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Robust maximization of tumor control probability for radicality constrained dose painting by numbers of head and neck cancer
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, Medical Radiation Science. The Skandion Clinic, Uppsala, Sweden.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology.
RaySearch Laboratories AB.
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(English)In: Article in journal (Refereed) Submitted
Abstract [en]

Background and Purpose The aim of this study was to evaluate the potential and robustness to increase the tumor control probability (TCP) for robustly optimized dose painting plans compared to conventional homogeneous dose plans for head and neck cancers.

Material and Methods We optimized a set of dose painting plans with a robust TCP maximizing objective under different mean dose constraints for the primary clinical target volume (CTVT). These plans were optimized with the robust mini-max algorithm together with dose-responses driven by standardized uptake values (SUV) from 18F-fluorodeoxyglucose positron emission tomography (FDG-PET). The robustness in TCP was evaluated through sampling treatment scenarios with iso-center displacements. We also analyzed the impact on TCP predictions by considering dose-response uncertainties.

Results The average increase in TCP with dose painting ranged between 3 to 20 percentage points (p.p.) which depended on the allowed integral CTVT dose. The median deviation in TCP increase was below 1p.p. for all sampled treatment scenarios versus the nominal plans. Patients with large tumors and large spread of SUV gained the greatest TCP increases. By considering dose-response uncertainties, a decrease of the TCP for a homogeneous dose yielded an increasing dose painting potential.

Conclusions We have found that it is feasible to optimize FDG-PET driven dose painting plans that robustly increase the TCP compared to homogeneous dose treatments for head and neck cancers. The greatest potential TCP increases were found for patients with larger and more SUV heterogeneous tumors, which may give guidance for patient selection to further test the presented dose painting formalism.

Keywords [en]
Dose painting; Dose painting by numbers; Head and neck cancer; 18F-FDG PET/CT
National Category
Cancer and Oncology
Research subject
Medical Radiophysics
Identifiers
URN: urn:nbn:se:uu:diva-394216OAI: oai:DiVA.org:uu-394216DiVA, id: diva2:1357972
Funder
Swedish Cancer Society, 130632Available from: 2019-10-05 Created: 2019-10-05 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, EricAlmhagen, ErikJohansson, SilviaAhnesjö, Anders

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