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Imaging is the mainstay in breast cancer diagnosis, with mammography being the primary screening tool used to detect small/asymptomatic cancers. Symptomatic patients undergo triple assessment, which includes a clinical assessment, imaging and, if indicated, an image-guided biopsy for histological diagnosis. We discuss current and emerging breast imaging techniques used in breast cancer care. These include mammography, digital breast tomosynthesis, ultrasound and magnetic resonance. We also discuss image-guided biopsy and miscellaneous image-guided interventions that influence the management of breast cancer care. [ABSTRACT FROM AUTHOR]

IntroductionDiffusion weighted MRI (DWI) has emerged as a promising adjunct to reduce unnecessary biopsies prompted by breast MRI through use of apparent diffusion coefficient (ADC) measures. The purpose of this study was to investigate the effects of different lesion ADC measurement approaches and ADC cutoffs on the diagnostic performance of breast DWI in a high-risk MRI screening cohort to identify the optimal approach for clinical incorporation.MethodsConsecutive screening breast MRI examinations (August 2014–Dec 2018) that prompted a biopsy for a suspicious breast lesion (BI-RADS 4 or 5) were retrospectively evaluated. On DWI, ADC (b=0/100/600/800s/mm2) measures were calculated with three different techniques for defining lesion region-of-interest (ROI; single slice(‘2D’), whole volume(‘3D’) and lowest ADC region(‘hotspot’)). An optimal data-derived ADC cutoff for each technique was retrospectively identified to reduce benign biopsies while avoiding any false negatives, inherently producing cutoffs with 100% sensitivity in this particular cohort. Further, diagnostic performance of these measures was validated using two prespecified ADC cutoffs: 1.53x10-3mm2/s from the ECOG-ACRIN A6702 trial and 1.30x10-3mm2/s from the international EUSOBI group. Diagnostic performance was compared between ADC maps generated with 2(0/800s/mm2) and 4(0/100/600/800s/mm2) b-values. Benign biopsy reduction rate was calculated (number of benign lesions with ADC >cutoff)/(total number of benign lesions).Results137 suspicious lesions (in 121 women, median age 44 years [range, 20-75yrs]) were detected on contrast-enhanced screening breast MRI and recommended for biopsy. Of those, 30(21.9%) were malignant and 107(78.1%) were benign. Hotspot ADC measures were significantly lower (p

Background: The value and utility of axillary lymph node (ALN) evaluation with MRI in breast cancer were not clear for various intrinsic subtypes. The aim of the current study is to test the potential of combining breast MRI and clinicopathologic factors to identify low-risk groups of ALN metastasis and improve diagnostic performance. Material and methods: Patients with primary operable invasive breast cancer with pre-operative breast MRI and post-operative pathologic reports were retrospectively collected from January 2009 to December 2021 in a single institute. The concordance of MRI and pathology of ALN status were determined, and also analyzed in different intrinsic subtypes. A stepwise strategy was designed to improve MRI-negative predictive value (NPV) on ALN metastasis. Results: 2473 patients were enrolled. The diagnostic performance of MRI in detecting metastatic ALN was significantly different between intrinsic subtypes (p = 0.007). Multivariate analysis identified tumor size and histologic type as independent predictive factors of ALN metastases. Patients with HER-2 (MRI tumor size ≤ 2 cm), or TNBC (MRI tumor size ≤ 2 cm) were found to have MRI–ALN-NPV higher than 90%, and these false cases were limited to low axillary tumor burden. Conclusion: The diagnostic performance of MRI to predict ALN metastasis varied according to the intrinsic subtype. Combined pre-operative clinicopathologic factors and intrinsic subtypes may increase ALN MRI NPV, and further identify some groups of patients with low risks of ALN metastasis, high NPV, and low burdens of axillary disease even in false-negative cases. [ABSTRACT FROM AUTHOR]

PURPOSE: To assess the feasibility and diagnostic accuracy of multispectral MRI (MSI) in the detection and localization of biopsy markers during MRI-guided breast biopsy. METHODS: This prospective study included 20 patients undergoing MR-guided breast biopsy. In 10 patients (Group 1), MSI was acquired following tissue sampling and biopsy marker deployment. In the other 10 patients (Group 2), MSI was acquired following tissue sampling but before biopsy marker deployment (to simulate deployment failure). All patients received post-procedure mammograms. Group 1 and Group 2 designations, in combination with the post-procedure mammogram, served as the reference standard. The diagnostic performance of MSI for biopsy marker identification was independently evaluated by two readers using two-spectral-bin MR and one-spectral-bin MR. The κ statistic was used to assess inter-rater agreement for biopsy marker identification. RESULTS: The sensitivity, specificity, and accuracy of biopsy marker detection for readers 1 and 2 using 2-bin MSI were 90.0% (9/10) and 90.0% (9/10), 100.0% (10/10) and 100.0% (10/10), 95.0% (19/20) and 95.0% (19/20); and using 1-bin MSI were 70.0% (7/10) and 80.0% (8/10), 100.0% (8/8) and 100.0% (10/10), 85.0% (17/20) and 90.0% (18/20). Positive predictive value was 100% for both readers for all numbers of bins. Inter-rater agreement was excellent: κ was 1.0 for 2-bin MSI and 0.81 for 1-bin MSI. CONCLUSION: MSI is a feasible, diagnostically accurate technique for identifying metallic biopsy markers during MRI-guided breast biopsy and may eliminate the need for a post-procedure mammogram.

Background: In the German Mammography Screening Program, 62% of ductal carcinoma in situ (DCIS) and 38% of invasive breast cancers are associated with microcalcifications (MCs). Vacuum-assisted stereotactic breast biopsies are necessary to distinguish precancerous lesions from benign calcifications because mammographic discrimination is not possible. The aim of this study was to investigate if breast magnetic resonance imaging (MRM) could assist the evaluation of MCs and thus help reduce biopsy rates. Methods: In this IRB-approved study, 58 women (mean age 58 +/− 24 years) with 59 suspicious MC clusters in the MG were eligible for this prospective single-center trial. Additional breast magnetic resonance imaging (MRI) was conducted before biopsy. Results: The breast MRI showed a sensitivity of 86%, a specificity of 84%, a positive predictive value (PPV) of 75% and a negative predictive value (NPV) of 91% for the differentiation between benign and malignant in these 59 MCs found with MG. Breast MRI in addition to MG could increase the PPV from 36% to 75% compared to MG alone. The MRI examination led to nine additional suspicious classified lesions in the study cohort. A total of 55% (5/9) of them turned out to be malignant. A total of 32 of 59 (54 %) women with suspicious MCs and benign histology were classified as non-suspicious by MRI. Conclusion: An additionally performed breast MRI could have increased the diagnostic reliability in the assessment of MCs. Further, in our small cohort, a considerable number of malignant lesions without mammographically visible MCs were revealed. [ABSTRACT FROM AUTHOR]

Imaging is the mainstay in breast cancer diagnosis, with mammography being the primary screening tool used to detect small/asymptomatic cancers. Symptomatic patients undergo triple assessment which includes a clinical assessment, imaging and, if indicated, an image-guided biopsy for histological diagnosis. We discuss current and emerging breast imaging techniques used in breast cancer care. These include mammography, digital breast tomosynthesis, ultrasound and magnetic resonance. We also discuss image-guided biopsy and miscellaneous image-guided interventions that influence the management of breast cancer care. [ABSTRACT FROM AUTHOR]

Background: In the German Mammography Screening Program, 62% of ductal carcinoma in situ (DCIS) and 38% of invasive breast cancers are associated with microcalcifications (MCs). Vacuum-assisted stereotactic breast biopsies are necessary to distinguish precancerous lesions from benign calcifications because mammographic discrimination is not possible. The aim of this study was to investigate if breast magnetic resonance imaging (MRM) could assist the evaluation of MCs and thus help reduce biopsy rates. Methods: In this IRB-approved study, 58 women (mean age 58 +/− 24 years) with 59 suspicious MC clusters in the MG were eligible for this prospective single-center trial. Additional breast magnetic resonance imaging (MRI) was conducted before biopsy. Results: The breast MRI showed a sensitivity of 86%, a specificity of 84%, a positive predictive value (PPV) of 75% and a negative predictive value (NPV) of 91% for the differentiation between benign and malignant in these 59 MCs found with MG. Breast MRI in addition to MG could increase the PPV from 36% to 75% compared to MG alone. The MRI examination led to nine additional suspicious classified lesions in the study cohort. A total of 55% (5/9) of them turned out to be malignant. A total of 32 of 59 (54 %) women with suspicious MCs and benign histology were classified as non-suspicious by MRI. Conclusion: An additionally performed breast MRI could have increased the diagnostic reliability in the assessment of MCs. Further, in our small cohort, a considerable number of malignant lesions without mammographically visible MCs were revealed.

PurposeTo assess the feasibility and diagnostic accuracy of multispectral MRI (MSI) in the detection and localization of biopsy markers during MRI-guided breast biopsy.MethodsThis prospective study included 20 patients undergoing MR-guided breast biopsy. In 10 patients (Group 1), MSI was acquired following tissue sampling and biopsy marker deployment. In the other 10 patients (Group 2), MSI was acquired following tissue sampling but before biopsy marker deployment (to simulate deployment failure). All patients received post-procedure mammograms. Group 1 and Group 2 designations, in combination with the post-procedure mammogram, served as the reference standard. The diagnostic performance of MSI for biopsy marker identification was independently evaluated by two readers using two-spectral-bin MR and one-spectral-bin MR. The κ statistic was used to assess inter-rater agreement for biopsy marker identification.ResultsThe sensitivity, specificity, and accuracy of biopsy marker detection for readers 1 and 2 using 2-bin MSI were 90.0% (9/10) and 90.0% (9/10), 100.0% (10/10) and 100.0% (10/10), 95.0% (19/20) and 95.0% (19/20); and using 1-bin MSI were 70.0% (7/10) and 80.0% (8/10), 100.0% (8/8) and 100.0% (10/10), 85.0% (17/20) and 90.0% (18/20). Positive predictive value was 100% for both readers for all numbers of bins. Inter-rater agreement was excellent: κ was 1.0 for 2-bin MSI and 0.81 for 1-bin MSI.ConclusionMSI is a feasible, diagnostically accurate technique for identifying metallic biopsy markers during MRI-guided breast biopsy and may eliminate the need for a post-procedure mammogram.

Objective: The A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance. Methods: The A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b-value, echoplanar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping. Results: Thirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability (P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p <0.03), though not significant after multiplicity correction. The AUC for differentiating benign and malignant lesions increased after excluding non-evaluable lesions, from 0.61 (95% CI: 0.50-0.71) to 0.75 (95% CI: 0.65-0.84). Conclusion: Image quality remains a technical challenge in breast DWI, particularly for smaller lesions. Protocol optimization and advanced acquisition and post-processing techniques would help to improve clinical utility. [ABSTRACT FROM AUTHOR]

Breast cancer is the most commonly diagnosed cancer in women worldwide. Conventional mammography and ultrasound no longer present the only options for imaging, in the detection of breast cancer. The imaging modalities currently available are described in the paper. Breast MRI is compared with contrast enhanced mammography, which is an emerging modality in breast cancer detection. These two modalities use intravenous contrast (i.v.) to provide functional information. They are compared in terms of sensitivity, specificity, radiation dose, rates of contrast reactions, as well as availability. [ABSTRACT FROM AUTHOR]

Abstract Purpose To investigate differences in clinical features, MRI findings and tumor biomarker characteristics in screen-detected (SCD) and non-screendetected (NSCD) cancers. Material and methods A total of 62 women (mean age, 48.4 years; range, 33–68 years) with biopsy confirmed breast cancer who underwent preoperative breast MRI were retrospectively evaluated by two expert radiologists. The women were divided into two groups according to the mode of cancer detection (Group A: screen- detected, Group B: non-screen/symptomatic cancer) and clinical, histopathological, MRI characteristics and biomarker features in each group were evaluated. Results NSCD tumors had significantly greater size (3.5 cm vs. 2.1 cm) and Ki-67 expression (68.4% vs. 41.7%) in comparison to SCD cancers. NSCD cancers were less likely to have strongly positive progesterone receptors (Pr) and more likely to have Ki-67 > 15% or positive nodal status (47.4% vs. 8.3%). Increased breast density (ACR C and D: 78.9% vs. 50%ACR A and B) and intense background parenchymal enhancement (BPE, moderate/marked: 42.1% vs. 8.3% minimal/mild) were significantly more frequent in NSCD cases. Conclusion NSCD cancers had higher prevalence of poor prognostic characteristics in comparison to SCD tumors, including larger tumor size, higher Ki-67 index, and positive nodes. Increased fibroglandular tissue and intense BPE were both strongly associated with NSCD cancers, supporting their use as potential MR biomarkers in breast cancer risk models. Highlights • NSDC display poor prognostic characteristics such as larger tumor size, increased Ki-67 and metastatic lymphadenopathy. • Increased FGT and BPE are strongly associated with NSDC, compared to SDC. • Larger prospective studies are needed to evaluate the role of FGT and BPE as potential biomarkers for breast cancer screening. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Various imaging modalities have been used to diagnose suspicious breast lesions. Purpose of this study is to compare the diagnostic accuracy for breast cancer using mammography, ultrasonography and magnetic resonance imaging (MRI). METHODS: Total 107 patients aged from 19 to 62 years are included in this retrospective study. Mammography, ultrasonography and MRI scans were performed for each patient detected with suspected breast tumor within a month. In addition, the tumor diversity (10 types of benign and 5 types of malignant) was confirmed by pathological findings of tumor biopsy. To compare the diagnosis performance of the three imaging modalities, the overall fraction correct (accuracy), positive predict value (PPV), negative predict value (NPV), sensitivity and specificity were calculated. Meanwhile, the receiver operating characteristic (ROC) analysis was also performed. RESULTS: The diagnostic accuracy ranged from 78.5% to 86.9% among three imaging modalities. All modalities yielded a PPV lower than 77.8% and a NPV higher than 90.0% in identifying the presence of malignant tumors. MRI presented a diagnostic accuracy of 86.9%, as well as a sensitivity of 95.5% and an area under curve (AUC) of 0.948, which are higher than mammography and ultrasonography. CONCLUSION: By using a diverse dataset and comparing the diagnostic accuracy of three imaging modalities commonly used in breast cancer detection and diagnosis, this study also demonstrated that mammography, ultrasonography and MRI had different diagnostic performance in breast tumor identification. Among them, MRI yielded the highest performance even though the unexpected specificity may lead to over-diagnosis, and ultrosonography is slightly better than mammography. [ABSTRACT FROM AUTHOR]

Objective: Prospective studies on postoperative residual breast tissue (RBT) after robotic-assisted nipple-sparing mastectomy (R-NSM) for breast cancer are limited. RBT presents an unknown risk of local recurrence or the development of new cancer after curative or risk-reducing mastectomies. This study investigated the technical feasibility of using magnetic resonance imaging (MRI) to evaluate RBT after R-NSM in women with breast cancer., Materials and Methods: In this prospective pilot study, 105 patients, who underwent R-NSM for breast cancer at Changhua Christian Hospital between March 2017 and May 2022, were subjected to postoperative breast MRI to evaluate the presence and location of RBT. The postoperative MRI scans of 43 patients (age, 47.8 ± 8.5 years), with existing preoperative MRI scans, were evaluated for the presence and location of RBT. In total, 54 R-NSM procedures were performed. In parallel, we reviewed the literature on RBT after nipple-sparing mastectomy, considering its prevalence., Results: RBT was detected in 7 (13.0%) of the 54 mastectomies (6 of the 48 therapeutic mastectomies and 1 of the 6 prophylactic mastectomies). The most common location for RBT was behind the nipple-areolar complex (5 of 7 [71.4%]). Another RBT was found in the upper inner quadrant (2 of 7 [28.6%]). Among the six patients who underwent RBT after therapeutic mastectomies, one patient developed a local recurrence of the skin flap. The other five patients with RBT after therapeutic mastectomies remained disease-free., Conclusion: R-NSM, a surgical innovation, does not seem to increase the prevalence of RBT, and breast MRI showed feasibility as a noninvasive imaging tool for evaluating the presence and location of RBT., Competing Interests: The authors have no potential conflicts of interest to disclose., (Copyright © 2023 The Korean Society of Radiology.)

Purpose: Ductal carcinoma in situ (DCIS) is a non-invasive cancerous breast lesion; however, from 10% to 50% of patients with DCIS diagnosed by core needle biopsy (CNB) or vacuum-assisted core biopsy (VACB) are shown to have invasive carcinoma after surgical excision. In this study, we evaluated whether preoperative clinicopathologic factors and breast magnetic resonance image (MRI) features are predictive of DCIS with invasive components before surgery.Materials and Methods: Patients comprised 128 adult women with a diagnosis of DCIS as determined by pathological analysis of CNB or VACB specimens and positive MRI findings who underwent breast surgery during the period January 2011 to December 2013 at the Changhua Christian Hospital. Clinicopathologic and breast MRI factors were compared between patients with postoperative pathology indicative of true DCIS and those with postoperative pathology showing DCIS with invasive components.Results: Of the 128 patients with a preoperative diagnosis of DCIS, 73 (57.0%) had postoperative histopathologic evidence of true DCIS and 55 (43.0%) showed evidence of DCIS with invasive components. Results of statistical analyses revealed that MRI evidence of a mass-like lesion (P=0.025), nipple-areolar complex (NAC) invasion (P=0.029), larger tumor volume (P=0.010), larger maximum measurable apparent diffusion coefficient (ADC) area (P=0.039), heterogenous or rim enhancement pattern (P=0.010), as well as immunohistochemical evidence of human epidermal growth factor receptor 2 (HER-2) overexpression (P=0.010) were predictive of DCIS with an invasive component in postoperative surgical specimens.Conclusion: Invasive component should be considered in biopsy proven DCIS patients with preoperative MRI evidence of a mass-like lesion, nipple-areolar complex invasion, large tumor volume, a larger maximum measurable ADC area, or a rim or heterogenous enhancement pattern, as well as in patients with immunohistochemical evidence of HER-2 overexpression. [ABSTRACT FROM AUTHOR]

This paper presents a robust atlas-based segmentation (ABS) algorithm for segmentation of the breast boundary in 3-D MR images. The proposed algorithm combines the well-known methodologies of ABS namely probabilistic atlas and atlas selection approaches into a single framework where two configurations are realized. The algorithm uses phase congruency maps to create an atlas which is robust to intensity variations. This allows an atlas derived from images acquired with one MR imaging sequence to be used to segment images acquired with a different MR imaging sequence and eliminates the need for intensity-based registration. Images acquired using a Dixon sequence were used to create an atlas which was used to segment both Dixon images (intra-sequence) and T1-weighted images (inter-sequence). In both cases, highly accurate results were achieved with the median Dice similarity coefficient values of 94\% \pm 4\% and 87 \pm 6.5\%, respectively. [ABSTRACT FROM AUTHOR]

Abstract: Background and purpose: Pre-treatment breast magnetic resonance imaging (MRI) findings in a cohort of women prospectively evaluated for accelerated partial breast irradiation (APBI) are reviewed and characterized to determine the optimal use of MRI in these patients. Materials and methods: Candidates initially deemed eligible for a prospective APBI trial based on physical examination, mammography, and ultrasound (US) were further evaluated with breast MRI before treatment. All abnormal MRI findings were biopsied. Results: Between 2002 and 2011, 180 women who met inclusion criteria for APBI underwent breast MRI prior to treatment (median age=59; range 38–86). 126 tumors (70%) were invasive carcinomas with or without associated DCIS, while 54 (30%) were pure DCIS. Breast MRI confirmed unifocal disease in 109 patients with 111 cancers (60.5% of MRI cohort). Multifocal disease was identified in 19 patients (10.5% of MRI cohort), while multicentric disease was present in 3 patients (1.6% of MRI cohort). Five patients (4%) had an MRI-detected contralateral cancer. False positive MRI findings were seen in 45 patients (25% of MRI cohort). Pre-menopausal patients and patients with tumors >2cm were more likely to have MRI-detected multifocal/multicentric disease. While there was no statistically significant correlation between multifocal/multicentric disease and breast density, tumor histology, grade, ER status, or Her2/Neu expression, numbers in each category were small, suggesting a lack of statistical power to detect differences that may be clinically meaningful. One hundred and fifty-two of the 180 patients (84.4%) successfully completed lumpectomy and APBI, while 6.7% of the cohort underwent mastectomy. Conclusions: Breast MRI identified additional disease in 12% of APBI candidates. Premenopausal women and patients with tumors >2cm were more likely to have MRI-detected multifocal/multicentric disease. [Copyright &y& Elsevier]

Abstract: Introduction: Magnetic resonance imaging (MRI) has been increasingly utilized to screen and manage breast care. As the literature demonstrating its benefit expands, so do the potential clinical indications. However, routine review of the literature is merited to re-evaluate the appropriate and cost-effective use of MRI and guide clinicians in the areas of controversy. Methods: A literature review was performed to evaluate the current evidence for the use of MRI. Results: Evidence supports MRI screening for genetic mutation carriers and for those with an equivalent lifetime risk (>50%). Regarding staging and management, MRI is indicated for monitoring tumour response to neoadjuvant therapy. MRI should also be considered for patients with invasive lobular carcinoma, mammographically occult breast cancer and Paget’s disease. Discussion: Though MRI is limited by moderate specificity and high cost, it can be a valuable, sensitive and cost-effective tool with thoughtful and judicious patient selection. [Copyright &y& Elsevier]

Background: The breast imaging reporting and data system (BI-RADS) lexicon provides a standardized terminology for describing leision characteristics but does not provide defined rules for converting specific imaging features into diagnostic categories. The inter-reader agreement of the BI-RADS is moderate. In this study, we explored the use of a simplified protocol and scoring system for BI-RADS categorization which integrates the morphologic features (MF), kinetic time-intensity curve (TIC), and apparent diffusion coefficient (ADC) values with equal weights, with a view to providing a convenient and practical method for breast magnetic resonance imaging (MRI) and improving the inter-reader agreement and diagnostic performance of BI-RADS., Methods: This cross-sectional, retrospective, single-center study included 879 patients with 898 histopathologically verified lesions who underwent an MRI scan on a 3.0 Tesla GE Discovery 750 MRI scanner between January 1, 2017, and June 30, 2020. The BI-RADS categorization of the studied lesions was assessed according to the sum of the assigned scores (the presence of malignant MF, lower ADC, and suspicious TIC each warranted a score of +1). Total scores of +2 and +3 were classified as category 5, scores of +1 were classified as category 4, and scores of +0 but with other lesions of interest were classified as category 3. The receiver operating characteristic (ROC) curves were plotted, and the sensitivity, specificity, and accuracy of this categorization were investigated to assess its efficacy and its consistency with pathology., Results: There were 472 malignant, 104 risk, and 322 benign lesions. Our simplified scoring protocol had high diagnostic accuracy, with an area under curve (AUC) value of 0.896. In terms of the borderline effect of pathological risk and category 4 lesions, our results showed that when risk lesions were classified together with malignant ones, the AUC value improved (0.876 vs. 0.844 and 0.909 vs. 0.900). When category 4 and 5 lesions were classified as malignant, the specificity, accuracy, and AUC value decreased (82.3% vs. 93.2%, 89.3% vs. 90.2%, and 0.876 vs. 0.909, respectively). Therefore, to improve the diagnostic accuracy of the protocol for BI-RADS categorization, only category 5 lesions should be considered to be malignant., Conclusions: Our simplified scoring protocol that integrates MF, TIC, and ADC values with equal weights for BI-RADS categorization could improve both the diagnostic performance of the protocol for BI-RADS categorization in clinical practice and the understanding of the benign-risk-malignant breast diseases., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-21-1036/coif). The authors have no conflicts of interest to declare., (2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Purpose: To assess the feasibility and diagnostic accuracy of multispectral MRI (MSI) in the detection and localization of biopsy markers during MRI-guided breast biopsy., Methods: This prospective study included 20 patients undergoing MR-guided breast biopsy. In 10 patients (Group 1), MSI was acquired following tissue sampling and biopsy marker deployment. In the other 10 patients (Group 2), MSI was acquired following tissue sampling but before biopsy marker deployment (to simulate deployment failure). All patients received post-procedure mammograms. Group 1 and Group 2 designations, in combination with the post-procedure mammogram, served as the reference standard. The diagnostic performance of MSI for biopsy marker identification was independently evaluated by two readers using two-spectral-bin MR and one-spectral-bin MR. The κ statistic was used to assess inter-rater agreement for biopsy marker identification., Results: The sensitivity, specificity, and accuracy of biopsy marker detection for readers 1 and 2 using 2-bin MSI were 90.0% (9/10) and 90.0% (9/10), 100.0% (10/10) and 100.0% (10/10), 95.0% (19/20) and 95.0% (19/20); and using 1-bin MSI were 70.0% (7/10) and 80.0% (8/10), 100.0% (8/8) and 100.0% (10/10), 85.0% (17/20) and 90.0% (18/20). Positive predictive value was 100% for both readers for all numbers of bins. Inter-rater agreement was excellent: κ was 1.0 for 2-bin MSI and 0.81 for 1-bin MSI., Conclusion: MSI is a feasible, diagnostically accurate technique for identifying metallic biopsy markers during MRI-guided breast biopsy and may eliminate the need for a post-procedure mammogram., Competing Interests: YW and PS are inventors on QSM-related patents issued to Cornell University and hold equity in Medimagemetric LLC. KP received payment for activities not related to the present article including lectures including service on speakers bureaus and for travel/accommodations/meeting expenses unrelated to activities listed from the European Society of Breast Imaging (MRI educational course, annual scientific meeting), and the IDKD 2019 (educational course). EM has received a grant from GRAIL, Inc. for research not related to the present article. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Eskreis-Winkler, Simon, Reichman, Spincemaille, Nguyen, Christos, Drotman, Prince, Pinker, Sutton, Morris and Wang.)

Objective: The A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance., Methods: The A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b -value, echo-planar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping., Results: Thirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability ( P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p <0.03), though not significant after multiplicity correction. The AUC for differentiating benign and malignant lesions increased after excluding non-evaluable lesions, from 0.61 (95% CI: 0.50-0.71) to 0.75 (95% CI: 0.65-0.84)., Conclusion: Image quality remains a technical challenge in breast DWI, particularly for smaller lesions. Protocol optimization and advanced acquisition and post-processing techniques would help to improve clinical utility., (© Society of Breast Imaging 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)