DICOM Interface Research Articles

A Comprehensive Clinical Decision Support Application Software for dose Optimisation Procedure in CT

CT images are the most common imaging modality after conventional X-ray imaging. There are used in order to determine organ position, location and size in relation to treatment area for treatment planning and for diagnoses of diseases. The general aims of the study is to design a comprehensive clinical decision support application software for patients' dose optimization. The design of the GUI involve the use of mathematical modeling procedure where the modeled equations reduces the data from empirical measurements to real clinical application process for implementation. The final component of the modeling process is the GUI applications. This was done in two different process and procedures. The first was the coding process where a software was developed with written C++ code and integrated on the data capturing application platform for clinical application. The second was the visual indicators where the shape and size were modeled to represent the variation in age and gender that exist between the various model equations. The GUI are then used by radiographers to predict and plan the choice of input parameters for effective managements of doses to patient undergoing abdominal CT examination. Finally, a GUI and CAD models were designed to adequately reflect the comfortable working process of all the mathematical model equations. Reference effective abdominal and renal dose parameters have been established and developed in a data base for clinical application. In addition, the displayed interface on the DICOM interface enable the prediction of CTDI and DLP parameters with known kVp and mAs parameters before imaging.

SU‐F‐J‐21: Clinical Evaluation of Surface Scanning Systems in Different Treatment Locations

Purpose:To reduce imaging dose in fractionated IGRT, the ability of optical surface imaging systems (OSIS) to detect setup errors was tested. Therefore, clinical studies to evaluate for different treatment locations setup corrections derived by OSIS in comparison with x‐ray image guidance in fractionated radiation therapy was performed.Methods:The setup correction accuracy of an OSIS system (AlignRT, VisionRT, London, UK) will be analysed for the 4 tumour locations Pelvis, Upper Abdomen, Thorax and Breast, 20 patients for each location in comparison to a different system (Sentinel, C‐RAD, SE). For each patient, the setup corrections of the cone‐beam computed tomography (CBCT) of an Elekta Versa HD linear accelerator (Elekta, Crawley, UK) is considered as gold‐standard and then compared with those of the OSIS for the first ten fractions retrospectively. There were no clinical decisions made based on the surrogate system. For the OSIS, the reference surface is highly important as it represents the actual ground truth. It can be obtained either with the system itself or the surface structure delineated in the planning CT can be imported via DICOM interface. In this paper, the first results for the treatment region thorax are presented. The reference image modalities were compared.Results:Table 1 displays the difference between the setup corrections obtained with OSIS and CBCT in lateral (LAT), longitudinal (LNG) and vertical (VRT) direction for the DICOM reference image. While the median deviations are within a few millimeters, some outliers showed large deviations. Generally, the mean deviation as well as the spread was smallest in lateral and largest in vertical direction.Conclusion:Although the system allows fast, simple and non‐invasive determination of setup corrections, it should be evaluated treatment region dependant. Therefore, the study is ongoing. The application of OSIS may help to reduce the imaging dose for the patient.We gratefully acknowledge the support by our colleagues from the Radiological University Clinic Heidelberg, where the study was performed. This work was funded by the Federal Ministry of Education and Research (BMBF) Germany, grant number 01IB13001B.

A framework for implementation of organ effect models in TOPAS with benchmarks extended to proton therapy

The aim of this work was to develop a framework for modeling organ effects within TOPAS (TOol for PArticle Simulation), a wrapper of the Geant4 Monte Carlo toolkit that facilitates particle therapy simulation. The DICOM interface for TOPAS was extended to permit contour input, used to assign voxels to organs. The following dose response models were implemented: The Lyman–Kutcher–Burman model, the critical element model, the population based critical volume model, the parallel-serial model, a sigmoid-based model of Niemierko for normal tissue complication probability and tumor control probability (TCP), and a Poisson-based model for TCP. The framework allows easy manipulation of the parameters of these models and the implementation of other models.As part of the verification, results for the parallel-serial and Poisson model for x-ray irradiation of a water phantom were compared to data from the AAPM Task Group 166. When using the task group dose-volume histograms (DVHs), results were found to be sensitive to the number of points in the DVH, with differences up to 2.4%, some of which are attributable to differences between the implemented models. New results are given with the point spacing specified. When using Monte Carlo calculations with TOPAS, despite the relatively good match to the published DVH’s, differences up to 9% were found for the parallel-serial model (for a maximum DVH difference of 2%) and up to 0.5% for the Poisson model (for a maximum DVH difference of 0.5%). However, differences of 74.5% (in Rectangle1), 34.8% (in PTV) and 52.1% (in Triangle) for the critical element, critical volume and the sigmoid-based models were found respectively.We propose a new benchmark for verification of organ effect models in proton therapy. The benchmark consists of customized structures in the spread out Bragg peak plateau, normal tissue, tumor, penumbra and in the distal region. The DVH’s, DVH point spacing, and results of the organ effect models are provided. The models were used to calculate dose response for a Head and Neck patient to demonstrate functionality of the new framework and indicate the degree of variability between the models in proton therapy.

SU‐E‐T‐466: Implementation of An Extension Module for Dose Response Models in the TOPAS Monte Carlo Toolkit

Purpose:To develop and verify an extension to TOPAS for calculation of dose response models (TCP/NTCP). TOPAS wraps and extends Geant4.Methods:The TOPAS DICOM interface was extended to include structure contours, for subsequent calculation of DVH's and TCP/NTCP. The following dose response models were implemented: Lyman‐Kutcher‐Burman (LKB), critical element (CE), population based critical volume (CV), parallel‐serials, a sigmoid‐based model of Niemierko for NTCP and TCP, and a Poisson‐based model for TCP. For verification, results for the parallel‐serial and Poisson models, with 6 MV x‐ray dose distributions calculated with TOPAS and Pinnacle v9.2, were compared to data from the benchmark configuration of the AAPM Task Group 166 (TG166). We provide a benchmark configuration suitable for proton therapy along with results for the implementation of the Niemierko, CV and CE models.Results:The maximum difference in DVH calculated with Pinnacle and TOPAS was 2%. Differences between TG166 data and Monte Carlo calculations of up to 4.2%±6.1% were found for the parallel‐serial model and up to 1.0%±0.7% for the Poisson model (including the uncertainty due to lack of knowledge of the point spacing in TG166). For CE, CV and Niemierko models, the discrepancies between the Pinnacle and TOPAS results are 74.5%, 34.8% and 52.1% when using 29.7 cGy point spacing, the differences being highly sensitive to dose spacing. On the other hand, with our proposed benchmark configuration, the largest differences were 12.05%±0.38%, 3.74%±1.6%, 1.57%±4.9% and 1.97%±4.6% for the CE, CV, Niemierko and LKB models, respectively.Conclusion:Several dose response models were successfully implemented with the extension module. Reference data was calculated for future benchmarking. Dose response calculated for the different models varied much more widely for the TG166 benchmark than for the proposed benchmark, which had much lower sensitivity to the choice of DVH dose points.This work was supported by National Cancer Institute Grant R01CA140735

TU‐G‐BRD‐02: Automated Systematic Quality Assurance Program for Radiation Oncology Information System Upgrades

Purpose:To: (1) describe an independent, automated, systematic software‐based protocol for verifying clinical data accuracy/integrity for mitigation of data corruption/loss risks following radiation oncology information system (ROIS) upgrades; and (2) report on application of this approach in an academic/community practice environment.Methods:We propose a robust approach to perform quality assurance on the ROIS after an upgrade, targeting four data sources: (1) ROIS relational database; (2) ROIS DICOM interface; (3) ROIS treatment machine data configuration; and (4) ROIS‐generated clinical reports. We investigated the database schema for differences between pre‐/post‐upgrade states. Paired DICOM data streams for the same object (such as RT‐Plan/Treatment Record) were compared between pre‐/post‐upgrade states for data corruption. We examined machine configuration and related commissioning data files for changes and corruption. ROIS‐generated treatment appointment and treatment parameter reports were compared to ensure patient encounter and treatment plan accuracy. This protocol was supplemented by an end‐to‐end clinical workflow test to verify essential ROI functionality and integrity of components interfaced during patient care chain of activities. We describe the implementation of this protocol during a Varian ARIA system upgrade at our clinic.Results:We verified 1,638 data tables with 2.4 billion data records. For 222 under‐treatment patients, 605 DICOM RT plans and 13,480 DICOM treatment records retrieved from the ROIS DICOM interface were compared, with no differences in fractions, doses delivered, or treatment parameters. We identified 82 new data tables and 78 amended/deleted tables consistent with the upgrade. Reports for 5,073 patient encounters over a 2‐week horizon were compared and were identical to those before the upgrade. Content in 12,237 xml machine files was compared, with no differences identified.Conclusion:An independent QA/validation approach for ROIS upgrades was developed and implemented at our clinic. The success of this approach ensures a robust QA of ROIS upgrades without manual paper/electronic checks and associated intensive labor.

Development of Color Doppler Ultrasound Image-Text Management System

In this paper, the advantages and disadvantages of the existing ultrasonic image management system are analyzed, and also a multi-functional color Doppler ultrasound image-text management system is researched and developed in combination with the experience of color Doppler ultrasound doctors. With this system, the related operations such as color Doppler ultrasound images acquisition, processing, preservation, and medical records are implemented. In the design of the system, a professional acquisition card is used for implementing the acquisition of ordinary video signals. In the meantime, DICOM interface is designed using DICOM3.0 protocol for implementing multi-mode acquisition.

EP-1541: Integration and evaluation of a DICOM interface in a Monte Carlo simulated medical linear accelerator

EP-1541: Integration and evaluation of a DICOM interface in a Monte Carlo simulated medical linear accelerator

WE-G-BRA-04: The Development of a Virtual Reality Dosimetry Training Platform for Physics Training.

Recently there has been a great deal of interest in the application of Simulation methodologies for training. We have previously developed a Virtual Environment for Radiotherapy Training, VERT, which simulates a fully interactive and functional Linac. Patient and plan data can be accessed across a DICOM interface, allowing the treatment process to be simulated. Here we present a newly developed range of Physics equipment, which allows the user to undertake realistic QC processes. Five devices are available: 1) scanning water phantom, 2) 'solid water' QC block/ion chamber, 3) light/ radiation field coincidence phantom, 4) laser alignment phantom and 5) water based calibration phantom with reference class and 'departmental' ion chamber. The devices were created to operate realistically and function as expected, each has an associated control screen which provides control and feedback information. The dosimetric devices respond appropriately to the beam qualities available on the Linac. Geometrical characteristics of the Linac, e.g. isocentre integrity, laser calibration and jaw calibrations can have random errors introduced in order to enable the user learn and observe fault conditions. In the calibration module appropriate factors for temperature and pressure must be set to correct for ambient, simulated, room conditions. The dosimetric devices can be used to characterise the Linac beams. Depth doses with Dmax of 15mm/29mm and d10 of 67%/77% respectively for 10cm square 6/15MV beams were measured. The Quality Indices (TPR20/10 ratios) can be measured as 0.668 and 0.761 respectively. At a simple level the tools can be used to demonstrate beam divergence or the effect of the inverse square law; They are also designed to be used to simulate the calibration of a new ion chamber. We have developed a novel set of tools that allow education of Physics processes via simulation training in our virtual environment. Both Authors are Founders and Directors of Vertual Ltd, a spin-out company that exists to commericalise the results of the research work presented in this abstract.

MO-D-BRB-07: Failure-Mode and Effects Analysis Study for CyberKnife Stereotactic Radiosurgery.

The purpose of this study is to conduct a Failure Modes and Effect Analysis (FMEA) for CyberKnife Stereotactic Radiosurgery to determine the sensitivity of existing QA procedures and determine in which areas new QA procedures needed to be implemented. Members from each professional team providing service for CyberKnife radiosurgery (Medical Physicists, Nurses, Physicians, Radiation Therapists, and Administrators) were interviewed to gather potential failure modes. A patient flow chart was developed from patient consult to conclusion of last treatment. Failure modes were mapped to nodes in the flow charts to identify potential high-risk areas. A matrix was created to correlate existing QA procedures with failure modes to identify failure modes that were not covered by any QA as well as identify the sensitivity of QA procedures to prevent failures. 180 failure modes were identified. Current AAPM QA recommendations were found to focus preferentially on technical failure modes (15%), while the majority of failure modes found are process failures and human errors (85%). Creating a Venn diagram of CyberKnife and Gamma Knife failure modes revealed a large overlap area. The most effective QA checks are checklists for physics second chart review and pre- treatment time-out checklists. Existing checklists were modified and new checklists added to address high-ranked failure modes. New procedure guidelines, e.g. for contouring workflow and add-on simulations, were developed as QC to address clusters of failure modes. An ARIA-CyberKnife DICOM interface is being implemented to resolve failure modes centering around multiple fraction, multiple plan treatments and total dose tracking. This work is the first FMEA study for the CyberKnife stereotactic radiosurgery. It will facilitate medical physicists using the CyberKnife to deliver SRS/SBRT treatments to transition from experience-based technical QA to a comprehensive new quality paradigm including technical, process, and human safety aspects.

Radiotherapy pre-treatment dose validation: A second verification of monitor units (MU) with a commercial software.

Inversely planned intensity-modulated radiotherapy (IMRT) and stereotactic small field radiotherapy should be verified before treatment execution. A second verification is carried out for planned treatments in IMRT and 3D conformal radiotherapy (3D-CRT) using a monitor verification commercial dose calculation management software (DCMS). For the same reference point the ion-chamber measured doses are compared for IMRT plans. DCMS (Diamond) computes dose based on modified Clarkson integration, accounting for multi-leaf collimators (MLC) transmission and measured collimator scatter factors. DCMS was validated with treatment planning system (TPS) (Eclipse 6.5 Version, Varian, USA) separately. Treatment plans computed from TPS are exported to DCMS using DICOM interface. Doses are re-calculated at selected points for fields delivered to IMRT phantom (IBA Scanditronix Wellhofer) in high-energy linac (Clinac 2300 CD, Varian). Doses measured at central axis, for the same points using CC13 (0.13 cc) ion chamber with Dose 1 Electrometer (Scanditronix Wellhofer) are compared with calculated data on DCMS and TPS. The data of 53 IMRT patients with fields ranging from 5 to 9 are reported. The computed dose for selected monitor units (MU) by Diamond showed good agreement with planned doses by TPS. DCMS dose prediction matched well in 3D-CRT forward plans (0.8 ± 1.3%, n = 37) and in IMRT inverse plans (–0.1 ± 2.2%, n = 37). Ion chamber measurements agreed well with Eclipse planned doses (–2.1 ± 2.0%, n = 53) and re-calculated DCMS doses (–1.5 ± 2.6%, n = 37) in phantom. DCMS dose validation is in reasonable agreement with TPS. DCMS calculations corroborate well with ionometric measured doses in most of the treatment plans.

Vega library for processing DICOM data required in Monte Carlo verification of radiotherapy treatment plans

Monte Carlo (MC) methods provide the most accurate to-date dose calculations in heterogeneous media and complex geometries, and this spawns increasing interest in incorporating MC calculations into treatment planning quality assurance process. This involves MC dose calculations for clinically produced treatment plans. To perform these calculations, a number of treatment plan parameters specifying radiation beam and patient geometries need to be transferred to MC codes, such as BEAMnrc and DOSXYZnrc. Extracting these parameters from DICOM files is not a trivial task, one that has previously been performed mostly using Matlab-based software. This paper describes the DICOM tags that contain information required for MC modeling of conformal and IMRT plans, and reports the development of an in-house DICOM interface, through a library (named Vega) of platform-independent, object-oriented C++ codes. The Vega library is small and succinct, offering just the fundamental functions for reading/modifying/writing DICOM files in a C++ program. The library, however, is flexible enough to extract all MC required data from DICOM files, and write MC produced dose distributions into DICOM files that can then be processed in a treatment planning system environment. The library can be made available upon request to the authors.

Einsatz einer elektronischen Patientenakte (EPA) an der Universit�tsaugenklinik Magdeburg

The electronic or paper-based patient record is the most important documentation file. The electronic patient record has many advantages compared to a paper-based record. An example of an electronic patient record (EPR) system accessed by several departments of the Faculty of Medicine of Magdeburg is presented. To guarantee faculty-wide communication with sharing of clinical pictures and findings, e.g., with the Departments of Radiology and Pathology, the system of MEDOS Inc. is used in our department. Several examination devices, for example fundus camera, slit lamp, and ultrasound, are equipped with an digital picture storage and communication system via a DICOM interface to the MEDOS system. The software AnalySIS is used as a gateway for picture transferation. The MEDOS system also supports the clinical workflow. The use of an electronic patient record system in ophthalmology is already possible, but still needs further tuning and improvement.

MCDE: a new Monte Carlo dose engine for IMRT

A new accurate Monte Carlo code for IMRT dose computations, MCDE (Monte Carlo dose engine), is introduced. MCDE is based on BEAMnrc/DOSXYZnrc and consequently the accurate EGSnrc electron transport. DOSXYZnrc is reprogrammed as a component module for BEAMnrc. In this way both codes are interconnected elegantly, while maintaining the BEAM structure and only minimal changes to BEAMnrc.mortran are necessary. The treatment head of the Elekta SLiplus linear accelerator is modelled in detail. CT grids consisting of up to 200 slices of 512 × 512 voxels can be introduced and up to 100 beams can be handled simultaneously. The beams and CT data are imported from the treatment planning system GRATIS via a DICOM interface. To enable the handling of up to 50 × 106 voxels the system was programmed in Fortran95 to enable dynamic memory management. All region-dependent arrays (dose, statistics, transport arrays) were redefined. A scoring grid was introduced and superimposed on the geometry grid, to be able to limit the number of scoring voxels. The whole system uses approximately 200 MB of RAM and runs on a PC cluster consisting of 38 1.0 GHz processors. A set of in-house made scripts handle the parallellization and the centralization of the Monte Carlo calculations on a server. As an illustration of MCDE, a clinical example is discussed and compared with collapsed cone convolution calculations. At present, the system is still rather slow and is intended to be a tool for reliable verification of IMRT treatment planning in the case of the presence of tissue inhomogeneities such as air cavities.

Integrating IT into the radiology environment.

Rather than perpetuating the struggle, "who controls the PACS, Radiology or Information Technology (IT)," Community Hospital of the Monterey Peninsula (CHOMP) took the approach of incorporating IT support within the Radiology Department. CHOMP faced the challenge of staffing Radiology computer systems and networks by using a two-pronged approach; promoting and training clinical staff in IT functions and transferring an experienced IT person into the Radiology Department. Roles and responsibilities are divided. CHOMP's IT Department supports the Radiology Department's desktop devices, PCs, printers, and standard peripherals; while the department's DICOM print and archive network, specialized hardware (e.g., Merge DICOM interface computers), and applications are supported by the Radiology Department. The IT Department provides operating system support for multi-user VMS, Unix, and NT-based systems, e.g. Sun Solaris for the DICOM archive, and Windows NT for Mitra PACS Broker, the HL7/DICOM interface engine. IT also supports network communications, i.e., network electronics (routers, switches, etc.), TCP/IP communications, and network traffic analysis; and OS operations support for major Radiology systems, e.g. back-ups and off-site tape storage. Radiology staff provides applications support and troubleshooting, including analyst functions for RIS; and are the first point of contact with the Radiology systems vendors, e.g., GE Medical, or Siemens. The Radiology Department's senior IT person, the Clinical Technology Coordinator, transferred from CHOMP's IT Department after 7 years in that department. She performs analysis and design associated with Radiology's computer systems, coordinates development of the department's strategic plan, evaluates vendor proposals, and assists the department with product and application selection. Her IT experience and growing knowledge of Radiology's clinical tasks enhances communications between the Radiology and IT departments. Formal meetings between the two departments are held monthly; informal and project-related meetings and discussion are frequent and vital to the continued good relationship between them. When CHOMP either upgrades or replaces its DICOM archive, and Radiology becomes completely filmless, the vendor's contract will include an on-site vendor-supplied picture archiving and communications systems support person for at least 6 months after deployment, to insure a better knowledge transfer. Having an on-site support person would have reduced the number of technical challenges the Radiology Department has faced over the past 2 years. Finding and maintaining qualified staff versed in both IT and Radiology has been and will continue to be difficult. A blend of IT and Radiology support staff and open communication between the departments is working for CHOMP.