Towards optimal heterogeneous prostate radiotherapy dose prescriptions based on patient‐specific or population‐based biological features

Author:

Zhao Yutong1ORCID,Haworth Annette2,Reynolds Hayley M.3,Williams Scott G.45,Finnegan Robert267,Rowshanfarzad Pejman1,Ebert Martin A.189

Affiliation:

1. School of Physics Mathematics and Computing The University of Western Australia Crawley Western Australia Australia

2. Institute of Medical Physics School of Physics The University of Sydney Camperdown New South Wales Australia

3. Auckland Bioengineering Institute University of Auckland Auckland New Zealand

4. Sir Peter MacCallum Department of Oncology University of Melbourne Melbourne Victoria Australia

5. Division of Radiation Oncology and Cancer Imaging Peter MacCallum Cancer Centre Melbourne Victoria Australia

6. Northern Sydney Cancer Centre Royal North Shore Hospital St Leonards New South Wales Australia

7. Ingham Institute for Applied Medical Research Liverpool New South Wales Australia

8. Department of Radiation Oncology Sir Charles Gairdner Hospital Nedlands Western Australia Australia

9. 5D Clinics Claremont Western Australia Australia

Abstract

AbstractBackgroundEscalation of prescribed dose in prostate cancer (PCa) radiotherapy enables improvement in tumor control at the expense of increased toxicity. Opportunities for reduction of treatment toxicity may emerge if more efficient dose escalation can be achieved by redistributing the prescribed dose distribution according to the known heterogeneous, spatially‐varying characteristics of the disease.PurposeTo examine the potential benefits, limitations and characteristics of heterogeneous boost dose redistribution in PCa radiotherapy based on patient‐specific and population‐based spatial maps of tumor biological features.MethodHigh‐resolution prostate histology images, from a cohort of 63 patients, annotated with tumor location and grade, provided patient‐specific “maps” and a population‐based “atlas” of cell density and tumor probability. Dose prescriptions were derived for each patient based on a heterogeneous redistribution of the boost dose to the intraprostatic lesions, with the prescription maximizing patient tumor control probability (TCP). The impact on TCP was assessed under scenarios where the distribution of population‐based biological data was ignored, partially included, or fully included in prescription generation. Heterogeneous dose prescriptions were generated for three combinations of maps and atlas, and for conventional fractionation (CF), extreme hypo‐fractionation (EH), moderate hypo‐fractionation (MH), and whole Pelvic RT + SBRT Boost (WPRT + SBRT). The predicted efficacy of the heterogeneous prescriptions was compared with equivalent homogeneous dose prescriptions.ResultsTCPs for heterogeneous dose prescriptions were generally higher than those for homogeneous dose prescriptions. TCP escalation by heterogeneous dose prescription was the largest for CF. When only using population‐based atlas data, the generated heterogeneous dose prescriptions of 55 to 58 patients (out of 63) had a higher TCP than for the corresponding homogeneous dose prescriptions. The TCPs of the heterogeneous dose prescriptions generated with the population‐based atlas and tumor probability maps did not differ significantly from those using patient‐specific biological information. The generated heterogeneous dose prescriptions achieved significantly higher TCP than homogeneous dose prescriptions in the posterior section of the prostate.ConclusionHeterogeneous dose prescriptions generated via biologically‐optimized dose redistribution can produce higher TCP than the homogeneous dose prescriptions for the majority of the patients in the studied cohort. For scenarios where patient‐specific biological information was unavailable or partially available, the generated heterogeneous dose prescriptions can still achieve TCP improvement relative to homogeneous dose prescriptions.

Publisher

Wiley

Subject

General Medicine

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