基于EUD鼻咽癌调强放疗中NTCP和TCP的计算程序设计研究

目的 设计一个基于等效均一剂量（EUD）的计算程序来计算鼻咽癌调强放疗（IMRT）计划中正常组织并发症概率（NTCP）和肿瘤控制概率（TCP）。方法 采用具有较强数学特性及友好交互界面等优势的高效编程语言Matlab编写计算NTCP和TCP程序,其中NTCP 数学模型选用基于EUD的Lyman Kutcher Burman模型,而TCP模型则选用Schultheiss逻辑模型 。收集3例接受IMRT治疗的鼻咽癌患者的正常组织和靶区剂量体积直方图（DVH）,计划系统为医科达precise plan。结果编写计算机代码保存为Matlab可执行程序。3例鼻咽癌患者的4种正常组织（脑干、脊髓、左右侧腮腺）和肿瘤的EUD被编写程序算出,进而计算出NTCP和TCP。结论 编写的程序对正常组织耐受量的计算结果与理论值非常吻合,有助于临床选择更安全和高效的治疗方案,将来还可将程序用于其他肿瘤如前列腺癌和肺癌的放疗计划中。     

A Test of the Claim that Plan Rankings are Determined by Relative Complication and Tumor-Control Probabilities

Purpose: This study tests an accepted claim regarding tumor control (TCP) and normal tissue complication (NTCP) probability functions. The claim is that treatment plans can be ranked using relative probabilities, even when the absolute probabilities are unknown. The assumption supports the use of probability models for plan optimization and the comparison of treatment techniques.Methods: The claim was tested using a hypothetical model consisting of two tissues, and illustrated with clinical data. Plans were scored using the probability of uncomplicated tumor control. The scores of different plans were compared by fixing their relative risks for an individual tissue complication, but adjusting the absolute probability levels up or down. The tested claim is that the plan rankings should not change.Results: In the two-tissue model, the rankings of competing plans were reversed by doubling all the probabilities. The preference ordering of lung cancer plans changed after the risk of pulmonary complication was reduced by 3-fold. In another site, the ranking of plans by overall complication-free probability was disturbed by errors that preserved the ordering of plans with respect to any individual complication. An adjustment of ± 2.5% in the initial NTCP values for two tissues changed the direction in which a plan score moved in response to a fixed tradeoff in complication risk in an optimization search.Conclusions: Contrary to claims, plan rankings are not determined by the relative probabilities of adverse events. The effect on plan scores of trading one complication for another depends on the absolute levels of risk. Absolute errors in NTCP and TCP functions result in the wrong ranking of plans, even when relative probabilities are correct. An optimization routine based on TCP and NTCP calculations may be forced in the wrong direction by small errors in the probability estimates.     

The impact of geometric uncertainty on hypofractionated external beam radiation therapy of prostate cancer

PURPOSE: Recent publications indicate alpha/beta for prostate carcinoma could be lower than assumed. Therefore, hypofractionation might increase the therapeutic ratio. However, patient repositioning and organ motion may affect hypofractionated treatments more than conventional treatments. Our purpose is to evaluate the potential impact of geometric uncertainties on hypofractionated treatments. METHODS AND MATERIALS: Tumor control probability (TCP) and normal tissue complication probability (NTCP) are calculated for simulated conventional and hypofractionated treatments, assuming alpha/beta of 1.5 Gy for prostate and 3.0 Gy for rectum. A Monte Carlo simulation randomly samples systematic and random displacements and produces the cumulative dose distribution for the prostate and rectum. The limiting number of fractions and the impact of different alpha/beta values are also explored. RESULTS: A consistent but small reduction in TCP is seen with hypofractionation (generally <1%) as a result of geometric uncertainties. Escalated hypofractionation seems to allow large TCP gains ( approximately 20%) without increasing NTCP. Treatments of five fractions seem to affect outcome minimally. The alpha/beta value has a much greater impact on TCP than geometric uncertainties. CONCLUSION: The potential increased influence of geometric uncertainties on hypofractionation seems small. Limited knowledge of radiobiologic response is likely a greater obstacle to prostate hypofractionation than geometric uncertainties.     

Dose-volume histograms

A plot of a cumulative dose-volume frequency distribution, commonly known as a dose-volume histogram (DVH), graphically summarizes the simulated radiation distribution within a volume of interest of a patient which would result from a proposed radiation treatment plan. DVHs show promise as tools for comparing rival treatment plans for a specific patient by clearly presenting the uniformity of dose in the target volume and any hot spots in adjacent normal organs or tissues. However, because of the loss of positional information in the volume(s) under consideration, it should not be the sole criterion for plan evaluation. DVHs can also be used as input data to estimate tumor control probability (TCP) and normal tissue complication probability (NTCP). The sensitivity of TCP and NTCP calculations to small changes in the DVH shape points to the need for an accurate method for computing DVHs. We present a discussion of the methodology for generating and plotting the DVHs, some caveats, limitations on their use and the general experience of four hospitals using DVHs.     

Risk-adaptive optimization: selective boosting of high-risk tumor subvolumes

BACKGROUND AND PURPOSE: A tumor subvolume-based, risk-adaptive optimization strategy is presented. METHODS AND MATERIALS: Risk-adaptive optimization employs a biologic objective function instead of an objective function based on physical dose constraints. Using this biologic objective function, tumor control probability (TCP) is maximized for different tumor risk regions while at the same time minimizing normal tissue complication probability (NTCP) for organs at risk. The feasibility of risk-adaptive optimization was investigated for a variety of tumor subvolume geometries, risk-levels, and slopes of the TCP curve. Furthermore, the impact of a correlation parameter, delta, between TCP and NTCP on risk-adaptive optimization was investigated. RESULTS: Employing risk-adaptive optimization, it is possible in a prostate cancer model to increase the equivalent uniform dose (EUD) by up to 35.4 Gy in tumor subvolumes having the highest risk classification without increasing predicted normal tissue complications in organs at risk. For all tumor subvolume geometries investigated, we found that the EUD to high-risk tumor subvolumes could be increased significantly without increasing normal tissue complications above those expected from a treatment plan aiming for uniform dose coverage of the planning target volume. We furthermore found that the tumor subvolume with the highest risk classification had the largest influence on the design of the risk-adaptive dose distribution. The parameter delta had little effect on risk-adaptive optimization. However, the clinical parameters D(50) and gamma(50) that represent the risk classification of tumor subvolumes had the largest impact on risk-adaptive optimization. CONCLUSIONS: On the whole, risk-adaptive optimization yields heterogeneous dose distributions that match the risk level distribution of different subvolumes within the tumor volume.     

Comparative analysis of dose volume histogram reduction algorithms for normal tissue complication probability calculations

A model for estimating radiotherapy treatment outcome through the probability of damage to normal tissue and the probability of tumour control is a useful tool for treatment plan optimization, dose escalation strategies and other currently used procedures in radiation oncology. Normal tissue complication estimation (NTCP) is here analysed from the point of view of the reliability and internal consistency of the most popular model. Five different dose volume histogram (DVH) reduction algorithms, applied to the Lyman model for NTCP calculation, were analysed and compared. The study was carried out for sets of parameters corresponding to quite different expected dose-response relationships. In particular, we discussed the dependence of the models on the parameters and on the dose bin size in the DVH. The sensitivity of the different reduction schemes to dose inhomogeneities was analysed, using a set of simple DVHs representing typical situations of radiation therapy routine. Significant differences were substantiated between the various reduction methods regarding the sensitivity to the degree of irradiation homogeneity, to the model parameters and to the dose bin size. Structural aspects of the reduction formalism allowed an explanation for these differences. This work shows that DVH reduction for NTCP calculation has still to be considered as a very delicate field and used with extreme care, especially for clinical applications, at least until the actual formulations are tuned against strong clinical data.     

Calculation of the uncertainty in complication probability for various dose-response models, applied to the parotid gland

PURPOSE: Usually, models that predict normal tissue complication probability (NTCP) are fitted to clinical data with the maximum likelihood (ML) method. This method inevitably causes a loss of information contained in the data. In this study, an alternative method is investigated that calculates the parameter probability distribution (PD), and, thus, conserves all information. The PD method also allows the calculation of the uncertainty in the NTCP, which is an (often-neglected) prerequisite for the intercomparison of both treatment plans and NTCP models. The PD and ML methods are applied to parotid gland data, and the results are compared. METHODS AND MATERIALS: The drop in salivary flow due to radiotherapy was measured in 25 parotid glands of 15 patients. Together with the parotid gland dose-volume histograms (DVH), this enabled the calculation of the parameter PDs for three different NTCP models (Lyman, relative seriality, and critical volume). From these PDs, the NTCP and its uncertainty could be calculated for arbitrary parotid gland DVHs. ML parameters and resulting NTCP values were calculated also. RESULTS: All models fitted equally well. The parameter PDs turned out to have nonnormal shapes and long tails. The NTCP predictions of the ML and PD method usually differed considerably, depending on the NTCP model and the nature of irradiation. NTCP curves and ML parameters suggested a highly parallel organization of the parotid gland. CONCLUSIONS: Considering the substantial differences between the NTCP predictions of the ML and PD method, the use of the PD method is preferred, because this is the only method that takes all information contained in the clinical data into account. Furthermore, PD method gives a true measure of the uncertainty in the NTCP.     

Analysis of radiation pneumonitis risk using a generalized Lyman model

PURPOSE: 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. METHODS AND MATERIALS: 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. RESULTS: 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. CONCLUSIONS: 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.     

Multivariable modeling of radiotherapy outcomes, including dose-volume and clinical factors

PURPOSE: The probability of a specific radiotherapy outcome is typically a complex, unknown function of dosimetric and clinical factors. Current models are usually oversimplified. We describe alternative methods for building multivariable dose-response models. METHODS: Representative data sets of esophagitis and xerostomia are used. We use a logistic regression framework to approximate the treatment-response function. Bootstrap replications are performed to explore variable selection stability. To guard against under/overfitting, we compare several analytical and data-driven methods for model-order estimation. Spearman's coefficient is used to evaluate performance robustness. Novel graphical displays of variable cross correlations and bootstrap selection are demonstrated. RESULTS: Bootstrap variable selection techniques improve model building by reducing sample size effects and unveiling variable cross correlations. Inference by resampling and Bayesian approaches produced generally consistent guidance for model order estimation. The optimal esophagitis model consisted of 5 dosimetric/clinical variables. Although the xerostomia model could be improved by combining clinical and dose-volume factors, the improvement would be small. CONCLUSIONS: Prediction of treatment response can be improved by mixing clinical and dose-volume factors. Graphical tools can mitigate the inherent complexity of multivariable modeling. Bootstrap-based variable selection analysis increases the reliability of reported models. Statistical inference methods combined with Spearman's coefficient provide an efficient approach to estimating optimal model order.     

A Dosimetric and Radiobiological Comparison of Intensity Modulated Radiotherapy,Volumetric Modulated Arc Therapy and Helical Tomotherapy Planning Techniques in Synchronous Bilateral Breast Cancer

Objective: The present investigation intends to identify the optimal radiotherapy treatment plan for synchronous bilateral breast cancer (SBBC) using dosimetric and radiobiological indexes for three techniques, namely, helical tomotherapy (HT), volumetric modulated arc therapy (VMAT), and intensity-modulated radiotherapy (IMRT). Methods: Twenty SBBC treated female patients treatment planning data (average age of 52.5 years) were used as the sample for the present study. Three different plans were created using 50 Gy in a 25 fraction dose regime. Poisson, Niemierko, and LKB models were applied for calculating normal tissue complication probability (NTCP) and tumour control probability (TCP). Result: The target average dose comparison between IMRT with HT and VMAT with HT was highly substantial (P=0.001). The percentage of TCP for IMRT, VMAT, and HT in the Poisson model were 93.70±0.28, 94.68±0.30, and 94.34±0.57, respectively (p<0.05). The dose maximum was lower for the whole lung in the HT plan, with an average dose of 49.31Gy±3.9 (p<0.009). The NTCP values of both Niemierko and LKB models were lower for the heart, lungs, and liver for the IMRT plan. Conclusion: The sparing of organs at risk was higher in the HT plan dosimetrically, and the TCP was higher in the three techniques. The comparison between the three techniques shows that the IMRT and HT techniques could be considered for treating SBBC.     

Comparing different NTCP models that predict the incidence of radiation pneumonitis. Normal tissue complication probability

PURPOSE: To compare different normal tissue complication probability (NTCP) models to predict the incidence of radiation pneumonitis on the basis of the dose distribution in the lung. METHODS AND MATERIALS: The data from 382 breast cancer, malignant lymphoma, and inoperable non-small-cell lung cancer patients from two centers were studied. Radiation pneumonitis was scored using the Southwestern Oncology Group criteria. Dose-volume histograms of the lungs were calculated from the dose distributions that were corrected for dose per fraction effects. The dose-volume histogram of each patient was reduced to a single parameter using different local dose-effect relationships. Examples of single parameters were the mean lung dose (MLD) and the volume of lung receiving more than a threshold dose (V(Dth)). The parameters for the different NTCP models were fit to patient data using a maximum likelihood analysis. RESULTS: The best fit resulted in a linear local dose-effect relationship, with the MLD as the resulting single parameter. The relationship between the MLD and NTCP could be described with a median toxic dose (TD(50)) of 30.8 Gy and a steepness parameter m of 0.37. The best fit for the relationship between the V(Dth) and the NTCP was obtained with a D(th) of 13 Gy. The MLD model was found to be significantly better than the V(Dth) model (p <0.03). However, for 85% of the studied patients, the difference in NTCP calculated with both models was <10%, because of the high correlation between the two parameters. For dose distributions outside the range of the studied dose-volume histograms, the difference in NTCP, using the two models could be >35%. For arbitrary dose distributions, an estimate of the uncertainty in the NTCP could be determined using the probability distribution of the parameter values of the Lyman-Kutcher-Burman model. CONCLUSION: The maximum likelihood method revealed that the underlying local dose-effect relation for radiation pneumonitis was linear (the MLD model), rather than a step function (the V(Dth) model). Thus, for the studied patient population, the MLD was the most accurate predictor for the incidence of radiation pneumonitis.     

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 x 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.     

Physical and Radiobiological Evaluation of Accelerated Intensity Modulated Radiotherapy for Locally Advanced Head and Neck Cancer and Comparison with Short-Term Clinical Outcomes

Objective: The present study aims to evaluate the accelerated intensity modulated radiotherapy (IMRT) of headand neck (HandN) treatments using physical indices and radiobiological models with its clinical correlation usinghistogram analysis in radiation therapy (HART). The radiobiological evaluation in terms of tumor control probability(TCP) and normal tissue complication probability (NTCP) indices were compared with acute toxicity. Materials andMethods: A total of twenty patients with stage III and IV of HandN cases treated with accelerated IMRT using 6MVphotons were chosen for the study. Using HART software, physical indices of the IMRT plans have been defined byuniversal plan indices (UPI’s) which summarize the various recognized plan indices. The overall quality factor (QF)of a plan was determined by a linear combination of all indices in UPI set. The clinical outcomes in terms of the acutetoxicity like dysphagia and xerostomia were compared with NTCP values of the OAR calculated from HART software.Results: The mean QF and the mean Poisson TCP index was found to be 0.993±0.02 and 0.86 ±0.02 respectively. Themean JT Lyman NTCP index for bilateral parotid, constrictors, and larynx were found to be 0.23±0.14, 0.30±0.17 and0.22±0.15 respectively. The acute toxicities in terms of severity of xerostomia and dysphagia have shown a moderatecorrelation with NTCP values of bilateral parotids, constrictors, and larynx, respectively. Conclusion: The meanQF based on UPI was found to be close to unity, which correlates with being a better IMRT plan. The present studysuggested the existence of a moderate correlation between the calculated NTCP values and their respective severitiesof the organ at risk (OAR’s). Accelerated IMRT with chemotherapy is a clinically feasible option in the treatmentof locally advanced head and neck squamous cell carcinoma (HNSCC) with encouraging initial tumor response andacceptable acute toxicities.     

Radiotherapy of prostate cancer with or without intensity modulated beams: a planning comparison

PURPOSE: To evaluate whether intensity modulated radiotherapy (IMRT) by static segmented beams allows the dose to the main portion of the prostate target to escalate while keeping the maximal dose at the anterior rectal wall at 72 Gy. The value of such IMRT plans was analyzed by comparison with non-IMRT plans using the same beam incidences. METHODS AND MATERIALS: We performed a planning study on the CT data of 32 consecutive patients with localized adenocarcinoma of the prostate. Three fields in the transverse plane with gantry angles of 0 degrees, 116 degrees, and 244 degrees were isocentered at the center of gravity of the target volume (prostate and seminal vesicles). The geometry of the beams was determined by beam's eye view autocontouring of the target volume with a margin of 1.5 cm.In study 1, the beam weights were determined by a human planner (3D-man) or by computer optimization using a biological objective function with (3D-optim-lim) or without (3D-optim-unlim) a physical term to limit target dose inhomogeneity.In study 2, the 3 beam incidences mentioned above were used and in-field uniform segments were added to allow IMRT. Plans with (IMRT-lim) or without (IMRT-unlim) constraints on target dose inhomogeneity were compared. In the IMRT-lim plan, target dose inhomogeneity was constrained between 15% and 20%.After optimization, plans in both studies were normalized to a maximal rectal dose of 72 Gy. Biological (tumor control probability [TCP], normal tissue complication probability [NTCP]) and physical indices for tumor control and normal tissue complication probabilities were computed, as well as the probability of the uncomplicated local control (P+).Results: The IMRT-lim plan was superior to all other plans concerning TCP (p < 0.0001). The IMRT-unlim plan had the worst TCP. Within the 3D plans, the 3D-optim-unlim had the best TCP, which was significantly different from the 3D-optim-lim plan (p = 0.0003).For rectal NTCP, both IMRT plans were superior to all other plans (p < 0.0001). The IMRT-unlim plan was significantly better than the IMRT-lim plan (p < 0.0001). Again, 3D-optim-unlim was superior to the other 3D plans (p < 0. 0007).Physical endpoints for target showed the mean minimal target dose to be the lowest in the IMRT-unlim plan, caused by a large target dose inhomogeneity (TDI). Medial target dose, 90th percentile, and maximal target dose were significantly higher in both IMRT plans.Physical endpoints for the rectum showed the IMRT-unlim plan to be superior compared to all other plans. There was a strong correlation between the 65th percentile (Rp65) and rectal NTCP (correlation coefficient > or =89%). For bladder, maximal bladder dose was significantly higher in the IMRT-unlim plan compared to all other plans (p < or = 0.0001).P+ was significantly higher in both IMRT-plans than in all other plans. The 3D-optim-unlim plan was significantly better than the two other 3D plans (p < 0.0001). CONCLUSION: IMRT significantly increases the ratio of TCP over NTCP of the rectum in the treatment of prostate cancer. However, constraints for TDI are needed, because a high degree of TDI reduced minimal target dose. IMRT improved uncomplicated local control probability. In our department, IMRT by static segmented beams is planned and delivered in a cost-effective way. IMRT-lim has replaced non-modulated conformal radiotherapy as the standard treatment for prostate cancer.     

Radiotherapy adapted to spatial and temporal variability in tumor hypoxia

PURPOSE: To explore the feasibility and clinical potential of adapting radiotherapy to temporal and spatial variations in tumor oxygenation. METHODS AND MATERIALS: Repeated dynamic contrast enhanced magnetic resonance (DCEMR) images were taken of a canine sarcoma during the course of fractionated radiation therapy. The tumor contrast enhancement was assumed to represent the oxygen distribution. The IMRT plans were retrospectively adapted to the DCEMR images by employing tumor dose redistribution. Optimized nonuniform tumor dose distributions were calculated and compared with a uniform dose distribution delivering the same integral dose to the tumor. Clinical outcome was estimated from tumor control probability (TCP) and normal tissue complication probability (NTCP) modeling. RESULTS: The biologically adapted treatment was found to give a substantial increase in TCP compared with conventional radiotherapy, even when only pretreatment images were used as basis for the treatment planning. The TCP was further increased by repeated replanning during the course of treatment, and replanning twice a week was found to give near optimal TCP. Random errors in patient positioning were found to give a small decrease in TCP, whereas systematic errors were found to reduce TCP substantially. NTCP for the adapted treatment was similar to or lower than for the conventional treatment, both for parallel and serial normal tissue structures. CONCLUSION: Biologically adapted radiotherapy is estimated to improve treatment outcome of tumors having spatial and temporal variations in radiosensitivity.     

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

PURPOSE: 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). METHODS AND MATERIALS: 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. RESULTS: 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. CONCLUSIONS: The Michigan model was probably not fit to predict RILD in PLC patients. A modified Lyman NTCP model for RILD was recommended.