Journal of Radiation Oncology Informatics
Not a member yet
    26 research outputs found

    Determination of the source dwell position of an afterloading device with a detector array

    Full text link
    It was the aim to develop and test a measurement technique for the source position of an afterloading system using an electronic two-dimensional detector array (2D array). A "GammaMed plus IX" high dose rate afterloading device (Varian Medical Systems, Palo Alto, USA), and a Seven29 2D detector array (PTW Freiburg GmbH, Freiburg, Germany) have been used. A hollow needle has been connected to the afterloading device. Its outer diameter is 3.0 mm and its length about 220mm. A 14 mm thick Perspex slab was fixed in a reproducible position on the 2D array. Above the 14th detector row, a groove was cut in the slab which accommodates the hollow needle in a fixed position relative to the 2D array. In order to define the position of the source, the signals of the detectors in the 14th detector row have been evaluated. A theoretical curve depending on the source position and strength, has been fitted to the acquired detector signals. It has been shown that the reproducibility of the measurement technique - including the reproducibility of the source placement - was within 0.15mm. This method can not only replace film measurements, it is also more exact and less time consuming

    Pilot Study of a Radiation Oncology Telemedicine Platform

    Full text link
    Purpose: A pilot study was undertaken to develop an integrated telemedicine platform for radiation oncology at Memorial Sloan-Kettering Cancer Center (MSKCC) and its regional sites. The platform consisted of a computer system with simultaneous display of multiple live data portals including 1) video-conferencing between physicians, 2) radiology, and 3) radiation treatment-planning system (RTPS). Methods and Materials: Two MSKCC regional centers were set up with a widescreen monitor, a dedicated computer, and a web camera with microphone. Each computer ran a Microsoft operating system, utilized video-conferencing software, and connected to the MSKCC Ethernet. This allowed for access to the health information system, radiology (web-based picture archiving and communication systems), RTPS, shared network drives and the internet. Results: After 3 months, physicians at two MSKCC sites were successfully able to implement the proposed telemedicine platform. A small sample of cases (prostate, breast, head and neck, and anal cases) were tested. Radiology images, radiation treatment volumes and plans, and portal images were reviewed. Side-by-side comparison of contouring techniques was performed. The platform allowed physicians to remotely review details of cases efficiently. The interactions of the telemedicine platform improved clinical understanding of each case and often resulted in contouring changes. Conclusion: From this experience, we feel that telemedicine could have a significant clinical impact on patient care, especially at centers with satellite clinics. The future goal of the system will be the development of a virtual tumor board for radiation oncologists. We envision the simultaneous display of multiple clinical components, including face photo, pathology, tumor images/videos of procedures, radiology, RTPS, and anatomy/contouring databases, on one screen surface

    RadOnc: An R Package for Analysis of Dose-Volume Histogram and Three-Dimensional Structural Data

    Full text link
    Purpose/Objectives: Dose volume histogram (DVH) data are generally analyzed within the context of a treatment planning system (TPS) on a per-patient basis, with evaluation of single-plan or comparative dose distributions. However, TPS software generally cannot perform simultaneous comparative dosimetry among a cohort of patients. The same limitations apply to parallel analyses of three-dimensional structures and other clinical data. Materials/Methods: We developed a suite of tools ("RadOnc" package) using R statistical software to better compare pooled DVH data and empower analysis of structure data and clinical correlates. Representative patient data were identified among previously analyzed adult (n=13) and pediatric (n=1) cohorts and these data were used to demonstrate the performance and functionality of the RadOnc package. Results: The RadOnc package facilitates DVH data import from the TPS and includes automated methods for DVH visualization, dosimetric parameter extraction, statistical comparison among multiple DVHs, basic three-dimensional structural processing, and visualization tools to enable customizable production of publication-quality images. Conclusions: The RadOnc package provides a potent clinical research tool with the ability to integrate robust statistical software and dosimetric data from cohorts of patients. It is made freely available to the community for their current use and remains under active development

    Dodes (diagnostic nodes) for Guideline Manipulation

    Full text link
    Background: Treatment recommendations (guidelines) are commonly represented in text form. Based on parameters (questions) recommendations are defined (answers). Objectives: To improve handling, alternative forms of representation are required. Methods: The concept of Dodes (diagnostic nodes) has been developed. Dodes contain answers and questions. Dodes are based on linked nodes and additionally contain descriptive information and recommendations. Dodes are organized hierarchically into Dode trees. Dode categories must be defined to prevent redundancy. Results: A centralized and neutral Dode database can provide standardization, which is a requirement for the comparison of recommendations. Centralized administration of Dode categories can provide information about diagnostic criteria (Dode categories) underutilized in existing recommendations (Dode trees). Conclusions: Representing clinical recommendations in Dode trees improves their manageability, handling and updateability

    Regmentation: A New View of Image Segmentation and Registration

    Full text link
    Image segmentation and registration have been the two major areas of research in the medical imaging community for decades and still are. In the context of radiation oncology, segmentation and registration methods are widely used for target structure definition such as prostate or head and neck lymph node areas. In the past two years, 45% of all articles published in the most important medical imaging journals and conferences have presented either segmentation or registration methods. In the literature, both categories are treated rather separately even though they have much in common. Registration techniques are used to solve segmentation tasks (e.g. atlas based methods) and vice versa (e.g. segmentation of structures used in a landmark based registration). This article reviews the literature on image segmentation methods by introducing a novel taxonomy based on the amount of shape knowledge being incorporated in the segmentation process. Based on that, we argue that all global shape prior segmentation methods are identical to image registration methods and that such methods thus cannot be characterized as either image segmentation or registration methods. Therefore we propose a new class of methods that are able solve both segmentation and registration tasks. We call it regmentation. Quantified on a survey of the current state of the art medical imaging literature, it turns out that 25% of the methods are pure registration methods, 46% are pure segmentation methods and 29% are regmentation methods. The new view on image segmentation and registration provides a consistent taxonomy in this context and emphasizes the importance of regmentation in current medical image processing research and radiation oncology image-guided applications

    Developing a tool for crowd-sourcing to Verify a Radiation Oncology Ontology: a Summer Project

    No full text
    We have been unable to find a verified, published Radiation Oncology Ontology. We undertook the process of verifying a Radiation Oncology Ontology with a mixture of crowd-sourcing and expert-based approaches to verify relationships in the ontology. We used a natural language based approach to portray concepts and relationships, surveying users to assess the relationships between concepts in the Radiation Oncology ontology. The work used a description of a patient\u27s history expressed in XML. The natural language statements relating concepts are available on a website for verification, and readers are invited to complete the survey at http://coi-hs-survey.appspot.com/ to contribute

    Fully Automatic Danger Zone Determination for SBRT in NSCLC

    Full text link
    Lung cancer is the major cause of cancer death worldwide. The most common form of lung cancer is non-small cell lung cancer(NSCLC). Stereotactic body radiation therapy (SBRT) has emerged as a good alternative to surgery in patients with peripheralstage I NSCLC, demonstrating favorable tumor control and low toxicity. Due to spatial relationship to several critical organs atrisk, SBRT of centrally located lesions is associated with more severe toxicity and requires modification in dose application andfractionation, which is currently evaluated in clinical trials. Therefore a classification of lung tumors into central or peripheralis required. In this work we present a novel, highly versatile, mulitmodality tool for tumor classification which requires no userinteraction. Furthermore the tool can automatically segment the trachea, proximal bronchial tree, mediastinum, gross target volumeand internal target volume. The proposed work is evaluated on 19 cases with different image modalities assessing segmentationquality as well as classification accuracy. Experiments showed a good segmentation quality and a classification accuracy of 95 %.These results suggest the use of the proposed tool for clinical trials to assist clinicians in their work and to fasten up the workflowin NSCLC patients treatment

    A Radiation Oncology Based Electronic Health Record in an Integrated Radiation Oncology Network

    Full text link
    Purpose: The goal of this ongoing project is to develop and integrate a comprehensive electronic health record (EHR) throughout a multi-facility radiation oncology network to facilitate more efficient workflow and improve overall patient care and safety. Methodology: We required that the EHR provide pre-defined record and verify capability for radiation treatment while still providing a robust clinical health record. In 1996, we began to integrate the Local Area Network Treatment Information System (LANTIS®) across the West Penn Allegheny Radiation Oncology Network (currently including 9 sites). By 2001, we began modifying and expanding the assessment components and creating user-defined templates and have developed a comprehensive electronic health record across our network. Results: In addition to access to the technical record and verify information and imaging obtained for image-guided therapy, we designed and customized 6 modules according to our networks needs to facilitate information acquisition, tracking, and analysis as follows: 1) Demographics/scheduling; 2) Charge codes; 3) Transcription/clinical documents; 4) Clinical/technical assessments; 5) Physician orders 6) Quality assurance pathways. Each module was developed to acquire specific technical/clinical data prospectively in an efficient manner by various staff within the department in a format that facilitates data queries for outcomes/statistical analyses and promotes standardized quality guidelines resulting in a more efficient workflow and improved patient safety and care. Conclusions: Development of a comprehensive EHR across a radiation oncology network is feasible and can be customized to promote clinical/technical standards, facilitate outcomes studies, and improve communication and peer review. The EHR has improved patient care and network integration across a multi-facility radiation oncology system and has markedly reduced the flow and storage of paper across the network

    Automated contrast painting for position verification in radiotherapy

    Full text link
    The influence of information technology in medicine has been constantly rising and represents a central part in many medical disciplines, especially radio-oncology. For the proper delivery of radiation treatment, the correct position of the patient is essential. To verify the correct position of the patient radiological images are made. In order to compare positions, contours of structures (often bones) may be used, these need to be identified and painted. The software that was provided with the linear accelerator contains a bitmap paint program, where these structures are painted manually. This manual painting of structures could be replaced by automated algorithms. However, amendments, innovations or customization of the original software are costly and difficult to achieve due to copyright, license and certification issues. The concept described here aims to get around these issues by creating an automated algorithm on the user level, with no interference of the underlying original software. This system uses the Java platform; with the help of the Java Robot class user input can be simulated. The developed tool proved to be time-saving, functional and the development could easily be accomplished and individually tailored to users needs

    Operations Research Methods for Optimization in Radiation Oncology

    Full text link
    Operations Research has a successful tradition of applying mathematical analysis to a wide range of applications, and problems in Medical Physics have been popular over the last couple of decades. The original application was in the optimal design of the uence map for a radiotherapy treatment, a problem that has continued to receive attention. However, Operations Research has been applied to other clinical problems like patient scheduling, vault design, and image alignment. The overriding theme of this article is to present how techniques in Operations Research apply to clinical problems, which we accomplish in three parts. First, we present the perspective from which an operations researcher addresses a clinical problem. Second, we succinctly introduce the underlying methods that are used to optimize a system, and third, we demonstrate how modern software facilitates problem design. Our discussion is supported by several publications to foster continued study. With numerous clinical, medical, and managerial decisions associated with a clinic, operations research has a promising future at improving how radiotherapy treatments are designed and delivered

    19

    full texts

    26

    metadata records
    Updated in last 30 days.
    Journal of Radiation Oncology Informatics
    Access Repository Dashboard
    Do you manage Journal of Radiation Oncology Informatics? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!