Shear Wave Elastography (SWE): An Analysis of Breast Lesion Characterization in 83 Breast Lesions.

Qualitative and quantitative shear wave elastography (SWE) criteria were assessed to differentiate between malignant and benign breast lesions. This prospective study included 83 lesions. SWE features measured included maximal stiffness values inside the lesion (E(lesion)) and in the peri-lesion area (E(perilesion)) and ratio values (R(lesion) and R(perilesion)) according to the formula E(lesion) or E(perilesion)/E(fat), with E(fat) corresponding to normal fatty tissue. We compared ultrasonography (B-mode), SWE and histologic sizes. With qualitative and quantitative SWE analysis, sensitivity was 94% and specificity 73%. Malignant lesions appeared more heterogeneous, with higher stiffness and ratio values than benign lesions (p < 0.001). For malignant lesions, SWE size was better correlated to histologic size than B-mode size. Using benign SWE signs to selectively downgrade category 4a and 4b lesions, the specificity improved from 13% to 51% without loss in sensitivity (100%) compared to ultrasound.

Computer-aided detection of acute pulmonary embolism with 64-slice multi-detector row computed tomography: impact of the scanning conditions and overall image quality in the detection of peripheral clots.

PURPOSE: To evaluate the performance of a computer-aided detection (CAD) system for diagnosing peripheral acute pulmonary embolism (PE) with a 64-slice multi-detector row computed tomography (CT). MATERIALS AND METHODS: Two radiologists investigated the accuracy of a software aimed at detecting peripheral clots (PECAD prototype, version 7; Siemens Medical Systems, Forchheim, Germany) by applying this tool for the analysis of the pulmonary arterial bed of 74 CT angiograms obtained with 64-slice dual-source CT (Definition; Siemens Medical Systems). These cases were retrospectively selected from a database of CT studies performed on the same CT unit, with a similar collimation (64 x 0.6 mm) and similar injection protocols. Patient selection was based on a variety of (1) scanning conditions, namely, nongated (n = 30), electrocardiography-gated (n = 30), and dual-energy CT angiograms (n = 14), and (2) image quality (IQ), namely, scans of excellent IQ (n = 53) and lower IQ due to lower levels of arterial enhancement and/or presence of noise (n = 21). The standard of truth was based on the 2 radiologists' consensus reading and the results of CAD. RESULTS: The software detected 80 of 93 peripheral clots present in the 21 patients (42 segmental and 38 subsegmental clots). The overall sensitivity (95% confidence interval) of the CAD tool was 86% (77%-92%) for detecting peripheral clots, 78% (64.5%-88%) at the segmental level and 97% (85.5%-99.9%) at the subsegmental level. Assuming normal vascular anatomy with 20 segmental and 40 subsegmental arteries, overall specificity and positive and negative predictive values (95% confidence interval) of the software were 91.8% (91%-92.6%), 18.4% (15%-22.4%), and 99.7% (99.5%-99.8%), respectively. A mean of 5.4 false positives was found per patient (total, 354 false positives), mainly linked to the presence of perivascular connective tissue (n = 119; 34%) and perivascular airspace consolidation (n = 97; 27%). The sensitivities (95% confidence interval) for the CAD tool were 91% (69.8%-99.3%) for dual-energy, 87% (59.3%-93.2%) for electrocardiography-gated, and 87% (73.5%-95.3%) for nongated scans (P > 0.05). No significant difference was found in the sensitivity of the CAD software when comparing the scans according to the scanning conditions and image quality. CONCLUSIONS: The evaluated CAD software has a good sensitivity in detecting peripheral PE, which is not influenced by the scanning conditions or the overall image quality.