Performance of CAD systems for mass detection at mammography varies significantly, depending on examination and system used. Actual performance of all systems in clinical environment can be improved.

Limiting the maximum number of cued regions per case can improve the overall case-based performance of computer-aided detection schemes in mammography.

The goal of this study was to assess whether radiologists' search paths for lung nodule detection in chest computed tomography (CT) between different rendering and display schemes have reliable properties that can be exploited as an indicator of ergonomic efficiency for the purpose of comparing different display paradigms. Eight radiologists retrospectively viewed 30 lung cancer screening CT exams, containing a total of 91 nodules, in each of three display modes [i.e., slice-by-slice, orthogonal maximum intensity projection (MIP) and stereoscopic] for the purpose of detecting and classifying lung nodules. Radiologists' search patterns in the axial direction were recorded and analyzed along with the location, size, and shape for each detected feature, and the likelihood that the feature is an actual nodule. Nodule detection performance was analyzed by employing free-response receiver operating characteristic methods. Search paths were clearly different between sliceby-slice displays and volumetric displays but, aside from training and novelty effects, not between MIP and stereographic displays. Novelty and training effects were associated with the stereographic display mode, as evidenced by differences between the beginning and end of the study. The stereo display provided higher detection and classification performance with less interpretation time compared to other display modes tested in the study; however, the differences were not statistically significant. Our preliminary results indicate a potential role for the use of radiologists' search paths in evaluating the relative ergonomic efficiencies of different display paradigms, but systematic training and practice is necessary to eliminate training curve and novelty effects before search strategies can be meaningfully compared.

Optimal (maximum) PPV1 can occur at any sensitivity level and should not be used as the sole indicator for practice optimization because it does not take into account the number of cancers that would be missed at that sensitivity.

Radiologists' performance reviewing and rating breast cancer screening mammography exams using a telemammography system was evaluated and compared with the actual clinical interpretations of the same interpretations. Mammography technologists from three remote imaging sites transmitted 245 exams to a central site (radiologists), which they (the technologists) believed needed additional procedures (termed "recall"). Current exam image data and non-image data (i.e., technologist's text message, technologist's graphic marks, patient's prior report, and Computer Aided Detection (CAD) results) were transmitted to the central site and displayed on three highresolution, portrait monitors. Seven radiologists interpreted ("recall" or "no recall") the exams using the telemammography workstation in three separate multi-mode studies. The mean telemammography recall rates ranged from 72.3% to 82.5% while the actual clinical recall rates ranged from 38.4% to 42.3% across the three studies. Mean Kappa of agreement ranged from 0.102 to 0.213 and mean percent agreement ranged from 48.7% to 57.4% across the three studies. Eighty-seven percent of the disagreement interpretations occurred when the telemammography interpretation resulted in a recommendation to recall and the clinical interpretation resulted in a recommendation not to recall. The poor agreement between the telemammography and clinical interpretations may indicate a critical dependence on images from prior screening exams rather than any text based information. The technologists were sensitive, if not specific, to the mammography features and changes that may lead to recall. Using the telemammography system the radiologists were able to reduce the recommended recalls by the technologist by approximately 25 percent.