Dosimetric and NTCP analyses for selecting parotid gland cancer patients for proton therapy.

PURPOSE/OBJECTIVE: To perform a dosimetric and a normal tissue complication probability (NTCP) comparison between intensity modulated proton therapy and photon volumetric modulated arc therapy in a cohort of patients with parotid gland cancers in a post-operative or radical setting. MATERIALS AND METHODS: From May 2011 to September 2021, 37 parotid gland cancers patients treated at two institutions were eligible. Inclusion criteria were as follows: patients aged ⩾ 18 years, diagnosis of parotid gland cancers candidate for postoperative radiotherapy or definitive radiotherapy, presence of written informed consent for the use of anonymous data for research purposes. Organs at risk (OARs) were retrospectively contoured. Target coverage goal was defined as D95 > 98%. Six NTCP models were selected. NTCP profiles were calculated for each patient using an internally-developed Python script in RayStation TPS. Average differences in NTCP between photon and proton plans were tested for significance with a two-sided Wilcoxon signed-rank test. RESULTS: Seventy-four plans were generated. A lower Dmean to the majority of organs at risk (inner ear, cochlea, oral cavity, pharyngeal constrictor muscles, contralateral parotid and submandibular gland) was obtained with intensity modulated proton therapy vs volumetric modulated arc therapy with statistical significance (p < .05). Ten (27%) patients had a difference in NTCP (photon vs proton plans) greater than 10% for hearing loss and tinnitus: among them, seven qualified for both endpoints, two patients for hearing loss only, and one for tinnitus. CONCLUSIONS: In the current study, nearly one-third of patients resulted eligible for proton therapy and they were the most likely to benefit in terms of prevention of hearing loss and tinnitus.

A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy.

OBJECTIVE: This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LETd) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LETdis associated with variability in the relative biological effectiveness (RBE) of protons, we also evaluate the implications of using NN predictions for normal tissue complication probability (NTCP) models within a variable-RBE context. Approach: The predictive performance of three-dimensional NN architectures was evaluated using five-fold cross-validation on a cohort of brain tumor patients (n=151). The best-performing model was identified and externally validated on patients from a different center (n=107). LETdpredictions were compared to MC-simulated results in clinically relevant regions of interest. We assessed the impact on NTCP models by leveraging LETdpredictions to derive RBE-weighted doses, using the Wedenberg RBE model. Main results: We found NNs based solely on the planned dose profile, i.e. without additional usage of CT images, can approximate MC-based LETddistributions. Root mean squared errors (RMSE) for the median LETdwithin the brain, brainstem, CTV, chiasm, lacrimal glands (ipsilateral/contralateral) and optic nerves (ipsilateral/contralateral) were 0.36, 0.87, 0.31, 0.73, 0.68, 1.04, 0.69 and 1.24~keV/µm, respectively. Although model predictions showed statistically significant differences from MC outputs, these did not result in substantial changes in NTCP predictions, with RMSEs of at most 3.2 percentage points. Significance: The ability of NNs to predict LETdbased solely on planned dose profiles suggests a viable alternative to the compute-intensive MC simulations in a variable-RBE setting. This is particularly useful in scenarios where MC simulation data are unavailable, facilitating resource-constrained proton therapy treatment planning, retrospective patient data analysis and further investigations on the variability of proton RBE.

Dependence of the AUC of NTCP models on the observational dose-range highlights cautions in comparison of discriminative performance.

BACKGROUND: Normal tissue complication probability (NTCP) models are probabilistic models that describe the risk of radio-induced toxicity in tissues or organs. In the field of radiotherapy, the area under the ROC curve (AUC) is widely used to estimate the performance in risk prediction of NTCP models. METHODS: In this work, we derived an analytical expression of the AUC for the logistic NTCP model in the case of both symmetrical and asymmetrical dose (to the normal tissue) windows around D50. Using numerical simulations, we studied the behavior of the AUC in general clinical settings, enforcing non-logistic NTCP models (Lyman-Kutcher-Burman and LogEUD) and including risk factors beyond the dose. We validated our findings using real-world radiotherapy data sets of prostate cancer patients. RESULTS: Our analytical expression of the AUC made explicit the dependence on both the steepness of the logistic curve (ß) and the dose window width (w), showing that an increase of w pushes AUC towards higher values. Increasing values of the AUC with increasing values of w were consistently observed across simulated data sets with diverse clinical settings from published studies and real clinical data sets. CONCLUSION: Our results reveal that the AUC of NTCP models inherits intrinsic characteristics from the clinical setting of the data set on which the models are developed, and warn against the use of the AUC to compare the performance of models constructed upon data from trials in which substantially different dose ranges were administered or accounting for different risk factors beyond the dose.

Validation of prediction models for radiation-induced late rectal bleeding: Evidence from a large pooled population of prostate cancer patients.

PURPOSE: To validate published models for the risk estimate of grade ≥ 1 (G1+), grade ≥ 2 (G2+) and grade = 3 (G3) late rectal bleeding (LRB) after radical radiotherapy for prostate cancer in a large pooled population from three prospective trials. MATERIALS AND METHODS: The external validation population included patients from Europe, and Oceanian centres enrolled between 2003 and 2014. Patients received 3DCRT or IMRT at doses between 66-80 Gy. IMRT was administered with conventional or hypofractionated schemes (2.35-2.65 Gy/fr). LRB was prospectively scored using patient-reported questionnaires (LENT/SOMA scale) with a 3-year follow-up. All Normal Tissue Complication Probability (NTCP) models published until 2021 based on the Equivalent Uniform Dose (EUD) from the rectal Dose Volume Histogram (DVH) were considered for validation. Model performance in validation was evaluated through calibration and discrimination. RESULTS: Sixteen NTCP models were tested on data from 1633 patients. G1+ LRB was scored in 465 patients (28.5%), G2+ in 255 patients (15.6%) and G3 in 112 patients (6.8%). The best performances for G2+ and G3 LRB highlighted the importance of the medium-high doses to the rectum (volume parameters n = 0.24 and n = 0.18, respectively). Good performance was seen for models of severe LRB. Moreover, a multivariate model with two clinical factors found the best calibration slope. CONCLUSION: Five published NTCP models developed on non-contemporary cohorts were able to predict a relative increase in the toxicity response in a more recent validation population. Compared to QUANTEC findings, dosimetric results pointed toward mid-high doses of rectal DVH. The external validation cohort confirmed abdominal surgery and cardiovascular diseases as risk factors.

Cost-effectiveness of proton radiotherapy versus photon radiotherapy for non-small cell lung cancer patients: Exploring the model-based approach.

INTRODUCTION: Proton radiotherapy (PT) is a promising but more expensive strategy than photon radiotherapy (XRT) for the treatment of non-small cell lung cancer (NSCLC). PT is probably not cost-effective for all patients. Therefore, patients can be selected using normal tissue complication probability (NTCP) models with predefined criteria. This study aimed to explore the cost-effectiveness of three treatment strategies for patients with stage III NSCLC: 1. photon radiotherapy for all patients (XRTAll); 2. PT for all patients (PTAll); 3. PT for selected patients (PTIndividualized). METHODS: A decision-analytical model was constructed to estimate and compare costs and QALYs of all strategies. Three radiation-related toxicities were included: dyspnea, dysphagia and cardiotoxicity. Costs and QALY's were incorporated for grade 2 and ≥ 3 toxicities separately. Incremental Cost-Effectiven Ratios (ICERs) were calculated and compared to a threshold value of €80,000. Additionally, scenario, sensitivity and value of information analyses were performed. RESULTS: PTAll yielded most QALYs, but was also most expensive. XRTAll was the least effective and least expensive strategy, and the most cost-effective strategy. For thresholds higher than €163,467 per QALY gained, PTIndividualized was cost-effective. When assuming equal minutes per fraction (15 minutes) for PT and XRT, PTIndividualized was considered the most cost-effective strategy (ICER: €76,299). CONCLUSION: Currently, PT is not cost-effective for all patients, nor for patient selected on the current NTCP models used in the Dutch indication protocol. However, with improved clinical experience, personnel and treatment costs of PT can decrease over time, which potentially leads to PTIndividualized, with optimal patient selection, will becoming a cost-effective strategy.

Comparison of photon intensity modulated, hybrid and volumetric modulated arc radiation treatment techniques in locally advanced non-small cell lung cancer.

Background and purpose: There is no consensus on the best photon radiation technique for non-small cell lung cancer (NSCLC). This study quantified the differences between commonly used treatment techniques in NSCLC to find the optimal technique. Materials and methods: Treatment plans were retrospectively generated according to clinical guidelines for 26 stage III NSCLC patients using intensity modulated radiation therapy (IMRT), hybrid, and volumetric modulated arc therapy (VMATC, and VMATV5 optimized for lower lung and heart dose). Plans were evaluated for target coverage, organs at risk dose (including heart substructures) and normal tissue complication probabilities (NTCP). Results: The comparison showed significant and largest median differences (>1 Gy or >5%) in favor of IMRT for the mediastinal envelope and heart (maximum dose), in favor of the hybrid technique for the lungs (V5Gy of the total lungs and V5Gy of the contralateral lung) and in favor of VMATC for the heart (Dmean), most of the substructures of the heart, and the spinal cord (maximum dose). The VMATV5 technique had significantly lower heart dose compared to the hybrid technique and significantly lower lung dose compared to the VMATC, combining both advantages in one technique. The mean ΔNTCP did not exceed the 2 percent point (pp) for grade 5 (mortality), and 10 pp for grade ≥2 toxicities (radiation pneumonitis and acute esophageal toxicity), but ΔNTCP was mostly in favor of VMATC/V5 for individual patients. Conclusion: This planning study showed that VMATV5 was preferred as it achieved low lung and heart doses, as well as low NTCPs, simultaneously.

Impact of sarcopenia on acute radiation-induced toxicity in head and neck cancer patients.

BACKGROUND AND PURPOSE: Sarcopenia is related to late radiation-induced toxicities and worse survival in head and neck cancer (HNC) patients. This study tested the hypothesis that sarcopenia improves the performance of current normal tissue complication probability (NTCP) models of radiation-induced acute toxicity in HNC patients. MATERIAL/METHODS: This was a retrospective analysis in a prospective cohort of HNC patients treated from January 2007 to December 2018 with (chemo)radiotherapy. Planning CT scans were used for evaluating skeletal muscle mass. Characteristics of sarcopenic and non-sarcopenic patients were compared. The impact of sarcopenia was analysed by adding sarcopenia to the linear predictors of current NTCP models predicting physician- and patient-rated acute toxicities. RESULTS: The cut-off values of sarcopenia in the study population (n = 977) were established at skeletal muscle index < 42.0 cm2/m2 (men) and < 31.2 cm2/m2 (women), corresponding to the lowest sex-specific quartile. Compared to non-sarcopenic patients, sarcopenic patients were more frequently smokers (61% vs. 48%, p < 0.001), had more often advanced stage of disease (stage III-IV, p = 0.004), higher age (67 vs. 63 years, p < 0.001) and experienced more pretreatment complaints, such as dysphagia (grade ≥ 2, p < 0.001). Sarcopenia remained statistically significant, next to the linear predictor, only for physician-rated grade ≥ 3 dysphagia (week 3-6 during RT, p < 0.01). However, sarcopenia did not improve the performance of these NTCP models (p > 0.99). CONCLUSION: Sarcopenia in HNC patients was an independent prognostic factor for radiation-induced physician-rated acute grade ≥ 3 dysphagia, which might be explained by its impact on swallowing muscles. However, addition of sarcopenia did not improve the NTCP model performance.

Modelling of late side-effects following cranial proton beam therapy.

BACKGROUND: The limited availability of proton beam therapy (PBT) requires individual treatment selection strategies that can be based on normal tissue complication probability (NTCP) models. We developed and externally validated NTCP models for common late side-effects following PBT in brain tumour patients to optimise patients' quality of life. METHODS: Cohorts from three PBT centres (216 patients) were investigated for several physician-rated endpoints at 12 and 24 months after PBT: alopecia, dry eye syndrome, fatigue, headache, hearing and memory impairment, and optic neuropathy. Dose-volume parameters of associated normal tissues and clinical factors were used for logistic regression modelling in a development cohort. Statistically significant parameters showing high area under the receiver operating characteristic curve (AUC) values in internal cross-validation were externally validated. In addition, analyses of the pooled cohorts and of time-dependent generalised estimating equations including all patient data were performed. RESULTS: In the validation study, mild alopecia was related to high dose parameters to the skin [e.g. the dose to 2% of the volume (D2%)] at 12 and 24 months after PBT. Mild hearing impairment at 24 months after PBT was associated with the mean dose to the ipsilateral cochlea. Additionally, the pooled analyses revealed dose-response relations between memory impairment and intermediate to high doses to the remaining brain as well as D2% of the hippocampi. Mild fatigue at 24 months after PBT was associated with D2% to the brainstem as well as with concurrent chemotherapy. Moreover, in generalised estimating equations analysis, dry eye syndrome was associated with the mean dose to the ipsilateral lacrimal gland. CONCLUSION: We developed and in part validated NTCP models for several common late side-effects following PBT in brain tumour patients. Validation studies are required for further confirmation.

Model-based comparison of organ at risk protection between VMAT and robustly optimised IMPT plans.

The comparison between intensity-modulated proton therapy (IMPT) and volume-modulated arc therapy (VMAT) plans, based on models of normal tissue complication probabilities (NTCP), can support the choice of radiation modality. IMPT irradiation plans for 50 patients with head and neck tumours originally treated with photon therapy have been robustly optimised against density and setup uncertainties. The dose distribution has been calculated with a Monte Carlo (MC) algorithm. The comparison of the plans was based on dose-volume parameters in organs at risk (OARs) and NTCP-calculations for xerostomia, sticky saliva, dysphagia and tube feeding using Langendijk's model-based approach. While the dose distribution in the target volumes is similar, the IMPT plans show better protection of OARs. Therefore, it is not the high dose confirmation that constitutes the advantage of protons, but it is the reduction of the mid-to-low dose levels compared to photons. This work investigates to what extent the advantages of proton radiation are beneficial for the patient's post-therapeutic quality of life (QoL). As a result, approximately one third of the patients examined benefit significantly from proton therapy with regard to possible late side effects. Clinical data is needed to confirm the model-based calculations.

Identification of patient benefit from proton beam therapy in brain tumour patients based on dosimetric and NTCP analyses.

BACKGROUND: The limited availability of proton beam therapy (PBT) requires individual treatment selection strategies, such as the model-based approach. In this study, we assessed the dosimetric benefit of PBT compared to photon therapy (XRT), analysed the corresponding changes in normal tissue complication probability (NTCP) on a variety of available models, and illustrated model-based patient selection in an in-silico study for patients with brain tumours. METHODS: For 92 patients treated at two PBT centres, volumetric modulated arc therapy treatment plans were retrospectively created for comparison with the clinically applied PBT plans. Several dosimetric parameters for the brain excluding tumour and margins, cerebellum, brain stem, frontal and temporal lobes, hippocampi, cochleae, chiasm, optic nerves, lacrimal glands, lenses, pituitary gland, and skin were compared between both modalities using Wilcoxon signed-rank tests. NTCP differences (ΔNTCP) were calculated for 11 models predicting brain necrosis, delayed recall, temporal lobe injury, hearing loss, tinnitus, blindness, ocular toxicity, cataract, endocrine dysfunction, alopecia, and erythema. A patient was assumed to be selected for PBT if ΔNTCP exceeded a threshold of 10 percentage points for at least one of the side-effects. RESULTS: PBT substantially reduced the dose in almost all investigated OARs, especially in the low and intermediate dose ranges and for contralateral organs. In general, NTCP predictions were significantly lower for PBT compared to XRT, in particular in ipsilateral organs. Considering ΔNTCP of all models, 80 patients (87.0%) would have been selected for PBT in this in-silico study, mainly due to predictions of a model on delayed recall (51 patients). CONCLUSION: In this study, substantial dose reductions for PBT were observed, mainly in contralateral organs. However, due to the sigmoidal dose response, NTCP was particularly reduced in ipsilateral organs. This underlines that physical dose-volume parameters alone may not be sufficient to describe the clinical relevance between different treatment techniques and highlights potential benefits of NTCP models. Further NTCP models for different modern treatment techniques are mandatory and existing models have to be externally validated in order to implement the model-based approach in clinical practice for cranial radiotherapy.

Normal tissue complication probability (NTCP) models of acute urinary toxicity (AUT) following carbon ion radiotherapy (CIRT) for prostate cancer.

PURPOSE: To estimate the Lyman Kutcher Burman (LKB) and multivariate NTCP models predicting the AUT of prostate cancer treated with CIRT. MATERIALS AND METHODS: A cohort of 154 prostate adenocarcinoma patients were retrospectively analyzed. The AUT levels were graded according to CTCAE 4.03. Based on dosimetric parameters and/or clinical factors, a set of variables with best-fit values determined in the two models was validated by the area under the receiver operating characteristic curve (AUC) and used to correlate the predicted and observed NTCP rates for both levels and related endpoints. RESULT: 59 (38.3%) patients experienced AUT. For LKB model, the equivalent uniform doses (EUDs) were calculated to be 62.0 GyE (following V61.5 > 1.7%) and 61.2 GyE (following maximum dose > 63.0 GyE) with predicted NTCP rates of 37.0% (AUC: 0.71) and 15.6% (AUC: 0.65) for AUT G1&2 and G2 of bladder. While for the multivariate model, the predicted NTCP rates was 37.1% (AUC: 0.70) and 20.2% (AUC: 0.64) for AUT G1&2 and G2, associated with V61 and V65, respectively. Nocturia was associated with bladder volume and maximum dose for G1&2, with patient's age and maximum bladder dose for G2. Other predictable endpoints were associated with V≥61. The predicted NTCPs agree with the observed complication rates for bladder and its wall. CONCLUSIONS: The LKB model successfully predicted the NTCP rates of both AUT levels and urgency urination. The multivariate model predicted well on both levels and nocturia. Decreasing high bladder dose volume may reduce the incidence of AUT.

Generalizability assessment of head and neck cancer NTCP models based on the TRIPOD criteria.

This review aimed to provide an overview of the level of maturity of normal tissue complication probability (NTCP) models for head and neck cancer (HNC) patients. A systematic literature review was performed to retrieve NTCP models for HNC toxicities. Patient population characteristics, NTCP model and the predictors, treatment technique and endpoint definition were extracted per article. Models were then scored based on the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) consensus guidelines to evaluate their generalizability. 335 articles on photon and proton therapy of HNC were identified and 52 relevant articles were further analyzed. Eighteen articles on xerostomia and sticky saliva (TRIPOD types 1a-2b: 15; TRIPOD type 3: 1; TRIPOD types 4a: 1 & 4b:1), thirteen articles on dysphagia and tube feeding dependence (TRIPOD types 1a-2b: 7; TRIPOD type 3: 2; TRIPOD types 4a:2 & 4b:2), five articles on oral mucositis (TRIPOD types 1a-2b: 4; TRIPOD type 4b: 1), seven articles on hypothyroidism (TRIPOD types 1a-2b: 4; TRIPOD type 3: 1; TRIPOD types 4a: 1 & 4b:1), four articles on hearing loss and tinnitus (TRIPOD type 1a: 4) and ten articles on esophagitis (TRIPOD types 1a-2b: 9; TRIPOD type 4a: 1) were included. External validation studies of HNC NTCP models are scarce. Moreover, the majority of them were validating a model developed by the same researchers. Only 2 independent external validation studies were found. There is a strong need to publish external validation studies to get more mature NTCP models applicable in clinical practice.

The use of real-world evidence to audit normal tissue complication probability models for acute esophageal toxicity in non-small cell lung cancer patients.

INTRODUCTION: The aim of this work is to assess the validity of real world data (RWD) derived from an electronic toxicity registration (ETR). As a showcase, the NTCP-models of acute esophageal toxicity (AET) for concurrent chemoradiation (CCRT) for NSCLC patients were used to validate the ETR of AET before/after dose de-escalation to the mediastinal lymph nodes. MATERIAL AND METHODS: One hundred and one patients received 24 × 2.75 Gy and 116 patients received de-escalated dose of 24 × 2.42 Gy to the mediastinal lymph nodes. The validity and completeness of the ETR was analyzed. The grade ≥2 AET probability was defined according the V50 Gy and V60 Gy NTCP-models from literature. Validity of the models was assessed by calibration and discrimination. Furthermore, sensitivity and specificity for different cut-off points were determined. RESULTS: The compliance of ETR was 73-80%, with sensitivity and specificity rates of 83% and 86% for grade ≥2 AET, respectively. Discrimination of both NTCP-models demonstrated a moderate accuracy (V50 model, AUC 0.71; V60-model, AUC 0.69). Dose de-escalation did not influence the accuracy of the V50-model; AUC before: 0.69, and AUC after: 0.71. For the V60-model the model-accuracy decreased after dose de-escalation; AUC before: 0.72 and AUC after: 0.62, respectively. CONCLUSION: RWD is a useful method to audit NTCP models in clinical practice. The NTCP models to predict AET in NSCLC patients showed moderate predictive accuracy. For clinical practice, the V50Gy seems to be most stable for dose de-escalation without compromising safety and efficacy.

Development and validation of NTCP models for acute side-effects resulting from proton beam therapy of brain tumours.

BACKGROUND: The limited availability of proton beam therapy (PBT) requires individual treatment selection strategies, such as based on normal tissue complication probability (NTCP). We developed and externally validated NTCP models for common acute side-effects following PBT in brain tumour patients in effort to provide guidance on optimising patient quality of life. METHODS: An exploration cohort including 113 adult brain tumour patients who underwent PBT was investigated for the following endpoints: alopecia, scalp erythema, headache, fatigue and nausea. Dose-volume parameters of associated normal tissues were used for logistic regression modelling. Statistically significant parameters showing high area under the receiver operating characteristic curve (AUC) values in internal cross-validation were externally validated on two cohorts of 71 and 96 patients, respectively. RESULTS: Statistically significant correlations of dose-volume parameters of the skin for erythema and alopecia were found. In internal cross-validation, the following prognostic parameters were selected: V35Gy (absolute volume receiving 35 Gy) for erythema grade ≥1, D2% (dose to 2% of the volume) for alopecia grade ≥1 and D5% for alopecia grade ≥2. Validation was successful for both cohorts with AUC >0.75. A bivariable model for fatigue grade ≥1 could not be validated externally. No correlations of dose-volume parameters of the brain were seen for headache or nausea. CONCLUSION: We developed and successfully validated NTCP models for scalp erythema and alopecia in primary brain tumour patients treated with PBT.

SPECT/CT-guided elective nodal irradiation for head and neck cancer: Estimation of clinical benefits using NTCP models.

BACKGROUND AND PURPOSE: The great majority of patients with lateralized head and neck squamous cell carcinoma (HNSCC) treated with radiotherapy routinely undergo bilateral elective nodal irradiation (ENI), even though the incidence of contralateral regional failure after unilateral ENI is low. Excluding the contralateral neck from elective irradiation could reduce radiation-related toxicity and improve quality-of-life. The current study investigated the dosimetric benefits of a novel approach using lymph drainage mapping by SPECT/CT to select patients for unilateral ENI. PATIENTS AND METHODS: Forty patients with lateralized cT1-3N0-2bM0 HNSCC underwent lymph drainage mapping. Two radiation plans were made; the real plan with which patients were actually treated (selective SPECT/CT-guided plan irradiating the ipsilateral neck ±â€¯any contralateral draining level); and the virtual plan (standard plan according to institutional guidelines, as if the same patient would have been treated bilaterally). Radiation doses to clinically important organs-at-risk were compared between the two plans. We used five normal tissue complication probability (NTCP) models to predict the clinical benefits of this approach. RESULTS: Median dose reductions to the contralateral parotid gland, contralateral submandibular gland, glottic larynx, supraglottic larynx, constrictor muscle and thyroid gland were 19.2, 27.3, 11.4, 9.7, 12.1 and 18.4 Gy, respectively. Median NTCP reductions for xerostomia, contralateral parotid function, dysphagia, hypothyroidism and laryngeal edema were 20%, 14%, 10%, 20% and 5% respectively. CONCLUSIONS: Selective SPECT/CT-guided ENI results in significant dose reductions to various organs-at-risk and corresponding NTCP values, and will subsequently reduce the incidence and severity of different troublesome radiation-related toxicities and improve quality-of-life.

Development of a virtual spacer to support the decision for the placement of an implantable rectum spacer for prostate cancer radiotherapy: Comparison of dose, toxicity and cost-effectiveness.

INTRODUCTION: Previous studies have shown that the implantable rectum spacer (IRS) is not beneficial for all patients. A virtual IRS (V-IRS) was constructed to help identify the patients for whom it is cost-effective to implant an IRS, and its viability as a tool to tailor the decision of an IRS implantation to be beneficial for the specified patient was assessed. Please watch animation: (https://www.youtube.com/watch?v=tDlagSXMKqw) MATERIALS AND METHODS: The V-IRS was tested on 16 patients: 8 with a rectal balloon implant (RBI) and 8 with a hydrogel spacer. A V-IRS was developed using 7 computed tomography (CT) scans of patients with a RBI. To examine the V-IRS, CT scans before and after the implantation of an IRS were used. IMRT plans were made based on CT scans before the IRS, after IRS and with the V-IRS, prescribing 70 Gray (Gy) to the planning target volume. Toxicity was accessed using externally validated normal tissue complication probability (NTCP) models, and the Cost-effectiveness was analyzed using a published Markov model. RESULTS: The rectum volume receiving 75Gy (V75) were improved by both the IRS and the V-IRS with on average 4.2% and 4.3% respectively. The largest NTCP reduction resulting from the IRS and the V-IRS was 4.0% and 3.9% respectively. The RBI was cost-effective for 1 out of 8 patients, and the hydrogel was effective for 2 out of 8 patients, and close to effective for a third patient. The classification accuracy of the model, regarding cost-effectiveness, was 100%. CONCLUSION: The V-IRS approach in combination with a toxicity prediction model and a cost-effectiveness analyses is a promising basis for a decision support tool for the implantation of either a hydrogel spacer or a rectum balloon implant.

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 OFDYS and OFTFD-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 OFNTCP-based plans. RESULTS: All OFNTCP-based plans were reviewed and classified as clinically acceptable. On average, the Δdose and ΔNTCP were small comparing the OFDYS-plan, OFTFD-plan, and clinical plan. For 5% of patients NTCPTFD reduced >5% using OFTFD-based planning compared to the OFDYS-plans. CONCLUSIONS: Plan optimization using NTCPDYS- and NTCPTFD-based objective functions resulted in clinically acceptable plans. For patients with considerable risk factors of TFD, the OFTFD steered the optimizer to dose distributions which directly led to slightly lower predicted NTCPTFD values as compared to the other studied plans.

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.

Selection of patients for radiotherapy with protons aiming at reduction of side effects: the model-based approach.

Most new radiation techniques, have been introduced primarily to reduce the dose to normal tissues in order to prevent radiation-induced side effects. Radiotherapy with protons is such a radiation technique that due to its superior beam properties compared to photons enables better sparing of normal tissues. This paper describes a stepwise methodology to select patients for proton therapy when the primary aim is to reduce side effects. This method has been accepted by the Dutch health authorities to select patients for proton therapy. In addition, an alternative method is described in case randomised controlled trials are considered not appropriate.