Comparison of computer workstation with light box for detecting setup errors from portal images.

PURPOSE: Observer studies were conducted to test the hypothesis that radiation oncologists using a computer workstation for portal image analysis can detect setup errors at least as accurately as when following standard clinical practice of inspecting portal films on a light box. METHODS AND MATERIALS: In a controlled observer study, nine radiation oncologists used a computer workstation, called PortFolio, to detect setup errors in 40 realistic digitally reconstructed portal radiograph (DRPR) images. PortFolio is a prototype workstation for radiation oncologists to display and inspect digital portal images for setup errors. PortFolio includes tools for image enhancement; alignment of crosshairs, field edges, and anatomic structures on reference and acquired images; measurement of distances and angles; and viewing registered images superimposed on one another. The test DRPRs contained known in-plane translation or rotation errors in the placement of the fields over target regions in the pelvis and head. Test images used in the study were also printed on film for observers to view on a light box and interpret using standard clinical practice. The mean accuracy for error detection for each approach was measured and the results were compared using repeated measures analysis of variance (ANOVA) with the Geisser-Greenhouse test statistic. RESULTS: The results indicate that radiation oncologists participating in this study could detect and quantify in-plane rotation and translation errors more accurately with PortFolio compared to standard clinical practice. CONCLUSIONS: Based on the results of this limited study, it is reasonable to conclude that workstations similar to PortFolio can be used efficaciously in clinical practice.

Segmentation, registration, and measurement of shape variation via image object shape.

A model of object shape by nets of medial and boundary primitives is justified as richly capturing multiple aspects of shape and yet requiring representation space and image analysis work proportional to the number of primitives. Metrics are described that compute an object representation's prior probability of local geometry by reflecting variabilities in the net's node and link parameter values, and that compute a likelihood function measuring the degree of match of an image to that object representation. A paradigm for image analysis of deforming such a model to optimize a posteriori probability is described, and this paradigm is shown to be usable as a uniform approach for object definition, object-based registration between images of the same or different imaging modalities, and measurement of shape variation of an abnormal anatomical object, compared with a normal anatomical object. Examples of applications of these methods in radiotherapy, surgery, and psychiatry are given.

Portfolio: a prototype workstation for development and evaluation of tools for analysis and management of digital portal images.

PURPOSE: The purpose of this investigation was to design and implement a prototype physician workstation, called PortFolio, as a platform for developing and evaluating, by means of controlled observer studies, user interfaces and interactive tools for analyzing and managing digital portal images. The first observer study was designed to measure physician acceptance of workstation technology, as an alternative to a view box, for inspection and analysis of portal images for detection of treatment setup errors. METHODS AND MATERIALS: The observer study was conducted in a controlled experimental setting to evaluate physician acceptance of the prototype workstation technology exemplified by PortFolio. PortFolio incorporates a windows user interface, a compact kit of carefully selected image analysis tools, and an object-oriented data base infrastructure. The kit evaluated in the observer study included tools for contrast enhancement, registration, and multimodal image visualization. Acceptance was measured in the context of performing portal image analysis in a structured protocol designed to simulate clinical practice. The acceptability and usage patterns were measured from semistructured questionnaires and logs of user interactions. RESULTS: Radiation oncologists, the subjects for this study, perceived the tools in PortFolio to be acceptable clinical aids. Concerns were expressed regarding user efficiency, particularly with respect to the image registration tools. CONCLUSIONS: The results of our observer study indicate that workstation technology is acceptable to radiation oncologists as an alternative to a view box for clinical detection of setup errors from digital portal images. Improvements in implementation, including more tools and a greater degree of automation in the image analysis tasks, are needed to make PortFolio more clinically practical.

Acceptability and usage patterns of an image analysis workstation.

Critical to the successful deployment and use of new computer systems is the acceptance of the system by the users, i.e., the clinicians. We describe a study which evaluated, in an experimental setting, the potential acceptability of an image analysis workstation for radiation therapy. The acceptability and usage patterns were measured using semi-structured questionnaires and maintaining logs of user interactions. The results of the study showed that the radiation oncologists, who were the subjects for the study, perceived the workstation as acceptable. The results also suggested several areas for improvement of workstation that could increase its acceptance in the clinical setting.

Benchmark test cases for evaluation of computer-based methods for detection of setup errors: realistic digitally reconstructed electronic portal images with known setup errors.

PURPOSE: The purpose of this investigation was to develop methods and software for computing realistic digitally reconstructed electronic portal images with known setup errors for use as benchmark test cases for evaluation and intercomparison of computer-based methods for image matching and detecting setup errors in electronic portal images. METHODS AND MATERIALS: An existing software tool for computing digitally reconstructed radiographs was modified to compute simulated megavoltage images. An interface was added to allow the user to specify which setup parameter(s) will contain computer-induced random and systematic errors in a reference beam created during virtual simulation. Other software features include options for adding random and structured noise, Gaussian blurring to simulate geometric unsharpness, histogram matching with a "typical" electronic portal image, specifying individual preferences for the appearance of the "gold standard" image, and specifying the number of images generated. The visible male computed tomography data set from the National Library of Medicine was used as the planning image. RESULTS: Digitally reconstructed electronic portal images with known setup errors have been generated and used to evaluate our methods for automatic image matching and error detection. Any number of different sets of test cases can be generated to investigate setup errors involving selected setup parameters and anatomic volumes. This approach has proved to be invaluable for determination of error detection sensitivity under ideal (rigid body) conditions and for guiding further development of image matching and error detection methods. Example images have been successfully exported for similar use at other sites. CONCLUSIONS: Because absolute truth is known, digitally reconstructed electronic portal images with known setup errors are well suited for evaluation of computer-aided image matching and error detection methods. High-quality planning images, such as the visible human CT scans from the National Library of Medicine, are essential for producing realistic images. Sets of test cases with systematic and random errors in selected setup parameters and anatomic volumes are suitable for use as standard benchmarks by the radiotherapy community. In addition to serving as an aid to research and development, benchmark images may also be useful for evaluation of commercial systems and as part of a quality assurance program for clinical systems. Test cases and software are available upon request.

Core-based portal image registration for automatic radiotherapy treatment verification.

PURPOSE: Portal imaging is the most important quality assurance procedure for monitoring the reproducibility of setup geometry in radiation therapy. The role of portal imaging has become even more critical in recent years due to the migration of three-dimensional (3D) treatment planning technology, including high-precision conformal therapy, from the research setting to routine clinical practice. Unfortunately, traditional methods for acquiring and interpreting portal images suffer from a number of deficiencies that contribute to the well-documented observation that many setup errors go undetected, and some persist for a clinically significant portion of the prescribed dose. Significant improvements in both accuracy and efficiency of detecting setup errors can, in principle, be achieved by using automatic image registration for on-line screening of images obtained from electronic portal imaging devices (EPIDs). METHODS AND MATERIALS: This article presents recent developments in a method called core-based image analysis that shows great promise for achieving the desired improvements in error detection. Core-based image analysis is a fundamental computer vision method that is capable of exploiting the full power of EPIDs by providing for on-line detection of setup errors via automatic registration of user-selected anatomical structures. We describe a robust method for automatic portal image registration based on core analysis and demonstrate an approach for assessing both accuracy and precision of registration methods using realistic, digitally reconstructed portal radiographs (DRPRs) where truth is known. RESULTS: Automatic core-based analysis of a set of 20 DRPRs containing known, random field positioning errors was performed for a patient undergoing treatment for prostate cancer. In all cases, the reported translation was within 1 mm of the actual translation with mean absolute errors of 0.3 mm and standard deviations of 0.3 mm. In all cases, the reported rotation was within 0.6 degree of the actual rotation with a mean absolute error of 0.18 degree and a standard deviation of 0.23 degree. CONCLUSION: Our results, using digitally reconstructed portal radiographs that closely resemble clinical portal images, suggest that automatic core-based registration is suitable as an on-line screening tool for detecting and quantifying patient setup errors.