Impact of bowel space contouring variability on radiation dose and volume assessments in treatment planning for gynaecologic cancers.

INTRODUCTION: Correlations between radiation dose/volume measures and small bowel (SB) toxicity are inconsistent in the medical literature. We assessed the impact of inter-provider variation in bowel bag contouring technique on estimates of radiation dose received by the SB during pelvic radiotherapy. METHODS: Ten radiation oncologists contoured rectum, bladder and bowel bags on treatment planning computed tomography (CT) scans of two patients receiving adjuvant radiation for endometrial cancer. A radiation plan was generated for each patient and used to determine the radiation dose/volume for each organ. Kappa statistics were applied to assess the inter-provider contouring agreement, and Levene test evaluated the homogeneity of variance for radiation dose/volume metrics, including the V45Gy (cm3 ). RESULTS: The bowel bag showed greater variation in radiation dose/volume estimates compared to the bladder and rectum. The V45Gy ranged from 163 to 384 cm3 for data set A and 109 to 409 cm3 for dataset B. Kappa values were 0.82/0.83, 0.92/0.92 and 0.94/0.86 for the bowel bag, rectum, and bladder on data sets A/B, demonstrating lower inter-provider agreement for bowel bag compared with bladder and rectum. CONCLUSION: Inter-provider contouring variability is more significant for the bowel bag than the rectum and bladder, with an associated greater variability in dose and volume estimates during radiation planning.

Correlation between Biological Effective Dose and Radiation-induced Liver Disease from Hypofractionated Radiotherapy.

BACKGROUND: The prevention of radiation-induced liver disease (RILD) is very significant in ensuring a safe radiation treatment and high quality of life. AIMS AND OBJECTIVES: The purpose of this study is to investigate the correlation of physical and biological effective dose (BED) metrics with liver toxicity from hypo-fractionated liver radiotherapy. MATERIALS AND METHODS: 41 hypo-fractionated patients in 2 groups were evaluated for classic radiation-induced liver disease (RILD) and chronic RILD, respectively. Patients were graded for effective toxicity (post-treatment minus pre-treatment) using the Common Terminology Criteria for Adverse Events (CTCAE) v4.0. Physical dose (PD) distributions were converted to BED. The V10Gy, V15Gy, V20Gy, V25Gy and V30Gy physical dose-volume metrics were used in the analysis together with their respective BED-converted metrics of V16.7Gy3, V30Gy3, V46.7Gy3, V66.7Gy3 and V90Gy3. All levels were normalized to their respective patient normal liver volumes (NLV) and evaluated for correlation to RILD. Results were measured quantitatively using R2 regression analysis. RESULTS: The classic RILD group had median follow-up time of 1.9 months and the average PD-NLV normalized V10Gy, V15Gy, V20Gy, V25Gy and V30Gy metrics per grade were plotted against RILD yielding R2 correlations of 0.84, 0.72, 0.73, 0.65 and 0.70, respectively while the BED-volume metrics of V16.7Gy3, V30Gy3, V46.7Gy3, V66.7Gy3 and V90Gy3 resulted in correlation values of 0.84, 0.74, 0.66, 0.78 and 0.74, respectively. BED compared to PD showed a statistically significant (p=.03) increase in R2 for the classic RILD group. Chronic RILD group had median follow-up time of 12.3 months and the average PD-NLV normalized V10Gy, V15Gy, V20Gy, V25Gy and V30Gy metrics per grade were plotted against RILD grade yielding R2 correlations of 0.48, 0.92, 0.88, 0.90 and 0.99 while the BED-volume metrics of V16.7Gy3, V30Gy3, V46.7Gy3, V66.7Gy3 and V90Gy3 resulted in correlation values of 0.43, 0.94, 0.99, 0.21 and 0.00, respectively. CONCLUSION: The strong correlations of the V10Gy and V15Gy PD-volume metrics as well as the V16.7Gy3 (BED of V10Gy) to both classic and chronic RILD imply the appropriateness of the current 15Gy evaluation level for liver toxicity with hypo-fractionated treatments.

Use of 3D biological effective dose (BED) for optimizing multi-target liver cancer treatments.

The purpose is to calculate the composite 3D biological effective dose (BED) distribution in healthy liver, when multiple lesions are treated concurrently with different hypo-fractionated schemes and stereotactic body radiation therapy, and to investigate the potential of biological based plan optimization. Two patients, each having two tumors that were treated sequentially with different treatment plans, were selected. The treatment information of both treatment plans of the patients was used and their dose matrices were exported to an in-house MATLAB software, which was used to calculate the composite BED distribution. The composite BED distributions were used to determine if the healthy liver received BED beyond tolerance. When the dose to the minimum critical volume was less than tolerance, an optimization code was used to derive the scaling factors (ScF) that should be applied to the dose matrix of each plan until the minimum critical volume of healthy liver reaches a BED close to tolerance. It was shown that for each patient, there is a margin for dose escalation regarding the doses to the individual targets. More specifically, the ScFs of the doses range between 5.6 and 99 in the first patient, whereas for the second patient, the ScFs of the optimal doses range between 12.7 and 35.6. The present study indicates that there is a significant margin for dose escalation without increasing the radiation toxicity to the healthy liver. Also, the calculation of the composite BED distribution can provide additional information that may lead to a better assessment of the liver's tolerance to different fractionation schemes and prescribed doses as well as more clinically relevant treatment plan optimization.

Clinical analysis of the approximate, 3-dimensional, biological effective dose equation in multiphase treatment plans.

A multiphase, approximate biological effective dose (BEDA) equation was introduced because most treatment planning systems (TPS) are incapable of calculating the true BED (BEDT). This work investigates the accuracy and precision of the multiphase BEDA relative to the BEDT in clinical cases. Ten patients with head and neck cancer and 10 patients with prostate cancer were studied using their treatment plans from Pinnacle3 9.2 (Philips Medical, Fitchburg, WI). The organs at risk (OARs) that were studied are the normal brain, left and right optic nerves, optic chiasm, spinal cord, brainstem, bladder, and rectum. BEDA and BEDT distributions were calculated using MATLAB 2010b (MathWorks, Natick, MA) and analyzed on a voxel basis for percent error, percent error volume histograms (PEVHs), Pearson correlation coefficient, and Bland-Altman analysis. The maximum BED values that were calculated using the BEDA and BEDT methods were also analyzed. BEDA was found to always underestimate BEDT. The accuracy and precision of BEDA distributions varied between the organs: for optic chiasm and brainstem, 50% of the patients had an overall BEDA percent error of <1%; for left and right optic nerves, rectum, and bladder, 60% to 70% of the patients had an overall BEDA percent error of <1%; and for normal brain and spinal cord, 80% of the patients had an overall BEDA percent error of <1%. BEDA distributions had maximum errors ranging from 2% to 11%, with the 11% error occurring for bladder. BEDA produced much more accurate maximum BED values with adjacent organs such as normal brain, bladder, and rectum. This study has shown that BEDA can calculate BED distributions with acceptable accuracy under certain circumstances. However, its consistency and accuracy strongly depend on the dose distributions of the different treatment phases. One should be cautious when using BEDA.

A graphical user interface (GUI) toolkit for the calculation of three-dimensional (3D) multi-phase biological effective dose (BED) distributions including statistical analyses.

A toolkit has been developed for calculating the 3-dimensional biological effective dose (BED) distributions in multi-phase, external beam radiotherapy treatments such as those applied in liver stereotactic body radiation therapy (SBRT) and in multi-prescription treatments. This toolkit also provides a wide range of statistical results related to dose and BED distributions. MATLAB 2010a, version 7.10 was used to create this GUI toolkit. The input data consist of the dose distribution matrices, organ contour coordinates, and treatment planning parameters from the treatment planning system (TPS). The toolkit has the capability of calculating the multi-phase BED distributions using different formulas (denoted as true and approximate). Following the calculations of the BED distributions, the dose and BED distributions can be viewed in different projections (e.g. coronal, sagittal and transverse). The different elements of this toolkit are presented and the important steps for the execution of its calculations are illustrated. The toolkit is applied on brain, head & neck and prostate cancer patients, who received primary and boost phases in order to demonstrate its capability in calculating BED distributions, as well as measuring the inaccuracy and imprecision of the approximate BED distributions. Finally, the clinical situations in which the use of the present toolkit would have a significant clinical impact are indicated.

Practical aspects and uncertainty analysis of biological effective dose (BED) regarding its three-dimensional calculation in multiphase radiotherapy treatment plans.

PURPOSE: There is a growing interest in the radiation oncology community to use the biological effective dose (BED) rather than the physical dose (PD) in treatment plan evaluation and optimization due to its stronger correlation with radiobiological effects. Radiotherapy patients may receive treatments involving a single only phase or multiple phases (e.g., primary and boost). Since most treatment planning systems cannot calculate the analytical BED distribution in multiphase treatments, an approximate multiphase BED expression, which is based on the total physical dose distribution, has been used. The purpose of this paper is to reveal the mathematical properties of the approximate BED formulation, relative to the true BED. METHODS: The mathematical properties of the approximate multiphase BED equation are analyzed and evaluated. In order to better understand the accuracy of the approximate multiphase BED equation, the true multiphase BED equation was derived and the mathematical differences between the true and approximate multiphase BED equations were determined. The magnitude of its inaccuracies under common clinical circumstances was also studied. All calculations were performed on a voxel-by-voxel basis using the three-dimensional dose matrices. RESULTS: Results showed that the approximate multiphase BED equation is accurate only when the dose-per-fractions (DPFs) in both the first and second phases are equal, which occur when the dose distribution does not significantly change between the phases. In the case of heterogeneous dose distributions, which significantly vary between the phases, there are fewer occurrences of equal DPFs and hence the inaccuracy of the approximate multiphase BED is greater. These characteristics are usually seen in the dose distributions being delivered to organs at risk rather than to targets. CONCLUSIONS: The finding of this study indicates that the true multiphase BED equation should be implemented in the treatment planning systems due to the inconsistent accuracy of the approximate multiphase BED equation in most of the clinical situations.

γ+ index: A new evaluation parameter for quantitative quality assurance.

PURPOSE: The accuracy of dose delivery and the evaluation of differences between calculated and delivered dose distributions, has been studied by several groups. The aim of this investigation is to extend the gamma index by including radiobiological information and to propose a new index that we will here forth refer to as the gamma plus (γ+). Furthermore, to validate the robustness of this new index in performing a quality control analysis of an IMRT treatment plan using pure radiobiological measures such as the biologically effective uniform dose (D) and complication-free tumor control probability (P+). MATERIAL AND METHODS: A new quality assurance index, the (γ+), is proposed based on the theoretical concept of gamma index presented by Low et al. (1998). In this study, the dose difference, including the radiobiological dose information (biological effective dose, BED) is used instead of just the physical dose difference when performing the γ+ calculation. An in-house software was developed to compare different dose distributions based on the γ+ concept. A test pattern for a two-dimensional dose comparison was built using the in-house software platform. The γ+ index was tested using planar dose distributions (exported from the treatment planning system) and delivered (film) dose distributions acquired in a solid water phantom using a test pattern and a theoretical clinical case. Furthermore, a lung cancer case for a patient treated with IMRT was also selected for the analysis. The respective planar dose distributions from the treatment plan and the film were compared based on the γ+ index and were evaluated using the radiobiological measures of P+ and D. RESULTS: The results for the test pattern analysis indicate that the γ+ index distributions differ from those of the gamma index since the former considers radiobiological parameters that may affect treatment outcome. For the theoretical clinical case, it is observed that the γ+ index varies for different treatment parameters (e.g. dose per fraction). The dose area histogram (DAH) from the plan and film dose distributions are associated with P+ values of 50.8% and 49.0%, for a D to the target of 54.0 Gy and 53.3 Gy, respectively. CONCLUSION: The γ+ index shows advantageous properties in the quantitative evaluation of dose delivery and quality control of IMRT treatments because it includes information about the expected responses and radiobiological doses of the individual tissues.

Liver motion during cone beam computed tomography guided stereotactic body radiation therapy.

PURPOSE: Understanding motion characteristics of liver such as, interfractional and intrafractional motion variability, difference in motion within different locations in the organ, and their complex relationship with the breathing cycles are particularly important for image-guided liver SBRT. The purpose of this study was to investigate such motion characteristics based on fiducial markers tracked with the x-ray projections of the CBCT scans, taken immediately prior to the treatments. METHODS: Twenty liver SBRT patients were analyzed. Each patient had three fiducial markers (2 × 5-mm gold) percutaneously implanted around the gross tumor. The prescription ranged from 2 to 8 fractions per patient. The CBCT projections data for each fraction (∼650 projections∕scan), for each patient, were analyzed and the 2D positions of the markers were extracted using an in-house algorithm. In total, >55 000 x-ray projections were analyzed from 85 CBCT scans. From the 2D extracted positions, a 3D motion trajectory of the markers was constructed, from each CBCT scans, resulting in left-right (LR), anterior-posterior (AP), and cranio-caudal (CC) location information of the markers with >55 000 data points. The authors then analyzed the interfraction and intrafraction liver motion variability, within different locations in the organ, and as a function of the breathing cycle. The authors also compared the motion characteristics against the planning 4DCT and the RPM™ (Varian Medical Systems, Palo Alto, CA) breathing traces. Variations in the appropriate gating window (defined as the percent of the maximum range at which 50% of the marker positions are contained), between fractions were calculated as well. RESULTS: The range of motion for the 20 patients were 3.0 ± 2.0 mm, 5.1 ± 3.1 mm, and 17.9 ± 5.1 mm in the planning 4DCT, and 2.8 ± 1.6 mm, 5.3 ± 3.1 mm, and 16.5 ± 5.7 mm in the treatment CBCT, for LR, AP, and CC directions, respectively. The range of respiratory period was 3.9 ± 0.7 and 4.2 ± 0.8 s during the 4DCT simulation and the CBCT scans, respectively. The authors found that breathing-induced AP and CC motions are highly correlated. That is, all markers moved cranially also moved posteriorly and vice versa, irrespective of the location. The LR motion had a more variable relationship with the AP∕CC motions, and appeared random with respect to the location. That is, when the markers moved toward cranial-posterior direction, 58% of the markers moved to the patient-right, 22% of the markers moved to the patient-left, and 20% of the markers had minimal∕none motion. The absolute difference in the motion magnitude between the markers, in different locations within the liver, had a positive correlation with the absolute distance between the markers (R(2) = 0.69, linear-fit). The interfractional gating window varied significantly for some patients, with the largest having 29.4%-56.4% range between fractions. CONCLUSIONS: This study analyzed the liver motion characteristics of 20 patients undergoing SBRT. A large variation in motion was observed, interfractionally and intrafractionally, and that as the distance between the markers increased, the difference in the absolute range of motion also increased. This suggests that marker(s) in closest proximity to the target be used.

GateCT™ surface tracking system for respiratory signal reconstruction in 4DCT imaging.

PURPOSE: To assess the temporal and spatial accuracy of the GateCT™ system (VisionRT, London, UK), a recently released respiratory tracking system for 4DCT, under both ideal and nonideal respiratory conditions. METHODS: Three experiments were performed by benchmarking and comparing its results with the ground-truth input data and those generated by the widely used Varian RPM™ system (Real-time Position Management, Varian, Palo Alto, CA). The first experiment used 10 sinusoidal breathing patterns (constant amplitude and frequency using sin(6)ωt), 10 "consistent" patient breathing patterns, and 10 "sporadic" patient breathing patterns. Motion was simulated with the quasar™ Programmable Respiratory Motion Platform (MODUS, London, Canada) as the surrogate. The GateCT™ and RPM™ systems were used to track the breathing patterns. The data from both systems were then analyzed in the Fourier domain, to evaluate temporal/phase accuracy, using the Pearson's correlation coefficient (PCC). The analysis correlated the ground-truth input data against the GateCT™ and RPM™ tracking results, respectively. The second experiment used 10 ideal sinusoidal breathing patterns, five of period 2.0 s, and five of period 5.0 s, with varying abdominal amplitudes found in clinical cases (peak-to-peak range: 1.67-10 mm) to test the sensitivity of the system to reconstruct various range of motion. And, the third experiment used 12 consecutive clinical patients to track the abdominal motion simultaneously by the GateCT™ and RPM™ systems. The baseline of the tracking results from both the two systems was analyzed via the mean-position-estimate (MPE) calculations. All experiments were tracked for at least 120 s. RESULTS: In the first experiment, the average PCC values (±SD) of all thirty breathing patterns were 0.9995 ± 0.00035 and 0.9994 ± 0.00041 for the GateCT™ and the RPM™ system, respectively. These nearly identical results demonstrated similar temporal/phase tracking accuracy for the two systems. The results in the second experiment, however, revealed a pattern for the GateCT™ system in which the uncertainty of its mean-position tracking increased as the amplitude of the breathing pattern decreased. For example, a non-negligible baseline drift of up to 29.3% with respect to the peak-to-peak amplitude of 1.67-mm was observed. On the contrary, the RPM™ system displayed a more consistent recording of amplitudes over time with the greatest drift being <7.7%. The third experiment confirmed these findings in the clinical setting. Consistent decrease in PCC values due to the increase in artificial amplitude drifts, as the breathing amplitude decreased, was found. The lowest PCC value was 0.7239 for a patient with 1.57-mm peak-to-peak amplitude. CONCLUSIONS: The GateCT™ system revealed its consistency in temporal/phase tracking but had limitations in accurately tracking the absolute abdominal positions, thus suggesting its appropriateness for phase-sorting of 4DCT rather than amplitude-sorting. In contrast, the RPM™ system demonstrated stable respiratory signal tracking in all ranges and accurately both in phase and amplitude, and is a robust system to use for both phase-sorting and amplitude-sorting techniques. The impact of the observed mean-position drift in the GateCT™ system on the resulting 4DCT image quality, in amplitude-sorting, needs further investigation.