Optimization of radiotherapy dose-time fractionation with consideration of tumor specific biology

Optimization of antitumor radiotherapy fractionation via mathematical modeling with account of 4 R's of radiobiology

A spatially-distributed continuous mathematical model of solid tumor growth and treatment by fractionated radiotherapy is presented. The model explicitly accounts for the factors, widely referred to as 4 R's of radiobiology, which influence the efficacy of radiotherapy fractionation protocols: tumor cell repopulation, their redistribution in cell cycle, reoxygenation and repair of sublethal damage of both tumor and normal tissues. With the use of special algorithm the fractionation protocols that provide increased tumor control probability, compared to standard clinical protocol, are found for various physiologically-based values of model parameters under the constraints of fixed overall normal tissue damage and maximum admissible fractional dose. In particular, it is shown that significant gain in treatment efficacy can be achieved for tumors of low malignancy by the use of protracted hyperfractionated protocols. The optimized non-uniform protocols are characterized by gradual escalation of fractional doses in their last parts, which start after the levels of oxygen and nutrients significantly elevate throughout the tumor and accelerated tumor proliferation manifests itself, which is a well-known experimental phenomenon.

Updates on the APBI-IMRT-Florence Trial (NCT02104895) Technique: From the Intensity Modulated Radiation Therapy Trial to the Volumetric Modulated Arc Therapy Clinical Practice

Several phase 3 trials have demonstrated partial breast irradiation noninferiority compared with whole breast irradiation in terms of local control and similar or reduced toxicity. During recent years, especially owing to the COVID-19 pandemic, a growing interest in 5-fraction regimens emerged. The APBI-IMRT-Florence trial (NCT02104895) schedule (30 Gy in 5 fractions) might represent an appealing treatment option, being both a safe and effective partial breast irradiation schedule, with long-term reported results. The aim of this report is to support planners interested in implementing this technique and to warrant equal access to postoperative radiation treatment for most early breast cancer patient candidates. We report the current delivery technique optimized from the original protocol and the updated dose constraints for plan optimization. We also report a statistical analysis of dosimetric parameters on 50 patients treated in consecutive fractions. Treatment-related toxic effects were assessed using the acute radiation morbidity scoring criteria and late radiation morbidity scoring scheme from the Radiation Therapy Oncology Group and the European Organisation for Research and Treatment of Cancer. The mean volume of ipsilateral breast was 731 cm³ (standard deviation ± 450; range, 151-2205) and the mean planning target volume (PTV) was 139 cm³ (standard deviation ± 48; range, 55-259). There was good correlation between ipsilateral breast V_15Gy and the ratio between the PTV and ipsilateral breast volume (R² = .911). At a median follow-up of 4.5 years, 32% of patients (n = 16) developed any grade 1 acute toxic effect. No grade >1 toxic effect was observed. Sixteen percent of patients (n = 8) developed any grade 1 late toxic effect. No grade >1 toxic effect was observed. Physician-assessed cosmesis was reported as excellent (84%), good (14%), and fair (2%). The schedule of 30 Gy in 5 consecutive fractions might represent a safe, easy-to-deliver, and cost-effective option for appropriately selected patients affected by early breast cancer.

Comparing the Effects of Warm Footbath and Foot Reflexology on the Fatigue of Patients Undergoing Radiotherapy: A Randomized Clinical Trial

BACKGROUND AND AIM

Fatigue is a common side effect of radiotherapy. While warm footbath and foot reflexology can both reduce fatigue, it is still unclear which method is more effective in reducing fatigue. This study aimed to compare the effects of warm footbath and foot reflexology on the fatigue of patients undergoing radiotherapy.

METHOD

A randomized clinical trial study was conducted on 62 patients undergoing radiotherapy. Eligible patients were randomly assigned to the 2 groups. Patients in the footbath group immersed their feet in 41°C water for 20 minutes every night for 2 weeks starting from the seventh day of radiotherapy. Patients in the reflexology group received 20 minutes of foot reflexology every night for 2 weeks starting from the seventh day of radiotherapy. Fatigue was measured by the Multidimensional Fatigue Inventory (MFI) once on the seventh day of radiotherapy and 3 more times on days 7, 14, and 28 after the start of the intervention. Data were analyzed by SPSS20 and descriptive/inferential statistics.

RESULTS

The total MFI score of both groups declined significantly over time (P < .001). The reflexology group indicated a significant reduction from 90.9 ± 3.2 in the pre-test to 56.0 ± 3.7 on the 28th day in, while the footbath group indicated it from 90 ± 2.6 in the pre-test to 71.4 ± 2.8 on the 28th day.

CONCLUSION

Our results showed that foot reflexology and warm footbath reduced the fatigue of patients undergoing radiotherapy. However, foot reflexology was more effective in reducing the fatigue of patients undergoing radiotherapy than warm footbath. It is recommended that simple and low cost non-pharmacological interventions such as foot reflexology to decrease of side effect of radiotherapy among cancer patients should be widely performed.Trial registration: Iranian Registry of Clinical Trials (IRCT20190625044009N1).

Evaluation of Biological Effective Dose in Gamma Knife Staged Stereotactic Radiosurgery for Large Brain Metastases

Objective

Gamma knife (GK) staged stereotactic radiosurgery (Staged-SRS) has become an effective treatment option for large brain metastases (BMs); however, it has been challenging to evaluate the total dose because of tumor shrinkage between two staged sessions. This study aims to evaluate total biological effective dose (BED) in Staged-SRS, and to compare the BED with those in single-fraction SRS (SF-SRS) and hypo-fractionated SRS (HF-SRS).

Methods

Patients treated with GK Staged-SRS at a single institution were retrospectively included. The dose delivered in two sessions of Staged-SRS was summed using the deformable image registration. Each patient was replanned for SF-SRS and HF-SRS. The total BEDs were computed using the linear-quadratic model. Tumor BED_98% and brain V_84Gy2, equivalent to V_12Gy in SF-SRS, were compared between SF-SRS, HF-SRS, and Staged-SRS plans with the Wilcoxon test.

Results

Twelve patients with 24 BMs treated with GK Staged-SRS were identified. We observed significant differences (p < 0.05) in tumor BED_98% but comparable brain V_84Gy2 (p = 0.677) between the Staged-SRS and SF-SRS plans. No dosimetric advantages of Staged-SRS over HF-SRS were observed. Tumor BED_98% in the HF-SRS plans were significantly higher than those in the Staged-SRS plans (p < 0.05). Despite the larger PTVs, brain V_84Gy2 in the HF-SRS plans remained lower (p < 0.05).

Conclusion

We presented an approach to calculate the composite BEDs delivered to both tumor and normal brain tissue in Staged-SRS. Compared to SF-SRS, Staged-SRS delivers a higher dose to tumor but maintains a comparable dose to normal brain tissue. Our results did not show any dosimetric advantages of Staged-SRS over HF-SRS.

Adaptive proton therapy

Radiation therapy treatments are typically planned based on a single image set, assuming that the patient's anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research.

A reinforcement learning approach for finding optimal policy of adaptive radiation therapy considering uncertain tumor biological response

Recent studies have shown that a tumor's biological response to radiation varies over time and has a dynamic nature. Dynamic biological features of tumor cells underscore the importance of using fractionation and adapting the treatment plan to tumor volume changes in radiation therapy treatment. Adaptive radiation therapy (ART) is an iterative process to adjust the dose of radiation in response to potential changes during the treatment. One of the key challenges in ART is how to determine the optimal timing of adaptations corresponding to tumor response to radiation. This paper aims to develop an automated treatment planning framework incorporating the biological uncertainties to find the optimal adaptation points to achieve a more effective treatment plan. First, a dynamic tumor-response model is proposed to predict weekly tumor volume regression during the period of radiation therapy treatment based on biological factors. Second, a Reinforcement Learning (RL) framework is developed to find the optimal adaptation points for ART considering the uncertainty in biological factors with the goal of achieving maximum final tumor control while minimizing or maintaining the toxicity level of the organs at risk (OARs) per the decision-maker's preference. Third, a beamlet intensity optimization model is solved using the predicted tumor volume at each adaptation point. The performance of the proposed RT treatment planning framework is tested using a clinical non-small cell lung cancer (NSCLC) case. The results are compared with the conventional fractionation schedule (i.e., equal dose fractionation) as a reference plan. The results show that the proposed approach performed well in achieving a robust optimal ART treatment plan under high uncertainty in the biological parameters. The ART plan outperformed the reference plan by increasing the mean biological effective dose (BED) value of the tumor by 2.01%, while maintaining the OAR BED within +0.5% and reducing the variability, in terms of the interquartile range (IQR) of tumor BED, by 25%.

Technical Note: Break-even dose level for hypofractionated treatment schedules

PURPOSE

To derive the isodose line R relative to the prescription dose below which irradiated normal tissue (NT) regions benefit from a hypofractionated schedule with an isoeffective dose to the tumor. To apply the formalism to clinical case examples.

METHODS

From the standard biologically effective dose (BED) equation based on the linear-quadratic (LQ) model, the BED of an NT that receives a relative proportion r of the prescribed dose per fraction for a given α/β-ratio of the tumor, (α/β)_T , and NT, (α/β)_NT , is derived for different treatment schedules while keeping the BED to the tumor constant. Based on this, the "break-even" isodose line R is then derived. The BED of NT regions that receive doses below R decreases for more hypofractionated treatment schedules, and hence a lower risk for NT injury is predicted in these regions. To assess the impact of a linear behavior of BED for high doses per fraction (>6 Gy), we evaluated BED also using the LQ-linear (LQ-L) model.

RESULTS

The formalism provides the equations to derive the BED of an NT as function of dose per fraction for an isoeffective dose to the tumor and the corresponding break-even isodose line R. For generic α/β-ratios of (α/β)_T  = 10 Gy and (α/β)_NT  = 3 Gy and homogeneous dose in the target, R is 30%. R is doubling for stereotactic treatments for which tumor control correlates with the maximum dose of 100% instead of the encompassing isodose line of 50%. When using the LQ-L model, the notion of a break-even dose level R remains valid up to about 20 Gy per fraction for generic α/β-ratios and D T = 2 ( α / β ) .

CONCLUSIONS

The formalism may be used to estimate below which relative isodose line R there will be a differential sparing of NT when increasing hypofractionation. More generally, it allows to assess changes of the therapeutic index for sets of isoeffective treatment schedules at different relative dose levels compared to a reference schedule in a compact manner.

A general algorithm for distributed treatments of multiple brain metastases

PURPOSE

Stereotactic radiosurgery (SRS) has become a primary treatment for multiple brain metastases (BM) but may require distribution of BMs over several sessions to make delivery time and radiation toxicity manageable. Contrasting to equal fraction dose in conventional fractionation, distributed SRS delivers full dose to a subset of BMs in each session while avoiding adjacent BMs in the same session to reduce toxicity from overlapping radiation. However, current clinical treatment planning for distributed SRS relies on manual BM assignment, which can be tedious and error prone. This work describes a novel approach to automate the distribution of BM in the Gamma Knife (GK) clinical workflow.

METHODS

We represent each BM as an electrostatic field of the same polarity that exerts repulsive forces on other BMs in the same session. This representation naturally leads to separation of close BMs into different sessions to lower the potential energy. Indeed, the BM distribution problem can be formulated as minimization of the total potential energy from all treatment sessions subject to delivery time constraints in mixed-integer quadratic programming (MIQP). We retrospectively studied eight clinical GK cases of multiple BM and compared the automated MIQP solution with clinically used BM distribution to demonstrate the efficacy of the proposed approach.

RESULTS

With the problem size equal to the number of BMs times the number of sessions, this MIQP can be solved in a minute on a personal workstation. The MIQP solution effectively separated BMs for a given number of treatment sessions and evened out the delivery time distribution among sessions. Compared to the clinically used manual BM distributions in paired t-test for a similar range of delivery time variation, the automated BM distributions had lower energy objectives (range of decrease: [11% 89%]; median: 25%; P = . 073 ), more uniformly distributed treatment volumes (range of decrease for the normalized standard deviation of volume distribution: [0.02 0.95]; median: 0.16; P = . 013 ), more scattered BMs in each treatment session (range of increase for the mean minimum BM distance: [0 14] mm; median: 6 mm; P = . 008 ), and lower overall V 12 (range of decrease: [0.0 1.6] cc; median: 0.2 cc; P = . 052 ). Moreover, without distribution, that is, with all BMs treated in the same session, V 12 was substantially larger compared to both manual and automated BM distributions; the increase ranged from 0.1 to 16.6 cc with a median of 1.3 cc.

CONCLUSIONS

The proposed approach models the clinical practice and provides an efficient solution for optimal selection of BM subsets for distributed SRS. Further evaluations are underway to establish this approach as a tool for improving clinical workflow and to facilitate systematic study on the benefits of distributed SRS treatments.

Treating Glioblastoma Multiforme (GBM) with super hyperfractionated radiation therapy: Implication of temporal dose fractionation optimization including cancer stem cell dynamics

PURPOSE

A previously developed ordinary differential equation (ODE) that models the dynamic interaction and distinct radiosensitivity between cancer stem cells (CSC) and differentiated cancer cells (DCC) was used to explain the definitive treatment failure in Glioblastoma Multiforme (GBM) for conventionally and hypo-fractionated treatments. In this study, optimization of temporal dose modulation based on the ODE equation is performed to explore the feasibility of improving GBM treatment outcome.

METHODS

A non-convex optimization problem with the objective of minimizing the total cancer cell number while maintaining the normal tissue biological effective dose (BEDnormal) at 100 Gy, equivalent to the conventional 2 Gy × 30 dosing scheme was formulated. With specified total number of dose fractions and treatment duration, the optimization was performed using a paired simulated annealing algorithm with fractional doses delivered to the CSC and DCC compartments and time intervals between fractions as variables. The recurrence time, defined as the time point at which the total tumor cell number regrows to 2.8×109 cells, was used to evaluate optimization outcome. Optimization was performed for conventional treatment time frames equivalent to currently and historically utilized fractionation schemes, in which limited improvement in recurrence time delay was observed. The efficacy of a super hyperfractionated approach with a prolonged treatment duration of one year was therefore tested, with both fixed regular and optimized variable time intervals between dose fractions corresponding to total number of fractions equivalent to weekly, bi-weekly, and monthly deliveries (n = 53, 27, 13). Optimization corresponding to BEDnormal of 150 Gy was also obtained to evaluate the possibility in further recurrence delay with dose escalation.

RESULTS

For the super hyperfractionated schedules with dose fraction number equivalent to weekly, bi-weekly, and monthly deliveries, the recurrence time points were found to be 430.5, 423.9, and 413.3 days, respectively, significantly delayed compared with the recurrence time of 250.3 days from conventional fractionation. Results show that optimal outcome was achieved by first delivering infrequent fractions followed by dense once per day fractions in the middle and end of the treatment course, with sparse and low dose treatments in the between. The dose to the CSC compartment was held relatively constant throughout while larger dose fractions to the DCC compartment were observed in the beginning and final fractions that preceded large time intervals. Dose escalation to BEDnormal of 150 Gy was shown capable of further delaying recurrence time to 452 days.

CONCLUSION

The development and utilization of a temporal dose fractionation optimization framework in the context of CSC dynamics have demonstrated that substantial delay in GBM local tumor recurrence could be achieved with a super hyperfractionated treatment approach. Preclinical and clinical studies are needed to validate the efficacy of this novel treatment delivery method.

Accelerated Partial-Breast Irradiation Compared With Whole-Breast Irradiation for Early Breast Cancer: Long-Term Results of the Randomized Phase III APBI-IMRT-Florence Trial

PURPOSE

To report the long-term results of external-beam accelerated partial-breast irradiation (APBI) intensity-modulated radiation therapy (IMRT) Florence phase III trial comparing whole-breast irradiation (WBI) to APBI in early-stage breast cancer.

PATIENTS AND METHODS

The primary end point was to determine the 5-year difference in ipsilateral breast tumor recurrence (IBTR) between 30 Gy in 5 once-daily fractions (APBI arm) and 50 Gy in 25 fractions with a tumor bed boost (WBI arm) after breast-conserving surgery.

RESULTS

Five hundred twenty patients, more than 90% of whom had characteristics associated with low recurrence risk, were randomly assigned (WBI, n = 260; APBI, n = 260) between 2005 and 2013. Median follow-up was 10.7 years. The 10-year cumulative incidence of IBTR was 2.5% (n = 6) in the WBI and 3.7% (n = 9) in the APBI arm (hazard ratio [HR], 1.56; 95% CI, 0.55 to 4.37; P = .40). Overall survival at 10 years was 91.9% in both arms (HR, 0.95; 95% CI, 0.50 to 1.79; P = .86). Breast cancer–specific survival at 10 years was 96.7% in the WBI and 97.8% in the APBI arm (HR, 0.65; 95% CI, 0.21 to 1.99; P = .45). The APBI arm showed significantly less acute toxicity ( P = .0001) and late toxicity ( P = .0001) and improved cosmetic outcome as evaluated by both physician ( P = .0001) and patient ( P = .0001).

CONCLUSION

The 10-year cumulative IBTR incidence in early breast cancer treated with external APBI using IMRT technique in 5 once-daily fractions is low and not different from that after WBI. Acute and late treatment-related toxicity and cosmesis outcomes were significantly in favor of APBI.

Imputing radiobiological parameters of the linear-quadratic dose-response model from a radiotherapy fractionation plan

The objective in cancer radiotherapy is to maximize tumor-kill while limiting toxic effects of radiation dose on nearby organs-at-risk (OAR). Given a fixed number of treatment sessions, planners thus face the problem of finding a dosing sequence that achieves this goal. This is called the fractionation problem, and has received steady attention over a long history in the clinical literature. Mathematical formulations of the resulting optimization problem utilize the linear-quadratic (LQ) framework to characterize radiation dose-response of tumors and OAR. This yields a nonconvex quadratically constrained quadratic program. The optimal dosing plan in this forward problem crucially depends on the parameters of the LQ model. Unfortunately, these parameters are difficult to estimate via in vitro or in vivo studies, and as such, their values are unknown to treatment planners. The clinical literature is thus replete with debates about what parameter values will make specific dosing plans effective. This paper formulates this as an inverse optimization problem. The LQ dose-response parameters appear in the objective function, the left hand side, and the right hand side of the forward problem, and none of the existing generic methods can provide an exact solution of the inverse problem. This paper exploits the structure of the problem and identifies all possible parameter values that render the given dosing plan optimal, in closed-form. This closed-form formula is applied to dosing-plans from three clinical studies published within the last two years.

Optimization of Dose Fractionation for Radiotherapy of a Solid Tumor with Account of Oxygen Effect and Proliferative Heterogeneity

A spatially-distributed continuous mathematical model of solid tumor growth and treatment by fractionated radiotherapy is presented. The model explicitly accounts for three time and space-dependent factors that influence the efficiency of radiotherapy fractionation schemes—tumor cell repopulation, reoxygenation and redistribution of proliferative states. A special algorithm is developed, aimed at finding the fractionation schemes that provide increased tumor cure probability under the constraints of maximum normal tissue damage and maximum fractional dose. The optimization procedure is performed for varied radiosensitivity of tumor cells under the values of model parameters, corresponding to different degrees of tumor malignancy. The resulting optimized schemes consist of two stages. The first stages are aimed to increase the radiosensitivity of the tumor cells, remaining after their end, sparing the caused normal tissue damage. This allows to increase the doses during the second stages and thus take advantage of the obtained increased radiosensitivity. Such method leads to significant expansions in the curative ranges of the values of tumor radiosensitivity parameters. Overall, the results of this study represent the theoretical proof of concept that non-uniform radiotherapy fractionation schemes may be considerably more effective that uniform ones, due to the time and space-dependent effects.

Applications of Nonlinear Programming to the Optimization of Fractionated Protocols in Cancer Radiotherapy

The present work of review collects and evidences the main results of our previous papers on the optimization of fractionated radiotherapy protocols. The problem under investigation is presented here in a unitary framework as a nonlinear programming application that aims to determine the optimal schemes of dose fractionation commonly used in external beam radiotherapy. The radiation responses of tumor and normal tissues are described by means of the linear quadratic model. We formulate a nonlinear, non-convex optimization problem including two quadratic constraints to limit the collateral normal tissue damages and linear box constraints on the fractional dose sizes. The general problem is decomposed into two subproblems: (1) analytical determination of the optimal fraction dose sizes as a function of the model parameters for arbitrarily fixed treatment lengths; and (2) numerical determination of the optimal fraction number, and of the optimal treatment time, in different parameter settings. After establishing the boundedness of the optimal number of fractions, we investigate by numerical simulation the optimal solution behavior for experimentally meaningful parameter ranges, recognizing the crucial role of some parameters, such as the radiosensitivity ratio, in determining the optimality of hypo- or equi-fractionated treatments. Our results agree with findings of the theoretical and clinical literature.

Optimal modality selection in external beam radiotherapy

The goal in external beam radiotherapy (EBRT) for cancer is to maximize damage to the tumour while limiting toxic effects on the organs-at-risk. EBRT can be delivered via different modalities such as photons, protons and neutrons. The choice of an optimal modality depends on the anatomy of the irradiated area and the relative physical and biological properties of the modalities under consideration. There is no single universally dominant modality. We present the first-ever mathematical formulation of the optimal modality selection problem. We show that this problem can be tackled by solving the Karush-Kuhn-Tucker conditions of optimality, which reduce to an analytically tractable quartic equation. We perform numerical experiments to gain insights into the effect of biological and physical properties on the choice of an optimal modality or combination of modalities.

Outcome of three-fraction gamma knife radiosurgery for brain metastases according to fractionation scheme: preliminary results

PURPOSE

The optimal interfraction intervals for fractionated radiosurgery has yet to be established. We investigated the outcome of fractionated gamma knife radiosurgery (FGKRS) for large brain metastases (BMs) according to different interfraction intervals.

METHODS

Between September 2016 and May 2018, a total of 45 patients who underwent FGKRS for BMs were enrolled in this study. They were divided into two groups (standard fractionation over 3 consecutive days with a 24-h interfraction interval versus prolonged fractionation over 4 or 5 days with an interfraction interval of at least 48-h). BMs with ≥ 2 cm in maximum diameter or ≥ 5 cm³ in volume were included in analysis.

RESULTS

Among 52 BMs treated with 3-fraction GKRS, 25 (48.1%) were treated with standard fractionation scheme, and 27 (51.9%) with prolonged fractionation scheme. The median follow-up period was 10.5 months (range 5-25). Local tumor control rates of the standard group were 88.9% at 6 months and 77.8% at 12 months, whereas those of the prolonged group were 100% at 6 and 12 months (p = 0.023, log-rank test). In multivariate analysis, fractionation scheme (hazard ratio [HR] 0.294, 95% CI 0.099-0.873; p = 0.027) and tumor volume (HR 0.200, 95% CI 0.051-0.781; p = 0.021) were revealed as the only significant factors affecting the local tumor control after 3-fraction GKRS.

CONCLUSIONS

Our preliminary tumor control results suggest a promising role of 3-fraction GKRS with an interfraction interval of at least 48-h. This fractionation regimen could be an effective and safe treatment option in the management of large BMs.

A feasibility study of spatiotemporally integrated radiotherapy using the LQ model

This paper investigates the feasibility of spatiotemporally modulated radiotherapy (STMRT)-integrated model with explicit constraints on the tumor dose heterogeneity. In particular, we demonstrate the effect of the tumor dose heterogeneity on the tumor biologically effective dose (BED) achievable and optimal fractionation. We propose an STMRT model that simultaneously optimizes the dose distributions and fractionation schedule for each individual case with the maximum and minimum constraints on the tumor BED to explicitly control the level of tumor dose heterogeneity. Sixteen thoracic phantom cases were planned using (1) STMRT and (2) standard fractionation (60 Gy in 30 fractions fixed) IMRT. Constraints on the organs-at-risk (OAR) BED were identical for both plans. BEDs were calculated using the [Formula: see text] ratio of 10 Gy for the tumor and 3 Gy for all OARs. The maximum tumor BED for STMRT plans was constrained to be less than 100%-150% of the maximum tumor BED resulted from the standard fractionation plans. The mean tumor BED from STMRT plans was up to 110.7%, 128.3%, 135.0% and 148.0% of that from the standard fractionation plans when the maximum tumor BED was constrained to be less than 100%, 120%, 130% and 150% of the maximum BED achieved using the standard plans. The optimal number of fractions varied widely for different phantom geometries for the same radiobiological parameter values. The increase in the tumor BED and the range of optimal fractionation was larger with a larger tumor dose heterogeneity allowed. The results have shown the feasibility of personalizing fractionation schedule using an STMRT integrated model to deliver a maximum feasible BED to the tumor for a fixed OAR BED. The potential increase in the tumor BED was positively correlated to the tumor dose heterogeneity allowed.

A feasibility study of dynamic adaptive radiotherapy for nonsmall cell lung cancer

PURPOSE

The final state of the tumor at the end of a radiotherapy course is dependent on the doses given in each fraction during the treatment course. This study investigates the feasibility of using dynamic adaptive radiotherapy (DART) in treating lung cancers assuming CBCT is available to observe midtreatment tumor states. DART adapts treatment plans using a dynamic programming technique to consider the expected changes of the tumor in the optimization process.

METHODS

DART is constructed using a stochastic control formalism framework. It minimizes the total expected number of tumor cells at the end of a treatment course, which is equivalent to maximizing tumor control probability, subject to the uncertainty inherent in the tumor response. This formulation allows for nonstationary dose distributions as well as nonstationary fractional doses as needed to achieve a series of optimal plans that are conformal to the tumor over time, i.e., spatiotemporally optimal plans. Sixteen phantom cases with various sizes and locations of tumors and organs-at-risk (OAR) were generated using in-house software. Each case was planned with DART and conventional IMRT prescribing 60 Gy in 30 fractions. The observations of the change in the tumor volume over a treatment course were simulated using a two-level cell population model. Monte Carlo simulations of the treatment course for each case were run to account for uncertainty in the tumor response. The same OAR dose constraints were applied for both methods. The frequency of replanning was varied between 1, 2, 5 (weekly), and 29 times (daily). The final average tumor dose and OAR doses have been compared to quantify the potential dosimetric benefits of DART.

RESULTS

The average tumor max, min, mean, and D95 doses using DART relative to these using conventional IMRT were 124.0%-125.2%, 102.1%-114.7%, 113.7%-123.4%, and 102.0%-115.9% (range dependent on the frequency of replanning). The average relative maximum doses for the cord and esophagus, mean doses for the heart and lungs, and D05 for the unspecified tissue resulting 84%-102.4%, 99.8%-106.9%, 66.9%-85.6%, 58.2%-78.8%, and 85.2%-94.0%, respectively.

CONCLUSIONS

It is feasible to apply DART to the treatment of NSCLC using CBCT to observe the midtreatment tumor state. Potential increases in the tumor dose and reductions in the OAR dose, particularly for parallel OARs with mean or dose-volume constraints, could be achieved using DART compared to nonadaptive IMRT.

Effect of the histone deacetylase inhibitor resminostat on head and neck squamous cell carcinoma cell lines

BACKGROUND

Carcinogenesis is determined by various epigenetic events, such as histone deacetylation. The purpose of this study was to investigate the effect of the new histone deacetylase inhibitor resminostat on head and neck squamous cell carcinoma (HNSCC) cell lines.

METHODS

The cytotoxicity of resminostat and cisplatin on HNSCC cell lines SCC25, CAL27, and FaDu was determined using CCK-8 cell proliferation assay and combination index analysis. Cells were irradiated with 2 to 8 Gray. Apoptosis was measured using flow cytometry and expression of Mcl-1, p-AKT, and survivin was investigated.

RESULTS

Treatment with resminostat showed a decrease of cell proliferation of HNSCC cell lines. In addition, a synergistic effect with cisplatin as well as with radiation treatment could be observed. Induction of cell death and dose-dependent downregulation of survivin was evident in all cell lines.

CONCLUSION

Resminostat is a promising treatment of HNSCC because of its antiproliferative, chemosensitizing, and radiosensitizing effects. © 2017 Wiley Periodicals, Inc. Head Neck 39: 900-907, 2017.

A validated tumor control probability model based on a meta-analysis of low, intermediate, and high-risk prostate cancer patients treated by photon, proton, or carbon-ion radiotherapy

PURPOSE

A fully heterogeneous population averaged mechanistic tumor control probability (TCP) model is appropriate for the analysis of external beam radiotherapy (EBRT). This has been accomplished for EBRT photon treatment of intermediate-risk prostate cancer. Extending the TCP model for low and high-risk patients would be beneficial in terms of overall decision making. Furthermore, different radiation treatment modalities such as protons and carbon-ions are becoming increasingly available. Consequently, there is a need for a complete TCP model.

METHODS

A TCP model was fitted and validated to a primary endpoint of 5-year biological no evidence of disease clinical outcome data obtained from a review of the literature for low, intermediate, and high-risk prostate cancer patients (5218 patients fitted, 1088 patients validated), treated by photons, protons, or carbon-ions. The review followed the preferred reporting item for systematic reviews and meta-analyses statement. Treatment regimens include standard fractionation and hypofractionation treatments. Residual analysis and goodness of fit statistics were applied.

RESULTS

The TCP model achieves a good level of fit overall, linear regression results in a p-value of <0.000 01 with an adjusted-weighted-R(2) value of 0.77 and a weighted root mean squared error (wRMSE) of 1.2%, to the fitted clinical outcome data. Validation of the model utilizing three independent datasets obtained from the literature resulted in an adjusted-weighted-R(2) value of 0.78 and a wRMSE of less than 1.8%, to the validation clinical outcome data. The weighted mean absolute residual across the entire dataset is found to be 5.4%.

CONCLUSIONS

This TCP model fitted and validated to clinical outcome data, appears to be an appropriate model for the inclusion of all clinical prostate cancer risk categories, and allows evaluation of current EBRT modalities with regard to tumor control prediction.

Optimal treatment and stochastic modeling of heterogeneous tumors

In this work we review past articles that have mathematically studied cancer heterogeneity and the impact of this heterogeneity on the structure of optimal therapy. We look at past works on modeling how heterogeneous tumors respond to radiotherapy, and take a particularly close look at how the optimal radiotherapy schedule is modified by the presence of heterogeneity. In addition, we review past works on the study of optimal chemotherapy when dealing with heterogeneous tumors.

REVIEWERS

This article was reviewed by Thomas McDonald, David Axelrod, and Leonid Hanin.

Optimization of the fractionated irradiation scheme considering physical doses to tumor and organ at risk based on dose-volume histograms

PURPOSE

Radiotherapy of solid tumors has been performed with various fractionation regimens such as multi- and hypofractionations. However, the ability to optimize the fractionation regimen considering the physical dose distribution remains insufficient. This study aims to optimize the fractionation regimen, in which the authors propose a graphical method for selecting the optimal number of fractions (n) and dose per fraction (d) based on dose-volume histograms for tumor and normal tissues of organs around the tumor.

METHODS

Modified linear-quadratic models were employed to estimate the radiation effects on the tumor and an organ at risk (OAR), where the repopulation of the tumor cells and the linearity of the dose-response curve in the high dose range of the surviving fraction were considered. The minimization problem for the damage effect on the OAR was solved under the constraint that the radiation effect on the tumor is fixed by a graphical method. Here, the damage effect on the OAR was estimated based on the dose-volume histogram.

RESULTS

It was found that the optimization of fractionation scheme incorporating the dose-volume histogram is possible by employing appropriate cell surviving models. The graphical method considering the repopulation of tumor cells and a rectilinear response in the high dose range enables them to derive the optimal number of fractions and dose per fraction. For example, in the treatment of prostate cancer, the optimal fractionation was suggested to lie in the range of 8-32 fractions with a daily dose of 2.2-6.3 Gy.

CONCLUSIONS

It is possible to optimize the number of fractions and dose per fraction based on the physical dose distribution (i.e., dose-volume histogram) by the graphical method considering the effects on tumor and OARs around the tumor. This method may stipulate a new guideline to optimize the fractionation regimen for physics-guided fractionation.

A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

PURPOSE

To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs).

METHODS

Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (Td), and the size and location of tumor target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (Dmean≤45 Gy), lungs (Dmean≤20 Gy), cord (Dmax≤45 Gy), esophagus (Dmax≤63 Gy), and unspecified tissues (D05≤60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D95 of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of Td (3-100 days), tumor lag-time (Tk=0-10 days), and the size of tumors on optimal fractionation schedule.

RESULTS

Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D95 were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on Td and Tk used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating tumors with Td less than 10 days, there was no significant increase in tumor BED but the treatment course could be shortened without a loss in tumor BED. The improvement in the tumor mean BED was more pronounced with smaller tumors (p-value=0.08).

CONCLUSIONS

Spatiotemporal optimization of patient plans has the potential to significantly improve local tumor control (larger BED/EUD) of patients with a favorable geometry, such as smaller tumors with larger distances between the tumor target and nearby OAR. In patients with a less favorable geometry and for fast growing tumors, plans optimized using spatiotemporal optimization and conventional (spatial-only) optimization are equivalent (negligible differences in tumor BED/EUD). However, spatiotemporal optimization yields shorter treatment courses than conventional spatial-only optimization. Personalized, spatiotemporal optimization of treatment schedules can increase patient convenience and help with the efficient allocation of clinical resources. Spatiotemporal optimization can also help identify a subset of patients that might benefit from nonconventional (large dose per fraction) treatments that are ineligible for the current practice of stereotactic body radiation therapy.

Optimization of radiation dosing schedules for proneural glioblastoma

Glioblastomas are the most aggressive primary brain tumor. Despite treatment with surgery, radiation and chemotherapy, these tumors remain uncurable and few significant increases in survival have been observed over the last half-century. We recently employed a combined theoretical and experimental approach to predict the effectiveness of radiation administration schedules, identifying two schedules that led to superior survival in a mouse model of the disease (Leder et al., Cell 156(3):603-616, 2014). Here we extended this approach to consider fractionated schedules to best minimize toxicity arising in early- and late-responding tissues. To this end, we decomposed the problem into two separate solvable optimization tasks: (i) optimization of the amount of radiation per dose, and (ii) optimization of the amount of time that passes between radiation doses. To ensure clinical applicability, we then considered the impact of clinical operating hours by incorporating time constraints consistent with operational schedules of the radiology clinic. We found that there was no significant loss incurred by restricting dosage to an 8:00 a.m. to 5:00 p.m. window. Our flexible approach is also applicable to other tumor types treated with radiotherapy.

Optimal weekly scheduling in fractionated radiotherapy: effect of an upper bound on the dose fraction size

This work concerns the optimization of the dose fractionation for cancer radiotherapy schedules of the kind one fraction/day, five fractions/week, assuming a fixed overall treatment time. Constraints are set to limit the radiation damages to surrounding normal tissues, as well as the daily fraction size. The response to radiation of tumour and normal tissues is represented by the classical LQ model, including the exponential repopulation term. We provide a framework to analytically determine the optimal weekly scheme of radiation doses as a function of the tumour type, the fraction upper bound and the normal tissue parameters. For a comparison with the literature, we present some numerical examples of optimal treatment schedules for specific tumour types.

Simultaneous optimization of dose distributions and fractionation schemes in particle radiotherapy

PURPOSE

The paper considers the fractionation problem in intensity modulated proton therapy (IMPT). Conventionally, IMPT fields are optimized independently of the fractionation scheme. In this work, we discuss the simultaneous optimization of fractionation scheme and pencil beam intensities.

METHODS

This is performed by allowing for distinct pencil beam intensities in each fraction, which are optimized using objective and constraint functions based on biologically equivalent dose (BED). The paper presents a model that mimics an IMPT treatment with a single incident beam direction for which the optimal fractionation scheme can be determined despite the nonconvexity of the BED-based treatment planning problem.

RESULTS

For this model, it is shown that a small α∕β ratio in the tumor gives rise to a hypofractionated treatment, whereas a large α∕β ratio gives rise to hyperfractionation. It is further demonstrated that, for intermediate α∕β ratios in the tumor, a nonuniform fractionation scheme emerges, in which it is optimal to deliver different dose distributions in subsequent fractions. The intuitive explanation for this phenomenon is as follows: By varying the dose distribution in the tumor between fractions, the same total BED can be achieved with a lower physical dose. If it is possible to achieve this dose variation in the tumor without varying the dose in the normal tissue (which would have an adverse effect), the reduction in physical dose may lead to a net reduction of the normal tissue BED. For proton therapy, this is indeed possible to some degree because the entrance dose is mostly independent of the range of the proton pencil beam.

CONCLUSIONS

The paper provides conceptual insight into the interdependence of optimal fractionation schemes and the spatial optimization of dose distributions. It demonstrates the emergence of nonuniform fractionation schemes that arise from the standard BED model when IMPT fields and fractionation scheme are optimized simultaneously. Although the projected benefits are likely to be small, the approach may give rise to an improved therapeutic ratio for tumors treated with stereotactic techniques to high doses per fraction.

[IMRT and head and neck tumors: does differential fractionation have a role?]

For head and neck cancer, intensity-modulated radiation therapy (IMRT) provides benefits in terms of coverage of the target tumour volume and reduction of the dose to organs at risk. Altered fractionation called SMART (simultaneous modulated accelerated radiation therapy) or SIB (simultaneous integrated boost), equivalent to the "concomitant boost" of conventional techniques, provides additional theoretical gain in the therapeutic index and simplifies the practical implementation of the treatment. The impact on tumour control and acute and late toxicities is encouraging but needs to be confirmed by prospective clinical studies with sufficient follow-up. A lot of different protocols have been tested without really bringing out a "gold standard". However, the current results tend to suggest a SIB/SMART-IMRT moderately accelerated without combined chemotherapy for limited stages (I and II), and SIB-IMRT slightly accelerated with induction and/or concomitant chemotherapy for more advanced stages (III and IV).

Improving the therapeutic ratio in stereotactic radiosurgery: optimizing treatment protocols based on kinetics of repair of sublethal radiation damage

Sublethal damage after radiation exposure may become lethal or be repaired according to repair kinetics. This is a well-established concept in conventional radiotherapy. It also plays an important role in single-dose stereotactic radiotherapy treatments, often called stereotactic radiosurgery, when duration of treatment is extended due to source decay or treatment planning protocol. The purpose of this study is to look into the radiobiological characteristics of normal brain tissue and treatment protocols and find a way to optimize the time course of these protocols. The general problem is nonlinear and can be solved numerically. For numerical optimization of the time course of radiation protocol, a biexponential repair model with slow and fast components was considered. With the clinically imposed constraints of a fixed total dose and total treatment time, three parameters for each fraction (dose-rate, fraction duration, time of each fraction) were simultaneously optimized. A biological optimization can be performed by maximizing the therapeutic difference between tumor control probability and normal tissue complication probability. Specifically, for gamma knife radiosurgery, this approach can be implemented for normal brain tissue or tumor voxels separately in a treatment plan. Differences in repair kinetics of normal tissue and tumors can be used to find clinically optimized protocols. Thus, in addition to considering the physical dose in tumor and normal tissue, we also account for repair of sublethal damage in both these tissues.

Graphical representation of the effects on tumor and OAR for determining the appropriate fractionation regimen in radiation therapy planning

PURPOSE

The authors propose a graphical representation of the relation between the effect on the tumor and the damage effect on an organ at risk (OAR) against the irradiation dose, as an aid for choosing an appropriate fractionation regimen.

METHODS

The graphical relation is depicted by the radiation effect on the tumor E(1) versus that on an OAR E(0). By observing the features of the E(1) vs E(0) relation curve, i.e., convex or concave shape, one can judge whether multifractionation is better or not. This method is applied to the linear-quadratic model (with α and β parameters) as an example. Further, the method is extended to the general case for nonuniform dose distribution to the OAR, which is frequently seen in clinical situations.

RESULTS

The criterion for selecting multi- or hypofractionation is based on the relation between the dose for the OAR and the α∕β ratio of the OAR to the tumor. It is also shown that the graphical relation enables us to estimate the final effect after multifractionated treatment by plotting a tangent line on the curve.

CONCLUSIONS

The graphical representation method is of use for improving planning in radiotherapy by determining the effective fractionation scheme.

Optimal solution for a cancer radiotherapy problem

We address the problem of finding the optimal radiotherapy fractionation scheme, representing the response to radiation of tumour and normal tissues by the LQ model including exponential repopulation and sublethal damage due to incomplete repair. We formulate the nonlinear programming problem of maximizing the overall tumour damage, while keeping the damages to the late and early responding normal tissues within a given admissible level. The optimum is searched over a single week of treatment and its possible structures are identified. In the two simpler but important cases of absence of the incomplete repair term or of prevalent late constraint, we prove the uniqueness of the optimal solution and we characterize it in terms of model parameters. The optimal solution is found to be not necessarily uniform over the week. The theoretical results are confirmed by numerical tests and comparisons with literature fractionation schemes are presented.

An Estimation of Radiobiological Parameters for Head-and-Neck Cancer Cells and the Clinical Implications

In vitro survival measurements using two human head-and-neck cancer (HNC) cell lines were performed. The specially designed split-dose surviving fraction was obtained and fitted to the linear-quadratic formalism. The repair halftime (Tr), the potential doubling time (Td), a/β and radiosensitivity a, were estimated. Other radiobiological models: EUD, BED, TCP, etc., were used to examine the potential treatment effectiveness of different IMRT techniques. Our data indicated the repair halftime of ~17 min based on two HNC cell lines. The combined a/β, a and Td are a/β = 8.1 ± 4.1 Gy, a = 0.22 ± 0.08 Gy-1, Td = 4.0 ± 1.8 day, respectively. The prolonged IMRT dose delivery for entire HNC treatment course could possibly result in the loss of biological effectiveness, i.e., the target EUDs decreased by 11% with fraction dose delivery time varying from 5 to 30 min. We determined the sublethal damage repair halftime and other radiobiological parameters for HNC cells, and to evaluate treatment effectiveness of the prolonged dose delivery times associated with different IMRT techniques. The estimated repair halftime for HNC is relatively short and may be comparable to the step-and-shoot IMRT fraction dose delivery time. The effectiveness of IMRT treatment may be improved by reducing the fraction delivery time for HNC treatment.

The effect of stochastic fluctuation in radiation dose-rate on cell survival following fractionated radiation therapy

In radiobiological models, it is often assumed that the radiation dose rate remains constant during the course of radiation delivery. However, instantaneous radiation dose rate undergoes random (stochastic) temporal fluctuation. The effect of stochastic dose rate in fractionated radiation therapy is unknown and there has been no analytical formulation of stochastic dose-rate fluctuation effect in fractionated radiation therapy which we endeavor to pursue here. We have obtained the quantitative expression of cellular survival fraction considering stochastic temporal fluctuation or noise in dose rate. We have shown that the constant dose-rate approximation overestimates the survival fraction compared to that under stochastic dose rate in a fractionated radiation therapy situation and this overestimation effect increases appreciably with the increase in the fluctuation level in dose rate. However, for a given level of fluctuation in dose rate, overestimation of survival fraction also depends on the value of cellular radiation sensitivity parameter β and the repair rate of DNA lesion. This overestimation effect is higher for the cells which have a higher value of β parameter or have a lower repair rate. Our study draws attention to stochastic temporal fluctuation in the radiation dose rate and its potential contribution to cell survival following fractionated radiotherapy.

A mathematical study to select fractionation regimen based on physical dose distribution and the linear-quadratic model

PURPOSE

Hypofractionated irradiation is often used in precise radiotherapy instead of conventional multifractionated irradiation. We propose a novel mathematical method for selecting a hypofractionated or multifractionated irradiation regimen based on physical dose distribution adding to biologic consideration.

METHODS AND MATERIALS

The linear-quadratic model was used for the radiation effects on tumor and normal tissues, especially organs at risk (OARs). On the basis of the assumption that the OAR receives a fraction of the dose intended for the tumor, the minimization problem for the damage effect on the OAR was treated under the constraint that the radiation effect on the tumor is fixed.

RESULTS

For an N-time fractionated irradiation regimen, the constraint of tumor lethality was described by an N-dimensional hypersphere. The total dose of the fractionated irradiations was considered for minimizing the damage effect on the OAR under the hypersphere condition. It was found that the advantage of hypofractionated or multifractionated irradiation therapies depends on the magnitude of the ratio of α/β parameters for the OAR and tumor in the linear-quadratic model and the ratio of the dose for the OAR and tumor.

CONCLUSIONS

Our mathematical method shows that multifractionated irradiation with a constant dose is better if the ratio of α/β for the OAR and tumor is less than the ratio of the dose for the OAR and tumor, whereas hypofractionated irradiation is better otherwise.

The impact of microscopic disease on the tumor control probability in non-small-cell lung cancer

PURPOSE

To indicate which clinical target volume (CTV) margin (if any) is needed for an adequate treatment of non-small-cell lung cancer (NSCLC) using either 3D conformal or stereotactic radiotherapy, taking the distribution of the microscopic disease extension (MDE) into account.

METHODS AND MATERIALS

On the basis of the linear-quadratic biological model, a Monte-Carlo simulation was used to study the impact of MDE and setup deviations on the tumor control probability (TCP) after typical 3D conformal and stereotactic irradiation techniques. Setup deviations were properly accounted for in the planning target volume (PTV) margin. Previously measured distributions of MDE outside the macroscopic tumor in NSCLC patients were used. The dependence of the TCP on the CTV margins was quantified.

RESULTS

The presence of MDE had a demonstratable influence on the TCP in both the 3D conformal and the stereotactic technique when no CTV margins were employed. The impact of MDE on the TCP values was greater in the 3D conformal scenario (67% TCP with MDE; 84% TCP without MDE) than for stereotactic radiotherapy (91% TCP with MDE; 100% TCP without MDE). Accordingly, an increase of the CTV margin had the greatest impact for the 3D conformal technique. Larger setup errors, with appropriate PTV margins, lead to an increase in TCP for both techniques, showing the interdependence of CTV and PTV margins.

CONCLUSIONS

MDE may not always be eradicated by the beam penumbra or existing PTV margins using either 3D conformal or stereotactic radiotherapy. Nonetheless, TCP modeling indicates an overall local control rate above 90% for the stereotactic technique, while a non-zero CTV margin is recommended for better local control of MDE when using the 3D conformal technique.

Feasibility of dose painting using volumetric modulated arc optimization and delivery

PURPOSE

Dose painting strategies are limited by optimization algorithms in treatment planning systems and physical constraints of the beam delivery. We investigate dose conformity using the RapidArc optimizer and beam delivery technique. Furthermore, robustness of the plans with respect to positioning uncertainties are evaluated.

METHODS

A head & neck cancer patient underwent a [(61)Cu]Cu-ATSM PET/CT-scan. PET-SUVs were converted to prescribed dose with a base dose of 60 Gy, and target mean dose 90 Gy. The voxel-based prescription was converted into 3, 5, 7, 9, and 11 discrete prescription levels. Optimization was performed in Eclipse, varying the following parameters: MLC leaf width (5 mm and 2.5 mm), number of arcs (1 and 2) and collimator rotation (0, 15, 30 and 45 degrees). Dose conformity was evaluated using quality volume histograms (QVHs), and relative volumes receiving within ±5% of prescribed dose (Q(0.95-1.05)). Deliverability was tested using a Delta4(®) phantom. Robustness was tested by shifting the isocenter 1 mm and 2 mm in all directions, and recalculating the dose.

RESULTS

Good conformity was obtained using MLC leaf width 2.5 mm, two arcs, and collimators 45/315 degrees, with Q(0.95-1.05)=92.8%, 91.6%, 89.7% and 84.6%. Using only one arc or increasing the MLC leaf width had a small deteriorating effect of 2-5%. Small changes in collimator angle gave small changes, but large changes in collimator angle gave a larger decrease in plan conformity; for angles of 15 and 0 degrees (two arcs, 2.5 mm leaf width), Q(0.95-1.05) decreased by up to 15%. Consistency between planned and delivered dose was good, with ∼90% of gamma values <1. For 1 mm shift, Q(0.95-1.05) was decreased by 5-15%, while for 2 mm shift, Q(0.95-1.05) was decreased to 55-60%.

CONCLUSIONS

Results demonstrate feasibility of planning of prescription doses with multiple levels for dose painting using RapidArc, and plans were deliverable. Robustness to positional error was low.

The biological effectiveness of targeted radionuclide therapy based on a whole-body pharmacokinetic model

Biologically effective dose (BED) may be more of a relevant quantity than absorbed dose for establishing tumour response relationships. By taking into account the dose rate and tissue-specific parameters such as repair and radiosensitivity, it is possible to compare the relative biological effects of different targeted radionuclide therapy (TRT) agents. The aim of this work was to develop an analytical tumour BED calculation for TRT that could predict a relative biological effect based on normal body and tumour pharmacokinetics. This work represents a step in the direction of establishing relative pharmacokinetic criteria of when the BED formalism is more applicable than absorbed dose for TRT. A previously established pharmacokinetic (PK) model for TRT was used and adapted into the BED formalism. An analytical equation for the protraction factor, which incorporates dose rate and repair rate, was derived. Dose rates within the normal body and tumour were related to the slopes of their time-activity curves which were determined by the ratios of their respective PK parameters. The relationships between the tumour influx-to-efflux ratio (k(34):k(43)), central compartment efflux-to-influx ratio (k(12):k(21)), central elimination (k(el)), and tumour repair rate (μ), and tumour BED were investigated. As the k(34):k(43) ratio increases and the k(12):k(21) ratio decreases, the difference between tumour BED and D increases. In contrast, as the k(34):k(43) ratios decrease and the k(12):k(21) ratios increase, the tumour BED approaches D. At large k(34):k(43) ratios, the difference between tumour BED and D increases to a maximum as k(el) increases. At small k(34):k(43) ratios, the tumour BED approaches D at very small k(el). At small μ and small k(34):k(43) ratios, the tumour BED approaches D. For large k(34):k(43) ratios, large μ values cause tumour BED to approach D. This work represents a step in the direction of establishing relative PK criteria of when the BED formalism is more applicable than absorbed dose for TRT. It also provides a framework by which the biological effects of different TRT agents can be compared in order to predict efficacy.

Phase I study of accelerated conformal radiotherapy for stage I non-small-cell lung cancer in patients with pulmonary dysfunction: CALGB 39904

PURPOSE

The optimal treatment for medically inoperable stage I non-small-cell lung cancer (NSCLC) has not been defined.

PATIENTS AND METHODS

Cancer and Leukemia Group B trial 39904 prospectively assessed accelerated, once-daily, three-dimensional radiotherapy for early-stage NSCLC. The primary objectives were to define the maximally accelerated course of conformal radiotherapy and to describe the short-term and long-term toxicity of therapy. Entry was limited to patients with clinical stage T1N0 or T2N0 NSCLC (< 4 cm) and pulmonary dysfunction. The nominal total radiotherapy dose remained at 70 Gy, while the number of daily fractions in each successive cohort was reduced.

RESULTS

Thirty-nine eligible patients were accrued (eight patients each on cohorts 1 to 4 and seven patients on cohort 5) between January 2001 and July 2005. One grade 3 nonhematologic toxicity was observed in both cohort 3 (dyspnea) and cohort 4 (pain). The major response rate was 77%. After a median follow-up time of 53 months, the actuarial median survival time of all eligible patients was 38.5 months. Local relapse was observed in three patients.

CONCLUSION

Accelerated conformal radiotherapy was well tolerated in a high-risk population with clinical stage I NSCLC. Outcomes are comparable to prospective reports of alternative therapies, including stereotactic body radiation therapy and limited resection, with less apparent severe toxicity. Further investigation of this approach is warranted.

SORS: a new software for the simulation of radiotherapy schedule

We present a software for choosing the best radiotherapy treatment schedule for head and neck cancers as a beginning radiotherapy plan or a temporarily interrupted plan. Its application occurs according to two modalities: the first adopts the best estimates for model parameters; the second takes into account the parameters' uncertainty too. In both cases, the choice becomes the schedule with the highest uncomplicated tumor control probability (UTCP). In the UTCP valuation, the normal tissue complication probability (NTCP) of each organ is related to the gravity of its possible late injury. For NTCP calculation, it has been adopted the empirical LKB (Lyman-Kutcher-Burman) model corrected for dose/fraction via linear-quadratic model and the incomplete repair effect. The tumor control probability (TCP) model is Poisson based and contains corrections for dose/fraction and regrowth effect; optionally, it can be accounted for the incomplete repair effect as well. At the end of processing, a detailed file with all informations about UTCP, TCP and single organ NTCP is furnished for every examined schedule. Moreover, a useful 3-D graphic representation of the schedule's UTCP is available, allowing the physician to easily understand the schedules with the highest radiotherapeutic efficacy. The open source characteristic allows the program to adapt to the individual clinical case as well as to be a valid support in radiobiological research.