Institute of Genetics and Molecular Medicine [Edinburgh] (IGMM), University of Edinburgh-Medical Research Council-Medical Research Council, NCIC Clinical Trials Group [Kingston, Canada], Université Queen's [Canada], The meta-analysis was funded by the French National Cancer Institute (Programme Hospitalier de Recherche Clinique), the Ligue Nationale Contre le Cancer, and partly by Sanofi-Aventis (unrestricted grants). The investigators meeting was also funded by Gustave Roussy, Lilly and Astra-Zeneca (unrestricted grants). No grant number is applicable., RTT-SCLC Collaborative Group : De Ruysscher D, Le Pechoux C, Lueza B, Paris E, Pignon JP, Pijls-Johannesma M, Veillard AS, Arriagada R, Baas P, Blackstock W, Chevret S, Choy H, Crawford J, Dafni U, Dahlberg S, De Ruysscher D, Hackshaw A, Hasan B, Johnson DH, Le Pechoux C, Lebeau B, Lovato J, Lueza B, Murray N, O'Brien M, Paris E, Pignon JP, Pijls-Johannesma M, Price A, Spiro S, Seymour L, Shibata T, Skarlos D, Spiro S, Takada M, Veillard AS, Wang X., Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), and Lueza, Béranger

Subjects
Male, medicine.medical_specialty, medicine.medical_treatment, Thoracic radiotherapy, Reviews, [SDV.CAN]Life Sciences [q-bio]/Cancer, Disease-Free Survival, 03 medical and health sciences, 0302 clinical medicine, [SDV.CAN] Life Sciences [q-bio]/Cancer, Drug Therapy, radiotherapy timing, small-cell lung cancer, medicine, Humans, 030212 general & internal medicine, Lung cancer, Proportional Hazards Models, Randomized Controlled Trials as Topic, randomised clinical trials, Chemotherapy, business.industry, Incidence (epidemiology), Standard treatment, Hazard ratio, Hematology, medicine.disease, individual participant data meta-analysis, Combined Modality Therapy, Small Cell Lung Carcinoma, 3. Good health, Surgery, Radiation therapy, Oncology, chemotherapy compliance, 030220 oncology & carcinogenesis, Meta-analysis, Female, Cisplatin, business, thoracic radiotherapy
Abstract

International audience; BackgroundChemotherapy combined with radiotherapy is the standard treatment of “limited-stage” small-cell lung cancer. However, controversy persists over the optimal timing of thoracic radiotherapy and chemotherapy.Material and methodsWe performed a meta-analysis of individual patient data in randomised trials comparing earlier versus later radiotherapy, or shorter vs. longer radiotherapy duration, as defined in each trial. We combined the results from trials using the stratified log-rank test to calculate pooled hazard ratios (HRs). The primary outcome was overall survival.ResultsTwelve trials with 2,668 patients were eligible. Data from nine trials comprising 2,305 patients were available for analysis. The median follow-up was 10 years. When all trials were analysed together, “earlier or shorter” vs. “later or longer” thoracic radiotherapy did not affect overall survival. However, the HR for overall survival was significantly in favour of “earlier or shorter” radiotherapy among trials with a similar proportion of patients who were compliant with chemotherapy (defined as having received 100% or more of the planned chemotherapy cycles) in both arms (HR 0.79, 95% CI 0.69–0.91) and in favour of “later or longer” radiotherapy among trials with different chemotherapy compliance (HR 1.19, 1.05–1.34, interaction test p

Published
2016

7. Une nouvelle méthode de détermination automatique des volumes fonctionnels pour les applications de l’imagerie d’émission en oncologie

Author

Christian Roux, P. Lambin, C. Cheze-Le Rest, M Oellers, Dimitris Visvikis, Mathieu Hatt, Dirk De Ruysscher, A. Dekker, Laboratoire de Traitement de l'Information Medicale (LaTIM), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Mines-Télécom [Paris] (IMT), Service de médecine nucléaire [Brest], Hôpital Morvan [Brest]-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), MAASTRO clinic, Maastro Lab, GET (GET), Ecole Nationale Supérieure des Télécommunications de Bretagne, Région Bretagne, ANR, cancéropôle grand ouest, CHRU Brest - Service de médecine nucléaire (CHU - BREST - Med Nucléaire), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Maastricht Radiation Oncology Clinic (MAASTRO), Maastricht University [Maastricht], Direction Scientifique (DS), Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Hatt, Mathieu, and Université européenne de Bretagne - European University of Brittany (UEB)-Université de Brest (UBO)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)

Subjects
03 medical and health sciences, TEP, 0302 clinical medicine, imagerie d'émission, segmentation automatique, oncologie, 030220 oncology & carcinogenesis, Biomedical Engineering, Biophysics, [SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicine, volumes fonctionnels, [SDV.IB.MN] Life Sciences [q-bio]/Bioengineering/Nuclear medicine, 030218 nuclear medicine & medical imaging
Abstract

International audience; La détermination des volumes fonctionnels est une étape cruciale pour les applications en oncologie comme le suivi thérapeutique ou la planification en radiothérapie guidée par l’image. Il n’existe pour l’instant pas de consensus dans la communauté sur la méthode appropriée pour définir automatiquement un volume tumoral sur l’image fonctionnelle d’émission (e.g. TEP au 18F-FDG), à cause de la grande variabilité des images obtenues dans ce contexte, en termes de bruit, de textures, de contrastes ou des formes et des fixations hétérogènes des tumeurs. Nous proposons une méthode automatique dont la robustesse et la précision ont été validées sur des acquisitions de fantôme, des tumeurs simulées et réelles, avec des performances très supérieures aux méthodes de référence par seuillage, constituant un outil prometteur pour les applications de la TEP en oncologie.

Published
2009

8. Radiogenomics: radiobiology enters the era of big data and team science

Author

Douglas F. Easton, Gillian C. Barnett, George D. D. Jones, Andre Dekker, Christian Nicolaj Andreassen, Ana Vega, Paul D.P. Pharoah, Christopher J. Talbot, Søren M. Bentzen, Timothy R. Rebbeck, David Azria, Dirk De Ruysscher, Rosalind A. Eeles, Frederic Zenhausern, Matthew Parliament, Kim De Ruyck, Neil G. Burnet, Laura Fachal, Harry Ostrer, Karin Haustermans, Sara Gutiérrez-Enríquez, Luis Alberto Henríquez-Hernández, Eric Y. Chuang, Karen Drumea, Jan Alsner, Takashi Imai, Hubert Thierens, Barry S. Rosenstein, Philip Wong, Zhongxing Liao, Sarah L. Kerns, Alison M. Dunning, John S. Witte, Michael Baumann, Catharine M L West, Charlotte E. Coles, Kenan Onel, Jenny Chang-Claude, CRLCC Val d'Aurelle - Paul Lamarque, Institut de recherche en cancérologie de Montpellier (IRCM - U896 Inserm - UM1), Université Montpellier 1 (UM1)-CRLCC Val d'Aurelle - Paul Lamarque-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Maastricht Radiation Oncology Clinic (MAASTRO), Maastricht University [Maastricht], Radiotherapie, RS: GROW - Oncology, and RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy

Subjects
Gerontology, Cancer Research, Genotype, Radiogenomics, Library science, [SDV.CAN]Life Sciences [q-bio]/Cancer, Polymorphism, Single Nucleotide, Radiation Tolerance, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Neoplasms, Medicine, Humans, Radiology, Nuclear Medicine and imaging, Genetic Predisposition to Disease, Radiation Injuries, Alleles, Chromosome Aberrations, Radiation, Extramural, business.industry, Radiotherapy Dosage, Genomics, collaboration, 3. Good health, Team science, Phenotype, Oncology, 030220 oncology & carcinogenesis, Sample Size, business, Genome-Wide Association Study
Abstract

Radiogenomics is the study of the link between germ line genotypic variations and the large clinical variability observed in response to radiation therapy. The radiogenomics hypothesis is that a proportion of the variance in the phenotype of interest – radiation toxicity - is explained by genotypic variation. Thus, the aim of radiogenomics is to identify the alleles that underlie the inherited dissimilarities in phenotype. However, this hypothesis does not assume that all of the phenotypic differences are due to germ line genetic alterations, but acknowledges that epigenetic changes (inherited and acquired) and other factors could also be important. In order to foster collaborative research, the Radiogenomics Consortium (RGC) was established in 2009 (1). The RGC currently has 174 members from 90 institutions in 20 countries and is an NCI supported cancer epidemiology consortium (2). The goal of the RGC is to facilitate large-scale collaborative research assessing gene-radiation effect relationships, including genome wide association studies (GWAS). The aim of this research is to produce assays for use in the clinic to predict risk of toxicities following radiotherapy, given alone or in multi-modality treatments. The results of this research could also lead to the identification of novel strategies for prevention or mitigation of toxicities. Currently, the radiogenomics landscape is rapidly changing. This is partly a result of research advances within the field of radiogenomics itself and partly due to progress in biotechnology and medical informatics that facilitate the pursuit of novel discovery strategies. Radiogenomics is now rapidly advancing from an effort to screen a limited number of candidate genes towards an open discovery approach. Or, from relatively small studies conducted by a few scientists to the potentially powerful, but challenging, era of Big Data and Team Science. However, the substantial progress in radiogenomics may be largely unnoticed by the broader radiotherapy community leading to underestimation of its potential for improving patient outcomes. Therefore, it is critical to address the following questions at this stage in the development of research in radiogenomics.

Published
2014

9. Predictive value of tumor uptake heterogeneity spatial patterns in sequential 18F-FDG PET for rectal cancer radio-chemotherapy response monitoring

Author

Hatt, Mathieu, Tixier, Florent, Cheze-Le Rest, Catherine, VAN STIPHOUT, R, Lammering, Guido, Lambin, Philippe, VISVIKIS, Dimitris, Optimisation Continue des Actions Thérapeutiques par l'Intégration d'Informations Multimodales, Université de Brest (UBO)-Télécom Bretagne-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Poitiers - Département de médecine nucléaire (CHU Poitiers - Département de médecine nucléaire), Centre hospitalier universitaire de Poitiers (CHU Poitiers), Maastricht Radiation Oncology Clinic (MAASTRO), Maastricht University [Maastricht], Direction Scientifique (DS), and Institut Mines-Télécom [Paris] (IMT)-Télécom Bretagne

Abstract

International audience; Objectives: 18F-FDG PET image-derived indices such as textural features have been recently introduced to provide characterization of uptake heterogeneity. The objective of this retrospective study was to assess their predictive value on sequential scans during treatment for rectal cancer. Methods: 28 patients were included; all underwent 3 scans, at baseline (PET1), 1 week (PET2), and 2 weeks (PET3) into treatment. Tumor response grade (TRG) was assessed by histopathology after surgery, and patients were classified as responders (TRG 1-2) and non-responders (TRG 3-5). Several local and regional uptake heterogeneity parameters (homogeneity, entropy) were extracted. The predictive value of these parameters at PET1, as well as their evolution at PET2 and PET3 was evaluated using receiver operating characteristics (ROC) area under the curves (AUC), and were compared to standard parameters (functional volume, SUV). Results: Prediction of no response using baseline PET1 values was not accurate (AUC values from 0.58 for homogeneity to 0.75 for SUVmean). Although results were not improved by considering differences with PET2 parameters, the use of PET3 derived values led to AUCs varying from 0.79 ({Delta}SUVmean, {Delta}TLG) to 0.88 for {Delta}homogeneity (94% sensitivity, 83% specificity). Combining 2 parameters (for example SUVmean and homogeneity) at PET1 or PET2 through logistic regression led to improved AUCs of 0.80 and 0.95 respectively. SUVmax consistently showed a lower predictive value. Conclusions: Characterization of the tumor uptake spatial heterogeneity may provide complementary information of added predictive value within the context of radio-chemotherapy response monitoring using sequential 18F-FDG PET scans in the management of rectal cancer. Combination of several parameters to derive more accurate predictive models is feasible however it will require training and validation in larger cohorts, which will be the focus of future studies.

Published
2013

10. 18F-FDG PET derived indices and impact of partial volume effects correction for prediction of pathological response of locally advanced rectal cancer tumor

Author

Hatt, Mathieu, VAN STIPHOUT, R, Le Pogam, Adrien, Lammering, Guido, VISVIKIS, Dimitris, Lambin, Philippe, Laboratoire de Traitement de l'Information Medicale (LaTIM), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Mines-Télécom [Paris] (IMT), Maastricht Radiation Oncology Clinic (MAASTRO), and Maastricht University [Maastricht]

Abstract

International audience; Objectives: The objectives of this study were to investigate the predictive value of sequential 18F-FDG PET scans for pathological tumor response grade (TRG) after preoperative chemoradiotherapy (PCRT) in locally advanced rectal cancer (LARC) and the impact of partial volume effects correction (PVC). Methods: 28 LARC patients were included. TRG responders and nonresponders status were determined in histopathology. PET indices (SUV max, peak and mean, volume and total lesion glycolysis (TLG)) at baseline and their evolution after one and two weeks of PCRT were extracted by delineation of the PET images, with or without PVC. Their predictive value was investigated using Mann-Whitney-U tests and ROC curve analysis. Results: Only baseline SUVmean was correlated with response. No evolution after one week was predictive of the response, whereas after two weeks all the parameters except volume were, the best prediction being obtained with TLG (AUC 0.79, sensitivity 63%, specificity 92%). PVC had no significant impact on these results. Conclusions: Several PET indices at baseline and their evolution after two weeks of PCRT are good predictors of response in LARC, with or without PVC. Best predictor was TLG reduction after two weeks, although baseline SUVmean had similar predictive power

Published
2012

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