Dose painting by numbers based on retrospectively determined recurrence probabilities
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, 1306322017-04-252017-04-252017-04-25Bibliographically approved