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Dose painting of prostate cancer based on Gleason score correlations with apparent diffusion coefficients
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science.ORCID iD: 0000-0002-4603-6338
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
Umea Univ, Dept Radiat Sci, Umea, Sweden.
Umea Univ, Dept Radiat Sci, Umea, Sweden.
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2018 (English)In: Acta Oncologica, ISSN 0284-186X, E-ISSN 1651-226X, Vol. 57, no 5, p. 574-581Article in journal (Refereed) Published
Abstract [en]

Background: Gleason scores for prostate cancer correlates with an increased recurrence risk after radiotherapy (RT). Furthermore, higher Gleason scores correlates with decreasing apparent diffusion coefficient (ADC) data from diffusion weighted MRI (DWI-MRI). Based on these observations, we present a formalism for dose painting prescriptions of prostate volumes based on ADC images mapped to Gleason score driven dose-responses.Methods: The Gleason score driven dose-responses were derived from a learning data set consisting of pre-RT biopsy data and post-RT outcomes for 122 patients treated with a homogeneous dose to the prostate. For a test data set of 18 prostate cancer patients with pre-RT ADC images, we mapped the ADC data to the Gleason driven dose-responses by using probability distributions constructed from published Gleason score correlations with ADC data. We used the Gleason driven dose-responses to optimize dose painting prescriptions that maximize the tumor control probability (TCP) with equal average dose as for the learning sets homogeneous treatment dose.Results: The dose painting prescriptions increased the estimated TCP compared to the homogeneous dose by 0-51% for the learning set and by 4-30% for the test set. The potential for individual TCP gains with dose painting correlated with increasing Gleason score spread and larger prostate volumes. The TCP gains were also found to be larger for patients with a low expected TCP for the homogeneous dose prescription.Conclusions: We have from retrospective treatment data demonstrated a formalism that yield ADC driven dose painting prescriptions for prostate volumes that potentially can yield significant TCP increases without increasing dose burdens as compared to a homogeneous treatment dose. This motivates further development of the approach to consider more accurate ADC to Gleason mappings, issues with delivery robustness of heterogeneous dose distributions, and patient selection criteria for design of clinical trials.

Place, publisher, year, edition, pages
Taylor & Francis, 2018. Vol. 57, no 5, p. 574-581
National Category
Urology and Nephrology Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:uu:diva-353194DOI: 10.1080/0284186X.2017.1415457ISI: 000430114000002PubMedID: 29260950OAI: oai:DiVA.org:uu-353194DiVA, id: diva2:1216872
Funder
Swedish Cancer Society, 130632Available from: 2018-06-12 Created: 2018-06-12 Last updated: 2019-10-14Bibliographically approved
In thesis
1. Dose painting: Can radiotherapy be improved with image driven dose-responses derived from retrospective radiotherapy data?
Open this publication in new window or tab >>Dose painting: Can radiotherapy be improved with image driven dose-responses derived from retrospective radiotherapy data?
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The main aim of curative radiotherapy for cancer is to prescribe and deliver doses that eradicate the tumor and spare the normal healthy tissues. Radiotherapy is commonly performed by delivering a homogeneous radiation dose to the tumor. However, concern have been raised that functional imaging methods such as magnetic resonance imaging (MRI) and positron emission tomography (PET) can provide a basis for prescribing heterogeneous doses - higher doses in malignant regions of the tumor and less dose where the tumor is less malignant. This form of radiotherapy is called “dose painting” and has the aim of utilizing the radiant energy as efficiently as possible to increase the tumor control probability (TCP) and to reduce the risk for unwanted side effects of the neighboring normal tissues.

In this project we have studied how dose painting prescriptions could be derived through retrospectively analyzing pre-RT image data and post-RT outcomes for two different patient groups: one diagnosed with head and neck cancer with pre-RT fluorodeoxyglucose (18F-FDG) PET image data; and one patient group diagnosed with prostate cancer with pre-RT Gleason score data that were constructed to be mapped from apparent diffusion coefficient (ADC) data acquired from MRI. The resulting dose painting prescriptions for each of these diagnoses indicated that the TCP could be increased without increasing the average dose to the tumor volumes as compared to homogeneous dose treatments. These TCP increases were more noticeable when the tumors were larger and more heterogeneous than for smaller and more homogeneous tumors.

We have also studied the potential to realize TCP increases with dose painting in comparison to homogeneous dose treatments by optimizing clinically deliverable dose painting plans for both diagnoses, i.e. head and neck cancer and prostate cancer. These plans were optimized with minimax optimization that aimed to maximize a robust TCP increase by considering uncertainties of the patient geometry. These plan optimizations indicated that the TCP compared to homogeneous dose treatments was increasing and robust regarding uncertainties of the patient geometry.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 56
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1603
Keywords
Radiotherapy, functional imaging, dose painting, dose painting by numbers, robust optimization
National Category
Cancer and Oncology
Research subject
Medical Radiophysics
Identifiers
urn:nbn:se:uu:diva-393418 (URN)978-91-513-0776-3 (ISBN)
Public defence
2019-11-29, Hedstrandsalen, Akademiska Sjukhuset, Ingång 70, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2019-11-08 Created: 2019-10-14 Last updated: 2019-11-08

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Grönlund, EricJohansson, SilviaAhnesjö, Anders

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