Impact of contrast-enhanced mammography in surgical management of breast cancers for women with dense breasts: a dual-center, multi-disciplinary study in Asia.

OBJECTIVE: To evaluate the impact of pre-operative contrast-enhanced mammography (CEM) in breast cancer patients with dense breasts. METHODS: We conducted a retrospective review of 232 histologically proven breast cancers in 200 women (mean age: 53.4 years ± 10.2) who underwent pre-surgical CEM imaging across two Asian institutions (Singapore and Taiwan). Majority (95.5%) of patients had dense breast tissue (BI-RADS category C or D). Surgical decision was recorded in a simulated blinded multi-disciplinary team setting on two separate scenarios: (i) pre-CEM setting with standard imaging, and clinical and histopathological results; and (ii) post-CEM setting with new imaging and corresponding histological findings from CEM. Alterations in surgical plan (if any) because of CEM imaging were recorded. Predictors CEM of patients who benefitted from surgical plan alterations were evaluated using logistic regression. RESULTS: CEM resulted in altered surgical plans in 36 (18%) of 200 patients in this study. CEM discovered clinically significant larger tumor size or extent in 24 (12%) patients and additional tumors in 12 (6%) patients. CEM also detected additional benign/false-positive lesions in 13 (6.5%) of the 200 patients. Significant predictors of patients who benefitted from surgical alterations found on multivariate analysis were pre-CEM surgical decision for upfront breast conservation (OR, 7.7; 95% CI, 1.9-32.1; p = 0.005), architectural distortion on mammograms (OR, 7.6; 95% CI, 1.3-42.9; p = .022), and tumor size of ≥ 1.5 cm (OR, 1.5; 95% CI, 1.0-2.2; p = .034). CONCLUSION: CEM is an effective imaging technique for pre-surgical planning for Asian breast cancer patients with dense breasts. KEY POINTS: • CEM significantly altered surgical plans in 18% (nearly 1 in 5) of this Asian study cohort with dense breasts. • Significant patient and imaging predictors for surgical plan alteration include (i) patients considered for upfront breast-conserving surgery; (ii) architectural distortion lesions; and (iii) tumor size of ≥ 1.5 cm. • Additional false-positive/benign lesions detected through CEM were uncommon, affecting only 6.5% of the study cohort.

Ultrasound Guided Optoacoustic Tomography in Assessment of Tumor Margins for Lumpectomies.

PURPOSE: To determine the accuracy of a handheld ultrasound-guided optoacoustic tomography (US-OT) probe developed for human deep-tissue imaging in ex vivo assessment of tumor margins postlumpectomy. METHODS: A custom-built two-dimensional (2D) US-OT-handheld probe was used to scan 15 lumpectomy breast specimens. Optoacoustic signals acquired at multiple wavelengths between 700 and 1100 nm were reconstructed using model linear algorithm, followed by spectral unmixing for lipid and deoxyhemoglobin (Hb). Distribution maps of lipid and Hb on the anterior, posterior, superior, inferior, medial, and lateral margins of the specimens were inspected for margin involvement, and results were correlated with histopathologic findings. The agreement in tumor margin assessment between US-OT and histopathology was determined using the Bland-Altman plot. Accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of margin assessment using US-OT were calculated. RESULTS: Ninety margins (6 × 15 specimens) were assessed. The US-OT probe resolved blood vessels and lipid up to a depth of 6 mm. Negative and positive margins were discriminated by marked differences in the distribution patterns of lipid and Hb. US-OT assessments were concordant with histopathologic findings in 87 of 89 margins assessed (one margin was uninterpretable and excluded), with diagnostic accuracy of 97.9% (kappa = 0.79). The sensitivity, specificity, PPV, and NPV were 100% (4/4), 97.6% (83/85), 66.7% (4/6), and 100% (83/83), respectively. CONCLUSION: US-OT was capable of providing distribution maps of lipid and Hb in lumpectomy specimens that predicted tumor margins with high sensitivity and specificity, making it a potential tool for intraoperative tumor margin assessment.