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Purpose: To compare the influence of visual and acoustical CAD markers on radiologist’s performance with regard to suggestive and distractive effects. Materials and methods: Ten radiologists analyzed 150 pictures of ches t CT slices. Every picture contained a visual CAD marker. 100 pictures showed one nodule: CAD marker marked this in 50 cases and in 50 cases a false positive finding (f.p.). The other 50 cases showed no nodule but an f.p. marker. After 3 years same images were presented to thirteen radiologists with only a sound as CAD marker. 55 of 150 images were marked, 30 true positive and 25 f.p. Sensitivity and f.p. rate were calculated for both marker ty pes. Significance between sens itivities and f.p. rates were calculated by multiple-ana lysis-of-variance (MANOVA). Results: Without CAD mean sensitivity resp. f.p. were 57.7% /.13 . In case of correct optical resp. acoustical marker sensitivity increased to 75.6% resp. 63.1%. For incorrect se t marker mean f.p. rate increased to .31 resp. .24. MANOVA showed that marker’s correctness highly significan tly influenced sensitivity (p

Purpose: The efficiency of the detection of pulmonary nodules by a radiologist with the help of CAD is influenced by the user interface of the system. Marker with a visually dominant appearance may distract the radiologist from other parts of the screen. Purpose was to analyse the influence of different CAD markers on radiologist's performance. Materials and methods: 10 radiologists analysed 150 pictures of chest CT slices. Every picture contained a CAD marker; five different types of markers were used - each respectively on 30 pictures (1: thick walled square, 2: thin walled circle, 3: small arrow, 4: pixel sized point on nodule, 5: very subtle change of colour). One hundred images contained one nodule: CAD markers marked this finding in 50 cases; in 50 cases a false positive finding was marked instead. The remaining 50 images contained no nodule but a marker of a false positive finding. The radiologists had to decide for each image if there was a nodule visible and either click on the nodule or on a button "no finding". Sensitivity and specificity were calculated for each marker type. Results: Mean sensitivity was 59%, 62%, 64%, 65% and 64% for marker 1 to 5, respectively. Specificity was 50%, 51%, 64%, 45% and 67%. In the cases with false positive findings sensitivity for detection of the unmarked nodule was 41%, 58%, 59%, 49% and 54%. New work to be presented: The study shows that the marker type influences radiologist's sensitivity and distraction from other findings. Conclusion: Of the tested markers a small arrow was most efficient for the presentation of the results to the radiologist.

The purpose of the presented study was to determine the impact of two different CAD systems used as concur-rent reader for detection of actionable nodules (>4 mm) on the interpretation of chest CT scans during routine reporting. Fifty consecutive MDCT scans (1 mm or 1.25 mm slice thickness, 0.8 mm reconstruction increment) were se-lected from clinical routine. All cases were read by a resident and a staff radiologist, and a written report was available in the radiology information system (RIS). The RIS report mentioned at least one actionable pulmonary nodule in 18 cases (50%) and did not report any pulmonary nodule in the remaining 32 cases. Two different recent CAD systems were independently applied to the 50 CT scans as concurrent reader with two radiologists: Siemens LungCare NEV and MEDIAN CAD-Lung. Two radiologists independently reviewed the CAD results and determined if a CAD result was a true positive or a false positive finding. Patients were classified into two groups: in group A if at least one actionable nodule was detected and in group B if no actionable nodules were found. The effect of CAD on routine reporting was simulated as set union of the findings of routine reporting and CAD thus applying CAD as concurrent reader. According to the RIS report group A (patients with at least one actionable nodule) contained 18 cases (36% of all 50 cases), and group B contained 32 cases. Application of a CAD system as concurrent reader resulted in detec-tion of additional CT scans with actionable nodules and reclassification into group A in 16 resp. 18 cases (radi-ologist 1 resp. radiologist 2) with Siemens NEV and in 19 resp. 18 cases with MEDIAN CAD-Lung. In seven cases MEDIAN CAD-Lung and in four cases Siemens NEV reclassified a case into group A while the other CAD system missed the relevant finding. Sensitivity on a nodule (>4 mm) base was .45 for Siemens NEV and .55 for MEDIAN CAD-Lung; the difference was not yet significant (p=.077). In our study use of CAD as second reader in routine reporting doubled the percentage of patients with actionable nodules larger than 4 mm.