Two-year follow-up of stereotactically guided 9-G breast biopsy: a multicenter evaluation of a self-contained vacuum-assisted device.

PURPOSE: To evaluate the performance of a self-contained, battery-driven, vacuum-assisted breast biopsy (VABB) system for the sampling of clustered breast microcalcifications and masses under stereotactic guidance. METHODS AND MATERIALS: A total of 144 patients (median age: 56 years; range: 21-87 years) in four European breast centers underwent percutaneous 9-gauge (G), stereotactic-guided VABB. The median lesion size was 11 mm (range 2-60 mm). Patients were biopsied in the prone (n=125) or upright position (n=19). All patients were followed up for at least 24 months. RESULTS: The stereotactic procedure was successful in 142 (98.6%) of 144 cases, with two cases cancelled due to either severe patient motion (one case) or failure to detect faint calcifications (one case). A median of 12 specimens per procedure was obtained. In 39 cases (27.5%), the suspicious lesion could no longer be detected mammographically after the biopsy procedure. The histological diagnosis was malignancy in 45 (31.7%) cases. One case of atypical ductal hyperplasia diagnosed preoperatively was upgraded to ductal carcinoma in situ (DCIS) at operation, giving an overall sensitivity of 97.7% for the vacuum-assisted biopsy procedure. In two cases where DCIS was diagnosed at vacuum-assisted biopsy, the malignant tissue was apparently completely removed and could no longer be found at operation. No serious complications occurred. During the follow-up period, no breast cancers appeared at the location of biopsy. Six patients dropped out during the follow-up period. CONCLUSION: The self-contained, vacuum-assisted biopsy device is well suited for stereotactically guided breast biopsies, having demonstrated excellent sensitivity and specificity in the preoperative workup of mammographically detected breast lesions after 2 years of follow-up.

The performance of computer-aided detection when analyzing prior mammograms of newly detected breast cancers with special focus on the time interval from initial imaging to detection.

PURPOSE: The clinical role of CAD systems to detect breast cancer, which have not been on cancer containing mammograms not detected by the radiologist was proven retrospectively. METHODS: All patients from 1992 to 2005 with a histologically verified malignant breast lesion and a mammogram at our department, were analyzed in retrospect focussing on the time of detection of the malignant lesion. All prior mammograms were analyzed by CAD (CADx, USA). The resulting CAD printout was matched with the cancer containing images yielding to the radiological diagnosis of breast cancer. CAD performance, sensitivity as well as the association of CAD and radiological features were analyzed. RESULTS: 278 mammograms fulfilled the inclusion criteria. 111 cases showed a retrospectively visible lesion (71 masses, 23 single microcalcification clusters, 16 masses with microcalcifications, in one case two microcalcification clusters). 54/87 masses and 34/41 microcalcifications were detected by CAD. Detection rates varied from 9/20 (ACR 1) to 5/7 (ACR 4) (45% vs. 71%). The detection of microcalcifications was not influenced by breast tissue density. CONCLUSION: CAD might be useful in an earlier detection of subtle breast cancer cases, which might remain otherwise undetected.

Characteristics of ductal carcinoma in situ in magnetic resonance imaging.

PURPOSE: The aim of this study was to evaluate typical dynamic and morphological characteristics of ductal carcinoma in situ (DCIS) in magnetic resonance imaging (MRI). An optimized diagnosis of DCIS is considered to be valuable for radiologists and clinicians, especially for early and successful treatment planning. MATERIALS AND METHODS: Magnetic resonance examinations of 74 patients with pure DCIS were evaluated. Categories were established for signal increase (C1=the same enhancement as glandular tissue; C2=slow and continuous; C3=strong initial and slow further increase; C4=strong initial increase and plateau phenomenon; and C5=strong initial increase followed by a washout phenomenon) and morphological findings (M0=no pattern observed; M1=linear or linear-branched; M2=segmental dotted or granular; M3=segmental homogenous; and M4=focal spotlike). All cases were associated with histopathological results. RESULTS: Regarding the 74 DCIS lesions, 37 (50%) showed a signal increase typical of malignancy (C4 and C5). Among all cases, 33.3% of G1 lesions, 68.4% of G2 lesions, and 55.5% of G3 lesions presented a C4 or C5 enhancement. Furthermore, 55.4% (n=41) showed a segmental dotted enhancement (M2), whereas 17.6% showed a focal spotlike enhancement (M4). The morphological features of the other lesions were as follows: 12.2% homogeneous (M3) and 4.0% linear (M1). In 8 cases (10.8%), no significant pattern was observed (M0). Combining dynamic and morphological characteristics, 68.9% presented an appearance comparable with the appearance of invasive breast cancer in MRI. CONCLUSIONS: Ductal CIS lesions show typical morphological and kinetic, but heterogeneous, characteristics in MRI, comparable with the histopathological variety of the disease. For detecting pure DCIS cases early and precisely, a combination of dynamic and morphological criteria seems to be important.

Potential MRI interpretation model: differentiation of benign from malignant breast masses.

OBJECTIVE: Our objective was to increase the accuracy of breast MRI using a semiquantitative analysis of typical MRI features and their diagnostic potential. The prevalence of recently reported MRI signs of breast lesions were analyzed and compared with other well-known signs. CONCLUSION: New MRI features, especially from T2-weighted images, are promising for more reliable and accurate interpretation of breast lesions. Prospective studies of these findings are required to define cut-off values and test clinical practicality.

Effect of breast density on computer aided detection.

PURPOSE: This study was conducted to assess the clinical impact of breast density and density of the lesion's background on the performance of a computer-aided detection (CAD) system in the detection of breast masses (MA) and microcalcifications (MC). MATERIALS AND METHODS: A total of 200 screening mammograms interpreted as BI-RADS 1 and suspicious mammograms of 150 patients having a histologically verified malignancy from 1992 to 2000 were selected by using a sampler of tumor cases. Excluding those cases having more than one lesion or a contralateral malignancy attributable to statistical reasons, 127 cases with 127 malignant findings were analyzed with a CAD system (Second Look 5.0, CADx Systems, Inc., Beavercreek, OH). Of the 127 malignant lesions, 56 presented as MC and 101 presented as MA, including 30 cases with both malignant signs. Overall breast density of the mammogram and density of the lesion's background were determined by two observers in congruence (density a: entirely fatty, density b: scattered fibroglandular tissue, density c: heterogeneously dense, density d: extremely dense). RESULTS: Within the unsuspicious group, 100/200 cases did not have any CAD MA marks and were therefore truly negative (specificity 50%), and 151/200 cases did not have any CAD MC marks (specificity 75.5%). For these 200 cases, the numbers of marks per image were 0.41 and 0.37 (density a), 0.38 and 0.97 (density b), 0.44 and 0.91 (density c), and 0.58 and 0.68 (density d) for MC and MA marks, respectively (Fisher's t-test: n.s. for MC, p < 0.05 for MA). Malignant lesions were correctly detected in at least one view by the CAD system for 52/56 (92.8%) MC and 91/101 (90.1%) MA. Detection rate versus breast density was: 4/6 (66.7%) and 18/19 (94.7%) (density a), 32/33 (97.0%) and 49/51 (96.1%) (density b), 14/15 (93.3%) and 23/28 (82.1%) (density c), and 2/2 (100%) and 1/3 (33.3%) (density d) for MC and MA, respectively. Detection rate versus the lesion's background was: 19/21 (90.5%) and 36/38 (94.7%) (density a), 34/36 (94.4%) and 59/62 (95.2%) (density b), 8/9 (88.9%) and 20/24 (83.3%) (density c), and 9/10 (90%) and 4/8 (50%) (density d) for groups 2 and 3, respectively. Detection rates differed significantly for masses in heterogeneously dense and extremely dense tissue (overall or lesion's background) versus all other densities (Fisher's t-test: p < 0.05). A significantly lowered FP rate for masses was found on mammograms of entirely fatty tissue. CONCLUSION: Overall breast density and density at a lesion's background do not appear to have a significant effect on CAD sensitivity or specificity for MC. CAD sensitivity for MA may be lowered in cases with heterogeneously and extremely dense breasts, and CAD specificity for MA is highest in cases with extremely fatty breasts. The effects of overall breast density and density of a lesion's background appear to be similar.

Are unnecessary follow-up procedures induced by computer-aided diagnosis (CAD) in mammography? Comparison of mammographic diagnosis with and without use of CAD.

OBJECTIVE: To evaluate the rate of unnecessary follow-up procedures recommended by radiologists using a CAD-system. MATERIALS AND METHODS: 185 patients (740 images) were consecutively selected from three groups (36 histologically proven cancers = group 1; 49 histologically proven benign lesions = group 2 and 100 screening cases (4 years-follow up = group 3). Mammograms were evaluated by a CAD system (Second Look, CADx, Canada). Five blinded radiologists assessed the images without/with CAD outputs. Diagnostic decisions were ranked from surely benign to surely malignant according to BIRADS classification, follow-up procedures were recommended for each observed lesion (a, screening; b, short interval follow-up examination in 6 months; c, pathologic clarification). RESULTS: CAD-system detected 32/36 cancers (88.9%) (FP-rate: 1.04 massmarks and 0.27 calcmarks/image). The following values were reached by all observers without/with CAD in the mean: Sensitivity 80.6/80.0%, specificity 83.2/86.4%, PPV 53.1/58.1%, and NPV 94.6/94.7%. Observers described a similar number of additional lesions without/with the use of CAD (325/326). Whereas the number of unnecessary short-time follow up recommendations increased in all case-subgroups with CAD: 40.8/42.9% (group 1), 35.6/38.1% (group 2), 44.7/46.8% (group 3), respectively, the number of recommended biopsies decreased in all subgroups: group 1: 34.7/27.1%; group 2: 47.4/41.5%, group 3: 33.3/22.0%, respectively. CONCLUSION: In this rather small population additional usage of CAD led to a lower rate of unnecessary biopsies. The observed decrease of recommended unnecessary biopsies due to the usage of CAD in the screening group suggests a potential financial benefit by using CAD as diagnostic aid.

Influence of breast lesion size and histologic findings on tumor detection rate of a computer-aided detection system.

PURPOSE: To evaluate associations between histopathologic findings, tumor size, and detection rate of malignant mammographic findings by using a computer-aided detection (CAD) system. MATERIALS AND METHODS: The study included 208 mammographically detected histologically proven malignant breast lesions in 208 women. Findings were 150 masses and 114 microcalcifications; 56 lesions showed both findings; 94 lesions, mass only; and 58 lesions, microcalcification only. CAD was used to evaluate mammograms in two views retrospectively. Also, corresponding histopathologic findings and lesion size were evaluated. CAD marks were considered positive if, on at least one view, they correctly identified the corresponding mammographic lesion location. RESULTS: Ninety percent (135 of 150) of masses and 93.0% (106 of 114) of microcalcifications were marked correctly by the CAD system. Overall tumor detection rate was 93.8% (195 of 208). Size-related detection rate for masses was 83.3% (25 of 30) for lesions up to 10 mm, 100% (45 of 45) for lesions 11-20 mm, 100% (46 of 46) for lesions 21-30 mm, 83.3% (10 of 12) for lesions 31-40 mm, and 52.9% (nine of 17) for lesions larger than 40 mm. Size-related tumor detection rate for microcalcifications was 92.5% (37 of 40) for microcalcifications up to 10 mm, 93.1% (27 of 29) for lesions 11-20 mm, 100% (20 of 20) for lesions 21-30 mm, 87.5% (seven of eight) for lesions 31-40 mm, and 88.2% (15 of 17) for larger microcalcifications. Detection rates for mammographically visible masses (invasive ductal carcinoma, invasive lobular carcinoma, invasive tubular carcinoma, noninvasive cancers, mucinoid cancers, and others) were 92.3% (84 of 91), 89.3% (25 of 28), 75.0% (six of eight), 100% (15 of 15), 33.3% (one of three), and 80.0% (four of five), respectively. Detectability rates for mammographically visible areas suspicious for microcalcifications (invasive ductal carcinoma, invasive lobular carcinoma, invasive tubular carcinoma, and noninvasive cancers) were 92.3% (60 of 65), 100% (eight of eight), 100% (five of five), and 91.9% (31 of 34), respectively. Highest overall detection rates were observed for invasive ductal carcinomas (96.6% [112 of 116]) and noninvasive cancers (92.9% [39 of 42]). CONCLUSION: Highest detection rates were observed for 10-30-mm tumor masses and for invasive ductal carcinomas and noninvasive cancers.

Influence of size and depth on accuracy of electrical impedance scanning.

Cancer cells exhibit altered local dielectric properties which can be assessed using electrical impedance scanning (EIS). The study was aimed at clarifying influence of lesion size and depth on EIS performance. From a series of 387 lesions (129 malignant and 258 benign) from 363 patients being sonographically and/or mammographically evaluated, size and depth information was not available in 112 lesions, size was available in 86 lesions and additional depth information was available in 189 lesions, respectively, while performing EIS. Lesions were either histologically verified or had a follow-up of at least 2 years. One hundred three of 129 malignant lesions and 165 of 258 benign lesions were correctly detected (sensitivity 79.8%, specificity 64.0%, accuracy 71.9%). Sensitivity without knowledge of size and depth was 64.6% (10 of 16 malignant lesions detected). This value increased to 76.2% (32 of 42) with knowledge of the size and further increased to 85.9% with knowledge of size and depth (61 of 71). Specificity values in the three subgroups were almost similar: 64.6 (62 of 96), 65.9 (29 of 44), and 62.7% (74 of 118), respectively. Accuracy rises from 63.6% (without knowledge of size/depth) to 71.1 and 74.3% (with size knowledge and with size and depth knowledge, respectively). Accuracy of EIS improved significantly by including sonographical information about depth and size into the analysis. Ultrasound examination should be performed prior to EIS.

Animal-based model to investigate the minimum tumor size detectable with an electrical impedance scanning technique.

RATIONALE AND OBJECTIVES: The purpose of this study was to determine the minimum tumor size detectable with electrical impedance scanning (EIS) in laboratory animals. MATERIALS AND METHODS: VX2 tumor cells (1 mm3) were implanted bilaterally into the upper leg musculature of five white New Zealand rabbits. EIS and ultrasound (US) were performed before, during, and immediately after implantation and on every 2nd day thereafter until tumors could be visualized with both modalities. This was followed by an extended follow-up regimen until a tumor size of 1 cm3 was reached. Rabbits were anesthetized subcutaneously. RESULTS: Tumors could not be implanted in one rabbit. Neither EIS nor US were performed in one rabbit due to severe skin alterations at the implantation site. No focal increase in conductance was visible before or immediately after tumor injection. The smallest tumor identified with EIS was determined with US to be approximately 8 mm3. The mean tumor size at initial detection was 52 mm3 (determined with EIS). In two cases, the tumor was first seen with US (EIS detection was delayed with a delay of 1 and 2 days, respectively). In all remaining cases, tumors were detected simultaneously with both EIS and US. All tumors were visible with EIS. CONCLUSION: The animal-based model is feasible. VX2 tumors are detectable with EIS. Tumors characterized by a focal spot at EIS could be detected starting at a tumor size of 7.5 mm3.