Lyman Normal Tissue Complication Probability Research Articles

Predicting Lung Radiotherapy-Induced Pneumonitis Using a Model Combining Parametric Lyman Probit With Nonparametric Decision Trees

To develop and test a model to predict for lung radiation-induced Grade 2+ pneumonitis. The model was built from a database of 234 lung cancer patients treated with radiotherapy (RT), of whom 43 were diagnosed with pneumonitis. The model augmented the predictive capability of the parametric dose-based Lyman normal tissue complication probability (LNTCP) metric by combining it with weighted nonparametric decision trees that use dose and nondose inputs. The decision trees were sequentially added to the model using a "boosting" process that enhances the accuracy of prediction. The model's predictive capability was estimated by 10-fold cross-validation. To facilitate dissemination, the cross-validation result was used to extract a simplified approximation to the complicated model architecture created by boosting. Application of the simplified model is demonstrated in two example cases. The area under the model receiver operating characteristics curve for cross-validation was 0.72, a significant improvement over the LNTCP area of 0.63 (p = 0.005). The simplified model used the following variables to output a measure of injury: LNTCP, gender, histologic type, chemotherapy schedule, and treatment schedule. For a given patient RT plan, injury prediction was highest for the combination of pre-RT chemotherapy, once-daily treatment, female gender and lowest for the combination of no pre-RT chemotherapy and nonsquamous cell histologic type. Application of the simplified model to the example cases revealed that injury prediction for a given treatment plan can range from very low to very high, depending on the settings of the nondose variables. Radiation pneumonitis prediction was significantly enhanced by decision trees that added the influence of nondose factors to the LNTCP formulation.

WE‐C‐BRA‐04: Optimising Radiotherapy Using NTCP Models: 17 Years in Ann Arbor

Phase One clinical trials seek to determine the maximum tolerated dose (MTD) of the investigational treatment. Similarly, traditional radiation oncology dose escalation trials assign groups of patients to increasing dose levels until an unacceptable level of complications appear. This generally transpires on a sequential basis, regardless of tumor size or the distribution pattern of radiation dose to surrounding normal tissues (beyond the specification of a few well‐accepted dose constraints such as maximum spinal cord dose). This can be a poor strategy for treatments limited primarily by complications to so‐called volume‐effect normal tissues which encompass the tumors, such as may be the case for tumors located in the liver or lung. A better scheme for Phase I/II dose escalation trials limited by these volume effect organs would attempt to treat sequential groups of patients with dose “distributions” that might be expected to lead to similar anticipated levels of complications (but of course with different tumor doses); with sequential escalation of each potential iso‐complication level until an MTD profile is realized (which would inherently include the volume effect). The use of normal tissue complication probability (NTCP) models prospectively, in the treatment planning process, facilitates this type of normal tissue iso‐complication based dose escalation.Given the desire for iso‐NTCP based dose escalation, clinical trials were developed and carried out at the University of Michigan for tumors located in the liver and lungs. In the 3‐D conformal therapy era, these trials took place via recognition of one particular aspect of the effective volume (Veff) dose volume histogram (DVH) reduction scheme (due to Kutcher and Burman) often employed in order to use the Lyman NTCP model for non‐uniformly irradiated organs. That is, computation of a normal tissue Veff for a particular dose distribution does not depend on the units of dose in the treatment plan (e.g., Gy, cGy/hr, or of greatest interest here, % dose). Given this, we recognized that treatment planning could proceed in the normal manner of that time (dose distributions generated in relative dose (%) with respect to an ICRU reference point prescription dose (most often the isocenter)), while at the same time attempts could be made to minimize the Veff of the dose limiting normal tissue, with ultimate physical isocenter normalization dose (Dnorm in Gy) prescribed after planning. That is, each Veff has a corresponding Dnorm leading to a fixed iso‐NTCP level. Thus, reductions in Veff generated during treatment planning, led to individualized increases in prescription isocenter dose after planning (a perceived benefit/goal for the treatment planner), all at fixed perceived level of NTCP. In the IMRT/optimization era, biological cost functions have been developed to accomplish these same goals.This talk will summarize experiences in iso‐NTCP dose escalation and planning at the University of Michigan for tumors in the liver and lungs; including current, ongoing, functional imaging based, adaptive treatment trials. Work supported in great part by NIH grant P01‐CA59827.Educational Objective:Understand the basis and ongoing use of iso‐NTCP based dose escalation at the University of Michigan.

Prediction of radiation-induced liver disease by Lyman normal-tissue complication probability model in three-dimensional conformal radiation therapy for primary liver carcinoma: In regards to Xu et al. (Int J Radiat Oncol Biol Phys 2006;65:189–195)

Prediction of radiation-induced liver disease by Lyman normal-tissue complication probability model in three-dimensional conformal radiation therapy for primary liver carcinoma: In regards to Xu et al. (Int J Radiat Oncol Biol Phys 2006;65:189–195)

Dose–volume modeling of the risk of postoperative pulmonary complications among esophageal cancer patients treated with concurrent chemoradiotherapy followed by surgery

The aim of this study was to investigate the effect of radiation dose distribution in the lung on the risk of postoperative pulmonary complications among esophageal cancer patients. We analyzed data from 110 patients with esophageal cancer treated with concurrent chemoradiotherapy followed by surgery at our institution from 1998 to 2003. The endpoint for analysis was postsurgical pneumonia or acute respiratory distress syndrome. Dose-volume histograms (DVHs) and dose-mass histograms (DMHs) for the whole lung were used to fit normal-tissue complication probability (NTCP) models, and the quality of fits were compared using bootstrap analysis. Normal-tissue complication probability modeling identified that the risk of postoperative pulmonary complications was most significantly associated with small absolute volumes of lung spared from doses > or = 5 Gy (VS5), that is, exposed to doses < 5 Gy. However, bootstrap analysis found no significant difference between the quality of this model and fits based on other dosimetric parameters, including mean lung dose, effective dose, and relative volume of lung receiving > or = 5 Gy, probably because of correlations among these factors. The choice of DVH vs. DMH or the use of fractionation correction did not significantly affect the results of the NTCP modeling. The parameter values estimated for the Lyman NTCP model were as follows (with 95% confidence intervals in parentheses): n = 1.85 (0.04, infinity), m = 0.55 (0.22, 1.02), and D50 = 17.5 Gy (9.4 Gy, 102 Gy). In this cohort of esophageal cancer patients, several dosimetric parameters including mean lung dose, effective dose, and absolute volume of lung receiving < 5 Gy provided similar descriptions of the risk of postoperative pulmonary complications as a function of the radiation dose distribution in the lung.

A theoretical approach to the problem of dose-volume constraint estimation and their impact on the dose-volume histogram selection

This paper outlines a theoretical approach to the problem of estimating and choosing dose-volume constraints. Following this approach, a method of choosing dose-volume constraints based on biological criteria is proposed. This method is called "reverse normal tissue complication probability (NTCP) mapping into dose-volume space" and may be used as a general guidance to the problem of dose-volume constraint estimation. Dose-volume histograms (DVHs) are randomly simulated, and those resulting in clinically acceptable levels of complication, such as NTCP of 5 +/- 0.5%, are selected and averaged producing a mean DVH that is proven to result in the same level of NTCP. The points from the averaged DVH are proposed to serve as physical dose-volume constraints. The population-based critical volume and Lyman NTCP models with parameter sets taken from literature sources were used for the NTCP estimation. The impact of the prescribed value of the maximum dose to the organ, D(max), on the averaged DVH and the dose-volume constraint points is investigated. Constraint points for 16 organs are calculated. The impact of the number of constraints to be fulfilled based on the likelihood that a DVH satisfying them will result in an acceptable NTCP is also investigated. It is theoretically proven that the radiation treatment optimization based on physical objective functions can sufficiently well restrict the dose to the organs at risk, resulting in sufficiently low NTCP values through the employment of several appropriate dose-volume constraints. At the same time, the pure physical approach to optimization is self-restrictive due to the preassignment of acceptable NTCP levels thus excluding possible better solutions to the problem.

Sci‐Sat AM (1) General‐06: Theoretical estimation of dose volume constraints and their impact on DVH selection

Dose‐volume constraints are essential for treatment planning optimization using physical objective functions. A theoretical approach to the problem of choosing dose‐volume constraints based on the reverse normal tissue complication probability (NTCP) mapping into dose‐volume space is developed. Dose‐volume histograms (DVHs) are randomly simulated and those resulting in clinically acceptable levels of complication, e.g. NTCP of 5±0.5%, are selected and averaged producing a mean DVH which is proven to result in the same level of NTCP. The points from the averaged DVH are proposed to serve as dose‐volume constraints for treatment planning optimization using physical objective functions. The population based Critical Volume and the Lyman NTCP models with parameter sets taken from literature were used for the NTCP estimation. Constraint points for 16 organs are calculated. These dose‐volume constraints are not unique and depend on the range in which the maximum dose to the organ at risk, Dmax, is allowed to vary. It is theoretically proven that the radiation treatment optimization based on physical objective functions can sufficiently well restrict the dose to the organs at risk resulting in sufficiently low NTCP values through the employment of several appropriate dose‐volume constraints. At the same time, the pure physical approach to optimization is self‐restrictive due to the pre‐assignment of acceptable NTCP levels thus excluding possible better solutions to the problem.

Prediction of radiation-induced liver disease by Lyman normal-tissue complication probability model in three-dimensional conformal radiation therapy for primary liver carcinoma

To describe the probability of RILD by application of the Lyman-Kutcher-Burman normal-tissue complication (NTCP) model for primary liver carcinoma (PLC) treated with hypofractionated three-dimensional conformal radiotherapy (3D-CRT). A total of 109 PLC patients treated by 3D-CRT were followed for RILD. Of these patients, 93 were in liver cirrhosis of Child-Pugh Grade A, and 16 were in Child-Pugh Grade B. The Michigan NTCP model was used to predict the probability of RILD, and then the modified Lyman NTCP model was generated for Child-Pugh A and Child-Pugh B patients by maximum-likelihood analysis. Of all patients, 17 developed RILD in which 8 were of Child-Pugh Grade A, and 9 were of Child-Pugh Grade B. The prediction of RILD by the Michigan model was underestimated for PLC patients. The modified n, m, TD50 (1) were 1.1, 0.28, and 40.5 Gy and 0.7, 0.43, and 23 Gy for patients with Child-Pugh A and B, respectively, which yielded better estimations of RILD probability. The hepatic tolerable doses (TD5) would be MDTNL of 21 Gy and 6 Gy, respectively, for Child-Pugh A and B patients. The Michigan model was probably not fit to predict RILD in PLC patients. A modified Lyman NTCP model for RILD was recommended.

Normal tissue complication probability modeling for acute esophagitis in patients treated with conformal radiation therapy for non-small cell lung cancer

Purpose To evaluate the ability of a well-known normal tissue complication probability (NTCP) model to predict radiation esophagitis by determining updated model parameters and then comparing these results with the predictive value of other dosimetric parameters. Material and methods Clinical and dosimetric data regarding esophagitis were analyzed in 101 inoperable/unresectable non-small-cell lung cancer patients treated by external beam irradiation. Grade 2 or higher esophagitis counted as events. Parameters ( TD 50 , n, and m) of the Lyman normal tissue complication probability (NTCP) model were determined using maximum likelihood analysis, and compared to other dose/volume threshold values including: percentage of esophagus receiving >40 Gy (V40) to >75 Gy (V75), and maximum esophageal doses. Results Sixteen patients developed grade 2–3 acute esophagitis (no G4 or 5). The maximum likelihood analysis produced new Lyman model parameters of: TD 50 =51 Gy, n=0.44 and m=0.32. The mean NTCP value is significantly lower ( P<0.001) in the group of patients without esophagitis (13.5%) than with esophagitis (27.2%). The rates of esophagitis are 2.5, 7, 9 and 13.4%, respectively, when the NTCP values are <10%, <15%, <20% and <25%. A significant association is found between esophagitis and dose/volume parameters V40 ( P=0.001) to V70 ( P=0.024). Conclusions New values of TD 50 , n and m offer a good description of the esophagitis distribution in our population. Compared to the use of this model with previously published parameters (associated with late toxicity) predictions of the model for acute esophagitis using the new parameters would indicate that, for a population of patients, the distribution of events as a function of uniform dose would occur with a lower mean uniform dose value (smaller TD 50 ), over a wider range of uniform doses (larger m), while also exhibiting a bigger volume effect (larger n). These new parameter values are supported in essence by the correlations found for the dose/volume threshold parameters.

Partial Volume Tolerance of the Liver to Radiation

The use of conformal radiotherapy (RT) and the follow-up of patients for radiation liver toxicities has led to a quantitative understanding of partial liver RT tolerance. The most common toxicity is radiation-induced liver disease (RILD), a syndrome of anicteric ascites and hepatomegaly. Elevation of transaminases and reactivation of viral hepatitis have also been reported after liver RT. The Lyman normal tissue complication probability (NTCP) model and a local damage-organ injury NTCP model have been used to describe the partial tolerance of the liver to RT. The liver exhibits a large volume effect and a low threshold volume for RILD. The RT tolerance of the liver is reduced in patients with primary liver cancer versus metastases. Elevated transaminases are more common in the presence of poor liver function and hepatitis B infection. If the effective liver volume irradiated is less than 25%, very high RT doses may be delivered with little risk of liver toxicity. The mean liver doses associated with a 5% risk of classic RILD for primary and metastatic liver cancer are 28 Gy and 32 Gy, respectively, in 2 Gy per fraction.

Evaluating the influence of setup uncertainties on treatment planning for focal liver tumors

A mechanism has been developed to evaluate the influence of random setup variations on dose during treatment planning. The information available for studying these factors shifts from population-based models toward patient-specific data as treatment progresses and setup measurements for an individual patient become available. This study evaluates the influence of population as well as patient-specific setup distributions on treatment plans for focal liver tumors. Eight patients with focal liver tumors were treated on a protocol that involved online setup measurement and adjustment, as well as ventilatory immobilization. Summary statistics from these three-dimensional conformal treatments yielded individual and population distributions of position at initial setup for each fraction. A convolution model for evaluation of the influence of random setup variation on calculated dose distributions has been previously described and investigated for application to focal liver radiotherapy by our department. Individual patient doses based on initial setup positions were calculated by convolving the calculated dose distribution with an anisotropic probability distribution function representing the individual patient's random variations. A separate convolution using population-averaged random variations was performed. Individual beam apertures were then adjusted to provide plans that ensured proper dose to the clinical target volume following convolution with population distributions, as well as individual patient position uncertainty models. Individual patient setup distributions for the course of treatment had random setup variations (sigma) that ranged from 2.5 to 5.7 mm (left-right), 2.1 to 8.3 mm (anterior-posterior), and 4.1 to 10.8 mm (cranial-caudal). The population random components were 4.2 mm (left-right), 4.1 mm (anterior-posterior), and 7.0 mm (cranial-caudal) at initial setup. The initial static planned dose distribution overestimated the volume of liver irradiated to high doses, because inclusion of setup uncertainties generally blurred the resulting doses, shifting the higher-dose region of normal liver dose-volume histograms to lower doses. Furthermore, the population-based dose convolution tended to predict a higher risk of radiation damage to the liver (based on an in-house parameterization of the Lyman normal tissue complication probability model) than the individual patient calculations. For an individual plan, application of different individual random variations yielded change in effective volume differences with a 3% range. Plan adjustment to account for random setup variations generally resulted in a lower change in effective volume than initial planning using a planning target volume followed by calculation of delivered dose based on random offsets. This study hints at the factors that most strongly influence planning of liver treatments taking into account geometric variations. Given a setup verification methodology that rapidly reduces systematic offsets, the importance of realistic incorporation of geometric variations as an initial step in treatment planning, as well as possible plan refinement, is demonstrated.

Predicting radiotherapy‐induced cardiac perfusion defects

The purpose of this work is to compare the efficacy of mathematical models in predicting the occurrence of radiotherapy-induced left ventricular perfusion defects assessed using single-photon emission computed tomography (SPECT). The basis of this study is data from 73 left-sided breast/ chestwall patients treated with tangential photon fields. The mathematical models compared were three commonly used parametric models [Lyman normal tissue complication probability (LNTCP), relative serialty (RS), generalized equivalent uniform dose (gEUD)] and a nonparametric model (Linear discriminant analysis--LDA). Data used by the models were the left ventricular dose--volume histograms, or SPECT-based dose-function histograms, and the presence/absence of SPECT perfusion defects 6 months postradiation therapy (21 patients developed defects). For the parametric models, maximum likelihood estimation and F-tests were used to fit the model parameters. The nonparametric LDA model step-wise selected features (volumes/function above dose levels) using a method based on receiver operating characteristics (ROC) analysis to best separate the groups with and without defects. Optimistic (upper bound) and pessimistic (lower bound) estimates of each model's predictive capability were generated using ROC curves. A higher area under the ROC curve indicates a more accurate model (a model that is always accurate has area = 1). The areas under these curves for different models were used to statistically test for differences between them. Pessimistic estimates of areas under the ROC curve using dose-volume histogram/ dose-function histogram inputs, in order of increasing prediction accuracy, were LNTCP (0.79/0.75), RS (0.80/0.77), gEUD (0.81/0.78), and LDA (0.84/0.86). Only the LDA model benefited from SPECT-based regional functional information. In general, the LDA model was statistically superior to the parametric models. The LDA model selected as features the left ventricular volumes above approximately 23 Gy (V23), essentially volume in field, and 33 Gy (V33), as best separating the groups with and without defects. In conclusion, the nonparametric LDA model appears to be a more accurate predictor of radiotherapy-induced left ventricular perfusion defects than commonly used parametric models.

Dose-volume factors contributing to the incidence of radiation pneumonitis in non-small-cell lung cancer patients treated with three-dimensional conformal radiation therapy

Purpose: To analyze acute lung toxicity data of non-small-cell lung cancer patients treated with three-dimensional conformal radiation therapy in terms of dosimetric variables, location of dose within subvolumes of the lungs, and models of normal-tissue complication probability (NTCP).Methods and Materials: Dose distributions of 49 non-small-cell lung cancer patients treated in a dose escalation protocol between 1992 and 1999 were analyzed (dose range: 57.6–81 Gy). Nine patients had RTOG Grade 3 or higher acute lung toxicity. Correlation with dosimetric and physical variables, as well as Lyman and parallel NTCP models, was assessed. Lungs were evaluated as a single structure, as superior and inferior halves (to assess significance of dose to upper and lower lungs), and as ipsilateral and contralateral lungs.Results: For the whole lung, Grade 3 or higher pneumonitis was significantly correlated (p ≤ 0.05) with mean dose and Lyman and parallel model indices (deff and fdam). It was significantly correlated with these indices and with V20 for the ipsilateral lung and with mean dose and deff for the inferior half of the lungs. Dosimetric and NTCP model quantities for the superior half of the lungs and contralateral lung were not significantly correlated (p > 0.5 for superior lung indices, and >0.1 for contralateral lung indices studied).Conclusions: For these patients, commonly used dosimetric and NTCP models are significantly correlated with ≥ Grade 3 pneumonitis. Equivalently strong correlations are found in the lower portion of the lungs and the ipsilateral lung, but not in the upper portion or contralateral lung.

Radiation-induced liver disease after three-dimensional conformal radiotherapy for patients with hepatocellular carcinoma: dosimetric analysis and implication

Purpose: To analyze the correlation of radiation-induced liver disease (RILD) with patient-related and treatment-related dose-volume factors and to describe the probability of RILD by a normal tissue complication probability (NTCP) model for patients with hepatocellular carcinoma (HCC) treated with three-dimensional conformal radiotherapy (3D-CRT). Methods and Materials: Between November 1993 and December 1999, 93 patients with intrahepatic malignancies were treated with 3D-CRT at our institution. Sixty-eight patients who were diagnosed with HCC and had complete 3D dose-volume data were included in this study. Of the 68 patients, 50 had chronic viral hepatitis before treatment, either type B or type C. According to the Child-Pugh classification for liver cirrhosis, 53 patients were in class A and 15 in class B. Fifty-two patients underwent transcatheter arterial chemoembolization with an interval of at least 1 month between transcatheter arterial chemoembolization and 3D-CRT to allow adequate recovery of hepatic function. The mean dose of radiation to the isocenter was 50.2 ± 5.9 Gy, in daily fractions of 1.8–2Gy. No patient received whole liver irradiation. RILD was defined as Grade 3 or 4 hepatic toxicity according to the Common Toxicity Criteria of the National Cancer Institute. All patients were evaluated for RILD within 4 months of RT completion. Three-dimensional treatment planning with dose-volume histogram analysis of the normal liver was used to compare the dosimetric difference between patients with and without RILD. Maximal likelihood analysis was conducted to obtain the best estimates of parameters of the Lyman NTCP model. Confidence intervals of the fitted parameters were estimated by the profile likelihood method. Results: Twelve of the 68 patients developed RILD after 3D-CRT. None of the patient-related variables were significantly associated with RILD. No difference was found in tumor volume (780 cm 3 vs. 737 cm 3, p = 0.86), normal liver volume (1210 cm 3 vs. 1153 cm 3, p = 0.64), percentage of normal liver volume with radiation dose >30 Gy (V 30 Gy; 42% vs. 33%, p = 0.05), and percentage of normal liver volume with >50% of the isocenter dose (V 50%; 45% vs. 36%, p = 0.06) between patients with and without RILD. The mean hepatic dose was significantly higher in patients with RILD (2504 cGy vs. 1965 cGy, p = 0.02). The probability of RILD in patients could be expressed as follows: probability = 1/[1 + exp −(0.12 × mean dose − 4.29)], with coefficients significantly different from 0. The best estimates of the parameters in the Lyman NTCP model were the volume effect parameter of 0.40, curve steepness parameter of 0.26, and 50% tolerance dose for uniform irradiation of whole liver [TD 50(1)] of 43 Gy. Patients with RILD had a significantly higher NTCP than did those with no RILD (26.2% vs. 15.8%; p = 0.006), using the best-estimated parameters. Conclusion: Dose-volume histogram analysis can be effectively used to quantify the tolerance of the liver to RT. Patients with RILD had received a significantly higher mean dose to the liver and a significantly higher NTCP. The fitted volume effect parameter of the Lyman NTCP model was close to that from the literature, but much lower in our patients with HCC and prevalent chronic viral hepatitis than that reported in other series with patients with normal liver function. Additional efforts should be made to test other models to describe the radiation tolerance of the liver for Asian patients with HCC and preexisting compromised hepatic reserve.

Analysis of radiation-induced liver disease using the Lyman NTCP model

Purpose: To describe the dose—volume tolerance for radiation-induced liver disease (RILD) using the Lyman—Kutcher—Burman (LKB) normal tissue complication probability (NTCP) model.Methods and Materials: A total of 203 patients treated with conformal liver radiotherapy and concurrent hepatic arterial chemotherapy were prospectively followed for RILD. Normal liver dose—volume histograms and RILD status for these patients were used as input data for determination of LKB model parameters. A complication was defined as Radiation Therapy Oncology Group Grade 3 or higher RILD ≤4 months after completion of radiotherapy. A maximal likelihood analysis yielded best estimates for the LKB NTCP model parameters for the liver for the entire patient population. A multivariate analysis of the potential factors associated with RILD was also completed, and refined LKB model parameters were obtained for patient subgroups with different risks of RILD.Results: Of 203 patients treated with focal liver irradiation, 19 developed RILD. The LKB NTCP model fit the complication data for the entire group. The “n” parameter was larger than previously described, suggesting a strong volume effect for RILD and a correlation of NTCP with the mean liver dose. No cases of RILD were observed when the mean liver dose was <31 Gy. Multivariate analysis demonstrated that in addition to NTCP and the mean liver dose, a primary hepatobiliary cancer diagnosis (vs. liver metastases), bromodeoxyuridine hepatic artery chemotherapy (vs. fluorodeoxyuridine chemotherapy), and male gender were associated with RILD. For 169 patients treated with fluorodeoxyuridine, the refined LKB model parameters were n = 0.97, m = 0.12, tolerance dose for 50% complication risk for whole organ irradiated uniformly [TD50(1)] = 45.8 Gy for patients with liver metastases, and TD50(1) = 39.8 Gy for patients with primary hepatobiliary cancer.Conclusion: These data demonstrate that the liver exhibits a large volume effect for RILD, suggesting that the mean liver dose may be useful in ranking radiation plans. The inclusion of clinical factors, especially the diagnosis of primary hepatobiliary cancer vs. liver metastases, improves the estimation of NTCP over that obtained solely by the use of dose—volume data. These findings should facilitate the application of focal liver irradiation in future clinical trials.

Partial irradiation of the liver

The use of three-dimensional radiotherapy (RT) and the prospective follow-up of patients for radiation-induced liver disease (RILD) have led to a more quantitative understanding of the partial organ tolerance of the liver compared with previous estimates based on clinical judgment alone. Parameters of both the Lyman normal tissue complication probability (NTCP) model and a local damage-organ injury (D-I) NTCP model have been fit to clinical data from patients who have received hepatic radiation. Based on analyses of over 180 patients, the liver exhibits a large volume effect and a low threshold volume for RILD. Mean liver dose is associated with RILD, and no cases of RILD have been reported in patients with a mean liver dose of less than 31 Gy. Most recent estimates of the partial liver tolerance to RT suggest that if less than 25% of the normal liver is treated with RT, then there may be no upper limit on dose associated with RILD. Estimates of the liver doses associated with a 5% risk of RILD for uniform irradiation of one third, two thirds, and the whole liver are 90 Gy, 47 Gy, and 31 Gy, respectively.

A method of analyzing rectal surface area irradiated and rectal complications in prostate conformal radiotherapy

To develop a method of analyzing rectal surface area irradiated and rectal complications in prostate conformal radiotherapy. Dose-surface histograms of the rectum, which state the rectal surface area irradiated to any given dose, were calculated for a group of 27 patients treated with a four-field box technique to a total (tumor minimum) dose ranging from 68 to 70 Gy. Occurrences of rectal toxicities as defined by the Radiation Therapy Oncology Group (RTOG) were recorded and examined in terms of dose and rectal surface area irradiated. For a specified end point of rectal complication, the complication probability was analyzed as a function of dose irradiated to a fixed rectal area, and as a function of area receiving a fixed dose. Lyman's model of normal tissue complication probability (NTCP) was used to fit the data. The observed occurrences of rectal complications appear to depend on the rectal surface area irradiated to a given dose level. The patient distribution of each toxicity grade exhibits a maximum as a function of percentage surface area irradiated, and the maximum moves to higher values of percentage surface area as the toxicity grade increases. The dependence of the NTCP for the specified end point on dose and percentage surface area irradiated was fitted to Lyman's NTCP model with a set of parameters. The curvature of the NTCP as a function of the surface area suggests that the rectum is a parallel structured organ. The described method of analyzing rectal surface area irradiated yields interesting insight into understanding rectal complications in prostate conformal radiotherapy. Application of the method to a larger patient data set has the potential to facilitate the construction of a full dose-surface-complication relationship, which would be most useful in guiding clinical practice.