The impact of different dose–response parameters on biologically optimized IMRT in breast cancer

Dose-response modeling and treatment plan assessment with a python software toolkit

This software assistant aims at calculating the dose-response relations of tumors and normal tissues, or clinically assessing already determined values by other researchers. It can also indicate the optimal dose prescription by optimizing the expected treatment outcome. The software is developed solely in python programming language, and it employs PSFL license for its Graphical User Interface (GUI), NUMPY, MATPLOTLIB, and SCIPY libraries. It comprises of two components. The first is the Dose-response relations derivation component, which takes as input the dose volume histograms (DVHs) of patients and their recorded responses regarding a given clinical endpoint to determine the parameters of different tumor control probability (TCP) or normal tissue complication probability (NTCP) models. The second is the Treatment Plan Assessment component, which uses the DVHs of a plan and the dose-response parameters values of the involved tumors and organs at risk (OARs) to calculate their expected responses. Additionally, the overall probabilities of benefit (PB), injury (PI) and complication-free tumor control (P+) are calculated. The software calculates rapidly the corresponding generalized equivalent uniform doses (gEUD) and biologically effective uniform doses (D‾‾) for the Lyman-Kutcher-Burman (LKB), parallel volume (PV) and relative seriality (RS) models respectively, determining the model parameters. In the Dose-Response Relations Derivation component, the software plots the dose-response curves of the irradiated organ with the relevant confidence internals along with the data of the patients with and without toxicity. It also calculates the odds ratio (OR) and the area under the curve (AUC) of different dose metrics or model parameter values against the individual patient outcomes to determine their discrimination capacity. It also performs a goodness-of-fit evaluation of any model parameter set. The user has the option of viewing plots like Scatter, 3D surfaces, and Bootstrap plots. In the Treatment Plan Assessment part, the software calculates the TCP and NTCP values of the involved tumors and OARs, respectively. Furthermore, it plots the dose-response curves of the TCPs, NTCPs, PB, PI, and P+ for a range of prescription doses for different treatment plans. The presented software is ideal for efficiently conducting studies of radiobiological modeling. Furthermore, it is ideal for performing treatment plan assessment, comparison, and optimization studies.

Biological optimization for mediastinal lymphoma radiotherapy - a preliminary study

Purpose: In current radiotherapy (RT) planning and delivery, population-based dose-volume constraints are used to limit the risk of toxicity from incidental irradiation of organs at risks (OARs). However, weighing tradeoffs between target coverage and doses to OARs (or prioritizing different OARs) in a quantitative way for each patient is challenging. We introduce a novel RT planning approach for patients with mediastinal Hodgkin lymphoma (HL) that aims to maximize overall outcome for each patient by optimizing on tumor control and mortality from late effects simultaneously.Material and Methods: We retrospectively analyzed 34 HL patients treated with conformal RT (3DCRT). We used published data to model recurrence and radiation-induced mortality from coronary heart disease and secondary lung and breast cancers. Patient-specific doses to the heart, lung, breast, and target were incorporated in the models as well as age, sex, and cardiac risk factors (CRFs). A preliminary plan of candidate beams was created for each patient in a commercial treatment planning system. From these candidate beams, outcome-optimized (O-OPT) plans for each patient were created with an in-house optimization code that minimized the individual risk of recurrence and mortality from late effects. O-OPT plans were compared to VMAT plans and clinical 3DCRT plans.Results: O-OPT plans generally had the lowest risk, followed by the clinical 3DCRT plans, then the VMAT plans with the highest risk with median (maximum) total risk values of 4.9 (11.1), 5.1 (17.7), and 7.6 (20.3)%, respectively (no CRFs). Compared to clinical 3DCRT plans, O-OPT planning reduced the total risk by at least 1% for 9/34 cases assuming no CRFs and 11/34 cases assuming presence of CRFs.Conclusions: We developed an individualized, outcome-optimized planning technique for HL. Some of the resulting plans were substantially different from clinical plans. The results varied depending on how risk models were defined or prioritized.

Radiobiological Evaluation of Breast Cancer Radiotherapy Accounting for the Effects of Patient Positioning and Breathing in Dose Delivery. A Meta Analysis

In breast cancer radiotherapy, significant discrepancies in dose delivery can contribute to underdosage of the tumor or overdosage of normal tissue, which is potentially related to a reduction of local tumor control and an increase of side effects. To study the impact of these factors in breast cancer radiotherapy, a meta analysis of the clinical data reported by Mavroidis et al. (2002) in Acta Oncol (41:471–85), showing the patient setup and breathing uncertainties characterizing three different irradiation techniques, were employed. The uncertainties in dose delivery are simulated based on fifteen breast cancer patients (5 mastectomized, 5 resected with negative node involvement (R-) and 5 resected with positive node involvement (R+)), who were treated by three different irradiation techniques, respectively. The positioning and breathing effects were taken into consideration in the determination of the real dose distributions delivered to the CTV and lung in each patient. The combined frequency distributions of the positioning and breathing distributions were obtained by convolution. For each patient the effectiveness of the dose distribution applied is calculated by the Poisson and relative seriality models and a set of parameters that describe the dose-response relations of the target and lung. The three representative radiation techniques are compared based on radiobiological measures by using the complication-free tumor control probability, P+ and the biologically effective uniform dose, D̿ concepts. For the Mastectomy case, the average P+ values of the planned and delivered dose distributions are 93.8% for a D̿CTV of 51.8 Gy and 85.0% for a D̿CTV of 50.3 Gy, respectively. The respective total control probabilities, PB values are 94.8% and 92.5%, whereas the corresponding total complication probabilities, PI values are 0.9% and 7.4%. For the R- case, the average P+ values are 89.4% for a D̿CTV of 48.9 Gy and 88.6% for a D̿CTV of 49.0 Gy, respectively. The respective PB values are 89.8% and 89.9%, whereas the corresponding PI values are 0.4% and 1.2%. For the R+ case, the average P+ values are 86.1% for a D̿CTV of 49.2 Gy and 85.5% for a D̿CTV of 49.1 Gy, respectively. The respective PB values are 90.2% and 90.1%, whereas the corresponding PI values are 4.1% and 4.6%. The combined effects of positioning uncertainties and breathing can introduce a significant deviation between the planned and delivered dose distributions in lung in breast cancer radiotherapy. The positioning and breathing uncertainties do not affect much the dose distribution to the CTV. The simulated delivered dose distributions show larger lung complication probabilities than the treatment plans. This means that in clinical practice the true expected complications are underestimated. Radiation pneumonitis of Grade 1–2 is more frequent and any radiotherapy optimization should use this as a more clinically relevant endpoint.

Evaluation of the effect of prostate volume change on tumor control probability in LDR brachytherapy

Purpose

This study evaluates low dose-rate brachytherapy (LDR) prostate plans to determine the biological effect of dose degradation due to prostate volume changes.

Material and methods

In this study, 39 patients were evaluated. Pre-implant prostate volume was determined using ultrasound. These images were used with the treatment planning system (Nucletron Spot Pro 3.1^®) to create treatment plans using ¹⁰³Pd seeds. Following the implant, patients were imaged using CT for post-implant dosimetry. From the pre and post-implant DVHs, the biologically equivalent dose and the tumor control probability (TCP) were determined using the biologically effective uniform dose. The model used RBE = 1.75 and α/β = 2 Gy.

Results

The prostate volume changed between pre and post implant image sets ranged from –8% to 110%. TCP and the mean dose were reduced up to 21% and 56%, respectively. TCP is observed to decrease as the mean dose decreases to the prostate. The post-implant tumor dose was generally observed to decrease, compared to the planned dose. A critical uniform dose of 130 Gy was established. Below this dose, TCP begins to fall-off. It was also determined that patients with a small prostates were more likely to suffer TCP decrease.

Conclusions

The biological effect of post operative prostate growth due to operative trauma in LDR was evaluated using the concept. The post-implant dose was lower than the planned dose due to an increase of prostate volume post-implant. A critical uniform dose of 130 Gy was determined, below which TCP begun to decline.

Radiobiologically based treatment plan evaluation for prostate seed implants

Purpose

Accurate prostate low dose-rate brachytherapy treatment plan evaluation is important for future care decisions. Presently, an evaluation is based on dosimetric quantifiers for the tumor and organs at risk. However, these do not account for effects of varying dose-rate, tumor repopulation and other biological effects. In this work, incorporation of the biological response is used to obtain more clinically relevant treatment plan evaluation.

Material and methods

Eleven patients were evaluated. Each patient received a 145 Gy implant. Iodine-125 seeds were used and the treatment plans were created on the Prowess system. Based on CT images the post-implant plan was created. In the post-plan, the tumor, urethra, bladder and rectum were contoured. The biologically effective dose was used to determine the tumor control probability and the normal tissue complication probabilities for the urethra, bladder, rectum and surrounding tissue.

Results

The average tumor control probability and complication probabilities for the urethra, bladder, rectum and surrounding tissue were 99%, 29%, 0%, 12% and 6%, respectively. These measures provide a simpler means for evaluation and since they include radiobiological factors, they provide more reliable estimation of the treatment outcome. 

Conclusions

The goal of this work was to create more clinically relevant prostate seed-implant evaluation by incorporating radiobiological measures. This resulted in a simpler descriptor of treatment plan quality and was consistent with patient outcomes.

Toolkit for determination of dose-response relations, validation of radiobiological parameters and treatment plan optimization based on radiobiological measures

Accurately determined dose-response relations of the different tumors and normal tissues should be estimated and used in the clinic. The aim of this study is to demonstrate developed tools that are necessary for determining the dose-response parameters of tumors and normal tissues, for clinically verifying already published parameter sets using local patient materials and for making use of all this information in the optimization and comparison of different treatment plans and radiation techniques. One of the software modules (the Parameter Determination Module) is designed to determine the dose-response parameters of tumors and normal tissues. This is accomplished by performing a maximum likelihood fitting to calculate the best estimates and confidence intervals of the parameters used by different radiobiological models. Another module of this software (the Parameter Validation Module) concerns the validation and compatibility of external or reported dose-response parameters describing tumor control and normal tissue complications. This is accomplished by associating the expected response rates, which are calculated using different models and published parameter sets, with the clinical follow-up records of the local patient population. Finally, the last module of the software (the Radiobiological Plan Evaluation Module) is used for estimating and optimizing the effectiveness a treatment plan in terms of complication-free tumor control, P(+). The use of the Parameter Determination Module is demonstrated by deriving the dose-response relation of proximal esophagus from head and neck cancer radiotherapy. The application of the Parameter Validation Module is illustrated by verifying the clinical compatibility of those dose-response parameters with the examined treatment methodologies. The Radiobiological Plan Evaluation Module is demonstrated by evaluating and optimizing the effectiveness of head and neck cancer treatment plans. The results of the radiobiological evaluation are compared against dosimetric criteria. The presented toolkit appears to be very convenient and efficient for clinical implementation of radiobiological modeling. It can also be used for the development of a clinical data and health information database for assisting the performance of epidemiological studies and the collaboration between different institutions within research and clinical frameworks.

Radiobiological evaluation of the influence of dwell time modulation restriction in HIPO optimized HDR prostate brachytherapy implants

Purpose

One of the issues that a planner is often facing in HDR brachytherapy is the selective existence of high dose volumes around some few dominating dwell positions. If there is no information available about its necessity (e.g. location of a GTV), then it is reasonable to investigate whether this can be avoided. This effect can be eliminated by limiting the free modulation of the dwell times. HIPO, an inverse treatment plan optimization algorithm, offers this option. In treatment plan optimization there are various methods that try to regularize the variation of dose non-uniformity using purely dosimetric measures. However, although these methods can help in finding a good dose distribution they do not provide any information regarding the expected treatment outcome as described by radiobiology based indices.

Material and methods

The quality of 12 clinical HDR brachytherapy implants for prostate utilizing HIPO and modulation restriction (MR) has been compared to alternative plans with HIPO and free modulation (without MR). All common dose-volume indices for the prostate and the organs at risk have been considered together with radiobiological measures. The clinical effectiveness of the different dose distributions was investigated by calculating the response probabilities of the tumors and organs-at-risk (OARs) involved in these prostate cancer cases. The radiobiological models used are the Poisson and the relative seriality models. Furthermore, the complication-free tumor control probability, P₊ and the biologically effective uniform dose (D¯¯) were used for treatment plan evaluation and comparison.

Results

Our results demonstrate that HIPO with a modulation restriction value of 0.1-0.2 delivers high quality plans which are practically equivalent to those achieved with free modulation regarding the clinically used dosimetric indices. In the comparison, many of the dosimetric and radiobiological indices showed significantly different results. The modulation restricted clinical plans demonstrated a lower total dwell time by a mean of 1.4% that was proved to be statistically significant (p = 0.002). The HIPO with MR treatment plans produced a higher P₊ by 0.5%, which stemmed from a better sparing of the OARs by 1.0%.

Conclusions

Both the dosimetric and radiobiological comparison shows that the modulation restricted optimization gives on average similar results with the optimization without modulation restriction in the examined clinical cases. Concluding, based on our results, it appears that the applied dwell time regularization technique is expected to introduce a minor improvement in the effectiveness of the optimized HDR dose distributions.

A graphic user interface toolkit for specification, report and comparison of dose-response relations and treatment plans using the biologically effective uniform dose

A toolkit (BEUDcal) has been developed for evaluating the effectiveness and for predicting the outcome of treatment plans by calculating the biologically effective uniform dose (BEUD) and complication-free tumor control probability. The input for the BEUDcal is the differential dose-volume histograms of organs exported from the treatment planning system. A clinical database is built for the dose-response parameters of different tumors and normal tissues. Dose-response probabilities of all the examined organs are illustrated together with the corresponding BEUDs and the P(+) values. Furthermore, BEUDcal is able to generate a report that simultaneously presents the radiobiological evaluation together with the physical dose indices, showing the complementary relation between the physical and radiobiological treatment plan analysis performed by BEUDcal. Comparisons between treatment plans for helical tomotherapy and multileaf collimator-based intensity modulated radiotherapy of a lung patient were demonstrated to show the versatility of BEUDcal in the assessment and report of dose-response relations.

Assessing four-dimensional radiotherapy planning and respiratory motion-induced dose difference based on biologically effective uniform dose

Four-dimensional (4D) radiotherapy is considered as a feasible and ideal solution to accommodate intra-fractional respiratory motion during conformal radiation therapy. With explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy, 4D treatment planning in principle provides better dose conformity. However, the clinical benefits of developing 4D treatment plans in terms of tumor control rate and normal tissue complication probability as compared to other treatment plans based on CT images of a fixed respiratory phase remains mostly unproven. The aim of our study is to comprehensively evaluate 4D treatment planning for nine lung tumor cases with both physical and biological measures using biologically effective uniform dose (D =) together with complication-free tumor control probability, P+. Based on the examined lung cancer patients and PTV margin applied, we found similar but not identical curves of DVH, and slightly different mean doses in tumor (up to 1.5%) and normal tissue in all cases when comparing 4D, P0%, and P50% plans. When it comes to biological evaluations, we did not observe definitively PTV size dependence in P+ among these nine lung cancer patients with various sizes of PTV. Moreover, it is not necessary that 4D plans would have better target coverage or higher P+ as compared to a fixed phase IMRT plan. However, on the contrary to significant deviations in P+ (up to 14.7%) observed if delivering the IMRT plan made at end-inhalation incorrectly at end-exhalation phase, we estimated the overall P+, PB, and PI for 4D composite plans that have accounted for intra-fractional respiratory motion.

Interpretation of the dosimetric results of three uniformity regularization methods in terms of expected treatment outcome

In IMRT treatment plan optimization there are various methods that try to regularize the variation of dose nonuniformity using purely dosimetric measures. However, although these methods can help in finding a good dose distribution, they do not provide any information regarding the expected treatment outcome. When a treatment plan optimization is performed using biological measures, the final goal should be some indication about the expected tumor control or normal tissue complications, which is the primary goal of treatment planning (the association of treatment configurations and dose prescription with the treatment outcome). In this study, this issue is analyzed distinguishing the dose-oriented treatment plan optimization from the response-oriented optimization. Three different dose distributions were obtained by using a dose-based optimization technique, an EUD-based optimization without applying any technique for regularizing the nonuniformity of the dose distribution, and an EUD-based optimization using a variational regularization technique, which controls dose nonuniformity. The clinical effectiveness of the three dose distributions was investigated by calculating the response probabilities of the tumors and organs-at-risk (OARs) involved in two head and neck and prostate cancer cases. The radiobiological models used are the linear-quadratic-Poisson and the Relative Seriality models. Furthermore, the complication-free tumor control probability and the biologically effective uniform dose (D) were used for treatment plan evaluation and comparison. The radiobiological comparison shows that the EUD-based optimization using L-curve regularization gives better results than the EUD-based optimization without regularization and dose-based optimization in both clinical cases. Concluding, it appears that the applied dose nonuniformity regularization technique is expected to improve the effectiveness of the optimized IMRT dose distributions. However, more patient cases are needed to validate the statistical significance of the results and conclusions presented in this paper.