False-positive incidental lesions detected on contrast-enhanced breast MRI: clinical and imaging features

Contrast-enhanced mammography in the management of breast architectural distortions and avoidance of unnecessary biopsies

BACKGROUND

To assess contrast-enhanced mammography (CEM) in the management of BI-RADS3 breast architectural distortions (AD) in digital breast tomosynthesis (DBT).

METHODS

We retrospectively reviewed 328 women with 332 ADs detected on DBT between 2017 and 2021 and selected those classified as BI-RADS3 receiving CEM as problem-solving. In CEM recombined images, we evaluated AD's contrast enhancement (CE) according to its presence/absence, type, and size. AD with enhancement underwent imaging-guided biopsy while AD without enhancement follow-up or biopsy if detected in high/intermediate-risk women.

RESULTS

AD with enhancement were 174 (52.4%): 72 (41.4%) were malignant lesions, 102 (59.6%) false positive results: 28 (16%) B3 lesions, and 74 (42.5%) benign lesions. AD without enhancement were 158 (47.6%): 26 (16.5%) were subjected to biopsy (1 malignant and 25 benign) while the other 132 cases were sent to imaging follow-up, still negative after two years. CEM's sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and accuracy were 98.63%, 60.62%, 41.38%, 99.37%, and 68.98%. The AUC determined by ROC was 0.796 (95% CI, 0.749-0.844).

CONCLUSION

CEM has high sensitivity and NPV in evaluating BI-RADS3 AD and can be a complementary tool in assessing AD, avoiding unnecessary biopsies without compromising cancer detection.

MRI-visualized T2 hyperintense breast lesions: identifying clinical and imaging factors linked to malignant biopsy outcomes

PURPOSE

To determine the malignancy rate for MRI-guided breast biopsies performed for T2 hyperintense breast lesions and to assess additional clinical and MRI characteristics that can predict benign and malignant outcomes.

METHODS

A retrospective chart review of consecutive MRI-guided breast biopsies performed in two tertiary hospitals was conducted over two years. Biopsies performed for T2 hyperintense lesions were selected, and further lesion imaging characteristics and patient risk factors were collected. Univariate and multivariate modeling regression were used to determine additional imaging and patient factors associated with malignant outcomes for biopsies of T2 hyperintense lesions.

RESULTS

Out of 369 MRI-guided breast biopsies, 100 (27%) were performed for T2 hyperintense lesions. Two biopsy-proven benign lesions were excluded as the patient was lost on follow-up. With a study cohort of 98 lesions, the final pathology results were benign for 80 (80%) of these lesions, while 18 (18%) were malignant. Using multivariate logistic modeling, patient age > 50 (OR 5.99 (1.49, 24.08 95% CI), p < 0.05) and lesion size > 3 cm (OR 5.54 (1.54-18.7), p < 0.01) were found to be important predictors of malignant outcomes for MRI biopsies performed for T2 hyperintense lesions.

CONCLUSION

Our study observed a high malignancy rate, challenging the assumption that T2 hyperintensity can be considered a benign imaging characteristic for otherwise suspicious MRI-detected lesions. Decision-making regarding tissue sampling should be made based on a thorough evaluation of more reliable additional demographic and imaging factors, including patient age and lesion size.

How Does Diagnostic Accuracy Evolve with Increased Breast MRI Experience?

Introduction: Our institution is part of a provincial program providing annual breast MRI screenings to high-risk women. We assessed how MRI experience, background parenchymal enhancement (BPE), and the amount of fibroglandular tissue (FGT) affect the biopsy-proven predictive value (PPV3) and accuracy for detecting suspicious MRI findings. Methods: From all high-risk screening breast MRIs conducted between 1 July 2011 and 30 June 2020, we reviewed all BI-RADS 4/5 observations with pathological tissue diagnoses. Overall and annual PPV3s were computed. Radiologists with fewer than ten observations were excluded from performance analyses. PPV3s were computed for each radiologist. We assessed how MRI experience, BPE, and FGT impacted diagnostic accuracy using logistic regression analyses, defining positive cases as malignancies alone (definition A) or malignant or high-risk lesions (definition B). Findings: There were 536 BI-RADS 4/5 observations with tissue diagnoses, including 77 malignant and 51 high-risk lesions. A total of 516 observations were included in the radiologist performance analyses. The average radiologist's PPV3 was 16 ± 6% (definition A) and 25 ± 8% (definition B). MRI experience in years correlated significantly with positive cases (definition B, OR = 1.05, p = 0.03), independent of BPE or FGT. Diagnostic accuracy improved exponentially with increased MRI experience (definition B, OR of 1.27 and 1.61 for 5 and 10 years, respectively, p = 0.03 for both). Lower levels of BPE significantly correlated with increased odds of findings being malignant, independent of FGT and MRI experience. Summary: More extensive MRI reading experience improves radiologists' diagnostic accuracy for high-risk or malignant lesions, even in MRI studies with increased BPE.