Limited Impact of Setup and Range Uncertainties, Breathing Motion, and Interplay Effects in Robustly Optimized Intensity Modulated Proton Therapy for Stage III Non-small Cell Lung Cancer.

PURPOSE: To investigate the impact of setup and range uncertainties, breathing motion, and interplay effects using scanning pencil beams in robustly optimized intensity modulated proton therapy (IMPT) for stage III non-small cell lung cancer (NSCLC). METHODS AND MATERIALS: Three-field IMPT plans were created using a minimax robust optimization technique for 10 NSCLC patients. The plans accounted for 5- or 7-mm setup errors with ±3% range uncertainties. The robustness of the IMPT nominal plans was evaluated considering (1) isotropic 5-mm setup errors with ±3% range uncertainties; (2) breathing motion; (3) interplay effects; and (4) a combination of items 1 and 2. The plans were calculated using 4-dimensional and average intensity projection computed tomography images. The target coverage (TC, volume receiving 95% of prescribed dose) and homogeneity index (D2 - D98, where D2 and D98 are the least doses received by 2% and 98% of the volume) for the internal clinical target volume, and dose indexes for lung, esophagus, heart and spinal cord were compared with that of clinical volumetric modulated arc therapy plans. RESULTS: The TC and homogeneity index for all plans were within clinical limits when considering the breathing motion and interplay effects independently. The setup and range uncertainties had a larger effect when considering their combined effect. The TC decreased to <98% (clinical threshold) in 3 of 10 patients for robust 5-mm evaluations. However, the TC remained >98% for robust 7-mm evaluations for all patients. The organ at risk dose parameters did not significantly vary between the respective robust 5-mm and robust 7-mm evaluations for the 4 error types. Compared with the volumetric modulated arc therapy plans, the IMPT plans showed better target homogeneity and mean lung and heart dose parameters reduced by about 40% and 60%, respectively. CONCLUSIONS: In robustly optimized IMPT for stage III NSCLC, the setup and range uncertainties, breathing motion, and interplay effects have limited impact on target coverage, dose homogeneity, and organ-at-risk dose parameters.

Robust Intensity Modulated Proton Therapy (IMPT) Increases Estimated Clinical Benefit in Head and Neck Cancer Patients.

PURPOSE: To compare the clinical benefit of robust optimized Intensity Modulated Proton Therapy (minimax IMPT) with current photon Intensity Modulated Radiation Therapy (IMRT) and PTV-based IMPT for head and neck cancer (HNC) patients. The clinical benefit is quantified in terms of both Normal Tissue Complication Probability (NTCP) and target coverage in the case of setup and range errors. METHODS AND MATERIALS: For 10 HNC patients, PTV-based IMRT (7 fields), minimax and PTV-based IMPT (2, 3, 4, 5 and 7 fields) plans were tested on robustness. Robust optimized plans differed from PTV-based plans in that they target the CTV and penalize possible error scenarios, instead of using the static isotropic CTV-PTV margin. Perturbed dose distributions of all plans were acquired by simulating in total 8060 setup (±3.5 mm) and range error (±3%) combinations. NTCP models for xerostomia and dysphagia were used to predict the clinical benefit of IMPT versus IMRT. RESULTS: The robustness criterion was met in the IMRT and minimax IMPT plans in all error scenarios, but this was only the case in 1 of 40 PTV-based IMPT plans. Seven (out of 10) patients had relatively large NTCP reductions in minimax IMPT plans compared to IMRT. For these patients, xerostomia and dysphagia NTCP values were reduced by 17.0% (95% CI; 13.0-21.1) and 8.1% (95% CI; 4.9-11.2) on average with minimax IMPT. Increasing the number of fields did not contribute to plan robustness, but improved organ sparing. CONCLUSIONS: The estimated clinical benefit in terms of NTCP of robust optimized (minimax) IMPT is greater than that of IMRT and PTV-based IMPT in HNC patients. Furthermore, the target coverage of minimax IMPT plans in the presence of errors was comparable to IMRT plans.

Multicriteria optimization enables less experienced planners to efficiently produce high quality treatment plans in head and neck cancer radiotherapy.

OBJECTIVES: To demonstrate that novice dosimetry planners efficiently create clinically acceptable IMRT plans for head and neck cancer (HNC) patients using a commercially available multicriteria optimization (MCO) system. METHODS: Twenty HNC patients were enrolled in this in-silico comparative planning study. Per patient, novice planners with less experience in dosimetry planning created an IMRT plan using an MCO system (RayStation). Furthermore, a conventionally planned clinical IMRT plan was available (Pinnacle(3)). All conventional IMRT and MCO-plans were blind-rated by two expert radiation-oncologists in HNC, using a 5-point scale (1-5 with 5 the highest score) assessment form comprising 10 questions. Additionally, plan quality was reported in terms of planning time, dosimetric and normal tissue complication probability (NTCP) comparisons. Inter-rater reliability was derived using the intra-class correlation coefficient (ICC). RESULTS: In total, the radiation-oncologists rated 800 items on plan quality. The overall plan score indicated no differences between both planning techniques (conventional IMRT: 3.8 ± 1.2 vs. MCO: 3.6 ± 1.1, p = 0.29). The inter-rater reliability of all ratings was 0.65 (95% CI: 0.57-0.71), indicating substantial agreement between the radiation-oncologists. In 93% of cases, the scoring difference of the conventional IMRT and MCO-plans was one point or less. Furthermore, MCO-plans led to slightly higher dose uniformity in the therapeutic planning target volume, to a lower integral body dose (13.9 ± 4.5 Gy vs. 12.9 ± 4.0 Gy, p < 0.001), and to reduced dose to the contra-lateral parotid gland (28.1 ± 11.8 Gy vs. 23.0 ± 11.2 Gy, p < 0.002). Consequently, NTCP estimates for xerostomia reduced by 8.4 ± 7.4% (p < 0.003). The hands-on time of the conventional IMRT planning was approximately 205 min. The time to create an MCO-plan was on average 43 ± 12 min. CONCLUSIONS: MCO planning enables novice treatment planners to create high quality IMRT plans for HNC patients. Plans were created with vastly reduced planning times, requiring less resources and a short learning curve.

Direct use of multivariable normal tissue complication probability models in treatment plan optimisation for individualised head and neck cancer radiotherapy produces clinically acceptable treatment plans.

BACKGROUND AND PURPOSE: Recently, clinically validated multivariable normal tissue complication probability models (NTCP) for head and neck cancer (HNC) patients have become available. We test the feasibility of using multivariable NTCP-models directly in the optimiser for inverse treatment planning of radiotherapy to improve the dose distributions and corresponding NTCP-estimates in HNC patients. MATERIAL AND METHODS: For 10 HNC cases, intensity-modulated radiotherapy plans were optimised either using objective functions based on the 'generalised equivalent uniform dose' (OFgEUD) or based on multivariable NTCP-models (OFNTCP). NTCP-models for patient-rated xerostomia, physician-rated RTOG grade II-IV dysphagia, and various patient-rated aspects of swallowing dysfunction were incorporated. The NTCP-models included dose-volume parameters as well as clinical factors contributing to a personalised optimisation process. Both optimisation techniques were compared by means of 'pseudo Pareto fronts' (target dose conformity vs. the sum of the NTCPs). RESULTS: Both optimisation techniques resulted in clinically realistic treatment plans with only small differences. For nine patients the sum-NTCP was lower for the OFNTCP optimised plans (on average 5.7% (95%CI 1.7-9.9%, p<0.006)). Furthermore, the OFNTCP provided the advantages of fewer unknown optimisation parameters and an intrinsic mechanism of individualisation. CONCLUSIONS: Treatment plan optimisation using multivariable NTCP-models directly in the OF is feasible as has been demonstrated for HNC radiotherapy.

Evaluation of DVH-based treatment plan verification in addition to gamma passing rates for head and neck IMRT.

BACKGROUND AND PURPOSE: Treatment plan verification of intensity modulated radiotherapy (IMRT) is generally performed with the gamma index (GI) evaluation method, which is difficult to extrapolate to clinical implications. Incorporating Dose Volume Histogram (DVH) information can compensate for this. The aim of this study was to evaluate DVH-based treatment plan verification in addition to the GI evaluation method for head and neck IMRT. MATERIALS AND METHODS: Dose verifications of 700 subsequent head and neck cancer IMRT treatment plans were categorised according to gamma and DVH-based action levels. Fractionation dependent absolute dose limits were chosen. The results of the gamma- and DVH-based evaluations were compared to the decision of the medical physicist and/or radiation oncologist for plan acceptance. RESULTS: Nearly all treatment plans (99.7%) were accepted for treatment according to the GI evaluation combined with DVH-based verification. Two treatment plans were re-planned according to DVH-based verification, which would have been accepted using the evaluation alone. DVH-based verification increased insight into dose delivery to patient specific structures increasing confidence that the treatment plans were clinically acceptable. Moreover, DVH-based action levels clearly distinguished the role of the medical physicist and radiation oncologist within the Quality Assurance (QA) procedure. CONCLUSIONS: DVH-based treatment plan verification complements the GI evaluation method improving head and neck IMRT-QA.

The effects of computed tomography image characteristics and knot spacing on the spatial accuracy of B-spline deformable image registration in the head and neck geometry.

OBJECTIVES: To explore the effects of computed tomography (CT) image characteristics and B-spline knot spacing (BKS) on the spatial accuracy of a B-spline deformable image registration (DIR) in the head-and-neck geometry. METHODS: The effect of image feature content, image contrast, noise, and BKS on the spatial accuracy of a B-spline DIR was studied. Phantom images were created with varying feature content and varying contrast-to-noise ratio (CNR), and deformed using a known smooth B-spline deformation. Subsequently, the deformed images were repeatedly registered with the original images using different BKSs. The quality of the DIR was expressed as the mean residual displacement (MRD) between the known imposed deformation and the result of the B-spline DIR.Finally, for three patients, head-and-neck planning CT scans were deformed with a realistic deformation field derived from a rescan CT of the same patient, resulting in a simulated deformed image and an a-priori known deformation field. Hence, a B-spline DIR was performed between the simulated image and the planning CT at different BKSs. Similar to the phantom cases, the DIR accuracy was evaluated by means of MRD. RESULTS: In total, 162 phantom registrations were performed with varying CNR and BKSs. MRD-values < 1.0 mm were observed with a BKS between 10-20 mm for image contrast ≥ ± 250 HU and noise < ± 200 HU. Decreasing the image feature content resulted in increased MRD-values at all BKSs. Using BKS = 15 mm for the three clinical cases resulted in an average MRD < 1.0 mm. CONCLUSIONS: For synthetically generated phantoms and three real CT cases the highest DIR accuracy was obtained for a BKS between 10-20 mm. The accuracy decreased with decreasing image feature content, decreasing image contrast, and higher noise levels. Our results indicate that DIR accuracy in clinical CT images (typical noise levels < ± 100 HU) will not be effected by the amount of image noise.

Differences in delineation guidelines for head and neck cancer result in inconsistent reported dose and corresponding NTCP.

PURPOSE: To test the hypothesis that delineation of swallowing organs at risk (SWOARs) based on different guidelines results in differences in dose-volume parameters and subsequent normal tissue complication probability (NTCP) values for dysphagia-related endpoints. MATERIALS AND METHODS: Nine different SWOARs were delineated according to five different delineation guidelines in 29 patients. Reference delineation was performed according to the guidelines and NTCP-models of Christianen et al. Concordance Index (CI), dosimetric consequences, as well as differences in the subsequent NTCPs were calculated. RESULTS: The median CI of the different delineation guidelines with the reference guidelines was 0.54 for the pharyngeal constrictor muscles, 0.56 for the laryngeal structures and 0.07 for the cricopharyngeal muscle and esophageal inlet muscle. The average difference in mean dose to the SWOARs between the guidelines with the largest difference (maxΔD) was 3.5±3.2Gy. A mean ΔNTCP of 2.3±2.7% was found. For two patients, ΔNTCP exceeded 10%. CONCLUSIONS: The majority of the patients showed little differences in NTCPs between the different delineation guidelines. However, large NTCP differences >10% were found in 7% of the patients. For correct use of NTCP models in individual patients, uniform delineation guidelines are of great importance.

The potential of intensity-modulated proton radiotherapy to reduce swallowing dysfunction in the treatment of head and neck cancer: A planning comparative study.

BACKGROUND: Predictive models for swallowing dysfunction were developed previously and showed the potential of improved intensity-modulated radiotherapy to reduce the risk of swallowing dysfunction. Still the risk is high. The aim of this study was to determine the potential of swallowing-sparing (SW) intensity-modulated proton therapy (IMPT) in head and neck cancer (HNC) for reducing the risk of swallowing dysfunction relative to currently used photon therapy. MATERIAL AND METHODS: Twenty-five patients with oropharyngeal (n = 21) and hypopharyngeal (n = 4) cancer received primary radiotherapy, including bilateral neck irradiation, using standard (ST) intensity-modulated photon therapy (IMRT). Prophylactic (54 Gy) and therapeutic (70 Gy) target volumes were defined. The dose to the parotid and submandibular glands was reduced as much as possible. Four additional radiotherapy plans were created for each patient: SW-IMRT, ST-IMPT, 3-beam SW-IMPT (3B-SW-IMPT) and 7-beam SW-IMPT (7B-SW-IMPT). All plans were optimized similarly, with additional attempts to spare the swallowing organs at risk (SWOARs) in the SW plans. Probabilities of swallowing dysfunction were calculated with recently developed predictive models. RESULTS: All plans complied with standard HNC radiotherapy objectives. The mean parotid gland doses were similar for the ST and SW photon plans, but clearly lower in all IMPT plans (ipsilateral parotid gland ST-IMRT: 46 Gy, 7B-SW-IMPT: 29 Gy). The mean dose in the SWOARs was lowest with SW-IMPT, in particular with 7B-SW-IMPT (supraglottic larynx ST-IMRT: 60 Gy, 7B-SW-IMPT: 40 Gy). The observed dose reductions to the SWOARs translated into substantial overall reductions in normal tissue complication risks for different swallowing dysfunction endpoints. Compared with ST-IMRT, the risk of physician-rated grade 2-4 swallowing dysfunction was reduced on average by 8.8% (95% CI 6.5-11.1%) with SW-IMRT, and by 17.2% (95% CI: 12.7-21.7%) with 7B-SW-IMPT. CONCLUSION: SWOAR-sparing with proton therapy has the potential to substantially reduce the risk of swallowing dysfunction compared to similar treatment with photons.

Statistical validation of normal tissue complication probability models.

PURPOSE: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. RESULTS: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. CONCLUSION: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.

3D Variation in delineation of head and neck organs at risk.

BACKGROUND: Consistent delineation of patient anatomy becomes increasingly important with the growing use of highly conformal and adaptive radiotherapy techniques. This study investigates the magnitude and 3D localization of interobserver variability of organs at risk (OARs) in the head and neck area with application of delineation guidelines, to establish measures to reduce current redundant variability in delineation practice. METHODS: Interobserver variability among five experienced radiation oncologists was studied in a set of 12 head and neck patient CT scans for the spinal cord, parotid and submandibular glands, thyroid cartilage, and glottic larynx. For all OARs, three endpoints were calculated: the Intraclass Correlation Coefficient (ICC), the Concordance Index (CI) and a 3D measure of variation (3D SD). RESULTS: All endpoints showed largest interobserver variability for the glottic larynx (ICC = 0.27, mean CI = 0.37 and 3D SD = 3.9 mm). Better agreement in delineations was observed for the other OARs (range, ICC = 0.32-0.83, mean CI = 0.64-0.71 and 3D SD = 0.9-2.6 mm). Cranial, caudal, and medial regions of the OARs showed largest variations. All endpoints provided support for improvement of delineation practice. CONCLUSIONS: Variation in delineation is traced to several regional causes. Measures to reduce this variation can be: (1) guideline development, (2) joint delineation review sessions and (3) application of multimodality imaging. Improvement of delineation practice is needed to standardize patient treatments.

Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.

PURPOSE: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. RESULTS: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. CONCLUSIONS: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

Multivariate modeling of complications with data driven variable selection: guarding against overfitting and effects of data set size.

PURPOSE: Multivariate modeling of complications after radiotherapy is frequently used in conjunction with data driven variable selection. This study quantifies the risk of overfitting in a data driven modeling method using bootstrapping for data with typical clinical characteristics, and estimates the minimum amount of data needed to obtain models with relatively high predictive power. MATERIALS AND METHODS: To facilitate repeated modeling and cross-validation with independent datasets for the assessment of true predictive power, a method was developed to generate simulated data with statistical properties similar to real clinical data sets. Characteristics of three clinical data sets from radiotherapy treatment of head and neck cancer patients were used to simulate data with set sizes between 50 and 1000 patients. A logistic regression method using bootstrapping and forward variable selection was used for complication modeling, resulting for each simulated data set in a selected number of variables and an estimated predictive power. The true optimal number of variables and true predictive power were calculated using cross-validation with very large independent data sets. RESULTS: For all simulated data set sizes the number of variables selected by the bootstrapping method was on average close to the true optimal number of variables, but showed considerable spread. Bootstrapping is more accurate in selecting the optimal number of variables than the AIC and BIC alternatives, but this did not translate into a significant difference of the true predictive power. The true predictive power asymptotically converged toward a maximum predictive power for large data sets, and the estimated predictive power converged toward the true predictive power. More than half of the potential predictive power is gained after approximately 200 samples. Our simulations demonstrated severe overfitting (a predicative power lower than that of predicting 50% probability) in a number of small data sets, in particular in data sets with a low number of events (median: 7, 95th percentile: 32). Recognizing overfitting from an inverted sign of the estimated model coefficients has a limited discriminative value. CONCLUSIONS: Despite considerable spread around the optimal number of selected variables, the bootstrapping method is efficient and accurate for sufficiently large data sets, and guards against overfitting for all simulated cases with the exception of some data sets with a particularly low number of events. An appropriate minimum data set size to obtain a model with high predictive power is approximately 200 patients and more than 32 events. With fewer data samples the true predictive power decreases rapidly, and for larger data set sizes the benefit levels off toward an asymptotic maximum predictive power.

Electronic portal images (EPIs) based position verification for the breast simultaneous integrated boost (SIB) technique.

BACKGROUND AND PURPOSE: To develop a method based on electronic portal images (EPIs) for the position verification of breast cancer patients that are treated with a simultaneous integrated boost (SIB) technique. METHOD: 3D setup errors of the breast outline and the thoracic wall were determined from EPIs of the tangential treatment fields and anterior posterior (AP) verification field. The method was verified with repeated CT scans of 38 patients with an average setup error larger than 5 mm. RESULT: The 3D position deviation of the boost volume can best be determined from the position deviation of the breast outline in the ventrodorsal direction and the thoracic wall in the lateral and longitudinal directions from the tangential and AP EPIs. The method gives an average overestimation of the deviation of the boost volume in the ventrodorsal, lateral and longitudinal directions by 28%, 20% and 6%, respectively and an average underestimation of the deviation of the whole breast by 32%, 17% and 39%. CONCLUSIONS: The described method is superior to using tangential EPIs only and is recommended for position verification of breast cancer patients that are treated with a SIB technique if no Cone beam CT (CBCT) or fiducial markers can be used.

Clinical introduction of a linac head-mounted 2D detector array based quality assurance system in head and neck IMRT.

BACKGROUND AND PURPOSE: IMRT QA is commonly performed in a phantom geometry but the clinical interpretation of the results in a 2D phantom plane is difficult. The main objective of our work is to move from film measurement based QA to 3D dose reconstruction in a patient CT scan. In principle, this could be achieved using a dose reconstruction method from 2D detector array measurements as available in the COMPASS system (IBA Dosimetry). The first step in the clinical introduction of this system instead of the currently used film QA procedures is to test the reliability of the dose reconstruction. In this paper we investigated the validation of the method in a homogeneous phantom with the film QA procedure as a reference. We tested whether COMPASS QA results correctly identified treatment plans that did or did not fulfil QA requirements in head and neck (H&N) IMRT. MATERIALS AND METHODS: A total number of 24 treatments were selected from an existing database with more than 100 film based H&N IMRT QA results. The QA results were classified as either good, just acceptable or clinically rejected (mean gamma index <0.4, 0.4-0.5 or >0.5, respectively with 3%/3mm criteria). Film QA was repeated and compared to COMPASS QA with a MatriXX detector measurement performed on the same day. RESULTS: Good agreement was found between COMPASS reconstructed dose and film measured dose in a phantom (mean gamma 0.83±0.09, 1SD with 1%/1mm criteria, 0.33±0.04 with 3%/3mm criteria). COMPASS QA results correlated well with film QA, identifying the same patients with less good QA results. Repeated measurements with film and COMPASS showed changes in delivery after a modified MLC calibration, also visible in a standard MLC check in COMPASS. The time required for QA reduced by half by using COMPASS instead of film. CONCLUSIONS: Agreement of COMPASS QA results with film based QA supports its clinical introduction for a phantom geometry. A standard MLC calibration check is sensitive to <1mm changes that could be significant in H&N IMRT. These findings offer opportunities to further investigate the method based on a 2D detector array to 3D dose reconstruction in a patient anatomy.

Comparison of normal tissue dose with three-dimensional conformal techniques for breast cancer irradiation including the internal mammary nodes.

PURPOSE: To compare the Para Mixed technique for irradiation of the internal mammary nodes (IMN) with three commonly used strategies, by analyzing the dose to the heart and other organs at risk. METHODS AND MATERIALS: Four different three-dimensional conformal dose plans were created for 30 breast cancer patients. The IMN were enclosed with the Para Mixed technique by a widened mediolateral tangent photon beam and an anterior electron beam, with the Patched technique by an anterior electron beam, with the Standard technique by an anterior photon and electron beam, and with the PWT technique by partially wide tangents. All techniques were optimized for conformality and produced equally adequate target coverage. RESULTS: Heart dose was lowest with the Para Mixed and Patched technique for all patients and with the PWT technique for right-sided treatment only. Lung dose was highest with the PWT, lowest with the Patched, and intermediate with the Para Mixed and Standard techniques. Skin dose was highest with the Patched, lowest with the PWT, and intermediate with the Para Mixed and the Standard techniques. The Para Mixed technique resulted in a 13-Gy lower dose in an overlap area, and the PWT technique was the only technique that incorporated considerable volumes of the contralateral breast. CONCLUSION: The Para Mixed technique yielded the overall best results. No other technique resulted in a lower heart dose. Lung and skin were equally spared instead of one of them being compromised, and the contralateral breast was avoided.