Fitting tumor control probability models to biopsy outcome after three-dimensional conformal radiation therapy of prostate cancer: pitfalls in deducing radiobiologic parameters for tumors from clinical data.

PURPOSE: The goal of tumor control probability (TCP) models is to predict local control for inhomogeneous dose distributions. All existing fits of TCP models to clinical data have utilized summaries of dose distributions (e.g., prescription dose). Ideally, model fits should be based on dose distributions in the tumor, but usually only dose-volume histograms (DVH) of the planning target volume (PTV) are available. We fit TCP models to biopsy outcome after three-dimensional conformal radiation therapy of prostate cancer using either a dose distribution summary or the full DVH in the PTV. We discuss differences in the radiobiologic parameters and dose-response curves and demonstrate pitfalls in interpreting the results. METHODS AND MATERIAL: Two mechanistic TCP models were fit with a maximum likelihood technique to biopsy outcome from 103 prostate patients treated at Memorial Sloan-Kettering Cancer Center. Fits were performed separately for different patient subgroups defined by tumor-related prognostic factors. Fits were based both on full DVHs, denoted TCP(DVH(calc)), and, alternatively, assuming a homogeneous PTV dose given by the mean dose (Dmean) of each DVH, denoted TCP(Dmean(calc)). Dose distributions for these patients were very homogeneous with any cold spots located on the periphery of the PTV. These cold spots were uncorrelated with biopsy outcome, likely because the low-dose regions may not contain tumor cells. Therefore, fits of TCP models that are potentially sensitive to cold spots (e.g., TCP(DVH(calc))) likely give biologic parameters that diminish this sensitivity. In light of this, we examined differences in fitted clonogenic cell number, N(C), or density, rho(C), surviving fraction after 2 Gy, SF(2), or radiosensitivity, alpha, and their standard deviations in the population, sigma(SF(2)) and sigma(alpha), resulting from fits based on TCP(DVH(calc)) and TCP(Dmean(calc)). Dose-response curves for homogeneous irradiation (characterized by TCD(50), the dose for a TCP of 50%) and differences in TCP predictions calculated from the DVH using alternatively derived parameters were evaluated. RESULTS: Fits of TCP(Dmean(calc)) are better (i.e., have larger likelihood) than fits of TCP(DVH(calc)). For TCP(Dmean(calc)) fits, matching values of SF(2) and sigma(SF(2)) (or alpha and sigma(alpha)) exist for all N(C) (rho(C)) above a threshold that give fits of equal quality, with no maximum in likelihood. In contrast, TCP(DVH(calc)) fits have maximum likelihood for high SF(2) (low alpha) values that minimize effects of cold spots. Consequently, small N(C) (rho(C)) values are obtained to match the observed control rate. For example, for patients in low-, intermediate-, and high-risk groups, optimum values of SF(2) and N(C) are 0.771 and 3.3 x 10(3), 0.736 and 2.2 x 10(4), and 0.776 and 1.0 x 10(4), respectively. The TCD(50) of dose-response curves for intermediate-risk patients is 2.6 Gy lower using TCP(DVH(calc)) parameters (TCD(50) = 67.8 Gy) than for TCP(Dmean(calc)) parameters (TCD(50) = 70.4 Gy). TCP predictions calculated from the DVH using risk group-dependent TCP(Dmean(calc)) parameters are up to 53% lower than corresponding calculations with TCP(DVH(calc)) parameters. CONCLUSION: For our data, TCP parameters derived from DVHs likely do not reflect true radiobiologic parameters in the tumor, but are a consequence of the reduced importance of low-dose regions at the periphery of the PTV. Deriving radiobiologic parameters from TCP(Dmean(calc)) fits is not possible unless one parameter is already known. TCP predictions using TCP(DVH(calc)) and TCP(Dmean(calc)) parameters may differ substantially, requiring consistency in the derivation and application of model parameters. The proper derivation of radiobiologic parameters from clinical data requires both substantial dose inhomogeneities and understanding of how these coincide with tumor location.

Partial irradiation of the brain.

Late radiation injury is the main dose-limiting factor for radiotherapy of tumors of the central nervous system (CNS). Clinical experience as well as analyses of complication data, both for brain necrosis and for changes in neuroimaging after radiosurgery, suggest a pronounced volume effect in the brain. However, the relationships of dose and volume to complications after irradiation of lesions in the brain have yet to be quantitatively assessed. The quantification of volume effects and the modeling of normal tissue response to partial organ irradiation of the brain are particularly demanding because of the highly differentiated and complex structure of the brain and the variety of endpoints after radiotherapy for CNS diseases. This article summarizes the existing clinical data that demonstrate a volume effect in the brain and the current state of knowledge regarding the modeling of complications following partial irradiation of the brain.

Late rectal bleeding after conformal radiotherapy of prostate cancer. II. Volume effects and dose-volume histograms.

PURPOSE AND OBJECTIVE: Late rectal bleeding is a potentially dose limiting complication of three-dimensional conformal radiotherapy (3D-CRT) for prostate cancer. The frequency of late rectal bleeding has been shown to increase as the prescription dose rises above 70 Gy. The purpose of this study is to identify features of the cumulative dose-volume histogram (DVH) for the rectal wall that correlate with late rectal bleeding after 3D-CRT for prostate cancer. METHODS AND MATERIALS: Follow-up information on rectal bleeding is available for 261 and 315 patients treated using 3D-CRT at Memorial Sloan-Kettering Cancer Center for Stage T1c-T3 prostate cancer with minimum target doses of 70.2 and 75.6 Gy, respectively. All patients in this study were treated with a coplanar 6-field technique (2 lateral and 4 oblique fields). Patients were classified as having rectal bleeding if they bled (> or = Grade 2) before 30 months, and nonbleeding (< or = Grade 1) if they were without bleeding at 30 months, using the RTOG morbidity scale. Rectal bleeding was observed in 13 and 38 of the patients treated at 70.2 and 75.6 Gy, respectively. Treatment plans were analyzed for 39 nonbleeding and 13 bleeding patients receiving 70.2 Gy, and 83 nonbleeding and 36 bleeding patients receiving 75.6 Gy. Dose-volume histograms (DVHs) for the anatomic rectal wall were calculated. Average DVHs of the bleeding and nonbleeding patients were generated, and a permutation test was used to assess the significance of differences between them, for each dose group. The confounding effect of total rectal wall volume (V(RW)) was removed by calculating the average differences in DVHs between all combinations of bleeding and nonbleeding patients with similar V(RW)s. Finally, multivariate analysis using logistic regression was performed to test the significance of the DVH variables in the presence of anatomic, geometric, and medical variables previously found to correlate with rectal bleeding in a companion analysis of the same patients. RESULTS: The area under the average percent volume DVH for the rectal wall of patients with bleeding was significantly higher than those of patients without bleeding in both dose groups (p = 0.02, 70.2 Gy; p < 0.0001, 75.6 Gy). However, small V(RW)s were associated with rectal bleeding (p = 0.06, 70.2 Gy; p < 0.01, 75.6 Gy), resulting in an increase in average percent volumes exposed to all doses for patients with rectal bleeding. For patients with similar V(RW)s, rectal bleeding was significantly correlated with the volumes exposed to 46 Gy in both dose groups (p = 0.02, 70.2 Gy; p = 0.005, 75.6 Gy, tolerance in V(RW): 5 ccs). For the 75.6 Gy dose group, the percent volume receiving 77 Gy was significantly correlated with rectal bleeding (p < 0.005). Bivariate analysis using logistic regression, including V(RW) together with a single DVH variable, showed good agreement with the above analysis. Multivariate analysis revealed a borderline significant correlation of the percent volume receiving 71 Gy in the 70.2 Gy dose group. It also showed that the DVH variables were highly correlated with geometric and dosimetric variables previously found to correlate with rectal bleeding in multivariate analysis. CONCLUSION: Significant volume effects were found in the probability of late rectal bleeding for patients undergoing 3D-CRT for prostate cancer with prescription doses of 70.2 and 75.6 Gy. The percent volumes exposed to 71 and 77 Gy in the 70.2 and 75.6 Gy dose groups respectively were significantly correlated with rectal bleeding. The independent correlation of small V(RW) with rectal bleeding may indicate the existence of a functional reserve for the rectum. The independent association with larger percent volumes exposed to intermediate doses ( approximately 46 Gy) seen in both dose groups may indicate that a large surrounding region of intermediate dose may interfere with the ability to repair the effects of a central high dose region.

Analysis of biopsy outcome after three-dimensional conformal radiation therapy of prostate cancer using dose-distribution variables and tumor control probability models.

PURPOSE: To investigate tumor control following three-dimensional conformal radiation therapy (3D-CRT) of prostate cancer and to identify dose-distribution variables that correlate with local control assessed through posttreatment prostate biopsies. METHODS AND MATERIAL: Data from 132 patients, treated at Memorial Sloan-Kettering Cancer Center (MSKCC), who had a prostate biopsy 2.5 years or more after 3D-CRT for T1c-T3 prostate cancer with prescription doses of 64.8-81 Gy were analyzed. Variables derived from the dose distribution in the PTV included: minimum dose (Dmin), maximum dose (Dmax), mean dose (Dmean), dose to n% of the PTV (Dn), where n = 1%,...,99%. The concept of the equivalent uniform dose (EUD) was evaluated for different values of the surviving fraction at 2 Gy (SF(2)). Four tumor control probability (TCP) models (one phenomenologic model using a logistic function and three Poisson cell kill models) were investigated using two sets of input parameters, one for low and one for high T-stage tumors. Application of both sets to all patients was also investigated. In addition, several tumor-related prognostic variables were examined (including T-stage, Gleason score). Univariate and multivariate logistic regression analyses were performed. The ability of the logistic regression models (univariate and multivariate) to predict the biopsy result correctly was tested by performing cross-validation analyses and evaluating the results in terms of receiver operating characteristic (ROC) curves. RESULTS: In univariate analysis, prescription dose (Dprescr), Dmax, Dmean, dose to n% of the PTV with n of 70% or less correlate with outcome (p < 0.01). The area under the ROC curve for Dmean is 0.64. In contrast, Dmin (p = 0.6), D98 (p = 0.2) or D95 (p = 0.1) are not significantly correlated with outcome. The results for EUD depend on the input parameter SF(2): EUD correlates significantly with outcome for SF(2) of 0.4 or more, but not for lower SF(2) values. Using either of the two input parameters sets, all TCP models correlate with outcome (p < 0.05; ROC areas 0.60-0.62). Using T-stage dependent input parameters, the correlation is improved (logistic function: p < 0.01, ROC area 0.67, Poisson models: p < 0.01, ROC areas 0.64-0.66). In comparison, the ROC area is 0.68 for the combination of Dmean and T-stage. After multivariate analysis, a model based on TCP, D20 and Gleason score is the best overall model (ROC area 0.73). However, an alternative model based on Dmean, Gleason score, and T-stage is competitive (ROC area 0.70). CONCLUSION: Biopsy outcome after 3D-CRT of prostate cancer at MSKCC is not correlated with Dmin in the PTV and appears to be insensitive to cold spots in the dose distribution. This observation likely reflects the fact that much of the PTV, especially at the periphery, may not contain viable tumor cells and that the treatment margins were sufficiently large. Therefore, the predictive power of all variables which are sensitive to cold spots, like TCPs with Poisson models and EUD for low SF(2), is limited because the low dose region may not coincide with the tumor location. Instead, for MSKCC prostate cancer patients with their standardized CTV definition, substantial target motion and small dose inhomogeneities, Dmean (or any variable that downplays the effect of cold spots) is a very good predictor of biopsy outcome. While our findings may indicate a general problem in the application of current TCP models to clinical data, these conclusions should not be extrapolated to other disease sites without careful analysis.

Late rectal toxicity after conformal radiotherapy of prostate cancer (I): multivariate analysis and dose-response.

PURPOSE: The purpose of this paper is to use the outcome of a dose escalation protocol for three-dimensional conformal radiation therapy (3D-CRT) of prostate cancer to study the dose-response for late rectal toxicity and to identify anatomic, dosimetric, and clinical factors that correlate with late rectal bleeding in multivariate analysis. METHODS AND MATERIALS: Seven hundred forty-three patients with T1c-T3 prostate cancer were treated with 3D-CRT with prescribed doses of 64.8 to 81.0 Gy. The 5-year actuarial rate of late rectal toxicity was assessed using Kaplan-Meier statistics. A retrospective dosimetric analysis was performed for patients treated to 70.2 Gy (52 patients) or 75.6 Gy (119 patients) who either exhibited late rectal bleeding (RTOG Grade 2/3) within 30 months after treatment (i.e., 70.2 Gy-13 patients, 75. 6 Gy-36 patients) or were nonbleeding for at least 30 months (i.e., 70.2 Gy-39 patients, 75.6 Gy-83 patients). Univariate and multivariate logistic regression was performed to correlate late rectal bleeding with several anatomic, dosimetric, and clinical variables. RESULTS: A dose response for >/= Grade 2 late rectal toxicity was observed. By multivariate analysis, the following factors were significantly correlated with >/= Grade 2 late rectal bleeding for patients prescribed 70.2 Gy: 1) enclosure of the outer rectal contour by the 50% isodose on the isocenter slice (i.e., Iso50) (p < 0.02), and 2) smaller anatomically defined rectal wall volume (p < 0.05). After 75.6 Gy, the following factors were significant: 1) smaller anatomically defined rectal wall volume (p < 0.01), 2) higher rectal D(max) (p < 0.01), 3) enclosure of rectal contour by Iso50 (p < 0.01), 4) patient age (p = 0.02), and 5) history of diabetes mellitus (p = 0.04). In addition to these five factors, acute rectal toxicity was also significantly correlated (p = 0.05) with late rectal bleeding when patients from both dose groups were combined in multivariate analysis. CONCLUSION: A multivariate logistic regression model is presented which describes the probability of developing late rectal bleeding after conformal irradiation of prostate cancer. Late rectal bleeding correlated with factors which may indicate that a greater fractional volume of rectal wall was exposed to high dose, such as smaller rectal wall volume, inclusion of the rectum within the 50% isodose on the isocenter slice, and higher rectal D(max).

Intensity modulation with the "step and shoot" technique using a commercial MLC: a planning study. Multileaf collimator.

PURPOSE/OBJECTIVE: For complex planning situations where organs at risk (OAR) surrounding the target volume place stringent constraints, intensity-modulated treatments with photons provide a promising solution to improve tumor control and/or reduce side effects. One approach for the clinical implementation of intensity-modulated treatments is the use of a multileaf collimator (MLC) in the "step and shoot" mode, in which multiple subfields are superimposed for each beam direction to generate stratified intensity distributions with a discrete number of intensity levels. In this paper, we examine the interrelation between the number of intensity levels per beam for various numbers of beams, the conformity of the resulting dose distribution, and the treatment time on a commercial accelerator (Siemens Mevatron KD2) with built-in MLC. METHODS AND MATERIALS: Two typical, clinically relevant cases of patients with head and neck tumors were selected for this study. Using the inverse planning technique, optimized treatment plans are generated for 3-25 evenly distributed coplanar beams as well as noncoplanar beams. An iterative gradient method is used to optimize a physical treatment objective that is based on the specified target dose and individual dose constraints assigned to each organ at risk (brain stem, eyes, optic nerves) by the radiation oncologist. The intensity distribution of each beam is discretized within the inverse planning program into three to infinitely many intensity levels or strata. These stratified intensity distributions are converted into MLC leaf position sequences, which can be subsequently transferred via computer link to the linac console, and can be delivered without user intervention. The quality of the plan is determined by comparing the values of the objective function, dose-volume histograms (DVHs), and isodose distributions. RESULTS: Highly conformal dose distributions can be achieved with five intensity levels in each of seven beams. The merit of using more intensity levels or more beams is relatively small. Acceptable results are achievable even with three levels only. On average, the number of subfields per beam is about 2-2.5 times the number of intensity levels. The average treatment time per subfield is about 20 s. The total treatment time for the three-level and seven-beam case with a total of 39 subfields is 13 min. CONCLUSION: Optimizing stratified intensity distributions in the inverse planning process allows us to achieve close to optimum results with a surprisingly small number of intensity levels. This finding may help to facilitate and accelerate the delivery of intensity-modulated treatments with the "step and shoot" technique.

Digitally reconstructed radiographs from abdominal CT scans as a new tool for radiotherapy planning.

OBJECTIVE: Abdominal extended field radiotherapy requires exact field shaping. Conventional treatment planning is difficult to adapt to individual anatomy, whereas three-dimensional planning is time-consuming. The authors introduce a method with digitally reconstructed radiographs of spiral CT data to facilitate radiotherapy planning. METHODS: Twenty-two patients underwent imaging with a standardized CT protocol, and digitally reconstructed radiographs were calculated in central beam projection using a maximum intensity projection algorithm (MIP-DRR). For comparison, the expected error from parallel projection was calculated depending on object thickness and field length. RESULTS: The contrast-enhanced protocol used in spiral CT produces a good rendition of all relevant structures. The resulting MIP images have a geometry identical to standard simulation films and to the linear accelerator, whereas standard MIPs with parallel projection show significant distortion compared to the treatment process. CONCLUSIONS: Because of the integration of the geometry of the radiotherapy treatment, the described central beam projection method might be used as a new tool for abdominal radiotherapy planning. The CT protocol offers sufficient contrast enhancement in all relevant structures and provides all necessary anatomic information for individual beam shaping.

Usability of semiautomatic segmentation algorithms for tumor volume determination.

RATIONALE AND OBJECTIVES: Tumor volume is an important parameter for clinical decision making. At present, semiautomatic image segmentation is not a standard for tumor volumetry. The aim of this work was to investigate the usability of semiautomatic algorithms for tumor volume determination. METHODS: Semiautomatic region- and volume-growing, isocontour, snakes, hierarchical, and histogram-based segmentation algorithms were tested for accuracy, contour variability, and time performance. The test were performed on a newly developed organic phantom for the simulation of a human liver and liver metastases. The real tumor volumes were measured by water displacement. These measured volumes were used as the gold standard for determining the accuracy of the algorithms. RESULTS: Variability of the segmented volumes ranging from 3.9 +/- 3.2% (isocontour algorithm) to 11.5 +/- 13.9% (hierarchical segmentation) was observed. The segmentation time per slice varied between 32 (volume-growing) and 72 seconds (snakes) on an IBM/RS6000 workstation. CONCLUSIONS: Only the region-growing and isocontour algorithms have the potential to be used for tumor volumetry. However, further improvements of these algorithms are necessary before they can be placed into clinical use.

Target volume definition in radiation therapy.

Target volume definition in radiation therapy is a broad field of interdisciplinary research. We give a brief history of clinical research in this field and outline some remarkable steps which led to the well-defined target volume concepts. The challenges in target volume definition for high-precision conformal radiation therapy are discussed, and possibilities of improving target volume definition, such as the integration of modern imaging modalities and the use of computer-based systems to support the radiation oncologist are indicated, as well as novel techniques for increasing the accuracy of patient positioning. All these tools should be evaluated with regard to their potential for increasing the therapeutic ratio and, as appropriate, should be implemented in clinical practice. However, target volume definition is a complex process influenced by many factors, currently under investigation. While questions remain in this field, and the impact of the influencing factors is not defined, the process of target volume definition should remain the subject of clinical research.