The use of biologically related model (Eclipse) for the intensity-modulated radiation therapy planning of nasopharyngeal carcinomas

Direct incorporation of patient-specific efficacy and toxicity estimates in radiation therapy plan optimization

PURPOSE

Current radiation therapy (RT) treatment planning relies mainly on pre-defined dose-based objectives and constraints to develop plans that aim to control disease while limiting damage to normal tissues during treatment. These objectives and constraints are generally population-based, in that they are developed from the aggregate response of a broad patient population to radiation. However, correlations of new biologic markers and patient-specific factors to treatment efficacy and toxicity provide the opportunity to further stratify patient populations and develop a more individualized approach to RT planning. We introduce a novel intensity-modulated radiation therapy (IMRT) optimization strategy that directly incorporates patient-specific dose response models into the planning process. In this strategy, we integrate the concept of utility-based planning where the optimization objective is to maximize the predicted value of overall treatment utility, defined by the probability of efficacy (e.g., local control) minus the weighted sum of toxicity probabilities. To demonstrate the feasibility of the approach, we apply the strategy to treatment planning for non-small cell lung cancer (NSCLC) patients.

METHODS AND MATERIALS

We developed a prioritized approach to patient-specific IMRT planning. Using a commercial treatment planning system (TPS), we calculate dose based on an influence matrix of beamlet-dose contributions to regions-of-interest. Then, outside of the TPS, we hierarchically solve two optimization problems to generate optimal beamlet weights that can then be imported back to the TPS. The first optimization problem maximizes a patient's overall plan utility subject to typical clinical dose constraints. In this process, we facilitate direct optimization of efficacy and toxicity trade-off based on individualized dose-response models. After optimal utility is determined, we solve a secondary optimization problem that minimizes a conventional dose-based objective subject to the same clinical dose constraints as the first stage but with the addition of a constraint to maintain the optimal utility from the first optimization solution. We tested this method by retrospectively generating plans for five previously treated NSCLC patients and comparing the prioritized utility plans to conventional plans optimized with only dose metric objectives. To define a plan utility function for each patient, we utilized previously published correlations of dose to local control and grade 3-5 toxicities that include patient age, stage, microRNA levels, and cytokine levels, among other clinical factors.

RESULTS

The proposed optimization approach successfully generated RT plans for five NSCLC patients that improve overall plan utility based on personalized efficacy and toxicity models while accounting for clinical dose constraints. Prioritized utility plans demonstrated the largest average improvement in local control (16.6%) when compared to plans generated with conventional planning objectives. However, for some patients, the utility-based plans resulted in similar local control estimates with decreased estimated toxicity.

CONCLUSION

The proposed optimization approach, where the maximization of a patient's RT plan utility is prioritized over the minimization of standardized dose metrics, has the potential to improve treatment outcomes by directly accounting for variability within a patient population. The implementation of the utility-based objective function offers an intuitive, humanized approach to biological optimization in which planning trade-offs are explicitly optimized.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Paradigm Shift in Radiation Treatment Planning Over Multiple Treatment Modalities

The inverse planning simulated annealing optimization engine was used to develop a new method of incorporating biological parameters into radiation treatment planning. This method integrates optimization of a radiation schedule over multiple types of delivery methods into a single algorithm. We demonstrate a general procedure of incorporating a functional biological dose model into the calculation of physical dose prescriptions. This paradigm differs from current practice in that it combines biology-informed dose constraints with a physical dose optimizer allowing for the comparison of treatment plans across multiple different radiation types and fractionation schemes.

Comparisons of normal tissue complication probability models derived from planned and delivered dose for head and neck cancer patients

BACKGROUND AND PURPOSE

Normal tissue complication probability (NTCP) models are typically derived from the planned dose distribution, which can deviate from the delivered dose due to anatomical day-to-day variations. The aim of this study was to compare NTCP models derived from the planned and the delivered dose for head and neck cancer (HNC) patients.

MATERIAL AND METHOD

322 HNC patients who received radiotherapy with daily CBCT guidance were included in this retrospective study. The delivered dose was estimated by deformably accumulating dose from daily CBCT to planning anatomy. We used a Lyman-Kutcher-Burman NTCP model, to relate the equivalent uniform dose (EUD) of organs at risk (OAR) with oral mucositis, xerostomia and dysphagia respectively. We compared the model parameters and performances.

RESULTS

The median differences between planned and delivered EUD to the OARs were significantly larger for patients with toxicity than without for acute dysphagia (≥G2 and ≥G3) and late dysphagia (≥G3) (p < 0.05). Those differences resulted in small differences in steepness and agreement to the data between delivered- and planned-fitted NTCP curves, and the differences were not significant. The differences in AUC were less than 0.01.

CONCLUSION

Differences between delivered and planned dose did not lead to significant differences in NTCP curves. The additional clinical relevance of NTCP models using accumulated dose for oral mucositis, xerostomia and dysphagia in HNC radiotherapy is likely to be limited.

Research Goal-Driven Data Model and Harmonization for De-Identifying Patient Data in Radiomics

There are various efforts in de-identifying patient's radiation oncology data for their uses in the advancement of research in medicine. Though the task of de-identification needs to be defined in the context of research goals and objectives, existing systems lack the flexibility of modeling data and normalization of names of attributes for accomplishing them. In this work, we describe a de-identification process of radiation and clinical oncology data, which is guided by a data model and a schema of dynamically capturing domain ontology and normalization of terminologies, defined in tune with the research goals in this area. The radiological images are obtained in DICOM format. It consists of diagnostic, radiation therapy (RT) treatment planning, RT verification, and RT response images. During the DICOM de-identification, a few crucial pieces of information are taken about the dataset. The proposed model is generic in organizing information modeling in sync with the de-identification of a patient's clinical information. The treatment and clinical data are provided in the comma-separated values (CSV) format, which follows a predefined data structure. The de-identified data is harmonized throughout the entire process. We have presented four specific case studies on four different types of cancers, namely glioblastoma multiforme, head-neck, breast, and lung. We also present experimental validation on a few patients' data in these four areas. A few aspects are taken care of during de-identification, such as preservation of longitudinal date changes (LDC), incremental de-identification, referential data integrity between the clinical and image data, de-identified data harmonization, and transformation of the data to an underlined database schema.

Radiobiological assessment of nasopharyngeal cancer IMRT using various collimator angles and non-coplanar fields

Aim:

The aim of this study was to evaluate clinical efficacy and radiobiological outcome of intensity-modulated radiation therapy (IMRT) modalities using various collimator angles and non-coplanar fields for nasopharyngeal cancer (NPC).

Materials and methods:

A 70-Gy planning target volume dose was administered for 30 NPC patients referred for IMRT. Standard IMRT plans were constructed based on the target and organs at risk (OARs) volume; and dose constraints recommended by Radiation Therapy Oncology Group (RTOG). Using various collimator angles and non-coplanar fields, 11 different additional IMRT protocols were investigated. Homogeneity indexes (HIs) and conformation numbers (CNs) were calculated. Poisson and relative seriality models were utilised for estimating tumour control probability (TCP) and normal tissue complication probabilities (NTCPs), respectively.

Results:

Various collimator angles and non-coplanar fields had no significant effect on HI, CN and TCP, while significant effects were noted for some OARs, with a maximum mean dose (Dmax). No significant differences were observed among the calculated NTCPs of all the IMRT protocols. However, the protocol with 10° collimator angle (for five fields out of seven) and 8° couch angle had the lowest NTCP. Furthermore, the standard and some of non-coplanar IMRT protocols led to the reduction in OARs Dmax.

Conclusions:

Using appropriate standard/non-coplanar IMRT protocols for NPC treatment could potentially reduce the dose to the OARs and the probability of inducing secondary cancer in patients.

Split Common Coincidence Point Problem: A Formulation Applicable to (Bio)Physically-Based Inverse Planning Optimization

Inverse planning is a method of radiotherapy treatment planning where the care team begins with the desired dose distribution satisfying prescribed clinical objectives, and then determines the treatment parameters that will achieve it. The variety in symmetry, form, and characteristics of the objective functions describing clinical criteria requires a flexible optimization approach in order to obtain optimized treatment plans. Therefore, we introduce and discuss a nonlinear optimization formulation called the split common coincidence point problem (SCCPP). We show that the SCCPP is a suitable formulation for the inverse planning optimization problem with the flexibility of accommodating several biological and/or physical clinical objectives. Also, we propose an iterative algorithm for approximating the solution of the SCCPP, and using Bregman techniques, we establish that the proposed algorithm converges to a solution of the SCCPP and to an extremum of the inverse planning optimization problem. We end with a note on useful insights on implementing the algorithm in a clinical setting.

De-Identification of Radiomics Data Retaining Longitudinal Temporal Information

We propose a de-identification system which runs in a standalone mode. The system takes care of the de-identification of radiation oncology patient's clinical and annotated imaging data including RTSTRUCT, RTPLAN, and RTDOSE. The clinical data consists of diagnosis, stages, outcome, and treatment information of the patient. The imaging data could be the diagnostic, therapy planning, and verification images. Archival of the longitudinal radiation oncology verification images like cone beam CT scans along with the initial imaging and clinical data are preserved in the process. During the de-identification, the system keeps the reference of original data identity in encrypted form. These could be useful for the re-identification if necessary.

Temporal lobe microstructural abnormalities in patients with nasopharyngeal carcinoma quantitatively evaluated by high-resolution DWI and DKI after concurrent chemoradiotherapy

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DKI could detect early radiation-induced microstructural abnormalities after CCRT.

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The ADC, Dmean, and FA of temporal lobe showed a unique time-dependent trajectory.

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Kmean might be more sensitive to detection of effects in the late delayed phases.

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White and grey matter all underwent microstructural changes after radiotherapy.

Purpose

To investigate temporal lobe microstructural abnormalities and neurocognitive function impairment after concurrent chemoradiotherapy (CCRT) in patients with nasopharyngeal carcinoma (NPC).

Methods

NPC patients who underwent CCRT were enrolled. High-resolution diffusion-weighted imaging (DWI) magnetic resonance imaging (MRI) and diffusion-kurtosis imaging (DKI) MRI, were performed 5 times per patient (once pre-CCRT, 1 week post-CCRT, 3 months post-CCRT, 6 months post-CCRT, and 12 months post-CCRT). Neurocognitive function was evaluated by Montreal Neurocognitive Assessment (MoCA) twice per patient, once pre-CCRT, and once 12-months after CCRT.

Results

Of 111 patients, 56 completed the entire protocol. The MRI derived apparent diffusion coefficient (ADC), mean of diffusion coefficient (Dmean) and fractional anisotropy (FA) values were significantly decreased (p < 0.05) over the 0–3 month period following CCRT and significantly increased (p < 0.05) over the 3–12 month period following CCRT. The mean of kurtosis coefficient (Kmean) continued to decline over a year post-CCRT. All parameters reveal more pronounced changes in white matter (WM) than in grey matter (GM). MoCA also declined after CCRT (p < 0.001). MoCA showed significant positive correlation with Kmean-WM-6 m, Kmean-WM-12 m and ΔKmean-WM.

Conclusions

High-resolution DWI and DKI should be considered as a promising method for the investigation of temporal lobe microstructural change in NPC patients after CCRT.

Using biologically based objectives to optimize boost intensity-modulated radiation therapy planning for brainstem tumors in dogs

Irradiated brain tumors commonly progress at the primary site, generating interest in focal dose escalation. The aim of this retrospective observational study was to use biological optimization objectives for a modeling exercise with simultaneously‐integrated boost IMRT (SIB‐IMRT) to generate a dose‐escalated protocol with acceptable late radiation toxicity risk estimate and improve tumor control for brainstem tumors in dogs safely. We re‐planned 20 dog brainstem tumor datasets with SIB‐IMRT, prescribing 20 × 2.81 Gy to the gross tumor volume (GTV) and 20 × 2.5 Gy to the planning target volume. During the optimization process, we used biologically equivalent generalized equivalent uniform doses (gEUD) as planning aids. These were derived from human data, calculated to adhere to normal tissue complication probability (NTCP) ≤5%, and converted to the herein used fractionation schedule. We extracted the absolute organ at risk dose‐volume histograms to calculate NTCP of each individual plan. For planning optimization, gEUD_{(a = 4)} = 39.8 Gy for brain and gEUD_{(a = 6.3)} = 43.8 Gy for brainstem were applied. Mean brain NTCP was low with 0.43% (SD ±0.49%, range 0.01‐2.04%); mean brainstem NTCP was higher with 7.18% (SD ±4.29%, range 2.87‐20.72%). Nevertheless, NTCP of < 10% in brainstem was achievable in 80% (16/20) of dogs. Spearman's correlation between relative GTV and NTCP was high (ρ = 0.798, P < .001), emphasizing increased risk with relative size even with subvolume‐boost. Including biologically based gEUD values into optimization allowed estimating NTCP during the planning process. In conclusion, gEUD‐based SIB‐IMRT planning resulted in dose‐escalated treatment plans with acceptable risk estimate of NTCP < 10% in the majority of dogs with brainstem tumors. Risk was correlated with relative tumor size.

Comparison of three and four-field radiotherapy technique and the effect of laryngeal shield on vocal and spinal cord radiation dose in radiotherapy of non-laryngeal head and neck tumors

Introduction: Due to the effect of radiation on both the tumor and the surrounding normal tissues, the side effects of radiation in normal tissues are expected. One of the important complications in the head and neck radiotherapy is the doses reached to the larynx and spinal cord of patients with non-laryngeal head and neck tumors.

Materials and Methods: In this study, CT scan images of 25 patients with non-laryngeal tumors including; lymph nodes, tongue, oropharynx and nasopharynx were used. A three-field and a four-field treatment planning with and without laryngeal shield in 3D CRT technique were planned for each patient. Subsequently, the values of Dmin, Dmean, Dmax and Dose Volume Histogram from the treatment planning system and NTCP values of spinal cord and larynx were calculated with BIOPLAN and MATLAB software for all patients.

Results: Statistical results showed that mean values of doses of larynx in both three and four-field methods were significantly different between with and without shield groups. Comparison of absorbed dose didn’t show any difference between the three and four field methods (P>0.05). Using Shield, just the mean and minimum doses of spinal cord decreased in both three and four fields. The NTCP of the spinal cord and larynx by three and four-field methods with shield in the LKB and EUD models significantly are less than that of the three and four fields without shields, and in the four-field method NTCP of larynx is less than three radiation field.

Conclusion: The results of this study indicate that there is no significant difference in doses reached to larynx and spinal cord between the treatments techniques, but laryngeal shield reduce dose and NTCP values in larynx considerably.

Radiobiological Optimization in Lung Stereotactic Body Radiation Therapy: Are We Ready to Apply Radiobiological Models?

Lung tumors are often associated with a poor prognosis although different schedules and treatment modalities have been extensively tested in the clinical practice. The complexity of this disease and the use of combined therapeutic approaches have been investigated and the use of high dose-rates is emerging as effective strategy. Technological improvements of clinical linear accelerators allow combining high dose-rate and a more conformal dose delivery with accurate imaging modalities pre- and during therapy. This paper aims at reporting the state of the art and future direction in the use of radiobiological models and radiobiological-based optimizations in the clinical practice for the treatment of lung cancer. To address this issue, a search was carried out on PubMed database to identify potential papers reporting tumor control probability and normal tissue complication probability for lung tumors. Full articles were retrieved when the abstract was considered relevant, and only papers published in English language were considered. The bibliographies of retrieved papers were also searched and relevant articles included. At the state of the art, dose–response relationships have been reported in literature for local tumor control and survival in stage III non-small cell lung cancer. Due to the lack of published radiobiological models for SBRT, several authors used dose constraints and models derived for conventional fractionation schemes. Recently, several radiobiological models and parameters for SBRT have been published and could be used in prospective trials although external validations are recommended to improve the robustness of model predictive capability. Moreover, radiobiological-based functions have been used within treatment planning systems for plan optimization but the advantages of using this strategy in the clinical practice are still under discussion. Future research should be directed toward combined regimens, in order to potentially improve both local tumor control and survival. Indeed, accurate knowledge of the relevant parameters describing tumor biology and normal tissue response is mandatory to correctly address this issue. In this context, the role of medical physicists and the AAPM in the development of radiobiological models is crucial for the progress of developing specific tool for radiobiological-based optimization treatment planning.

On the gEUD biological optimization objective for organs at risk in Photon Optimizer of Eclipse treatment planning system

Inverse planning optimization using biologically based objectives is becoming part of the intensity modulated optimization process. The performances and efficacy of the biologically based gEUD (generalized Equivalent Uniform Dose) objective implemented in the Photon Optimizer (PO) of Varian Eclipse treatment planning system have been here analyzed. gEUD is associated with the parameter a that accounts for the seriality of a structure, being higher for more serial organs. The PO was used to optimize volumetric modulated arc therapy (VMAT) plans on a virtual homogeneous cylindrical phantom presenting a target and an organ at risk (OAR). The OAR was placed at 4 mm, 1 and 2 cm distance, or cropped at 0, 2 and 4 mm from the target. Homogeneous target dose of 60 Gy in 20 fractions was requested with physical dose-volume objectives, while OAR dose was minimized with the upper gEUD objective. The gEUD specific a parameter was varied from 0.1 to 40 to assess its impact to OAR sparing and target coverage. Actual head and neck and prostate cases, with one parotid and the rectum as test OAR, were also analyzed to translate the results in the more complex clinical environment. Increasing the a parameter value in the gEUD objective, the optimization achieved lower volumes of the OAR which received the highest dose levels. The maximum dose in the OAR was minimized well with a values up to 20, while further increase of a to 40 did not further improve the result. The OAR mean dose was reduced for the OAR located at 1 and 2 cm distance from the target, enforced with increasing a. For cropped OARs, a mean dose reduction was achieved for a values up to 3-5, but mean dose increased for higher a values. The optimal choice of the parameter a depends on the mutual OAR and target position, and seriality of the organ. Today no significant compendium of clinical and biological specific a and gEUD values are available for a wide range of OARs.

Three-dimensional dose prediction and validation with the radiobiological gamma index based on a relative seriality model for head-and-neck IMRT

This study proposes a quality assurance (QA) method incorporating radiobiological factors based on the QUANTEC-determined tumor control probability and the normal tissue complication probability (NTCP) of head-and-neck intensity-modulated radiation therapy (HN-IMRT). Per-beam measurements were conducted for 20 cases using a 2D detector array. Three-dimensional predicted dose distributions within targets and organs at risk were reconstructed based on the per-beam QA results derived from differences between planned and measured doses. Under the predicted dose distributions, the differences between the physical and radiobiological gamma indices (PGI and RGI, respectively) based on the relative seriality (RS) model were evaluated. The NTCP values in the RS and Niemierko models were compared. The dose covers 98% (D98%) of the clinical target volume (CTV) decreased by 3.2% (P < 0.001), and the mean dose of the ipsilateral parotid increased by 6.3% (P < 0.001) compared with the original dose. RGI passing rates in the CTV and brain stem were greater than PGI ones by 5.8% (P < 0.001) and 2.0% (P < 0.001), respectively. The RS model's average NTCP values for the ipsilateral and contralateral parotids under the original dose were smaller than those of the Niemierko model by 9.0% (P < 0.001) and 7.0% (P < 0.001), respectively. The 3D predicted dose evaluation with RGI based on the RS model was introduced for QA of HN-IMRT, leading to dose evaluation for each organ with consideration of the radiobiological effect. This method constitutes a rational way to perform QA of HN-IMRT in clinical practice.

An integrated strategy of biological and physical constraints in biological optimization for cervical carcinoma

Background

For cervical carcinoma cases, this study aimed to evaluate the quality of intensity-modulated radiation therapy (IMRT) plans optimized by biological constraints. Furthermore, a new integrated strategy in biological planning module was proposed and verified.

Methods

Twenty patients of advanced stage cervical carcinoma were enrolled in this study. For each patient, dose volume optimization (DVO), biological model optimization (BMO) and integrated strategy optimization (ISO) plans were created using same treatment parameters. Different biological models were also used for organ at risk (OAR) in BMO plans, which include the LKB and Poisson models. Next, BMO plans were compared with their corresponding DVO plans, in order to evaluate BMO plan quality. ISO plans were also compared with DVO and BMO plans, in order to verify the performance of the integrated strategy.

Results

BMO plans produced slightly inhomogeneity and less coverage of planning target volume (PTV) (V95=96.79, HI = 0.10: p < 0.01). However, the tumor control probability (TCP) value, both from DVO and BMO plans, were comparable. For the OARs, BMO plans produced lower normal tissue complication probability (NTCP) of rectum (NTCP = 0.11) and bladder (NTCP = 0.14) than in the corresponding DVO plans (NTCP = 0.19 and 0.18 for rectum and bladder; p < 0.01 for rectum and p = 0.03 for bladder). V95, D98, CI and HI values that were produced by ISO plans (V95 = 98.31, D98 = 54.18Gy, CI = 0.76, HI = 0.09) were greatly better than BMO plans (V95 = 96.79, D98 = 53.42Gy, CI = 0.71, HI = 0.10) with significant differences. Furthermore, ISO plans produced lower NTCP values of rectum (NTCP = 0.14) and bladder (NTCP = 0.16) than DVO plans (NTCP = 0.19 and 0.18 for rectum and bladder, respectively) with significant differences.

Conclusions

BMO plans produced lower NTCP values of OARs compared to DVO plans for cervical carcinoma cases, and resulted in slightly less target coverage and homogeneity. The integrated strategy, proposed in this study, could improve the coverage, conformity and homogeneity of PTV greater than the BMO plans, as well as reduce the NTCP values of OARs greater than the DVO plans.

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.

Multivariable normal tissue complication probability model-based treatment plan optimization for grade 2-4 dysphagia and tube feeding dependence in head and neck radiotherapy

BACKGROUND AND PURPOSE

Radiotherapy of the head and neck is challenged by the relatively large number of organs-at-risk close to the tumor. Biologically-oriented objective functions (OF) could optimally distribute the dose among the organs-at-risk. We aimed to explore OFs based on multivariable normal tissue complication probability (NTCP) models for grade 2-4 dysphagia (DYS) and tube feeding dependence (TFD).

MATERIALS AND METHODS

One hundred head and neck cancer patients were studied. Additional to the clinical plan, two more plans (an OF_DYS and OF_TFD-plan) were optimized per patient. The NTCP models included up to four dose-volume parameters and other non-dosimetric factors. A fully automatic plan optimization framework was used to optimize the OF_NTCP-based plans.

RESULTS

All OF_NTCP-based plans were reviewed and classified as clinically acceptable. On average, the Δdose and ΔNTCP were small comparing the OF_DYS-plan, OF_TFD-plan, and clinical plan. For 5% of patients NTCP_TFD reduced >5% using OF_TFD-based planning compared to the OF_DYS-plans.

CONCLUSIONS

Plan optimization using NTCP_DYS- and NTCP_TFD-based objective functions resulted in clinically acceptable plans. For patients with considerable risk factors of TFD, the OF_TFD steered the optimizer to dose distributions which directly led to slightly lower predicted NTCP_TFD values as compared to the other studied plans.