Purpose: To build a statistical model to quantitatively correlate the anatomic features of structures and the corresponding dose-volume histogram (DVH) of head and neck (HN) Tomotherapy (Tomo) plans. To study if the model built upon one intensity modulated radiation therapy (IMRT) technique (such as conventional Linac) can be used to predict anticipated organs-at-risk (OAR) DVH of patients treated with a different IMRT technique (such as Tomo). To study if the model built upon the clinical experience of one institution can be used to aid IMRT planning for another institution.
Methods: Forty-four Tomotherapy intensity modulate radiotherapy plans of HN cases (Tomo-IMRT) from Institution A were included in the study. A different patient group of 53 HN fixed gantry IMRT (FG-IMRT) plans was selected from Institution B. The analyzed OARs included the parotid, larynx, spinal cord, brainstem, and submandibular gland. Two major groups of anatomical features were considered: the volumetric information and the spatial information. The volume information includes the volume of target, OAR, and overlapped volume between target and OAR. The spatial information of OARs relative to PTVs was represented by the distance-to-target histogram (DTH). Important anatomical and dosimetric features were extracted from DTH and DVH by principal component analysis. Two regression models, one for Tomotherapy plan and one for IMRT plan, were built independently. The accuracy of intratreatment-modality model prediction was validated by a leave one out cross-validation method. The intertechnique and interinstitution validations were performed by using the FG-IMRT model to predict the OAR dosimetry of Tomo-IMRT plans. The dosimetry of OARs, under the same and different institutional preferences, was analyzed to examine the correlation between the model prediction and planning protocol.
Results: Significant patient anatomical factors contributing to OAR dose sparing in HN Tomotherapy plans have been analyzed and identified. For all the OARs, the discrepancies of dose indices between the model predicted values and the actual plan values were within 2.1%. Similar results were obtained from the modeling of FG-IMRT plans. The parotid gland was spared in a comparable fashion during the treatment planning of two institutions. The model based on FG-IMRT plans was found to predict the median dose of the parotid of Tomotherapy plans quite well, with a mean error of 2.6%. Predictions from the FG-IMRT model suggested the median dose of the larynx, median dose of the brainstem and D2 of the brainstem could be reduced by 10.5%, 12.8%, and 20.4%, respectively, in the Tomo-IMRT plans. This was found to be correlated to the institutional differences in OAR constraint settings. Re-planning of six Tomotherapy patients confirmed the potential of optimization improvement predicted by the FG-IMRT model was correct.
Conclusions: The authors established a mathematical model to correlate the anatomical features and dosimetric indexes of OARs of HN patients in Tomotherapy plans. The model can be used for the setup of patient-specific OAR dose sparing goals and quality control of planning results.
The institutional clinical experience was incorporated into the model which allows the model from one institution to generate a reference plan for another institution, or another IMRT technique.