Differential Dose-volume Histograms Research Articles

Second cancer risk after 3D-CRT, IMRT and VMAT for breast cancer

PurposeSecond cancer risk after breast conserving therapy is becoming more important due to improved long term survival rates. In this study, we estimate the risks for developing a solid second cancer after radiotherapy of breast cancer using the concept of organ equivalent dose (OED). Materials and methodsComputer-tomography scans of 10 representative breast cancer patients were selected for this study. Three-dimensional conformal radiotherapy (3D-CRT), tangential intensity modulated radiotherapy (t-IMRT), multibeam intensity modulated radiotherapy (m-IMRT), and volumetric modulated arc therapy (VMAT) were planned to deliver a total dose of 50Gy in 2Gy fractions. Differential dose volume histograms (dDVHs) were created and the OEDs calculated. Second cancer risks of ipsilateral, contralateral lung and contralateral breast cancer were estimated using linear, linear-exponential and plateau models for second cancer risk. ResultsCompared to 3D-CRT, cumulative excess absolute risks (EAR) for t-IMRT, m-IMRT and VMAT were increased by 2±15%, 131±85%, 123±66% for the linear-exponential risk model, 9±22%, 82±96%, 71±82% for the linear and 3±14%, 123±78%, 113±61% for the plateau model, respectively. ConclusionSecond cancer risk after 3D-CRT or t-IMRT is lower than for m-IMRT or VMAT by about 34% for the linear model and 50% for the linear-exponential and plateau models, respectively.

SU‐E‐T‐616: Dosimetric Comparison of Volumetric Modulated Arc Therapy, Step‐And‐Shoot, and Sliding Window IMRT for Prostate Cancer

Purpose: To evaluate treatment plans generated by Step‐and‐Shoot (SS), Sliding Window (SW) and Volumetric Modulated Arc Therapy (VMAT) in order to assess the differences in dose volume histograms of planning target volume (PTV) and organs at risk (OAR), conformity indices, radiobiological evaluations, normal tissue dose, and plan quality for prostate cancer cases. Methods: Ten prostate cancer patients treated in our center were selected for this retrospective study. Treatment plans were generated with Eclipse version 8.9 using 10 MV photon beams. For VMAT, Varian Rapid Arc with 1 or 2 arcs, and for SS and SW IMRT, 7ndash;9 coplanar fields were used. Each plan had three PTVs with prescription doses of 81, 59.4, and 45 Gy to prostate, to prostate and lymph nodes, and to pelvis, respectively. Doses to PTV, OAR, normal tissues, and the conformal indices (COIN) were compared among three techniques. The equivalent uniform dose (EUD), tumor control probability (TCP), and normal tissue complication probability (NTCP) were calculated and compared. Results: The average mean doses to the PTV prostate were 82.8 Gy and the average differences of mean dose among all techniques were below 0.3 Gy. For bladder and rectum, the percent differences of average mean dose among all techniques were below 2.2%, though high dose rectal volumes were reduced for VMAT. The COIN slightly favoured VMAT. The average TCP varied by less than 0.001%. The average NTCP for the rectum was 3.55%, 3.75% and 3.87% for VMAT, SS and SW, respectively, while the differences in the average NTCP for the bladder was negligible. The full body volumes receiving 20 to 30 Gy were reduced in VMAT treatments. Conclusion: Data indicates similar target coverage and OAR sparing in general. Additional patients will continue to be added to the study. Variation in normal tissue distribution was less than expected.

TU‐E‐141‐08: Dosimetric Impact of Partial Volume Correction On PET‐Based Targeted Radionuclide Therapy Planning

Purpose: Partial volume effects have been shown to introduce a significant error in positron emission tomography (PET) quantitation. In this study, we investigated the impact of PET partial volume correction (PVC) on the dosimetry of PET‐based targeted radionuclide therapy (TRT) planning. Methods: Five tumor‐bearing nude mice were injected with ∼230 μCi of a 124I‐CLR1404, a small‐molecule, phospholipid ether analog featuring selective retention and accumulation in malignant cells. PET/CT data were acquired at 1, 6, 12, 24, 36, 48, 60, 72, 96, 120, 168, and 240 hours post injection and reconstructed with and without PVC using an OSEM3D algorithm. Assuming identical uptake between 124I‐CLR1404 and its therapeutic analog, 131I‐CLR1404, absorbed doses of 131I‐CLR1404 were modeled by applying a piecewise trapezoidal integration to the 124I‐CLR1404 kinetics. Dose volume histograms (DVHs) and normalized differential DVHs (dDVHs) were used to quantify the impact of PVC on PET‐based TRT planning. Results: Partial volume corrected PET images showed higher tumor uptake, increased the recovery of tumor heterogeneity structures, and a generally improved recovery of small normal tissue structures such as the heart ventricles. In tumors, the mean and maximum 124I‐CLR1404 standardized uptake value at peak drug concentration increased by 1.95±0.86% and 34.97±9.36%, respectively. DVHs of planned 131I‐CLR1404 doses showed an increase in maximum tumor dose levels by 15.63±3.53% due to PVC. Tumor dDVHs confirmed a shift towards higher therapeutic doses with an average increase of 13.09±1.21 mGy per mCi of injected 131I‐CLR1404 activity. Conclusion: PVC of PET data more accurately recovered the biodistribution of 124I‐CLR1404 and thus further improved TRT planning and delivery by increasing the quantitative accuracy. PVC will especially benefit the identification of cold spots in the target volume and the dose estimation in dose limiting organs. JJG and JPWare affiliated with Novelos Therapeutics, Inc., which owns the licensing rights to CLR1404 and related compounds.

A novel four-dimensional radiotherapy planning strategy from a tumor-tracking beam's eye view

To investigate the feasibility of four-dimensional radiotherapy (4DRT) planning from a tumor-tracking beam's eye view (ttBEV) with reliable gross tumor volume (GTV) delineation, realistic normal tissue representation, high planning accuracy and low clinical workload, we propose and validate a novel 4D conformal planning strategy based on a synthesized 3.5D computed tomographic (3.5DCT) image with a motion-compensated tumor. To recreate patient anatomy from a ttBEV in the moving tumor coordinate system for 4DRT planning (or 4D planning), the centers of delineated GTVs in all phase CT images of 4DCT were aligned, and then the aligned CTs were averaged to produce a new 3.5DCT image. This GTV-motion-compensated CT contains a motionless target (with motion artifacts minimized) and motion-blurred normal tissues (with a realistic temporal density average). Semi-automatic threshold-based segmentation of the tumor, lung and body was applied, while manual delineation was used for other organs at risk (OARs). To validate this 3.5DCT-based 4D planning strategy, five patients with peripheral lung lesions of small size (<5 cm3) and large motion range (1.2–3.5 cm) were retrospectively studied for stereotactic body radiotherapy (SBRT) using 3D conformal radiotherapy planning tools. The 3.5DCT-based 4D plan (3.5DCT plan) with 9–10 conformal beams was compared with the 4DCT-based 4D plan (4DCT plan). The 4DCT plan was derived from multiple 3D plans based on all phase CT images, each of which used the same conformal beam configuration but with an isocenter shift to aim at the moving tumor and a minor beam aperture and weighting adjustment to maintain plan conformality. The dose–volume histogram (DVH) of the 4DCT plan was created with two methods: one is an integrated DVH (iDVH4D), which is defined as the temporal average of all 3D-phase-plan DVHs, and the other (DVH4D) is based on the dose distribution in a reference phase CT image by dose warping from all phase plans using the displacement vector field (DVF) from a free-form deformable image registration (DIR). The DVH3.5D (for the 3.5DCT plan) was compared with both iDVH4D and DVH4D. To quantify the DVH difference between the 3.5DCT plan and the 4DCT plan, two methods were used: relative difference (%) of the areas underneath the DVH curves and the volumes receiving more than 20% (V20) and 50% (V50) of prescribed dose of these 4D plans. The volume of the delineated GTV from different phase CTs varied dramatically from 24% to 112% among the five patients, whereas the GTV from 3.5DCT deviated from the averaged GTV in 4DCT by only −6%±6%. For planning tumor volume (PTV) coverage, the difference between the DVH3.5D and iDVH4D was negligible (<1% area), whereas the DVH3.5D and DVH4D were quite different, due to DIR uncertainty (∼2 mm), which propagates to PTV dose coverage with a pronounced uncertainty for small tumors (0.3–4.0 cm3) in stereotactic plans with sharp dose falloff around PTV. For OARs, such as the lung, heart, cord and esophagus, the three DVH curves (DVH3.5D, DVH4D and iDVH4D) were found to be almost identical for the same patients, especially in high-dose regions. For the tumor-containing lung, the relative difference of the areas underneath the DVH curves was found to be small (5.3% area on average), of which 65% resulted from the low-dose region (D < 20%). The averaged V20 difference between the two 4D plans was 1.2% ± 0.8%. For the mean lung dose (MLD), the 3.5DCT plan differed from the 4DCT plan by −1.1%±1.3%. GTV-motion-compensated CT (3.5DCT) produces an accurate and reliable GTV delineation, which is close to the mean GTV from 4DCT. The 3.5DCT plan is equivalent to the 4DCT plan with <1% dose difference to the PTV and negligible dose difference in OARs. The 3.5DCT approach simplifies 4D planning and provides accurate dose calculation without a substantial increase of clinical workload for motion-tracking delivery to treat small peripheral lung tumors with large motion.

SU-E-T-621: Comprehensive Study of Head and Neck IMRT Parameters on Planning and Delivery Efficiency, Plan Quality, and Dose Accuracy.

To optimize planning and delivery efficiency, and quality of head and neck IMRT through the evaluation of planning parameters. This study also serves to identify the impact on dose accuracy due to calculation grid size. Eleven head and neck patients, 45 trials per patient (495 trials in total), were evaluated varying IMRT parameters of dose grid, minimum MU per segment, minimum segment area, and control point number. Plans were recomputed on Pinnacle Treatment Planning System (TPS), and scaled to the planning target volume (PTV) constraint of 95% volume. Differential dose volume histograms (DVHs) were exported, and a program was written to compile DVH results. Plans were delivered on an Elekta Synergy linear accelerator to assess delivery time. Plan quality, calculation time, and delivery time served as this study's endpoints. The 4 mm dose grid with 2 mm fluence grid in each direction, saving 1/3 the computation time, were most comparable by DVH results to the 2 mm dose and fluence grid. Dose uncertainty due to dose calculation grid effect was as high as 8.2%, 5.5 Gy for PTVs and 13.3%, 2.1 Gy for organs at risk. Smaller volumes and high gradient regions were more susceptible to uncertainties. Threshold values that maintained adequate plan quality were 5 cm2 for minimum segment area and 5 MU for minimum MU. Minimum MU was more costly in terms of plan quality compared to the minimum segment area. DVH differences can be effectively used to quantify the dose grid calculation uncertainty. For minimum MU and segment area, the DVH differences are an effect of the intensity map, defined by MLC shape and the number of control points. Exceeding the adequate number of control points diminishes returns of plan quality and increases patient treatment time.

SU-E-T-577: Dosimetric Comparison of Volumetric Modulated Arc Therapy (VMAT), Step and Shoot and Sliding Window IMRT for Prostate Cancer.

This study aims to evaluate treatment plans generated by Step- and-Shoot (SS), Sliding Window (SW) and Volumetric Modulated Arc Therapy (VMAT) in order to assess the differences in dose volume histograms of planning target volume (PTV) and organs at risk (OAR), conformity indices, radiobiological evaluations, and plan quality for prostate cancer cases. Six prostate cancer patients treated in our center were selected for this retrospective study. Treatment plans were generated with Eclipse version 8.9 using 10 MV photon beams. For VMAT, Varian Rapid Arc with 1 or 2 arcs, and for SS and SW IMRT, 7-9 fields were used. Each plan had three PTVs with prescription doses of 81, 59.4, and 45 Gy to prostate, to prostate and lymph nodes, and to pelvis, respectively. Doses to PTV and OAR and the conformal indices (COIN) were compared among three techniques. The equivalent uniform dose (EUD), tumor control probability (TCP) and normal tissue complication probability (NTCP) was also calculated and compared. The mean doses to the PTV prostate on average were 83 Gy and the percent differences of mean dose among all techniques were below 0.28. For bladder and rectum, the percent differences of mean dose among all techniques were below 2.2. The COIN did not favour any particular delivery method over the other. The TCP was higher with SS and SW for four patients and higher with VMAT for two patients. The NTCP for the rectum was the lowest with VMAT in all patients except one. Preliminary data shows similar target coverage in general. We will extend our study to include 15 patients to compare different approaches with statistics. We will attempt to define characteristics predictive of the superior delivery technique.

SU‐E‐T‐12: Development of a Software Tool for Investigation of Methods to Compensate for an Interrupted Radiation Treatment

Purpose: When a prescribed course of radiation treatment is interrupted, the remaining treatment sessions must be altered. A number of compensation methods have been suggested in the literature. Some of these methods may not be accepted because of tumor underdosage, increased risk of reactions in organs at risk (OARs) and departmental policies. The goal of this research was to develop a software tool that enables the radiation oncology team to investigate available options and select the best method of compensation on an individual patient basis. Methods: Compensating methods differ in overall treatment time, number of compensating fractions and dose per fraction. For each method, we calculated biological effective dose (BED) and normal tissue complication probability (NTCP) of the OARs using the same tumor BED and tumor control probability (TCP) as the prescribed regimen. The suitable method was then selected as the method with the least increase in OARsˈ BED and NTCP. BED values were calculated using the linear quadratic model formalism. TCP and NTCP values were estimated using Tumorlet and Lyman‐Kutcher‐Burman models, respectively. The gap‐ compensation software developed in this research accepts differential dose volume histograms and gap information as input and uses the provided database to calculate BED, TCP and NTCP values for each compensation method. Results: The results indicate that while the change in BED relative to the intended BED does not depend on the gap position, it is strongly dependent on the type of tumor and OARsˈ tissue types: 13% for head and neck vs. 8.7% for prostate, and about 8.5% to 10% for normal tissues. Conclusions: A software tool was developed to allow for the selection of the best compensation method for interrupted radiation treatments. The method with the lowest change in BED and NTCP in comparison to intended program, is selected to substitute the original plan.

SU‐E‐T‐658: Calculation of the Prostate Equivalent Uniform Dose for Interfraction Organ Motion Using the Gaussian Error Function Model

Purpose: The Gaussian error function (GEF) model was used to fit into the dose‐volume histograms (DVHs) of prostate IMRT and calculate the prostate equivalent uniform dose (EUD) associated with interfraction organ motion. Methods: Three patients with small (39 cc), medium (60 cc) and large (87 cc) prostate volume were selected from a group of twenty in this study. Cumulative DVHs for the prostate that were shifted in the anterior‐posterior directions based on a 7‐beam IMRT plan were calculated and modeled using the Pinnacle3 treatment planning system (TPS) and GEF. To simulate the interfraction prostate motion, the prostate was shifted 1 cm in the anterior and posterior directions in 2 mm steps, using the dose distribution based on the IMRT plan without actual prostate motion. The prostate cumulative DVHs were converted to corresponding differential DVHs to calculate the prostate EUDs in each interfraction motion using MATLAB. Results: Prostate EUD was computed to per fraction in order to measure the equivalent dose at each movement step. Prostate EUDs were found to decrease as the prostate shifted to both the anterior and posterior directions. The prostate EUD was also expected to have the maximum value at the isocentre, since the target received the best dose coverage when the prostate displacement remains zero. Our result showed that patient with the smallest prostate volume (39 cc) in the group has the smallest prostate EUD, when the prostate was shifted 1 cm anteriorly and posteriorly. Since the percentage difference of the prostate EUD calculated by the TPS and GEF is significantly less than 0.5%, we consider the GEF model a good potential alternative to determine the prostate EUD. Conclusions: We validated our GEF model which can predict the prostate EUD with accuracy less than 0.5% compared to the results from the TPS.

Geometric and Dosimetric Approach to Determine Probability of Late Cardiac Mortality in Left Tangential Breast Irradiation: Comparison Between Wedged Beams and Field-in-Field Technique

To evaluate the probability of late cardiac mortality resulting from left breast irradiation planned with tangential fields and to compare this probability between the wedged beam and field-in-field (FIF) techniques and to investigate whether some geometric/dosimetric indicators can be determined to estimate the cardiac mortality probability before treatment begins. For 30 patients, differential dose-volume histograms were calculated for the wedged beam and FIF plans, and the corresponding cardiac mortality probabilities were determined using the relative seriality model. As a comparative index of the dose distribution uniformity, the planning target volume (PTV) percentages involved in 97-103% of prescribed dose were determined for the two techniques. Three geometric parameters were measured for each patient: the maximal length, indicates how much the heart contours were displaced toward the PTV, the angle subtended at the center of the computed tomography slice by the PTV contour, and the thorax width/thickness ratio. Evaluating the differential dose-volume histograms showed that the gain in uniformity between the two techniques was about 1.5. With the FIF technique, the mean dose sparing for the heart, the left anterior descending coronary artery, and the lung was 15% (2.5 Gy vs. 2.2 Gy), 21% (11.3 Gy vs. 9.0 Gy), and 42% (8.0 Gy vs. 4.6 Gy) respectively, compared with the wedged beam technique. Also, the cardiac mortality probability decreased by 40% (from 0.9% to 0.5%). Three geometric parameters, the maximal length, angle subtended at the center of the computed tomography slice by the PTV contour, and thorax width/thickness ratio, were the determining factors (p = .06 for FIF, and p = .10 for wedged beam) for evaluating the cardiac mortality probability. The FIF technique seemed to yield a lower cardiac mortality probability than the conventional wedged beam technique. However, although our study demonstrated that FIF technique improved the dose coverage of the PTV, the restricted number of patients enrolled and the short follow-up did not allow us to evaluate and compare the breast cancer survival rates of the patients.

3D Analysis of Intensity-Modulated Radiation Therapy Quality Assurance Measurement using a 2D Diode Array

Intensity-modulated radiation therapy (IMRT) quality assurance (QA) is often performed using a 2D device and compares measured and computed fluence maps to determine if a field passes or fails certain dose and position criteria. The effects of a measured deviation to the 3D patient spatial dosimetry and dose volume histogram (DVH) are largely unknown because they cannot be analyzed using commercial 2D array IMRT QA systems. We report an in-house treatment planning system (TPS) PLanUNC based 3D IMRT QA analysis approach that has been used in our institution for the past ten years when 2D fluence map IMRT QA failed. In this approach the measured 2D fluence maps are imported back to PLanUNC and used to re-compute 3D patient dosimetry including DVHs. The 2D fluence map IMRT QA criteria is that the measured dose for 95% of the detectors is within 5% of the planned dose, and that the distance-to-agreement be within 4mm (5%/4mm). 22 IMRT plans that had at least one field fail initial QA using MapCHECK 2 are examined using our 3D QA approach. The DVH analysis shows that 19/22 plans that failed initial QA were within 2% of the planned target and critical structure DVHs. 3/22 IMRT plans were found to have DVH difference greater than 2%. The 3D analysis of 2D IMRT QA result shows that when a fluence map QA fails for a single field, often it is clinically insignificant in terms of patient 3D dosimetry

The Impact of BED Correction on Application of the Lyman NTCP Model

The Impact of BED Correction on Application of the Lyman NTCP Model

Technical Note: Calculation of normal tissue complication probability using Gaussian error function model

The Gaussian error function was first used and verified in normal tissue complication probability (NTCP) calculation to reduce the dose-volume histogram (DVH) database by replacing the dose-volume bin set with the error function parameters for the differential DVH (dDVH). Seven-beam intensity modulated radiation therapy (IMRT) treatment planning was performed in three patients with small (40 cm3), medium (53 cm3), and large (87 cm3) prostate volume, selected from a group of 20 patients. Rectal dDVH varying with the interfraction prostate motion along the anterior-posterior direction was determined by the treatment planning system (TPS) and modeled by the Gaussian error function model for the three patients. Rectal NTCP was then calculated based on the routine dose-volume bin set of the rectum by the TPS and the error function model. The variations in the rectal NTCP with the prostate motion and volume were studied. For the ranges of prostate motion of 8-2, 4-8, and 4-3 mm along the anterior-posterior direction for the small, medium, and large prostate patient, the rectal NTCP was determined varying in the ranges of 4.6%-4.8%, 4.5%-4.7%, and 4.6%-4.7%, respectively. The deviation of the rectal NTCP calculated by the TPS and the Gaussian error function model was within +/- 0.1%. The Gaussian error function was successfully applied in the NTCP calculation by replacing the dose-volume bin set with the model parameters. This provides an option in the NTCP calculation using a reduced size of dose-volume database. Moreover, the rectal NTCP was found varying in about +/- 0.2% with the interfraction prostate motion along the anterior-posterior direction in the radiation treatment. The dependence of the variation in the rectal NTCP with the interfraction prostate motion on the prostate volume was found to be more significant in the patient with larger prostate.

Dose to medium versus dose to water as an estimator of dose to sensitive skeletal tissue

The purpose of this study is to determine whether dose to medium, Dm, or dose to water, Dw, provides a better estimate of the dose to the radiosensitive red bone marrow (RBM) and bone surface cells (BSC) in spongiosa, or cancellous bone. This is addressed in the larger context of the ongoing debate over whether Dm or Dw should be specified in Monte Carlo calculated radiotherapy treatment plans. The study uses voxelized, virtual human phantoms, FAX06/MAX06 (female/male), incorporated into an EGSnrc Monte Carlo code to perform Monte Carlo dose calculations during simulated irradiation by a 6 MV photon beam from an Elekta SL25 accelerator. Head and neck, chest and pelvis irradiations are studied. FAX06/MAX06 include precise modelling of spongiosa based on µCT images, allowing dose to RBM and BSC to be resolved from the dose to bone. Modifications to the FAX06/MAX06 user codes are required to score Dw and Dm in spongiosa. Dose uncertainties of ∼1% (BSC, RBM) or ∼0.5% (Dm, Dw) are obtained after up to 5 days of simulations on 88 CPUs. Clinically significant differences (>5%) between Dm and Dw are found only in cranial spongiosa, where the volume fraction of trabecular bone (TBVF) is high (55%). However, for spongiosa locations where there is any significant difference between Dm and Dw, comparisons of differential dose volume histograms (DVHs) and average doses show that Dw provides a better overall estimate of dose to RBM and BSC. For example, in cranial spongiosa the average Dm underestimates the average dose to sensitive tissue by at least 5%, while average Dw is within ∼1% of the average dose to sensitive tissue. Thus, it is better to specify Dw than Dm in Monte Carlo treatment plans, since Dw provides a better estimate of dose to sensitive tissue in bone, the only location where the difference is likely to be clinically significant.

SU-GG-T-580: Parameterization of Dose Volume Histograms (DVHs) of Planning Target Volume (PTV) Among Patients Undergoing Radiation Therapy for Prostate Cancer

Purpose: To propose and validate a method to parameterize Dose Volume Histograms (DVHs) of the Planning Target Volume (PTV) for prostate cancer patients undergoing radiation therapy. Methods and Materials: There are generally two different formats of DVH: differential DVH (dDVH) and cumulative DVH (cDVH). Although cDVHs are more commonly used for radiotherapy treatment plan evaluation, dDVHs were used in our study to test the parameterization, as mathematically, the deferential format preserves more details than the cumulative/integral format. Prostate adenocarcinoma patients previously irradiated at our institution were selected for the study. For these patients, the total dose was 7400 cGy prescribed to cover 95%–98% of the PTV. The treatments were planned using a 7–9 field IMRT technique. It was found that the PTV dDVHs could be characterized by a normal function. Fifteen patients were selected and their PTV DVHs were fitted with a normal function. Parameters regularly used for the treatment plan evaluations, e.g. D95, mean dose and generalized mean dose (GMD), from the original DVHs were compared with those from fitted DVHs. Results: The fittings of the rectal DVHs yielded high goodness of fit with adjusted R-square greater than 0.97. The mode of the peak was 7575.4 ± 57.1 cGy. The standard deviation was 43.3 ± 10.5 cGy. For D95, mean dose and GMD, the relative differences between original and fitted DVHs were within 3%. Conclusions: DVHs could be represented by several parameters. The PTV DVH of patients undergoing irradiation to the prostate gland could successfully be parameterized using a normal function.

SU-GG-T-506: Composition of Daily Tumor Control Probabilities for Fractionated Non Homogeneous External Beam Therapy

Introduction: A number of methods for computing tumorcontrol probabilities from dose response models have been developed. Most authors consider independence among voxels in order to obtain TCP for a planning target volume (PTV) multiplying probabilities for every voxel. This value is then raised to“n”, the number of fractions, in order to obtain TCP for the global, fractionated treatment. The fact is that at the beginning of every fraction the ratio active tumor cells/non active tumor cells is different and thus, probabilities change from fraction to fraction. Methods: A two compartment method has been developed to take this fact into account: the first compartment is the one containing surviving clonogens, and the other one is the rest of the cells in the tumor. The intra fraction tumourcontrol probability is still computed under the assumption of independence of voxels, but the cumulative effect of radiation is modeled in a novel way. Results: The following equation has been derived: TCP(n, v) = ∏ k=1 n [ (n · P(d k )) v(d k ) (v(d k ))! · e −n · P(d k ) ] where v(d) is the number of cells receiving dose“d”, obtained multiplying the differential DVH by the cell density; and P(d) is the dose response function. Conclusions: The use of standard repopulation models to account for interruptions in the course of treatment becomes feasible as well, combining them with the equation above to obtain a personalized estimate of tumorcontrol probability. This method is rigorous, flexible and can be personalized to any course of treatment, including interruptions and non standard schedules. It is also independent of the dose response relationship.

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.

A computational tool for the efficient analysis of dose‐volume histograms for radiation therapy treatment plans

A Histogram Analysis in Radiation Therapy (HART) program was primarily developed to increase the efficiency and accuracy of dose–volume histogram (DVH) analysis of large quantities of patient data in radiation therapy research. The program was written in MATLAB to analyze patient plans exported from the treatment planning system (Pinnacle3) in the American Association of Physicists in Medicine/Radiation Therapy Oncology Group (AAPM/RTOG) format. HART‐computed DVH data was validated against manually extracted data from the planning system for five head and neck cancer patients treated with the intensity‐modulated radiation therapy (IMRT) technique. HART calculated over 4000 parameters from the differential DVH (dDVH) curves for each patient in approximately 10–15 minutes. Manual extraction of this amount of data required 5 to 6 hours. The normalized root mean square deviation (NRMSD) for the HART–extracted DVH outcomes was less than 1%, or within 0.5% distance‐to‐agreement (DTA). This tool is supported with various user‐friendly options and graphical displays. Additional features include optimal polynomial modeling of DVH curves for organs, treatment plan indices (TPI) evaluation, plan‐specific outcome analysis (POA), and spatial DVH (zDVH) and dose surface histogram (DSH) analyses, respectively. HART is freely available to the radiation oncology community.PACS numbers: 87.53.‐j; 87.53.Tf; 87.53.Xd.

SU‐FF‐T‐468: Comparison of Target Dose Inhomogeneity for Four Different Techniques of Breast Cancer Treatment

Purpose: To evaluate target dose inhomogeneity for four different breast cancer treatment techniques. Method and Materials: External beam radiotherapy (EBRT) was performed for 12 patients each using either whole or 3D conformal partial breast irradiation (WBI or PBI), 19 patients with high dose rate (HDR) MammoSite® brachytherapy and 13 patients with Contura® multi‐lumen applicator. The PTV_EVAL volume was defined by following NSABP B‐39/RTOG 0413 for PBI, MammoSite® and Contura® while retrospectively delineated for WBI. The differential dose volume histogram was evaluated using mean dose (Dm) and most probable dose (Dmp) relative to prescribed dose (Dpr) and root mean square deviation (RMSD). The biologically effective dose (BED) accounting for non‐uniform dose distribution was computed. Generalized equivalent uniform dose (gEUD) was calculated together with dose homogeneity index (DHI) and conformal index (COIN). Results: Compared to EBRT, the target received higher dose with HDR (Dm: 143% vs. 101%, Dmp: 111% vs. 101%) which increased BED values (77 Gy vs. 73 Gy for fibrosis, 56 Gy vs.47 Gy for erythema, and 63 Gy vs. 57 Gy for breast carcinoma, respectively) and dose inhomogeneity (RMSD: 12.1 vs. 1.8). Due to steeper dose fall‐off, HDR plans were more conformal than EBRT (COIN: 0.84 vs. 0.45). Compared to MammoSite®, Contura® yielded slightly higher dose (BED difference &lt; 0.5 Gy and 0.3 Gy higher in gEUD) which increased DHI by 5% and COIN by 1%. The PBI had large inter‐patient variability of BED values (2–8 times &gt; others) and the smallest BED and gEUD values. The WBI had large inter‐patient variability of gEUD values (14 times &gt; others) due to cold spots. Conclusion: Despite greater inhomogeneity, HDR plans have higher target dose conformality and are less patient‐specific than EBRT plans. However, based on the biological and dosimetric data, the four different techniques are clinically comparable.

SU‐FF‐T‐495: Risk Estimation of Radiation Induced Second Cancers in Prostate Cancer Patient Treated by Intensity Modulated Radiotherapy (IMRT) and Three Dimensional Conformal Radiotherapy (3D‐CRT)

Purpose: The main purpose of this study was to determine the organ equivalent dose (OED) from primary beam and scatter components reflecting the second cancer risk in prostate cancer patients treated with 10 MV photon by the intensity modulated radiotherapy (IMRT) compared to the three dimensional conformal radiotherapy (3D‐CRT). Method and materials: Both IMRT and 3D‐CRT plans were optimized for each of the 10 patients using Eclipse Radiation Therapy Planning System (RTPS), from which the differential dose volume histograms (dDVHs) for organs of interest were extracted. The three‐dimensional dose distribution data were used for calculation of the primary beam OED. The scatter dose was measured by thermoluminescence dosimeters 700 (TLD‐700 rods) using an Alderson Rando phantom to simulate the treatment condition according to IMRT and 3D‐CRT plans. Results: IMRT plan induced a significant 2‐fold increase in scatter component of OED compared with 3D‐CRT (p = 0.0092) and a 1.13 fold reduction in primary beam component (p = 0.0001). When the primary and scatter components were combined, the total OEDs for IMRT and 3D‐CRT were 0.41 and 0.43 Gy, respectively. No significant difference could be observed (p = 0.1845). On average, risk of the second cancer from IMRT and 3D‐CRT plans was 12.47 risks/10,000 patients/year. Conclusions: IMRT plan does not induce greater second cancer risk than 3D‐CRT. The average OED for both techniques was 0.42 Gy.

SU‐EE‐A2‐01: Spatial Dose‐Volume Histogram (sDVH) — Incorporating Spatial Dose Information Back Into the DVH

Purpose: To incorporate spatial information into dose‐volume histograms (DVH). Methods and materials: For clinical prostate and head/neck cases, initial plans were created using dose‐volume constraints for planning target volume (PTV) and organs at risk in the Eclipse treatment planning system. Dicom RT files were exported to in‐house Matlab‐based software which categorizes target dose voxels by their location within the PTV. For this study, we arbitrarily chose three regions: center, middle, and periphery. Spatial dose‐volume histograms (sDVH) were created by color‐coding the three regions within the differential DVH. Spatially optimized plans were then created using the sDVH concept to preferentially push cold spots from the target center to the periphery. Results: For both prostate and head/neck cases, the DVH and dose distributions are different for the two plans. Using DVH only, the initial plan appears more homogeneous than the spatially optimized plan, however, inspection of the dose distribution reveals that the spatially optimized plan may be clinically favorable since there is less underdosing in the center of the target. The more homogeneous initial plan has a sharper peak in the sDVH. However, it also leaves a significantly larger fraction of the center region underdosed in comparison to the spatially optimized plan (5% vs 0.5% for prostate; 11% vs 3% for head/neck). Conclusion: Treatment plan evaluation based on DVH analysis alone excludes spatial information about the dose distribution. Plans with superior DVHs might be clinically inferior once spatial dose information is considered. The sDVH is a very simple and intuitive way to incorporate spatial dose information back into the DVH format. The sDVH provides more information than DVH alone and may be more consistent with dose distribution analysis for plan ranking purposes, thus making it a useful tool for plan quality evaluation and optimization.Conflict of interest: Supported by Varian Medical Systems.