by Lee, Robert E.; Welch, E. Brian; Cobb, Jared G.; Sinha, Tuhin; Gore, John C.; Yankeelov, Thomas E.

Magnetic resonance imaging (MRI) investigations of breast cancer incorporate computationally intense techniques to develop parametric maps of pathophysiological tissue characteristics. Common approaches employ, for example, quantitative measurements of T
₁, the apparent diffusion coefficient, and kinetic modeling based on dynamic contrast-enhanced MRI (DCE-MRI). In this paper, an integrated medical image post-processing and archive system (MIPAS) is presented. MIPAS demonstrates how image post-processing and user interface programs, written in the interactive data language (IDL) programming language with data storage provided by a Microsoft Access database, and the file system can reduce turnaround time for creating MRI parametric maps and provide additional organization for clinical trials. The results of developing the MIPAS are discussed including potential limitations of the use of IDL for the application framework and how the MIPAS design supports extension to other programming languages and imaging modalities. We also show that network storage of images and metadata has a significant (p < 0.05) increase in data retrieval time compared to collocated storage. The system shows promise for becoming both a robust research picture archival and communications system working with the standard hospital PACS and an image post-processing environment that extends to other medical image modalities.

DOI: 10.1007/s10278-008-9123-2
Online Date: 4/30/2008
Print publication date: 8/1/2009
View article on SpringerLink

by Foos, David H.; Sehnert, W. James; Reiner, Bruce; Siegel, Eliot L.; Segal, Arthur; Waldman, David L.

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.

DOI: 10.1007/s10278-008-9112-5
Online Date: 4/30/2008
Print publication date: 2/1/2009
View article on SpringerLink

by Koivikko, Mika P.; Kauppinen, Tomi; Ahovuo, Juhani

Speech recognition (SR), available since the 1980s, has only recently become sufficiently reliable to allow utilization in medical environment. This study measured the effect of SR for the radiological dictation process and estimated differences in report turnaround times (RTTs). During the transition from cassette-based reporting to SR, the workflow of 14 radiologists was periodically followed up for 2 years in a university hospital. The sample size was more than 20,000 examinations, and the radiologists were the same throughout the study. A RTT was defined as the time from imaging at the modality to the time when the report was available for the clinician. SR cut down RTTs by 81% and the standard deviation by 83%. The proportion of reports available within 1 h escalated from 26% to 58%. The proportion of reports created by SR increased during a follow-up time of this study from 0% up to 88%. SR decreases turnaround times and may thus speed up the whole patient care process by facilitating online reporting. SR was easily adopted and well accepted by radiologists. Our findings encourage the utilization of SR, which improves the productivity and accelerates the workflow with excellent end-user satisfaction.

DOI: 10.1007/s10278-008-9121-4
Online Date: 4/24/2008
Print publication date: 12/1/2008
View article on SpringerLink

by Honey, Ian D.; Mackenzie, Alistair

A series of artifact images, obtained over 5 years of performance testing, of both computed radiography (CR) and integrated digital radiographic X-ray imaging detectors are presented. The images presented are all either flat field or test object images and show artifacts previously either undescribed in the existing literature or meriting further comment. The artifacts described are caused by incorrect flat field corrections, a failing amplifier, damaged detector lines affecting their neighbors, lost information between neighboring detector tiles, image retention, delamination of a detector, poor setup of mechanical movements in CR, suckers damaging a CR plate, inappropriate use of grid suppression software, inappropriate use of a low pass spatial frequency filter, and unsharp masking filters. The causes and significance of the artifacts are explained and categorized as software or hardware related. Actions taken to correct the artifacts are described and explained. This work will help physicists, radiographers, and radiologists identify various image quality problems and shows that quality assurance is useful in identifying artifacts.

DOI: 10.1007/s10278-008-9109-0
Online Date: 4/22/2008
Print publication date: 8/1/2009
View article on SpringerLink

by Honeyman-Buck, Janice

DOI: 10.1007/s10278-008-9119-y
Online Date: 4/22/2008
Print publication date: 6/1/2008
View article on SpringerLink

by Guliato, Denise; Bôaventura, Ricardo S.; Maia, Marcelo A.; Rangayyan, Rangaraj M.; Simedo, Mariângela S.; Macedo, Túlio A. A.

We propose the design of a teaching system named Interpretation and Diagnosis of Mammograms (INDIAM) for training students in the interpretation of mammograms and diagnosis of breast cancer. The proposed system integrates an illustrated tutorial on radiology of the breast, that is, mammography, which uses education techniques to guide the user (doctors, students, or researchers) through various concepts related to the diagnosis of breast cancer. The user can obtain informative text about specific subjects, access a library of bibliographic references, and retrieve cases from a mammographic database that are similar to a query case on hand. The information of each case stored in the mammographic database includes the radiological findings, the clinical history, the lifestyle of the patient, and complementary exams. The breast cancer tutorial is linked to a module that simulates the analysis and diagnosis of a mammogram. The tutorial incorporates tools for helping the user to evaluate his or her knowledge about a specific subject by using the education system or by simulating a diagnosis with appropriate feedback in case of error. The system also makes available digital image processing tools that allow the user to draw the contour of a lesion, the contour of the breast, or identify a cluster of calcifications in a given mammogram. The contours provided by the user are submitted to the system for evaluation. The teaching system is integrated with AMDI—An Indexed Atlas of Digital Mammograms—that includes case studies, e-learning, and research systems. All the resources are accessible via the Web.

DOI: 10.1007/s10278-008-9111-6
Online Date: 4/19/2008
Print publication date: 8/1/2009
View article on SpringerLink

Submit a creative and provocative question for the SIIM 2008 closing session and if it is selected to be used you may win an Amazon Kindle, an Apple IPOD Touch 16 GB, an IBM Think Pad T40, or a Garmin nuvi 750 Portable GPS System.  You must be present to win.  What a great session this will be - excellent topics, an expert panel, and awesome gadgets.    For more on SIIM 2008, click on the link in the Blogroll on the right side of this page.

by Tsuchiya, Yuichiro; Kodera, Yoshie; Tanaka, Rie; Sanada, Shigeru

Early detection and treatment of lung cancer is one of the most effective means of reducing cancer mortality, and to this end, chest X-ray radiography has been widely used as a screening method. A related technique based on the development of computer analysis and a flat panel detector (FPD) has enabled the functional evaluation of respiratory kinetics in the chest and is expected to be introduced into clinical practice in the near future. In this study, we developed a computer analysis algorithm to detect lung nodules and to evaluate quantitative kinetics. Breathing chest radiographs obtained by modified FPD and breath synchronization utilizing diaphragmatic analysis of vector movement were converted into four static images by sequential temporal subtraction processing, morphological enhancement processing, kinetic visualization processing, and lung region detection processing. An artificial neural network analyzed these density patterns to detect the true nodules and draw their kinetic tracks. Both the algorithm performance and the evaluation of clinical effectiveness of seven normal patients and simulated nodules showed sufficient detecting capability and kinetic imaging function without significant differences. Our technique can quantitatively evaluate the kinetic range of nodules and is effective in detecting a nodule on a breathing chest radiograph. Moreover, the application of this technique is expected to extend computer-aided diagnosis systems and facilitate the development of an automatic planning system for radiation therapy.

DOI: 10.1007/s10278-008-9116-1
Online Date: 4/16/2008
Print publication date: 4/1/2009
View article on SpringerLink

We know all you scientific presenters are anxious to get your work published.  Be sure to submit your full paper to JDI prior to the annual meeting.  The link to manuscript central is included on the webroll to the right of this posting for your convenience.  As soon as your papers are accepted and published online first, the abstracts will be published in our blog for everyone’s notice so you will have immediate recognition. 

On behalf of the Board of Directors of Society of Imaging Informatics in Medicine (SIIM), SIIM management, Springer management and the Journal of Digital Imaging (JDI) Editorial Board and Office, I welcome you to the blog for JDI, the official journal of SIIM.  Our goal is to provide a forum for stimulating discussion of all topics relating to our fascinating and ever evolving profession, hopefully stirring up a little controversy and making everyone’s day a little more interesting.  We want to be the place everyone starts their day.

We invite you to register so you can post your comments and make suggestions on topics for the blog.  This blog is edited so we can keep it professional at all times with the Editor-in-Chief of JDI, Janice Honeyman-Buck along with Caroline Wilson and Linda Scott from the Editorial office at SIIM acting as editors.  When you submit a comment, our goal is to approve the comment for publication within 24 hours.