A radiobiological Markov simulation tool for aiding decision making in proton therapy referral

Markov models for clinical decision-making in radiation oncology: A systematic review

The intrinsic stochasticity of patients' response to treatment is a major consideration for clinical decision-making in radiation therapy. Markov models are powerful tools to capture this stochasticity and render effective treatment decisions. This paper provides an overview of the Markov models for clinical decision analysis in radiation oncology. A comprehensive literature search was conducted within MEDLINE using PubMed, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only studies published from 2000 to 2023 were considered. Selected publications were summarized in two categories: (i) studies that compare two (or more) fixed treatment policies using Monte Carlo simulation and (ii) studies that seek an optimal treatment policy through Markov Decision Processes (MDPs). Relevant to the scope of this study, 61 publications were selected for detailed review. The majority of these publications (n = 56) focused on comparative analysis of two or more fixed treatment policies using Monte Carlo simulation. Classifications based on cancer site, utility measures and the type of sensitivity analysis are presented. Five publications considered MDPs with the aim of computing an optimal treatment policy; a detailed statement of the analysis and results is provided for each work. As an extension of Markov model-based simulation analysis, MDP offers a flexible framework to identify an optimal treatment policy among a possibly large set of treatment policies. However, the applications of MDPs to oncological decision-making have been understudied, and the full capacity of this framework to render complex optimal treatment decisions warrants further consideration.

Proton beam therapy for skull base chordomas: a systematic review of tumor control rates and survival rates

The management of base of skull (BS) chordomas is a neurosurgical conundrum owing to their close proximity to the critical neurovascular structures. Surgical resection is the gold standard treatment followed by adjuvant radiotherapy which includes photon therapy, proton beam therapy (PBT), gamma knife radiosurgery, etc. PBT has become an unparalleled therapeutic modality in the management of BS chordomas. The aim of this systematic review was to assess the outcomes in BS chordoma patients who received PBT as a primary or adjuvant therapy. PubMed and Cochrane databases were screened till May 2022. Following the PRISMA guidelines, studies were reviewed thoroughly, and the data of the included study was extracted. Statistical analysis was performed using the SAS 9.4 with P value < .05 considered as significant. Sixteen studies with 752 patients were included. The majority of the patients were adults (> 18 years) with a male:female ratio of 1.2. The most common clinical features were cranial nerve (3rd, 6th, or 12th) palsy and hearing impairment. Ninety-five percent of the patients underwent surgical resection before PBT. The mean PBT dose received was 74.02 cGe (cobalt gray equivalent). Eighty percent of the patients showed a positive response to the therapy defined in terms of tumor regression. Five-year local control (LC), overall survival (OS), and progression-free survival (PFS) were calculated as 76.6%, 79.6%, and 89%, respectively. Statistical analysis revealed none of the factors had any significant association with 5-year LC. PBT is a growing therapeutic technique that has revolutionized the treatment of BS chordomas.

Proton Therapy for Squamous Cell Carcinoma of the Head and Neck: Early Clinical Experience and Current Challenges

Simple Summary

Proton therapy is a promising type of radiation therapy used to destroy tumor cells. It has the potential to further improve the outcomes for patients with head and neck cancer since it allows to minimize the radiation dose to vital structures around the tumor, leading to less toxicity. This paper describes the current experience worldwide with proton therapy in head and neck cancer.

Abstract

Proton therapy (PT) is a promising development in radiation oncology, with the potential to further improve outcomes for patients with squamous cell carcinoma of the head and neck (HNSCC). By utilizing the finite range of protons, healthy tissue can be spared from beam exit doses that would otherwise be irradiated with photon-based treatments. Current evidence on PT for HNSCC is limited to comparative dosimetric analyses and retrospective single-institution series. As a consequence, the recognized indications for the reimbursement of PT remain scarce in most countries. Nevertheless, approximately 100 PT centers are in operation worldwide, and initial experiences for HNSCC are being reported. This review aims to summarize the results of the early clinical experience with PT for HNSCC and the challenges that are currently faced.

Current practice in proton therapy delivery in adult cancer patients across Europe

BACKGROUND AND PURPOSE

Major differences exist among proton therapy (PT) centres regarding PT delivery in adult cancer patient. To obtain insight into current practice in Europe, we performed a survey among European PT centres.

MATERIALS AND METHODS

We designed electronic questionnaires for eight tumour sites, focusing on four main topics: 1) indications and patient selection methods; 2) reimbursement; 3) on-going or planned studies, 4) annual number of patients treated with PT.

RESULTS

Of 22 centres, 19 (86%) responded. In total, 4233 adult patients are currently treated across Europe annually, of which 46% consists of patients with central nervous system tumours (CNS), 15% head and neck cancer (HNC), 15% prostate, 9% breast, 5% lung, 5% gastrointestinal, 4% lymphoma, 0.3% gynaecological cancers. CNS are treated in all participating centres (n = 19) using PT, HNC in 16 centres, lymphoma in 10 centres, gastrointestinal in 10 centres, breast in 7 centres, prostate in 6 centres, lung in 6 centres, and gynaecological cancers in 3 centres. Reimbursement is provided by national health care systems for the majority of commonly treated tumour sites. Approximately 74% of centres enrol patients for prospective data registration programs. Phase II-III trials are less frequent, due to reimbursement and funding problems. Reasons for not treating certain tumour types with PT are lack of evidence (30%), reimbursement issues (29%) and/or technical limitations (20%).

CONCLUSION

Across European PT centres, CNS tumours and HNC are the most frequently treated tumour types. Most centres use indication protocols. Lack of evidence for PT and reimbursement issues are the most reported reasons for not treating specific tumour types with PT.

Normal tissue complication probability modeling to guide individual treatment planning in pediatric cranial proton and photon radiotherapy

PURPOSE

Proton therapy (PT) is broadly accepted as the gold standard of care for pediatric patients with cranial cancer. The superior dose distribution of PT compared to photon radiotherapy reduces normal tissue complication probability (NTCP) for organs at risk. As NTCPs for pediatric organs are not well understood, clinics generally base radiation response on adult data. However, there is evidence that radiation response strongly depends on the age and even sex of a patient. Furthermore, questions surround the influence of individual intrinsic radiosensitivity (α/β ratio) on pediatric NTCP. While the clinical pediatric NTCP data is scarce, radiobiological modeling and sensitivity analyses can be used to investigate the NTCP trends and its dependence on individual modeling parameters. The purpose of this study was to perform sensitivity analyses of NTCP models to ascertain the dependence of radiosensitivity, sex, and age of a child and predict cranial side-effects following intensity-modulated proton therapy (IMPT) and intensity-modulated radiotherapy (IMRT).

METHODS

Previously, six sex-matched pediatric cranial datasets (5, 9, and 13 years old) were planned in Varian Eclipse treatment planning system (13.7). Up to 108 scanning beam IMPT plans and 108 IMRT plans were retrospectively optimized for a range of simulated target volumes and locations. In this work, dose-volume histograms were extracted and imported into BioSuite Software for radiobiological modeling. Relative-Seriality and Lyman-Kutcher-Burman models were used to calculate NTCP values for toxicity endpoints, where TD50, (based on reported adult clinical data) was varied to simulate sex dependence of NTCP. Plausible parameter ranges, based on published literature for adults, were used in modeling. In addition to sensitivity analyses, a 20% difference in TD50 was used to represent the radiosensitivity between the sexes (with females considered more radiosensitive) for ease of data comparison as a function of parameters such as α/β ratio.

RESULTS

IMPT plans resulted in lower NTCP compared to IMRT across all models (p < 0.0001). For medulloblastoma treatment, the risk of brainstem necrosis (> 10%) and cochlea tinnitus (> 20%) among females could potentially be underestimated considering a lower TD50 value for females. Sensitivity analyses show that the difference in NTCP between sexes was significant (p < 0.0001). Similarly, both brainstem necrosis and cochlea tinnitus NTCP varied significantly (p < 0.0001) across tested α/β as a function of TD50 values (assumption being that TD50 values are 20% lower in females). If the true α/β of these pediatric tissues is higher than expected (α/β ∼ 3), the risk of tinnitus for IMRT can significantly increase (p < 0.0001).

CONCLUSION

Due to the scarcity of pediatric NTCP data available, sensitivity analyses were performed using plausible ranges based on published adult data. In the clinical scenario where, if female pediatric patients were 20% more radiosensitive (lower TD50 value), they could be up to twice as likely to experience side-effects of brainstem necrosis and cochlea tinnitus compared to males, highlighting the need for considering the sex in NTCP models. Based on our sensitivity analyses, age and sex of a pediatric patient could significantly affect the resultant NTCP from cranial radiotherapy, especially at higher α/β values.

Normal tissue tolerance amongst paediatric brain tumour patients- current evidence in proton radiotherapy

BACKGROUND

Proton radiotherapy (PT) is used increasingly for paediatric brain cancer patients. However, as demonstrated here, the knowledge on normal tissue dose constraints, to minimize side-effects, for this cohort is limited.

METHODS

A search strategy was systematically conducted on MEDLINE® database. 65 papers were evaluated ranging from 2013 to 2021.

RESULTS

Large variations in normal tissue tolerance and toxicity reporting across PT studies makes estimation of normal tissue dose constraints difficult, with the potential for significant late effects to go unmeasured. Mean dose delivered to the pituitary gland varies from 20 to 30 Gy across literature. Similarly, the hypothalamic dose delivery ranges from 20 to 54.6 Gy for paediatric patients.

CONCLUSION

There is a significant lack of radiobiological data for paediatric brain cancer patients undergoing proton therapy, often using data from x-ray radiotherapy and adult populations. The way forward is through standardisation of reporting in order to validate relevant dose constraints.

Generalized approach for radiotherapy treatment planning by optimizing projected health outcome: preliminary results for prostate radiotherapy patients

Research in cancer care increasingly focuses on survivorship issues, e.g. managing disease- and treatment-related morbidity and mortality occurring during and after treatment. This necessitates innovative approaches that consider treatment side effects in addition to tumor cure. Current treatment-planning methods rely on constrained iterative optimization of dose distributions as a surrogate for health outcomes. The goal of this study was to develop a generally applicable method to directly optimize projected health outcomes. We developed an outcome-based objective function to guide selection of the number, angle, and relative fluence weight of photon and proton radiotherapy beams in a sample of ten prostate-cancer patients by optimizing the projected health outcome. We tested whether outcome-optimized radiotherapy (OORT) improved the projected longitudinal outcome compared to dose-optimized radiotherapy (DORT) first for a statistically significant majority of patients, then for each individual patient. We assessed whether the results were influenced by the selection of treatment modality, late-risk model, or host factors. The results of this study revealed that OORT was superior to DORT. Namely, OORT maintained or improved the projected health outcome of photon- and proton-therapy treatment plans for all ten patients compared to DORT. Furthermore, the results were qualitatively similar across three treatment modalities, six late-risk models, and 10 patients. The major finding of this work was that it is feasible to directly optimize the longitudinal (i.e. long- and short-term) health outcomes associated with the total (i.e. therapeutic and stray) absorbed dose in all of the tissues (i.e. healthy and diseased) in individual patients. This approach enables consideration of arbitrary treatment factors, host factors, health endpoints, and times of relevance to cancer survivorship. It also provides a simpler, more direct approach to realizing the full beneficial potential of cancer radiotherapy.

Justification and optimization of radiation exposures: a new framework to aggregate arbitrary detriments and benefits

Myriad radiation effects, including benefits and detriments, complicate justifying and optimizing radiation exposures. The purpose of this study was to develop a comprehensive conceptual framework and corresponding quantitative methods to aggregate the detriments and benefits of radiation exposures to individuals, groups, and populations. In this study, concepts from the ICRP for low dose were integrated with clinical techniques focused on high dose to develop a comprehensive figure of merit (FOM) that takes into account arbitrary host- and exposure-related factors, endpoints, and time points. The study built on existing methods with three new capabilities: application to individuals, groups, and populations; extension to arbitrary numbers and types of endpoints; and inclusion of limitation, where relevant. The FOM was applied to three illustrative exposure situations: emergency response, diagnostic imaging, and cancer radiotherapy, to evaluate its utility in diverse settings. The example application to radiation protection revealed the FOM's utility in optimizing the benefits and risks to a population while keeping individual exposures below applicable regulatory limits. Examples in diagnostic imaging and cancer radiotherapy demonstrated the FOM's utility for guiding population- and patient-specific decisions in medical applications. The major finding of this work is that it is possible to quantitatively combine the benefits and detriments of any radiation exposure situation involving an individual or population to perform cost-effectiveness analyses using the ICRP key principles of radiation protection. This FOM fills a chronic gap in the application of radiation-protection theory, i.e., limitations of generalized frameworks to algorithmically justify and optimize radiation exposures. This new framework potentially enhances objective optimization and justification, especially in complex exposure situations.

Individualised selection of left-sided breast cancer patients for proton therapy based on cost-effectiveness

Introduction

The significantly greater cost of proton therapy compared with X‐ray therapy is frequently justified by the expected reduction in normal tissue toxicity. This is often true for indications such as paediatric and skull base cancers. However, the benefit is less clear for other more common indications such as breast cancer, and it is possible that the degree of benefit may vary widely between these patients. The aim of this work was to demonstrate a method of individualised selection of left‐sided breast cancer patients for proton therapy based on cost‐effectiveness of treatment.

Methods

16 left‐sided breast cancer patients had a treatment plan generated for the delivery of intensity‐modulated proton therapy (IMPT) and of intensity‐modulated photon therapy (IMRT) with the deep inspiration breath‐hold (DIBH) technique. The resulting dosimetric data was used to predict probabilities of tumour control and toxicities for each patient. These probabilities were used in a Markov model to predict costs and the number of quality‐adjusted life years expected as a result of each of the two treatments.

Results

IMPT was not cost‐effective for the majority of patients but was cost‐effective where there was a greater risk reduction of second malignancies with IMPT.

Conclusion

The Markov model predicted that IMPT with DIBH was only cost‐effective for selected left‐sided breast cancer patients where IMRT resulted in a significantly greater dose to normal tissue. The presented model may serve as a means of evaluating the cost‐effectiveness of IMPT on an individual patient basis.

Patient selection for proton therapy: a radiobiological fuzzy Markov model incorporating robust plan analysis

While proton therapy can offer increased sparing of healthy tissue compared with X-ray therapy, it can be difficult to predict whether a benefit can be expected for an individual patient. Predictive modelling may aid in this respect. However, the predictions of these models can be affected by uncertainties in radiobiological model parameters and in planned dose. The aim of this work is to present a Markov model that incorporates these uncertainties to compare clinical outcomes for individualised proton and X-ray therapy treatments. A time-inhomogeneous fuzzy Markov model was developed which estimates the response of a patient to a given treatment plan in terms of quality adjusted life years. These are calculated using the dose-dependent probabilities of tumour control and toxicities as transition probabilities in the model. Dose-volume data representing multiple isotropic patient set-up uncertainties and range uncertainties (for proton therapy) are included to model dose delivery uncertainties. The model was retrospectively applied to an example patient as a demonstration. When uncertainty in the radiobiological model parameter was considered, the model predicted that proton therapy would result in an improved clinical outcome compared with X-ray therapy. However, when dose delivery uncertainty was included, there was no difference between the two treatments. By incorporating uncertainties in the predictive modelling calculations, the fuzzy Markov concept was found to be well suited to providing a more holistic comparison of individualised treatment outcomes for proton and X-ray therapy. This may prove to be useful in model-based patient selection strategies.

Proton radiotherapy and treatment delay in head and neck squamous cell carcinoma

OBJECTIVE

For patients with head and neck squamous cell carcinoma (HNSCC), delays in the initiation of radiotherapy (RT) have been closely associated with worse outcomes. We sought to investigate whether RT modality (proton vs. photon) is associated with differences in the time to initiation of RT.

METHODS

The National Cancer Database was queried for patients diagnosed with nonmetastatic HNSCC between 2004 and 2015 who received either proton or photon RT as part of their initial treatment. Wilcoxon rank-sum and chi-square tests were used to compare continuous and categorical variables, respectively. Multivariable logistic regression was used to determine the association between use of proton RT and delayed RT initiation.

RESULTS

A total of 175,088 patients with HNSCC receiving either photon or proton RT were identified. Patients receiving proton RT were more likely to be white, reside in higher income areas, and have private insurance. Proton RT was associated with delayed RT initiation compared to photon RT (median 59 days vs. 45, P < 0.001). Receipt of proton therapy was independently associated with RT initiation beyond 6 weeks after diagnosis (adjusted OR [aOR, definitive RT] = 1.69; 95% confidence interval [CI] 1.26-2.30) or surgery (aOR [adjuvant RT] = 4.08; 95% CI 2.64-6.62). In the context of adjuvant proton RT, increases in treatment delay were associated with worse overall survival (weeks, adjusted hazard ratio = 1.099, 95% CI 1.011-1.194).

CONCLUSION

Use of proton therapy is associated with delayed RT in both the definitive and adjuvant settings for patients with HNSCC and could be associated with poorer outcomes.

LEVEL OF EVIDENCE

2b Laryngoscope, 122:0000-0000, 2019 Laryngoscope, 130:E598-E604, 2020.

Intensity-modulated proton therapy decreases dose to organs at risk in low-grade glioma patients: results of a multicentric in silico ROCOCO trial

BACKGROUND AND PURPOSE

Patients with low-grade glioma (LGG) have a prolonged survival expectancy due to better discriminative tumor classification and multimodal treatment. Consequently, long-term treatment toxicity gains importance. Contemporary radiotherapy techniques such as intensity-modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT), tomotherapy (TOMO) and intensity-modulated proton therapy (IMPT) enable high-dose irradiation of the target but they differ regarding delivered dose to organs at risk (OARs). The aim of this comparative in silico study was to determine these dosimetric differences in delivered doses.

MATERIAL AND METHODS

Imaging datasets of 25 LGG patients having undergone postoperative radiotherapy were included. For each of these patients, in silico treatment plans to a total dose of 50.4 Gy to the target volume were generated for the four treatment modalities investigated (i.e., IMRT, VMAT, TOMO, IMPT). Resulting treatment plans were analyzed regarding dose to target and surrounding OARs comparing IMRT, TOMO and IMPT to VMAT.

RESULTS

In total, 100 treatment plans (four per patient) were analyzed. Compared to VMAT, the IMPT mean dose (D_mean) for nine out of 10 (90%) OARs was statistically significantly (p < .02) reduced, for TOMO this was true in 3/10 (30%) patients and for 1/10 (10%) patients for IMRT. IMPT was the prime modality reducing dose to the OARs followed by TOMO.

DISCUSSION

The low dose volume to the majority of OARs was significantly reduced when using IMPT compared to VMAT. Whether this will lead to a significant reduction in neurocognitive decline and improved quality of life is to be determined in carefully designed future clinical trials.

Physical parameter optimization scheme for radiobiological studies of charged particle therapy

We have developed an easy-to-implement method to optimize the spatial distribution of a desired physical quantity for charged particle therapy. The basic methodology requires finding the optimal solutions for the weights of the constituent particle beams that together form the desired spatial distribution of the specified physical quantity, e.g., dose or dose-averaged linear energy transfer (LETd), within the target region. We selected proton, 4He ion, and 12C ion beams to demonstrate the feasibility and flexibility of our method. The pristine dose Bragg curves in water for all ion beams and the LETd for proton beams were generated from Geant4 Monte Carlo simulations. The optimization algorithms were implemented using the Python programming language. High-accuracy optimization results of the spatial distribution of the desired physical quantity were then obtained for different cases. The relative difference between the real value and the expected value of a given quantity was approximately within ±1.0% in the whole target region. The optimization examples include a flat dose spread-out Bragg peak (SOBP) for the three selected ions, an upslope dose SOBP for protons, and a downslope dose SOBP for protons. The relative difference was approximately within ±2.0% for the case with a flat LETd (target value = 4 keV/µm) distribution for protons. These one-dimensional optimization algorithms can be extended to two or three dimensions if the corresponding physical data are available. In addition, this physical quantity optimization strategy can be conveniently extended to encompass biological dose optimization if appropriate biophysical models are invoked.

Mathematical Modelling for Patient Selection in Proton Therapy

Proton beam therapy (PBT) is still relatively new in cancer treatment and the clinical evidence base is relatively sparse. Mathematical modelling offers assistance when selecting patients for PBT and predicting the demand for service. Discrete event simulation, normal tissue complication probability, quality-adjusted life-years and Markov Chain models are all mathematical and statistical modelling techniques currently used but none is dominant. As new evidence and outcome data become available from PBT, comprehensive models will emerge that are less dependent on the specific technologies of radiotherapy planning and delivery.