Add-on device for stereotactic core-needle breast biopsy: how many biopsy specimens are needed for a reliable diagnosis?

PURPOSE: To prospectively determine whether there is a minimum number of cores required for histopathologic diagnosis of mammographically detected nonpalpable breast lesions with an add-on 14-gauge stereotactic core-needle biopsy device. MATERIALS AND METHODS: The study was approved by the ethics committee of the hospital; informed consent was obtained. Biopsy was performed in 197 patients with 205 lesions (97 masses, 108 microcalcifications). The first sample (from the center) was collected in container A; second and third samples (2 mm from center), in container B; and additional samples, in container C. Malignancies, atypical ductal hyperplasia (ADH), and radial scars were excised. Benign lesions were followed up mammographically (mean, 24 months). Strict sensitivity and working sensitivity were calculated separately. Stereotactic biopsy with diagnosis of a nonmalignant lesion that, after surgery, proved to be malignant was considered false-negative when strict sensitivity was calculated. Stereotactic biopsy with diagnosis of ADH or radial scar was considered true-positive if the findings at surgery corresponded to the results at biopsy or indicated malignancy and was considered false-positive if the findings at surgery were benign when working sensitivity was calculated. Sensitivity, specificity, and overall accuracy of stereotactic biopsy were determined for masses and microcalcifications in all three containers by using surgical samples and findings at mammographic follow-up as reference. At chi2 analysis, P < .05 was considered to indicate significant difference. RESULTS: Strict sensitivity of the first sample was 77% (66 of 86) (90% [35 of 39] for masses, 66% [31 of 47] for microcalcifications). Results of the first sample were false-negative significantly more often in microcalcifications (n = 16) than in masses (n = 4) (P = .010). Combined results of containers A and B (ie, three samples) yielded higher strict sensitivity than those with first sample alone (95% [37 of 39] for masses [P = .196], 91% [43 of 47] for microcalcifications [P < .001]). With multiple samples, strict and working sensitivity were both 100% (39 of 39) for masses and 91% (43 of 47) and 98% (46 of 47), respectively, for microcalcifications. Four false-negative diagnoses (ADH, three cases; lesion with discordant mammographic and stereotactic biopsy findings, one case) were microcalcifications. CONCLUSION: More than three samples are needed (a minimum number was not determined) for a histologic diagnosis of a mass lesion by using an add-on stereotactic biopsy device.

Carotid artery stenosis: reproducibility of automated 3D CT angiography analysis method.

The aim of this study was to assess the reproducibility and anatomical accuracy of automated 3D CT angiography analysis software in the evaluation of carotid artery stenosis with reference to rotational DSA (rDSA). Seventy-two vessels in 36 patients with symptomatic carotid stenosis were evaluated by 3D CT angiography and conventional DSA (cDSA). Thirty-one patients also underwent rotational 3D DSA (rDSA). Multislice CT was performed with bolus tracking and slice thickness of 1.5 mm (1-mm collimation, table feed 5 mm/s) and reconstruction interval of 1.0 mm. Two observers independently performed the stenosis measurements on 3D CTA and on MPR rDSA according to the NASCET criteria. The first measurements on CTA utilized an analysis program with automatic stenosis recognition and quantitation. In the subsequent measurements, manual corrections were applied when necessary. Interfering factors for stenosis quantitation, such as calcifications, ulcerations, and adjacent vessels, were registered. Intraobserver and interobserver correlation for CTA were 0.89 and 0.90, respectively (p<0.001). The interobserver correlation between two observers for MPR rDSA was 0.90 (p<0.001). The intertechnique correlation between CTA and rDSA was 0.69 (p<0.001) using automated measurements but increased to 0.81 (p<0.001) with the manually corrected measurements. Automated stenosis recognition achieved a markedly poorer correlation with MPR rDSA in carotids with interfering factors than those in cases where there were no such factors. Automated 3D CT angiography analysis methods are highly reproducible. Manually corrected measurements facilitated avoidance of the interfering factors, such as ulcerations, calcifications, and adjacent vessels, and thus increased anatomical accuracy of arterial delineation by automated CT angiography with reference to MPR rDSA.