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Dose painting by numbers based on retrospectively determined recurrence probabilities
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 Immunology, Genetics and Pathology, Medical Radiation Science.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science.
2017 (English)In: Radiotherapy and Oncology, ISSN 0167-8140, E-ISSN 1879-0887, Vol. 122, no 2, p. 236-241Article in journal (Refereed) Published
Abstract [en]

Background and purpose: The aim of this study is to derive "dose painting by numbers" prescriptions from retrospectively observed recurrence volumes in a patient group treated with conventional radiotherapy for head and neck squamous cell carcinoma. Materials and methods: The spatial relation between retrospectively observed recurrence volumes and pre-treatment standardized uptake values (SUV) from fluorodeoxyglucose positron emission tomography (FDG-PET) imaging was determined. Based on this information we derived SUV driven dose-response functions and used these to optimize ideal dose redistributions under the constraint of equal average dose to the tumor volumes as for a conventional treatment. The response functions were also implemented into a treatment planning system for realistic dose optimization. Results: The calculated tumor control probabilities (TCP) increased between 0.1-14.6% by the ideal dose redistributions for all included patients, where patients with larger and more heterogeneous tumors got greater increases than smaller and more homogeneous tumors. Conclusions: Dose painting prescriptions can be derived from retrospectively observed recurrence volumes spatial relation to pre-treatment FDG-PET image data. The ideal dose redistributions could significantly increase the TCP for patients with large tumor volumes and large spread in SUV from FDG-PET. The results yield a basis for prospective studies to determine the clinical value for dose painting of head and neck squamous cell carcinomas.

Place, publisher, year, edition, pages
ELSEVIER IRELAND LTD , 2017. Vol. 122, no 2, p. 236-241
Keywords [en]
Dose painting, Dose painting by numbers, Dose painting optimization, Head and neck cancer, FDG-PET/CT
National Category
Cancer and Oncology Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:uu:diva-320782DOI: 10.1016/j.radonc.2016.09.007ISI: 000395607300011PubMedID: 27707505OAI: oai:DiVA.org:uu-320782DiVA, id: diva2:1090744
Funder
Swedish Cancer Society, 130632
Note

Correction in: RADIOTHERAPY AND ONCOLOGY, Volume: 131, Pages: 243-243, DOI: 10.1016/j.radonc.2018.11.004

Available from: 2017-04-25 Created: 2017-04-25 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, SilviaMontelius, AndersAhnesjö, Anders

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