Implementation of Intraoperative Ultrasound Localization for Breast-Conserving Surgery in a Large, Integrated Health Care System is Feasible and Effective.

BACKGROUND: Intraoperative ultrasound (IUS) localization for breast cancer is a noninvasive localization technique. In 2015, an IUS program for breast-conserving surgery (BCS) was initiated in a large, integrated health care system. This study evaluated the clinical results of IUS implementation. METHODS: The study identified breast cancer patients with BCS from 1 January to 31 October 2015 and from 1 January to 31 October 2019. Clinicopathologic characteristics were collected, and localization types were categorized. Clinical outcomes were analyzed, including localization use, surgeon adoption of IUS, day-of-surgery intervals, and re-excision rates. Multivariate logistic regression analysis was performed to evaluate predictors of re-excision. RESULTS: The number of BCS procedures increased 23%, from 1815 procedures in 2015 to 2226 procedures in 2019. The IUS rate increased from 4% of lumpectomies (n = 79) in 2015 to 28% of lumpectomies (n = 632) in 2019 (p < 0.001). Surgeons using IUS increased from 6% (5 of 88 surgeons) in 2015 to 70% (42 of 60 surgeons) in 2019. In 2019, 76% of IUS surgeons performed at least 25% of lumpectomies with IUS. The mean time from admission to incision was shorter with IUS or seed localization than with wire localization (202 min with IUS, 201 with seed localization, 262 with wire localization in 2019; p < 0.001). The IUS re-excision rates were lower than for other localization techniques (13.6%, vs 19.6% for seed localization and 24.7% for wire localization in 2019; p = 0.006), and IUS predicted lower re-excision rates in a multivariable model (odds ratio [OR], 0.59). CONCLUSIONS: In a high-volume integrated health system, IUS was adopted for BCS by a majority of surgeons. The use of IUS decreased the time from admission to incision compared with wire localization, and decreased re-excision rates compared with other localization techniques.

Mask-Guided Convolutional Neural Network for Breast Tumor Prognostic Outcome Prediction on 3D DCE-MR Images.

In this proof-of-concept work, we have developed a 3D-CNN architecture that is guided by the tumor mask for classifying several patient-outcomes in breast cancer from the respective 3D dynamic contrast-enhanced MRI (DCE-MRI) images. The tumor masks on DCE-MRI images were generated using pre- and post-contrast images and validated by experienced radiologists. We show that our proposed mask-guided classification has a higher accuracy than that from either the full image without tumor masks (including background) or the masked voxels only. We have used two patient outcomes for this study: (1) recurrence of cancer after 5 years of imaging and (2) HER2 status, for comparing accuracies of different models. By looking at the activation maps, we conclude that an image-based prediction model using 3D-CNN could be improved by even a conservatively generated mask, rather than overly trusting an unguided, blind 3D-CNN. A blind CNN may classify accurately enough, while its attention may really be focused on a remote region within 3D images. On the other hand, only using a conservatively segmented region may not be as good for classification as using full images but forcing the model's attention toward the known regions of interest.

Can Radiologists Predict the Presence of Ductal Carcinoma In Situ and Invasive Breast Cancer?

OBJECTIVE: We hypothesize that radiologists' estimated percentage likelihood assessments for the presence of ductal carcinoma in situ (DCIS) and invasive cancer may predict histologic outcomes. MATERIALS AND METHODS: Two hundred fifty cases categorized as BI-RADS category 4 or 5 at four University of California Medical Centers were retrospectively reviewed by 10 academic radiologists with a range of 1-39 years in practice. Readers assigned BI-RADS category (1, 2, 3, 4a, 4b, 4c, or 5), estimated percentage likelihood of DCIS or invasive cancer (0-100%), and confidence rating (1 = low, 5 = high) after reviewing screening and diagnostic mammograms and ultrasound images. ROC curves were generated. RESULTS: Sixty-two percent (156/250) of lesions were benign and 38% (94/250) were malignant. There were 26 (10%) DCIS, 20 (8%) invasive cancers, and 48 (19%) cases of DCIS and invasive cancer. AUC values were 0.830-0.907 for invasive cancer and 0.731-0.837 for DCIS alone. Sensitivity of 82% (56/68), specificity of 84% (153/182), positive predictive value (PPV) of 66% (56/85), negative predictive value (NPV) of 93% (153/165), and accuracy of 84% ([56 + 153]/250) were calculated using an estimated percentage likelihood of 20% or higher as the prediction threshold for invasive cancer for the radiologist with the highest AUC (0.907; 95% CI, 0.864-0.951). Every 20% increase in the estimated percentage likelihood of invasive cancer increased the odds of invasive cancer by approximately two times (odds ratio, 2.4). For DCIS, using a threshold of 40% or higher, sensitivity of 81% (21/26), specificity of 79% (178/224), PPV of 31% (21/67), NPV of 97% (178/183), and accuracy of 80% ([21 + 178]/250) were calculated. Similarly, these values were calculated at thresholds of 2% or higher (BI-RADS category 4) and 95% or higher (BI-RADS category 5) to predict the presence of malignancy. CONCLUSION: Using likelihood estimates, radiologists may predict the presence of invasive cancer with fairly high accuracy. Radiologist-assigned estimated percentage likelihood can predict the presence of DCIS, albeit with lower accuracy than that for invasive cancer.

Inter-reader Variability in the Use of BI-RADS Descriptors for Suspicious Findings on Diagnostic Mammography: A Multi-institution Study of 10 Academic Radiologists.

RATIONALE AND OBJECTIVES: The study aimed to determine the inter-observer agreement among academic breast radiologists when using the Breast Imaging Reporting and Data System (BI-RADS) lesion descriptors for suspicious findings on diagnostic mammography. MATERIALS AND METHODS: Ten experienced academic breast radiologists across five medical centers independently reviewed 250 de-identified diagnostic mammographic cases that were previously assessed as BI-RADS 4 or 5 with subsequent pathologic diagnosis by percutaneous or surgical biopsy. Each radiologist assessed the presence of the following suspicious mammographic findings: mass, asymmetry (one view), focal asymmetry (two views), architectural distortion, and calcifications. For any identified calcifications, the radiologist also described the morphology and distribution. Inter-observer agreement was determined with Fleiss kappa statistic. Agreement was also calculated by years of experience. RESULTS: Of the 250 lesions, 156 (62%) were benign and 94 (38%) were malignant. Agreement among the 10 readers was strongest for recognizing the presence of calcifications (k = 0.82). There was substantial agreement among the readers for the identification of a mass (k = 0.67), whereas agreement was fair for the presence of a focal asymmetry (k = 0.21) or architectural distortion (k = 0.28). Agreement for asymmetries (one view) was slight (k = 0.09). Among the categories of calcification morphology and distribution, reader agreement was moderate (k = 0.51 and k = 0.60, respectively). Readers with more experience (10 or more years in clinical practice) did not demonstrate higher levels of agreement compared to those with less experience. CONCLUSIONS: Strength of agreement varies widely for different types of mammographic findings, even among dedicated academic breast radiologists. More subtle findings such as asymmetries and architectural distortion demonstrated the weakest agreement. Studies that seek to evaluate the predictive value of certain mammographic features for malignancy should take into consideration the inherent interpretive variability for these findings.

Improving Screening Mammography Outcomes Through Comparison With Multiple Prior Mammograms.

OBJECTIVE: The objective of the present study is to evaluate the effect of comparison with multiple prior mammograms on the outcomes of screening mammography relative to comparison with a single prior mammogram. MATERIALS AND METHODS: We retrospectively analyzed 46,288 consecutive screening mammograms performed at our institution for 22,792 women. We divided these examinations into three groups: those interpreted without comparison with prior mammograms, those interpreted in comparison with one prior examination, and those interpreted in comparison with two or more prior examinations. For each group, we determined the rate of examination recall. We also calculated the positive predictive value of recall (i.e., positive predictive value level 1 [PPV1]) and the cancer detection rate (CDR) for both the group of examinations compared with a single prior mammogram and the group compared with multiple prior mammograms. Generalized estimating equations with the logistic link function were used to determine the relative odds ratio of recall as a function of the number of comparisons, with adjustment made for age as a confounding variable. The Fisher exact test was performed to compare the PPV1 and the CDR in the different cohorts. RESULTS: The recall rate for mammograms interpreted without comparison with prior examinations was 16.6%, whereas that for mammograms compared with one prior examination was 7.8% and that for mammograms compared with two or more prior examinations was 6.3%. After adjustment was made for age, the odds ratio of recall for the group with multiple prior examinations relative to the group with a single prior examination was 0.864 (95% CI, 0.776-0.962; p = 0.0074). Statistically significant increases in the PPV1 of 0.05 (p = 0.0009) and in the CDR of 2.3 cases per 1000 examinations (p = 0.0481) were also noted for mammograms compared with multiple prior examinations relative to those compared with a single prior examination. CONCLUSION: Comparison with two or more prior mammograms resulted in a statistically significant reduction in the screening mammography recall rate and increases in the CDR and PPV1 relative to comparison with a single prior mammogram.

Follow-up outcomes after benign concordant MRI-guided breast biopsy.

OBJECTIVE: To evaluate outcomes of benign concordant magnetic resonance imaging (MRI)-guided breast biopsy. METHODS: We retrospectively reviewed 611 consecutive MRI-guided breast core biopsies at our institution from 2005 to 2012. Benign concordant cases with MRI follow-up constituted the study group. Lesion appearance on follow-up MRI was assessed and the false-negative rate was calculated. RESULTS: Eighty-four lesions in 68 women underwent benign concordant MRI-guided biopsy with subsequent MRI follow-up. Mean time to first follow-up MRI was 10.5 months. Two false negatives were identified on follow-up at 8 and 26 months. CONCLUSIONS: We report a false-negative rate of MRI-guided breast biopsy of 2.4%.

Internal mammary lymph nodes as incidental findings at screening breast MRI.

OBJECTIVE: To evaluate the prevalence of internal mammary lymph nodes (IMLNs) on breast magnetic resonance imaging (MRI) in a screening population. MATERIALS AND METHODS: We retrospectively reviewed 92 consecutive screening breast MRI exams. Logistic regression was performed to ascertain the risk of IMLNs in cancer-free subjects and to determine whether the risk varies with age. RESULTS: IMLNs were present in 48.9% of patients. Mean node size was 4 mm (range, 3-10 mm). The prevalence of IMLNs was not related to age. No patients developed breast cancer after a mean follow-up of 3 years. CONCLUSION: Subcentimeter IMLNs are common incidental findings at screening breast MRI.

Extra-mammary findings on breast MRI: a pictorial review.

Recent improvements in breast coil performance have made detection of extra-mammary findings increasingly common. Some of these findings have important clinical implications. The radiologist should be aware of the spectrum of extra-mammary pathologies found on breast magnetic resonance imaging (MRI) and be able to distinguish clinically significant findings from those that are inconsequential. The purpose of this essay is to demonstrate various common and uncommon extra-mammary findings encountered while interpreting breast MRI and to detail appropriate management recommendations.

Imaging features of HER2 overexpression in breast cancer: a systematic review and meta-analysis.

Breast cancer imaging phenotype is diverse and may relate to molecular alterations driving cancer behavior. We systematically reviewed and meta-analyzed relations between breast cancer imaging features and human epidermal growth factor receptor type 2 (HER2) overexpression as a marker of breast cancer aggressiveness. MEDLINE and EMBASE were searched for mammography, breast ultrasound, magnetic resonance imaging (MRI), and/or [(18)F]fluorodeoxyglucose positron emission tomography studies through February 2013. Of 68 imaging features that could be pooled (85 articles, 23,255 cancers; random-effects meta-analysis), 11 significantly related to HER2 overexpression. Results based on five or more studies and robustness in subgroup analyses were as follows: the presence of microcalcifications on mammography [pooled odds ratio (pOR), 3.14; 95% confidence interval (CI), 2.46-4.00] or ultrasound (mass-associated pOR, 2.95; 95% CI, 2.34-3.71), branching or fine linear microcalcifications (pOR, 2.11; 95% CI, 1.07-4.14) or extremely dense breasts on mammography (pOR, 1.37; 95% CI, 1.07-1.76), and washout (pOR, 1.57; 95% CI, 1.11-2.21) or fast initial kinetics (pOR, 2.60; 95% CI, 1.43-4.73) on MRI all increased the chance of HER2 overexpression. Maximum [(18)F]fluorodeoxyglucose standardized uptake value (SUVmax) was higher upon HER2 overexpression (pooled mean difference, +0.76; 95% CI, 0.10-1.42). These results show that several imaging features relate to HER2 overexpression, lending credibility to the hypothesis that imaging phenotype reflects cancer behavior. This implies prognostic relevance, which is especially relevant as imaging is readily available during diagnostic work-up.

High resolution in vivo characterization of apparent diffusion coefficient at the tumor-stromal boundary of breast carcinomas: a pilot study to assess treatment response using proximity-dependent diffusion-weighted imaging.

PURPOSE: To evaluate diffusion changes in the breast tumor-stromal boundary and adjacent tissue in response to neoadjuvant chemotherapy using high resolution diffusion-weighted imaging (HR-DWI). MATERIALS AND METHODS: Seven patients with invasive breast cancer were imaged with HR-DWI before and early during treatment. The mean apparent diffusion coefficient (ADC) was plotted in 1-mm increments around the tumor boundary. Early change in ADC was measured for tumor, tumor boundary, and stromal regions, and the relationship to treatment response was evaluated using Spearman's correlation. RESULTS: Statistically significant correlations between treatment response and early changes in ADC were found for: (i) whole tumor (ρ = 0.93, 95% confidence interval [CI] = (0.58, 0.99), P = 0.003); (ii) tumor rim (ρ = 0.75, 95% CI = (-0.007, 0.96), P = 0.05); and (iii) boundary transition region (ρ = 0.86, 95% CI = (0.29, 0.98), P = 0.01). Early change in ADC of distal stroma had a marginally statistically significant positive correlation to treatment response (ρ = 0.71, 95% CI = (-0.084, 0.95), P = 0.07). CONCLUSION: Proximity-dependent evaluation of HR-DWI data in the breast tumor-stromal boundary and adjacent tissue may provide information about response to therapy.

High-resolution diffusion-weighted imaging for the separation of benign from malignant BI-RADS 4/5 lesions found on breast MRI at 3T.

PURPOSE: To determine whether readout-segmented echo-planar diffusion imaging (RESOLVE) improves separation of malignant versus benign lesions compared to standard single-shot echo-planar imaging (ss-EPI) on BI-RADS 4/5 lesions detected on breast magnetic resonance imaging (MRI). MATERIALS AND METHODS: Consecutive 3T breast MRI studies with BI-RADS 4/5 designation and subsequent biopsy or benign mastectomy were retrospectively identified. Freehand regions of interest (ROIs) were drawn on lesions and also on normal background fibroglandular tissue for comparison. Lesion-to-background contrast was evaluated by normalizing signal intensity of the lesion ROI by the normal background tissue ROI at b = 800. Statistical analysis used the Mann-Whitney/Wilcoxon rank-sum test for unpaired and Wilcoxon signed-rank for paired comparisons. RESULTS: Of 38 lesions in 32 patients, 10 were malignant. Lesion-to-background contrast was higher on RESOLVE than ss-EPI (1.80 ± 0.71 vs. 1.62 ± 0.63, P = 0.03). Mean apparent diffusion coefficient (ADC) was the same or lower on RESOLVE than ss-EPI, and this effect was largest in malignant lesions (RESOLVE 0.90 ± 0.13; ss-EPI 1.00 ± 0.13; median difference -0.10 (95% confidence interval [CI]: -0.17, -0.02) × 10(-3) mm(2) /sec; P = 0.014). By either diffusion method, there was a statistically significant difference between benign and malignant mean ADC (P < 0.001). CONCLUSION: Increased lesion-to-background contrast and improved separation of benign from malignant lesions by RESOLVE compared to standard diffusion suggests that RESOLVE may show promise as an adjunct to clinical breast MRI.

Breast MR imaging for extent of disease assessment in patients with newly diagnosed breast cancer.

Breast cancer staging and surgical planning are affected by the burden of pathologically proven cancer detected on clinical examination and/or imaging. Magnetic resonance (MR) imaging has superior sensitivity and accuracy for the detection of invasive and in situ breast cancer as compared with physical examination, mammography, and ultrasound but can be limited in specificity. The use of preoperative breast MR imaging for evaluating the extent of disease remains controversial at present because studies have not definitively shown it to improve overall survival, decrease re-excision rates, or to decrease the cost of care.

Triple-negative and non-triple-negative invasive breast cancer: association between MR and fluorine 18 fluorodeoxyglucose PET imaging.

PURPOSE: To assess the relationship between parameters measured on dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging and fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in primary invasive breast cancer. MATERIALS AND METHODS: This HIPAA-compliant study was a retrospective review of medical records and therefore approved by the institutional review board without the requirement for informed consent. Patients with a diagnosis of invasive breast cancer from January 2005 through December 2009 who underwent both DCE MR imaging and FDG PET/CT before treatment initiation were retrospectively identified. Fractional volumes were measured for ranges of signal enhancement ratio (SER) values from DCE MR imaging data and compared with maximum standardized uptake values (SUVmax) from FDG PET/CT data. Linear regression analysis was performed to clarify the relationship between SER and SUVmax, adjusting for tumor size, pathologic grade, and receptor status. RESULTS: Analyzed were 117 invasive breast cancers in 117 patients. Overall, a higher percentage of high washout kinetics was positively associated with SUVmax (1.57% increase in SUVmax per 1% increase in high washout; P = .020), and a higher percentage of low plateau kinetics was negatively associated with SUVmax (1.19% decrease in SUVmax per 1% increase in low plateau; P = .003). These relationships were strongest among triple-negative (TN) tumors (4.34% increase in SUVmax per 1% increase in high washout and 2.65% decrease in SUVmax per 1% increase in low plateau; P = .018 and .004, respectively). CONCLUSION: In invasive breast carcinoma, there is a positive relationship between the percentage of high washout and SUVmax and a negative relationship between the percentage of low plateau and SUVmax. These results are stronger in TN tumors. SUPPLEMENTAL MATERIAL: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13130058/-/DC1.

Recognizing artifacts and optimizing breast MRI at 1.5 and 3 T.

OBJECTIVE: This article will discuss routine 1.5 and 3 T MRI of the breast as well as illustrate several examples of patient-related and technical artifacts one might encounter. Suggestions to help eliminate these artifacts and optimize images will be provided. CONCLUSION: Artifacts seen on breast MR images can degrade image quality and obscure important findings. Recognizing artifacts and understanding how to address and troubleshoot them is essential for any radiologist interpreting breast MRI.

High-resolution diffusion-weighted imaging for monitoring breast cancer treatment response.

RATIONALE AND OBJECTIVES: The aim of this work was to compare a high-resolution diffusion-weighted imaging (HR-DWI) acquisition (voxel size = 4.8 mm(3)) to a standard diffusion-weighted imaging (STD-DWI) acquisition (voxel size = 29.3 mm(3)) for monitoring neoadjuvant therapy-induced changes in breast tumors. MATERIALS AND METHODS: Nine women with locally advanced breast cancer were imaged with both HR-DWI and STD-DWI before and after 3 weeks (early treatment) of neoadjuvant taxane-based treatment. Tumor apparent diffusion coefficient (ADC) metrics (mean and histogram percentiles) from both DWI methods were calculated, and their relationship to tumor volume change after 12 weeks of treatment (posttreatment) measured by dynamic contrast enhanced magnetic resonance imaging was evaluated with a Spearman's rank correlation. RESULTS: The HR-DWI pretreatment 15th percentile tumor ADC (P = .03) and early treatment 15th, 25th, and 50th percentile tumor ADCs (P = .008, .010, .04, respectively) were significantly lower than the corresponding STD-DWI percentile ADCs. The mean tumor HR-ADC was significantly lower than STD-ADC at the early treatment time point (P = .02), but not at the pretreatment time point (P = .07). A significant early treatment increase in tumor ADC was found with both methods (P < .05). Correlations between HR-DWI tumor ADC and posttreatment tumor volume change were higher than the STD-DWI correlations at both time points and the lower percentile ADCs had the strongest correlations. CONCLUSION: These initial results suggest that the HR-DWI technique has potential for improving characterization of low tumor ADC values over STD-DWI and that HR-DWI may be of value in evaluating tumor change with treatment.

High-resolution diffusion-weighted magnetic resonance imaging in patients with locally advanced breast cancer.

RATIONALE AND OBJECTIVES: The aim of this study was to evaluate differences in tumor depiction and measured tumor apparent diffusion coefficient (ADC) with the use of a high-resolution diffusion-weighted (DW) magnetic resonance imaging (MRI) sequence, compared to a standard DW MRI sequence, in patients with locally advanced breast cancer. MATERIALS AND METHODS: Patients with locally advanced breast cancer were scanned with a reduced-field of view (rFOV) DW MRI sequence (high resolution) and a standard-field of view diffusion sequence (standard resolution), and differences between the two sequences were evaluated quantitatively (by calculating tumor ADC distribution parameters) and qualitatively (by radiologists' visual assessments of images). RESULTS: Although the mean tumor ADC for both sequences was similar, differences were found in other parameters, including the 12.5th percentile (P = .042) and minimum tumor ADC (P = .003). Qualitatively, visualization of tumor morphologic detail, heterogeneity, and conspicuity was improved with rFOV DW MRI, and image quality was higher. CONCLUSIONS: Differences in ADC distribution parameters and qualitative image features suggest that the sequences differ in their ability to capture tumor heterogeneity. These differences are not apparent when the mean is used to evaluate tumor ADC. In particular, differences found in lower ADC values are compatible with reduced partial voluming in rFOV DW MRI, suggesting that rFOV DW MRI may be valuable in imaging the lower ADCs expected to correspond to viable tumor in most invasive breast cancers.