title: Improved tumour response prediction with equivalent uniform dose in pre-clinical study using direct intratumoural infusion of liposome-encapsulated ¹⁸⁶Re radionuclides.
abstract: Crucial to all cancer therapy modalities is a strong correlation between treatment and effect. Predictability of therapy success/failure allows for the optimization of treatment protocol and aids in the decision of whether additional treatment is necessary to prevent tumour progression. This work evaluated the relationship between cancer treatment and effect for intratumoural infusions of liposome-encapsulated ¹⁸⁶Re to head and neck squamous cell carcinoma xenografts of nude rats. Absorbed dose calculations using a dose-point kernel convolution technique showed significant intratumoural dose heterogeneity due to the short range of the beta-particle emissions. The use of three separate tumour infusion locations improved dose homogeneity compared to a single infusion location as a result of a more uniform radioactivity distribution. An improved dose-response correlation was obtained when using effective uniform dose (EUD) calculations based on a generic set of radiobiological parameters (R² = 0.84) than when using average tumour absorbed dose (R² = 0.22). Varying radiobiological parameter values over ranges commonly used for all types of tumours showed little effect on EUD calculations, which suggests that individualized parameter use is of little significance as long as the intratumoural dose heterogeneity is taken into consideration in the dose-response relationship. The improved predictability achieved when using EUD calculations for this cancer therapy modality may be useful for treatment planning and evaluation.
authors.affiliation: Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
authors.forename: Brian A
authors.initials: BA
authors.lastname: Hrycushko
authors.forename: Steve
authors.initials: S
authors.lastname: Ware
authors.forename: Shihong
authors.initials: S
authors.lastname: Li
authors.forename: Ande
authors.initials: A
authors.lastname: Bao
mesh_terms: D000465:Algorithms; D000818:Animals; D002294:Carcinoma, Squamous Cell / Q000378:metabolism / Q000532:radiotherapy*; D045744:Cell Line, Tumor / Q000378:metabolism; D004195:Disease Models, Animal; D004307:Dose-Response Relationship, Radiation; D006258:Head and Neck Neoplasms / Q000378:metabolism / Q000532:radiotherapy*; D006801:Humans; D036502:Infusions, Intralesional; D008081:Liposomes; D011868:Radioisotopes / Q000008:administration & dosage; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D051381:Rats; D011923:Rats, Nude; D012211:Rhenium / Q000008:administration & dosage*; D014183:Transplantation, Heterologous; D016896:Treatment Outcome
chemical_list: D008081:Liposomes; D011868:Radioisotopes; D012211:Rhenium