4.1 Article

Dosimetric comparison of volume-based and inverse planning simulated annealing-based dose optimizations for high-dose rate brachytherapy

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MEDICAL DOSIMETRY
卷 40, 期 3, 页码 235-239

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.meddos.2015.01.003

关键词

Brachytherapy; Optimization; Inverse planning

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The aim of this study was to compare the clinical benefits of inverse planning simulated annealing (IPSA)-based optimization over volume-based optimization for high-dose rate (HDR) cervix interstitial implants. Overall, 10 patients of cervical carcinoma were considered for treatment with HDR interstitial brachytherapy. Oncentra Master Plan brachytherapy planning system was used for generating 3-dimensional HDR treatment planning for all patients. All patient treatments were planned using volume-based optimization and inverse planning optimization (IPSA). The parameters V-100, V-150, and V-200 for the target; D-2 cm3 of bladder, rectum, and sigmoid colon; and V-80 and V-100 for bladder, rectum, and sigmoid colon were compared using dose-volume histograms (DVHs). The conformity index (Cl), relative dose homogeneity index, overdose volume index (ODI), and dose nonuniformity index (DNR) were computed from cumulative DVHs. Good target coverage for prescription dose was achieved with volume-based optimization as compared with IPSA-based dose optimization. Homogeneity was good with the IPSA-based technique as compared with the volume-based dose optimization technique. Volume-based optimization resulted in a higher Cl (with a mean value of 0.87) compared with the IPSA-based optimization (with a mean value of 0.76). ODI and DNR are better for the IPSA-based plan as compared with the volume-based plan. Mean doses to the bladder, rectum, and sigmoid colon were least with IPSA. IPSA also spared the critical organs but with considerable target conformity as compared with the volume-based plan. IPSA significantly reduces overall treatment planning time with improved reduced doses to the organs at risk compared with the volume-based optimization treatment planning method. (C) 2015 American Association of Medical Dosimetrists.

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