Intra- and Interobserver Reliability of Shear Wave Elastography in Breast Cancer Diagnosis.

OBJECTIVES: Shear wave elastography (SWE) is increasingly used in breast cancer diagnostics. However, large, prospective, multicenter data evaluating the reliability of SWE is missing. We evaluated the intra- and interobserver reliability of SWE in patients with breast lesions categorized as BIRADS 3 or 4. METHODS: We used data of 1288 women at 12 institutions in 7 countries with breast lesions categorized as BIRADS 3 to 4 who underwent conventional B-mode ultrasound and SWE. 1243 (96.5%) women had three repetitive conventional B-mode ultrasounds as well as SWE measurements performed by a board-certified senior physician. 375 of 1288 (29.1%) women received an additional ultrasound examination with B-mode and SWE by a second physician. Intraclass correlation coefficients (ICC) were calculated to examine intra- and interobserver reliability. RESULTS: ICC for intraobserver reliability showed an excellent correlation with ICC >0.9, while interobserver reliability was moderate with ICC of 0.7. There were no clinically significant differences in intraobserver reliability when SWE was performed in lesions categorized as BI-RADS 3 or 4 as well as in histopathologically benign or malignant lesions. CONCLUSION: Reliability of additional SWE was evaluated on a study cohort consisting of 1288 breast lesions categorized as BI-RADS 3 and 4. SWE shows an excellent intraobserver reliability and a moderate interobserver reliability in the evaluation of solid breast masses.

Potential of Lesion-to-Fat Elasticity Ratio Measured by Shear Wave Elastography to Reduce Benign Biopsies in BI-RADS 4 Breast Lesions.

OBJECTIVES: We evaluated whether lesion-to-fat ratio measured by shear wave elastography in patients with Breast Imaging Reporting and Data System (BI-RADS) 3 or 4 lesions has the potential to further refine the assessment of B-mode ultrasound alone in breast cancer diagnostics. METHODS: This was a secondary analysis of an international diagnostic multicenter trial (NCT02638935). Data from 1288 women with breast lesions categorized as BI-RADS 3 and 4a-c by conventional B-mode ultrasound were analyzed, whereby the focus was placed on differentiating lesions categorized as BI-RADS 3 and BI-RADS 4a. All women underwent shear wave elastography and histopathologic evaluation functioning as reference standard. Reduction of benign biopsies as well as the number of missed malignancies after reclassification using lesion-to-fat ratio measured by shear wave elastography were evaluated. RESULTS: Breast cancer was diagnosed in 368 (28.6%) of 1288 lesions. The assessment with conventional B-mode ultrasound resulted in 53.8% (495 of 1288) pathologically benign lesions categorized as BI-RADS 4 and therefore false positives as well as in 1.39% (6 of 431) undetected malignancies categorized as BI-RADS 3. Additional lesion-to-fat ratio in BI-RADS 4a lesions with a cutoff value of 1.85 resulted in 30.11% biopsies of benign lesions which correspond to a reduction of 44.04% of false positives. CONCLUSIONS: Adding lesion-to-fat ratio measured by shear wave elastography to conventional B-mode ultrasound in BI-RADS 4a breast lesions could help reduce the number of benign biopsies by 44.04%. At the same time, however, 1.98% of malignancies were missed, which would still be in line with American College of Radiology BI-RADS 3 definition of <2% of undetected malignancies.

The Potential of Shear Wave Elastography to Reduce Unnecessary Biopsies in Breast Cancer Diagnosis: An International, Diagnostic, Multicenter Trial.

PURPOSE: In this prospective, multicenter trial we evaluated whether additional shear wave elastography (SWE) for patients with BI-RADS 3 or 4 lesions on breast ultrasound could further refine the assessment with B-mode breast ultrasound for breast cancer diagnosis. MATERIALS AND METHODS: We analyzed prospective, multicenter, international data from 1288 women with breast lesions rated by conventional 2 D B-mode ultrasound as BI-RADS 3 to 4c and undergoing 2D-SWE. After reclassification with SWE the proportion of undetected malignancies should be < 2 %. All patients underwent histopathologic evaluation (reference standard). RESULTS: Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6 %). The assessment with B-mode breast ultrasound resulted in 1.39 % (6 of 431) undetected malignancies (malignant lesions in BI-RADS 3) and 53.80 % (495 of 920) unnecessary biopsies (biopsies in benign lesions). Re-classifying BI-RADS 4a patients with a SWE cutoff of 2.55 m/s resulted in 1.98 % (11 of 556) undetected malignancies and a reduction of 24.24 % (375 vs. 495) of unnecessary biopsies. CONCLUSION: A SWE value below 2.55 m/s for BI-RADS 4a lesions could be used to downstage these lesions to follow-up, and therefore reduce the number of unnecessary biopsies by 24.24 %. However, this would come at the expense of some additionally missed cancers compared to B-mode breast ultrasound (rate of undetected malignancies 1.98 %, 11 of 556, versus 1.39 %, 6 of 431) which would, however, still be in line with the ACR BI-RADS 3 definition (< 2 % of undetected malignancies).

Intelligent multi-modal shear wave elastography to reduce unnecessary biopsies in breast cancer diagnosis (INSPiRED 002): a retrospective, international, multicentre analysis.

BACKGROUND: Breast ultrasound identifies additional carcinomas not detected in mammography but has a higher rate of false-positive findings. We evaluated whether use of intelligent multi-modal shear wave elastography (SWE) can reduce the number of unnecessary biopsies without impairing the breast cancer detection rate. METHODS: We trained, tested, and validated machine learning algorithms using SWE, clinical, and patient information to classify breast masses. We used data from 857 women who underwent B-mode breast ultrasound, SWE, and subsequent histopathologic evaluation at 12 study sites in seven countries from 2016 to 2019. Algorithms were trained and tested on data from 11 of the 12 sites and externally validated using the additional site's data. We compared findings to the histopathologic evaluation and compared the diagnostic performance between B-mode breast ultrasound, traditional SWE, and intelligent multi-modal SWE. RESULTS: In the external validation set (n = 285), intelligent multi-modal SWE showed a sensitivity of 100% (95% CI, 97.1-100%, 126 of 126), a specificity of 50.3% (95% CI, 42.3-58.3%, 80 of 159), and an area under the curve of 0.93 (95% CI, 0.90-0.96). Diagnostic performance was significantly higher compared to traditional SWE and B-mode breast ultrasound (P < 0.001). Unlike traditional SWE, positive-predictive values of intelligent multi-modal SWE were significantly higher compared to B-mode breast ultrasound. Unnecessary biopsies were reduced by 50.3% (79 versus 159, P < 0.001) without missing cancer compared to B-mode ultrasound. CONCLUSION: The majority of unnecessary breast biopsies might be safely avoided by using intelligent multi-modal SWE. These results may be helpful to reduce diagnostic burden for patients, providers, and healthcare systems.

The importance of multi-modal imaging and clinical information for humans and AI-based algorithms to classify breast masses (INSPiRED 003): an international, multicenter analysis.

OBJECTIVES: AI-based algorithms for medical image analysis showed comparable performance to human image readers. However, in practice, diagnoses are made using multiple imaging modalities alongside other data sources. We determined the importance of this multi-modal information and compared the diagnostic performance of routine breast cancer diagnosis to breast ultrasound interpretations by humans or AI-based algorithms. METHODS: Patients were recruited as part of a multicenter trial (NCT02638935). The trial enrolled 1288 women undergoing routine breast cancer diagnosis (multi-modal imaging, demographic, and clinical information). Three physicians specialized in ultrasound diagnosis performed a second read of all ultrasound images. We used data from 11 of 12 study sites to develop two machine learning (ML) algorithms using unimodal information (ultrasound features generated by the ultrasound experts) to classify breast masses which were validated on the remaining study site. The same ML algorithms were subsequently developed and validated on multi-modal information (clinical and demographic information plus ultrasound features). We assessed performance using area under the curve (AUC). RESULTS: Of 1288 breast masses, 368 (28.6%) were histopathologically malignant. In the external validation set (n = 373), the performance of the two unimodal ultrasound ML algorithms (AUC 0.83 and 0.82) was commensurate with performance of the human ultrasound experts (AUC 0.82 to 0.84; p for all comparisons > 0.05). The multi-modal ultrasound ML algorithms performed significantly better (AUC 0.90 and 0.89) but were statistically inferior to routine breast cancer diagnosis (AUC 0.95, p for all comparisons ≤ 0.05). CONCLUSIONS: The performance of humans and AI-based algorithms improves with multi-modal information. KEY POINTS: • The performance of humans and AI-based algorithms improves with multi-modal information. • Multimodal AI-based algorithms do not necessarily outperform expert humans. • Unimodal AI-based algorithms do not represent optimal performance to classify breast masses.

The potential of combined shear wave and strain elastography to reduce unnecessary biopsies in breast cancer diagnostics - An international, multicentre trial.

BACKGROUND: Shear wave elastography (SWE) and strain elastography (SE) have shown promising potential in breast cancer diagnostics by evaluating the stiffness of a lesion. Combining these two techniques could further improve the diagnostic performance. We aimed to exploratorily define the cut-offs at which adding combined SWE and SE to B-mode breast ultrasound could help reclassify Breast Imaging Reporting and Data System (BI-RADS) 3-4 lesions to reduce the number of unnecessary breast biopsies. METHODS: We report the secondary results of a prospective, multicentre, international trial (NCT02638935). The trial enrolled 1288 women with BI-RADS 3 to 4c breast masses on conventional B-mode breast ultrasound. All patients underwent SWE and SE (index test) and histopathologic evaluation (reference standard). Reduction of unnecessary biopsies (biopsies in benign lesions) and missed malignancies after recategorising with SWE and SE were the outcome measures. RESULTS: On performing histopathologic evaluation, 368 of 1288 breast masses were malignant. Following the routine B-mode breast ultrasound assessment, 53.80% (495 of 920 patients) underwent an unnecessary biopsy. After recategorising BI-RADS 4a lesions (SWE cut-off ≥3.70 m/s, SE cut-off ≥1.0), 34.78% (320 of 920 patients) underwent an unnecessary biopsy corresponding to a 35.35% (320 versus 495) reduction of unnecessary biopsies. Malignancies in the new BI-RADS 3 cohort were missed in 1.96% (12 of 612 patients). CONCLUSION: Adding combined SWE and SE to routine B-mode breast ultrasound to recategorise BI-RADS 4a patients could help reduce the number of unnecessary biopsies in breast diagnostics by about 35% while keeping the rate of undetected malignancies below the 2% ACR BI-RADS 3 definition.

Serous Borderline Tumor in Transgender Female-to-Male Individuals: A Case Report of Androgen Receptor-Positive Ovarian Cancer.

Ovarian cancer is the most fatal gynecologic malignancy. The incidence of ovarian cancer among female-to-male transsexuals receiving treatment with testosterone is unknown, and few cases have been reported in the literature. We report a recent case in our institution, a 23-year-old female-to-male transsexual patient who received testosterone supplementation. The patient underwent a pelvic magnetic resonance imaging to study an ovarian complex cyst that revealed the presence of a bilateral ovarian tumor with imaging features of borderline serous tumor. These masses were surgically removed and the pathology report confirmed the diagnosis associated with noninvasive peritoneal implants and the presence of numerous androgen receptors in the tumor cells. Although there is still insufficient data to validate a direct correlation between hormonotherapy and ovarian cancer in these patients, this case may reinforce previous reports on this association and highlights the relevance of radiological follow-up and bilateral salpingo-oophorectomy as part of gender reassignment surgery.

Imaging Findings of Metaplastic Carcinoma of the Breast with Pathologic Correlation.

OBJECTIVES: To review the imaging findings of a series of cases of metaplastic carcinoma of the breast, a rare and aggressive form of breast cancer with variable imaging features. MATERIALS AND METHODS: Retrospective review of multimodality imaging features of eleven cases of metaplastic carcinoma of the breast retrieved from a single hospital institution database. Clinical and pathologic data were also documented. RESULTS: The median age of presentation was 65 years. Four cases had axillary lymphadenopathies, and two had distant metastases. An oval mass was the most common sonographic finding (7/11; 64%). Lesions displayed circumscribed/partially circumscribed margins (6/11; 55%) or non-circumscribed margins (5/11; 45%). Most lesions had a heterogeneous echo structure (9/11; 82%) and posterior acoustic enhancement (6/11; 55%). In nine patients, mammographies were available. An oval dense mass was the most common mammographic finding (5/9; 56%). The majority of cases had non-circumscribed margins (6/9; 67%), and nearly half displayed calcifications (4/9; 44%). CONCLUSIONS: Mammographic findings were not different from the usual features of more prevalent types of breast cancer, though the majority of metaplastic carcinoma of the breast showed possible distinctive sonographic features, such as circumscribed margins or complex echogenicity, reflecting the histologic background.

Diagnostic Value of ARFI (Acoustic Radiation Force Impulse) in Differentiating Benign From Malignant Breast Lesions.

RATIONALE AND OBJECTIVES: The aim of this study was to correlate acoustic radiation force impulse (ARFI) imaging velocities with the pathology results and to evaluate the ability of ARFI in distinguishing benign from malignant breast lesions. MATERIALS AND METHODS: B-mode ultrasonography (US) and ARFI were performed in patients with previously diagnosed and selected breast lesions for biopsy. Shear wave velocity (SWV) was measured inside lesions and in the surrounding parenchyma (m/s). SWV measurements as well as lesion-to-parenchyma ratio (LPR) were compared between benign and malignant lesions, and receiver operating characteristic (ROC) curves were plotted. Two blinded readers independently classified the lesions as benign or malignant in two separate reading sessions, one using B-mode US alone and the other using a combined set of B-mode US and ARFI. RESULTS: Eighty-one patients with a total of 92 breast lesions were included (57 benign and 35 malignant nodules). SWV inside lesions were significantly higher for malignant neoplasms compared to benign (medians of 9.1 m/s vs 3.5 m/s; P < 0.001). LPR was also significantly higher for malignant lesions (3.0 vs 1.4; P < 0.001). Parenchyma SWV had no differences between groups (P = 0.071). ROC curves showed a significant discriminative power for lesion SWV (area under the curve [AUC] = 0.980; P < 0.001) and LPR (AUC = 0.954; P < 0.001). For lesion measures, a cutoff of 6.593 m/s was obtained, with sensitivity and specificity of 88.6% and 96.5%, respectively. CONCLUSIONS: ARFI provides quantitative elasticity measurements, adding valuable complementary information to B-mode ultrasound, that can potentially help in breast lesion characterization and assisting the decision for biopsy recommendations.