Oscillations in a Spatial Oncolytic Virus Model.

Virotherapy treatment is a new and promising target therapy that selectively attacks cancer cells without harming normal cells. Mathematical models of oncolytic viruses have shown predator-prey like oscillatory patterns as result of an underlying Hopf bifurcation. In a spatial context, these oscillations can lead to different spatio-temporal phenomena such as hollow-ring patterns, target patterns, and dispersed patterns. In this paper we continue the systematic analysis of these spatial oscillations and discuss their relevance in the clinical context. We consider a bifurcation analysis of a spatially explicit reaction-diffusion model to find the above mentioned spatio-temporal virus infection patterns. The desired pattern for tumor eradication is the hollow ring pattern and we find exact conditions for its occurrence. Moreover, we derive the minimal speed of travelling invasion waves for the cancer and for the oncolytic virus. Our numerical simulations in 2-D reveal complex spatial interactions of the virus infection and a new phenomenon of a periodic peak splitting. An effect that we cannot explain with our current methods.

Theoretical evaluation of the impact of diverse treatment conditions by calculation of the tumor control probability (TCP) of simulated cervical cancer Hyperthermia-Radiotherapy (HT-RT) treatments in-silico.

INTRODUCTION: Hyperthermia (HT) induces various cellular biological processes, such as repair impairment and direct HT cell killing. In this context, in-silico biophysical models that translate deviations in the treatment conditions into clinical outcome variations may be used to study the extent of such processes and their influence on combined hyperthermia plus radiotherapy (HT + RT) treatments under varying conditions. METHODS: An extended linear-quadratic model calibrated for SiHa and HeLa cell lines (cervical cancer) was used to theoretically study the impact of varying HT treatment conditions on radiosensitization and direct HT cell killing effect. Simulated patients were generated to compute the Tumor Control Probability (TCP) under different HT conditions (number of HT sessions, temperature and time interval), which were randomly selected within margins based on reported patient data. RESULTS: Under the studied conditions, model-based simulations suggested a treatment improvement with a total CEM43 thermal dose of approximately 10 min. Additionally, for a given thermal dose, TCP increased with the number of HT sessions. Furthermore, in the simulations, we showed that the TCP dependence on the temperature/time interval is more correlated with the mean value than with the minimum/maximum value and that comparing the treatment outcome with the mean temperature can be an excellent strategy for studying the time interval effect. CONCLUSION: The use of thermoradiobiological models allows us to theoretically study the impact of varying thermal conditions on HT + RT treatment outcomes. This approach can be used to optimize HT treatments, design clinical trials, and interpret patient data.

The risk of radiation-induced neurocognitive impairment and the impact of sparing the hippocampus during pediatric proton cranial irradiation.

BACKGROUND AND PURPOSE: Hippocampus is a central component for neurocognitive function and memory. We investigated the predicted risk of neurocognitive impairment of craniospinal irradiation (CSI) and the deliverability and effects of hippocampal sparing. The risk estimates were derived from published NTCP models. Specifically, we leveraged the estimated benefit of reduced neurocognitive impairment with the risk of reduced tumor control. MATERIAL AND METHODS: For this dose planning study, a total of 504 hippocampal sparing intensity modulated proton therapy (HS-IMPT) plans were generated for 24 pediatric patients whom had previously received CSI. Plans were evaluated with respect to target coverage and homogeneity index to target volumes, maximum and mean dose to OARs. Paired t-tests were used to compare hippocampal mean doses and normal tissue complication probability estimates. RESULTS: The median mean dose to the hippocampus could be reduced from 31.3 GyRBE to 7.3 GyRBE (p < .001), though 20% of these plans were not considered clinically acceptable as they failed one or more acceptance criterion. Reducing the median mean hippocampus dose to 10.6 GyRBE was possible with all plans considered as clinically acceptable treatment plans. By sparing the hippocampus to the lowest dose level, the risk estimation of neurocognitive impairment could be reduced from 89.6%, 62.1% and 51.1% to 41.0% (p < .001), 20.1% (p < .001) and 29.9% (p < .001) for task efficiency, organization and memory, respectively. Estimated tumor control probability was not adversely affected by HS-IMPT, ranging from 78.5 to 80.5% for all plans. CONCLUSIONS: We present estimates of potential clinical benefit in terms of neurocognitive impairment and demonstrate the possibility of considerably reducing neurocognitive adverse effects, minimally compromising target coverage locally using HS-IMPT.

The impact of random microenvironmental fluctuations on tumor control probability.

The tumor control probability (TCP) is a metric used to calculate the probability of controlling or eradicating tumors through radiotherapy. Cancer cells vary in their response to radiation, and although many factors are involved, the tumor microenvironment is a crucial one that determines radiation efficacy. The tumor microenvironment plays a significant role in cancer initiation and propagation, as well as in treatment outcome. We have developed stochastic formulations to study the impact of arbitrary microenvironmental fluctuations on TCP and extinction probability (EP), which is defined as the probability of cancer cells removal in the absence of treatment. Since the derivation of analytical solutions are not possible for complicated cases, we employ a modified Gillespie algorithm to analyze TCP and EP, considering the random variations in cellular proliferation and death rates. Our results show that increasing the standard deviation in kinetic rates initially enhances the probability of tumor eradication. However, if the EP does not reach a probability of 1, the increase in the standard deviation subsequently has a negative impact on probability of cancer cells removal, decreasing the EP over time. The greatest effect on EP has been observed when both birth and death rates are being randomly modified and are anticorrelated. In addition, similar results are observed for TCP, where radiotherapy is included, indicating that increasing the standard deviation in kinetic rates at first enhances the probability of tumor eradication. But, it has a negative impact on treatment effectiveness if the TCP does not reach a probability of 1.

Development of generalized time-dependent TCP model and the investigation of the effect of repopulation and weekend breaks in fractionated external beam therapy.

We developed a tumor control probability (TCP) model that incorporates variable time intervals between fractions and a kick-off time (Tk) for radiation-induced accelerated tumor proliferation. The resulting Lee-Rosen model, TCPLR, was used to compute TCPs for treatment courses with and without weekend treatment for tumors with different proliferation rates - slow (prostate), moderate (breast), and rapid (head and neck). TCPs were computed using ideal uniform dose distributions and actual patient plans. The doses for the uniform plans were the mean doses for the prostate and breast cases and the minimum tumor dose for the head and neck case. The TCPLR model predictions agreed with expectations that TCP increases with increasing Tk in all cases. For standard fractionation, as Tk increased from 0 to 4 weeks, TCP increased for the patient distributions by 74.7% for the head and neck cancer, by 6.2% for the breast cancer, and by 2.4% for the prostate cancers. For the uniform dose distributions, the increases were 79.2%, 5.7%, and 2.3%, respectively. TCP increased as the number of weekend breaks decreased. The effect of weekend breaks decreased as the tumor proliferation rate decreased. For the head and neck tumor, notable decreases in TCP of 6.0% (uniform dose distribution) and 6.8% (actual plan dose distribution) were observed with Friday starts compared to Monday starts for the standard 5 fx/wk schedule (Tk = 4 wk). The 7 fx/wk schedule produced increases in TCP of 17.0% and 20.5% for the uniform and patient dose distributions, respectively, compared to the standard schedule. For the breast cancer, starting the 5 fx/wk schedule on Friday decreased the TCP by 0.2% (Tk = 4 wk) compared to a Monday start. The 7 fx/wk schedule produced increases of 0.3% and 0.4% in TCP compared to the standard schedule for the uniform and patient dose distributions, respectively (Tk = 4 wk). For the prostate cancer, the change in TCP for 5 fx/wk schedules starting on different days was 0.1%. The 7 fx/wk schedule increased TCP by 0.8% compared to the standard schedule (Tk = 4 wk). TCP values for the uniform dose distributions for the standard schedule (Tk = 4 wk) agreed with the TCP values for the actual dose distributions within 4.5% for the head and neck tumor and within 0.2% for the breast and prostate tumors. This good agreement suggests that the doses chosen for the uniform dose distributions were good approximations to the clinical doses. The results for head and neck tumors support, in part, the current practice of hyperfractionated/accelerated radiotherapy. They also suggest that shortening the overall treatment time for conventional fractions by eliminating weekend breaks might be beneficial. The predicted effect on TCP of the various schedules studied was insignificant for prostate and breast tumors, suggesting that a weekend treatment might not be necessary for patients starting radiotherapy on a Friday. There is significant uncertainty in the values of the model parameters chosen for these calculations, and no consideration was given to the potential effects of these various schedules on normal tissues.

Radiobiological evaluation considering setup error on single-isocenter irradiation in stereotactic radiosurgery.

PURPOSE: We calculated the dosimetric indices and estimated the tumor control probability (TCP) considering six degree-of-freedom (6DoF) patient setup errors in stereotactic radiosurgery (SRS) using a single-isocenter technique. METHODS: We used simulated spherical gross tumor volumes (GTVs) with diameters of 1.0 cm (GTV 1), 2.0 cm (GTV 2), and 3.0 cm (GTV 3), and the distance (d) between the target center and isocenter was set to 0, 5, and 10 cm. We created the dose distribution by convolving the blur component to uniform dose distribution. The prescription dose was 20 Gy and the dose distribution was adjusted so that D95 (%) of each GTV was covered by 100% of the prescribed dose. The GTV was simultaneously rotated within 0°-1.0° (δR) around the x-, y-, and z-axes and then translated within 0-1.0 mm (δT) in the x-, y-, and z-axis directions. D95, conformity index (CI), and conformation number (CN) were evaluated by varying the distance from the isocenter. The TCP was estimated by translating the calculated dose distribution into a biological response. In addition, we derived the x-y-z coordinates with the smallest TCP reduction rate that minimize the sum of squares of the residuals as the optimal isocenter coordinates using the relationship between 6DoF setup error, distance from isocenter, and GTV size. RESULTS: D95, CI, and CN were decreased with increasing isocenter distance, decreasing GTV size, and increasing setup error. TCP of GTVs without 6DoF setup error was estimated to be 77.0%. TCP were 25.8% (GTV 1), 35.0% (GTV 2), and 53.0% (GTV 3) with (d, δT, δR) = (10 cm, 1.0 mm, 1.0°). The TCP was 52.3% (GTV 1), 54.9% (GTV 2), and 66.1% (GTV 3) with (d, δT, δR) = (10 cm, 1.0 mm, 1.0°) at the optimal isocenter position. CONCLUSION: The TCP in SRS for multiple brain metastases with a single-isocenter technique may decrease with increasing isocenter distance and decreasing GTV size when the 6DoF setup errors are exceeded (1.0 mm, 1.0°). Additionally, it might be possible to better maintain TCP for GTVs with 6DoF setup errors by using the optimal isocenter position.

Effect of hypofractionation on the incidental axilla dose during tangential field radiotherapy in breast cancer.

OBJECTIVE: Tangential field irradiation in breast cancer potentially treats residual tumor cells in the axilla after sentinel lymph node biopsy (SLNB). In recent years, hypofractionated radiotherapy has gained importance and currently represents the recommended standard in adjuvant breast cancer treatment for many patients. So far, the impact of hypofractionation on the effect of incidental lymph node irradiation has not be addressed. MATERIALS AND METHODS: Biological effective dose (BED) and tumor control probability (TCP) were estimated for four different hypofractionated radiation schemes (42.50 Gy in 16 fractions [Fx]; 40.05 Gy in 15 Fx; 27 Gy in 5 Fx; and 26 in 5 Fx) and compared to conventional fractionation (50 Gy in 25 Fx). For calculation of BED and TCP, a previously published radiobiological model with an α/ß ratio of 4 Gy was used. The theoretical BED and TCP for incidental irradiation between 0 and 100% of the prescribed dose were evaluated. Subsequently, we assessed BED and TCP in 431 axillary lymph node metastases. RESULTS: The extent of incidental lymph node irradiation and the fractionation scheme have a direct impact on BED and TCP. The estimated mean TCP in the axillary nodes ranged from 1.5 ± 6.4% to 57.5 ± 22.9%, depending on the patient's anatomy and the fractionation scheme. Hypofractionation led to a significant reduction of mean TCP of lymph node metastases for all schedules. CONCLUSION: Our data indicate that hypofractionation might affect the effectiveness of incidental radiotherapy in the axilla. This is particularly relevant for patients with positive sentinel lymph nodes who receive SLNB only.

Associating dose-volume characteristics with theoretical radiobiological metrics for rapid Gamma Knife stereotactic radiosurgery plan evaluation.

PURPOSE: To examine general dose-volume characteristics in Gamma Knife (GK) plans which may be associated with higher tumor control probability (TCP) and equivalent uniform dose (EUD) using characteristic curve sets. METHODS: Two sets of dose-volume histograms (DVHs) were exported alongside an analytical purpose-generated DVH: (a) single-shot large collimator (8 or 16 mm) emulated with multiple shots of 4 mm collimator. (b) shot-within-shot (SWS) technique with isodose lines (IDLs) of 40-75%. TCP, average dose, EUD in single-fraction (EUDT ) and 2 Gy fractionated regimens (EUDR ) were examined for trends with cumulative DVH (cDVH) shape as calculated using a linear-quadratic cell survival model (α/ß = 10.0 Gy, N0  = 1 × 106 ) with both α = 0.20 Gy-1 and α = 0.23 Gy-1 . RESULTS: Using α = 0.20 Gy-1 (α = 0.23 Gy-1 ), plans in the analytical set with higher shoulder regions had TCP, EUDT , EUDR increased by 180%, 5.9%, 10.7% (11.2%, 6.3%, 10.0%), respectively. With α = 0.20 Gy-1 (α = 0.23 Gy-1 ), plans with higher heels had TCP, EUDT , EUDR increased by 4.0%, <1%, <1% (0.6%, <1%, <1%), respectively. In emulating a 16 (8) mm collimator, 64 (12) shots of the small collimators were used. Plans based on small collimators had higher shoulder regions and, with α = 0.20 Gy-1 (α = 0.23 Gy-1 ), TCP, EUDT , EUDR was increased up to 351.4%, 5.0%, 8.8% (270.4%, 5.0%, 6.8%) compared with the single-shot large collimator. Delivery times ranged from 10.2 to 130.3 min. The SWS technique used 16:8 mm collimator weightings ranging from 1:2 to 9.2:1 for 40-75% IDL. With α = 0.20 Gy-1 (α = 0.23 Gy-1 ), the 40% IDL plan had the highest shoulder with increased TCP, EUDT , EUDR by 130.7%, 9.6%, 17.1% (12.9%, 9.1%, 16.4%) over the 75% IDL plan. Delivery times ranged 6.9-13.8 min. CONCLUSIONS: The magnitude of the shoulder region characteristic to GK cDVHs may be used to rapidly identify superior plan among candidates. Practical issues such as delivery time may require further consideration.

Correlation of clinical outcome, radiobiological modeling of tumor control, normal tissue complication probability in lung cancer patients treated with SBRT using Monte Carlo calculation algorithm.

PURPOSE/BACKGROUND: We analyzed the predictive value of non-x-ray voxel Monte Carlo (XVMC)-based modeling of tumor control probability (TCP) and normal tissue complication probability (NTCP) in patients treated with stereotactic body radiotherapy (SBRT) using the XVMC dose calculation algorithm. MATERIALS/METHODS: We conducted an IRB-approved retrospective analysis in patients with lung tumors treated with XVMC-based lung SBRT. For TCP, we utilized tumor size-adjusted biological effective dose (s-BED) TCP modeling validated in non-MC dose calculated SBRT to: (1) verify modeling as a function of s-BED in patients treated with XVMC-based SBRT; and (2) evaluate the predictive potential of different PTV dosimetric parameters (mean dose, minimum dose, max dose, prescription dose, D95, D98, and D99) for incorporation into the TCP model. Correlation between observed local control and TCPs was assessed by Pearson's correlation coefficient. For NTCP, Lyman NTCP Model was utilized to predict grade 2 pneumonitis and rib fracture. RESULTS: Eighty-four patients with 109 lung tumors were treated with XVMC-based SBRT to total doses of 40 to 60 Gy in 3 to 5 fractions. Median follow-up was 17 months. The 2-year local and local-regional control rates were 91% and and 78%, respectievly. All estimated TCPs correlated significantly with 2-year actuarial local control rates (P < 0.05). Significant corelations between TCPs and tumor control rate according to PTV dosimetric parameters were observed. D99 parameterization demonstrated the most robust correlation between observed and predicted tumor control. The incidences of grade 2 pneumonitis and rib fracture vs. predicted were 1% vs. 3% and 10% vs. 13%, respectively. CONCLUSION: Our TCP results using a XVMC-based dose calculation algorithm are encouraging and yield validation to previously described TCP models using non-XVMC dose methods. Furthermore, D99 as potential predictive parameter in the TCP model demonstrated better correlation with clinical outcome.

The impact of local control on overall survival after stereotactic body radiotherapy for liver and lung metastases from colorectal cancer: a combined analysis of 388 patients with 500 metastases.

BACKGROUND: The aim of this analysis was to model the effect of local control (LC) on overall survival (OS) in patients treated with stereotactic body radiotherapy (SBRT) for liver or lung metastases from colorectal cancer. METHODS: The analysis is based on pooled data from two retrospective SBRT databases for pulmonary and hepatic metastases from 27 centers from Germany and Switzerland. Only patients with metastases from colorectal cancer were considered to avoid histology as a confounding factor. An illness-death model was employed to model the relationship between LC and OS. RESULTS: Three hundred eighty-eight patients with 500 metastatic lesions (lung n = 209, liver n = 291) were included and analyzed. Median follow-up time for local recurrence assessment was 12.1 months. Ninety-nine patients with 112 lesions experienced local failure. Seventy-one of these patients died after local failure. Median survival time was 27.9 months in all patients and 25.4 months versus 30.6 months in patients with and without local failure after SBRT. The baseline risk of death after local failure exceeds the baseline risk of death without local failure at 10 months indicating better survival with LC. CONCLUSION: In CRC patients with lung or liver metastases, our findings suggest improved long-term OS by achieving metastatic disease control using SBRT in patients with a projected OS estimate of > 12 months.

Dosimetric effect of tissue heterogeneity for (125)I prostate implants.

AIM: To use Monte Carlo (MC) together with voxel phantoms to analyze the tissue heterogeneity effect in the dose distributions and equivalent uniform dose (EUD) for (125)I prostate implants. BACKGROUND: Dose distribution calculations in low dose-rate brachytherapy are based on the dose deposition around a single source in a water phantom. This formalism does not take into account tissue heterogeneities, interseed attenuation, or finite patient dimensions effects. Tissue composition is especially important due to the photoelectric effect. MATERIALS AND METHODS: The computed tomographies (CT) of two patients with prostate cancer were used to create voxel phantoms for the MC simulations. An elemental composition and density were assigned to each structure. Densities of the prostate, vesicles, rectum and bladder were determined through the CT electronic densities of 100 patients. The same simulations were performed considering the same phantom as pure water. Results were compared via dose-volume histograms and EUD for the prostate and rectum. RESULTS: The mean absorbed doses presented deviations of 3.3-4.0% for the prostate and of 2.3-4.9% for the rectum, when comparing calculations in water with calculations in the heterogeneous phantom. In the calculations in water, the prostate D 90 was overestimated by 2.8-3.9% and the rectum D 0.1cc resulted in dose differences of 6-8%. The EUD resulted in an overestimation of 3.5-3.7% for the prostate and of 7.7-8.3% for the rectum. CONCLUSIONS: The deposited dose was consistently overestimated for the simulation in water. In order to increase the accuracy in the determination of dose distributions, especially around the rectum, the introduction of the model-based algorithms is recommended.

Dose-rate effects and tumor control probability in177Lu-based targeted radionuclide therapy: a theoretical analysis.

Objective.177Lu-based targeted radionuclide therapy (TRT) has become an important cancer treatment option in recent years, in particular in the treatment of advanced prostate cancer and metastasized neuroendocrine tumors. Although it is known from conventional radiotherapy that the temporal dynamics of the dose-rate can be of relevance for tumor cell survival, the analysis of TRT efficacy usually considers only the absorbed dose. Thus, the aim of this theoretical analysis is to shed light on the possible effects of the pattern of dose-rate in TRT on tumor control probability (TCP).Approach.For this purpose, TCP is studied numerically in a typical four-cycle treatment regime based on the mechanistic lethal-potentially lethal model and the Zaider-Minerbo model for TCP including repopulation of tumor cells.Main results.It is shown that the dose-rate pattern in TRT can have a substantial effect on TCP even though the absorbed dose in the tumor lesion is unchanged. These dose-rate effects are particularly evident when repair of potentially lethal lesions is slow.Significance.The results indicate that in some situations in the analysis of the efficacy of TRT it is necessary to consider the full dose-rate pattern instead of the absorbed dose alone. This can be highly relevant for optimization and further development of TRTs. In particular, it could be of relevancy in studying the efficacy of newly emerging treatment concepts that combine the use of TRT and drugs that inhibit DNA damage repair.

Modeling of the resensitization effect on carbon-ion radiotherapy for stage I non-small cell lung cancer.

Objective. To investigate the effect of redistribution and reoxygenation on the 3-year tumor control probability (TCP) of patients with stage I non-small cell lung cancer (NSCLC) treated with carbon-ion radiotherapy.Approach. A meta-analysis of published clinical data of 233 NSCLC patients treated by carbon-ion radiotherapy under 18-, 9-, 4-, and single-fraction schedules was conducted. The linear-quadratic (LQ)-based cell-survival model incorporating the radiobiological 5Rs, radiosensitivity, repopulation, repair, redistribution, and reoxygenation, was developed to reproduce the clinical TCP data. Redistribution and reoxygenation were regarded together as a single phenomenon and termed 'resensitization' in the model. The optimum interval time between fractions was investigated for each fraction schedule using the determined model parameters.Main results.The clinical TCP data for 18-, 9-, and 4-fraction schedules were reasonably reproduced by the model without the resensitization effect, whereas its incorporation was essential to reproduce the TCP data for all fraction schedules including the single fraction. The curative dose for the single-fraction schedule was estimated to be 49.0 Gy (RBE), which corresponds to the clinically adopted dose prescription of 50.0 Gy (RBE). For 18-, 9-, and 4-fraction schedules, a 2-to-3-day interval is required to maximize the resensitization effect during the time interval. In contrast, the single-fraction schedule cannot benefit from the resensitization effect, and the shorter treatment time is preferable to reduce the effect of sub-lethal damage repair during the treatment.Significance.The LQ-based cell-survival model incorporating the radiobiological 5Rs was developed and used to evaluate the effect of the resensitization on clinical results of NSCLC patients treated with hypo-fractionated carbon-ion radiotherapy. The incorporation of the resensitization into the cell-survival model improves the reproducibility to the clinical TCP data. A shorter treatment time is preferable in the single-fraction schedule, while a 2-to-3-day interval between fractions is preferable in the multi-fraction schedules for effective treatments.

A dosiomics approach to treatment outcome modeling in carbon ion radiotherapy for skull base chordomas.

PURPOSE: To investigate the role of dosiomics features extracted from physical dose (DPHYS), RBE-weighted dose (DRBE) and dose-averaged Linear Energy Transfer (LETd), to predict the risk of local recurrence (LR) in skull base chordoma (SBC) treated with Carbon Ion Radiotherapy (CIRT). Thus, define and evaluate dosiomics-driven tumor control probability (TCP) models. MATERIALS AND METHODS: 54 SBC patients were retrospectively selected for this study. A regularized Cox proportional hazard model (r-Cox) and Survival Support Vector Machine (s-SVM) were tuned within a repeated Cross Validation (CV) and patients were stratified in low/high risk of LR. Models' performance was evaluated through Harrell's concordance statistic (C-index), and survival was represented through Kaplan-Meier (KM) curves. A multivariable logistic regression was fit to the selected feature sets to generate a dosiomics-driven TCP model for each map. These were compared to a reference model built with clinical parameters in terms of f-score and accuracy. RESULTS: The LETd maps reached a test C-index of 0.750 and 0.786 with r-Cox and s-SVM, and significantly separated KM curves. DPHYS maps and clinical parameters showed promising CV outcomes with C-index above 0.8, despite a poorer performance on the test set and patients stratification. The LETd-based TCP showed a significatively higher f-score (0.67[0.52-0.70], median[IQR]) compared to the clinical model (0.4[0.32-0.63], p < 0.025), while DPHYS achieved a significatively higher accuracy (DPHYS: 0.73[0.65-0.79], Clinical: 0.6 [0.52-0.72]). CONCLUSION: This analysis supports the role of LETd as relevant source of prognostic factors for LR in SBC treated with CIRT. This is reflected in the TCP modeling, where LETd and DPHYS showed an improved performance with respect to clinical models.

In Silico Study of Simultaneous Integrated Boost Carbon-Ion Radiotherapy for Locally Advanced Pancreatic Cancer.

BACKGROUND/AIM: Carbon-ion radiotherapy (CiRT) has been used for the treatment of locally advanced pancreatic cancer (LAPC) with uniform dose plan. The aim of the present study is to investigate the effectiveness of a simultaneous integrated boost (SIB) technique with scanned CiRT against LAPC. MATERIALS AND METHODS: Data of 21 patients with LAPC were used to compare two treatment planning approaches: a conventional uniform dose approach and a SIB approach. A relative biological effectiveness (RBE)-weighted dose (DRBE) of 55.2 Gy (RBE) in 12 fractions was prescribed to the planning target volume (PTV) in the conventional approach. In the SIB approach, DRBE of 67.2 Gy (RBE) and 43.2 Gy (RBE) in 12 fractions were prescribed to a high-risk PTV (HR-PTV) and low-risk PTV (LR-PTV), respectively. The DRBE and dose-averaged linear energy transfer (LETd) of targets and gastrointestinal tracts as organs at risk (OARs) were evaluated. RESULTS: The HR-PTV D90% and LR-PTV D90% were 64.4±0.6 and 42.5±0.1 Gy (RBE) in SIB approach compared to the PTV D90% of 54.1±0.4 Gy (RBE) in the conventional approach. All SIB plans achieved the D2cc lower than 46 Gy (RBE) and V30 lower than 4 cm3 within OARs. The SIB approach increased the minimum LETd within the GTV to 44 keV/µm or higher for 20 out of 21 patients as compared to 16 out of 21 patients in the conventional approach. CONCLUSION: The SIB approach effectively increased the RBE-weighted dose and LETd within the HR-PTV and GTV by accumulating the high-LET stopping carbon-ions into the HR-PTV in addition to the decreased RBE-weighted dose to OARs.

Quantify the Effect of Air Gap Errors on Skin Dose for Breast Cancer Radiotherapy.

Purpose: Determining the impact of air gap errors on the skin dose in postoperative breast cancer radiotherapy under dynamic intensity-modulated radiation therapy (IMRT) techniques. Methods: This was a retrospective study that involved 55 patients who underwent postoperative radiotherapy following modified radical mastectomy. All plans employed tangential IMRT, with a prescription dose of 50 Gy, and bolus added solely to the chest wall. Simulated air gap depth errors of 2 mm, 3 mm, and 5 mm were introduced at depression or inframammary fold areas on the skin, resulting in the creation of air gaps named Air2, Air3, and Air5. Utilizing a multivariable GEE, the average dose (Dmean) of the local skin was determined to evaluate its relationship with air gap volume and the lateral beam's average angle (AALB). Additionally, an analysis was conducted on the impact of gaps on local skin. Results: When simulating an air gap depth error of 2 mm, the average Dmean in plan2 increased by 0.46 Gy compared to the initial plan (planO) (p < .001). For the 3-mm air gap, the average Dmean of plan3 was 0.51 Gy higher than that of planO (p < .001). When simulating the air gap as 5 mm, the average Dmean of plan5 significantly increased by 0.59 Gy compared to planO (p < .001). The TCP results showed a similar trend to those of Dmean. As the depth of air gap error increases, NTCP values also gradually rise. The linear regression of the multivariable GEE equation indicates that the volume of air gaps and the AALB are strong predictors of Dmean. Conclusion: With small irregular air gap errors simulated in 55 patients, the values of skin's Dmean, TCP, and NTCP increased. A multivariable linear GEE regression model may effectively explain the impact of air gap volume and AALB on the local skin.

An in-silico study of conventional and FLASH radiotherapy iso-effectiveness: potential impact of radiolytic oxygen depletion on tumor growth curves and tumor control probability.

Objective. This work aims to investigate the iso-effectiveness of conventional and FLASH radiotherapy on tumors through in-silico mathematical models. We focused on the role of radiolytic oxygen depletion (ROD), which has been argued as a possible factor to explain the FLASH effect.Approach. We used a spatiotemporal reaction-diffusion model, including ROD, to simulate tumor oxygenation and response. From those oxygen distributions we obtained surviving fractions (SFs) using the linear-quadratic (LQ) model with the oxygen enhancement ratios (OERs). We then employed the calculated SFs to describe the evolution of preclinical tumor volumes through a mathematical model of tumor response, and we also extrapolated those results to calculate tumor control probabilities (TCPs) using the Poisson-LQ approach.Main results. Our study suggests that the ROD effect may cause differences in SF between FLASH and conventional radiotherapy, especially in lowα/ßandpoorly oxygenatedcells. However, a statistical analysis showed that these changes in SF generally do not result in significant differences in the evolution of preclinical tumor growth curves when the sample size is small, because such differences in SF may not be noticeable in the heterogeneity of the population of animals. Nonetheless, when extrapolating this effect to TCP curves, we observed important differences between both techniques (TCP is lower in FLASH radiotherapy). When analyzing the response of tumors with heterogeneous oxygenations, differences in TCP are more important forwell oxygenatedtumors. This apparent contradiction with the results obtained for homogeneously oxygenated cells is explained by the complex interplay between the heterogeneity of tumor oxygenation, the OER effect, and the ROD effect.Significance. This study supports the experimentally observed iso-effectiveness of FLASH and conventional radiotherapy when analyzing the volume evolution of preclinical tumors (that are far from control). However, this study also hints that tumor growth curves may be less sensitive to small variations in SF than tumor control probability: ROD may lead to increased SF in FLASH radiotherapy, which while not large enough to cause significant differences in tumor growth curves, could lead to important differences in clinical TCPs. Nonetheless, it cannot be discarded that other effects not modeled in this work, like radiation-induced immune effects, can contribute to tumor control and maintain the iso-effectiveness of FLASH radiotherapy. The study of tumor growth curves may not be the ideal experiment to test the iso-effectiveness of FLASH, and experiments reporting TCP orD50may be preferred.

Artificial neural network-assisted prediction of radiobiological indices in head and neck cancer.

Background and purpose: We proposed an artificial neural network model to predict radiobiological parameters for the head and neck squamous cell carcinoma patients treated with radiation therapy. The model uses the tumor specification, demographics, and radiation dose distribution to predict the tumor control probability and the normal tissue complications probability. These indices are crucial for the assessment and clinical management of cancer patients during treatment planning. Methods: Two publicly available datasets of 31 and 215 head and neck squamous cell carcinoma patients treated with conformal radiation therapy were selected. The demographics, tumor specifications, and radiation therapy treatment parameters were extracted from the datasets used as inputs for the training of perceptron. Radiobiological indices are calculated by open-source software using dosevolume histograms from radiation therapy treatment plans. Those indices were used as output in the training of a single-layer neural network. The distribution of data used for training, validation, and testing purposes was 70, 15, and 15%, respectively. Results: The best performance of the neural network was noted at epoch number 32 with the mean squared error of 0.0465. The accuracy of the prediction of radiobiological indices by the artificial neural network in training, validation, and test phases were determined to be 0.89, 0.87, and 0.82, respectively. We also found that the percentage volume of parotid inside the planning target volume is the significant parameter for the prediction of normal tissue complications probability. Conclusion: We believe that the model has significant potential to predict radiobiological indices and help clinicians in treatment plan evaluation and treatment management of head and neck squamous cell carcinoma patients.

Impact of Dose Calculation Algorithms and Radiobiological Parameters on Prediction of Cardiopulmonary Complications in Left Breast Radiation Therapy.

Background: Breast cancer requires evaluating treatment plans using dosimetric and biological parameters. Considering radiation dose distribution and tissue response, healthcare professionals can optimize treatment plans for better outcomes. Objective: This study aimed to evaluate the effects of the different Dose Calculation Algorithms (DCAs) and Biologically Model-Related Parameters (BMRPs) on the prediction of cardiopulmonary complications due to left breast radiotherapy. Material and Methods: In this practical study, the treatment plans of 21 female patients were simulated in the Monaco Treatment Planning System (TPS) with a prescribed dose of 50 Gy in 25 fractions. Dose distribution was extracted using the three DCAs [Pencil Beam (PB), Collapsed Cone (CC), and Monte Carlo (MC)]. Cardiopulmonary complications were predicted by Normal Tissue Complication Probability (NTCP) calculations using different dosimetric and biological parameters. The Lyman-Kutcher-Burman (LKB) and Relative-Seriality (RS) models were used to calculate NTCP. The endpoint for NTCP calculation was pneumonitis, pericarditis, and late cardiac mortality. The ANOVA test was used for statistical analysis. Results: In calculating Tumor Control Probability (TCP), a statistically significant difference was observed between the results of DCAs in the Poisson model. The PB algorithm estimated NTCP as less than others for all Pneumonia BMRPs. Conclusion: The impact of DCAs and BMRPs differs in the estimation of TCP and NTCP. DCAs have a stronger influence on TCP calculation, providing more effective results. On the other hand, BMRPs are more effective in estimating NTCP. Consequently, parameters for radiobiological indices should be cautiously used s to ensure the appropriate consideration of both DCAs and BMRPs.

Dose-response modeling and treatment plan assessment with a python software toolkit.

This software assistant aims at calculating the dose-response relations of tumors and normal tissues, or clinically assessing already determined values by other researchers. It can also indicate the optimal dose prescription by optimizing the expected treatment outcome. The software is developed solely in python programming language, and it employs PSFL license for its Graphical User Interface (GUI), NUMPY, MATPLOTLIB, and SCIPY libraries. It comprises of two components. The first is the Dose-response relations derivation component, which takes as input the dose volume histograms (DVHs) of patients and their recorded responses regarding a given clinical endpoint to determine the parameters of different tumor control probability (TCP) or normal tissue complication probability (NTCP) models. The second is the Treatment Plan Assessment component, which uses the DVHs of a plan and the dose-response parameters values of the involved tumors and organs at risk (OARs) to calculate their expected responses. Additionally, the overall probabilities of benefit (PB), injury (PI) and complication-free tumor control (P+) are calculated. The software calculates rapidly the corresponding generalized equivalent uniform doses (gEUD) and biologically effective uniform doses (D‾‾) for the Lyman-Kutcher-Burman (LKB), parallel volume (PV) and relative seriality (RS) models respectively, determining the model parameters. In the Dose-Response Relations Derivation component, the software plots the dose-response curves of the irradiated organ with the relevant confidence internals along with the data of the patients with and without toxicity. It also calculates the odds ratio (OR) and the area under the curve (AUC) of different dose metrics or model parameter values against the individual patient outcomes to determine their discrimination capacity. It also performs a goodness-of-fit evaluation of any model parameter set. The user has the option of viewing plots like Scatter, 3D surfaces, and Bootstrap plots. In the Treatment Plan Assessment part, the software calculates the TCP and NTCP values of the involved tumors and OARs, respectively. Furthermore, it plots the dose-response curves of the TCPs, NTCPs, PB, PI, and P+ for a range of prescription doses for different treatment plans. The presented software is ideal for efficiently conducting studies of radiobiological modeling. Furthermore, it is ideal for performing treatment plan assessment, comparison, and optimization studies.