Diagnostic Performance of an Artificial Intelligence System in Breast Ultrasound.

OBJECTIVES: We study the performance of an artificial intelligence (AI) program designed to assist radiologists in the diagnosis of breast cancer, relative to measures obtained from conventional readings by radiologists. METHODS: A total of 10 radiologists read a curated, anonymized group of 299 breast ultrasound images that contained at least one suspicious lesion and for which a final diagnosis was independently determined. Separately, the AI program was initialized by a lead radiologist and the computed results compared against those of the radiologists. RESULTS: The AI program's diagnoses of breast lesions had concordance with the 10 radiologists' readings across a number of BI-RADS descriptors. The sensitivity, specificity, and accuracy of the AI program's diagnosis of benign versus malignant was above 0.8, in agreement with the highest performing radiologists and commensurate with recent studies. CONCLUSION: The trained AI program can contribute to accuracy of breast cancer diagnoses with ultrasound.

Dedicated breast CT: state of the art-Part I. Historical evolution and technical aspects.

Dedicated breast CT is an emerging 3D isotropic imaging technology for breast, which overcomes the limitations of 2D compression mammography and limited angle tomosynthesis while providing some of the advantages of magnetic resonance imaging. This first installment in a 2-part review describes the evolution of dedicated breast CT beginning with a historical perspective and progressing to the present day. Moreover, it provides an overview of state-of-the-art technology. Particular emphasis is placed on technical limitations in scan protocol, radiation dose, breast coverage, patient comfort, and image artifact. Proposed methods of how to address these technical challenges are also discussed. KEY POINTS: • Advantages of breast CT include no tissue overlap, improved patient comfort, rapid acquisition, and concurrent assessment of microcalcifications and contrast enhancement. • Current clinical and prototype dedicated breast CT systems differ in acquisition modes, imaging techniques, and detector types. • There are still details to be decided regarding breast CT techniques, such as scan protocol, radiation dose, breast coverage, patient comfort, and image artifact.

Dedicated breast CT: state of the art-Part II. Clinical application and future outlook.

Dedicated breast CT is being increasingly used for breast imaging. This technique provides images with no compression, removal of tissue overlap, rapid acquisition, and available simultaneous assessment of microcalcifications and contrast enhancement. In this second installment in a 2-part review, the current status of clinical applications and ongoing efforts to develop new imaging systems are discussed, with particular emphasis on how to achieve optimized practice including lesion detection and characterization, response to therapy monitoring, density assessment, intervention, and implant evaluation. The potential for future screening with breast CT is also addressed. KEY POINTS: • Dedicated breast CT is an emerging modality with enormous potential in the future of breast imaging by addressing numerous clinical needs from diagnosis to treatment. • Breast CT shows either noninferiority or superiority with mammography and numerical comparability to MRI after contrast administration in diagnostic statistics, demonstrates excellent performance in lesion characterization, density assessment, and intervention, and exhibits promise in implant evaluation, while potential application to breast cancer screening is still controversial. • New imaging modalities such as phase-contrast breast CT, spectral breast CT, and hybrid imaging are in the progress of R & D.

Improving breast cancer diagnosis by incorporating raw ultrasound parameters into machine learning.

The improved diagnostic accuracy of ultrasound breast examinations remains an important goal. In this study, we propose a biophysical feature-based machine learning method for breast cancer detection to improve the performance beyond a benchmark deep learning algorithm and to furthermore provide a color overlay visual map of the probability of malignancy within a lesion. This overall framework is termed disease-specific imaging. Previously, 150 breast lesions were segmented and classified utilizing a modified fully convolutional network and a modified GoogLeNet, respectively. In this study multiparametric analysis was performed within the contoured lesions. Features were extracted from ultrasound radiofrequency, envelope, and log-compressed data based on biophysical and morphological models. The support vector machine with a Gaussian kernel constructed a nonlinear hyperplane, and we calculated the distance between the hyperplane and each feature's data point in multiparametric space. The distance can quantitatively assess a lesion and suggest the probability of malignancy that is color-coded and overlaid onto B-mode images. Training and evaluation were performed on in vivo patient data. The overall accuracy for the most common types and sizes of breast lesions in our study exceeded 98.0% for classification and 0.98 for an area under the receiver operating characteristic curve, which is more precise than the performance of radiologists and a deep learning system. Further, the correlation between the probability and Breast Imaging Reporting and Data System enables a quantitative guideline to predict breast cancer. Therefore, we anticipate that the proposed framework can help radiologists achieve more accurate and convenient breast cancer classification and detection.

Cone-Beam Breast Computed Tomography: Time for a New Paradigm in Breast Imaging.

It is time to reconsider how we image the breast. Although the breast is a 3D structure, we have traditionally used 2D mammography to perform screening and diagnostic imaging. Mammography has been continuously modified and improved, most recently with tomosynthesis and contrast mammography, but it is still using modifications of compression 2D mammography. It is time to consider 3D imaging for this 3D structure. Cone-beam breast computed tomography (CBBCT) is a revolutionary modality that will assist in overcoming the limitations of current imaging for dense breast tissue and overlapping structures. It also allows easy administration of contrast material for functional imaging. With a radiation dose on par with diagnostic mammography, rapid 10 s acquisition, no breast compression, and true high-resolution isotropic imaging, CBBCT has the potential to usher in a new era in breast imaging. These advantages could translate into lower morbidity and mortality from breast cancer.

Contrast-enhanced cone beam breast CT features of breast cancers: correlation with immunohistochemical receptors and molecular subtypes.

OBJECTIVES: To investigate the association of contrast-enhanced cone beam breast CT (CE-CBBCT) features, immunohistochemical (IHC) receptors, and molecular subtypes in breast cancer. METHODS: In this retrospective study, patients who underwent preoperative CE-CBBCT and received complete IHC results were analyzed. CE-CBBCT features were evaluated by two radiologists. Observer reproducibility and feature reliability were assessed. The association between CE-CBBCT features, IHC receptors, and molecular subtypes was analyzed using the chi-square, Mann-Whitney, and Kruskal-Wallis tests. Multivariate logistic regression was performed to assess the ability of combined imaging features to discriminate molecular subtypes. ROC curve was used to evaluate prediction performance. RESULTS: A total of 240 invasive cancers identified in 211 women were enrolled. Molecular subtypes of breast cancer were significantly associated with focality number of lesions, lesion type, tumor size, lesion density, internal enhancement pattern, degree of lesion enhancement (ΔHU), mass shape, spiculation, calcifications, calcification distribution, and increased peripheral vascularity of lesion (all p < 0.005), some of which also helped to differentiate IHC receptor status. A multivariate logistic regression model showed that tumor size (odds ratio, OR = 1.244), mass shape (OR = 0.311), spiculation (OR = 0.159), and internal enhancement pattern (OR = 0.227) were associated with differentiation between luminal and non-luminal subtypes (AUC = 0.809). Combined CE-CBBCT features, including lesion type (OR = 0.118), calcifications (OR = 0.181), and ΔHU (OR = 0.962), could be significant indicators of triple-negative versus HER-2-enriched subtypes (AUC = 0.913). CONCLUSIONS: CE-CBBCT features have the potential to help predict IHC receptor status and distinguish molecular subtypes of breast cancer, which could in turn help to develop individual treatment decisions and prognosis predictions. KEY POINTS: • A total of 11 CE-CBBCT features were associated with molecular subtypes, some of which also helped to differentiate IHC receptor status. • Tumor size, irregular mass shape, spiculation, and internal enhancement pattern could help identify luminal subtype. • Lesion type, calcification, and ΔHU could be significant indicators of HER-2- enriched versus triple-negative breast cancers.

Breast Imaging in Transgender Patients.

In the United States, at least 1.4 million adults identify as transgender. Despite growing national awareness, the transgender population experiences disparities in breast care access and breast health outcomes. One of the challenges of breast care delivery to transgender patients is the lack of evidence-based screening guidelines, which is likely partly due to the infrequency of transgender breast cancer cases. Several gender-affirming hormonal and surgical interventions are available that impact the imaging appearance of the breasts and the risk of breast cancer. Breast imaging radiologists should be familiar with the imaging appearance of expected findings and potential complications following gender-affirming interventions. It has been shown that the incidence of breast cancer in transgender women is higher than in natal males but still lower than in natal females, implying that estrogen supplementation confers an increased breast cancer risk. It is proposed that transgender women follow the screening guidelines for natal females if they have risk factors for breast cancer and received hormone therapy for > 5 years. However, further research is necessary, especially in transgender women who have no risk factors or received hormone therapy for ≤ 5 years. The breast cancer risk of presurgical transgender men is considered equivalent to that of natal females, but the risk markedly decreases following bilateral mastectomy. It is proposed that transgender men follow the screening guidelines for natal females if they have any preserved breast tissue, or that they undergo annual chest wall and axillary physical exam if they are status post bilateral mastectomy.

Newer Technologies in Breast Cancer Imaging: Dedicated Cone-Beam Breast Computed Tomography.

Dedicated breast computed tomography (CT) is the latest in a long history of breast imaging techniques dating back to the 1960s. Breast imaging is performed both for cancer screening as well as for diagnostic evaluation of symptomatic patients. Dedicated breast CT received US Food and Drug Administration approval for diagnostic use in 2015 and is slowly gaining recognition for its value in diagnostic 3-dimensional imaging of the breast, and also for injected contrast-enhanced imaging applications. Conventional mammography has known limitations in sensitivity and specificity, especially in dense breasts. Breast tomosynthesis was US Food and Drug Administration approved in 2011 and is now widely used. Dedicated breast CT is the next technological advance, combining real 3-dimensional imaging with the ease of contrast administration. The lack of painful compression and manipulation of the breasts also makes dedicated breast CT much more acceptable for the patients.

The potential role of dedicated 3D breast CT as a diagnostic tool: review and early clinical examples.

Mammography is the gold standard in routine screening for the detection of breast cancer in the general population. However, limitations in sensitivity, particularly in dense breasts, has motivated the development of alternative imaging techniques such as digital breast tomosynthesis, whole breast ultrasound, breast-specific gamma imaging, and more recently dedicated breast computed tomography or "breast CT". Virtually all diagnostic work-ups of asymptomatic nonpalpable findings arise from screening mammography. In most cases, diagnostic mammography and ultrasound are sufficient for diagnosis, with magnetic resonance imaging (MRI) playing an occasional role. Digital breast tomosynthesis, a limited-angle tomographic technique, is increasingly being used for screening. Dedicated breast CT has full three-dimensional (3D) capability with near-isotropic resolution, which could potentially improve diagnostic accuracy. In current dedicated breast CT clinical prototypes, 300-500 low-dose projections are acquired in a circular trajectory around the breast using a flat panel detector, followed by image reconstruction to provide the 3D breast volume. The average glandular dose to the breast from breast CT can range from as little as a two-view screening mammogram to approximately that of a diagnostic mammography examination. Breast CT displays 3D images of the internal structures of the breast; therefore, evaluation of suspicious features like microcalcifications, masses, and asymmetries can be made in multiple anatomical planes from a single scan. The potential role of breast CT for diagnostic imaging is illustrated here through clinical examples such as imaging soft tissue abnormalities and microcalcifications. The potential for breast CT to serve as an imaging tool for extent of disease evaluation and for monitoring neo-adjuvant chemotherapy response is also illustrated.

Dedicated Breast CT: Feasibility for Monitoring Neoadjuvant Chemotherapy Treatment.

OBJECTIVES: In this prospective pilot study, the feasibility of non-contrast dedicated breast computed tomography (bCT) to determine primary tumor volume and monitor its changes during neoadjuvant chemotherapy (NAC) treatment was investigated. MATERIALS AND METHODS: Eleven women who underwent NAC were imaged with a clinical prototype dedicated bCT system at three time points - pre-, mid-, and post-treatment. The study radiologist marked the boundary of the primary tumor from which the tumor volume was quantified. An automated algorithm was developed to quantify the primary tumor volume for comparison with radiologist's segmentation. The correlation between pre-treatment tumor volumes from bCT and MRI, and the correlation and concordance in tumor size between post-treatment bCT and pathology were determined. RESULTS: Tumor volumes from automated and radiologist's segmentations were correlated (Pearson's r = 0.935, P < 0.001) and were not different over all time points [P = 0.808, repeated measures analysis of variance (ANOVA)]. Pre-treatment tumor volumes from MRI and bCT were correlated (r = 0.905, P < 0.001). Tumor size from post-treatment bCT was correlated with pathology (r = 0.987, P = 0.002) for invasive ductal carcinoma larger than 5 mm and the maximum difference in tumor size was 0.57 cm. The presence of biopsy clip (3 mm) limited the ability to accurately measure tumors smaller than 5 mm. All study participants were pathologically assessed to be responders, with three subjects experiencing complete pathologic response for invasive cancer and the reminder experiencing partial response. Compared to pre-treatment tumor volume, there was a statistically significant (P = 0.0003, paired t-test) reduction in tumor volume at mid-treatment observed with bCT, with an average tumor volume reduction of 47%. CONCLUSIONS: This pilot study suggests that dedicated non-contrast bCT has the potential to serve as an expedient imaging tool for monitoring tumor volume changes during NAC. Larger studies are needed in future.

Breast metastases to thyroid gland.

Metastases to the thyroid gland are uncommon. We present the sonographic features of metastatic breast adenocarcinoma to the thyroid in a 67-year-old woman. The lesion measured up to 0.9 cm in diameter, contained an echogenic focus with associated ring-down, and was predominantly cystic, thereby resembling a benign nodule. Because of the patient's history of breast adenocarcinoma, the nodule nevertheless underwent fine-needle aspiration. The unusual appearance of the thyroid nodule underscores the importance of considering patient history in deciding whether obtaining tissue diagnosis of thyroid nodules is warranted.

Personalized estimates of radiation dose from dedicated breast CT in a diagnostic population and comparison with diagnostic mammography.

This study retrospectively analyzed the mean glandular dose (MGD) to 133 breasts from 132 subjects, all women, who participated in a clinical trial evaluating dedicated breast CT in a diagnostic population. The clinical trial was conducted in adherence to a protocol approved by institutional review boards and the study participants provided written informed consent. Individual estimates of MGD to each breast from dedicated breast CT was obtained by combining x-ray beam characteristics with estimates of breast dimensions and fibroglandular fraction from volumetric breast CT images, and using normalized glandular dose coefficients. For each study participant and for the breast corresponding to that imaged with breast CT, an estimate of the MGD from diagnostic mammography (including supplemental views) was obtained from the DICOM image headers for comparison. This estimate uses normalized glandular dose coefficients corresponding to a breast with 50% fibroglandular weight fraction. The median fibroglandular weight fraction for the study cohort determined from volumetric breast CT images was 15%. Hence, the MGD from diagnostic mammography was corrected to be representative of the study cohort. Individualized estimates of MGD from breast CT ranged from 5.7 to 27.8 mGy. Corresponding to the breasts imaged with breast CT, the MGD from diagnostic mammography ranged from 2.6 to 31.6 mGy. The mean (± inter-breast SD) and the median MGD (mGy) from dedicated breast CT exam were 13.9 ± 4.6 and 12.6, respectively. For the corresponding breasts, the mean (± inter-breast SD) and the median MGD (mGy) from diagnostic mammography were 12.4 ± 6.3 and 11.1, respectively. Statistical analysis indicated that at the 0.05 level, the distributions of MGD from dedicated breast CT and diagnostic mammography were significantly different (Wilcoxon signed ranks test, p = 0.007). While the interquartile range and the range (maximum-minimum) of MGD from dedicated breast CT was lower than diagnostic mammography, the median MGD from dedicated breast CT was approximately 13.5% higher than that from diagnostic mammography. The MGD for breast CT is based on a 1.45 mm skin layer and that for diagnostic mammography is based on a 4 mm skin layer; thus, favoring a lower estimate for MGD from diagnostic mammography. The median MGD from dedicated breast CT corresponds to the median MGD from four to five diagnostic mammography views. In comparison, for the same 133 breasts, the mean and the median number of views per breast during diagnostic mammography were 4.53 and 4, respectively. Paired analysis showed that there was approximately equal likelihood of receiving lower MGD from either breast CT or diagnostic mammography. Future work will investigate methods to reduce and optimize radiation dose from dedicated breast CT.

Technical note: Skin thickness measurements using high-resolution flat-panel cone-beam dedicated breast CT.

PURPOSE: To determine the mean and range of location-averaged breast skin thickness using high-resolution dedicated breast CT for use in Monte Carlo-based estimation of normalized glandular dose coefficients. METHODS: This study retrospectively analyzed image data from a clinical study investigating dedicated breast CT. An algorithm similar to that described by Huang et al. ["The effect of skin thickness determined using breast CT on mammographic dosimetry," Med. Phys. 35(4), 1199-1206 (2008)] was used to determine the skin thickness in 137 dedicated breast CT volumes from 136 women. The location-averaged mean breast skin thickness for each breast was estimated and the study population mean and range were determined. Pathology results were available for 132 women, and were used to investigate if the distribution of location-averaged mean breast skin thickness varied with pathology. The effect of surface fitting to account for breast curvature was also studied. RESULTS: The study mean (± interbreast SD) for breast skin thickness was 1.44 ± 0.25 mm (range: 0.87-2.34 mm), which was in excellent agreement with Huang et al. Based on pathology, pair-wise statistical analysis (Mann-Whitney test) indicated that at the 0.05 significance level, there were no significant difference in the location-averaged mean breast skin thickness distributions between the groups: benign vs malignant (p = 0.223), benign vs hyperplasia (p = 0.651), hyperplasia vs malignant (p = 0.229), and malignant vs nonmalignant (p = 0.172). CONCLUSIONS: Considering this study used a different clinical prototype system, and the study participants were from a different geographical location, the observed agreement between the two studies suggests that the choice of 1.45 mm thick skin layer comprising the epidermis and the dermis for breast dosimetry is appropriate. While some benign and malignant conditions could cause skin thickening, in this study cohort the location-averaged mean breast skin thickness distributions did not differ significantly with pathology. The study also underscored the importance of considering breast curvature in estimating breast skin thickness.

Dedicated breast CT: fibroglandular volume measurements in a diagnostic population.

PURPOSE: To determine the mean and range of volumetric glandular fraction (VGF) of the breast in a diagnostic population using a high-resolution flat-panel cone-beam dedicated breast CT system. This information is important for Monte Carlo-based estimation of normalized glandular dose coefficients and for investigating the dependence of VGF on breast dimensions, race, and pathology. METHODS: Image data from a clinical trial investigating the role of dedicated breast CT that enrolled 150 women were retrospectively analyzed to determine the VGF. The study was conducted in adherence to a protocol approved by the institutional human subjects review boards and written informed consent was obtained from all study participants. All participants in the study were assigned BI-RADS(®) 4 or 5 as per the American College of Radiology assessment categories after standard diagnostic work-up and underwent dedicated breast CT exam prior to biopsy. A Gaussian-kernel based fuzzy c-means algorithm was used to partition the breast CT images into adipose and fibroglandular tissue after segmenting the skin. Upon determination of the accuracy of the algorithm with a phantom, it was applied to 137 breast CT volumes from 136 women. VGF was determined for each breast and the mean and range were determined. Pathology results with classification as benign, malignant, and hyperplasia were available for 132 women, and were used to investigate if the distributions of VGF varied with pathology. RESULTS: The algorithm was accurate to within ±1.9% in determining the volume of an irregular shaped phantom. The study mean (± inter-breast SD) for the VGF was 0.172 ± 0.142 (range: 0.012-0.719). VGF was found to be negatively correlated with age, breast dimensions (chest-wall to nipple length, pectoralis to nipple length, and effective diameter at chest-wall), and total breast volume, and positively correlated with fibroglandular volume. Based on pathology, pairwise statistical analysis (Mann-Whitney test) indicated that at the 0.05 significance level, there was no significant difference in distributions of VGF without adjustment for age between malignant and nonmalignant breasts (p = 0.41). Pairwise comparisons of the distributions of VGF in increasing order of mammographic breast density indicated all comparisons were statistically significant (p < 0.002). CONCLUSIONS: This study used a different clinical prototype breast CT system than that in previous studies to image subjects from a different geographical region, and used a different algorithm for analysis of image data. The mean VGF estimated from this study is within the range reported in previous studies, indicating that the choice of 50% glandular weight fraction to represent an average breast for Monte Carlo-based estimation of normalized glandular dose coefficients in mammography needs revising. In the study, the distributions of VGF did not differ significantly with pathology.

Dedicated Cone-beam Breast Computed Tomography and Diagnostic Mammography: Comparison of Radiation Dose, Patient Comfort, And Qualitative Review of Imaging Findings in BI-RADS 4 and 5 Lesions.

OBJECTIVE: This pilot study was undertaken to compare radiation dose, relative visibility/conspicuity of biopsy-proven lesions, and relative patient comfort in diagnostic mammography and dedicated cone-beam breast computed tomography (CBBCT) in Breast Imaging-Reporting and Data System (BI-RADS)(®) 4 or 5 lesions. MATERIALS AND METHODS: Thirty-six consecutive patients (37 breasts) with abnormal mammographic and/or ultrasound categorized as BI-RADS(®) 4 or 5 lesions were evaluated with CBBCT prior to biopsy. Administered radiation dose was calculated for each modality. Mammograms and CBBCT images were compared side-by-side and lesion visibility/conspicuity was qualitatively scored. Histopathology of lesions was reviewed. Patients were administered a survey for qualitative evaluation of comfort between the two modalities. RESULTS: CBBCT dose was similar to or less than diagnostic mammography, with a mean dose of 9.4 mGy (±3.1 SD) for CBBCT vs. 16.9 mGy (±6.9 SD) for diagnostic mammography in a total of 37 imaged breasts (P<0.001). Thirty-three of 34 mammographic lesions were scored as equally or better visualized in CBBCT relative to diagnostic mammography. Characterization of high-risk lesions was excellent. Patients reported greater comfort in CBBCT imaging relative to mammography. CONCLUSION: Our experience of side-by-side comparison of CBBCT and diagnostic mammography in BI-RADS(®) 4 and 5 breast lesions demonstrated a high degree of correlation between the two modalities across a variety of lesion types. Owing to favorable radiation dose profile, excellent visualization of lesions, and qualitative benefits including improved patient comfort, excellent field-of-view, and more anatomical evaluation of lesion margins, CBBCT offers a promising modality for diagnostic evaluation of breast lesions.

Abnormal axillary lymph nodes on negative mammograms: causes other than breast cancer.

Enlargement of lymph nodes can be due to a variety of benign and malignant causes. The most common malignant cause is invasive ductal carcinoma, which is usually visualized with mammography. Excluding breast cancer, other causes of abnormal lymph nodes that produce a negative mammogram include lymphoma, metastases from other malignancies, and benign etiologies such as inflammatory processes, infectious diseases, collagen vascular diseases, and miscellaneous causes. In this essay, we described common causes of abnormal axillary lymph nodes on negative mammograms excluding breast cancer.