Plan Complexity and Delivery Accuracy of Knowledge-based Volumetric Modulated Arc Therapy Plans with Single Optimization for Oropharyngeal Cancer

Okuhata, Katsuya; Monzen, Hajime; Tamura, Mikoto; Matsumoto, Kenji; Otsuka, Masakazu; Kubo, Kazuki; Ueda, Yoshihiro; Uehara, Takuya; Doi, Hiroshi; Ishikawa, Kazuki; Nishimura, Yasumasa

doi:10.21873/anticanres.15074

Cited by 2 publications

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“…[6][7][8][9][10][11] Many studies reported that RP using a single optimization of dose-volume parameters and dose distributions can produce IMRT/VMAT plans superior or comparable to clinically accepted plans for various treatment sites. [12][13][14][15][16][17][18][19][20][21][22][23][24][25] The RP model performance, such as sparing of OARs, depends on the training plans included in the model library; therefore, the registration of better plans is useful to update the model and enhance its performance. 26,27 Wang et al investigated the performance of a RP model updated using a closed-loop technique and showed significant improvement in the sparing of OARs from first to second RP models.…”

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confidence: 99%

An updating approach for knowledge‐based planning models to improve plan quality and variability in volumetric‐modulated arc therapy for prostate cancer

Nakamura

Okuhata

Tamura

et al. 2021

J Applied Clin Med Phys

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The purpose of this study was to compare the dose-volume parameters and regression scatter plots of the iteratively improved RapidPlan (RP) models, specific knowledge-based planning (KBP) models, in volumetric-modulated arc therapy (VMAT) for prostate cancer over three periods.Methods: A RP1 model was created from 47 clinical intensity-modulated radiation therapy (IMRT)/VMAT plans. A RP2 model was created to exceed dosimetric goals which set as the mean values +1SD of the dose-volume parameters of RP1 (50 consecutive new clinical VMAT plans). A RP3 model was created with more strict dose constraints for organs at risks (OARs) than RP1 and RP2 models (50 consecutive anew clinical VMAT plans). Each RP model was validated against 30 validation plans (RP1, RP2, and RP3) that were not used for model configuration, and the dose-volume parameters were compared. The Cook's distances of regression scatterplots of each model were also evaluated.Results: Significant differences (p < 0.05) between RP1 and RP2 were found in D mean (101.5% vs. 101.9%), homogeneity index (3.90 vs. 4.44), 95% isodose conformity index (1.22 vs. 1.20) for the target, V 40Gy (47.3% vs. 45.7%), V 60Gy (27.9% vs. 27.1%), V 70Gy (16.4% vs. 15.2%), and V 78Gy (0.4% vs. 0.2%) for the rectal wall, and V 40Gy (43.8% vs. 41.8%) and V 70Gy (21.3% vs. 20.5%) for the bladder wall, whereas only V 70Gy (15.2% vs. 15.8%) of the rectal wall differed significantly between RP2 and RP3. The proportions of cases with a Cook's distance of <1.0 (RP1, RP2, and RP3 models) were 55%, 78%, and 84% for the rectal wall, and 77%, 68%, and 76% for the bladder wall, respectively. Conclusions:The iteratively improved RP models, reflecting the clear dosimetric goals based on the RP feedback (dose-volume parameters) and more strict dose constraints for the OARs, generated superior dose-volume parameters How to cite this article: Nakamura K, Okuhata K, Tamura M, et al. An updating approach for knowledge-based planning models to improve plan quality and variability in volumetricmodulated arc therapy for prostate cancer.

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