Systematic method for a deep learning-based prediction model for gamma evaluation in patient-specific quality assurance of volumetric modulated arc therapy

Seiji Tomori, Noriyuki Kadoya, Tomohiro Kajikawa, Yuto Kimura, Kakutarou Narazaki, Takahiro Ochi, Keiichi Jingu

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: This study aimed to develop and evaluate a novel strategy for establishing a deep learning-based gamma passing rate (GPR) prediction model for volumetric modulated arc therapy (VMAT) using dummy target plan data, one measurement process, and a multicriteria prediction method. Methods: A total of 147 VMAT plans were used for the training set (two sets of 48 dummy target plans) and test set (51 clinical target plans). The dummy plans were measured using a diode array detector. We developed an original convolutional neural network that accepts coronal and sagittal dose distributions to predict the GPRs of 36 pairs of gamma criteria from 0.5%/0.5 mm to 3%/3 mm. Sixfold cross-validation and model averaging were performed, and the mean training result and mean test result were derived from six trained models that were produced during cross-validation. Results: Strong or moderate correlations were observed between the measured and predicted GPRs in all criteria. The mean absolute errors and root mean squared errors of the test set (clinical target plan) were 0.63 and 1.11 in 3%/3 mm, 1.16 and 1.73 in 3%/2 mm, 1.96 and 2.66 in 2%/2 mm, 5.00 and 6.35 in 1%/1 mm, and 5.42 and 6.78 in 0.5%/1 mm, respectively. The Pearson correlation coefficients were 0.80 in the training set and 0.68 in the test set at the 0.5%/1 mm criterion. Conclusion: Our results suggest that the training of the deep learning-based quality assurance model can be performed using a dummy target plan.

Original languageEnglish
Pages (from-to)1003-1018
Number of pages16
JournalMedical Physics
Volume48
Issue number3
DOIs
Publication statusPublished - 2021 Mar

Keywords

  • IMRT
  • VMAT
  • deep learning
  • quality assurance
  • radiation therapy

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Systematic method for a deep learning-based prediction model for gamma evaluation in patient-specific quality assurance of volumetric modulated arc therapy'. Together they form a unique fingerprint.

Cite this