Contrast-enhanced Breast MRI Research Articles

The Role of Diffusion-Weighted Imaging Based on Maximum-Intensity Projection in Young Patients with Marked Background Parenchymal Enhancement on Contrast-Enhanced Breast MRI.

Diffusion-weighted imaging (DWI) utilizing maximum-intensity projection (MIP) was suggested as a cost-effective alternative tool without the risk of gadolinium-based contrast agents. The purpose of this study was to investigate whether DWI MIPs played a supportive role in young (≤60) patients with marked background parenchymal enhancement (BPE) on contrast-enhanced MRI (CE-MRI). The research included 1303 patients with varying degrees of BPE, and correlations between BPE on CE-MRI, the background diffusion signal (BDS) on DWI, and clinical parameters were analyzed. Lesion detection scores were compared between CE-MRI and DWI, with DWI showing higher scores. Among the 186 lesions in 181 patients with marked BPE on CE-MRI, the main lesion on MIPs of CE-MRI was partially or completely seen in 88.7% of cases, while it was not seen in 11.3% of cases. On the other hand, the main lesion on MIPs of DWI was seen in 91.4% of cases, with only 8.6% of cases showing no visibility. DWI achieved higher scores for lesion detection compared to CE-MRI. The presence of a marked BDS was significantly associated with a lower likelihood of a higher DWI score (p < 0.001), and non-mass lesions were associated with a decreased likelihood of a higher DWI score compared with mass lesions (p = 0.196). In conclusion, the inclusion of MIPs of DWI in the preoperative evaluation of breast cancer patients, particularly young women with marked BPE, proved highly beneficial in improving the overall diagnostic process.

Contrast-enhanced ultrasound-guided biopsy of suspicious breast lesions on contrast-enhanced mammography and contrast-enhanced MRI: a case series.

To assess the effectiveness of contrast-enhanced ultrasound (CEUS) in guiding biopsies of breast lesions that were detected on contrast-enhanced mammography (CEM) or contrast-enhanced breast MRI (CE-MRI) but were not clearly visible on B-mode ultrasound (B-US). In this study, 23 lesions in 16 patients were selected for CEUS-guided biopsy due to poor visualization on B-US despite being detected on CEM (n = 20) or CE-MRI (n = 3). B-US, color Doppler ultrasound (CDUS), and CEUS were used to visualize the suspicious lesions, followed by a CEUS-guided core needle biopsy using Sonazoid as the contrast agent. The accuracy of the biopsy was assessed based on pathology-radiology concordance and 12-month imaging follow-up. The conspicuity scores for lesion visualization were evaluated using a 5-point conspicuity scale agreed upon by two breast radiologists. The enhancing lesions detected on CEM/CE-MRI had an average size of 1.6 ± 1.3cm and appeared as mass-enhancing (61%) or non-mass-enhancing (39%). The lesions had mean conspicuity scores of 2.30 on B-US, 2.78 on CDUS, and 4.61 on CEUS, with 96% of the lesions showing contrast enhancement on CEUS. CEUS-guided biopsy showed increased visibility in 96% and 91% of the lesions compared to B-US and CDUS, respectively. The overall accuracy of CEUS-guided biopsy was 100% based on concordance with histology and 12-month follow-up. CEUS enhances the visibility of suspicious CEM/CE-MRI lesions that are poorly visible on B-US during biopsy procedures.

The performance of contrast-enhanced mammography and breast MRI in local preoperative staging of invasive lobular breast cancer

PurposeBreast MRI is considered the best modality for preoperative staging of invasive lobular carcinoma (ILC). However, contrast-enhanced mammography (CEM) shows comparable diagnostic performance to MRI, but evidence of CEM’s accuracy in women diagnosed with ILC is scant. We aimed to retrospectively evaluate CEM and MRI accuracy in preoperative staging of ILC. MethodsILC cases diagnosed between 2013 and 2021 were collected. For both modalities, tumour diameter was extracted from the reports. Bland-Altman plots were used to assess discrepancies between size measurements according to imaging and histopathological findings. CEM and MRI’s ability to detect multifocal/contralateral cancer was expressed as sensitivity, specificity, and diagnostic odds ratios (DORs). Pairwise comparison of women undergoing both CEM and MRI was not performed. Results305 ILC-cases fulfilled preset inclusion criteria. Mean age was 63.7 years. Preoperative staging was performed using MRI or CEM in 266 (87.2%) and 77 (25.2%) cases, respectively. MRI and CEM overestimated tumour size by 1.5 and 2.1 mm, respectively. Sensitivity to detect multifocal disease was higher for MRI than for CEM (86% versus 78%), but specificity was lower for MRI (79% versus 92%). For detection of contralateral breast cancer, sensitivity for MRI was 96% versus 88% for CEM, and specificity was 92% and 99%, respectively. For both indications, DOR was higher for CEM, but differences were non-significant (p = 0.56 and p = 0.78). ConclusionCEM and MRI overestimate ILC size with comparable systematic and random errors. MRI’s higher sensitivity for detection of multifocal/contralateral cancers is accompanied by lower specificity, but discriminative ability for both modalities was non-significant.

Tumor Size Assessment with Three Breast Imaging Modalities

Background and Objectives: Diagnostic accuracy of breast MR is higher than the routinely used sonomammography and digital mammography. There are mixed reports regarding usefulness of breast MR imaging regarding the tumor size estimation. The objective of this study was to determine which modality can assess the exact tumor dimension in comparison with corresponding tumor dimension at pathologic examinations. Materials and Methods: In a prospective study, 68 patients who came for screening diagnostic mammogram and who had breast lesions of Breast Imaging Reporting and Data System (BIRADS) category 3 and more were evaluated. All patients underwent bilateral digital mammography and targeted high-frequency sonography of the primary lesion. Those patients who were thought to possibly have breast cancer and to be candidates for surgical management were offered bilateral contrast-enhanced breast MRI. Tumor size was evaluated by digital mammography, sonomammography, contrast-enhanced mammography, and compared with histopathology reports. Results: Size of the lesions as measured by DM or SM correlated well with the size determined through breast MR (r = 0.975, P &lt; 0.01). There was a statistically significant difference between the measured sizes of lesions between breast MR and HPE (P = 0.76). Breast MR imaging, true size was overestimated in 28 breasts with range of 0–0.6 cm and underestimated in 25 breasts with range of 0–0.9 cm. Conclusion: Breast MR imaging depicts more accurate dimensions of the tumor and its extensions than digital and sonomammography.

Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images.

Background Reducing the amount of contrast agent needed for contrast-enhanced breast MRI is desirable. Purpose To investigate if generative adversarial networks (GANs) can recover contrast-enhanced breast MRI scans from unenhanced images and virtual low-contrast-enhanced images. Materials and Methods In this retrospective study of breast MRI performed from January 2010 to December 2019, simulated low-contrast images were produced by adding virtual noise to the existing contrast-enhanced images. GANs were then trained to recover the contrast-enhanced images from the simulated low-contrast images (approach A) or from the unenhanced T1- and T2-weighted images (approach B). Two experienced radiologists were tasked with distinguishing between real and synthesized contrast-enhanced images using both approaches. Image appearance and conspicuity of enhancing lesions on the real versus synthesized contrast-enhanced images were independently compared and rated on a five-point Likert scale. P values were calculated by using bootstrapping. Results A total of 9751 breast MRI examinations from 5086 patients (mean age, 56 years ± 10 [SD]) were included. Readers who were blinded to the nature of the images could not distinguish real from synthetic contrast-enhanced images (average accuracy of differentiation: approach A, 52 of 100; approach B, 61 of 100). The test set included images with and without enhancing lesions (29 enhancing masses and 21 nonmass enhancement; 50 total). When readers who were not blinded compared the appearance of the real versus synthetic contrast-enhanced images side by side, approach A image ratings were significantly higher than those of approach B (mean rating, 4.6 ± 0.1 vs 3.0 ± 0.2; P < .001), with the noninferiority margin met by synthetic images from approach A (P < .001) but not B (P > .99). Conclusion Generative adversarial networks may be useful to enable breast MRI with reduced contrast agent dose. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bahl in this issue.

False-positive incidental lesions detected on contrast-enhanced breast MRI: clinical and imaging features.

To identify demographic and imaging features of MRI-detected enhancing lesions without clinical, ultrasound, and mammographic correlation associated with false-positive outcomes, impacting patient care. A retrospective multi-institutional study of imaging studies and patient's chart review of consecutive women with MRI-detected enhancing lesions without clinical, mammogram, or ultrasound correlation between January and December 2018, who underwent MRI-guided biopsy. According to the BI-RADS lexicon, lesions' frequency and imaging features were recorded. The demographic and imaging characteristics variables were correlated with histopathology as the gold standard and an uneventful follow-up of at least one year. Univariate logistic regression analysis was used to explore the correlation between the baseline variables such as age, genetic mutation, family history of breast cancer, personal history of breast cancer, MRI indication, background parenchymal enhancement, and MRI characteristic of the lesion with the false-positive results in main data and subgroup analysis. Two hundred nineteen women (median age 49years; range 26-85years) with 219 MRI-detected enhancing lesions that underwent MRI-guided vacuum-assisted biopsy during the study period fulfilled the study criteria and formed the study cohort. Out of 219, 180 lesions (82.2%) yielded benign pathology results, including 137 benign outcomes (76%) and 43 high-risk lesions (24%). Most demographic and imaging characteristics variables did not help to differentiate malignant from benign lesions. The variables that showed statistically significant association with true-positive results in univariate analyses were age (OR 1.05; 95% CI 1.02-1.08; p = 0.0015), irregular mass-lesion shape when compared with oval/round mass lesion (OR 11.2; 95% CI 1.6-78.4; p = 0.015), and clumped and clustered ring of enhancement when compared with homogeneous (OR 3.22, 95% CI 1.40-7.40; p = 0.0058). For participants with mass breast lesion, the hyperintense signal on the T2-weighted sequence (compared to the normal fibroglandular signal) was significantly related to the false-positive result (OR 0.13; 95% CI 0.02-0.76; p = 0.024). Young patients, oval/round mass-lesion shape, and homogeneous pattern of non-mass enhancement showed the strongest association with false-positive results of enhancing lesions depicted by MRI. For participants with mass breast lesion, T2-bright mass lesion showed significant association with false-positive result. It may impact the patient's management with a suggestion of follow-up rather than interventional procedure when these demographic and imaging parameters are present, consequently decreasing the patient's anxiety and health care costs.

Clinical evaluation of cylindrical regional suppression in dynamic contrast-enhanced breast MRI: An intra-individual comparison study on image quality and lesion conspicuity

PurposeTo evaluate the effect of a cylindrical regional-suppression technique (CREST) on image quality and lesion conspicuity in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast. MethodThis was a comparative study of 67 women with 44 lesions who underwent breast DCE-MRI with CREST (CREST-DCE) and had a previous DCE-MRI without CREST (conv-DCE) available. Two radiologists assessed image quality parameters and lesion conspicuity using five-point Likert scales. In an intra-individual comparison, the effects of CREST on image quality (strong degradation to strong improvement) were assessed. Moreover, both radiologists identified the post-contrast phase, which benefited the most from using CREST in direct comparison. The statistical analysis included the Wilcoxon signed-rank test. ResultsCardiac motion-rated artefacts were significantly reduced in CREST-DCE compared to conv-DCE (3.6 ± 1.2 [CREST-DCE] vs 2.1 ± 0.8 [conv-DCE], p < 0.001). At the axilla, the visualisation of anatomical structures (3.9 ± 1.0 vs 2.3 ± 1.2, p < 0.001) and the skin contour (4.3 ± 0.8 vs 3.0 ± 1.1, p < 0.001) were significantly improved in CREST-DCE, whereas ghosting artefacts were significantly less pronounced (3.8 ± 1.1 vs 2.4 ± 1.0, p < 0.001). The parasternal region was similarly assessable using both techniques (4.3 ± 1.1 vs 4.2 ± 1.2, p = 0.47). In direct comparison, CREST-DCE images were classified as “improved” in 54/67 and “equivalent” in 13/67 exams. The effects of CREST were found to be most pronounced in the very early post-contrast phase (32/67). The lesion conspicuity was rated similar for CREST and conv-DCE (4.7 ± 0.7 vs 4.8 ± 0.2, p = 0.18). ConclusionsCREST appears to be an effective tool to reduce cardiac motion-related artefacts and, therefore, may improve image quality in breast DCE-MRI without impairing lesion conspicuity.

Contrast-Enhanced In-Phase Dixon Sequence: Impact on Biopsy Clip Detection on Breast MRI.

BACKGROUND. Identification of breast biopsy clips using conventional MRI sequences may be challenging. A contrast-enhanced in-phase Dixon sequence may have greater conspicuity for areas of susceptibility compared with standard clinical sequences. OBJECTIVE. The purpose of this article is to compare detection of breast biopsy clips on MRI between the contrast-enhanced in-phase Dixon sequence and three routine clinical sequences. METHODS. This retrospective study included 164 patients (mean age, 50.3 years) with a total of 281 breast biopsy clips who underwent contrast-enhanced breast MRI between January 2, 2019, and April 16, 2020. Three radiologists, blinded to the clip location and sequence used, independently annotated biopsy clip locations on three clinical sequences (T1-weighted non-fat-suppressed [NFS], STIR, and first phase from dynamic contrast-enhanced T1-weighted fat-suppressed [FS]) and on a contrast-enhanced in-phase Dixon sequence and then recorded confidence scores (1-4 scale). A study coordinator used all available imaging and reports to localize clips on MRI, which served as the reference standard. A physicist measured clip CNR. Sequences were compared using the McNemar test and two-tailed Wilcoxon signed rank tests. RESULTS. Among the three readers, pooled sensitivity and PPV were 78.2% and 96.2% for T1-weighted NFS, 26.6% and 92.7% for STIR, 61.7% and 95.9% for contrast-enhanced T1-weighted FS, and 85.1% and 95.1% for contrast-enhanced in-phase Dixon sequence. Pooled sensitivity was higher for contrast-enhanced in-phase Dixon sequence than for the other sequences (all p < .05); pooled PPV was not significantly different between contrast-enhanced in-phase Dixon and the other sequences (all p > .05). Mean confidence scores (pooled across readers for true-positive assessments) and mean CNR were 3.0 ± 0.9 (SD) and 1.21 ± 0.61 for T1-weighted NFS, 1.7 ± 0.9 and 0.57 ± 0.69 for STIR, 2.5 ± 1.0 and 0.54 ± 0.61 for contrast-enhanced T1-weighted FS, and 3.5 ± 0.8 and 4.05 ± 2.6 for the contrast-enhanced in-phase Dixon sequence. Pooled mean confidence scores and CNR were higher for contrast-enhanced in-phase Dixon than for the other sequences (all p < .001). CONCLUSION. Compared with clinical sequences, the contrast-enhanced in-phase Dixon sequence had higher sensitivity for detecting breast biopsy clips on MRI and higher reader confidence and CNR, without change in PPV. CLINICAL IMPACT. The contrast-enhanced in-phase Dixon sequence may help address a current challenge in clinical breast MRI interpretation.

Comparing the Diagnostic Performance of Contrast-Enhanced Mammography and Breast MRI: a Systematic Review and Meta-Analysis.

Background: To provide a systematic review and meta-analysis that evaluates the diagnostic accuracy of contrast-enhanced mammography (CEM) compared to standard contrast-enhanced breast magnetic resonance imaging (breast MRI). Like breast MRI, CEM enables tumour visualization by contrast accumulation. CEM seems to be a viable substitute for breast MRI. Methods: This systematic search assessed the diagnostic accuracy of these techniques in women with suspicious breast lesions on prior imaging or physical examination, who have undergone both breast MRI and CEM. CEM had to be performed on a commercially available system. The MRI sequence parameters had to be described sufficiently to ensure that standard breast MRI sequence protocols were used. Pooled values of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio (DOR), were estimated using bivariate mixed-effects logistic regression modeling. Hierarchical summary receiver operating characteristic curves for CEM and breast MRI were also constructed. Results: Six studies (607 patients with 775 lesions) met the predefined inclusion criteria. Pooled sensitivity was 96% for CEM and 97% for breast MRI. Pooled specificity was 77% for both modalities. DOR was 79.5 for CEM and 122.9 for breast MRI. Between-study heterogeneity expressed as the I2 -index was substantial with values over 80%. Conclusion: Pooled sensitivity was high for both CEM and breast MRI, with moderate specificity. The pooled DOR estimates, however, indicate higher overall diagnostic performance of breast MRI compared to CEM. Nonetheless, current scientific evidence is too limited to prematurely discard CEM as an alternative for breast MRI.

Dynamic Contrast-Enhanced Breast MRI Findings Predictive of Malignancy in MRI-Only Breast Lesions Examined by MR-Guided Biopsy: A Single-Center Experience

Dynamic Contrast-Enhanced Breast MRI Findings Predictive of Malignancy in MRI-Only Breast Lesions Examined by MR-Guided Biopsy: A Single-Center Experience

Tumor-Attentive Segmentation-Guided GAN for Synthesizing Breast Contrast-Enhanced MRI Without Contrast Agents.

Breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a sensitive imaging technique critical for breast cancer diagnosis. However, the administration of contrast agents poses a potential risk. This can be avoided if contrast-enhanced MRI can be obtained without using contrast agents. Thus, we aimed to generate T1-weighted contrast-enhanced MRI (ceT1) images from pre-contrast T1 weighted MRI (preT1) images in the breast. We proposed a generative adversarial network to synthesize ceT1 from preT1 breast images that adopted a local discriminator and segmentation task network to focus specifically on the tumor region in addition to the whole breast. The segmentation network performed a related task of segmentation of the tumor region, which allowed important tumor-related information to be enhanced. In addition, edge maps were included to provide explicit shape and structural information. Our approach was evaluated and compared with other methods in the local (n = 306) and external validation (n = 140) cohorts. Four evaluation metrics of normalized mean squared error (NRMSE), Pearson cross-correlation coefficients (CC), peak signal-to-noise ratio (PSNR), and structural similarity index map (SSIM) for the whole breast and tumor region were measured. An ablation study was performed to evaluate the incremental benefits of various components in our approach. Our approach performed the best with an NRMSE 25.65, PSNR 54.80 dB, SSIM 0.91, and CC 0.88 on average, in the local test set. Performance gains were replicated in the validation cohort. We hope that our method will help patients avoid potentially harmful contrast agents. Clinical and Translational Impact Statement-Contrast agents are necessary to obtain DCE-MRI which is essential in breast cancer diagnosis. However, administration of contrast agents may cause side effects such as nephrogenic systemic fibrosis and risk of toxic residue deposits. Our approach can generate DCE-MRI without contrast agents using a generative deep neural network. Thus, our approach could help patients avoid potentially harmful contrast agents resulting in an improved diagnosis and treatment workflow for breast cancer.

A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer

BackgroundMedical image analysis has evolved to facilitate the development of methods for high-throughput extraction of quantitative features that can potentially contribute to the diagnostic and treatment paradigm of cancer. There is a need for further improvement in the accuracy of predictive markers of response to neo-adjuvant chemotherapy (NAC). The aim of this study was to develop a radiomic classifier to enhance current approaches to predicting the response to NAC breast cancer.MethodsData on patients treated for breast cancer with NAC prior to surgery who had a pre-NAC dynamic contrast enhanced breast MRI were included. Response to NAC was assessed using the Miller–Payne system on the excised tumor. Tumor segmentation was carried out manually under the supervision of a consultant breast radiologist. Features were selected using least absolute shrinkage selection operator regression. A support vector machine learning model was used to classify response to NAC.Results74 patients were included. Patients were classified as having a poor response to NAC (reduction in cellularity < 90%, n = 44) and an excellent response (> 90% reduction in cellularity, n = 30). 4 radiomics features (discretized kurtosis, NGDLM contrast, GLZLM_SZE and GLZLM_ZP) were identified as pertinent predictors of response to NAC. A SVM model using these features stratified patients into poor and excellent response groups producing an AUC of 0.75. Addition of estrogen receptor status improved the accuracy of the model with an AUC of 0.811.ConclusionThis study identified a radiomic classifier incorporating 4 radiomics features to augment subtype based classification of response to NAC in breast cancer.

Abstract IA022: Imaging tools for DCIS: Past, present and future

Abstract In the past, mammography was considered the imaging test of choice to identify DCIS. More recent studies clarified breast MRI is more sensitive than mammography to identify DCIS overall and higher grade DCIS specifically. Techniques to support Fast or Abbreviated MRI were developed to try to support greater access, lower costs, increased patient acceptance of breast MRI in both the screening and the diagnostic setting. In the future, contrast enhanced mammography may provide greater access to more patients to the benefits of vascular imaging of DCIS, benefits previously limited to contrast enhanced breast MRI. Deep learning models in the domain of Artificial Intelligence may support more accurate triage of DCIS lesions more and less likely to progress, supporting more effective triage of low risk DCIS lesions to surveillance. Citation Format: Connie Lehman. Imaging tools for DCIS: Past, present and future [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA022.

Reproducibility assessment of uptake on dedicated breast PET for noise discrimination.

Dedicated breast PET (dbPET) systems have improved the detection of small breast cancers but have increased false-positive diagnoses due to an increased chance of noise detection. This study examined whether reproducibility assessment using paired images helped to improve noise discrimination and diagnostic performance in dbPET. This study included 21 patients with newly diagnosed breast cancer who underwent [18F]FDG-dbPET and contrast-enhanced breast MRI. A 10-min dbPET data scan was acquired per breast, and two sets of reconstructed images were generated (named dbPET-1 and dbPET-2, respectively), each of which consisted of randomly allocated 5-min data from the 10-min data. Uptake spots higher than the background were indexed for the study with visual assessment. All indexed uptakes on dbPET-1 were evaluated using dbPET-2 for reproducibility. MRI findings based on the Breast Imaging-Reporting and Data System (BI-RADS) 2013 were used as the gold standard. Uptake spots that corresponded to BI-RADS 1 on MRI were considered noise, while those with BI-RADS 4b-6 were considered malignancies. The diagnostic performance of dbPET for malignancy was evaluated using four different criteria: any uptake on dbPET-1 regarded as positive (criterion A), a subjective visual assessment of dbPET-1 (criterion B), reproducibility assessment between dbPET-1 and dbPET-2 (criterion C), and a combination of B and C (criterion D). A total of 213 indexed uptake spots were identified on dbPET-1, including 152, 15, 6, 6, and 34 lesions classified as BI-RADS MRI categories 1, 2, 4b, 4c, and 5, respectively. Overall, 31.9% of the index uptake values were reproducible. All malignant lesions were reproducible, whereas 93.4% of noise was not reproducible. The sensitivities for malignancy for criteria A, B, C, and D were 100%, 91.3%, 100%, and 91.3%, respectively, with positive predictive values (PPVs) of 21.4%, 68.9%, 67.6%, and 82.4%, respectively. Our results demonstrated that reproducibility assessment helped reduce false-positive findings caused by noise on dbPET without lowering the sensitivity for malignancy. While subjective visual assessment was also efficient in increasing PPV, it occasionally missed malignant uptake.

Deep Learning to Simulate Contrast-enhanced Breast MRI of Invasive Breast Cancer.

Background There is increasing interest in noncontrast breast MRI alternatives for tumor visualization to increase the accessibility of breast MRI. Purpose To evaluate the feasibility and accuracy of generating simulated contrast-enhanced T1-weighted breast MRI scans from precontrast MRI sequences in biopsy-proven invasive breast cancer with use of deep learning. Materials and Methods Women with invasive breast cancer and a contrast-enhanced breast MRI examination that was performed for initial evaluation of the extent of disease between January 2015 and December 2019 at a single academic institution were retrospectively identified. A three-dimensional, fully convolutional deep neural network simulated contrast-enhanced T1-weighted breast MRI scans from five precontrast sequences (T1-weighted non-fat-suppressed [FS], T1-weighted FS, T2-weighted FS, apparent diffusion coefficient, and diffusion-weighted imaging). For qualitative assessment, four breast radiologists (with 3-15 years of experience) blinded to whether the method of contrast was real or simulated assessed image quality (excellent, acceptable, good, poor, or unacceptable), presence of tumor enhancement, and maximum index mass size by using 22 pairs of real and simulated contrast-enhanced MRI scans. Quantitative comparison was performed using whole-breast similarity and error metrics and Dice coefficient analysis of enhancing tumor overlap. Results Ninety-six MRI examinations in 96 women (mean age, 52 years ± 12 [SD]) were evaluated. The readers assessed all simulated MRI scans as having the appearance of a real MRI scan with tumor enhancement. Index mass sizes on real and simulated MRI scans demonstrated good to excellent agreement (intraclass correlation coefficient, 0.73-0.86; P < .001) without significant differences (mean differences, -0.8 to 0.8 mm; P = .36-.80). Almost all simulated MRI scans (84 of 88 [95%]) were considered of diagnostic quality (ratings of excellent, acceptable, or good). Quantitative analysis demonstrated strong similarity (structural similarity index, 0.88 ± 0.05), low voxel-wise error (symmetric mean absolute percent error, 3.26%), and Dice coefficient of enhancing tumor overlap of 0.75 ± 0.25. Conclusion It is feasible to generate simulated contrast-enhanced breast MRI scans with use of deep learning. Simulated and real contrast-enhanced MRI scans demonstrated comparable tumor sizes, areas of tumor enhancement, and image quality without significant qualitative or quantitative differences. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Slanetz in this issue. An earlier incorrect version appeared online. This article was corrected on January 17, 2023.

Contemporary Nipple-Sparing Mastectomy Technique to Preserve the Internal Mammary Perforator Blood Flow to the Nipple and Analysis of Outcomes

Introduction: Nipple-sparing mastectomy (NSM) with immediate breast reconstruction is commonly performed; however, nipple-areolar complex (NAC) necrosis can represent a devastating complication. This study describes a contemporary NSM technique based on contrast-enhanced breast MRI blood flow data, to preserve the internal mammary artery perforator (IMP) blood supply to the NAC during NSM (IMP-NSM). Methods: A single-surgeon comparative analysis of consecutive patients who underwent IMP-NSM between 2018 and 2020 vs historic control of conventional NSM (performed in 2016 and 2017) was performed. The IMP-NSM surgical technique involves preservation of the IMP blood supply to the NAC with dissection near the sternal border where it perforates the pectoralis major muscle. Clinical outcomes were analyzed with a particular focus on ischemic complication and reoperation for necrosis. Results: Sixty-eight conventional NSM were performed with 19.1% (13/68) developing necrosis (4 partial nipple or areolar, 4 NAC, 5 skin necrosis), which resulted in 9/68 (13.2%) undergoing reoperation for necrosis. In contrast, 114 IMP-NSM were performed based on contrast enhanced breast MRI blood flow patterns. Preoperatively, breast MRI demonstrated IMP dominant NAC blood supply in 91%. In the IMP-NSM cohort, 10.5% (12/114) developed necrosis, of which the majority were partial or resolved non-operatively, with reoperation for necrosis in 3/114 (2.6 %). A significantly lower reoperation rate for necrosis was noted in the IMP-NSM cohort [2.6% vs 13.2%; p = 0.02]. Conclusion: IMP-NSM, a contemporary surgical approach to preserve the dominant vascular supply to the NAC, is associated with significantly lower rates of reoperation for necrosis, thereby improving clinical outcomes.

Nipple Sparing Mastectomy Technique to Reduce Ischemic Complications: Preserving Important Blood Flow Based on Breast MRI.

Nipple-sparing mastectomy (NSM) with immediate breast reconstruction is commonly performed. However, nipple areolar complex (NAC) and mastectomy skin necrosis represent significant complications requiring reoperation and revision. Breast MRI, often obtained for oncologic assessment, can visualize the dominant breast and NAC vascular supply. This study describes the surgical technique utilizing breast MRI blood flow information to preserve important NAC blood supply, thereby, reducing ischemic complications. After IRB approval, a prospectively maintained database of all NSM by a single breast surgeon from 2018 to 2020 formed the study group. Preoperative contrast enhanced Breast MRI analysis determined the dominant NAC blood supply. Intraoperatively, the dominant Internal Mammary Artery Perforator (IMP) to the NAC was preserved (IMP-NSM). The IMP-NSM surgical technique preserving the IMP blood flow, evaluation of breast MRI blood flow patterns, surgical findings, and ischemic complications were analyzed. 114 NSM were performed in 74 patients (mean age: 49years [range, 22-73years], BMI 25.8kg/m2 [range, 19-41kg/m2]). Breast MRI identified the dominant IMP to the NAC in 92%. IMP preservation was successful in 89% (101/114). Necrosis requiring NAC removal occurred in 0.9% (1/114), and skin necrosis reoperation in 1.8% (2/114). Including all post-operative necrosis occurred in 10.5% (12/114), statistically significantly lower compared to the literature for NSM assessing MRI blood flow data without surgical IMP preservation (necrosis 24.4%, p < 0.001) (Bahl et al. in J Am Coll Surg 223(2):279-285, 2016) utilizing Doppler for IMP preservation (necrosis 37%, p < 0.001) (Swistel et al. in Plast Reconstr Surg Glob Open 2(8):e198, 2014) and dividing the IMP in all (necrosis 31.4%, p < 0.001) (Ahn et al. in Eur J Surg Oncol 44(8):1170-1176, 2018). The IMP-NSM surgical technique preserves the dominant blood supply to the NAC, thereby, decreasing ischemic complications.

Contrast-Enhanced Spectral Mammography and tumor size assessment: a valuable tool for appropriate surgical management of breast lesions.

To compare the accuracy of Contrast-Enhanced Spectral Mammography (CESM), MG, US, and breast MRI in estimating the size of breast lesions requiring surgery. The postoperative histology size of the lesion was used as the gold standard. Two hundred thirty-three non-benign lesions in 189 patients were included in the analyses. All the selected patients underwent CESM and at least one other conventional diagnostic exam (US, MG, or MRI). Subsequently, all the patients underwent surgery preceded by cytological/histological examination. The largest diameter of the lesion at imaging was measured by a radiologist with more than 10years' experience and then compared with the size of the lesion in the histological sample at the surgery (gold standard). Among the 233 breast lesions, 196 were evaluated with US, 206 with MG and 160 with MRI. We found no statistically significant differences between size measurements using CESM and MRI compared with the measurements at the surgery (p value 0.63 and 0.51), whereas a significant difference was found for MG and US (p < 0.001). CESM is a reliable method for estimating the size of breast lesions: its performance seems superior to US and MG and comparable to MRI.

An intriguing journey of encapsulated apocrine papillary carcinoma of the breast

BackgroundEncapsulated Apocrine Papillary Carcinoma (EAPC) of the breast are very rare tumors. They usually present as a cystic mass with mural nodule in women aged 44–84 years. Affected patients may be asymptomatic or complain of breast swelling, or nipple discharge. Mammographic features are nonspecific. The tumor appears as a high-density round or oval mass with circumscribed or spiculated margins on mammography. On Ultrasonography (US) a classical lesion appears as predominantly cystic mass with intracystic solid papillary projections and area of vascularity within it. Contrast Enhanced Breast MRI helps to further characterize the lesion by showing intense contrast enhancement in early phase along with washout curve. Histological features of these tumors are similar to those of classical encapsulated papillary neoplasm, in that myoepithelial cells are absent within the papillary structures and at the periphery of the cyst. They show variable degree of cytological atypia and mitotic activity. Such tumors consist of abundant granular eosinophilic cytoplasm and large nuclei with prominent nucleoli and are androgen receptor positive. However, a multidisciplinary approach is crucial for diagnosis and tissue histology is essential to suitably formulate treatment guidelines. Surgical excision is the preferred treating option for these tumors. Little consensus is available about local radiation and adjuvant therapy for the treatment of such tumors, yet they have been reported to have good prognosis.Case presentationThis rare case report describes the intriguing journey towards the diagnosis of an encapsulated intracystic apocrine papillary carcinoma in a 52-year-old premenopausal female who presented with palpable breast swelling in left breast. The patient underwent mammography, breast ultrasound and breast MRI concluding it to be a BIRADS 4A lesion. Then the patient was subjected to trucut core biopsy and finally surgical excision was performed. On Histopathology this lesion was diagnosed as encapsulated apocrine papillary carcinoma with androgen receptor positivity and triple negative hormonal status. At present patient is on regular follow-up.ConclusionsEncapsulated intracystic apocrine papillary carcinoma has a favorable prognosis with low recurrence rate and excellent long-term survival regardless of its invasive nature. Therefore, we present this rare entity to highlight the importance of radiological and histopathology findings in its diagnosis.

Evaluation of the effects of neoadjuvant chemotherapy on probably benign breast lesions with MRI: Report of two cases

In cases with breast cancer, probably benign lesions can also be seen in the other areas of the breast. It is known that neoadjuvant chemotherapy causes morphological changes in the normal breast tissue and the benign lesions, in addition to effects on malignant mass. In cases with complete response with neoadjuvant chemotherapy, probably benign lesions without tissue diagnosis cause a dilemma in the breast conserving surgery plan, when they shrink or disappear at the end of the treatment. We aimed to demonstrate the effects of neoadjuvant chemotherapy in cases with probably benign breast lesions via dynamic contrast enhanced breast MRI.