Optoacoustic Imaging and Gray-Scale US Features of Breast Cancers: Correlation with Molecular Subtypes.

Background Optoacoustic imaging can assess tumor hypoxia coregistered with US gray-scale images. The combination of optoacoustic imaging and US may have a role in distinguishing breast cancer molecular subtypes. Purpose To investigate whether optoacoustic US feature scores correlate with breast cancer molecular subtypes. Materials and Methods A total of 1972 women (with a total of 2055 breast masses) underwent prebiopsy optoacoustic US in a prospective multi-institutional study between December 2012 and September 2015. Seven readers blinded to pathologic diagnosis scored gray-scale US and optoacoustic US features of the known cancers. Optoacoustic US features within (internal) and outside of the tumor boundary (external) were scored. Immunohistochemistry findings were obtained from pathology reports. Multinomial logistic regression analysis was used to fit the US scores, adding optoacoustic US features to the model to investigate the incremental benefit of each feature. Kruskal-Wallis tests were used to analyze the relationship between molecular subtypes and feature scores. Results Among 653 invasive cancers identified in 629 women, a total of 532 cancers in 519 women, all of which had molecular markers available, were included in the analysis. Mean age ± standard deviation was 57.9 years ± 12.6. Mean total external optoacoustic US feature scores of luminal (A and B) breast cancers were higher (9.9 vs 8.8; P < .05) and total internal scores were lower (6.8 vs 7.7; P < .001) than those of triple-negative and human epidermal growth factor receptor 2-positive (HER2+) cancers. A multinomial logistic regression model showed that optoacoustic internal vessel (odds ratio [OR], 0.6; 95% confidence interval [CI]: 0.5, 0.8; P = .002), optoacoustic internal blush (OR, 0.7; 95% CI: 0.5, 0.9; P = .02), and optoacoustic internal hemoglobin (OR, 0.6; 95% CI: 0.5, 0.8; P = .001) were associated with classification of luminal versus triple-negative and HER2+ cancer subtypes. Conclusion Combined optoacoustic US imaging and gray-scale US features may help distinguish luminal breast cancers from triple-negative and human epidermal growth factor receptor 2-positive cancers. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Mann in this issue.

Analysis of utilization patterns and associated costs of the breast imaging and diagnostic procedures after screening mammography.

BACKGROUND: Little data exist on real-world patterns and associated costs of downstream breast diagnostic procedures following an abnormal screening mammography or clinical exam. OBJECTIVES: To analyze the utilization patterns in real-world clinical settings for breast imaging and diagnostic procedures, including the frequency and volume of patients and procedures, procedure sequencing, and associated health care expenditures. MATERIALS AND METHODS: Using medical claims from 2011 to 2015 MarketScan Commercial and Medicare Databases, adult females with breast imaging/diagnostic procedures (diagnostic mammography, ultrasound, molecular breast imaging, tomosynthesis, magnetic resonance imaging, or biopsy) other than screening mammography were selected. Continuous health plan coverage without breast diagnostic procedures was required for ≥13 months before the first found breast diagnostic procedure (index event), with a 13-month post-index follow-up period. Key outcomes included diagnostic procedure volumes, sequences, and payments. Results reported descriptively were projected to provide US national patient and procedure volumes. RESULTS: The final sample of 875,526 patients was nationally projected to 12,394,432 patients annually receiving 8,732,909 diagnostic mammograms (53.3% of patients), 6,987,399 breast ultrasounds (42.4% of patients), and 1,585,856 biopsies (10.3% of patients). Following initial diagnostic procedures, 49.4% had second procedures, 20.1% followed with third procedures, and 10.0% had a fourth procedure. Mean (SD) costs for diagnostic mammograms of US$349 ($493), ultrasounds US$132 ($134), and biopsies US$1,938 ($2,343) contributed US$3.05 billion, US$0.92 billion, and US$3.07 billion, respectively, to annual diagnostic breast expenditures estimated at US$7.91 billion. CONCLUSION: The volume and expense of additional breast diagnostic testing, estimated at US$7.91 billion annually, underscores the need for technological improvements in the breast diagnostic landscape.

Exploring the Negative Likelihood Ratio and How It Can Be Used to Minimize False-Positives in Breast Imaging.

OBJECTIVE: This article describes the definition and proposed utilization of negative likelihood ratios (NLRs) as statistical parameters in breast imaging. Examples with calculations are provided using BI-RADS category 4 subcategories. CONCLUSION: By auditing individual performance early and often against American College of Radiology benchmark positive predictive value ranges for the BI-RADS category 4 subcategories, and by fully understanding NLRs and their application in breast imaging, radiologists can minimize false-positive findings and unnecessary biopsies.

ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee.

Thyroid nodules are a frequent finding on neck sonography. Most nodules are benign; therefore, many nodules are biopsied to identify the small number that are malignant or require surgery for a definitive diagnosis. Since 2009, many professional societies and investigators have proposed ultrasound-based risk stratification systems to identify nodules that warrant biopsy or sonographic follow-up. Because some of these systems were founded on the BI-RADS® classification that is widely used in breast imaging, their authors chose to apply the acronym TI-RADS, for Thyroid Imaging, Reporting and Data System. In 2012, the ACR convened committees to (1) provide recommendations for reporting incidental thyroid nodules, (2) develop a set of standard terms (lexicon) for ultrasound reporting, and (3) propose a TI-RADS on the basis of the lexicon. The committees published the results of the first two efforts in 2015. In this article, the authors present the ACR TI-RADS Committee's recommendations, which provide guidance regarding management of thyroid nodules on the basis of their ultrasound appearance. The authors also describe the committee's future directions.

Ultrasound positive predictive values by BI-RADS categories 3-5 for solid masses: An independent reader study.

OBJECTIVE: We assessed multiple readers' positive predictive values (PPVs) for ACR BI-RADS 3, 4a, 4b, 4c and 5 masses on ultrasound (US) pre- and post-proposed guidelines. METHODS: This retrospective, IRB-approved study included four American and four non-American readers who assigned BI-RADS categories for US images of 374 biopsy-proved masses. Readers were offered guidelines and re-classified the masses. We assessed readers' abilities to achieve ACR benchmarks BI-RADS categories pre- and post-guidelines. RESULTS: PPVs increased with BI-RADS category. The PPVs pre- and post-guidelines were 6.0% and 4.4% for category 3, 27.3% and 30.5% for category 4a, 49.9% and 51.5% for category 4b, 69.0% and 67.4% for category 4c, and 79.3% and 80.1% for category 5. Readers achieved the PPV benchmark for category 4c, but not for categories 3, 4a, 4b and 5, with no significant improvement after guidelines. Regular BI-RADS 4 subcategory users missed benchmarks by less than non-regular users. CONCLUSION: Pre- and post-guidelines, readers' PPVs increased with BI-RADS categories, ACR PPV benchmarks were achieved in category 4c, missed in other categories, especially in the critical 4a subcategory, where the PPV was too high. BI-RADS 4 subcategory users performed better than non-users. KEY POINTS: • Readers failed to achieve benchmarks for BI-RADS 4 subcategories, especially 4a. • USA and Brazilian readers performed similarly in ACR BI-RADS 4 subcategorization. • Proposed guidelines did not improve overall, USA or Brazilian reader performance. • Regularly BI-RADS 4 subcategory users performed better than did non-users. • US features distinguished between benign and malignant, not BI-RADS 4 subcategories.

Thyroid Ultrasound Reporting Lexicon: White Paper of the ACR Thyroid Imaging, Reporting and Data System (TIRADS) Committee.

Ultrasound is the most commonly used imaging technique for the evaluation of thyroid nodules. Sonographic findings are often not specific, and definitive diagnosis is usually made through fine-needle aspiration biopsy or even surgery. In reviewing the literature, terms used to describe nodules are often poorly defined and inconsistently applied. Several authors have recently described a standardized risk stratification system called the Thyroid Imaging, Reporting and Data System (TIRADS), modeled on the BI-RADS system for breast imaging. However, most of these TIRADS classifications have come from individual institutions, and none has been widely adopted in the United States. Under the auspices of the ACR, a committee was organized to develop TIRADS. The eventual goal is to provide practitioners with evidence-based recommendations for the management of thyroid nodules on the basis of a set of well-defined sonographic features or terms that can be applied to every lesion. Terms were chosen on the basis of demonstration of consistency with regard to performance in the diagnosis of thyroid cancer or, conversely, classifying a nodule as benign and avoiding follow-up. The initial portion of this project was aimed at standardizing the diagnostic approach to thyroid nodules with regard to terminology through the development of a lexicon. This white paper describes the consensus process and the resultant lexicon.

Shear-wave elastography improves the specificity of breast US: the BE1 multinational study of 939 masses.

PURPOSE: To determine whether adding shear-wave (SW) elastographic features could improve accuracy of ultrasonographic (US) assessment of breast masses. MATERIALS AND METHODS: From September 2008 to September 2010, 958 women consented to repeat standard breast US supplemented by quantitative SW elastographic examination in this prospective multicenter institutional review board-approved, HIPAA-compliant protocol. B-mode Breast Imaging Reporting and Data System (BI-RADS) features and assessments were recorded. SW elastographic evaluation (mean, maximum, and minimum elasticity of stiffest portion of mass and surrounding tissue; lesion-to-fat elasticity ratio; ratio of SW elastographic-to-B-mode lesion diameter or area; SW elastographic lesion shape and homogeneity) was performed. Qualitative color SW elastographic stiffness was assessed independently. Nine hundred thirty-nine masses were analyzable; 102 BI-RADS category 2 masses were assumed to be benign; reference standard was available for 837 category 3 or higher lesions. Considering BI-RADS category 4a or higher as test positive for malignancy, effect of SW elastographic features on area under the receiver operating characteristic curve (AUC), sensitivity, and specificity after reclassifying category 3 and 4a masses was determined. RESULTS: Median participant age was 50 years; 289 of 939 (30.8%) masses were malignant (median mass size, 12 mm). B-mode BI-RADS AUC was 0.950; eight of 303 (2.6%) BI-RADS category 3 masses, 18 of 193 (9.3%) category 4a lesions, 41 of 97 (42%) category 4b lesions, 42 of 57 (74%) category 4c lesions, and 180 of 187 (96.3%) category 5 lesions were malignant. By using visual color stiffness to selectively upgrade category 3 and lack of stiffness to downgrade category 4a masses, specificity improved from 61.1% (397 of 650) to 78.5% (510 of 650) (P<.001); AUC increased to 0.962 (P=.005). Oval shape on SW elastographic images and quantitative maximum elasticity of 80 kPa (5.2 m/sec) or less improved specificity (69.4% [451 of 650] and 77.4% [503 of 650], P<.001 for both), without significant improvement in sensitivity or AUC. CONCLUSION: Adding SW elastographic features to BI-RADS feature analysis improved specificity of breast US mass assessment without loss of sensitivity.