Dana H. Whaley

Dedicated Dual-Head Gamma Imaging for Breast Cancer Screening in Women with Mammographically Dense Breasts

PURPOSE To compare performance characteristics of dedicated dual-head gamma imaging and mammography in screening women with mammographically dense breasts. MATERIALS AND METHODS Asymptomatic women (n = 1007) who had heterogeneously or extremely dense breasts on prior mammograms and additional risk factors provided informed consent to enroll in an institutional review board-approved HIPAA-compliant protocol. Participants underwent mammography and gamma imaging after a 740-mBq (20-mCi) technetium 99m sestamibi injection. Reference standard (more severe cancer diagnosis or 12-month follow-up findings) was available for 936 of 969 eligible participants. Diagnostic yield, sensitivity, specificity, and positive predictive values (PPVs) were determined for mammography, gamma imaging, and both combined. RESULTS Of 936 participants, 11 had cancer (one with mammography only, seven with gamma imaging only, two with both combined, and one with neither). Diagnostic yield was 3.2 per 1000 (95% confidence interval [CI]: 1.1, 9.3) for mammography, 9.6 per 1000 (95% CI: 5.1, 18.2) for gamma imaging, and 10.7 per 1000 (95% CI: 5.8, 19.6) for both (P = .016 vs mammography alone). One participant had a second ipsilateral cancer detected with gamma imaging only. Prevalent screening gamma imaging demonstrated equivalent specificity relative to incident screening mammography (93% [861 of 925] vs 91% [840 of 925], P = .069). Of eight cancers detected with gamma imaging only, six (75%) were invasive (median size, 1.1 cm; range, 0.4-5.1 cm); all were node negative. The ratio of the number of patients with breast cancer per number of screening examinations with abnormal findings was 3% (three of 88) for mammography and 12% (nine of 73) for gamma imaging (P = .01). The number of breast cancers diagnosed per number of biopsies performed was 18% (three of 17) for mammography and 28% (10 of 36) for gamma imaging (P = .36). CONCLUSION Addition of gamma imaging to mammography significantly increased detection of node-negative breast cancer in dense breasts by 7.5 per 1000 women screened (95% CI: 3.6, 15.4). To be clinically important, gamma imaging will need to show equivalent performance at decreased radiation doses.

Molecular breast imaging: use of a dual-head dedicated gamma camera to detect small breast tumors.

OBJECTIVE Molecular breast imaging with a single-head cadmium zinc telluride (CZT) gamma camera has previously been shown to have good sensitivity for the detection of small lesions. To further improve sensitivity, we developed a dual-head molecular breast imaging system using two CZT detectors to simultaneously acquire opposing breast views and reduce lesion-to-detector distance. We determined the incremental gain in sensitivity of molecular breast imaging with dual detectors. SUBJECTS AND METHODS Patients with BI-RADS category 4 or 5 lesions < 2 cm that were identified on mammography or sonography and scheduled for biopsy underwent molecular breast imaging as follows: After injection of 740 MBq of technetium-99m ((99m)Tc) sestamibi, 10-minute craniocaudal and mediolateral oblique views of each breast were acquired. Blinded reviews were performed using images from both detectors 1 and 2 and images from detector 1 only (simulating a single-head system). Lesions were scored on a scale of 1-5; 2 or higher was considered positive. RESULTS Of the 150 patients in the study, 128 cancers were confirmed in 88 patients. Averaging the results from the three blinded readers, the sensitivity of dual-head molecular breast imaging was 90% (115/128), whereas the sensitivity from review of only single-head molecular breast imaging was 80% (102/128). The sensitivity for the detection of cancers < or = 10 mm in diameter was 82% (50/61) for dual-head molecular breast imaging and 68% (41/61) for single-head molecular breast imaging. On average, 13 additional cancers were seen on dual-head images and the tumor uptake score increased by 1 or more in 60% of the identified tumors. CONCLUSION Gains in sensitivity with the dual-head system molecular breast imaging are partially due to increased confidence in lesion detection. Molecular breast imaging can reliably detect breast lesions < 2 cm and dual-head molecular breast imaging can significantly increase sensitivity for subcentimeter lesions.

The Contributions of Breast Density and Common Genetic Variation to Breast Cancer Risk

We evaluated whether a 76-locus polygenic risk score (PRS) and Breast Imaging Reporting and Data System (BI-RADS) breast density were independent risk factors within three studies (1643 case patients, 2397 control patients) using logistic regression models. We incorporated the PRS odds ratio (OR) into the Breast Cancer Surveillance Consortium (BCSC) risk-prediction model while accounting for its attributable risk and compared five-year absolute risk predictions between models using area under the curve (AUC) statistics. All statistical tests were two-sided. BI-RADS density and PRS were independent risk factors across all three studies (P interaction = .23). Relative to those with scattered fibroglandular densities and average PRS (2(nd) quartile), women with extreme density and highest quartile PRS had 2.7-fold (95% confidence interval [CI] = 1.74 to 4.12) increased risk, while those with low density and PRS had reduced risk (OR = 0.30, 95% CI = 0.18 to 0.51). PRS added independent information (P < .001) to the BCSC model and improved discriminatory accuracy from AUC = 0.66 to AUC = 0.69. Although the BCSC-PRS model was well calibrated in case-control data, independent cohort data are needed to test calibration in the general population.

Comparison of Clinical and Automated Breast Density Measurements: Implications for Risk Prediction and Supplemental Screening

Purpose To compare the classification of breast density with two automated methods, Volpara (version 1.5.0; Matakina Technology, Wellington, New Zealand) and Quantra (version 2.0; Hologic, Bedford, Mass), with clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications and to examine associations of these measures with breast cancer risk. Materials and Methods In this study, 1911 patients with breast cancer and 4170 control subjects matched for age, race, examination date, and mammography machine were evaluated. Participants underwent mammography at Mayo Clinic or one of four sites within the San Francisco Mammography Registry between 2006 and 2012 and provided informed consent or a waiver for research, in compliance with HIPAA regulations and institutional review board approval. Digital mammograms were retrieved a mean of 2.1 years (range, 6 months to 6 years) before cancer diagnosis, with the corresponding clinical BI-RADS density classifications, and Volpara and Quantra density estimates were generated. Agreement was assessed with weighted κ statistics among control subjects. Breast cancer associations were evaluated with conditional logistic regression, adjusted for age and body mass index. Odds ratios, C statistics, and 95% confidence intervals (CIs) were estimated. Results Agreement between clinical BI-RADS density classifications and Volpara and Quantra BI-RADS estimates was moderate, with κ values of 0.57 (95% CI: 0.55, 0.59) and 0.46 (95% CI: 0.44, 0.47), respectively. Differences of up to 14% in dense tissue classification were found, with Volpara classifying 51% of women as having dense breasts, Quantra classifying 37%, and clinical BI-RADS assessment used to classify 43%. Clinical and automated measures showed similar breast cancer associations; odds ratios for extremely dense breasts versus scattered fibroglandular densities were 1.8 (95% CI: 1.5, 2.2), 1.9 (95% CI: 1.5, 2.5), and 2.3 (95% CI: 1.9, 2.8) for Volpara, Quantra, and BI-RADS classifications, respectively. Clinical BI-RADS assessment showed better discrimination of case status (C = 0.60; 95% CI: 0.58, 0.61) than did Volpara (C = 0.58; 95% CI: 0.56, 0.59) and Quantra (C = 0.56; 95% CI: 0.54, 0.58) BI-RADS classifications. Conclusion Automated and clinical assessments of breast density are similarly associated with breast cancer risk but differ up to 14% in the classification of women with dense breasts. This could have substantial effects on clinical practice patterns. (©) RSNA, 2015 Online supplemental material is available for this article.

Potential applications of vibro-acoustography in breast imaging.

Vibro-acoustography has gained interest in the recent years as a new modality for medical imaging. This method is based on low-frequency vibrations induced in the object by the radiation force of ultrasound. This paper focuses on potential applications of vibro-acoustography in breast imaging, including detection of microcalcifications, detection of arterial calcifications, and soft tissue imaging. In addition, we will briefly discuss our recent results of in vivo breast vibro-acoustography. Future developments and potential impact of vibro-acoustography in breast imaging are also discussed.

Application of Vibro-acoustography for Detection of Calcified Arteries in Breast Tissue

Objective. The relationship between breast arterial calcification and coronary artery calcification and stenosis is currently an area of active research. It has been suggested in the literature that calcified arteries in the breast may be positively correlated with coronary artery disease. The sensitivity of x‐ray mammography, the main breast imaging method, is reduced in radiologically dense breasts. In a recent study, we showed that vibro‐acoustography, a novel noninvasive imaging technique that is based on the dynamic response of the object to a vibrating force, can detect microcalcifications in the breast regardless of breast density. In this study, we examined the application of vibro‐acoustography in detecting calcified arteries in breast tissue. Methods. Experiments were conducted on 207 postsurgical excised human breast tissue samples. Tissues specimens were imaged with a high‐resolution x‐ray mammography unit. Each sample with confirmed arterial calcification was then scanned by the vibro‐acoustography system, and the resulting image was compared with the corresponding mammogram. We also studied the histologic characteristics of each sample to positively identify the disease and the presence of arterial calcification. Results. Initial mammograms clearly showed 14 calcified arteries. The corresponding vibro‐acoustographic images showed all calcified arteries as fragmented linear structures. The vibro‐acoustographic appearance of the arteries was highly correlated with their distinctive radiographic appearance, which allowed us to identify all the calcified arteries in the vibro‐acoustographic images. Conclusions. Vibro‐acoustography can be used to detect calcified arteries in excised breast tissue. This method may eventually play a role in identifying individuals with an increased risk of coronary artery disease.

Scientific Impact Recognition Award

BACKGROUND Molecular breast imaging (MBI) depicts functional uptake of targeted radiotracers in the breast using dedicated gamma cameras. METHODS MBI studies were performed under several institutional protocols evaluating the use of MBI in screening and diagnosis. RESULTS By using a single-head system, sensitivity for breast cancer detection was 85% (57 of 67) overall and 29% for tumors 5 mm or less in diameter. Sensitivity improved to 91% (117 of 128) overall and 69% for tumors 5 mm or less using a dual-head system. In 650 high-risk patients undergoing breast cancer screening, MBI detected 7 cancers, 5 of which were missed on mammography. In 24 of 149 (16%) breast cancer patients MBI detected additional disease not seen on mammography. The sensitivity of MBI was 88% (83 of 94) for invasive ductal carcinoma, 79% (23 of 29) for invasive lobular carcinoma, and 89% (25 of 28) for ductal carcinoma in situ. CONCLUSIONS MBI can detect invasive ductal carcinoma, ductal carcinoma in situ, and invasive lobular carcinoma. It has a promising role in evaluating the extent of disease and multifocal disease in the breast for surgical treatment planning.

Scientific Impact Recognition Award: Molecular breast imaging: A review of the Mayo Clinic experience

BACKGROUND Molecular breast imaging (MBI) depicts functional uptake of targeted radiotracers in the breast using dedicated gamma cameras. METHODS MBI studies were performed under several institutional protocols evaluating the use of MBI in screening and diagnosis. RESULTS By using a single-head system, sensitivity for breast cancer detection was 85% (57 of 67) overall and 29% for tumors 5 mm or less in diameter. Sensitivity improved to 91% (117 of 128) overall and 69% for tumors 5 mm or less using a dual-head system. In 650 high-risk patients undergoing breast cancer screening, MBI detected 7 cancers, 5 of which were missed on mammography. In 24 of 149 (16%) breast cancer patients MBI detected additional disease not seen on mammography. The sensitivity of MBI was 88% (83 of 94) for invasive ductal carcinoma, 79% (23 of 29) for invasive lobular carcinoma, and 89% (25 of 28) for ductal carcinoma in situ. CONCLUSIONS MBI can detect invasive ductal carcinoma, ductal carcinoma in situ, and invasive lobular carcinoma. It has a promising role in evaluating the extent of disease and multifocal disease in the breast for surgical treatment planning.

Comb-Push Ultrasound Shear Elastography of Breast Masses: Initial Results Show Promise

Purpose or Objective To evaluate the performance of Comb-push Ultrasound Shear Elastography (CUSE) for classification of breast masses. Materials and Methods CUSE is an ultrasound-based quantitative two-dimensional shear wave elasticity imaging technique, which utilizes multiple laterally distributed acoustic radiation force (ARF) beams to simultaneously excite the tissue and induce shear waves. Female patients who were categorized as having suspicious breast masses underwent CUSE evaluations prior to biopsy. An elasticity estimate within the breast mass was obtained from the CUSE shear wave speed map. Elasticity estimates of various types of benign and malignant masses were compared with biopsy results. Results Fifty-four female patients with suspicious breast masses from our ongoing study are presented. Our cohort included 31 malignant and 23 benign breast masses. Our results indicate that the mean shear wave speed was significantly higher in malignant masses (6 ± 1.58 m/s) in comparison to benign masses (3.65 ± 1.36 m/s). Therefore, the stiffness of the mass quantified by the Young’s modulus is significantly higher in malignant masses. According to the receiver operating characteristic curve (ROC), the optimal cut-off value of 83 kPa yields 87.10% sensitivity, 82.61% specificity, and 0.88 for the area under the curve (AUC). Conclusion CUSE has the potential for clinical utility as a quantitative diagnostic imaging tool adjunct to B-mode ultrasound for differentiation of malignant and benign breast masses.

Image features in medical vibro-acoustography: in vitro and in vivo results.

Vibro-acoustography is an imaging method based on audio-frequency harmonic vibrations induced in the object by the radiation force of focused ultrasound. The purpose of this study is to investigate features of vibro-acoustography images and manifestation of various tissue structures and calcifications in such images. Our motivation for this study is to pave the way for further in vitro and in vivo applications of vibro-acoustography. Here, vibro-acoustography images of excised prostate and in vivo breast are presented and compared with images obtained with other modalities. Resulting vibro-acoustography images obtained with a 3 MHz ultrasound transducer and at a vibration frequency of 50-60 kHz show soft tissue structures, tissue borders, and microcalcifications with high contrast, high resolution, and no speckle. It is concluded that vibro-acoustography offers features that may be valuable for diagnostic purposes.