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Rationale and Objectives: The aim of this study was to evaluate the effect of computer-aided diagnosis (CAD) on radiologists'' estimates of the likelihood of malignancy of lung nodules on computed tomographic (CT) imaging. Methods and Materials: A total of 256 lung nodules (124 malignant, 132 benign) were retrospectively collected from the thoracic CT scans of 152 patients. An automated CAD system was developed to characterize and provide malignancy ratings for lung nodules on CT volumetric images. An observer study was conducted using receiver-operating characteristic analysis to evaluate the effect of CAD on radiologists'' characterization of lung nodules. Six fellowship-trained thoracic radiologists served as readers. The readers rated the likelihood of malignancy on a scale of 0% to 100% and recommended appropriate action first without CAD and then with CAD. The observer ratings were analyzed using the Dorfman-Berbaum-Metz multireader, multicase method. Results: The CAD system achieved a test area under the receiver-operating characteristic curve (A z) of 0.857 ± 0.023 using the perimeter, two nodule radii measures, two texture features, and two gradient field features. All six radiologists obtained improved performance with CAD. The average A z of the radiologists improved significantly (P < .01) from 0.833 (range, 0.817–0.847) to 0.853 (range, 0.834–0.887). Conclusion: CAD has the potential to increase radiologists'' accuracy in assessing the likelihood of malignancy of lung nodules on CT imaging. [Copyright &y& Elsevier]

Rationale and Objectives: To retrospectively investigate the effect of a computer-aided detection (CAD) system on radiologists'' performance for detecting small pulmonary nodules in computed tomography (CT) examinations, with a panel of expert radiologists serving as the reference standard. Materials and Methods: Institutional review board approval was obtained. Our dataset contained 52 CT examinations collected by the Lung Image Database Consortium, and 33 from our institution. All CTs were read by multiple expert thoracic radiologists to identify the reference standard for detection. Six other thoracic radiologists read the CT examinations first without and then with CAD. Performance was evaluated using free-response receiver operating characteristics (FROC) and the jackknife FROC analysis methods (JAFROC) for nodules above different diameter thresholds. Results: A total of 241 nodules, ranging in size from 3.0 to 18.6 mm (mean, 5.3 mm) were identified as the reference standard. At diameter thresholds of 3, 4, 5, and 6 mm, the CAD system had a sensitivity of 54%, 64%, 68%, and 76%, respectively, with an average of 5.6 false positives (FPs) per scan. Without CAD, the average figures of merit (FOMs) for the six radiologists, obtained from JAFROC analysis, were 0.661, 0.729, 0.793, and 0.838 for the same nodule diameter thresholds, respectively. With CAD, the corresponding average FOMs improved to 0.705, 0.763, 0.810, and 0.862, respectively. The improvement achieved statistical significance for nodules at the 3 and 4 mm thresholds (P = .002 and .020, respectively), and did not achieve significance at 5 and 6 mm (P = .18 and .13, respectively). At a nodule diameter threshold of 3 mm, the radiologists'' average sensitivity and FP rate were 0.56 and 0.67, respectively, without CAD, and 0.67 and 0.78 with CAD. Conclusion: CAD improves thoracic radiologists'' performance for detecting pulmonary nodules smaller than 5 mm on CT examinations, which are often overlooked by visual inspection alone. [Copyright &y& Elsevier]

Magnetic resonance imaging (MRI) is an established imaging modality, recognized for its value in the assessment and monitoring of a wide range of cardiac pathology. It can provide physiologic as well as anatomic information. Image interpretation requires both well-developed MRI skills and knowledge of cardiac pathology. Radiologists, because of their extensive experience in MRI, have an important role in its application in the heart. The guidelines presented here are an educational tool designed to assist practitioners in providing the best possible patient care via the diagnostic methods of cardiac MRI. American College of Radiology requirements for physicians and personnel performing and interpreting cardiac MRI, which will become applicable by July 1, 2008, are also presented. [Copyright &y& Elsevier]

Rationale and Objectives: We sought to develop a computer-aided diagnosis (CAD) system for assisting radiologists in the detection of pulmonary embolism (PE) on computed tomography pulmonary angiographic (CTPA) images.Materials and Methods: An adaptive three-dimensional (3D) voxel clustering method was developed based on expectation-maximization (EM) analysis to extract vessels from their surrounding tissues. Using a connected component analysis, the vessel tree was reconstructed by tracking the vessel and its branches in 3D space. The tracked vessels were prescreened for suspicious PE areas using a second EM analysis. A rule-based false-positive (FP) reduction method was designed to detect true PE based on the features of PE and vessels. In this preliminary study, 14 patients with positive CTPA for PE were studied. CT scans were performed at 1.25-mm collimation using a GE LightSpeed CT scanner; eight of these patients also had extensive lung parenchymal or pleural disease. One hundred sixty-three emboli were identified by two experienced thoracic radiologists. The emboli identified by the radiologists were used as the "gold standard." For each embolus, the percent diameter occlusion (clot) and conspicuity of embolus (rating of 1 to 5, with 5 being the most conspicuous) were visually estimated. One hundred one emboli were identified in the six patients without lung diseases; 57 were proximal to the subsegmental and 44 were subsegmental. For the eight patients with lung diseases, 62 emboli were identified, of which 37 were proximal to the subsegmental and 25 were subsegmental. A computer-detected volume was counted as true-positive when it overlapped with an embolus volume identified by the radiologists.Results: In the cases without lung diseases, if the PE had a conspicuity of >2 and only partially (20%-80%) occluded the vessel, our method detected 92.0% of proximal emboli and 77.8% of subsegmental emboli, with an average of 18.3 FPs/case. In the cases containing extensive lung disease, 66.7% and 40.0% of the PEs were detected with an average of 11.4 FPs/case under the same conditions. For the 14 PE cases, 13 of them were diagnosed as positive PE cases (case sensitivity was 92.9%).Conclusion: This preliminary study indicates that our automated method is a promising approach to CAD of PE on CTPA. Further study is under way to collect a larger data set and to improve the detection accuracy for PE, especially those with <20% or >80% occlusion, and for very subtle PE. A fully developed CAD system is expected to provide a useful aid for PE detection on CTPA. [ABSTRACT FROM AUTHOR]

Objective: To describe a quality improvement process that was initiated in a Department of Radiology to reduce the number of incomplete or "lost" imaging studies and decrease the time from the initiation of an imaging study to printing of the final report., Methods: Incomplete cases were defined as those imaging studies that did not have a signed final report more than 3 days and less than 90 days after imaging. A computer program was written to generate a monthly incomplete case list from the radiology information system database; each step in the process, from patient arrival to final report printing, was analyzed and a list of root causes (for the incomplete cases) was developed. Short- and long-term interventions were introduced and the effects were monitored from 1992-1999., Results: Problems were identified at each step in the process. Although some of the root causes originated outside the authority of the Department of Radiology, interventions we implemented within the department reduced the incomplete list by 72%, from a high of 2.8% of all imaging examinations to less than 0.8%. Continual monitoring of the problem is necessary to maintain this level., Conclusion: The number of incomplete or "lost" imaging studies can be decreased using a continuous quality improvement process. This leads to improved patient care and increased revenue.

Rationale and Objectives: The purpose of this study was to determine relative rates of missed diagnoses for radiologists as a measure of competence in interpreting chest radiographs., Materials and Methods: Cases involving differing interpretations of chest radiographs were collected from January 1994 through December 1999 by faculty (chest and nonchest radiology specialists) in an academic radiology department. A quarterly peer-review process designated cases months after the fact, and anonymously, as no miss or as class I (nondiagnosable), class II (very difficult diagnosis), class III (should be diagnosed most of time), or class IV (should almost always be diagnosed) missed diagnoses. The rates and classes of missed diagnoses were compared among chest faculty and for the nonchest radiology specialists as a group., Results: Chest radiologists read 184,977 studies, and nonchest radiologists read 300,684 studies. Of these, 243 missed diagnoses were classified (classes I and II, 184 cases; class III, 50; and class IV, nine). No difference was detected in the rate of class III and IV misses among chest faculty, but nonchest faculty had significantly more class III (P = .022) and class IV misses (P = .016)., Conclusion: Random sampling of differing interpretations can yield a relative rate of missed diagnoses for radiologists. No difference was detected in clinically important misses (ie, classes III and IV) among chest radiologists, but a statistically significantly higher rate of seemingly obvious misdiagnoses was found for nonchest specialty radiologists. Potential biases may have influenced this analysis, including disease prevalence, sampling, clinical factors, observer variability, and truth-in-diagnosis.

Objective: To evaluate the use of bedside chest radiography and patient outcome before and after implementation of a cardiac surgery critical care pathway that included guidelines for bedside radiography., Design: A cohort observational study., Setting: A university hospital in the midwest., Patients: Three groups, of 100 patients each, undergoing cardiac surgery in 1990, 1991, and 1995., Intervention: Introduction of a critical care pathway., Measurements: Medical records were retrospectively reviewed in three groups of 100 patients each: before the introduction of the critical care pathway; 2 months after introduction of the pathway in 1991; and 4 yrs after introduction in 1995. Data were analyzed to determine operative risk for each group. Subsequent analyses determined bedside radiography use, total length of hospital stay, and patient outcome (mortality rate, complications requiring intervention, and reoperation) during hospitalization and at outpatient follow-up 15-30 days postdischarge., Results: Total length of hospital stay was shorter for the 1995 group (7.6+/-6.6 days) compared with other groups (prepathway, 11.1+/-10.3 days; 1991 postpathway, 10.2+/-9.6 days; p<.05). The mean numbers of radiographs per patient were as follows: prepathway, 5.1; 1991 postpathway, 5.2; and 1995 postpathway, 3.3. The mean number of radiographs in the 1995 group was significantly lower (p = .02). More patients had the proposed number of two bedside radiographs described in the pathway in the 1995 group compared with the other groups (prepathway, p<.0001; the two-month postpathway group, p = .01). Twenty-three malpositioned catheters/tubes were found in the prepathway and 1991 groups compared with 11 in the 1995 group (p = .02). No statistically significant difference was found in inpatient complications (mediastinal bleeding, pneumothoraces, and pleural effusions), postdischarge complications, reoperations, or mortality rate., Conclusion: Introduction of a critical care pathway can decrease the use of bedside radiography without adversely affecting near-term patient outcomes.