Comparison of a PACS workstation with laser hard copies for detecting scaphoid fractures in the emergency department

An Evaluation Protocol for Picture Archiving and Communication System: a Systematic Review

Introduction:

Picture archiving and communication system (PACS) serves to store, transmit, communicate and manage medical images. A logical evaluation protocol assists to determine whether the system is technically, structurally and operationally fit. The purpose of this systematic review was to propose a logical evaluation protocol for PACS, particularly useful for new hospitals and other healthcare institutions in developing countries.

Methods and Materials:

We systematically reviewed 25 out of 267 full-length articles, published between 2000 and 2017, retrieved from four sources: Science Direct, Scopus, PubMed and Google Scholar. The extracted data were tabulated and reviewed successively by three independent panels of experts that oversaw the design of this study and the process by which the PACS evaluation protocol was systematically developed.

Results:

The outcome data were ranked by expert panels and analyzed statistically, with the reliability established at 0.82 based on the Pearson’s correlation coefficient. The essential components and the best options to establish an optimal PACS were organized under nine main sections: system configuration;system network;data storage; datacompression;image input; image characteristics; image presentation; communication link; and system security, with a total of 20 components, each of which capable of working optimally with one or more program options.

Conclusions:

This systematic review presents an objective protocol that is an ideal tool for the evaluation of new or existing PACS at healthcare institutions, particularly in developing countries. Despite the significant advantages, the protocol may face minor limitations, largely due to lack of appropriate technical resources in various clinical settings and the host countries.

Can paper replace laser film to communicate the results of wrist radiographs in trauma cases? A reproducibility study of the reading of wrist trauma case radiographs on a PACS workstation, laser film, and paper

The main goal of this study was to determine the reproducibility of the reading of wrist trauma case radiographs using three different media: laser film, a picture archiving and communication systems (PACS) workstation, and paper with an optimized layout. The study was conducted retrospectively in 200 consecutive patients consulting at the emergency department for wrist trauma and who underwent wrist X-ray investigation using a computed radiography system. There were 82 men and 118 women. The mean age was 48.3 years (16-95 years). Our institutional review board does not require patient approval or informed consent for retrospective review of case records. The readings were made by two independent readers who analyzed the 200 patient radiographs consecutively in one session for each type of media: paper, laser film, and on a PACS dual-screen workstation. The inter-reader agreements were substantial or almost perfect, with kappa values of 0.83 (0.76-0.90) for the PACS, 0.83 (0.76-0.90) for film, and 0.80 (0.72-0.87) for paper. The inter-technique agreement was almost perfect in all cases. There is a high interobserver agreement between PACS, laser film, and paper readings for wrist trauma cases. With a layout of one radiograph on each sheet, paper could replace laser films to communicate the results of wrist radiographs in trauma cases for outpatients.

X-ray categorization and retrieval on the organ and pathology level, using patch-based visual words

In this study we present an efficient image categorization and retrieval system applied to medical image databases, in particular large radiograph archives. The methodology is based on local patch representation of the image content, using a "bag of visual words" approach. We explore the effects of various parameters on system performance, and show best results using dense sampling of simple features with spatial content, and a nonlinear kernel-based support vector machine (SVM) classifier. In a recent international competition the system was ranked first in discriminating orientation and body regions in X-ray images. In addition to organ-level discrimination, we show an application to pathology-level categorization of chest X-ray data, the most popular examination in radiology. The system discriminates between healthy and pathological cases, and is also shown to successfully identify specific pathologies in a set of chest radiographs taken from a routine hospital examination. This is a first step towards similarity-based categorization, which has a major clinical implications for computer-assisted diagnostics.