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Robust treatment planning of dose painting for prostate cancer based on ADC-to-Gleason score mapping: what is the potential to increase the tumor control probability?
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.
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.
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Background and Purpose

We have in this study evaluated our earlier published dose painting formalism for prostate cancer that is driven by dose-responses of Gleason scores mapped from apparent diffusion coefficient (ADC) image data. The aim of this study is to evaluate the ability to actualize increases of the tumor control probability (TCP) with optimization of “dose painting by numbers” (DPBN) plans in a treatment planning system (TPS) compared to uniform dose treatments for patients with high-risk prostate cancer.

Material and Methods

We have evaluated the potential to actualize TCP increases with realistic DPBN plans as compared to uniform dose treatments for a test set of 17 patients diagnosed with high-risk prostate cancer and pre-RT ADC image data. This potential was evaluated through calculating the DPBN efficiency, defined as the ratio of TCP increases for realistic DPBN plans by TCP increases for ideal DPBN prescriptions. Both the ideal DPBN prescriptions and the realistic DPBN plans were optimized with the objective to maximize the TCP for the target prostate volumes (CTVT) while retaining the same average dose as for conventional uniform dose treatments. For the realistic DPBN plan optimization we tested the impact on the TCP by applying different photon energies, different levels of precision of the mapping of ADC data into Gleason score driven dose-responses, and with respect to different levels of iso-center positioning uncertainties through optimizing with robust minimax optimization.

Results

The median DPBN efficiency for the most conservative planning scenario optimized with 15MV photons, a low precision ADC-to-Gleason mapping, and a robustness distance of 0.6 cm was 10%, meaning that more than half of the patients had a gain in TCP of at least 10% of the TCP for an ideal DPBN prescription. By using 6MV photons, increasing the precision of the ADC-to-Gleason mapping, and decreasing the robustness distance the median of the DPBN efficiency increased by up to 40%.

Conclusions

Optimization of DPBN plans in a TPS can according to our formalism yield TCP increases compared to conventional uniform dose treatments for prostate cancer. These TCP increases are more likely when there is a high precision on the mapping of image data into dose-responses and a high certainty of the tumor position during treatment. These findings motivate further development to ensure accurate and precise mappings of image data into dose-responses and to ensure a high spatial certainty of the tumor position when implementing DPBN in a TPS.

Keywords [en]
Dose painting; Dose painting by numbers; Prostate cancer;
National Category
Cancer and Oncology
Research subject
Medical Radiophysics
Identifiers
URN: urn:nbn:se:uu:diva-394217OAI: oai:DiVA.org:uu-394217DiVA, id: diva2:1357973
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, SilviaNyholm, TufveAhnesjö, Anders

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