Statistical Analysis of Treatment Planning Parameters for Prediction of Delivery Quality Assurance Failure for Helical Tomotherapy

Autor: Kyung Hwan Chang PhD, Young Hyun Lee MS, Byung Hun Park MS, Min Cheol Han PhD, Jihun Kim PhD, Hojin Kim PhD, Min-Seok Cho MS, Hyokyeong Kang MS, Ho Lee PhD, Dong Wook Kim PhD, Kwangwoo Park PhD, Jaeho Cho MD, PhD, Yong Bae Kim MD, PhD, Jin Sung Kim PhD, Chae-Seon Hong PhD
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Technology in Cancer Research & Treatment, Vol 19 (2020)
Druh dokumentu: article
ISSN: 1533-0338
15330338
DOI: 10.1177/1533033820979692
Popis: Purpose: This study aimed to investigate the parameters with a significant impact on delivery quality assurance (DQA) failure and analyze the planning parameters as possible predictors of DQA failure for helical tomotherapy. Methods: In total, 212 patients who passed or failed DQA measurements were retrospectively included in this study. Brain (n = 43), head and neck (n = 37), spinal (n = 12), prostate (n = 36), rectal (n = 36), pelvis (n = 13), cranial spinal irradiation and a treatment field including lymph nodes (n = 24), and other types of cancer (n = 11) were selected. The correlation between DQA results and treatment planning parameters were analyzed using logistic regression analysis. Receiver operating characteristic (ROC) curves, areas under the curves (AUCs), and the Classification and Regression Tree (CART) algorithm were used to analyze treatment planning parameters as possible predictors for DQA failure. Results: The AUC for leaf open time (LOT) was 0.70, and its cut-off point was approximately 30%. The ROC curve for the predicted probability calculated when the multivariate variable model was applied showed an AUC of 0.815. We confirmed that total monitor units, total dose, and LOT were significant predictors for DQA failure using the CART. Conclusions: The probability of DQA failure was higher when the percentage of LOT below 100 ms was higher than 30%. The percentage of LOT below 100 ms should be considered in the treatment planning process. The findings from this study may assist in the prediction of DQA failure in the future.
Databáze: Directory of Open Access Journals
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