A Pyakuryal

SU‐E‐T‐301: Evaluation of Simultaneously Integrated Boost (SIB) and Sequential IMRT Boost (SqIB) Treatments of Head and Neck Cancer Using Empirical Radiobiological Modeling

PURPOSEnTo evaluate and compare normal tissue complication probabilities (NTCP) in SIB (simultaneous integrated boost) and SqIB (sequential IMRT boost) IMRT methods in head and neck cancer using the radiobiological modeling of HART program (Histogram Analysis in Radiation Therapy; J Appl Clin Med Phys 11(1): 3013, 2010).nnnMETHODSnOf the 40 SIB IMRT cases identified in a 2-year follow up study, 14 SIB (Rx range: 66-70Gy) cases that developed dysphagia(N=11) or xerostomia(N=10) or both types of complications(N=9) were studied. Similarly 10 SqIB cases (Rx=73.5Gy) was studied previously. The TCP and NTCPs were calculated from the dose-volume histogram (DVH) statistics using the Poisson Statistics (PS) and JT Lyman models respectively. Values for the volume parameter (n), slope parameter (m), tumor control dose (TCD=63.8Gy) and tolerance dose (TD50,5 = 46 and 47 Gy for bilateral parotids and esophagus, respectively) were selected from Luxton et al. (Phys. Med. Biol. 53, 23-36, 2008).nnnRESULTSnIn the SIB method (N=14; Students t-test), TCP of tumor was estimated to be 0.78±0.02; while NTCP for parotids and esophagus were 0.16±0.10, and 0.20±0.06 respectively. The corresponding numbers in the SqIB method (N=10) were 0.83±0.02; 0.45±0.14 and 0.17±0.09 respectively.nnnCONCLUSIONnIn a 2-year follow up study with SIB treatments, the estimated values of NTCP of esophagus correlated with the severity of dysphagia. In addition, the hot spots were also reduced and better parotid sparing was found in SIB method than in SqIB method which may partially be related to smaller prescription doses. However JT Lyman model provided better correlation between severity of xerostomia and NTCP of parotids; and PS models for tumor progression free survivability in SqIB treatments. These findings are not in direct comparison due to the differences in tumors and stages. This novel methodology of radiobiological outcome-related analysis can be utilized to evaluate different treatment plan techniques.

SU‐E‐T‐570: Improvement to the Histogram Analysis in Radiation Therapy (HART): An Open Source Software System for the Multi‐Dimensional Dose‐ Volume Histogram Analysis in Digital Image Communication in Medicine ‐ Radiation Therapy (DICOM‐RT) Treatment Plans

PURPOSEnHistogram Analysis in Radiation Therapy (HART) is an efficient and accurate dose-volume histogram (DVH) computational tool in radiotherapy research. Several applications of the program have been presented previously (J Appl Clin Med Phys 11(1): 3013, 2010; Med Phys 38(6), p.3678, 2011) for the Radiation Therapy Oncology Group (RTOG) users. The program has been further developed to incorporate various types of DVH analysis features to support the research using DICOM-RT plans. The main objective of this work was to present the improvement and compatibility of the program for the DICOM-RT plans.nnnMETHODS AND MATERIALSnMATLAB based codes were primarily designed to read and write a simpler HART format from the standard DICOM-RT data objects exported from the Xio treatment planning system (CMS Inc., St. Louis, MO). This format employed an optimal polynomial fitting technique to interpolate the co-ordinates of the contours in the regions-of-interest. The format was efficient for the (a) precise extraction of the cumulative DVH (cDVH) and spatial DVH (sDVH; x-,y-, and z-DVHs respectively) data- statistics, (b) universal-plan indices evaluation, (c) biological modeling based outcome analyses (BMOA), (d) radiobiological dose-response modeling, and (e) physical parameterization modules. The fundamental DVH statistics were validated using the DVH statistics extracted from the Computational Environment for Radiotherapy Research program.nnnRESULTSnHART offers various types of DVH computational functionalities, several plan evaluation and radiobiological outcome analysis modules in a user- friendly software package for the RTOG and DICOM-RT planners. The cDVH and BMOA modules were found to be the most applicable features for the global researchers.nnnCONCLUSIONSnHART is a novel and universal multi-dimensional DVH analysis tool for the radiation therapy research. We further expect to develop HART for the space-time DVH analysis and proton therapy applications. The software is available online (http://www2.uic.edu/∼apyaku1) for the radiotherapy research. This work was partially supported by NIH-NIDCD grant.

SU‐E‐T‐823: Implication of the Spatial Resolution of the Conventional Dose‐Volume Histogram Analysis in the Radiation Therapy Treatments

Purpose: The detection of the local‐spots of interest is important in evaluation of radiotherapytreatment plans. The conventional dose‐volume histogram (DVH) analysis loses the spatial information of the dose‐distribution such as “hot” and “cold” spots in the evaluation process. However, the cDVH can be resolved into the components of spatial‐DVHs (sDVHs; x‐,y‐ and zDVHs respectively). The objective of this work was to assess the accuracy of IMRT plans using a noble approach of sDVH analysis in the open‐source software system, Histogram Analysis in Radiation Therapy, HART (J Appl Clin Med Phys, Vol.11 (1), p. 3013, 2010). Method and Materials:The contours of the regions‐of‐interest along z‐direction were reformatted to generate contours along x‐, and y‐ planes respectively, using RTOG format of the IMRT plans of 10 head and neck cancer patients (N=10). The dose computed along z‐planes of the CT slices were used to compute dose‐volume matrices along x‐,y‐ and z‐planes respectively, using the user‐friendly HART program. The sDVH data‐points were validated with the cumulative‐DVH (cDVH) statistics of the corresponding organs. The sDVH statistics were utilized to assess the dose‐distribution in organs‐at‐risk such as salivary glands and larynx. Results: HART extracted more than 7000 sDVH statistics in 15–20 minutes for 20–30 organs using the dual‐core processor of 3GB RAM. The hot‐spots estimated from the sDVH analyses, were consistent with the cDVH analyses at higher resolution (1 mm). The low‐density hot‐spots (< 5% per slice) were symmetrically polarized in 3D‐space in 57 ±12% and 93 ±2% of the slices (N=10) of parotid glands and larynx respectively, however high‐density hot‐spots were detected in 90 ±8% of the slices (N=10) of the submandibular glands. Conclusions: The sDVH analysis is an accurate and efficient approach for the in‐depth analysis of the radiotherapy plans and the radio‐biological outcomes of the treatments, using the HART program.

SU‐E‐T‐816: Application of the Histogram Analysis in Radiation Therapy (HART): An Open Source Software System

Purpose: Histogram Analysis in Radiation Therapy (HART) is an efficient dose‐volume histogram (DVH) computational tool in radiation therapy and radiationoncology research. Various applications of the software were also presented and published earlier in different journals (Med Phys 37(6), p.3217, 2010; J Appl Clin Med Phys 11(1), p.3013, 2010). The main objective of this work was to review the important applications of the program. Method and Materials:MATLAB based codes were primarily designed to read and write a simpler HART format of the DVH statistics, from the standard RTOG data formats exported from the Pinnacle3 treatment planning system (TPS; Philips Healthcare, Best, Netherlands). Various applications such as conventional DVH (cDVH) analysis, and spatial DVH (sDVH; x‐,y‐, and z‐DVHs respectively) analysis, universal‐plan indices (UPI) evaluation, biological modeling based outcome analyses (BMOA), radiobiological dose‐response modeling (DRM), and physical parameterization (PP) modules have been incorporated in the program. The fundamental results obtained in these applications, were thoroughly validated using the primary data derived from the DVH statistics extracted from the Pinnacle3 system. The program also comprises the simple computational mechanism, the graphical simulations, and the flexible interactive modules. Results: HART offers cDVH and sDVH computational modules, UPI evaluations, BMOA features, DRM simulations, and PP modules respectively for the radiotherapy plans. The cDVH and BMOA were the most applicable features among the HART users in the past year. Nearly 50% of the users (N=91) have found the program useful around the globe. The program is also available freely online. Conclusions: Several applications have been upgraded into a simpler, user‐friendly, and automated software package, HART. The program is useful to the medical physics and radiationoncology communities. We further expect to develop HART for various applications in radiotherapy research, and its expansion to other TPSs that utilize DICOM‐RT objects.

SU‐GG‐T‐141: Current Status of the Histogram Analysis in Radiation Therapy (HART): An Open‐Source Software System

Purpose: HART is a useful tool in radiation therapy research utilizing 3D conformai radiation therapy (3DCRT) and intensity modulated radiation therapy(IMRT) techniques in the treatment of cancer. Various applications of the software were also presented and published earlier in different journals (Med Phys 36(6), p.2547 (2009); J Appl Clin Med Phys 11 (1), 2010). The main objective of this work was to review the applications of the program, and to present its current status. Method and Materials: Matlab based codes were primarily designed to read RTOG data formats exported from the Pinnacle3treatment planning system (TPS; Philips Healthcare, Best, Netherlands), and to write into a simpler HART format. This format is the basis to execute various applications in the software, such as the conventional and spatialdose‐volume (or surface) histogram (CSDH) analyses, universal plan indices (UPI) evaluation, biological modeling based outcome analyses (BMOA), radiobiological dose response modeling (DRM), and physical parameterization (PP) modules to estimate the differential attenuation coefficients and center of mass of a region of interest. The program executes efficiently due to the simple computational mechanism, graphical simulations, and flexible interactive modes. The CSDH computational module was the most applicable feature for the global users of HART in the past three years. The fundamental results in various applications were validated with the Pinnacle3 data. Results: Currently, HART offers CSDH computational modules, UPI evaluations, BMOA features, DRM simulations, and PP modules respectively for the IMRT and 3DCRT plans. The program is also available online. Conclusion: Several applications have been upgraded into a simpler, user‐friendly, and automated software package (HART). The open‐source mechanism would be useful to the radiation oncology community. We expect to develop HART for various applications in radiotherapy research, and its expansion to other TPSs in the future. This work was partially supported by NIH/NIDCD grant.

SU‐FF‐T‐110: Evaluating Head and Neck IMRT Plans with a Computational Tool for Spatial Dose‐Volume Histograms

Purpose: To evaluate head and neck IMRT plans with spatialdose‐volume histograms (DVHs) that have been calculated with a computational tool for DVH analysis.Method and Materials: A computational tool called HART (Histogram Analysis in Radiation Therapy) was developed for the efficient analysis of treatment plan DVHs. Notable functions include user‐defined DVH endpoints, an outcome analysis toolbox for biological endpoints such as tumor control probability (TCP) and normal tissue complication probability (NTCP) and a user‐friendly graphical interface. A recent addition to the HART package is the ability to calculate spatial DVHs in all three dimensions (xDVH, yDVH and zDVH). In this study, spatial DVHs in all three directions were extracted for ten head and neck IMRT plans and compared to conventional DVHs. Dose‐volume data was examined for all targets and 26 critical structures. Results: The attraction of the conventional DVH has been that it can summarize a 3‐D isodose distribution onto a 2‐D plot. Unfortunately, the cost of this transformation is the loss of spatial information. Spatial DVHs have been shown to provide information on the position of “hot” and “cold” spots in the dose distribution while still maintaining the simplicity of a 2‐D plot. This additional spatial data can then be used for correlation to complications in normal tissues. By automating the extraction and computation of all DVH data, it was shown that HART is a useful tool for the evaluation of IMRTtreatment plans with spatial and conventional DVHs. Conclusion:Spatial DVHs can be used as a complementary tool to conventional DVHs in the evaluation of head and neck IMRT plans. Automating these computations with software such as HART allows for the routine clinical use of spatial DVHs.

SU‐FF‐T‐523: A Comparison of Head and Neck IMRT Plans Optimized with Biologically Based Versus Dose‐Volume Based Objectives in a Commercial Treatment Planning System

Purpose: To compare the quality of IMRT plans optimized with biologically (EUD) based versus dose‐volume based objectives in a commercial treatment planningsystem in the treatment of head and neck cancers.Method and Materials: EUD‐based optimization was utilized in the Philips Pinnacle P3IMRTtreatment planningsystem (licensed for Biological Evaluation) to obtain intensity‐modulated radiation therapy plans for five head and neck cancer patients. These plans were evaluated against IMRT plans optimized with conventional dose‐volume objectives. Each patient had twenty‐six organs‐at‐risk (OAR) contoured within the head and neck region. The plans were compared by examining dose‐volume histograms, dosimetric indices and biological endpoints. Dosimetric indices included mean, minimum and maximum doses, as well as target conformality, dose uniformity and the generalized EUD. Biological endpoints included tumor control probability (TCP), normal tissue complication probability (NTCP) and uncomplicated tumor control probability (P+). Results: Preliminary results show that the EUD‐based optimization in P3IMRT is capable of improving the sparing of OAR while maintaining target coverage. The biologically‐based optimization resulted in greater dose inhomogeneity and less conformality than the dose‐volume based optimization plans. It was also shown that plans optimized with EUD‐based objectives could obtain similar target coverage as the dose‐volume optimized plans but with fewer parameters. Conclusion: The P3IMRT biologically‐based optimization of head and neck IMRT plans resulted in equivalent target coverage while increasing the sparing of normal tissues compared to dose‐volume based optimization. This system can increase the efficiency of obtaining plans of equivalent or better quality by utilizing fewer parameters and has the potential of being incorporated into routine clinical use.

SU-FF-T-553: A DVH Study of Single and Multiple Shot Gammaknife Treatments

Purpose: The objective of this study was to analyze the relationships of dose and volume coverage in the comparison of a single shot (SS) and multiple shot (MS) Gammaknife treatments. The diseases studied were arteriovenous malformation (AVM), meningioma (MN), brainmetastasis (BM), pituitary tumor (PT), vestibular schwannoma (VS), and trigeminal neuralgia (TN) (n=10 for each disease). Method and Materials: The relationships between dose and volume coverage were measured at 90%, 80%, 70%, 60%, 50%, 40%, and 30% of the maximum doses using dose‐volume histograms (DVHs). We set the control volume covered by the prescribed dose (=50% of maximum dose) as unity. Then, volumes covered by different percentages of the maximum dose were divided by the control volume. This method was used for the analysis of four helmet sizes (4, 8, 14, 18 mm) and six diseases. The impact of plug patterns was analyzed for TN. Results: Average volume ratios (AVRs) covered by SS using four helmets were 0.31, 0.47, 0.61, 0.77, 1.36, and 2.06 times the control volume while AVRs covered by MS in the first five diseases were 0.03, 0.14, 0.34, 0.62, 1.47, and 2.23, at 90%, 80%, 70%, 60%, 40%, and 30% of the maximum dose, respectively. The mean doses for six diseases were 18.7, 15.1, 17.2, 15.0, 12.4 Gy to 50%, and 72 Gy to 80%, respectively. AVRs of MS to those of SS were 0.11, 0.30, 0.55, 0.81, 1.08 and 1.08, respectively. Plug patterns did not affect much on the relationship of dose and volume coverage in TN. Conclusions: Greater volumes were covered by the higher percentage isodose lines in SS than in MS. TN had the highest volume ratios covered by doses greater than 50% of the maximum dose; and PT and VS had higher volume ratios than AVM, MN, and BM in this study.

SU‐FF‐T‐118: Improvements to the Histogram Analysis in Radiation Therapy (HART) Open‐Source Software System

Purpose: The histogram analysis in radiation therapy (HART) software has been widely used for the research in intensity modulation radiation therapy(IMRT)treatments in cancer. The common application of HART is the precise and efficient dose volume histogram (DVH) analysis of structures in IMRT plans as presented earlier (Med Phys.35(6), p.2812 (2008)). The tool has been further developed with additional features, such as multi‐dimensional dose histogram (MDH) computational module, dose response modeling (DRM) and plan‐specific outcome analysis (POA) features. Methods and Materials: Matlab based codes were designed to read RTOG data formats exported from the Pinnacle3treatment planning system (TPS; Philips Healthcare, Best, Netherlands), and to write into a simpler HART format. HART computes the MDH differential data utilizing the information on the raw dose values and the co‐ordinates of the primary dose grids for a given structure in the TPS. The DRM utilizes the polynomial models for cumulative DVH in order to simulate the optimal dose response models for structures. The POA feature can also be used for evaluations of IMRT plans using various biological modeling. DVH analysis results extracted by HART, can also be exported into customizable output formats. Results: HART offers MDH computational capability, DRM simulations, a simpler POA feature, and the DVH analysis module for IMRT plans. MDH computations and DRM simulations for an IMRT plan were accomplished relatively in 15–30 minutes with the clock speed of 1.8 GHz and 2 GB RAM support. The MDH and DVH analysis results were validated with the Pinnacle3 data. Conclusions: Several applications have been incorporated into a simpler, user‐friendly, and automated software package (HART). We have also implemented an open‐source mechanism for various users. We expect to develop HART for various applications in radiotherapy research, and its expansion to other TPSs. This work was partially supported by NIH/NIDCD grant.

SU‐GG‐T‐379: Dose Volume Histogram (DVH) Analysis Software for Radiation Therapy Research

Purpose: The purpose of this project was to develop dose‐volume histogram (DVH) analysissoftware that can be used for research with a large quantity of patient data in radiation therapy. Currently, the software converts RTOG output files from the Pinnacle treatment planning system (TPS) (Philips Healthcare, Best, Netherlands) into DVH analyzed data for all structures involved in the IMRT plans. Method and Materials:IMRT patient data to be analyzed were exported into RTOG format files from the TPS. RTOG files, with differential DVH information, were read and transformed into cumulative DVH data. Matlab (The Mathworks Inc, Natick, MA) based codes were developed to identify all the target and normal structure volumes, and treatment planning parameters in RTOG formats. The software utilized the CERR (Washington University at St. Louis) and standard DICOM image manipulation tools. The DVH analysis was based on a cosine interpolationnumerical analysis technique; and the uncertainty in data interpolation was controlled by using piecewise polynomial fittings in DVH curves. The accuracy of DVH analysis was compared with TPS produced DVHs and evaluated with a 4‐mm resolution. Results: The execution time for fully automated DVH analysis of all organs in the IMRT plan was typically 10 minutes per patient data with the clock speed of 1.8 GHz and 1024 MB RAM. The normalized root mean square deviation (NRMSD) was less than 1% for all DVHs except in the high dose gradient slope regions (<2% NRMSD). Conclusion: A DVH analysissoftware system has been developed that can be efficiently used for research requiring the handling of a large number of structures or patient data. More user‐friendly features of dose and volume selections, expansion to other TPSs, and statistical indices are under development. The software will be available to the radiation oncology community in the future.