Identification of patient benefit from proton beam therapy in brain tumour patients based on dosimetric and NTCP analyses

A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy

Objective.This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LETd) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LETdis associated with variability in the relative biological effectiveness (RBE) of protons, we also evaluate the implications of using NN predictions for normal tissue complication probability (NTCP) models within a variable-RBE context.Approach.The predictive performance of three-dimensional NN architectures was evaluated using five-fold cross-validation on a cohort of brain tumor patients (n= 151). The best-performing model was identified and externally validated on patients from a different center (n= 107). LETdpredictions were compared to MC-simulated results in clinically relevant regions of interest. We assessed the impact on NTCP models by leveraging LETdpredictions to derive RBE-weighted doses, using the Wedenberg RBE model.Main results.We found NNs based solely on the planned dose distribution, i.e. without additional usage of CT images, can approximate MC-based LETddistributions. Root mean squared errors (RMSE) for the median LETdwithin the brain, brainstem, CTV, chiasm, lacrimal glands (ipsilateral/contralateral) and optic nerves (ipsilateral/contralateral) were 0.36, 0.87, 0.31, 0.73, 0.68, 1.04, 0.69 and 1.24 keV µm-1, respectively. Although model predictions showed statistically significant differences from MC outputs, these did not result in substantial changes in NTCP predictions, with RMSEs of at most 3.2 percentage points.Significance.The ability of NNs to predict LETdbased solely on planned dose distributions suggests a viable alternative to compute-intensive MC simulations in a variable-RBE setting. This is particularly useful in scenarios where MC simulation data are unavailable, facilitating resource-constrained proton therapy treatment planning, retrospective patient data analysis and further investigations on the variability of proton RBE.

Proton Therapy for Advanced Juvenile Nasopharyngeal Angiofibroma

PURPOSE

To provide the first report on proton radiotherapy (PRT) in the management of advanced nasopharyngeal angiofibroma (JNA) and evaluate potential benefits compared to conformal photon therapy (XRT).

METHODS

We retrospectively reviewed 10 consecutive patients undergoing PRT for advanced JNA in a definitive or postoperative setting with a relative biological effectiveness weighted dose of 45 Gy in 25 fractions between 2012 and 2022 at the Heidelberg Ion Beam Therapy Center. Furthermore, dosimetric comparisons and risk estimations for short- and long-term radiation-induced complications between PRT plans and helical XRT plans were conducted.

RESULTS

PRT was well tolerated, with only low-grade acute toxicities (CTCAE I-II) being reported. The local control rate was 100% after a median follow-up of 27.0 (interquartile range 13.3-58.0) months. PRT resulted in considerable tumor shrinkage, leading to complete remission in five patients and bearing the potential to provide partial or complete symptom relief. Favorable dosimetric outcomes in critical brain substructures by the use of PRT translated into reduced estimated risks for neurocognitive impairment and radiation-induced CNS malignancies compared to XRT.

CONCLUSIONS

PRT is an effective treatment option for advanced JNA with minimal acute morbidity and the potential for reduced radiation-induced long-term complications.

Proton Bragg Peak FLASH Enables Organ Sparing and Ultra-High Dose-Rate Delivery: Proof of Principle in Recurrent Head and Neck Cancer

Proton pencil-beam scanning (PBS) Bragg peak FLASH combines ultra-high dose rate delivery and organ-at-risk (OAR) sparing. This proof-of-principle study compared dosimetry and dose rate coverage between PBS Bragg peak FLASH and PBS transmission FLASH in head and neck reirradiation. PBS Bragg peak FLASH plans were created via the highest beam single energy, range shifter, and range compensator, and were compared to PBS transmission FLASH plans for 6 GyE/fraction and 10 GyE/fraction in eight recurrent head and neck patients originally treated with quad shot reirradiation (14.8/3.7 CGE). The 6 GyE/fraction and 10 GyE/fraction plans were also created using conventional-rate intensity-modulated proton therapy techniques. PBS Bragg peak FLASH, PBS transmission FLASH, and conventional plans were compared for OAR sparing, FLASH dose rate coverage, and target coverage. All FLASH OAR V40 Gy/s dose rate coverage was 90-100% at 6 GyE and 10 GyE for both FLASH modalities. PBS Bragg peak FLASH generated dose volume histograms (DVHs) like those of conventional therapy and demonstrated improved OAR dose sparing over PBS transmission FLASH. All the modalities had similar CTV coverage. PBS Bragg peak FLASH can deliver conformal, ultra-high dose rate FLASH with a two-millisecond delivery of the minimum MU per spot. PBS Bragg peak FLASH demonstrated similar dose rate coverage to PBS transmission FLASH with improved OAR dose-sparing, which was more pronounced in the 10 GyE/fraction than in the 6 GyE/fraction. This feasibility study generates hypotheses for the benefits of FLASH in head and neck reirradiation and developing biological models.

The role of particle radiotherapy in the treatment of skull base tumors

The skull base is an anatomically and functionally critical area surrounded by vital structures such as the brainstem, the spinal cord, blood vessels, and cranial nerves. Due to this complexity, management of skull base tumors requires a multidisciplinary approach involving a team of specialists such as neurosurgeons, otorhinolaryngologists, radiation oncologists, endocrinologists, and medical oncologists. In the case of pediatric patients, cancer management should be performed by a team of pediatric-trained specialists. Radiation therapy may be used alone or in combination with surgery to treat skull base tumors. There are two main types of radiation therapy: photon therapy and particle therapy. Particle radiotherapy uses charged particles (protons or carbon ions) that, due to their peculiar physical properties, permit precise targeting of the tumor with minimal healthy tissue exposure. These characteristics allow for minimizing the potential long-term effects of radiation exposure in terms of neurocognitive impairments, preserving quality of life, and reducing the risk of radio-induced cancer. For these reasons, in children, adolescents, and young adults, proton therapy should be an elective option when available. In radioresistant tumors such as chordomas and sarcomas and previously irradiated recurrent tumors, particle therapy permits the delivery of high biologically effective doses with low, or however acceptable, toxicity. Carbon ion therapy has peculiar and favorable radiobiological characteristics to overcome radioresistance features. In low-grade tumors, proton therapy should be considered in challenging cases due to tumor volume and involvement of critical neural structures. However, particle radiotherapy is still relatively new, and more research is needed to fully understand its effects. Additionally, the availability of particle therapy is limited as it requires specialized equipment and expertise. The purpose of this manuscript is to review the available literature regarding the role of particle radiotherapy in the treatment of skull base tumors.

The characteristic of stem-related genes with pancreatic carcinoma cell after irradiation

Purpose

To investigate stem-related differentially expressed genes (DEGs) and their potential mechanism in pancreatic cancer cells (MIAPaCa-2) exposed to x-ray and proton radiation, as well as how these factors affected the prognosis of patients with pancreatic adenocarcinoma (PADC).

Methods

The stem-related DEGs were screened using the online tool Stemchecker after protons and x-rays were used to irradiate MIAPaCa-2 cells. Analysis was done on the probable processes and prognostic significance of the DEGs in PAC patients.

Results

Four datasets containing 401 DEGs were filtered, and the stem-related DEGs for each irradiation type indicated a variety of radiobiological characteristics. In pancreatic cancer cells, a number of stem-related DEGs may serve as biomarkers of radiation effects. Patients with pancreatic cancer demonstrated predictive significance for GRB7, B2M, and PMAIP1.

Conclusions

MIAPaCa-2 cells exposed to x-rays and protons repeatedly displayed heterogeneous expression of stem-related DEGs involved in complex radiosensitivity, radio-resistance, and radio-induced mortality pathways. GRB7 and B2M were considered potential radiation sensitivity indicators for pancreatic cancer.

The relation between prediction model performance measures and patient selection outcomes for proton therapy in head and neck cancer

BACKGROUND

Normal-tissue complication probability (NTCP) models predict complication risk in patients receiving radiotherapy, considering radiation dose to healthy tissues, and are used to select patients for proton therapy, based on their expected reduction in risk after proton therapy versus photon radiotherapy (ΔNTCP). Recommended model evaluation measures include area under the receiver operating characteristic curve (AUC), overall calibration (CITL), and calibration slope (CS), whose precise relation to patient selection is still unclear. We investigated how each measure relates to patient selection outcomes.

METHODS

The model validation and consequent patient selection process was simulated within empirical head and neck cancer patient data. By manipulating performance measures independently via model perturbations, the relation between model performance and patient selection was studied.

RESULTS

Small reductions in AUC (-0.02) yielded mean changes in ΔNTCP between 0.9-3.2 %, and single-model patient selection differences between 2-19 %. Deviations (-0.2 or +0.2) in CITL or CS yielded mean changes in ΔNTCP between 0.3-1.4 %, and single-model patient selection differences between 1-10 %.

CONCLUSIONS

Each measure independently impacts ΔNTCP and patient selection and should thus be assessed in a representative sufficiently large external sample. Our suggested practical model selection approach is considering the model with the highest AUC, and recalibrating it if needed.

A study on predicting cases that would benefit from proton beam therapy in primary liver tumors of less than or equal to 5 cm based on the estimated incidence of hepatic toxicity

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An advantage of PBT is reducing the liver receiving low doses of radiation.

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The factors predicting the benefit in PBT are different among NTCP models.

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The tumor size, number, and location are useful in estimating the benefits of PBT.

Background

Materials and methods

Results

Conclusions

Estimating the percentage of patients who might benefit from proton beam therapy instead of X-ray radiotherapy

OBJECTIVES

High-energy Proton Beam Therapy (PBT) commenced in England in 2018 and NHS England commissions PBT for 1.5% of patients receiving radical radiotherapy. We sought expert opinion on the level of provision.

METHODS

Invitations were sent to 41 colleagues working in PBT, most at one UK centre, to contribute by completing a spreadsheet. 39 responded: 23 (59%) completed the spreadsheet; 16 (41%) declined, arguing that clinical outcome data are lacking, but joined six additional site-specialist oncologists for two consensus meetings. The spreadsheet was pre-populated with incidence data from Cancer Research UK and radiotherapy use data from the National Cancer Registration and Analysis Service. 'Mechanisms of Benefit' of reduced growth impairment, reduced toxicity, dose escalation and reduced second cancer risk were examined.

RESULTS

The most reliable figure for percentage of radical radiotherapy patients likely to benefit from PBT was that agreed by 95% of the 23 respondents at 4.3%, slightly larger than current provision. The median was 15% (range 4-92%) and consensus median 13%. The biggest estimated potential benefit was from reducing toxicity, median benefit to 15% (range 4-92%), followed by dose escalation median 3% (range 0 to 47%); consensus values were 12 and 3%. Reduced growth impairment and reduced second cancer risk were calculated to benefit 0.5% and 0.1%.

CONCLUSIONS

The most secure estimate of percentage benefit was 4.3% but insufficient clinical outcome data exist for confident estimates. The study supports the NHS approach of using the evidence base and developing it through randomised trials, non-randomised studies and outcomes tracking.

ADVANCES IN KNOWLEDGE

Less is known about the percentage of patients who may benefit from PBT than is generally acknowledged. Expert opinion varies widely. Insufficient clinical outcome data exist to provide robust estimates. Considerable further work is needed to address this, including international collaboration; much is already underway but will take time to provide mature data.

Treatment plan comparison of proton vs photon radiotherapy for lower-grade gliomas

Background and purpose

Patients with lower-grade gliomas are long-term survivors after radiotherapy and may benefit from the reduced dose to normal tissue achievable with proton therapy. Here, we aimed to quantify differences in dose to the uninvolved brain and contralateral hippocampus and compare the risk of radiation-induced secondary cancer for photon and proton plans for lower-grade glioma patients.

Materials and methods

Twenty-three patients were included in this in-silico planning comparative study and had photon and proton plans calculated (50.4 Gy(RBE = 1.1), 28 Fx) applying similar dose constraints to the target and organs at risk. Automatically calculated photon plans were generated with a 3 mm margin from clinical target volume (CTV) to planning target volume. Manual proton plans were generated using robust optimisation on the CTV. Dose metrics of organs at risk were compared using population mean dose-volume histograms and Wilcoxon signed-rank test. Secondary cancer risk per 10,000 persons per year (PPY) was estimated using dose-volume data and a risk model for secondary cancer induction.

Results

CTV coverage (V95%>98%) was similar for the two treatment modalities. Mean dose (D_mean) to the uninvolved brain was significantly reduced from 21.5 Gy (median, IQR 17.1–24.4 Gy) with photons compared to 10.3 Gy(RBE) (8.1–13.9 Gy(RBE)) with protons. D_mean to the contralateral hippocampus was significantly reduced from 6.5 Gy (5.4–11.7 Gy) with photons to 1.5 Gy(RBE) (0.4–6.8 Gy(RBE)) with protons. The estimated secondary cancer risk was reduced from 6.7 PPY (median, range 3.3–10.4 PPY) with photons to 3.0 PPY (1.3–7.5 PPY) with protons.

Conclusion

A significant reduction in mean dose to uninvolved brain and contralateral hippocampus was found with proton planning. The estimated secondary cancer risk was reduced with proton therapy.