Normal Tissue Complication Probability Estimates Research Articles

Cluster-Based Toxicity Estimation of Osteoradionecrosis Via Unsupervised Machine Learning: Moving Beyond Single Dose-Parameter Normal Tissue Complication Probability by Using Whole Dose-Volume Histograms for Cohort Risk Stratification

PurposeGiven the limitations of extant models for normal tissue complication probability estimation for osteoradionecrosis (ORN) of the mandible, the purpose of this study was to enrich statistical inference by exploiting structural properties of data and provide a clinically reliable model for ORN risk evaluation through an unsupervised-learning analysis that incorporates the whole radiation dose distribution on the mandible. Materials and MethodsThe analysis was conducted on retrospective data of 1,259 head and neck cancer (HNC) patients treated at XXX between 2005 and 2015. During a minimum 12-month post-therapy follow-up period, 173 patients in this cohort (13.7%) developed ORN (grades I to IV). The (structural) clusters of mandibular dose-volume histograms (DVHs) for these patients were identified using the K-means clustering method. A soft-margin support vector machine (SVM) was used to determine the cluster borders and partition the dose-volume space. The risk of ORN for each dose-volume region was calculated based on incidence rates and other clinical risk factors. ResultsThe K-means clustering method identified six clusters among the DVHs. Based on the first five clusters, the dose-volume space was partitioned by the soft-margin SVM into distinct regions with different risk indices. The sixth cluster entirely overlapped with the others; the region of this cluster was determined by its envelopes. For each region, the ORN incidence rate per pre-radiation dental extraction status (a statistically significant, non-dose related risk factor for ORN) was reported as the corresponding risk index. ConclusionThis study presents an unsupervised-learning analysis of a large-scale data set to evaluate the risk of mandibular ORN among HNC patients. The results provide a visual risk-assessment tool for ORN (based on the whole DVH and pre-radiation dental extraction status) as well as a range of constraints for dose optimization under different risk levels.

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

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

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

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

Normal Tissue Complication Probability Modelling for Toxicity Prediction and Patient Selection in Proton Beam Therapy to the Central Nervous System: A Literature Review

Normal tissue complication probability (NTCP) models can guide clinical decision making in radiotherapy. In recent years, they have been used for patient selection for proton beam therapy (PBT) for some anatomical tumour sites. This review synthesizes the published evidence regarding the use of NTCP models to predict the toxicity of PBT, for different end points in patients with brain tumours. A search of Medline and Embase using the Patients, Intervention, Comparison, Outcome (PICO) criteria was undertaken. In total, 37 articles were deemed relevant and were reviewed in detail. Nineteen articles on NTCP modelling of toxicity end points were included. Of these, 11 were comparative NTCP studies of PBT versus conventional photon radiotherapy (XRT), which evaluated differences in plan dosimetry and then assumed that XRT-derived literature estimates of NTCP would be applicable to both. Seven papers derived NTCP models based on PBT outcome data, two of which provided model parameters. Among analysed end points, the reduced risk of secondary tumours with PBT as compared with XRT is estimated – through modelling studies – to be considerable and was highlighted by most authors. For other analysed end points, the clinical benefit of PBT mainly depends on tumour location in relation to organs at risk as well as prescription doses. NTCP models can be useful tools for treatment plan comparison. However, most published toxicity data were derived from XRT cohorts; this review has highlighted the need for further studies relating dose-volume parameters to observed toxicity in PBT-treated patients. Specifically, there is a need for PBT-specific NTCP models that can be implemented in the clinical practice. NTCP models built on robust clinical data for the most common radiotherapy toxicities in the brain would potentially redefine the current indications for PBT.

Development and validation of an indigenous, radiobiological model-based tumor control probability and normal tissue complication probability estimation software for routine plan evaluation in clinics.

Development and validation of a simple and convenient computational program in MATLAB environment for estimating the tumor control probability (TCP) and the normal tissue complication probability (NTCP), as a decision support system for routine plan evaluation. We developed an in-house software using MATLAB 2016b (Mathworks) for estimating TCP and NTCP named as RBMODELV1. The program contains Niemierko free equivalent uniform dose (EUD) program code provided in authors research article. For rest of radiobiological (RB) models in the software separate coding is performed. The program accepts cumulative dose-volume histogram file in (.txt) format containing two columns dose and volume. A set of two RB parameters were prepared, default and user-dependent in excel sheet named as RBDATA. We cross-validated results of RBMODELV1 software with BioSuite software for Poisson's TCP model and Lyman-Kutcher-Burman (LKB) model. A set of total 20 patient's data of head and neck site took under study and respective TCP and NTCP calculated by all the RB models and compared. This is the first study in which we tried to establish correlation between the mean doses (EUD) received by parallel structure (parotid gland and oral cavity) and predicted percentage of NTCP values. It is found that mean dose in the range of 35-40 Gy for parotid gland can result in more than 50% NTCP predicted by all four RB models. Similarly oral cavity receiving mean dose in the range of 53-58 Gy can results in more than 35% NTCP predicted by all the four models. There is <3% variation observed between TCP calculated by BioSuite and RBMODELV1 software and <4% variation observed between predicted NTCP for parotid gland and oral cavity OAR from LKB model by both the software. We created simple software RBMODELV1 which can be used as a research tool as well as decision support system.

Impact of RBE variations on risk estimates of temporal lobe necrosis in patients treated with intensity-modulated proton therapy for head and neck cancer

Background Temporal lobe necrosis (TLN) is a potential late effect after radiotherapy for skull base head and neck cancer (HNC). Several photon-derived dose constraints and normal tissue complication probability (NTCP) models have been proposed, however variation in relative biological effectiveness (RBE) may challenge the applicability of these dose constraints and models in proton therapy. The purpose of this study was therefore to investigate the influence of RBE variations on risk estimates of TLN after Intensity-Modulated Proton Therapy for HNC. Material and Methods Seventy-five temporal lobes from 45 previously treated patients were included in the analysis. Sixteen temporal lobes had radiation associated Magnetic Resonance image changes (TLIC) suspected to be early signs of TLN. Fixed (RWDFix) and variable RBE-weighed doses (RWDVar) were calculated using RBE = 1.1 and two RBE models, respectively. RWDFix and RWDVar for temporal lobes were compared using Friedman’s test. Based on RWDFix, six NTCP models were fitted and internally validated through bootstrapping. Estimated probabilities from RWDFix and RWDVar were compared using paired Wilcoxon test. Seven dose constraints were evaluated separately for RWDFix and RWDVar by calculating the observed proportion of TLIC in temporal lobes meeting the specific dose constraints. Results RWDVar were significantly higher than RWDFix (p < 0.01). NTCP model performance was good (AUC:0.79-0.84). The median difference in estimated probability between RWDFix and RWDVar ranged between 5.3% and 20.0% points (p < 0.01), with V60GyRBE and DMax at the smallest and largest differences, respectively. The proportion of TLIC was higher for RWDFix (4.0%–13.1%) versus RWDVar (1.3%–5.3%). For V65GyRBE ≤ 0.03 cc the proportion of TLIC was less than 5% for both RWDFix and RWDVar. Conclusion NTCP estimates were significantly influenced by RBE variations. Dmax as model predictor resulted in the largest deviations in risk estimates between RWDFix and RWDVar. V65GyRBE ≤ 0.03 cc was the most consistent dose constraint for RWDFix and RWDVar.

Ultra hypofractionated extended nodal irradiation using volumetric modulated arc therapy for oligorecurrent pelvic nodal prostate cancer.

Prostate cancer (PCa) may recur after primary treatment but no standard of care exists for patients with pelvic nodal relapse. Based on obervational data, Extended Nodal Irradiation (ENI) might be associated with fewer treatment failures than Stereotactic Ablative Radiotherapy (SABR) to the involved node(s) alone. Ultra hypofractionated ENI is yet to be evaluated in this setting, but it could provide a therapeutic advantage if PCa has a low α/β ratio in addition to patient convenience/resource benefits. This volumetric modulated arc therapy (VMAT) planning study developed a class solution for 5-fraction Extended Nodal Irradiation (ENI) plus a simultaneous integrated boost (SIB) to involved node(s). Ten patients with oligorecurrent nodal disease after radical prostatectomy/post-operative prostate bed radiotherapy were selected. Three plans were produced for each dataset to deliver 25 Gy in 5 fractions ENI plus SIBs of 40, 35 and 30 Gy. The biologically effective dose (BED) formula was used to determine the remaining dose in 5 fractions that could be delivered to re-irradiated segments of organs at risk (OARs). Tumour control probability (TCP) and normal tissue complication probability (NTCP) were calculated using the LQ-Poisson Marsden and Lyman-Kutcher-Burman models respectively. Six patients had an OAR positioned within planning target volume node (PTVn), which resulted in reduced target coverage to PTV node in six, five and four instances for 40, 35 and 30 Gy SIB plans respectively. In these instances, only 30 Gy SIB plans had a median PTV coverage >90% (inter-quartile range 90-95). No OAR constraint was exceeded for 30 Gy SIB plans, including where segments of OARs were re-irradiated. Gross tumour volume node (GTVn) median TCP was 95.7% (94.4-96), 90.7% (87.1-91.2) and 78.6% (75.8-81.1) for 40, 35 and 30 Gy SIB plans respectively, where an α/β ratio of 1.5 was assumed. SacralPlex median NTCP was 43.2% (0.7-61.2), 12.1% (0.6-29.7) and 2.5% (0.5-5.1) for 40, 35 and 30 Gy SIB plans respectively. NTCP for Bowel_Small was <0.3% and zero for other OARs for all three plan types. Ultra hypofractionated ENI planning for pelvic nodal relapsed PCa appears feasible with encouraging estimates of nodal TCP and low estimates of NTCP, especially where a low α/β ratio is assumed and a 30 Gy SIB is delivered. This solution should be further evaluated within a clinical trial and compared against SABR to involved node(s) alone.

Ipsilateral lung normal tissue complication probability parameters for different dose calculation algorithms in radiotherapy of breast cancer.

Different dose calculation algorithms (DCAs) predict different dose distributions for the same treatment. Awareness of optimal model parameters is vital for estimating normal tissue complication probability (NTCP) for different algorithms. The aim is to determine the NTCP parameter values for different DCAs in left-sided breast radiotherapy, using the Lyman-Kutcher-Burman (LKB) model. First, the methodology recommended by International Atomic Energy Agency TEC-DOC 1583 was used to establish the accuracy of dose calculations of different DCAs including: Monte Carlo (MC) and collapsed cone algorithms implemented in Monaco, pencil beam convolution (PBC) and analytical anisotropic algorithm (AAA) implemented in Eclipse, and superposition and Clarkson algorithms implemented in PCRT3D treatment planning systems (TPSs). Then, treatment planning of 15 patients with left-sided breast cancer was performed by the mentioned DCAs and NTCP of the left-lung normal tissue were calculated for each patient individually, using the LKB model. For the PB algorithm, the NTCP parameters were taken from previously published values and new model parameters obtained for each DCA, using the iterative least squares methods. For all cases and DCAs, NTCP computation with the same model parameters resulted in >15% deviation in NTCP values. The new NTCP model parameters were classified according to the algorithm type. Thus, the discrepancy of NTCP computations was reduced up to 5% after utilizing adjusted model parameters. This paper confirms that the NTCP values for a given treatment type are different for the different DCAs. Thus, it is essential to introduce appropriate NTCP parameter values according to DCA adopted in TPS, to obtain a more precise estimation of lung NTCP. Hence, new parameter values, classified according to the DCAs, must be determined before introducing NTCP estimation in clinical practice.

Dosimetric Evaluation of Incorporating Patient Geometric Variations Into Adaptive Plan Optimization Through Probabilistic Treatment Planning in Head and Neck Cancers

Four-dimensional (4D) adaptive radiation therapy (ART) treatment planning is an alternative to the conventional margin-based treatment planning approach. In 4D ART, interfraction patient geometric variations, gathered from computed tomography (CT) or cone beam CT (CBCT) images acquired during the patient treatment course, are directly incorporated into the adaptive plan optimization using a probabilistic treatment planning method. The goal of the present planning study was to evaluate the dosimetric differences between 4D ART and conventional margin-based adaptive planning strategies for head and neck cancers. In addition, we examined whether the dose differences achieved with 4D ART would translate into clinically relevant toxicity reductions using the existing normal tissue complication probability (NTCP) models. For 18 head and neck cancer patients, the treatment plans were retrospectively generated for 4 different treatment strategies, including a solely image guided radiation therapy (IGRT) strategy (IGRT-only), 2 conventional adaptive treatment planning strategies using 3- and 0-mm planning target volume (PTV) margins, and the 4D ART strategy. In the IGRT-only strategy, a conventional 3-mm PTV margin treatment plan was applied for the entire treatment course. In the 2 conventional adaptive strategies, 2 new treatment plans were generated during the treatment course using diagnostic planning CT scans acquired after the 10th and 22nd fractions. The 4D ART followed the same adaptive schedule, except that the 4D adaptive plan was generated using 5 CBCT images acquired during the 5 most recent treatment fractions. For each strategy, the actual delivered dose for the entire treatment course was constructed by calculating the daily doses on 35 CBCT scans, deforming back to the pretreatment planning CT scan, and accumulating over all 35 fractions. The target coverage was evaluated using the percentage of target volume receiving ≥100% of the prescription dose (V100%) and the minimum dose to 99% of the target volume (D99). It was considered adequate if the V100% was ≥95% and the dose deficit in D99 was ≤2Gy (with respect to the prescription dose). For each strategy, the dose received by the organs at risk (OARs) was also evaluated, and the corresponding NTCP values were subsequently calculated using 3 NTCP models. Adequate target coverage was achieved for the primary clinical target volume (CTV1) and elective nodal CTV (CTV2) with a 3-mm PTV margin, regardless of adaptation. The 3-mm ART plan reduced the OAR mean dose by 1 to 2Gy compared with the IGRT-only plan. The 0-mm ART plan further reduced the OAR dose by another 2 to 3Gy at the expense of target coverage: 3 and 1 patient had V100% <95%, and 6 and 5 patients had a >2 Gy dose deficit in D99 for the CTV1 and CTV2, respectively. Use of 4D ART improved target coverage and attained OAR sparing similar to that with 0-mm ART. The number of patients with V100% <95% and >2 Gy D99 deficit decreased to 0 and 0 for CTV1 and 0 and 2 for CTV2, respectively. The NTCP calculations suggested that 4D ART could benefit a substantial portion of patients compared with IGRT-only because 17 and 12 patients had ≥5% and ≥10% NTCP reductions for parotid toxicity and 18 and 3 patients had ≥5% and ≥10% NTCP reductions for swallowing toxicity, respectively. Compared with margin-based adaptive planning strategies, 4D ART provides a better balance between target coverage and OAR sparing. NTCP estimation predicted for theoretical clinical benefits that warrant further clinical validation.

A treatment planning comparison of proton therapy and intensity-modulated radiotherapy (IMRT) for prostate cancer using the normal tissue complication probability (NTCP).

153 Background: The volume of rectum receiving high-dose (i.e. &gt; or = 60 Gy) is consistently associated with the risk of Grade &gt; or = 2 rectal toxicity or rectal bleeding based on common terminology criteria for adverse events (CTCAE). Our goal was to compare intensity-modulated photon radiotherapy (IMRT) with proton radiotherapy in regard to the rectal dose using the normal tissue complication probability (NTCP). Methods: Between July 2014 and September 2015 the first 10 consecutive low or intermediate risk prostate cancer patients were treated with proton therapy at our institution. All 10 patients were planned with three-dimensional conformal proton therapy (3D-CPT) using two parallel opposed fields as well as comparison IMRT plans. A rectal balloon filled with water was used in all patients treated. Prescribed dose to the prostate was 79.2 Gy or cobalt Gy equivalent (CBE) for protons. Dose-volume histograms were compared. The Lyman-Kutcher-Burman model (n = 0.09, m = 0.13, and TD50 = 76.9 Gy) was used to generate NTCP estimates for both IMRT and proton plans. Results: At least 95% of the planning target volume received the prescription dose for both proton and IMRT plans. Dose constraints placed on the rectum included volume receiving 65 Gy (V65) less than 17% and V40 less than 35%. The mean dose to the rectum was 24.5 Gy (range, 19.5-30.1 Gy) and 31.7 Gy (range, 23.7-39.4 Gy) for the proton and IMRT plans, respectively. The V65 constraint was unachievable in 3 of the proton plans and 3 of the IMRT plans. The mean V70 and V75 for proton plans was 8.4% and 5.4% compared to 7.5% and 4.8% for the IMRT plans. The mean NTCP for proton treatment plans was 7.72% (range, 2.7-11.7%) and 7.92% (range, 1.7-15.3%) for IMRT (P = 0.45). After median follow-up of 6 months, no grade 2 or higher toxicity has been reported. Conclusions: Utilizing NTCP estimations, proton therapy and IMRT have similar predicted rates of rectal toxicity. Currently, a Phase III randomized clinical trial is underway comparing proton therapy and IMRT with regards to rectal toxicity and quality of life.

Estimation of late rectal normal tissue complication probability parameters in carbon ion therapy for prostate cancer

PurposeThe aim of this study was to estimate normal tissue complication probability (NTCP) parameters for late rectal complications after carbon ion radiotherapy (C-ion RT) for prostate cancer. Methods and materialsA total of 163 patients were used to derive NTCP parameters. These patients were treated with relative biological effectiveness (RBE)-weighted dose ranging from 57.6Gy (RBE) up to 72Gy (RBE) and included in dose escalation trials. The Lyman–Kutcher–Burman (LKB) model was used and the model parameters were fit to the relation between dose and complication observed after C-ion RT. ResultsThe resulting NTCP parameters were the volume effect parameter; n=0.035 (95% CI: 0.024–0.047), the steepness of the NTCP curve; m=0.10 (0.084–0.13), the tolerance dose associated with 50% probability of complication; TD50=63.6Gy (RBE) (61.8–65.4Gy (RBE)) for Grade⩾1, n=0.012 (0.0050–0.023), m=0.046 (0.033–0.062), TD50=69.1Gy (RBE) (67.6–70.9Gy (RBE)) for Grade⩾2. ConclusionA new set of rectal NTCP parameters in C-ion RT was determined. The rather small n values suggest that the rectum was consistent with being strictly serial organ. The new derived parameter values facilitate estimation of rectal NTCP in C-ion RT.

The Importance of Quasi-4D Path-Integrated Dose Accumulation for More Accurate Risk Estimation in Stereotactic Liver Radiotherapy.

Intrafraction organ deformation may be accounted for by inclusion of temporal information in dose calculation models. In this article, we demonstrate a quasi-4-dimensional method for improved risk estimation. Conventional 3-dimensional and quasi-4-dimensional calculations employing dose warping for dose accumulation were undertaken for patients with liver metastases planned for 42 Gy in 6 fractions of stereotactic body radiotherapy. Normal tissue complication probabilities and stochastic risks for radiation-induced carcinogenesis and cardiac complications were evaluated for healthy peripheral structures. Hypothetical assessments of other commonly employed dose/fractionation schedules on normal tissue complication probability estimates were explored. Conventional 3-dimensional dose computation may result in significant under- or overestimation of doses to organ at risk. For instance, doses differ (on average) by 17% (σ = 14%) for the left kidney, by 14% (σ = 7%) for the right kidney, by 7% (σ = 9%) for the large bowel, and by 10% (σ = 14%) for the duodenum. Discrepancies in the excess relative risk range up to about 30%. The 3-dimensional approach was shown to result in cardiac complication risks underestimated by >20%. For liver stereotactic body radiotherapy, we have shown that conventional 3-dimensional dose calculation may significantly over-/underestimate dose to organ at risk (90%-120% of the 4-dimensional estimate for the mean dose and 20%-150% for D2%). Providing dose estimates that most closely represent the actual dose delivered will provide valuable information to improve our understanding of the dose response for partial volume irradiation using hypofractionated schedules. Excess relative risks of radiocarcinogenesis were shown to range up to approximately excess relative risk = 4 and the prediction thereof depends greatly on the use of either 3-dimensional or 4-dimensional methods (with corresponding results differing by tens of percent).

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

ObjectivesTo 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.MethodsTwenty 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 (Pinnacle3). 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).ResultsIn 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.ConclusionsMCO 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.

Variation of normal tissue complication probability (NTCP) estimates of radiation-induced hypothyroidism in relation to changes in delineation of the thyroid gland

Background. To examine the variations of risk-estimates of radiation-induced hypothyroidism (HT) from our previously developed normal tissue complication probability (NTCP) model in patients with head and neck squamous cell carcinoma (HNSCC) in relation to variability of delineation of the thyroid gland.Patients and methods. In a previous study for development of an NTCP model for HT, the thyroid gland was delineated in 246 treatment plans of patients with HNSCC. Fifty of these plans were randomly chosen for re-delineation for a study of the intra- and inter-observer variability of thyroid volume, Dmean and estimated risk of HT. Bland-Altman plots were used for assessment of the systematic (mean) and random [standard deviation (SD)] variability of the three parameters, and a method for displaying the spatial variation in delineation differences was developed.Results. Intra-observer variability resulted in a mean difference in thyroid volume and Dmean of 0.4 cm3 (SD ± 1.6) and -0.5 Gy (SD ± 1.0), respectively, and 0.3 cm3 (SD ± 1.8) and 0.0 Gy (SD ± 1.3) for inter-observer variability. The corresponding mean differences of NTCP values for radiation-induced HT due to intra- and inter-observer variations were insignificantly small, -0.4% (SD ± 6.0) and -0.7% (SD ± 4.8), respectively, but as the SDs show, for some patients the difference in estimated NTCP was large.Conclusion. For the entire study population, the variation in predicted risk of radiation-induced HT in head and neck cancer was small and our NTCP model was robust against observer variations in delineation of the thyroid gland. However, for the individual patient, there may be large differences in estimated risk which calls for precise delineation of the thyroid gland to obtain correct dose and NTCP estimates for optimized treatment planning in the individual patient.

Variation in Clinical Target Volumes for Post-prostatectomy Patients and Effect on Normal Tissue Complication Probability

Background: Modern radiotherapy requires accurate contouring which may suffer in the post-surgical setting. We estimated post-prostatectomy inter- and intra-rater contouring reliability and assessed the effect on bladder and rectal normal tissue complication probability (NTCP). Methods: Four physicians each contoured two different treatment plans, separated by at least seven days, on 15 patients receiving post-prostatectomy four-field 3D-conformal radiotherapy. The Pinnacle 8.0 system determined CTV volume, shape, and center-of-volume coordinates. Inter- and intra-rater reliability was estimated using Gilder’s method. NTCP were estimated using parameters TD50=8190 cGy, n=0.23, m=0.19 for rectum and TD50=8000 cGy, n=0.5, m=0.11 for bladder. Results: Reliability estimates for center-of-volume were ≥0.993. Inter-rater reliability was ≤0.290 and intra-rater reliability between 0.375-0.729 for shape and volume. Inter-rater reliability estimates of NTCP were 0.398 for bladder and 0.0936 for rectum with highest inter-rater variation 4% and 8%, respectively. Intra-rater reliability NTCP estimates were 0.650 for bladder and 0.186 for rectum, with highest intra-rater NTCP variation 3% and 7%, respectively. Conclusions: Center-of-volume coordinates showed excellent agreement while volume and shape showed poor inter-rater, but moderate intra-rater, agreement. NTCP estimates showed generally poor agreement, but these differences were clinically significant only for rectum (not bladder), based on an a priori definition.

Dose Distribution in the Heart and Cardiac Chambers following 4-field Radiation Therapy of Breast Cancer: a Retrospective Study

Purpose:To evaluate cardiac doses in breast cancer patients with stage II/III treated with 4-field radiotherapy based on computed tomography (CT) dose planning.Methods and Materials:Based on archived CT images, whole heart and cardiac chamber radiation doses were analyzed in 216 (111 left-sided and 105 right-sided) mastectomized or lumpectomized breast cancer patients treated at a single institution, the Norwegian Radium Hospital, between 2000–2002. Individual dose volume histograms for the whole heart and for the four cardiac chambers were obtained, and mean, median and maximum doses to these structures were calculated. The dose (Gy) delivered to the 5% of the volume of each cardiac structure (D5%), and the volume percentage of each structure receiving ≥ 25 Gy (V25Gy) were reported. Normal tissue complication probability (NTCP) calculations were used to estimate the risk for ischemic heart disease (IHD).Results:Cohort-based medians of the whole heart mean dose (Dmean) for left- and right-sided tumors were 3.2 Gy and 1.3 Gy, respectively, with similar ventricular but lower atrial values. The atrial doses did not differ according to laterality of the breast tumor. In 13 patients with left-sided cancer, 5% of the heart volume was exposed to >25 Gy. The NTCP estimates were generelly low, with a maximum of 2.8%.Conclusions:During adjuvant CT-based locoregional radiotherapy of women with breast cancer, the cardiac radiation doses are, at the group level, below recommended threshold values (D5% < 25 Gy), though individual patients with left-sided disease may exceed these limits.

Normal Tissue Complication Probability Estimation by the Lyman-Kutcher-Burman Method Does Not Accurately Predict Spinal Cord Tolerance to Stereotactic Radiosurgery

To determine whether normal tissue complication probability (NTCP) analyses of the human spinal cord by use of the Lyman-Kutcher-Burman (LKB) model, supplemented by linear-quadratic modeling to account for the effect of fractionation, predict the risk of myelopathy from stereotactic radiosurgery (SRS). From November 2001 to July 2008, 24 spinal hemangioblastomas in 17 patients were treated with SRS. Of the tumors, 17 received 1 fraction with a median dose of 20 Gy (range, 18-30 Gy) and 7 received 20 to 25 Gy in 2 or 3 sessions, with cord maximum doses of 22.7 Gy (range, 17.8-30.9 Gy) and 22.0 Gy (range, 20.2-26.6 Gy), respectively. By use of conventional values for α/β, volume parameter n, 50% complication probability dose TD(50), and inverse slope parameter m, a computationally simplified implementation of the LKB model was used to calculate the biologically equivalent uniform dose and NTCP for each treatment. Exploratory calculations were performed with alternate values of α/β and n. In this study 1 case (4%) of myelopathy occurred. The LKB model using radiobiological parameters from Emami and the logistic model with parameters from Schultheiss overestimated complication rates, predicting 13 complications (54%) and 18 complications (75%), respectively. An increase in the volume parameter (n), to assume greater parallel organization, improved the predictive value of the models. Maximum-likelihood LKB fitting of α/β and n yielded better predictions (0.7 complications), with n= 0.023 and α/β= 17.8 Gy. The spinal cord tolerance to the dosimetry of SRS is higher than predicted by the LKB model using any set of accepted parameters. Only a high α/β value in the LKB model and only a large volume effect in the logistic model with Schultheiss data could explain the low number of complications observed. This finding emphasizes that radiobiological models traditionally used to estimate spinal cord NTCP may not apply to the dosimetry of SRS. Further research with additional NTCP models is needed.

On the use of published radiobiological parameters and the evaluation of NTCP models regarding lung pneumonitis in clinical breast radiotherapy

In this study we sought to evaluate and accent the importance of radiobiological parameter selection and implementation to the normal tissue complication probability (NTCP) models. The relative seriality (RS) and the Lyman-Kutcher-Burman (LKB) models were studied. For each model, a minimum and maximum set of radiobiological parameter sets was selected from the overall published sets applied in literature and a theoretical mean parameter set was computed. In order to investigate the potential model weaknesses in NTCP estimation and to point out the correct use of model parameters, these sets were used as input to the RS and the LKB model, estimating radiation induced complications for a group of 36 breast cancer patients treated with radiotherapy. The clinical endpoint examined was Radiation Pneumonitis. Each model was represented by a certain dose-response range when the selected parameter sets were applied. Comparing the models with their ranges, a large area of coincidence was revealed. If the parameter uncertainties (standard deviation) are included in the models, their area of coincidence might be enlarged, constraining even greater their predictive ability. The selection of the proper radiobiological parameter set for a given clinical endpoint is crucial. Published parameter values are not definite but should be accompanied by uncertainties, and one should be very careful when applying them to the NTCP models. Correct selection and proper implementation of published parameters provides a quite accurate fit of the NTCP models to the considered endpoint.

Analysis of Radiation Pneumonitis Risk Using a Generalized Lyman Model

To introduce a version of the Lyman normal-tissue complication probability (NTCP) model adapted to incorporate censored time-to-toxicity data and clinical risk factors and to apply the generalized model to analysis of radiation pneumonitis (RP) risk. Medical records and radiation treatment plans were reviewed retrospectively for 576 patients with non-small cell lung cancer treated with radiotherapy. The time to severe (Grade >/=3) RP was computed, with event times censored at last follow-up for patients not experiencing this endpoint. The censored time-to-toxicity data were analyzed using the standard and generalized Lyman models with patient smoking status taken into account. The generalized Lyman model with patient smoking status taken into account produced NTCP estimates up to 27 percentage points different from the model based on dose-volume factors alone. The generalized model also predicted that 8% of the expected cases of severe RP were unobserved because of censoring. The estimated volume parameter for lung was not significantly different from n = 1, corresponding to mean lung dose. NTCP models historically have been based solely on dose-volume effects and binary (yes/no) toxicity data. Our results demonstrate that inclusion of nondosimetric risk factors and censored time-to-event data can markedly affect outcome predictions made using NTCP models.

Sensitivity of NTCP parameter values against a change of dose calculation algorithm

Optimization of radiation treatment planning requires estimations of the normal tissue complication probability (NTCP). A number of models exist that estimate NTCP from a calculated dose distribution. Since different dose calculation algorithms use different approximations the dose distributions predicted for a given treatment will in general depend on the algorithm. The purpose of this work is to test whether the optimal NTCP parameter values change significantly when the dose calculation algorithm is changed. The treatment plans for 17 breast cancer patients have retrospectively been recalculated with a collapsed cone algorithm (CC) to compare the NTCP estimates for radiation pneumonitis with those obtained from the clinically used pencil beam algorithm (PB). For the PB calculations the NTCP parameters were taken from previously published values for three different models. For the CC calculations the parameters were fitted to give the same NTCP as for the PB calculations. This paper demonstrates that significant shifts of the NTCP parameter values are observed for three models, comparable in magnitude to the uncertainties of the published parameter values. Thus, it is important to quote the applied dose calculation algorithm when reporting estimates of NTCP parameters in order to ensure correct use of the models.