Low-Dose Computed Tomography Scanning Protocols for Online Adaptive Proton Therapy of Head-and-Neck Cancers

Abstract

Purpose: To evaluate the suitability of low-dose CT protocols for online plan adaptation of head-and-neck patients. Methods: We acquired CT scans of a head phantom with protocols corresponding to CT dose index volume CTDIvol in the range of 4.2–165.9 mGy. The highest value corresponds to the standard protocol used for CT simulations of 10 head-and-neck patients included in the study. The minimum value corresponds to the lowest achievable tube current of the GE Discovery RT scanner used for the study. For each patient and each low-dose protocol, the noise relative to the standard protocol, derived from phantom images, was applied to a virtual CT (vCT). The vCT was obtained from a daily CBCT scan corresponding to the fraction with the largest anatomical changes. We ran an established adaptive workflow twice for each low-dose protocol using a high-quality daily vCT and the corresponding low-dose synthetic vCT. For a relative comparison of the adaptation efficacy, two adapted plans were recalculated in the high-quality vCT and evaluated with the contours obtained through deformable registration of the planning CT. We also evaluated the accuracy of dose calculation in low-dose CT volumes using the standard CT protocol as reference. Results: The maximum differences in D98 between low-dose protocols and the standard protocol for the high-risk and low-risk CTV were found to be 0.6% and 0.3%, respectively. The difference in OAR sparing was up to 3%. The Dice similarity coefficient between propagated contours obtained with low-dose and standard protocols was above 0.982. The mean 2%/2 mm gamma pass rate for the lowest-dose image, using the standard protocol as reference, was found to be 99.99%. Conclusion: The differences between low-dose protocols and the standard scanning protocol were marginal. Thus, low-dose CT protocols are suitable for online adaptive proton therapy of head-and-neck cancers. As such, considering scanning protocols used in our clinic, the imaging dose associated with online adaption of head-and-neck cancers treated with protons can be reduced by a factor of 40.

Evaluating the effect of setup uncertainty reduction and adaptation to geometric changes on normal tissue complication probability using online adaptive head and neck intensity modulated proton therapy

“…While daily adaptation was used in this work as a proof of principle, it has been demonstrated that OAR sparing was comparable using daily and weekly OAs (Bobić et al 2021 ), suggesting that similar NTCP reductions as the one obtained in this study could be achieved using less frequent adaptations. Similarly, our results are expected to be representative of what would be achieved using CT-on-rails instead of scatter corrected CBCT as in-room imaging modality, since both were shown to provide clinically equivalent results in the context of head and neck online adaptive proton therapy (Nesteruk et al 2021 , 2022 ).…”

Large anatomical changes in head-and-neck cancers – A dosimetric comparison of online and offline adaptive proton therapy

“…Furthermore, we expect our results to be representative of using CT-on-rails instead of scatter-corrected CBCT for in-room imaging of the patient in the treatment position. Recent studies have shown that both modalities provide clinically equivalent results for adaptive proton therapy of head-andneck cancers [27,29].…”

“…We considered eight H&N patients initially treated with volumetric modulated arc therapy (VMAT) at the Massachusetts General Hospital between August 2019 and August 2021 because CBCT imaging was unavailable for our proton patients. Note that this patient cohort differs from the one in our previous studies [23,24,27,29] in that these patients required full offline replanning during their treatment due to large anatomical changes caused by weight loss, clinical target volume (CTV) shrinkage, or a combination of both. Table 1 summarizes the patient cohort, reflecting the observed weight and CTV size changes throughout the treatment.…”

“…We adapted nominal plans at every fraction with our online adaptive workflow published previously [19,23,24,27,29]. This workflow includes scatter-correction of CBCTs and DIR for contour propagation (see section 2.2), combined with GPU-accelerated MC dose calculations for an efficient treatment re-optimization.…”

Review and recommendations on deformable image registration uncertainties for radiotherapy applications

“…Sensitivity of DIR algorithms to image noise, resolution (Constable and Henkelman 1991 , Verdun et al 2015 , Zhao et al 2016 , Sarrut et al 2017 ), field of view (Barber et al 2020 ) and image contrast (Mencarelli et al 2014 , Barber et al 2020 , Dowling and O’Connor 2020 ) has been demonstrated in the literature. However, other studies find that the effect of image noise has only minor effects on DIR results for computed tomography (CT) to CT registrations (Nesteruk et al 2022 ).…”