Diagnostic performance of two versions of an artificial intelligence system in interval breast cancer detection.

BACKGROUND: Various versions of artificial intelligence (AI) have been used as a diagnostic tool aid in the diagnosis of breast cancer. One of the most important problems in breast screening progmrams is interval breast cancer (IBC). PURPOSE: To compare the diagnostic performance of Transpara v1.6 and v1.7 in the detection of IBC. MATERIAL AND METHODS: Reports of screening mammograms of a total 2,248,665 of women were evaluated retrospectively. Of 2,129,486 mammograms reported as Breast Imaging Reporting and Data System (BIRADS) 1 and 2, the IBC group consisted of 323 cases who were diagnosed as having cancer on mammography and were correlated with pathology in second mammogram taken >30 days after first mammogram. Four hundred and forty-one were defined as the control group because they did not change over 2 years. Cancer risk scores of both groups were determined from 1 to 10 with Tranpara v1.6 and v1.7. Diagnostic performances of both versions were evaluated by the receiver operating characteristic curve. RESULTS: Cancer risk scores 1 and 10 in v1.7 increased compared to v1.6 (P < 0.001). In all cases, sensitivity for v1.6 was 56.6%, specificity was 90%, and, for v1.7, sensitivity was 65.9% and specificity was 90%, respectively. In all cases, area under the curve values were 0.812 for v1.6 and 0.856 for v1.7, which was higher in v1.7 (P < 0.001). Diagnostic performance of v1.7 was higher than v1.6 at the 7-12-month period (P < 0.001). CONCLUSION: The present study showed that Tranpara v1.7 has a higher specificity, sensitivity and diagnostic performance in IBC determination than v1.6. AI systems can be used in breast screening as a secondary or third reader in screening programs.

Outcomes of high-risk breast lesions diagnosed using image-guided core needle biopsy: results from a multicenter retrospective study.

PURPOSE: The clinical management of high-risk lesions using image-guided biopsy is challenging. This study aimed to evaluate the rates at which such lesions were upgraded to malignancy and identify possible predictive factors for upgrading high-risk lesions. METHODS: This retrospective multicenter analysis included 1.343 patients diagnosed with high-risk lesions using an image-guided core needle or vacuum-assisted biopsy (VAB). Only patients managed using an excisional biopsy or with at least one year of documented radiological follow-up were included. For each, the Breast Imaging Reporting and Data System (BI-RADS) category, number of samples, needle thickness, and lesion size were correlated with malignancy upgrade rates in different histologic subtypes. Pearson's chi-squared test, the Fisher-Freeman-Halton test, and Fisher's exact test were used for the statistical analyses. RESULTS: The overall upgrade rate was 20.6%, with the highest rates in the subtypes of intraductal papilloma (IP) with atypia (44.7%; 55/123), followed by atypical ductal hyperplasia (ADH) (38.4%; 144/375), lobular neoplasia (LN) (12.7%; 7/55), papilloma without atypia (9.4%; 58/611), flat epithelial atypia (FEA) (8.7%; 10/114), and radial scars (RSs) (4.6%; 3/65). There was a significant relationship between the upgrade rate and BI-RADS category, number of samples, and lesion size Lesion size was the most predictive factor for an upgrade in all subtypes. CONCLUSION: ADH and atypical IP showed considerable upgrade rates to malignancy, requiring surgical excision. The LN, IP without atypia, pure FEA, and RS subtypes showed lower malignancy rates when the BI-RADS category was lower and in smaller lesions that had been adequately sampled using VAB. After being discussed in a multidisciplinary meeting, these cases could be managed with follow-up instead of excision.

Effects of iron oxide particles on MRI and mammography in breast cancer patients after a sentinel lymph node biopsy with paramagnetic tracers.

OBJECTIVE: The aim of this study is to evaluate the effect of iron oxide particle deposition on follow-up mammograms and MRI examinations of patients who underwent sentinel lymph node detection with iron oxide particles. MATERIALS AND METHODS: Two hundred and eighteen patients who had sentinel lymph node biopsy (SLNB) with iron oxide particles were evaluated. Follow-up MRI and mammography were available in 36 and 69 cases respectively. MRI examinations were evaluated for ferromagnetic artifacts that were graded as follows: 0 = No artifact, 1 = Focal area, 2 = Segmental and 3 = Regional signal void artifact. Mammography artifacts were evaluated for the presence of dense particles. Pearson's chi-square test was used for statistical analyses and P < 0.05 was accepted as significant. RESULTS: MRI artifact grading was as follows: Grade 0: 11 (30.6%), Grade 1: 14 (38.9%), Grade 2: 3 (8.3%), and Grade 3: 8 (22.2%). The grade of artifacts differed across surgery types (P = 0.019). Grade 3 artifacts were higher in breast conserving cases whereas Grade 0 was more frequent in subcutaneous mastectomy cases. Three out of 69 (4.4%) cases who had follow-up mammography had artifacts due to iron oxide particle accumulation which presented as Grade 3 MRI artifact in all. CONCLUSION: Accumulation of iron oxide particles after SLNB with paramagnetic tracers causes artifacts on follow-up MRI examinations in half of the cases but it is significantly low in mammograms. These artifacts may be confusing in the evaluation of the images. Radiologists must be aware of these tracers and their artifacts whereas patients should be questioned for the type of SLNB before a follow-up examination.