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    Diagnostic performance of two versions of an artificial intelligence system in interval breast cancer detection
    (Sage Publications Ltd, 2023) Çelik, Levent; Guner, Davut Can; Özcaglayan, Omer; Çubuk, Rahmi; Aribal, Mustafa Erkin
    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.
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    Effects of iron oxide particles on MRI and mammography in breast cancer patients after a sentinel lymph node biopsy with paramagnetic tracers
    (Elsevier Science Inc, 2021) Aribal, Erkin; Çelik, Levent; Yılmaz, Cem; Demirkiran, Cem; Guner, Davut Can
    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 followup 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.