Equivalent Uniform Dose Model Research Articles

Normal tissue complication probability modeling for late rectal bleeding after conventional or hypofractionated radiotherapy for prostate cancer

PurposeTo develop a single NTCP model for grade ≥ 2 late rectal bleeding (G2 LRB) after conventional or hypofractionated radiotherapy for prostate cancer. Methods and MaterialsThe development dataset consisted of prostate cancer patients (n = 656) previously randomized to conventional (39 x 2 Gy) or hypofractionated (19 x 3.4 Gy) external beam radiotherapy with N = 89 G2 LRB cases. Candidate predictors were obtained from literature. We fitted five separate logistic regression models to the data, each with one of the following dose parameters as candidate predictors in biological effective dose (BED), assuming α/β = 3 Gy: Equivalent uniform dose (EUD) with n = 0.1, EUD with n = 0.2, the relative volume receiving ≥ 111.9 Gy in BED (V111.9, the equivalent of physical V70 for a conventional schedule), minimum BED to the hottest 0.1 cm3 (D0.1cm3) or 2 cm3 (D2cm3). Previous abdominal surgery was included in every model and fractionation schedule was tested as predictor in each model. A sensitivity analysis was performed by varying the α/β-ratio, n and dose-volume cutoff. ResultsThe pre-selected candidate dosimetric predictor and previous abdominal surgery were significantly associated with the outcome in all five models. Fractionation schedule was eliminated by the backward scheme in only the EUD (n = 0.1), D0.1cm3 and D2cm3-based models. In internal validation these models showed AUC’s of 0.64, 0.60 & 0.62, respectively. The sensitivity analyses showed that EUD models with n ≥ 0.15 and / or α/β ≥ 4 Gy failed, and EUD models based on α/β = 2 Gy with n = 0.05–0.2 showed good fits as well. ConclusionsOur trial data set with different fractionation schedules offered the unique possibility to generate unbiased BED-based models. EUD (n = 0.1), D0.1cm3 and D2cm3 performed overall best in predicting G2 LRB; with α/β = 2 Gy equally good models were obtained. External validation is required to confirm our results.

Determination of Fractionation Scheme Based on Repair Effect Using Equivalent Uniform Dose (EUD) Model

Radiotherapy treatment planning is required to obtain an optimal balance between delivering a high dose to target volume and a low dose to organ at risks. In this planning, it is also necessary to determine the appropriate fractionation scheme for each patient. One of the commonly used methods to determine the fractionation scheme is calculating the Normal Tissue Complication Probability (NTCP) and Tumor Control Probability (TCP) parameters. In this study, the Equivalent Uniform Dose (EUD) model is used to calculate NTCP and TCP. This model is based on a non-uniform dose distribution that is sensitive to the biological factors of cells. The biological factor examined in this research is the repair effect, which is the ability of cells to repair themselves after being radiated. Thus, the objective of this research is to determine the fractionation scheme based on NTCP calculations using the EUD model while taking into account the repair effect. The data used in this study were obtained from 10 patients with glioblastoma brain cancer in the form of cumulative DVH (dose-volume histogram) and total time of radiation. Based on the NTCP calculations, the average risk of organ complication for each patient appears to be close to zero, with a range of values from 2 x 10-6% to 1 x 10-1%. These results indicate that the treatment planning conducted is proven to be safe and there are no complications for the patients. Furthermore, based on the NTCP and TCP calculations, the best fractionation scheme is hypofractionation, which remains safe while considering the dose limit for each normal organ surrounding the target.

Radiobiological evaluation of hypo-fractionated breast cancer radiotherapy regimens in comparison with conventional approaches

Abstract Purpose: This study compares tumor control probability (TCP) and normal tissue complication probability (NTCP) across different hypo-fractionated (HypoRT) and conventional breast radiotherapy regimens using radiobiological models. Materials and methods: Computed tomography data from 30 patients with left breast-conserving surgery were used to evaluate three HypoRT regimens (39 Gy and 41·6 Gy in 13 fractions, and 40 Gy in 15 fractions) and a conventional regimen (50 Gy in 25 fractions). Dose-volume histograms (DVHs) were extracted for radiobiological calculations using Equivalent Uniform Dose (EUD) and Poisson models for TCP, and EUD and LKB (Lyman-Kutcher-Burman) models for NTCP. Results: Conventional treatment achieved significantly higher TCP (95%) than all HypoRT regimens (p < 0·001), with no significant differences between HypoRT regimens (p > 0·05. The 39 Gy/13 fraction regimen showed the lowest lung NTCP (p < 0·05). HypoRT regimens had significantly lower NTCP for the lungs and heart compared to the conventional regimen (p < 0·01). TCP and NTCP values from Poisson and LKB models were higher than those from the EUD model (p < 0·01). Conclusion: HypoRT regimens reduced NTCP, with the lowest values in the regime of 39 Gy/13 fractions regimen, though the conventional regimen had higher TCP.

NTCP Calculations of Five Different Irradiation Techniques for the Treatment of Thymoma.

This study provided normal tissue complication probability (NTCP) calculations from photon radiotherapy techniques in eleven patients with thymoma. Five plans were created for each participant using three-dimensional conformal radiotherapy (3D-CRT), five-field intensity modulated radiotherapy (5F-IMRT), seven-field IMRT (7F-IMRT), and volumetric modulated arc therapy with full arcs (FA-VMAT) and partial arcs (PA-VMAT). The target coverage, homogeneity index and conformation number for the planning target volume (PTV) and dosimetric parameters for the organs-at-risk (OARs) were taken from the fifty-five generated plans. The patient-specific NTCP of the lungs, heart and esophagus was calculated with an in-house software tool using differential dose-volume histograms and the equivalent uniform dose model. The PTV dose metrics from 3D-CRT were inferior to those from IMRT and VMAT plans. The dose constraints for the OARs were met in all treatment plans. The NTCP range of the lungs, heart and esophagus was 0.34-0.49%, 0.03-0.06% and 0.08-0.10%, respectively. The NTCPs of the heart for the incidence of peridarditis from IMRT and VMAT were significantly smaller than those from conformal treatment (p < 0.05). The 7F-IMRT was significantly superior to FA-VMAT in reducing the NTCP of the lungs and the risk of pneumonitis (p = 0.001). Similar superiority of 5F-IMRT over PA-VMAT for lung protection was found (p = 0.009). The presented results may be employed in the selection of the appropriate irradiation technique for restricting the complications in the adjacent OARs.

Comparison of a Hybrid IMRT/VMAT technique with non-coplanar VMAT and non-coplanar IMRT for unresectable olfactory neuroblastoma using the RayStation treatment planning system—EUD, NTCP and planning study

The purpose of this study was to compare hybrid intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (Hybrid IMRT/VMAT), with non-coplanar (nc) IMRT and nc-VMAT treatment plans for unresectable olfactory neuroblastoma (ONB). Hybrid IMRT/VMAT, nc-IMRT and nc-VMAT plans were optimized for 12 patients with modified Kadish C stage ONB. Dose prescription was 65 Gy in 26 fractions. Dose–volume histogram parameters, conformation number (CN), homogeneity index (HI), integral dose and monitor units (MUs) delivered per fraction were assessed. Equivalent uniform dose (EUD) and normal tissue complication probability (NTCP) based on the EUD model (NTCPLogit) and the Lyman–Kutcher–Burman model (NTCPLKB) were also evaluated. We found that the Hybrid IMRT/VMAT plan significantly improved the CN for clinical target volume (CTV) and planning treatment volume (PTV) compared with the nc-VMAT plan. In general, sparing of organs at risk (OARs) is similar with the three techniques, although the Hybrid IMRT/VMAT plan resulted in a significantly reduced Dmax to contralateral (C/L) optic nerve compared with the nc-IMRT plan. The Hybrid IMRT/VMAT plan significantly reduce EUD to the ipsilateral (I/L) and C/L optic nerve in comparison with the nc-IMRT plan and nc-VMAT plan, but the difference in NTCP between the three technique was <1%. We concluded that the Hybrid IMRT/VMAT technique can offer improvement in terms of target conformity and EUD for optic nerves, while achieving equal or better OAR sparing compared with nc-IMRT and nc-VMAT, and can be a viable radiation technique for treating unresectable ONB. However, the clinical benefit of these small differences in dosimetric data, EUD and NTCP of optic nerves may be minimal.

Comparison of Radiobiological Models for Radiation Therapy Plans of Prostate Cancer: Three-dimensional Conformal versus Intensity Modulated Radiation Therapy.

Purpose:In the current study, using different radiobiological models, tumor control probability (TCP) and normal tissue complication probability (NTCP) of radiotherapy plans were calculated for three-dimensional conformal radiation therapy (3D-CRT) and intensity modulated radiation therapy (IMRT) of prostate cancer. Methods and Materials: 10 prostate plans were randomly selected among patients undergoing radiation therapy of prostate cancer. For each patient, 3D-CRT and IMRT plans were designed to deliver, on average 76 Gy and 82 Gy to planning target volume, respectively. Using different radiobiological models including Poisson, equivalent uniform dose (EUD) and Lyman-Kutcher-Burman (LKB), TCP and NTCP were calculated for prostate and critical organs including bladder, rectum and femoral heads. Results:IMRT plans provided significantly lower NTCP for bladder, rectum and femoral heads using LKB and EUD models (p-value <0.05). The EUD-calculated TCP for prostate cancer revealed no considerable improvement for IMRT plans relative to 3D-CRT plans. However, the TCPs calculated by Poisson model were dependent on α/β, and higher TCP for IMRT relative to 3D-CRT was seen for α/β higher than 5. Conclusion: It can be concluded that IMRT plans were superior to 3D-CRT plans in terms of estimated NTCP for studied critical organs. On the other hand, different mathematical models provided different quantitative outcome for TCP of prostate cancer plans. More clinical studies are suggested to confirm the accuracy of studied radiobiological models.

The Role of radiobiological parameters on Tumor control probability (TCP) in prostate cancer

Introduction: The aim of this study was to evaluation radiobiological modeling parameters on tumor control probability (TCP) for prostate cancer in three different models. These parameters included α⁄β ratios and cell surviving fraction at 2 Gy (SF2). Materials and Methods: The Poisson, equivalent uniform dose (EUD) and linear quadratic (LQ) models was used as the radiobiological models. TCP was calculated in 10 prostate cancer patients as a function of α⁄β ratios (1.5-20) for all radiobiological models and SF2 (0.3-0.7) for LQ model. For each patient, 3D-CRT and IMRT plans were designed to deliver, on average 76 Gy and 82 Gy to planning target volume, respectively. Results: The TCPs calculated by Poisson model were dependent on α/β, results demonstrated that dose escalation from 76 Gy in 3D-CRT to 82 Gy for IMRT caused 5% improvement in TCP for prostate cancer considering the α/β of 10 and higher TCP for IMRT relative to 3D-CRT was seen for α/β higher than 5. According to our results for EUD model the TCPs were independent on α/β. In the LQ model with increase in α/β in specific SF2, TCP will not change remarkable. but with the change of SF2 from 0.7 to 0.3, TCP values change from 0 to 100 % at the prescribed doses in both treatment planning’s. Conclusion: Different mathematical models provided different quantitative outcome for TCP of prostate cancer plans. The IMRT plans were significantly advantageous over the 3DCRT plans with some small variations in each patient. more studies are needed for the optimization of radiobiological models for the prediction of the treatment outcomes in radiation therapy.

Radiobiological Model-Based Comparison of Three-Dimensional Conformal and Intensity-Modulated Radiation Therapy Plans for Nasopharyngeal Carcinoma

Introduction: Radiobiological modeling of radiotherapy plans are used for treatment plan comparisons. The current study aimed to compare the three-dimensional conformal radiation therapy (3DCRT) and intensity-modulated radiation therapy (IMRT) plans for nasopharyngeal cancer using radiobiological modeling. Materials and Methods: This study was conducted on 10 patients with nasopharyngeal carcinoma, who were planned for 3DCRT and IMRT treatments by using the TiGRT treatment planning system. The planning target volume (PTV) doses of 70 and 72 Gy were administered for the 3DCRT and IMRT plans, respectively. The BIOLPLAN software and the Niemierko’s equivalent uniform dose (EUD) model were utilized for the estimation of tumor control probability (TCP) and normal tissue complication probability (NTCP). The NTCPs of the spinal cord, brain stem, parotid glands, middle ears, temporomandibular joints (TMJ), mandible, and thyroid were calculated by using two radiobiological models. Results: According to the results, the mean TCPs for 3DCRT and IMRT plans were 89.92%±8.92 and 94.9%±3.86, respectively, showing no statistically significant difference (P=0.08). The NTCPs of the parotid glands, thyroid gland, spinal cord, TMJ, and mandible were considerably lower in the IMRT plans, compared to those in the 3DCRT plans. On the other hand, the calculated NTCPs for the middle ears and brain stem increased for the IMRT plans, which were not statistically significant. On average, the NTCPs of the critical organs were lower based on the EUD model than the Lyman-Kutcher-Burman model. Conclusion: From the radiobiological point of view, the IMRT plans were significantly advantageous over the 3DCRT plans with some small variations in each patient. On average, the two radiobiological models generated different NTCPs depending on the studied organs. Consequently, more studies are needed for the optimization of radiobiological models for the prediction of the treatment outcomes in radiation therapy.

The use of TCP based EUD to rank and compare lung radiotherapy plans: in-silico study to evaluate the correlation between TCP with physical quality indices.

To apply the equivalent uniform dose (EUD) radiobiological model to estimate the tumor control probability (TCP) scores for treatment plans using different radiobiological parameter settings, and to evaluate the correlation between TCP and physical quality indices of the treatment plans. Ten radiotherapy treatment plans for lung cancer were generated. The dose distributions were calculated using anisotropic analytical algorithm (AAA). Dose parameters and quality indices derived from dose volume histograms (DVH) for target volumes were evaluated. The predicted TCP was computed using EUD model with tissue-specific parameter (a=-10). The assumed radiobiological parameter setting for adjuvant therapy [tumor dose to control 50% of the tumor (TCD50) =36.5 Gy and γ50=0.72] and curative intent (TCD50=51.24 Gy and γ50=0.83) were used. The bootstrap method was used to estimate the 95% confidence interval (95% CI). The coefficients (ρ) from Spearman's rank test were calculated to assess the correlation between quality indices with TCP. Wilcoxon paired test was used to calculate P value. The 95% CI of TCP were 70.6-81.5 and 46.6-64.7, respectively, for adjuvant radiotherapy and curative intent. The TCP outcome showed a positive and good correlation with calculated dose to 95% of the target volume (D95%) and minimum dose (Dmin). Consistently, TCP correlate negatively with heterogeneity indices. This study confirms that more relevant and robust radiobiological parameters setting should be integrated according to cancer type. The positive correlation with quality indices gives chance to improve the clinical out-come by optimizing the treatment plans to maximize the Dmin and D95%. This attempt to increase the TCP should be carried out with the respect of dose constraints for organs at risks. However, the negative correlation with heterogeneity indices shows that the optimization of beam arrangements could be also useful. Attention should be paid to obtain an appropriate optimization of initial plans, when comparing and ranking radiotherapy plans using TCP models, to avoid over or underestimated for TCP outcome.

The benefit of using bladder sub-volume equivalent uniform dose constraints in prostate intensity-modulated radiotherapy planning.

BackgroundTo assess the benefits of bladder wall sub-volume equivalent uniform dose (EUD) constraints in prostate cancer intensity-modulated radiotherapy (IMRT) planning.MethodsTwo IMRT plans, with and without EUD constraints on the bladder wall, were generated using beams that deliver 80 Gy to the prostate and 46 Gy to the seminal vesicles and were compared in 53 prostate cancer patients. The bladder wall was defined as the volume between the external manually delineated wall and a contraction of 7 mm apart from it. The bladder wall was then separated into two parts: the internal-bladder wall (bla-in) represented by the portion of the bladder wall that intersected with the planning target volume (PTV) plus 5 mm extension; the external-bladder wall (bla-ex) represented by the remaining part of the bladder wall. In the IMRT plan with EUD constraints, the values of “a” parameter for the EUD models were 10.0 for bla-in and 2.3 for bla-ex. The plans with and without EUD constraints were compared in terms of dose–volume histograms, 5-year bladder and rectum normal tissue complication probability values, as well as tumor control probability (TCP) values.ResultsThe use of bladder sub-volume EUD constraints decreased both the doses to the bladder wall (V70: 22.76% vs 19.65%, Dmean: 39.82 Gy vs 35.45 Gy) and the 5-year bladder complication probabilities (≥LENT/SOMA Grade 2: 20.35% vs 17.96%; bladder bleeding: 10.63% vs 8.64%). The doses to the rectum wall and the rectum complication probabilities were also slightly decreased by the EUD constraints compared to physical constraints only. The minimal dose and the V76Gy of PTVprostate were, however, slightly decreased by EUD optimization, nevertheless without significant difference in TCP values between the two plans, and the PTV parameters finally respected the Groupe d’Etude des Tumeurs Uro-Génitales recommendations.ConclusionSeparating the bladder wall into two parts with appropriate EUD optimization may reduce bladder toxicity in prostate IMRT. Combining biological constraints with physical constraints in the organs at risk at the inverse planning step of IMRT may improve the dose distribution.

SU‐E‐P‐42: Benefit of Equivalent Uniform Dose in Prostate IMRT Planning to Reduce Bladder Toxicity

Purpose:To assess the benefit of bladder wall sub‐volume equivalent uniform dose (EUD) constrains in prostate cancer IMRT planningMethods:The bladder wall was defined by the volume between the external manually delineated wall and a contraction of 7 mm from this external wall. This bladder wall was then separated into two parts: the internal‐bladder wall (bla‐in) represented by the portion of the bladder wall that intersected with the planning target volume (PTV) plus 5 mm extension; the external‐bladder wall (bla‐ex) represented by the remaining part of the bladder wall. Two IMRT plans, with and without using EUD constraints, were generated and compared for 53 prostate cancer patients, to deliver 80Gy to the prostate PTV (V95&gt;95%). In the plan with EUD constraints, the values of the “a” parameter of the EUD models were: 10.0 for bla‐in and 2.3 for bla‐ex., and 5 for the rectum.Results:The use of bladder EUD objectives increased significantly the conformal index (0.73±0.04 vs. 0.93±0.02) and decreased both the doses in the bladder wall (V70: 22.66% vs. 18.88%, Dmean: 39.40Gy vs. 35.04Gy) and the bladder wall NTCP values (NTCP at 3 years bladder toxicity &gt;= LENT/SOMA Grade2: 16.68% vs. 14.48%, NTCP at 3 years bladder bleeding: 7.16% vs. 5.88%, NTCP at 5 years bladder toxicity &gt;= LENT/SOMA Grade2: 20.15% vs. 17.75%, NTCP at 5 years bladder bleeding: 10.38% vs. 8.36%). The use of bladder EUD objectives, although slightly decreasing the dose to the rectum wall (Dmax: 75.19Gy vs. 75.05Gy, V72: 12.95Gy vs. 12.72Gy) as well, increased however the dose in the femoral heads (V55‐femoral head left: 0.06% vs. 0.30%, V55‐femoral head right: 0.04% vs. 0.21%).Conclusion:Separating bladder wall into two parts with appropriate bladder EUD objectives may reduce bladder toxicity, while keeping high dose to the prostate.

P13.25 * A RADIOBIOLOGICAL COMPARISON BETWEEN THE INVERSE INTENSITY MODULATED RADIATION THERAPY AND THE FIELD IN FIELD INTENSITY MODULATED RADIATION THERAPY FOR THE TREATMENT OF GLIOBLASTOMA

For critical structures the use of maximum or mean dose limits in the intensity modulated radiation therapy (IMRT) optimization is not very meaningful. The dose-volume limits and equivalent uniform dose (EUD) which is defined as the uniform dose that would lead to the same effect as the given non-uniform dose in as particular organ are combined to analyze the volume effect. The normal tissue complication probability (NTCP) is a predictor of radiobiological effect for organs at risk (OAR). The calculation of the NTCP is based on the DVH which is generated by the treatment planning system after calculation of the 3D dose distribution. Uniform EUD irradiation of an OAR results in the same NTCP as the original non-homogeneous distribution. The NTCP equation is therefore represented as a function of EUD. The inverse equation expresses EUD as a function of NTCP. Expressing NTCP in terms of EUD represents a step toward simplifying the conceptual framework for modeling probability of expected complications. The aim of this study is to compare radiobiological effects between the fif IMRT and inverse IMRT for treatment of Glioblastoma (GBM) using the equivalent uniform dose (EUD) and normal tissue complication probability (NTCP). Five representative patients treated with definitive radiation using IMRT at our clinic in the last two year were selected for treatment planning study. Criteria for inclusion were glioblastoma . The normal tissues (Organ at Risk, OaR) contoured included brain-stem, optic chiasm, optic nerves, right-left cohclea and whole brain. Brain was defined as total brain tissue minus the PTV. Two different radiation therapy techniques; inverse IMRT and FiF IMRT treatment plans were optimised with the prescription dose 60 Gy/30 fractions. All those calculations and IMRT optimizations were performed using the Prowess Panther DAQ TPS with 6 MV,Siemens Artiste, MLC with 160 leaves and evaluated by using EUD and NTCP models. In the present study, target dose coverage was improved with inverse IMRT planning as compared with fif IMRT planning. With respect to NTCP there is no significant differences between fif IMRT planning and inverse IMRT planning. For the optic chiasm, brainstem, right-left eyes and right-left lens the NTCP values were calculated to be smaller than %1 for both IMRT plannings, except for GBM3 patient as a result of eye(L) concurrent with PTV. So the maximum NTCP was 1 for lens(L) of GBM3 patient for both plannings. Eye(L) of NTCP values were 0.15479 and 0.10896 respectively for this patient with a frontosfenoidal tumor and a biggest size of tumor, 8.82 cm. After obtaining these results we decided to compare also the total monitor units (MU) of optimizations. Then, we find that total MU value of the fif IMRT plannings are smaller than inverse IMRT plannings. So, the fif IMRT planning can be chosen for short treatment time and comfort of the patients for GBM patients treatment.

Dose-response of acute urinary toxicity of long-course preoperative chemoradiotherapy for rectal cancer

Background. Long-course preoperative chemoradiotherapy (chemo-RT) improves outcomes for rectal cancer patients, but acute side effects during treatment may cause considerable patient discomfort and may compromise treatment compliance. We developed a dose-response model for acute urinary toxicity based on a large, single-institution series.Material and methods. In total 345 patients were treated with (chemo-)RT for primary rectal cancer from January 2007 to May 2012. Urinary toxicity during RT was scored prospectively using the CTCAE v 3.0 cystitis score (grade 0–5). Clinical variables and radiation dose to the bladder were related to graded toxicity using multivariate ordinal logistic regression. Three models were optimized, each containing all available clinical variables and one of three dose metrics: Mean dose (Dmean), equivalent uniform dose (EUD), or relative volume given x Gy or above (dose cut-off model, Vx). The optimal dose metric was chosen using the Akaike Information Criterion (AIC).Results. Grade 1 cystitis was experienced by 138 (40%), grade 2 by 39 (11%) and grade 3 by two (1%) patients, respectively. Dose metrics were significantly correlated with toxicity in all models, but the dose cut-off model provided the best AIC value. The only significant clinical risk factors in the Vx model were male gender (p = 0.006) and brachytherapy boost (p = 0.02). Reducing the model to include gender, brachytherapy boost and Vx yielded odds ratios ORmale = 1.82 (1.17–2.80), ORbrachy = 1.36 (1.02–1.80 for each 5 Gy), x = 35.1 Gy (28.6–41.5 Gy). The predicted risk of grade 2 and above cystitis ranged from 2% to 26%.Conclusion. Acute cystitis correlated significantly with radiation dose to the bladder; the dose-cut-off model (V35Gy) was superior to Dmean and EUD models. Male gender and brachytherapy boost increased the risk of toxicity. Wide variation in predicted risks suggests room for treatment optimization using individual dose constraints.

SU‐E‐T‐312: Test of the Generalized Tumor Dose (gTD) Model with An Independent Lung Tumor Dataset

Purpose:We previously developed a novel approach to tumor response modeling which was inspired by the gEUD model of tumor cell kill under inhomogeneous dose profiles. The model assumes that the cell‐kill law is valid, but further adds a parameter analogous to the generalized equivalent uniform dose model to test the independence of response of tumor subvolumes. The purpose of this study was to test the resulting generalized tumor dose (gTD) model on an independent lung cancer subset.Methods:Niemierko's gEUD model of cell kill introduces a generalization term describing interactions among tumor sub‐volumes under non‐uniform dose distributions. This parameter effectively applies weights to sub‐volumes based off of tumor type‐specific sensitivities to variance in dose. We combine the gEUD with the cell‐kill based cEUD to form the “generalized tumor dose” (gTD) model, which is given by gTD=‐α−1*ln(Vt/Vref)‐ (α*a)−1*ln(Σi=1:subvolsM#subvols−1 *e (‐α*a*di)). This model was previously applied to lung and H&amp;N data. Here, we apply the model to an independent lung dataset (N= 36).Results:We found that the model does not perform well for large tumors (volume &gt; 70 cc.) However,. However, for tumors smaller than this volume, the model was well‐correlated with local control, with a normalized log‐likelihood value (log‐likelihood divided by the number of cases) of −0.604.Conclusion:The presented model continues to predict tumor response in this dataset, for tumors less than 70 cc. To date, no other TCP model has been validated on clinical datasets for tumors with varying volumes and dose distributions. More tests are needed to further refine and validate the model.

Datamining approaches for modeling tumor control probability

Background. Tumor control probability (TCP) to radiotherapy is determined by complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables. The complexity of these heterogeneous variable interactions constitutes a challenge for building predictive models for routine clinical practice. We describe a datamining framework that can unravel the higher order relationships among dosimetric dose-volume prognostic variables, interrogate various radiobiological processes, and generalize to unseen data before when applied prospectively. Material and methods. Several datamining approaches are discussed that include dose-volume metrics, equivalent uniform dose, mechanistic Poisson model, and model building methods using statistical regression and machine learning techniques. Institutional datasets of non-small cell lung cancer (NSCLC) patients are used to demonstrate these methods. The performance of the different methods was evaluated using bivariate Spearman rank correlations (rs). Over-fitting was controlled via resampling methods. Results. Using a dataset of 56 patients with primary NCSLC tumors and 23 candidate variables, we estimated GTV volume and V75 to be the best model parameters for predicting TCP using statistical resampling and a logistic model. Using these variables, the support vector machine (SVM) kernel method provided superior performance for TCP prediction with an rs=0.68 on leave-one-out testing compared to logistic regression (rs=0.4), Poisson-based TCP (rs=0.33), and cell kill equivalent uniform dose model (rs=0.17). Conclusions. The prediction of treatment response can be improved by utilizing datamining approaches, which are able to unravel important non-linear complex interactions among model variables and have the capacity to predict on unseen data for prospective clinical applications.

Dosimetric Parameters in Partial Breast Irradiation Through Brachytherapy

The objective of this work is to evaluate biological models and dose homogeneity in a new partial breast irradiation method, the MammoSite RTS. The study is based on 11 patients who received the therapy. For each patient, we determined the dose volume distribution delivered to the breast. Based on these data, we estimate some important biological parameters. Eleven patients with early-stage, invasive, ductal breast cancer were treated using MammoSite RTS brachytherapy, which delivers radiation through a balloon placed in the lumpectomy bed. The radiation was provided by an Iridium-192 source, and 340 cGy were delivered per fraction twice daily. We calculated some commonly used dosimetric parameters, and evaluated the biological parameters tumor control probability (TCP) and normal tissue complication probability (NTCP). We also looked for correlations among these parameters. The average equivalent uniform dose (EUD), NTCP, and TCP were 43.66 Gy, 47.95%, and 91.78%, respectively. The coefficient of variation (CV) among the patients was very low for all 3 parameters. Two dose homogeneity indices (DHI and the S-index) are strongly correlated ( r = −0.815). The area under the dose-volume histogram (DVH) and the treatment volume (TXV) also showed a strong correlation ( r = 0.995, p < 0.0001). A simplified logit Poisson–EUD model is suitable for determining NTCP and TCP. Other factors such as the area under the DVH and dose homogeneity indices are also useful in planning radiotherapy treatments for early breast cancer.

Self‐consistent tumor control probability and normal tissue complication probability models based on generalized EUDa)

Traditional methods to compute the tumor control probability (TCP) or normal tissue complication probability (NTCP) typically require a heterogeneous radiation dose distribution to be converted into a simple uniform dose distribution with an equivalent biological effect. Several power-law type dose-volume-histogram reduction schemes, particularly Niemierko's generalized equivalent uniform dose model [Med. Phys. 26, 1000 (1999)], have been proposed to achieve this goal. In this study, we carefully examine the mathematical outcome of these schemes. We demonstrate that (1) for tumors, with each tumor cell independently responding to local radiation dose, a closed-form analytical solution for tumor survival fraction and TCP can be obtained; (2) for serial structured normal tissues, an exponential power-law form relating survival to functional sub-unit (FSU) radiation is required, and a closed-form analytical solution for the related NTCP is provided; (3) in the case of a parallel structured normal tissue, when NTCP is determined solely by the number of the surviving FSUs, a mathematical solution is available only when there is a non-zero threshold dose and/or a finite critical dose defining the radiotherapy response. Some discussion is offered for the partial irradiation effect on normal tissues in this category; (4) for normal tissues with alternative architectures, where the radiation response of FSU is inhomogeneous, there is no exact global mathematical solution for SF or NTCP within the available schemes. Finally, numerical fits of our models to some experimental data are also presented.

Comparison of three concomitant boost techniques for early-stage breast cancer

Whole breast radiotherapy (RT) followed by a tumor bed boost typically spans 5-6 weeks of treatment. Interest is growing in RT regimens, such as concomitant boost, that decrease overall treatment time, lessening the time/cost burden to patients and facilities. Computed tomography (CT) scans from 20 cases were selected for this retrospective, dosimetric study to compare three different techniques of concomitant boost delivery: (1) standard tangents plus an electron boost, (2) intensity-modulated RT (IMRT) tangents using custom compensators plus an electron boost, and (3) IMRT tangents plus a conformal photon boost. The equivalent uniform dose model was used to compare the plans. The average breast equivalent uniform dose value for the three techniques (standard, IMRT plus electrons, and IMRT plus photons) was 48.6, 47.9, and 48.3, respectively. The plans using IMRT more closely approximated the prescribed dose of 46 Gy to the whole breast. The breast volume receiving >110% of the dose was less with the IMRT tangents than with standard RT (p = 0.037), but no significant difference in the maximal dose or other evaluated parameters was noted. Although the IMRT techniques delivered the prescribed dose with better dose uniformity, the small improvement seen did not support a goal of improved resource use.

Predicting the risk of radiation-induced lung injury using a biophysical parameter

Predicting the risk of radiation-induced lung injury using a biophysical parameter

Predicting the risk of radiation-induced lung injury using a biophysical parameter

This research work is based on the premise that many normal organs have heterogeneous volumes with spatially variable function. Consequently, the utilization of biological models that incorporate functional imaging information is imperative in predicting and quantifying the risk of radiation-induced normal organs toxicity. The objective of this work is to correlate lung toxicity data from non-small cell lung cancer (NSCLC) patients with values from the functional equivalent uniform dose biological model, so that such information may be used to predict the risk of radiation-induced lung injury. The data from 38 NSCLC patients with single photon emission computed tomography (SPECT) perfusion data, who received 3DCRT treatments at our institution, were analyzed. The patients’ dose-volume histograms were used to calculate the lung generalized equivalent uniform dose (EUD) values. The EUD reports the generalized mean value of the non-uniform dose distribution, which represents the homogenous dose distribution that produces the same lung complication as that produced by the inhomogeneous dose distribution. The patients’ dose-function histograms (DFH), which relates dose to the percentage of total function value at that dose, were used to calculate lung functional EUD (FEUD) values. The DFH incorporates lung SPECT perfusion imaging data. A treatment plan with a low lung FEUD value implies more sparing of functional sub-units and this may result in lower complications. The CT anatomical-volume of lungs was first correlated with changes in SPECT regional perfusion data. The lungs dose distributions were then evaluated using the generalized EUD and FEUD models with a lung a value of 0.96 (a or 1/n is a critical structure specific parameter which describes the dose-volume effect). The a parameter value was calculated using the tolerance dose values of Emami et al to the whole lung and partial volumes that would result in a 5% complication probability in 5 years (TD5/5). The biophysical parameter (RFE), which is the ratio of FEUD to EUD, was evaluated for each patient in order to predict the risk of radiation-induced lung pneumonitis (RP) by correlating the patients’ outcome data with the RFE values. Figure 1(left) shows the lungs FEUD and EUD data for the lung patients with and without RP. The results suggest that there is a correlation between RFE and lung RP. Twenty-three out of 32 patients without RP have FEUD values less than EUD (RFE <1). Six out of 8 patients with RP have FEUD values higher or equal to EUD (RFE ≥ 1). The RFE data quantify the radiation-induced lung toxicity (i.e. the risk of RP is higher with the irradiation of more functioning lungs) and suggest that RFE may be used as predictor for RP. Figure 2(right) shows FEUD and EUD for the lung patients with their tumor T staging. The majority of patients with tumor staging T3 and T4 have FEUD values equal or less than EUD (RFE <1). Patients with stage T1 have FEUD values approximately equal to EUD. The RFE data show that as tumor aggressiveness increases, the lung function decreases, which may be due to tumor obstruction of blood flow to the lung vessels. The biophysical parameter (RFE), which combines EUD and FEUD, quantifies radiation-induced lung injury, a fact that is not revealed by the physical EUD data alone. Furthermore, this work shows that predictions from biological models that incorporate both dose-function and dose-volume information correlate better with patient outcome data.