The Importance of Verification CT-QA Scans in Patients Treated with IMPT for Head and Neck Cancers

Clinical workload profile of medical physics professionals at particle therapy Centers: a National Survey in Japan

The current research on staffing models is primarily focused on conventional external photon beam therapy, which predominantly involves using linear accelerators. This emphasizes the need for comprehensive studies to understand better and define specific particle therapy facilities' staffing requirements. In a 2022 survey of 25 particle therapy facilities in Japan with an 84% response rate, significant insights were obtained regarding workload distribution, defined as the product of personnel count and task time (person-minutes), for patient-related tasks and equipment quality assurance and quality control (QA/QC). The survey revealed that machinery QA/QC tasks were particularly demanding, with an average monthly workload of 376.9 min and weekly tasks averaging 162.1 min. In comparison, patient-related workloads focused on treatment planning, exhibiting substantial time commitments, particularly for scanning and passive scattering techniques. The average workloads for treatment planning per patient were 291.3 and 195.4 min, respectively. In addition, specific patient scenarios such as pre-treatment sedation in pediatric cases require longer durations (averaging 84.5 min), which likely include the workloads of not only the physician responsible for sedation but also the radiotherapy technology and medical physics specialists providing support during sedation and the nursing staff involved in sedation care. These findings underscore the significant time investments required for machinery QA/QC and patient-specific treatment planning in particle therapy facilities, along with the need for specialized care procedures in pediatric cases. The results of this survey also emphasized the challenges and staffing requirements to ensure QA/QC in high-precision medical environments.

Cone-Beam CT Images as an Indicator of QACT During Adaptive Proton Therapy of Extremity Sarcomas

Purpose

Periodic quality assurance CTs (QACTs) are routine in proton beam therapy. In this study, we tested whether the necessity for a QACT could be determined by evaluating the change in beam path length (BPL) on daily cone-beam CT (CBCT).

Patients and Methods

In this Institutional Review Board-approved study, we retrospectively analyzed 959 CBCT images from 78 patients with sarcomas treated with proton pencil-beam scanning. Plans on 17 QACTs out of a total of 243 were clinically determined to be replanned for various reasons. Daily CBCTs were retrospectively analyzed by automatic ray-tracing of each beam from the isocenter to the skin surface along the central axis. A script was developed for this purpose. Patterns of change in BPL on CBCT images were compared to those from adaptive planning using weekly QACTs.

Results

Sixteen of the 17 adaptive replans showed BPL changes ≥4 mm for at least 1 of the beams on 3 consecutive CBCT sessions. Similarly, 43 of 63 nonadaptively planned patients had BPL changes <4 mm for all of the beams. A new QACT criterium of a BPL change of any beam ≥4 mm on 3 consecutive CBCT sessions resulted in a sensitivity of 94.1% and a specificity of 68.3%. Had the BPL change been used as the QACT predictor, a total of 37 QACTs would have been performed rather than 243 QACTs in clinical practice.

Conclusion

The use of BPL changes on CBCT images represented a significant reduction (85%) in total QACT burden while maintaining treatment quality and accuracy. QACT can be performed only when it is needed, but not in a periodic manner. The benefits of reducing QACT frequency include reducing imaging dose and optimizing patient time and staff resources.

Impact of Relative Biologic Effectiveness for Proton Therapy for Head and Neck and Skull-Base Tumors: A Technical and Clinical Review

Proton therapy has emerged as a crucial tool in the treatment of head and neck and skull-base cancers, offering advantages over photon therapy in terms of decreasing integral dose and reducing acute and late toxicities, such as dysgeusia, feeding tube dependence, xerostomia, secondary malignancies, and neurocognitive dysfunction. Despite its benefits in dose distribution and biological effectiveness, the application of proton therapy is challenged by uncertainties in its relative biological effectiveness (RBE). Overcoming the challenges related to RBE is key to fully realizing proton therapy's potential, which extends beyond its physical dosimetric properties when compared with photon-based therapies. In this paper, we discuss the clinical significance of RBE within treatment volumes and adjacent serial organs at risk in the management of head and neck and skull-base tumors. We review proton RBE uncertainties and its modeling and explore clinical outcomes. Additionally, we highlight technological advancements and innovations in plan optimization and treatment delivery, including linear energy transfer/RBE optimizations and the development of spot-scanning proton arc therapy. These advancements show promise in harnessing the full capabilities of proton therapy from an academic standpoint, further technological innovations and clinical outcome studies, however, are needed for their integration into routine clinical practice.

Integrated-mode proton radiography with 2D lateral projections

Integrated-mode proton radiography leading to water equivalent thickness (WET) maps is an avenue of interest for motion management, patient positioning, andin vivorange verification. Radiographs can be obtained using a pencil beam scanning setup with a large 3D monolithic scintillator coupled with optical cameras. Established reconstruction methods either (1) involve a camera at the distal end of the scintillator, or (2) use a lateral view camera as a range telescope. Both approaches lead to limited image quality. The purpose of this work is to propose a third, novel reconstruction framework that exploits the 2D information provided by two lateral view cameras, to improve image quality achievable using lateral views. The three methods are first compared in a simulated Geant4 Monte Carlo framework using an extended cardiac torso (XCAT) phantom and a slanted edge. The proposed method with 2D lateral views is also compared with the range telescope approach using experimental data acquired with a plastic volumetric scintillator. Scanned phantoms include a Las Vegas (contrast), 9 tissue-substitute inserts (WET accuracy), and a paediatric head phantom. Resolution increases from 0.24 (distal) to 0.33 lp mm-1(proposed method) on the simulated slanted edge phantom, and the mean absolute error on WET maps of the XCAT phantom is reduced from 3.4 to 2.7 mm with the same methods. Experimental data from the proposed 2D lateral views indicate a 36% increase in contrast relative to the range telescope method. High WET accuracy is obtained, with a mean absolute error of 0.4 mm over 9 inserts. Results are presented for various pencil beam spacing ranging from 2 to 6 mm. This work illustrates that high quality proton radiographs can be obtained with clinical beam settings and the proposed reconstruction framework with 2D lateral views, with potential applications in adaptive proton therapy.

Deformable CT image registration via a dual feasible neural network

PURPOSE

A quality assurance (QA) CT scans are usually acquired during cancer radiotherapy to assess for any anatomical changes, which may cause an unacceptable dose deviation and therefore warrant a replan. Accurate and rapid deformable image registration (DIR) is needed to support contour propagation from the planning CT (pCT) to the QA CT to facilitate dose volume histogram (DVH) review. Further, the generated deformation maps are used to track the anatomical variations throughout the treatment course and calculate the corresponding accumulated dose from one or more treatment plans.

METHODS

In this study, we aim to develop a deep learning (DL)-based method for automatic deformable registration to align the pCT and the QA CT. Our proposed method, named dual-feasible framework, was implemented by a mutual network that functions as both a forward module and a backward module. The mutual network was trained to predict two deformation vector fields (DVFs) simultaneously, which were then used to register the pCT and QA CT in both directions. A novel dual feasible loss was proposed to train the mutual network. The dual-feasible framework was able to provide additional DVF regularization during network training, which preserves the topology and reduces folding problems. We conducted experiments on 65 head-and-neck cancer patients (228 CTs in total), each with 1 pCT and 2-6 QA CTs. For evaluations, we calculated the mean absolute error (MAE), peak-signal-to-noise ratio (PSNR), structural similarity index (SSIM), target registration error (TRE) between the deformed and target images and the Jacobian determinant of the predicted DVFs.

RESULTS

Within the body contour, the mean MAE, PSNR, SSIM, and TRE are 122.7 HU, 21.8 dB, 0.62 and 4.1 mm before registration and are 40.6 HU, 30.8 dB, 0.94, and 2.0 mm after registration using the proposed method. These results demonstrate the feasibility and efficacy of our proposed method for pCT and QA CT DIR.

CONCLUSION

In summary, we proposed a DL-based method for automatic DIR to match the pCT to the QA CT. Such DIR method would not only benefit current workflow of evaluating DVHs on QA CTs but may also facilitate studies of treatment response assessment and radiomics that depend heavily on the accurate localization of tissues across longitudinal images.

Improving workflow for adaptive proton therapy with predictive anatomical modelling: A proof of concept

PURPOSE

To demonstrate predictive anatomical modelling for improving the clinical workflow of adaptive intensity-modulated proton therapy (IMPT) for head and neck cancer.

METHODS

10 radiotherapy patients with nasopharyngeal cancer were included in this retrospective study. Each patient had a planning CT, weekly verification CTs during radiotherapy and predicted weekly CTs from our anatomical model. Predicted CTs were used to create predicted adaptive plans in advance with the aim of maintaining clinically acceptable dosimetry. Adaption was triggered when the increase in mean dose (Dmean) to the parotid glands exceeded 3 Gy(RBE). We compared the accumulated dose of two adaptive IMPT strategies: 1) Predicted plan adaption: One adaptive plan per patient was optimised on a predicted CT triggered by replan criteria. 2) Standard replan: One adaptive plan was created reactively in response to the triggering weekly CT.

RESULTS

Statistical analysis demonstrates that the accumulated dose differences between two adaptive strategies are not significant (p > 0.05) for CTVs and OARs. We observed no meaningful differences in D95 between the accumulated dose and the planned dose for the CTVs, with mean differences to the high-risk CTV of -1.20 %, -1.23 % and -1.25 % for no adaption, standard and predicted plan adaption, respectively. The accumulated parotid Dmean using predicted plan adaption is within 3 Gy(RBE) of the planned dose and 0.31 Gy(RBE) lower than the standard replan approach on average.

CONCLUSION

Prediction-based replanning could potentially enable adaptive therapy to be delivered without treatment gaps or sub-optimal fractions, as can occur during a standard replanning strategy, though the benefit of using predicted plan adaption over the standard replan was not shown to be statistically significant with respect to accumulated dose in this study. Nonetheless, a predictive replan approach can offer advantages in improving clinical workflow efficiency.

Analysis of the Rate of Re-planning in Spot-Scanning Proton Therapy

Purpose

Finite proton range affords improved dose conformality of radiation therapy when patient regions-of-interest geometries are well characterized. Substantial changes in patient anatomy necessitate re-planning (RP) to maintain effective, safe treatment. Regularly planned verification scanning (VS) is performed to ensure consistent treatment quality. Substantial resources, however, are required to conduct an effective proton plan verification program, which includes but is not limited to, additional computed tomography (CT) scanner time and dedicated personnel: radiation therapists, medical physicists, physicians, and medical dosimetrists.

Materials and Methods

Verification scans (VSs) and re-plans (RPs) of 711 patients treated with proton therapy between June 2015 and June 2018 were studied. All treatment RP was performed with the intent to maintain original plan integrity and coverage. The treatments were classified by anatomic site: brain, craniospinal, bone, spine, head and neck (H&N), lung or chest, breast, prostate, rectum, anus, pelvis, esophagus, liver, abdomen, and extremity. Within each group, the dates of initial simulation scan, number of VSs, number of fractions completed at the time of VS, and the frequency of RP were collected. Data were analyzed in terms of rate of RP and individual likelihood of RP.

Results

A total of 2196 VSs and 201 RPs were performed across all treatment sites. H&N and lung or chest disease sites represented the largest proportion of plan modifications in terms of rate of re-plan (RoR: 54% and 58%, respectively) and individual likelihood of RP on a per patient basis (likelihood of RP [RP%]: 46% and 39%, respectively). These sites required RP beyond 4 weeks of treatment, suggesting continued benefit for frequent, periodic VS. Disease sites in the lower pelvis demonstrated a low yield for RP per VS (0.01-0.02), suggesting that decreasing VS frequency, particularly late in treatment, may be reasonable.

Conclusions

A large degree of variation in RoR and individual RP% was observed between anatomic treatment sites. The present retrospective analysis provides data to help develop anatomic site–based VS protocols.

Air variability in maxillary sinus during radiotherapy for sinonasal carcinoma

INTRODUCTION

The aim was to characterise patterns and predictability of aeration changes in the ipsilateral maxillary sinus during intensity-modulated radiotherapy (IMRT) for sinonasal cancer (SNC), and in a sample evaluate the dosimetric effects of aeration changes for both photon and proton therapy.

MATERIALS AND METHODS

The study included patients treated with IMRT for SNC in a single institution in 2009-2017. The volume of air in the ipsilateral maxillary sinus was recorded in 1578 daily cone beam computer tomography (CBCT) from 53 patients. Patterns of changing air volumes were categorised as 'stable', increasing', 'decreasing', or 'erratic'. For the prediction analysis, categorisation was performed based both on the entire treatment course and the first five fractions (F1-5). Photon and proton therapy plans were generated for four patients, the one from each category with the largest aeration variation. Synthetic CT images were generated for each CBCT and all plans were recalculated on the daily synthetic CTs.

RESULTS

The absolute volume of air varied considerably during the treatment course, ranging from 0 to 25.9 cm3. Changes within a single participant varied in the range of 0-18.7 cm3. In the categorisation of patterns, most patients had increasing aeration of the sinus. Generally, patterns of aeration could not be predicted from F1-5. Patients categorised as increasing in F1-5 had the best prediction, with 78% predicted correctly as increasing for the entire treatment course. The numeric correlation coefficients for target coverage and air volume were low for 3/4 scenarios (photons 0.03-0.23, protons 0.26-0.48). No straightforward correlation between the dosimetric effect and the volume changes could be detected in the sample test of four patients for neither photon nor proton therapy.

CONCLUSION

The variation of aeration was large and unpredictable. No clear dosimetric consequences of the aeration variation were evident for neither IMRT nor proton therapy for the patients investigated.