Dosimetric Results for Adjuvant Proton Radiation Therapy of HPV-Associated Oropharynx Cancer

Purpose One significant advantage of proton therapy is its ability to improve normal tissue sparing and toxicity mitigation, which is relevant in the treatment of oropharyngeal squamous cell carcinoma (OPSCC). Here, we report our institutional experience and dosimetric results with adjuvant proton radiation therapy (PRT) versus intensity-modulated radiotherapy (IMRT) for Human Papilloma Virus (HPV)-associated OPSCC. Materials and Methods This was a retrospective, single institutional study of all patients treated with adjuvant PRT for HPV-associated OPSCC from 2015 to 2019. Each patient had a treatment-approved equivalent IMRT plan to serve as a reference. Endpoints included dosimetric outcomes to the organs at risk (OARs), local regional control (LRC), progression-free survival (PFS), and overall survival (OS). Descriptive statistics, a 2-tailed paired t test for dosimetric comparisons, and the Kaplan-Meier method for disease outcomes were used. Results Fifty-three patients were identified. Doses delivered to OARs compared favorably for PRT versus IMRT, particularly for the pharyngeal constrictors, esophagus, larynx, oral cavity, and submandibular and parotid glands. The achieved normal tissue sparing did not negatively impact disease outcomes, with 2-year LRC, PFS, and OS of 97.0%, 90.3%, and 97.5%, respectively. Conclusion Our study suggests that meaningful normal tissue sparing in the postoperative setting is achievable with PRT, without impacting disease outcomes.

NCOG-20. LONGITUDINAL ASSESSMENT OF SUBJECTIVE COGNITIVE FUNCTION IN ADULTS WITH LOW GRADE GLIOMA TREATED WITH PROTON RADIATION THERAPY

INTRODUCTION Our group previously demonstrated stability in neurocognitive function (NCF) over a 5-year period after proton radiation therapy (PRT) in low grade glioma (LGG) patients. Subjective cognitive function (SCF) had not been previously explored, nor had individual analyses of cognition, which can detect variability in trajectory. We used the newly derived Functional Assessment of Cancer Therapy-Brain Cognitive-Index (FACT-Br-CI) to examine SCF in LGG patients after PRT and compare longitudinal changes in SCF and NCF. METHODS 20 LGG patients (M age =37.5) treated with PRT completed NCF tests and self-report measures annually for 5 years or until tumor progression. Group change in SCF was examined with paired t-test (baseline vs final FACT-Br-CI). Individual change scores were calculated for FACT-Br-CI and NCF tests (clinical trials battery composite; CTBC). Individual deterioration in NCF was defined by reliable change index (RCI) on CTBC, and in SCF was defined as decline of >/=1 SD in FACT-Br-CI. Relationships between change in SCF and NCF were explored with correlations. RESULTS At the group level, no change was observed in FACT-Br-CI between baseline and last follow-up (t(19)=-.91;p=ns). Individual SCF analyses at last follow-up found the number of patients reporting decline=3 (15%), improvement=5 (25%), and no change=12 (60%). Individual changes were observed in SCF in 20% of patients at 3 months, 5.9% at 6 months, 12.5% at 12 months, 13.3% at 24 months, and 11.1% at 36 months. Median time to any deterioration in SCF was 36 months and for NCF was not reached. Correlation between CTBC and FACT-Br-CI change scores did not reach statistical significance (r=.41;p=ns). CONCLUSION Consistent with previous research, group analyses of LGG patients did not show cognitive decline after PRT. However individual analyses of SCF showed variability within the group: some patients experienced cognitive decline during follow up. Consideration of individual differences may yield additional information.

A comparative study on dispersed doses during photon and proton radiation therapy in pediatric applications

The Monte Carlo method was employed to simulate realistic treatment situations for photon and proton radiation therapy for a set of Oak Ridge National Laboratory (ORNL) pediatric phantoms for 15, 10, 5 and 1-year olds as well as newborns. Complete radiotherapy situations were simulated using the previously developed NRUrad input code for Monte Carlo N-Particle (MCNP) code package. Each pediatric phantom was irradiated at five different positions, namely, the testes, colon, liver, left lung and brain, and the doses in targeted organs (Dt) were determined using the track length estimate of energy. The dispersed photon and proton doses in non-targeted organs (Dd), namely, the skeleton, skin, brain, spine, left and right lungs were computed. The conversion coefficients (F = Dd/Dt) of the dispersed doses were used to study the dose dispersion in different non-targeted organs for phantoms for 15, 10, 5 and 1-year olds as well as newborns. In general, the F values were larger for younger patients. The F values for non-targeted organs for phantoms for 1-year olds and newborns were significantly larger compared to those for other phantoms. The dispersed doses from proton radiation therapy were also found to be significantly lower than those from conventional photon radiation therapy. For example, the largest F values for the brain were 65.6% and 0.206% of the dose delivered to the left lung (P4) for newborns during photon and proton radiation therapy, respectively. The present results demonstrated that dispersion of photons and generated electrons significantly affected the absorbed doses in non-targeted organs during pediatric photon therapy, and illustrated that proton therapy could in general bring benefits for treatment of pediatric cancer patients.

Accounting with a lessor — a manufacturer of expensive medical equipment

The article deals with the features of reflection in the accounting of organizations that are manufacturers of expensive medical equipment, the transfer of this medical equipment to non-operational (financial) lease to medical organizations. The article reviews the possibilities of proton therapy, manufacturers of equipment for proton therapy, including Russian ones. It is Russian manufacturers who are actively working on the development of compact proton accelerator samples that can be placed in any, not only specialized medical organizations. The article presents an example of accounting for accounting objects (revenue, cost, financial result (profit/loss)) arising on the date of conclusion of the contract of non-operational (financial) lease of equipment for proton radiation therapy.

Learning-Based Stopping Power Mapping on Dual-Energy CT for Proton Radiation Therapy

Purpose Dual-energy computed tomography (DECT) has been used to derive relative stopping power (RSP) maps by obtaining the energy dependence of photon interactions. The DECT-derived RSP maps could potentially be compromised by image noise levels and the severity of artifacts when using physics-based mapping techniques. This work presents a noise-robust learning-based method to predict RSP maps from DECT for proton radiation therapy. Materials and Methods The proposed method uses a residual attention cycle-consistent generative adversarial network to bring DECT-to-RSP mapping close to a 1-to-1 mapping by introducing an inverse RSP-to-DECT mapping. To evaluate the proposed method, we retrospectively investigated 20 head-and-neck cancer patients with DECT scans in proton radiation therapy simulation. Ground truth RSP values were assigned by calculation based on chemical compositions and acted as learning targets in the training process for DECT datasets; they were evaluated against results from the proposed method using a leave-one-out cross-validation strategy. Results The predicted RSP maps showed an average normalized mean square error of 2.83% across the whole body volume and an average mean error less than 3% in all volumes of interest. With additional simulated noise added in DECT datasets, the proposed method still maintained a comparable performance, while the physics-based stoichiometric method suffered degraded inaccuracy from increased noise level. The average differences from ground truth in dose volume histogram metrics for clinical target volumes were less than 0.2 Gy for D95% and Dmax with no statistical significance. Maximum difference in dose volume histogram metrics of organs at risk was around 1 Gy on average. Conclusion These results strongly indicate the high accuracy of RSP maps predicted by our machine-learning–based method and show its potential feasibility for proton treatment planning and dose calculation.