Femoroacetabular impingement syndrome (FAI) is a pathologic entity which can lead to chronic symptoms of pain, reduced range of motion in flexion and internal rotation, and has been shown to correlate with degenerative arthritis of the hip. History, physical examination, and supportive radiographic findings such as evidence of articular cartilage damage, acetabular labral tearing, and early-onset degenerative changes can help physicians diagnose this entity. Several pathologic changes of the femur and acetabulum are known to predispose patients to develop FAI and recognition of these findings can ultimately lead to therapeutic interventions. The two basic mechanisms of impingement-cam impingement and pincer impingement-are based on the type of anatomic anomaly contributing to the impingement process. These changes can be found on conventional radiography, MR imaging, and CT examinations. However, the radiographic findings of this entity are not widely discussed and recognized by physicians. In this paper, we will introduce these risk factors, the proposed supportive imaging criteria, and the ultimate interventions that can help alleviate patients' symptoms.

Speech recognition (SR) in the radiology department setting is viewed as a method of decreasing overhead expenses by reducing or eliminating transcription services and improving care by reducing report turnaround times incurred by transcription backlogs. The purpose of this study was to show the ability to integrate off-the-shelf speech recognition software into a Hospital Information System in 3 types of military medical facilities using the Windows programming language Visual Basic 6.0 (Microsoft, Redmond, WA). Report turnaround times and costs were calculated for a medium-sized medical teaching facility, a medium-sized nonteaching facility, and a medical clinic. Results of speech recognition versus contract transcription services were assessed between July and December, 2000. In the teaching facility, 2,042 reports were dictated on 2 computers equipped with the speech recognition program, saving a total of US $3,319 in transcription costs. Turnaround times were calculated for 4 first-year radiology residents in 4 imaging categories. Despite requiring 2 separate electronic signatures, we achieved an average reduction in turnaround time from 15.7 hours to 4.7 hours. In the nonteaching facility, 26,600 reports were dictated with average turnaround time improving from 89 hours for transcription to 19 hours for speech recognition saving US $45,500 over the same 6 months. The medical clinic generated 5,109 reports for a cost savings of US $10,650. Total cost to implement this speech recognition was approximately US $3,000 per workstation, mostly for hardware. It is possible to design and implement an affordable speech recognition system without a large-scale expensive commercial solution.KEY WORDS: computer, speech recognition, picture archiving and communication systems, interface, composite health-care system THE EFFORT to improve patient care by .1 collapsing the diagnostic and therapeutic timeline has driven computer applications development in a variety of areas. Tremendous improvements in hardware and software over Journal of Digital Imaging, Vol 15, No 1 (March}, 2002: pp 43-53 the last decade have stimulated this progress. With picture archiving and communication system (PACS) technology, images are available immediately throughout the health care system, but there continues to be a lag in the transmission of the corresponding completed radiology reports. 1,2 The purpose of this report is to relate our experience with the development and integration of an off-the-shelf speech/voice recognition application into a hospital information system (HIS) using a graphical interface program developed by one of the authors.Speech recognition in the radiology department setting decreases overhead expenses by reducing or eliminating transcription services or as a means to improve patient care by reducing report turnaround times. 2 ,3 Significant problems can arise in facilities that attempt to integrate a speech recognition system into the HIS. 4 This can be difficult particularly in the setting of a training program...

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