Carestream Peer-Reviewed Workflow Research

Novel, Portable, Cassette-sized, and Wireless Flat-panel Digital Radiography System: Initial Workflow Results Versus Computed Radiography

AJR Am J Roentgenol. 2011 Jun;196(6):1368-71. Lehnert T, Naguib NN, Ackermann H, Schomerus C, Jacobi V, Balzer JO, Vogl TJ. Source Department of Diagnostic and Interventional Radiology, Clinic of Johann Wolfgang Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany.

Abstract
The purpose of this article is to compare workflow efficiency between a conventional computed radiography (CR) system and a novel, portable, cassette-sized, and wireless flat-panel digital radiography (DR) system. Overall radiographer time was significantly shorter when performing examination-related tasks with the novel, portable DR system than when performing comparable tasks with the CR system, a difference that appears to result largely from technology configuration.

Improved Visualization of Tubes and Lines in Portable Intensive Care Unit Radiographs: A Study Comparing a New Approach to the Standard Approach

David H. Foos, David F. Yankelevitz, Xiaohui Wang, David Berlin, Dana Zappetti, Matthew Cham, Abraham Sanders, Katherine Novak Parker, Claudia I. Henschke, In Press Corrected Proof , 15 November 2010, Clinical Imaging

Abstract
Tube and line interpretation in portable chest radiographs was assessed using a new visualization method. When using the new method, radiologists' interpretation time was reduced by 30% vs. standard modality processing and window and level (23 vs. 33 s). For pulmonary ICU physicians, reading time was essentially unchanged. There was more than a 50% reduction in the use of inferential language in the dictation for both reader groups when using the new method, suggesting greater interpretation confidence.

Digital Radiography Reject Analysis: Data Collection Methodology, Results, and Recommendations from an In-depth Investigation at Two Hospitals

Foos DH, Sehnert WJ, Reiner B, Siegel EL, Segal A, Waldman DL. J Digit Imaging. 2009 Mar;22(1):89-98. Epub 2008 Apr 30.

Abstract
Reject analysis was performed on 288,000 computed radiography (CR) image records collected from a university hospital (UH) and a large community hospital (CH). Each record contains image information, such as body part and view position, exposure level, technologist identifier, and--if the image was rejected--the reason for rejection. Extensive database filtering was required to ensure the integrity of the reject-rate calculations. The reject rate for CR across all departments and across all exam types was 4.4% at UH and 4.9% at CH. The most frequently occurring exam types with reject rates of 8% or greater were found to be common to both institutions (skull/facial bones, shoulder, hip, spines, in-department chest, pelvis). Positioning errors and anatomy cutoff were the most frequently occurring reasons for rejection, accounting for 45% of rejects at CH and 56% at UH. Improper exposure was the next most frequently occurring reject reason (14% of rejects at CH and 13% at UH), followed by patient motion (11% of rejects at CH and 7% at UH). Chest exams were the most frequently performed exam at both institutions (26% at UH and 45% at CH) with half captured in-department and half captured using portable x-ray equipment. A ninefold greater reject rate was found for in-department (9%) versus portable chest exams (1%). Problems identified with the integrity of the data used for reject analysis can be mitigated in the future by objectifying quality assurance (QA) procedures and by standardizing the nomenclature and definitions for QA deficiencies.

Automatic Image Hanging Protocol for Chest Radiographs in PACS

Luo H, Hao W, Foos DH, Cornelius CW. IEEE Trans Inf Technol Biomed. 2006 Apr;10 (2):302-11.

Abstract
Chest radiography is one of the most widely used techniques in diagnostic imaging. It comprises at least one-third of all diagnostic radiographic procedures in hospitals. However, in the picture archive and communication system, images are often stored with the projection and orientation unknown or mislabeled, which causes inefficiency for radiologists' interpretation. To address this problem, an automatic hanging protocol for chest radiographs is presented. The method targets the most effective region in a chest radiograph, and extracts a set of size-, rotation-, and translation-invariant features from it. Then, a well-trained classifier is used to recognize the projection. The orientation of the radiograph is later identified by locating the neck, heart, and abdomen positions in the radiographs. Initial experiments are performed on the radiographs collected from daily routine chest exams in hospitals and show promising results. Using the presented protocol, 98.2% of all cases could be hung correctly on projection view (without protocol, 62%), and 96.1% had correct orientation (without protocol, 75%). A workflow study on the protocol also demonstrates a significant improvement in efficiency for image display.

Enhanced Visualization Processing: Effect on Workflow

Krupinski EA, Radvany M, Levy A, Ballenger D, Tucker J, Chacko A, VanMetter R. Acad Radiol. 2001 Nov; 8 (11):1127-33.

Abstract
Soft-copy viewing of digital radiographs allows for image processing to improve visualization of anatomy and lesions, but it can take more time than film-based viewing. Enhanced visualization processing (EVP) was developed to increase the latitude of an image without reducing the vital contrast, potentially reducing the need for the radiologist to manipulate images. This study examined the influence of processing radiographic images with EVP on workflow in a picture archiving and communications system (PACS). EVP of chest images displayed on PACS monitors significantly improved workflow as measured by viewing time. EVP decreased use of window and level manipulation and zooming and the amount of time each one was used.

Scientific Exhibit (EPOS poster C-3027) at ECR2010: Novel Cassette-sized, Flat-Panel Digital Radiography (DR) System: Initial Clinical and Workflow Results Versus Computed Radiography (CR).

T. Lehnert, M. Kissner, S. Raetzer, R. Bauer, V. Jacobi, T. J. Vogl; Frankfurt/Main/DE  

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