Immunotherapy, specifically the introduction of immune checkpoint inhibitors, has transformed the treatment of cancer, enabling long-term tumour control even in individuals with advanced-stage ...disease. Unfortunately, only a small subset of patients show a response to currently available immunotherapies. Despite a growing consensus that combining immune checkpoint inhibitors with radiotherapy can increase response rates, this approach might be limited by the development of persistent radiation-induced immunosuppression. The ultimate goal of combining immunotherapy with radiotherapy is to induce a shift from an ineffective, pre-existing immune response to a long-lasting, therapy-induced immune response at all sites of disease. To achieve this goal and enable the adaptation and monitoring of individualized treatment approaches, assessment of the dynamic changes in the immune system at the patient level is essential. In this Review, we summarize the available clinical data, including forthcoming methods to assess the immune response to radiotherapy at the patient level, ranging from serum biomarkers to imaging techniques that enable investigation of immune cell dynamics in patients. Furthermore, we discuss modelling approaches that have been developed to predict the interaction of immunotherapy with radiotherapy, and highlight how they could be combined with biomarkers of antitumour immunity to optimize radiotherapy regimens and maximize their synergy with immunotherapy.
The goal of this work was to develop a mathematical model to predict Kaplan-Meier survival curves for chemotherapy combined with radiation in Non-Small Cell Lung Cancer patients for use in clinical ...trial design. The Gompertz model was used to describe tumor growth, radiation effect was simulated by the linear-quadratic model with an α/β-ratio of 10, and chemotherapy effect was based on the log-cell kill model. To account for repopulation during treatment, we considered two independent methods: 1) kickoff-repopulation using exponential growth with a decreased volume doubling time, or 2) Gompertz-repopulation using the gradually accelerating growth rate with tumor shrinkage. The input parameters were independently estimated by fitting to the SEER database for untreated tumors, RTOG-8808 for radiation only, and RTOG-9410 for sequential chemo-radiation. Applying the model, the benefit from concurrent chemo-radiation comparing to sequential for stage III patients was predicted to be a 6.6% and 6.2% improvement in overall survival for 3 and 5-years respectively, comparing well to the 5.3% and 4.5% observed in RTOG-9410. In summary, a mathematical model was developed to model tumor growth over extended periods of time, and can be used for the optimization of combined chemo-radiation scheduling and sequencing.
To calculate the linear energy transfer (LET) distributions in patients undergoing proton therapy. These distributions can be used to identify areas of elevated or diminished biological effect. The ...location of such areas might be influenced in intensity-modulated proton therapy (IMPT) optimization.
Because Monte Carlo studies to investigate the LET distribution in patients have not been undertaken so far, the code is first validated with simulations in water. The code was used in five patients, for each of them three planning and delivery techniques were simulated: passive scattering, three-dimensional modulation IMPT (3D-IMPT), and distal edge tracking IMPT (DET-IMPT).
The inclusion of secondary particles led to significant differences compared with analytical techniques. In addition, passive scattering and 3D-IMPT led to largely comparable LET distributions, whereas the DET-IMPT plans resulted in considerably increased LET values in normal tissues and critical structures. In the brainstem, dose-averaged LET values exceeding 5 keV/μm were observed in areas with significant dose (>70% of prescribed dose). In noncritical normal tissues, even values >8 keV/μm occurred.
This work demonstrates that active scanning offers the possibility of influencing the distribution of dose-averaged LET (i.e., the biological effect) without significantly altering the distribution of physical dose. On the basis of this finding, we propose a method to alter deliberately the LET distribution of a treatment plan in such a manner that the LET is maximized within certain target areas and minimized in normal tissues, while maintaining the prescribed target dose and dose constraints for organs at risk.
To assess the impact of approximations in current analytical dose calculation methods (ADCs) on tumor control probability (TCP) in proton therapy.
Dose distributions planned with ADC were compared ...with delivered dose distributions as determined by Monte Carlo simulations. A total of 50 patients were investigated in this analysis with 10 patients per site for 5 treatment sites (head and neck, lung, breast, prostate, liver). Differences were evaluated using dosimetric indices based on a dose-volume histogram analysis, a γ-index analysis, and estimations of TCP.
We found that ADC overestimated the target doses on average by 1% to 2% for all patients considered. The mean dose, D95, D50, and D02 (the dose value covering 95%, 50% and 2% of the target volume, respectively) were predicted within 5% of the delivered dose. The γ-index passing rate for target volumes was above 96% for a 3%/3 mm criterion. Differences in TCP were up to 2%, 2.5%, 6%, 6.5%, and 11% for liver and breast, prostate, head and neck, and lung patients, respectively. Differences in normal tissue complication probabilities for bladder and anterior rectum of prostate patients were less than 3%.
Our results indicate that current dose calculation algorithms lead to underdosage of the target by as much as 5%, resulting in differences in TCP of up to 11%. To ensure full target coverage, advanced dose calculation methods like Monte Carlo simulations may be necessary in proton therapy. Monte Carlo simulations may also be required to avoid biases resulting from systematic discrepancies in calculated dose distributions for clinical trials comparing proton therapy with conventional radiation therapy.
To quantify the impact of respiratory motion on the treatment of lung tumors with spot scanning proton therapy.
Four-dimensional Monte Carlo simulations were used to assess the interplay effect, ...which results from relative motion of the tumor and the proton beam, on the dose distribution in the patient. Ten patients with varying tumor sizes (2.6-82.3 cc) and motion amplitudes (3-30 mm) were included in the study. We investigated the impact of the spot size, which varies between proton facilities, and studied single fractions and conventionally fractionated treatments. The following metrics were used in the analysis: minimum/maximum/mean dose, target dose homogeneity, and 2-year local control rate (2y-LC).
Respiratory motion reduces the target dose homogeneity, with the largest effects observed for the highest motion amplitudes. Smaller spot sizes (σ ≈ 3 mm) are inherently more sensitive to motion, decreasing target dose homogeneity on average by a factor 2.8 compared with a larger spot size (σ ≈ 13 mm). Using a smaller spot size to treat a tumor with 30-mm motion amplitude reduces the minimum dose to 44.7% of the prescribed dose, decreasing modeled 2y-LC from 87.0% to 2.7%, assuming a single fraction. Conventional fractionation partly mitigates this reduction, yielding a 2y-LC of 71.6%. For the large spot size, conventional fractionation increases target dose homogeneity and prevents a deterioration of 2y-LC for all patients. No correlation with tumor volume is observed. The effect on the normal lung dose distribution is minimal: observed changes in mean lung dose and lung V20 are <0.6 Gy(RBE) and <1.7%, respectively.
For the patients in this study, 2y-LC could be preserved in the presence of interplay using a large spot size and conventional fractionation. For treatments using smaller spot sizes and/or in the delivery of single fractions, interplay effects can lead to significant deterioration of the dose distribution and lower 2y-LC.
To investigate the feasibility and potential clinical benefit of linear energy transfer (LET) guided plan optimization in intensity modulated proton therapy (IMPT).
A multicriteria optimization (MCO) ...module was used to generate a series of Pareto-optimal IMPT base plans (BPs), corresponding to defined objectives, for 5 patients with head-and-neck cancer and 2 with pancreatic cancer. A Monte Carlo platform was used to calculate dose and LET distributions for each BP. A custom-designed MCO navigation module allowed the user to interpolate between BPs to produce deliverable Pareto-optimal solutions. Differences among the BPs were evaluated for each patient, based on dose-volume and LET-volume histograms and 3-dimensional distributions. An LET-based relative biological effectiveness (RBE) model was used to evaluate the potential clinical benefit when navigating the space of Pareto-optimal BPs.
The mean LET values for the target varied up to 30% among the BPs for the head-and-neck patients and up to 14% for the pancreatic cancer patients. Variations were more prominent in organs at risk (OARs), where mean LET values differed by a factor of up to 2 among the BPs for the same patient. An inverse relation between dose and LET distributions for the OARs was typically observed. Accounting for LET-dependent variable RBE values, a potential improvement on RBE-weighted dose of up to 40%, averaged over several structures under study, was noticed during MCO navigation.
We present a novel strategy for optimizing proton therapy to maximize dose-averaged LET in tumor targets while simultaneously minimizing dose-averaged LET in normal tissue structures. MCO BPs show substantial LET variations, leading to potentially significant differences in RBE-weighted doses. Pareto-surface navigation, using both dose and LET distributions for guidance, provides the means for evaluating a large variety of deliverable plans and aids in identifying the clinically optimal solution.
Roadmap: proton therapy physics and biology Paganetti, Harald; Beltran, Chris; Both, Stefan ...
Physics in medicine & biology,
02/2021, Letnik:
66, Številka:
5
Journal Article
Recenzirano
Odprti dostop
The treatment of cancer with proton radiation therapy was first suggested in 1946 followed by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated with proton ...beams worldwide and the number of operating proton therapy (PT) facilities will soon reach one hundred. PT has long moved from research institutions into hospital-based facilities that are increasingly being utilized with workflows similar to conventional radiation therapy. While PT has become mainstream and has established itself as a treatment option for many cancers, it is still an area of active research for various reasons: the advanced dose shaping capabilities of PT cause susceptibility to uncertainties, the high degrees of freedom in dose delivery offer room for further improvements, the limited experience and understanding of optimizing pencil beam scanning, and the biological effect difference compared to photon radiation. In addition to these challenges and opportunities currently being investigated, there is an economic aspect because PT treatments are, on average, still more expensive compared to conventional photon based treatment options. This roadmap highlights the current state and future direction in PT categorized into four different themes, 'improving efficiency', 'improving planning and delivery', 'improving imaging', and 'improving patient selection'.
To quantify the accuracy of a clinical proton treatment planning system (TPS) as well as Monte Carlo (MC)-based dose calculation through measurements and to assess the clinical impact in a cohort of ...patients with tumors located in the lung.
A lung phantom and ion chamber array were used to measure the dose to a plane through a tumor embedded in the lung, and to determine the distal fall-off of the proton beam. Results were compared with TPS and MC calculations. Dose distributions in 19 patients (54 fields total) were simulated using MC and compared to the TPS algorithm.
MC increased dose calculation accuracy in lung tissue compared with the TPS and reproduced dose measurements in the target to within ±2%. The average difference between measured and predicted dose in a plane through the center of the target was 5.6% for the TPS and 1.6% for MC. MC recalculations in patients showed a mean dose to the clinical target volume on average 3.4% lower than the TPS, exceeding 5% for small fields. For large tumors, MC also predicted consistently higher V5 and V10 to the normal lung, because of a wider lateral penumbra, which was also observed experimentally. Critical structures located distal to the target could show large deviations, although this effect was highly patient specific. Range measurements showed that MC can reduce range uncertainty by a factor of ~2: the average (maximum) difference to the measured range was 3.9 mm (7.5 mm) for MC and 7 mm (17 mm) for the TPS in lung tissue.
Integration of Monte Carlo dose calculation techniques into the clinic would improve treatment quality in proton therapy for lung cancer by avoiding systematic overestimation of target dose and underestimation of dose to normal lung. In addition, the ability to confidently reduce range margins would benefit all patients by potentially lowering toxicity.
Abstract
Background
We investigated differences in radiation-induced grade 3+ lymphopenia (G3+L), defined as an absolute lymphocyte count (ALC) nadir of <500 cells/µL, after proton therapy (PT) or ...X-ray (photon) therapy (XRT) for patients with glioblastoma (GBM).
Methods
Patients enrolled in a randomized phase II trial received PT (n = 28) or XRT (n = 56) concomitantly with temozolomide. ALC was measured before, weekly during, and within 1 month after radiotherapy. Whole-brain mean dose (WBMD) and brain dose-volume indices were extracted from planned dose distributions. Univariate and multivariate logistic regression analyses were used to identify independent predictive variables. The resulting model was evaluated using receiver operating characteristic (ROC) curve analysis.
Results
Rates of G3+L were lower in men (7/47 15%) versus women (19/37 51%) (P < 0.001), and for PT (4/28 14%) versus XRT (22/56 39%) (P = 0.024). G3+L was significantly associated with baseline ALC, WBMD, and brain volumes receiving 5‒40 Gy(relative biological effectiveness RBE) or higher (ie, V5 through V40). Stepwise multivariate logistic regression analysis identified being female (odds ratio OR 6.2, 95% confidence interval CI: 1.95‒22.4, P = 0.003), baseline ALC (OR 0.18, 95% CI: 0.05‒0.51, P = 0.003), and whole-brain V20 (OR 1.07, 95% CI: 1.03‒1.13, P = 0.002) as the strongest predictors. ROC analysis yielded an area under the curve of 0.86 (95% CI: 0.79–0.94) for the final G3+L prediction model.
Conclusions
Sex, baseline ALC, and whole-brain V20 were the strongest predictors of G3+L for patients with GBM treated with radiation and temozolomide. PT reduced brain volumes receiving low and intermediate doses and, consequently, reduced G3+L.
Lymphocytes play an important role in antitumor immunity; however, they are also especially vulnerable to depletion during chemoradiation therapy (CRT). The purpose of this study was to compare the ...incidence of grade 4 lymphopenia (G4L) between proton beam therapy (PBT) and intensity modulated photon radiation therapy (IMRT) in patients with esophageal cancer treated with CRT in a completed randomized trial and to ascertain patient heterogeneity to G4L risk based on treatment and established prognostic factors.
Between April 2012 and March 2019, a single-institution, open-label, nonblinded, phase 2 randomized trial (NCT01512589) was conducted at the University of Texas MD Anderson Cancer Center. Patients were randomly assigned to IMRT or PBT, either definitively or preoperatively. This secondary analysis of the randomized trial was G4L during concurrent CRT according to Common Terminology Criteria for Adverse Events version 5.0.
Among 105 patients evaluable for analysis, 44 patients (42%) experienced G4L at a median of 28 days after the start date of concurrent CRT. Induction chemotherapy (P = .003), baseline absolute lymphocyte count (P < .001), radiation therapy modality (P = .002), and planning treatment volume (P = .033) were found to be significantly associated with G4L. Multivariate classification analysis partitioned patients into 5 subgroups for whom the incidence of G4L was observed in 0%, 14%, 35%, 70%, and 100% of patients. The benefit of PBT over IMRT was most pronounced in patients with an intermediate baseline absolute lymphocyte count and large planning treatment volume (P = .011).
This is the first prospective evidence that limiting dose scatter by PBT significantly reduced the incidence of G4L, especially in the intermediate-risk patients. The implication of this immune-sparing effect of PBT, especially in the context of standard adjuvant immunotherapy, needs further examination in the current phase 3 randomized trials.
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