Breast MRI: EUSOBI recommendations for women's information

Prevalence of Silicone Lymphadenopathy in Women with Breast Implants: A single-center retrospective study

Introduction

Silicone lymphadenopathy (SLA) is a known finding after breast implant surgery. The prevalence of SLA is unknown and therefore its clinical implications are unclear. To make a statement about the clinical importance of SLA, more knowledge on its prevalence is necessary. This study aimed to provide details of SLA prevalence in a single-center.

Methods

This single-center retrospective cohort collected all breast radiology reports from breast or axillary ultrasound (US) and breast MRI exams between 2010 and 2020. These reports were screened for the presence of implant rupture (IR) and/or SLA.

Results

Overall, 1,217 women with silicone breast implants (SBIs) were included over 10 years. This resulted in 1,345 US and 900 MRI reports. In this cohort, 47 women (3.86%) had SLA with intact SBIs, 136 women (11.18) had IR, and 24 (1.97%) had SLA with IR. The sensitivity for IR on US and MRI were 76.2% and 91.7%, respectively. The specificity was 53.8% for IR on US and 66.7% on MRI. These calculations were based on the imaging results of patients whose implants were removed in the MUMC+.

Conclusion

This retrospective cohort provides a single-center ten-year representation of diagnostic imaging of patients with breast implants. The prevalence of SLA in this cohort of women with breast implants is 5.83%. IR increases the risk of developing SLA; however, it can also occur in women with intact SBIs. To our knowledge, this is the first study to report on the prevalence of SLA in patients with SBIs.

Role of Pectoralis Muscle Analysis in Breast Magnetic Resonance Imaging for Body Composition Evaluation Before and After Neoadjuvant Chemotherapy for Breast Cancer

Background: sarcopenia is a physical condition characterized by the loss of muscle mass and strength; it is associated with worse outcomes in oncological diseases and is recognized as an independent predictor of poor survival. The aim of our work is to evaluate the correlation between the pectoralis muscles area (PMA) calculated in breast MRI examinations and the body composition parameters assessed in CT examinations, in order to identify a threshold useful for diagnosing sarcopenia in breast cancer patients who are candidates for neoadjuvant chemotherapy (NACT), so as to be able to provide the correct nutritional counselling. Methods: we included 116 patients with non-metastatic breast cancer, who were studied with MRI before and after NACT, in the 2018-2023 period. All patients were categorized according to age, weight, height, and BMI. Using MRI scans, both before and after treatment, we measured the PMA at the level of the sternal angle of Louis and evaluated the changes caused by NACT, and we performed the same procedure for CT body composition parameters. Results: the ROC we calculated describes the ability of the PMA to discriminate sarcopenic patients from non-sarcopenic ones, identifying an optimal cut-off of 20.55, which achieves a specificity of 92%. The variations in PMA after NACT showed a strong, statistically significant association with the variations in all CT body composition parameters. Conclusions: these results introduce the possibility of also assessing body composition in breast MRI. The novelty in this study is to have estimated, on the basis of these correlations, a cut-off value that reflects the skeletal muscle index threshold for the definition of sarcopenia that is usually used.

A unified circular-polarization metamaterial-inspired resonator for increasing SNR in breast MRI

Magnetic Resonance Imaging (MRI) is crucial for population breast cancer screening. Since almost all MRI machines are equipped with transmit-receive body coils, this configuration of equipment makes MRI readily accessible to breast cancer screening. However, the signal-to-noise ratio (SNR) of breast images is limited by the low sensitivity of the body coil reception and high noise from surrounding tissues. To increase the SNR, we propose a unified circular-polarization metamaterial-inspired resonator (CPMR) for breast MRI at 1.5 T. Most MRI systems utilize birdcage coils as body coils, which produce circularly polarized magnetic fields, but the state-of-the-art resonators can only achieve magnetic field enhancement for linearly polarized fields, or enhance the two linearly polarized components of a circularly polarized magnetic field by using two separate resonators. The proposed CPMR can simultaneously enhance the two orthogonal linearly polarized components of a circularly polarized magnetic field, which will be accomplished by a single integrated resonator. The unified metamaterial-inspired resonator is easier to manufacture and position in an MRI system. The phantom imaging results indicate that, compared with using only the birdcage coil, when performing unilateral and bilateral imaging, the use of CPMR increases the SNR in the region of interest (ROI) by at least 18.4 times and 10.6 times respectively. Compared with using a dedicated breast coil, the SNR in the ROI is increased by at least 48 %.

Diagnostic performance of Kaiser score in the evaluation of breast cancer using MRI: A systematic review and meta-analysis

PURPOSE

To assess the performance of Kaiser score (KS) in detecting and characterizing breast cancer on magnetic resonance imaging (MRI).

METHODS

The protocol was pre-registered at (https://osf.io/83c6j/). We performed a comprehensive search in PubMed, Embase, Cochrane Library, and Web of Science until 30 October 2024 for studies that used KS for detection of breast cancer on MRI. The risk of bias in the included studies was evaluated utilizing Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Diagnostic values of area under the curve (AUC), sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio were calculated using a random-effects bivariate model. Meta-regression was used to explore the source of heterogeneity when I2 was ≥ 50 %. P-value < 0.05 was considered statistically significant.

RESULTS

A total of 29 studies with 7918 patients and 8451 breast lesions were included. The pooled sensitivity, specificity, and AUC of KS for detecting malignant breast lesions on MRI were 95 % (95 % CI = 94 % to 96 %), 70 % (95 % CI = 64 % to 75 %), and 0.94 (95 % CI = 0.91 to 0.96), while for Breast Imaging Reporting and Data System (BI-RADS), they were 97 % (95 % CI = 92 % to 99 %), 46 % (95 % CI = 30 % to 62 %), and 0.89 (95 % CI = 0.86 to 0.91). Sensitivity difference was not statistically significant (p-value = 0.803), but specificity difference was significant (p-value = 0.001). Also, KS demonstrated slightly better diagnostic accuracy for mass lesions with a sensitivity of 96 % (95 % CI = 94 % to 97 %), specificity of 69 % (95 % CI = 60 % to 77 %), and AUC of 0.96 (95 % CI = 0.94 to 0.97) compared to non-mass lesions with 93 % (95 % CI = 88 % to 96 %), 68 % (95 % CI = 58 % to 77 %), and 0.91 (95 % CI = 0.88 to 0.94) values, respectively. KS showed better performance in larger lesions.

CONCLUSION

The KS's superior diagnostic performance compared to BI-RADS, particularly its ability to avoid unnecessary biopsies, makes it valuable for diagnostic and clinical decision-making.

Role of radiomics in predicting early disease recurrence in locally advanced breast cancer patients: integration of radiomic features and RECIST criteria

BACKGROUND

Breast cancer (BC) is a major global health issue with significant heterogeneity among its subtypes. Neoadjuvant treatment (NAT) has been extended to include early BC patients, particularly those with HER2 + and triple-negative subtypes, to achieve pathological complete response and improve long-term outcomes. However, disease recurrence remains a challenge, highlighting the need for predictive biomarkers. This study evaluates the role of radiomics from pre-treatment breast MRI, integrated with clinical and radiological variables, in predicting early disease recurrence (EDR) after NAT.

METHODS

A retrospective analysis was conducted on 238 BC patients treated with NAT and assessed using pre- and post-treatment breast MRI. Radiomic features were extracted and combined with clinical and radiological data to develop predictive models for EDR. Models were evaluated using AUC, accuracy, sensitivity, and specificity metrics.

RESULTS

The radiological-radiomic model, which integrated pre-treatment MRI radiomics with RECIST response data, demonstrated the highest predictive performance for EDR (AUC 0.77, sensitivity 0.85). Internal validation confirmed the robustness of the model.

CONCLUSION

Combining radiomic features from pre-NAT MRI with RECIST response evaluation from post-NAT MRI enhances the prediction of EDR in BC patients, supporting precision medicine in treatment strategies and follow-up planning. Further validation on larger cohorts is needed to confirm these findings.

Benign and Malignant Breast Lesions: Differentiation Using Microstructural Metrics Derived from Time-Dependent Diffusion MRI

Purpose To investigate the diagnostic performance of microstructural metrics from time-dependent diffusion MRI (Td-dMRI) in distinguishing between benign and malignant breast lesions. Materials and Methods This prospective study (ClinicalTrials.gov identifier: NCT05373628) enrolled participants with breast lesions confirmed with US, mammography, or both from January 2022 to June 2023. Participants underwent oscillating and pulsed gradient encoded Td-dMRI and conventional diffusion-weighted imaging (DWI). Td-dMRI data were fitted using the imaging microstructural parameters using limited spectrally edited diffusion model. Lesions were classified as benign or malignant based on pathology. Diagnostic performances of Td-dMRI metrics and apparent diffusion coefficients (ADCs) from DWI in distinguishing between benign and malignant tumors were assessed using receiver operating characteristic analysis and compared using the DeLong test. Results The study included 102 female participants (mean age: 48 years ± 12 [SD]) with 105 breast lesions (three participants had two lesions), including 31 benign and 74 malignant lesions. The cell diameter, cell density, and intracellular volume fraction from Td-dMRI were higher and the ADC was lower in malignant lesions compared with benign lesions (P < .001 to P = .001). Among microstructural metrics from Td-dMRI, the cell density had the highest area under the receiver operating characteristic curve, which was higher than that of the ADC (0.93 [95% CI: 0.88, 0.98] vs 0.79 [95% CI: 0.70, 0.88], P = .03). Conclusion A single microstructural metric derived from Td-dMRI, cell density, had higher performance than conventional ADC in distinguishing benign and malignant breast lesions. Keywords: MR-Diffusion Weighted Imaging, Breast Clinical trial registration no. NCT05373628 Supplemental material is available for this article. © RSNA, 2025.

AI in 2D Mammography: Improving Breast Cancer Screening Accuracy

Background and Objectives: Breast cancer is a leading global health challenge, where early detection is essential for improving survival outcomes. Two-dimensional (2D) mammography is the established standard for breast cancer screening; however, its diagnostic accuracy is limited by factors such as breast density and inter-reader variability. Recent advances in artificial intelligence (AI) have shown promise in enhancing radiological interpretation. This study aimed to assess the utility of AI in improving lesion detection and classification in 2D mammography. Materials and Methods: A retrospective analysis was performed on a dataset of 578 mammographic images obtained from a single radiology center. The dataset consisted of 36% pathologic and 64% normal cases, and was partitioned into training (403 images), validation (87 images), and test (88 images) sets. Image preprocessing involved grayscale conversion, contrast-limited adaptive histogram equalization (CLAHE), noise reduction, and sharpening. A convolutional neural network (CNN) model was developed using transfer learning with ResNet50. Model performance was evaluated using sensitivity, specificity, accuracy, and area under the receiver operating characteristic (AUC-ROC) curve. Results: The AI model achieved an overall classification accuracy of 88.5% and an AUC-ROC of 0.93, demonstrating strong discriminative capability between normal and pathologic cases. Notably, the model exhibited a high specificity of 92.7%, contributing to a reduction in false positives and improved screening efficiency. Conclusions: AI-assisted 2D mammography holds potential to enhance breast cancer detection by improving lesion classification and reducing false-positive findings. Although the model achieved high specificity, further optimization is required to minimize false negatives. Future efforts should aim to improve model sensitivity, incorporate multimodal imaging techniques, and validate results across larger, multicenter prospective cohorts to ensure effective integration into clinical radiology workflows.

Reduction of biopsy rate in BI-RADS4 breast lesions: potential of an abbreviated advanced DWI protocol

OBJECTIVES

This study compared the diagnostic performance of diffusion biomarkers estimated from an abbreviated diffusion-weighted imaging (DWI) protocol and assessed their potential to reduce unnecessary biopsies of benign BI-RADS 4 lesions identified on dynamic contrast-enhanced (DCE) MRI.

METHODS

A retrospective study was conducted from 2019 to 2023. All patients underwent abbreviated DWI at 3 T with four b-values (0 s/mm2, 200 s/mm2, 800 s/mm2, and 1500 s/mm2). Regions of interest were manually placed on DWI, and biomarkers, including the apparent diffusion coefficient (ADC0-800), perfusion fraction intravoxel incoherent motion, non-Gaussian diffusion (ADC0 and kurtosis [K]), signature index (S-index), and shifted ADC (sADC), were estimated. Diagnostic performance and the potential to reduce unnecessary biopsies were evaluated for each parameter.

RESULTS

In total, 168 female patients (mean age ± standard deviation, 56.2 ± 13.5 years) with 178 BI-RADS 4 lesions on DCE MRI were analyzed. The median ADC0-800, sADC, and ADC0 were significantly lower in malignant lesions, while S-index and K were significantly higher (all p ≤ 0.001). The diagnostic performance to reclassify lesions as benign or malignant was identical for ADC0-800 (area under the curve = 0.67), sADC (0.69), S-index (0.69), ADC0 (0.68), and K (0.66). Applying an ad-hoc threshold cutoff, all parameters reduced unnecessary biopsies (around 16%), while K resulted in a slightly higher reduction rate than ADC0-800 (20.5% vs 15.9%, p = 0.317) without reducing sensitivity.

CONCLUSION

Diffusion MRI biomarkers obtained using an abbreviated DWI protocol reduced unnecessary biopsies in BI-RADS 4 lesions, with K performing slightly better than ADC.

KEY POINTS

Question MRI BI-RADS category 4 includes a substantial number of benign lesions, and reducing unnecessary biopsies remains a critical clinical concern. Findings The parameters from abbreviated DWI show lesion differentiation comparable to ADC and have greater potential to reduce unnecessary biopsies. Clinical relevance This study underscores the potential of imaging biomarkers from abbreviated DWI for assessing breast MRI BI-RADS 4 lesions. These biomarkers may be comparable or superior to standard ADC in reducing unnecessary biopsies and could aid in improving patient management decisions.

Breast tumour classification in DCE-MRI via cross-attention and discriminant correlation analysis enhanced feature fusion

AIM

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has proven to be highly sensitive in diagnosing breast tumours, due to the kinetic and volumetric features inherent in it. To utilise the kinetics-related and volume-related information, this paper aims to develop and validate a classification for differentiating benign and malignant breast tumours based on DCE-MRI, though fusing deep features and cross-attention-encoded radiomics features using discriminant correlation analysis (DCA).

MATERIALS AND METHODS

Classification experiments were conducted on a dataset comprising 261 individuals who underwent DCE-MRI including those with multiple tumours, resulting in 137 benign and 163 malignant tumours. To improve the strength of correlation between features and reduce features' redundancy, a novel fusion method that fuses deep features and encoded radiomics features based on DCA (eFF-DCA) is proposed. The eFF-DCA includes three components: (1) a feature extraction module to capture kinetic information across phases, (2) a radiomics feature encoding module employing a cross-attention mechanism to enhance inter-phase feature correlation, and (3) a DCA-based fusion module that transforms features to maximise intra-class correlation while minimising inter-class redundancy, facilitating effective classification.

RESULTS

The proposed eFF-DCA method achieved an accuracy of 90.9% and an area under the receiver operating characteristic curve of 0.942, outperforming methods using single-modal features.

CONCLUSION

The proposed eFF-DCA utilises DCE-MRI kinetic-related and volume-related features to improve breast tumour diagnosis accuracy, but non-end-to-end design limits multimodal fusion. Future research should explore unified end-to-end deep learning architectures that enable seamless multimodal feature fusion and joint optimisation of feature extraction and classification.

The Value of Second-look Ultrasound and Mammography for Assessment and Biopsy of MRI-detected Breast Lesions

RATIONALE AND OBJECTIVES

Suspicious lesions detected in multiparametric breast MRI can be further analyzed with second-look ultrasound (SLUS) and/or mammography. This study aims to assess the value of second-look imaging in selecting the appropriate biopsy method for different lesion characteristics.

MATERIALS AND METHODS

Between January 2021 and December 2023, 212 women underwent contrast-enhanced multiparametric breast MRI at 3 Tesla. A total of 241 suspicious lesions (108 malignancies, 44.8%) were further assessed with SLUS and second-look mammography. Subsequent image-guided biopsy of each lesion was performed using the most suitable modality. Size-dependent lesion detection rates in SLUS and mammography were compared by means of the McNemar test.

RESULTS

Lesions referred to MRI-guided biopsy were predominantly ≤ 10 mm in size (52.8%). SLUS allowed for higher detection rates than mammography in mass lesions (55.6% [95% confidence interval 46.4-64.4%] versus 16.7% [10.6-24.3%]; p < 0.001) with a particularly high sensitivity for malignant mass lesions > 10 mm (88.5% [69.9-97.6%]). In contrast, the detection rate for malignant non-mass lesions was lower in SLUS than in second-look mammography (22.0% [11.5-36.0%] versus 38.0% [24.7-52.8%]; p < 0.001). The malignancy rates in ultrasound-, mammography-, and MRI-guided biopsies were 53.7%, 55.2%, and 35.0%, respectively.

CONCLUSION

SLUS is an excellent tool for further assessment and biopsy of suspicious mass lesions > 10 mm without associated calcifications. In contrast, supplemental ultrasound is of limited value in the evaluation and biopsy guidance of suspicious non-mass lesions compared to second-look mammography.

Diagnostic performance of MRI-guided vacuum-assisted breast biopsy (VABB): an essential but still underused technique

BACKGROUND

Magnetic resonance imaging (MRI)-guided vacuum-assisted breast biopsy (VABB) is an increasingly requested procedure, but it implies training and experience both in its execution and in determining radiological-pathological concordance and is therefore performed in dedicated breast centers. The purpose of this study is to evaluate the diagnostic performance of MRI-guided vacuum-assisted biopsy and to determine the upgrade rate after surgery or follow-up.

METHODS

We retrospectively evaluated all consecutive patients with suspicious MRI findings without corresponding mammographic and ultrasonographic findings who underwent MRI-guided vacuum-assisted breast biopsy (VABB) at our Institution from November 2020 to March 2023. We determined the sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV) and accuracy of the procedure; we also assessed upgrade rate to malignancies using surgery or at least 1-year negative follow-up as reference standard. Fisher's exact test was used to evaluate the correlation between enhancement size and type (mass/non-mass) and histological outcomes.

RESULTS

A total of 121 patients with 122 suspicious breast lesions have been included. 29.5% (n = 36) of these lesions were classified as malignant (B5), 23% (n = 28) were lesions with uncertain malignant potential (B3 lesions), and 47.5% (n =58) were benign (B2). Among B5 lesions, 47.22% (n =17) were ductal carcinomas in situ (DCIS) and 52.77% (n = 19) were invasive carcinomas. Among patients with already diagnosed breast cancer (n = 36), MRI-guided VABB identified additional foci of disease in 36.1% (n = 13) of the cases, specifically 10 foci on the same breast and 3 in the contralateral breast. Accuracy of MRI-guided VABB was 96.7%, SE was 90%, SP was 100%, PPV was 100%, and NPV was 95.3%. 4 benign lesions (B2 and B3) were upgraded to B5 lesions after surgery or follow-up; the upgrade rate to malignancies was 3.28%. Fisher's exact test showed a significant association between enhancement size and histological outcomes (OR = 2.38, p = 0.046), while enhancement type was not significantly correlated (OR = 0.88, p = 0.841). No major complications have been reported.

CONCLUSIONS

MRI-guided VABB has proven to be a mini-invasive, safe, and accurate procedure for the diagnostic work-up of suspected breast lesions, which can help in the management of patients aiding in the correct surgical decisional process.

Multiparametric MRI and transfer learning for predicting positive margins in breast-conserving surgery: a multi-center study

This study aimed to predict positive surgical margins in breast-conserving surgery (BCS) using multiparametric MRI (mpMRI) and radiomics. A retrospective analysis was conducted on data from 444 BCS patients from three Chinese hospitals between 2019 and 2024, divided into four cohorts and five datasets. Radiomics features from preoperative mpMRI, along with clinicopathological data, were extracted and selected using statistical methods and LASSO logistic regression. Eight machine learning classifiers, integrated with a transfer learning (TL) method, were applied to enhance model generalization. The model achieved an AUC of 0.889 in the internal test set and 0.771 in the validation set. Notably, TL significantly improved performance in two external validation sets, increasing the AUC from 0.533 to 0.902 in XAH and from 0.359 to 0.855 in YNCH. These findings highlight the potential of combining mpMRI and TL to provide accurate predictions for positive surgical margins in BCS, with promising implications for broader clinical application across multiple hospitals.

Contrast Agents in Breast MRI: State of the Art and Future Perspectives

Contrast-enhanced magnetic resonance imaging (CE-MRI) has become an essential modality in breast cancer diagnosis and management. It is particularly used for locoregional staging, high-risk screening, monitoring treatment response, and assessing complications related to breast implants. The integration of gadolinium-based contrast agents (GBCAs) enhances the sensitivity and specificity of CE-MRI by providing detailed morphological and functional insights, particularly highlighting tumor neoangiogenesis. Despite its advantages, CE-MRI faces challenges such as high costs, limited accessibility, and concerns about gadolinium retention in tissues, prompting ongoing research into safer, high-relaxivity contrast agents like gadopiclenol. Advances in multiparametric imaging, including dynamic contrast-enhanced sequences and diffusion-weighted imaging, have refined diagnostic accuracy, enabling precise staging, and treatment planning. The introduction of abbreviated breast MRI (AB-MRI) protocols offers a promising solution to barriers of cost and scan duration, maintaining diagnostic efficacy while improving patient accessibility and comfort. Future innovations in contrast agents, imaging protocols, and patient-centered approaches hold the potential to further enhance the utility of breast MRI, ensuring equitable and effective application in global healthcare systems.

Digital mammography with AI-based computer-aided diagnosis to predict neoadjuvant chemotherapy response in HER2-positive and triple-negative breast cancer patients: comparison with MRI

OBJECTIVE

To investigate whether digital mammography (DM) with artificial intelligence-based computer-aided diagnosis (AI-CAD) predicts pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in human epidermal growth factor receptor 2 (HER2)-positive and triple-negative (TN) breast cancers and compare performance with dynamic contrast-enhanced (DCE)-MRI.

MATERIALS AND METHODS

In this single-center study, patients who underwent NAC and surgery for HER2-positive or TN cancers between September 2020 and August 2021 were retrospectively selected to develop prediction models for pCR after NAC. From a prospective ASLAN (Avoid axillary Sentinel Lymph node biopsy After Neoadjuvant chemotherapy) trial, HER2-positive and TN cancer patients who underwent NAC and surgery between December 2021 and July 2022 were prospectively selected for model validation. Clinical-pathologic data and DM and MRI scans were obtained before and after NAC. Logistic regression analyses identified factors associated with pCR for model development and four models (clinical-pathologic, MRI, DM-AI-CAD, and combined) were evaluated.

RESULTS

A total of 259 women (mean age, 53 years ± 10.5 [SD]) constituted the development cohort and 119 (50.8 years ± 11.1) the validation cohort. Age, clinical N stage, estrogen receptor, progesterone receptor, and Ki-67 were incorporated into the clinical-pathologic model. In the validation cohort, the DM-AI-CAD model, applying AI-CAD score ≤ 16 on post-NAC DM as the radiologic CR criterion, showed a higher area under the receiver operating characteristic curve (AUC) compared to the clinical-pathologic model (0.72 vs. 0.62; p = 0.01) for pCR. However, the MRI model showed the highest AUC (0.83), then the combined model (0.78).

CONCLUSION

The model utilizing post-NAC DM with AI-CAD score ≤ 16 predicted pCR more accurately than the clinical-pathologic model in HER2-positive and TN cancers but was inferior to the MRI model.

KEY POINTS

Question The performance of digital mammography (DM) with AI-based computer-aided diagnosis (AI-CAD) for predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) is unclear. Findings The DM-AI-CAD model incorporating AI-CAD score ≤ 16 on post-NAC DM predicted pCR more accurately than the clinical-pathologic model but not the MRI model. Clinical relevance The DM-AI-CAD model has potential to predict pCR after NAC in breast cancer patients for whom MRI is unavailable or contraindicated.

An update on multimodal imaging strategies for nipple discharge: from detection to decision

Nipple discharge affects over 80% of women at some point in their lives, with malignancy detected in up to 23% of cases. This review highlights the shift from traditional surgical approaches to advanced imaging techniques, which enhance diagnostic accuracy and reduce unnecessary procedures. Diagnosis begins with a thorough medical history and physical examination to assess the need for imaging. Physiological nipple discharge, which is bilateral, multiductal, and non-spontaneous, typically requires no imaging. Conversely, pathological nipple discharge (PND), characteristically unilateral, uniductal, and spontaneous, requires imaging to rule out malignancy. Bloody PND is frequently associated with breast cancer, and up to 12% of non-bloody PND cases also involve malignancy. For women over 40 years, the first-line imaging modality is full-field digital mammography (FFDM) or digital breast tomosynthesis (DBT), usually combined with ultrasound (US). Men with PND undergo FFDM/DBT starting at age 25 years due to their higher risk of breast cancer. For women aged 30-39 years, US is the first assessment tool, with FFDM/DBT added, if necessary, while US is preferred for younger women and men. When initial imaging is negative or inconclusive, magnetic resonance imaging (MRI) is useful, often replacing galactography. With its high sensitivity and negative predictive value of almost 100%, a negative MRI can often obviate the need for surgery. Contrast-enhanced mammography (CEM) offers a viable alternative when MRI is not feasible. Although invasive, ductoscopy helps identify patients who may not require duct excision. This review consolidates the latest evidence and proposes an updated diagnostic algorithm for managing PND effectively. CRITICAL RELEVANCE STATEMENT: Effective management of nipple discharge requires recognising when imaging tests are needed and selecting the most appropriate diagnostic technique to rule out malignancy and avoid unnecessary interventions. KEY POINTS: First-line imaging for pathological nipple discharge (PND) assessment includes ultrasound and mammography. MRI is recommended for patients with PND and negative conventional imaging. A negative MRI is sufficient to justify surveillance rather than surgery. Contrast-enhanced mammography (CEM) is an alternative when MRI is unavailable or contraindicated.

Can structured integration of BI-RADS criteria by a clinical decision rule reduce the number of unnecessary biopsies in BI-RADS 4 lesions? A systematic review and meta-analysis

AIM

This systematic review and meta-analysis investigate the added value of structured integration of Breast Imaging Reporting and Data System (BI-RADS) criteria using the Kaiser score (KS) to avoid unnecessary biopsies in BI-RADS 4 lesions.

MATERIAL AND METHODS

A systematic review and meta-analysis were conducted using predefined criteria. Eligible articles, published in English until May 2024, dealt with KS in the context of BI-RADS 4 MRI. Two reviewers extracted study characteristics, including true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN). Sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio were calculated using bivariate random effects. Fagan nomograms identified the maximum pre-test probability at which post-test probabilities of a negative MRI aligned with the 2% malignancy rate benchmark for downgrading BI-RADS 4 to BI-RADS 3. I² statistics and meta-regression explored sources of heterogeneity. p-values < 0.05 were considered significant.

RESULTS

Seven studies with 1877 lesions (833 malignant, 1044 benign) were included. The average breast cancer prevalence was 47.3%. Pooled sensitivity was 94.3% (95%-CI 88.9%-97.1%), and pooled specificity was 68.1% (95%-CI 56.6%-77.7%) using a random effects model. Overall, 52/833 cases were FNs (6.2%). Fagan nomograms showed that KS could rule out breast cancer in BI-RADS 4 lesions at a pre-test probability of 20.3% for all lesions, 25.4% for masses, and 15.2% for non-mass lesions.

CONCLUSIONS

In MRI-assessed BI-RADS 4 lesions, applying structured BI-RADS criteria with the KS reduces unnecessary biopsies by 70% with a 6.2% FN rate. Breast cancer can be ruled out up to pre-test probabilities of 20.3%.

KEY POINTS

Question What, if any, value is added by structured integration of BI-RADS criteria using the Kaiser Score (KS) to avoid unnecessary biopsies in BI-RADS 4 lesions? Findings The structured integration of BI-RADS criteria using the Kaiser Score (KS) reduces unnecessary biopsies in BI-RADS 4 lesions by 70%. Clinical relevance The structured approach offered by the Kaiser Score (KS) avoids unnecessary recalls, potentially reducing patient anxiety, lessening the burden on medical personnel, and the need for further imaging and biopsies due to more objective and thus efficient clinical decision-making in evaluating BI-RADS 4 lesions.

[Importance of parametric and molecular imaging for therapeutic management of breast cancer]

BACKGROUND

In recent years, various magnetic resonance (MRI) and positron emission tomography (PET) parameters have been investigated in breast cancer. Parametric imaging focuses on the visualization and quantification of biological, physiological, and pathological processes at the cellular and molecular level. It therefore provides important insights into the key processes in carcinogenesis and tumor progression. This article aims to illustrate the importance for the management of breast cancer.

MATERIALS AND METHODS

Based on the current literature, an overview of the current state of parametric breast imaging and its importance in therapy management is given. Moreover, future opportunities and challenges are highlighted.

RESULTS

Parametric imaging in breast cancer includes MRI, nuclear medicine procedures such as PET, the combination of different techniques (PET-CT, PET-MRI) and the use of specific radiotracers. Parametric MRI of the breast mainly uses T2 and diffusion-weighted imaging (DWI) as well as dynamic contrast-enhanced MRI (CM-MRI). Quantitative and qualitative imaging biomarkers provide insights into tumor biology and allow conclusions to be drawn about the molecular subtype or prognosis.

CONCLUSIONS

Recently, parametric imaging has become established in breast diagnostics. It is constantly evolving and will continue to gain in importance in the forthcoming years. It offers the opportunity to improve the diagnosis and treatment management of breast cancer.

Preoperative breast MRI reduces reoperations for unilateral invasive lobular carcinoma: a patient-matched analysis from the MIPA study

OBJECTIVES

To investigate the surgical impact of preoperative breast MRI in patients diagnosed with invasive lobular breast cancer (ILC) in a prospective observational study.

METHODS

The prospective MIPA observational study database was queried for patients aged 18-80 with newly diagnosed unilateral ILC at needle biopsy referred for primary surgery. Patients who underwent preoperative MRI (MRI group) were matched (1:1) with those who did not (noMRI group) according to nine confounding covariates. Surgical outcomes were compared between the matched groups with nonparametric statistics after calculating odds ratios (ORs).

RESULTS

A total of 547 women with unilateral needle biopsy-diagnosed ILC were identified (158 noMRI group, 389 MRI group). After patient matching, each group retained 103 patients, for a total of 206 matched patients. For the rate of women having a first-line mastectomy, there was no significant difference between the MRI group (21.4%, 22/103; p = 0.727; OR 1.20, 95% CI: 0.61-2.38) and the noMRI group (18.4%, 19/103). Conversely, the reoperation rate in the MRI group (1.9%, 2/103) was significantly lower (p = 0.007; OR of avoiding reoperation 7.29, 95% CI: 1.60-33.21) than in the noMRI group (12.6%, 13/103 patients). Overall mastectomy rates (first plus second-line) did not significantly differ between the MRI group (23.3%, 24/103; p = 0.867, OR 1.12, 95% CI: 0.58-2.16) and the noMRI group (21.4%, 22/103).

CONCLUSIONS

Women who had preoperative MRI after a needle biopsy diagnosis of ILC had a significant six-fold reduction in reoperations compared to those who did not have an MRI examination, with similar overall mastectomy rates.

KEY POINTS

Question No randomized controlled trials investigating the impact of preoperative MRI on surgical outcomes (mastectomy rates and reoperation) of needle-biopsy-diagnosed ILC have been conducted. Findings In a patient-matched analysis of 103 vs 103 women, preoperative MRI led to a greater than six-fold reduction of reoperations, without significant differences in first-line and overall mastectomy rates. Clinical relevance In the absence of randomized controlled trials, patient matching can be applied to mitigate confounding factors that drive the referral to preoperative MRI, showing that preoperative MRI has beneficial effects on surgical outcomes in patients with needle biopsy-diagnosed unilateral ILC.

Deep learning model for the early prediction of pathologic response following neoadjuvant chemotherapy in breast cancer patients using dynamic contrast-enhanced MRI

Purpose

This study aims to investigate the diagnostic accuracy of various deep learning methods on DCE-MRI, in order to provide a simple and accessible tool for predicting pathologic response of NAC in breast cancer patients.

Methods

In this study, we enrolled 313 breast cancer patients who had complete DCE-MRI data and underwent NAC followed by breast surgery. According to Miller-Payne criteria, the efficacy of NAC was categorized into two groups: the patients achieved grade 1-3 of Miller-Payne criteria were classified as the non-responders, while patients achieved grade 4-5 of Miller-Payne criteria were classified as responders. Multiple deep learning frameworks, including ViT, VGG16, ShuffleNet_v2, ResNet18, MobileNet_v2, MnasNet-0.5, GoogleNet, DenseNet121, and AlexNet, were used for transfer learning of the classification model. The deep learning features were obtained from the final fully connected layer of the deep learning models, with 256 features extracted based on DCE-MRI data for each patient of each deep learning model. Various machine-learning techniques, including support vector machine (SVM), K-nearest neighbor (KNN), RandomForest, ExtraTrees, XGBoost, LightGBM, and multiple-layer perceptron (MLP), were employed to construct classification models.

Results

We utilized various deep learning models to extract features and subsequently constructed machine learning models. Based on the performance of different machine learning models' AUC values, we selected the classifiers with the best performance. ResNet18 exhibited superior performance, with an AUC of 0.87 (95% CI: 0.82 - 0.91) and 0.87 (95% CI: 0.78 - 0.96) in the train and test cohorts, respectively.

Conclusions

Using pre-treatment DCE-MRI images, our study trained multiple deep models and developed the best-performing DLR model for predicting pathologic response of NAC in breast cancer patients. This prognostic tool provides a dependable and impartial basis for effectively identifying breast cancer patients who are most likely to benefit from NAC before its initiation. At the same time, it can also identify those patients who are insensitive to NAC, allowing them to proceed directly to surgical treatment and prevent the risk of losing the opportunity for surgery due to disease progression after NAC.

Radiomics Integration of Mammography and DCE-MRI for Predicting Molecular Subtypes in Breast Cancer Patients

Background

Accurate identification of the molecular subtypes of breast cancer is essential for effective treatment selection and prognosis prediction.

Aim

This study aimed to evaluate the diagnostic performance of a radiomics model, which integrates breast mammography and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the molecular subtypes of breast cancer.

Methods

We retrospectively included 462 female patients with pathologically confirmed breast cancer, including 53 cases of triple-negative, 94 cases of HER2 overexpression, 95 cases of luminal A, and 215 cases of luminal B breast cancer. Radiomics analysis was performed using FAE software, wherein the radiomic features were examined about the hormone receptor status. The performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC) and accuracy.

Results

In multivariate analysis, radiomic features were the only independent predictive factors for molecular subtypes. The model that incorporates multimodal fusion features from breast mammography and DCE-MRI images exhibited superior overall performance compared to using either modality independently. The AUC values (or accuracies) for six pairings were as follows: 0.648 (0.627) for luminal A vs luminal B, 0.819 (0.793) for luminal A vs HER2 overexpression, 0.725 (0.696) for luminal A vs triple-negative subtype, 0.644 (0.560) for luminal B vs HER2 overexpression, 0.625 (0.636) for luminal B vs triple-negative subtype, and 0.598 (0.500) for triple-negative subtype vs HER2 overexpression.

Conclusion

The radionics model utilizing multimodal fusion features from breast mammography combined with DCE-MRI images showed high performance in distinguishing molecular subtypes of breast cancer. It is of significance to accurately predict prognosis and determine treatment strategy of breast cancer by molecular classification.

A nomogram based on multiparametric magnetic resonance imaging improves the diagnostic performance of breast lesions diagnosed as BI-RADS category 4: A comparative study with the Kaiser score

PURPOSE

To construct a nomogram combining Kaiser score (KS), synthetic MRI (syMRI) parameters, apparent diffusion coefficient (ADC), and clinical features to distinguish benign and malignant breast lesions better.

METHODS

From December 2022 to February 2024, a retrospective cohort of 168 patients with breast lesions diagnosed as Breast Imaging Reporting and Data System (BI-RADS) category 4 by ultrasound and/or mammography was included. The research population was divided into the training set (n = 117) and the validation set (n = 51) by random sampling with a ratio of 7:3. Breast lesions' KS, ADC, relaxation time of syMRI, and clinical and imaging features were statistically analyzed and compared between malignant and benign groups. Two experienced radiologists independently assigned KS, and measured quantitative values of ADC and parameters of syMRI, and the intraclass correlation coefficient (ICC) was calculated. Independent predictors were identified by univariable and multivariable logistic regression analysis. Then, a nomogram was established, and its performance was evaluated by the area under the curve (AUC), calibration curve, and decision curve.

RESULTS

There were 168 lesions (118 malignant and 50 benign) in 168 female patients confirmed by histopathology. The interobserver agreement for each quantitative parameter was excellent. Older patient (OR = 1.091, 95 % confidence interval [CI]: 1.017-1.170, P = 0.014), higher lesions' KS (OR = 288.431, 95 % CI: 34.930-2381.654, P < 0.001), lower ADC (OR = 0.077, 95 % CI: 0.011-0.558, P = 0.011), and lower T2 relaxation time (OR = 0.918, 95 % CI: 0.868-0.972, P = 0.003) were independent predictors of breast malignancies and utilized to establish the nomogram. The accuracy of KS, ADC, T2, and patient age in predicting malignant breast lesions was 88.89 %, 79.48 %, 82.05 %, and 58.97 %, respectively. No significant differences in AUCs of KS, ADC and T2 were observed in distinguishing benign from malignant breast lesions. The nomogram yielded higher AUCs of 0.968 (0.934-0.996) and 0.959 (0.863-0.995) in training and validation sets than KS, ADC, T2, and patient age (p < 0.05).

CONCLUSION

Although there were no significant differences among the AUCs of KS, ADC, and T2, the constructed nomogram incorporating these parameters significantly improves diagnostic performance for distinguishing benign and malignant BI-RADS 4 breast lesions. Future external validation is needed in practical applications.

Breast MRI to Screen Women With Extremely Dense Breasts

Women with extremely dense breasts are at a higher risk of breast cancer, and the sensitivity of mammography in this group is reduced due to the masking effect of overlapping tissue. This review examines supplemental screening methods to improve detection in this population, with a focus on MRI. Morphologic techniques offer limited benefits, digital breast tomosynthesis (DBT) shows inconsistent results, and ultrasound (US), while improving cancer detection rates (CDR), results in a higher rate of false positives. Functional imaging techniques show better performance, molecular breast imaging increases CDR but is limited in availability, and contrast-enhanced mammography is promising, with good results and as an accessible technique, but requires further validation. MRI, with sensitivity ranging from 81% to 100%, is the most supported modality. Despite strong evidence for MRI in this population, high costs, use of contrast, and longer scan times hinder widespread use. Abbreviated MRI protocols aim to overcome these barriers by reducing costs and scan duration. As personalized screening becomes a future focus, MRI remains the most effective option for women with extremely dense breasts. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 5.

MRI biomarkers and their correlation with the Oncotype DX test

Breast cancer (BC) has high rates of incidence and prevalence, causing significant impact in our society. Magnetic resonance imaging (MRI) plays a crucial role in its detection and staging. The Oncotype DX Breast Recurrence Score (ODXRS) test can be used to guide decision making regarding adjuvant chemotherapy (CT) in early-stage luminal BC to allow for more tailored cancer treatment. The aim of this article is to review knowledge regarding MRI biomarkers to date according to the BI-RADS® classification and the use of artificial intelligence (AI) in this imaging technique to establish its correlation with the ODXRS test. The latest studies published on AI and MRI present promising findings, and their standardisation could mark a turning point in breast radiology.

Breast lesions on MRI in mass and non-mass enhancement: Kaiser score and modified Kaiser score + for readers of variable experience

OBJECTIVES

To compare the diagnostic performance of three readers using BI-RADS and Kaiser score (KS) based on mass and non-mass enhancement (NME) lesions.

METHODS

A total of 630 lesions, 393 malignant and 237 benign, 458 mass and 172 NME, were analyzed. Three radiologists with 3 years, 6 years, and 13 years of experience made diagnoses. 596 cases had diffusion-weighted imaging, and the apparent diffusion coefficient (ADC) was measured. For lesions with ADC > 1.4 × 10-3 mm2/s, the KS was reduced by 4 as the modified KS +, and the benefit was assessed.

RESULTS

When using BI-RADS, AUC was 0.878, 0.915, and 0.941 for mass, and 0.771, 0.838, 0.902 for NME for Reader-1, 2, and 3, respectively, better for mass than for NME. The diagnostic accuracy of KS was improved compared to BI-RADS for less experienced readers. For Reader-1, AUC was increased from 0.878 to 0.916 for mass (p = 0.005) and from 0.771 to 0.822 for NME (p = 0.124). Based on the cut-off value of BI-RADS ≥ 4B and KS ≥ 5 as malignant, the sensitivity of KS by Readers-1 and -2 was significantly higher for both Mass and NME. When ADC was considered to change to modified KS +, the AUC and the accuracy for all three readers were improved, showing higher specificity with slightly degraded sensitivity.

CONCLUSION

The benefit of KS compared to BI-RADS was most noticeable for the less experienced readers in improving sensitivity. Compared to KS, KS + can improve specificity for all three readers. For NME, the KS and KS + criteria need to be further improved.

CLINICAL RELEVANCE STATEMENT

KS provides an intuitive method for diagnosing lesions on breast MRI. BI-RADS and KS face greater difficulties in evaluating NME compared to mass lesions. Adding ADC to the KS can improve specificity with slightly degraded sensitivity.

KEY POINTS

KS provides an intuitive method for interpreting breast lesions on MRI, most helpful for novice readers. KS, compared to BI-RADS, improved sensitivity in both mass and NME groups for less experienced readers. NME lesions were considered during the development of the KS flowchart, but may need to be better defined.

Interhospital variations in diagnostic work-up following recall at biennial screening mammography-a population-based study

OBJECTIVES

Quality control in breast cancer screening programmes has been subject of several studies. However, less is known about the clinical diagnostic work-up in recalled women with a suspicious finding at screening mammography. The current study focuses on interhospital differences in diagnostic work-up strategies.

MATERIALS AND METHODS

In this retrospective analysis, using a prospectively obtained database, we included 17,809 women who participated in the Dutch national screening programme between 2009 and 2019 and were recalled to a hospital for analysis of a suspicious mammographic abnormality. The diagnostic work-up (e.g., type and frequency of additional imaging and biopsy) in the different hospitals were compared and analysed by multivariable analysis to correct for confounders.

RESULTS

Use of biopsy varied from 36.7% to 48.7% (p < 0.001) between hospitals, and the use of problem-solving magnetic resonance imaging (MRI) from 2.1% to 6.9% (p < 0.001). These interhospital differences remained after correction for patients and tumour characteristics. The percentage of women with a delayed breast cancer diagnosis, defined as histopathological confirmation of breast cancer more than three months after recall or first analysis in the hospital, varied from 2.7% to 6.1% between hospitals (p = 0.07).

CONCLUSIONS

In our screening region interhospital differences were observed in diagnostic work-up following recall at biennial screening mammography. Though statistically significant, absolute differences were small, and therefore, their clinical impact appears to be limited.

KEY POINTS

Question It is unclear how diagnostic work-up strategies vary between hospitals for women recalled after suspicious findings in breast cancer screening. Findings Significant differences in biopsy techniques and the use of problem-solving MRI were observed, though the clinical impact of these variations is likely to be marginal. Clinical relevance Evaluation of interhospital variation in the diagnostic work-up strategies after recall may aid in optimising the quality of breast cancer care and, indirectly, the effectiveness of the screening programme.

The verification of the utility of a commercially available phantom combination for quality control in contrast-enhanced mammography

Contrast-enhanced mammography is being increasingly implemented clinically, providing much improved contrast between tumour and background structures, particularly in dense breasts. Although CEM is similar to conventional mammography it differs via an additional exposure with high energy X-rays (≥ 40 kVp) and subsequent image subtraction. Because of its special operational aspects, the CEM aspect of a CEM unit needs to be uniquely characterised and evaluated. This study aims to verify the utility of a commercially available phantom set (BR3D model 020 and CESM model 022 phantoms (CIRS, Norfolk, Virginia, USA)) in performing key CEM performance tests (linearity of system response with iodine concentration and background subtraction) on two models of CEM units in a clinical setting. The tests were successfully performed, yielding results similar to previously published studies. Further, similarities and differences in the two systems from different vendors were highlighted, knowledge of which may potentially facilitate optimisation of the systems.

Are background breast parenchymal features on preoperative breast MRI associated with disease-free survival in patients with invasive breast cancer?

OBJECTIVE

To evaluate whether breast parenchymal features of the contralateral breast on preoperative MRI are associated with primary breast cancer characteristics and disease-free survival (DFS) in women with invasive breast cancer.

MATERIALS AND METHODS

Women with newly diagnosed invasive breast cancer who underwent preoperative breast MRI followed by surgery were retrospectively evaluated. Background parenchymal enhancement (BPE) on dynamic contrast-enhanced MRI and background diffusion signal (BDS) on diffusion-weighted MRI of the contralateral breast were qualitatively assessed using a four-category scale: minimal, mild, moderate, or marked. Primary breast cancer characteristics were compared based on the degree of BPE or BDS. Cox proportional hazards models were used to evaluate the association between MRI parenchymal features and DFS after adjusting for clinicopathologic features.

RESULTS

A total of 515 women (mean age, 54 years) were included. Of whom, 46 (8.9%) patients who developed disease recurrence at a median follow-up of 60 months were observed. A high level (moderate/marked) of BPE or BDS was associated with younger age (≤ 45) and premenopausal status (all P < 0.05) compared to a low level (minimal/mild), but it was not associated with primary cancer characteristics such as tumor stage, grade, or subtype. Multivariable Cox proportional hazards analysis demonstrated that larger tumor size (> 2 cm) (hazard ratio [HR], 3.877; P < . 001), triple-negative subtype (HR, 2.440; P = .013), and axillary node metastasis (HR, 1.823; P = .049) were associated with worse DFS. No associations were observed between background parenchymal features and disease outcomes.

CONCLUSIONS

MRI parenchymal features, including BPE and BDS, of the contralateral breast showed no associations with primary breast cancer characteristics or DFS in women with invasive breast cancer.

Prospective Study of Supplemental Screening With Contrast-Enhanced Mammography in Women With Elevated Risk of Breast Cancer: Results of the Prevalence Round

PURPOSE

Contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) have shown similar diagnostic performance in detection of breast cancer. Limited CEM data are available for high-risk breast cancer screening. The purpose of the study was to prospectively investigate the efficacy of supplemental screening CEM in elevated risk patients.

MATERIALS AND METHODS

A prospective, single-institution, institutional review board-approved observational study was conducted in asymptomatic elevated risk women age 35 years or older who had a negative conventional two-dimensional digital breast tomosynthesis screening mammography (MG) and no additional supplemental screening within the prior 12 months.

RESULTS

Four hundred sixty women were enrolled from February 2019 to April 2021. The median age was 56.8 (range, 35.0-79.2) years; 408 of 460 (88.7%) were mammographically dense. Biopsy revealed benign changes in 22 women (22/37, 59%), high-risk lesions in four women (4/37, 11%), and breast cancer in 11 women (11/37, 30%). Fourteen cancers (10 invasive, tumor size range 4-15 mm, median 9 mm) were diagnosed in 11 women. The overall supplemental cancer detection rate was 23.9 per 1,000 patients, 95% CI (12.0 to 42.4). All cancers were grade 1 or 2, ER+ ERBB2-, and node negative. CEM imaging screening offered high specificity (0.875 [95% CI, 0.844 to 0.906]), high NPV (0.998 [95% CI, 0.993 to 1.000), moderate PPV1 (0.164 [95% CI, 0.076 to 0.253), moderate PPV3 (0.275 [95% CI, 0.137 to 0.413]), and high sensitivity (0.917 [95% CI, 0.760 to 1.000]). At least 1 year of imaging follow-up was available on all patients, and one interval cancer was detected on breast MRI 4 months after negative screening CEM.

CONCLUSION

A pilot trial demonstrates a supplemental cancer detection rate of 23.9 per 1,000 in women at an elevated risk for breast cancer. Larger, multi-institutional, multiyear CEM trials in patients at elevated risk are needed for validation.

Contrast Enhancement in Breast Cancer: Magnetic Resonance vs. Mammography: A 10-Year Systematic Review

PURPOSE

Contrast Enhancement Magnetic Resonance (CEMR) and Contrast-Enhanced Mammography (CEM) are important diagnostic tools to evaluate breast cancer patients, and both are objects of interest in the literature. The purpose of this systematic review was to select publications from the last ten years in order to evaluate the literature contributions related to the frequency of contrast agents used, administration techniques and the presence of adverse reactions.

METHODS

We have selected, according to the PRISMA statement, publications reviewed on Pub Med in the period from 1 January 2012 to 31 December 2022. The search engine was activated using the following keywords: "CESM", "CEM", "CEDM", "Contrast mammography" for CEM, "DCE-MRI", "Contrast Enhancement MRI" for CEMR, excluding reviews, book chapters and meta-analyses. From the total number of publications, we made a preliminary selection based on titles and abstracts and excluded all articles published in languages other than English and all experimental studies performed on surgical specimen or animal population, as well as all articles for which the extended version was not available. Two readers evaluated all the articles and compiled a pre-compiled form accordingly.

RESULTS

After a preliminary collection of 571 CEM publications, 118 articles were selected, relating to an overall population of 21,178 patients. From a total of 3063 CEMR publications, 356 articles relating to an overall population of 45,649 patients were selected. The most used contrast agents are Iohexol for CEM (39.83%) and Gadopentetic acid (Gd-DTPA) for CEMR (32.5%). Regarding the CEM contrast administration protocol, in 84.7% of cases a dose of 1.5 mL/kg was used with an infusion rate of 2-3 mL/s. Regarding the CEMR infusion protocol, in 71% of cases a dose of 1 mmol/kg was used at an infusion rate of 2-4 mL/s. Twelve out of 118 CEM articles reported allergic reactions, involving 29 patients (0.13%). In DCE-MRI, only one out of 356 articles reported allergic reactions, involving two patients (0.004%). No severe reactions were observed in either cohort of exams.

CONCLUSIONS

CEM and CEMR are essential contrast methods to evaluate breast diseases. However, from the literature analysis, although there are preferences on the uses of the contrast agent (Iohexol for CESM, G-DTPA for CEMR), a wide range of molecules are still used in contrast methods, with different administration protocols. Based on the collected data, it is possible to state that both methods are safe, and no severe reactions were observed in our evaluation.

MR-contrast enhanced mammography (CEM) for follow-up of breast cancer patients: a "pros and cons" debate

Women with a personal history of breast cancer (PHBC) are at an increased risk of either a local recurrence or a new primary breast cancer. Thus, surveillance is essential for the detection of recurrent disease at the earliest possible stage, allowing for prompt treatment, and potentially improving overall survival. Nowadays, mammography follow-up is the only surveillance imaging technique recommended by international guidelines. Nevertheless, sensitivity of mammography is lower after breast cancer treatment, particularly during the first 5 years, due to increased density or post-treatment changes. Contrast-enhanced breast imaging techniques, such as MRI or contrast-enhanced mammography (CEM), are very sensitive to detect malignant enhancement, especially in dense breasts. This Special Report will provide arguments in favor of and against breast cancer follow-up with MRI or CEM, in a debate style between experts in Breast Imaging. Finally, the scientific points of pros and cons arguments will be summarized to help objectively decide the best follow-up strategy for women with a personal history of breast cancer. CLINICAL RELEVANCE STATEMENT: A personalized approach to follow-up imaging after conservative breast cancer treatment could optimize patient outcomes, using mammography as a baseline for most patients, and MRI or CEM selectively in patients with higher risks for a recurrence. KEY POINTS: • Women with a personal history of breast cancer are at an increased risk of either a local recurrence or a new primary breast cancer. • Breast cancer survivors may benefit from additional imaging with MRI/CEM, in case of increased risk of a second breast cancer, with dense breasts or a cancer diagnosis before age 50 years. • As survival after local recurrence seems to depend on the initial stage at diagnosis, imaging should be more focused on detecting tumors in the earliest stages.

Breast Biopsy Procedure Toolkit: Ultrasound, 2D Stereotactic, 3D Tomosynthesis, and MRI-Guided Procedures

This article explores various techniques and tips for performing successful percutaneous biopsies of the breast and axillary lymph nodes using different imaging modalities. The discussion includes detailed image guidance on ultrasound-guided, stereotactic/tomosynthesis-guided, and MRI-guided biopsies. Advice for draining fluid collections in the breast is also reviewed. Key findings include the comparative effectiveness of different imaging techniques and practical advice for improving procedural outcomes. This information is particularly relevant for radiologists involved in diagnostic and interventional breast care. Recommendations for optimizing biopsy procedures and managing complications are also presented.

Evaluating persistent T1-weighted lesions without concurrent abnormal enhancement on breast MRI in neoadjuvant chemotherapy patients: implications for complete pathological response

OBJECTIVE

This study aims to determine whether persistent T1-weighted lesions signify a complete pathological response (pCR) in breast cancer patients treated with neoadjuvant chemotherapy and surgery, and to evaluate their correlation with imaging responses on MRI.

MATERIALS AND METHODS

A retrospective review was conducted on data from breast cancer patients treated between January 2011 and December 2018. Patients who underwent breast MRI and pre- and post-neoadjuvant chemotherapy followed by surgery were included. Those with distant metastasis, no planned surgery, pre-surgery radiation, ineligibility for neoadjuvant chemotherapy, or unavailable surgical pathology were excluded. Groups with and without persistent T1-weighted lesions were compared using the chi-square test for categorical variables and the Student t test or Wilcox rank sum test for continuous variables. Univariate logistic regression was used to evaluate the association of the final pathological response with the presence of T1-persistent lesion and other characteristics.

RESULTS

Out of 319 patients, 294 met the inclusion criteria (breast cancer patients treated with neoadjuvant chemotherapy and subsequent surgery); 157 had persistent T1 lesions on post-chemotherapy MRI and 137 did not. A persistent T1 lesion indicated reduced likelihood of complete pathological response (14% vs. 39%, p < 0.001) and imaging response (69% vs. 93%, p < 0.001). Multivariable analysis confirmed these findings: OR 0.37 (95% CI 0.18-0.76), p = 0.007. No other characteristics correlated with T1 residual lesions.

CONCLUSION

Persistent T1-weighted lesions without associated abnormal enhancement on post-treatment breast MRI correlate with lower complete pathological and imaging response rates.

CLINICAL RELEVANCE STATEMENT

The study underscores the importance of persistent T1-weighted lesions on breast MRI as vital clinical markers, being inversely related to a complete pathological response following neoadjuvant chemotherapy; they should be a key factor in guiding post-neoadjuvant chemotherapy treatment decisions.

KEY POINTS

• Persistent T1 lesions on post-chemotherapy breast MRI indicate a reduced likelihood of achieving a complete pathological response (14% vs. 39%, p < 0.001) and imaging response (69% vs. 93%, p < 0.001). • Through multivariable analysis, it was confirmed that the presence of a persistent T1 lesion on breast MRI post-chemotherapy is linked to a decreased likelihood of complete pathological response, with an odds ratio (OR) of 0.37 (95% CI 0.18-0.76; p = 0.007). • In addition to the convention of equating the absence of residual enhancement to complete imaging response, our results suggest that the presence or absence of residual T1 lesions should also be considered.

Meta-analysis: Radial Scar and Breast MRI

BACKGROUND

The implementation of digital breast tomosynthesis has increased the detection of radial scar (RS). Managing this finding may be experienced as a clinical dilemma in daily practice. Breast Contrast-Enhanced MRI (CE-BMR) is a known modality in case of problem-solving tool for mammographic abnormalities. However, the data about AD and CE-BMR are scant.

OBJECTIVE

The purpose was to estimate the benefit of CE-BMR in the setting of RS detected mammographically through a systematic review and meta-analysis of the literature.

METHODS

A search of MEDLINE and EMBASE databases were conducted in 2022. Based on the PRISMA guidelines, an analysis was performed. The primary endpoint was the correlation between CE-BMR findings and definite outcome for RS (pure RS versus RS associated with atypia or malignancy).

RESULTS

Three studies were available. The negative predictive value (NPV) was 100% for each.

CONCLUSION

The high NPV could allow for deferral of a biopsy in favor of a short-interval imaging follow-up in the setting of a negative CE-BMR.

Optimizing Image Quality with High-Resolution, Deep-Learning-Based Diffusion-Weighted Imaging in Breast Cancer Patients at 1.5 T

The objective of this study was to evaluate a high-resolution deep-learning (DL)-based diffusion-weighted imaging (DWI) sequence for breast magnetic resonance imaging (MRI) in comparison to a standard DWI sequence (DWIStd) at 1.5 T. It is a prospective study of 38 breast cancer patients, who were scanned with DWIStd and DWIDL. Both DWI sequences were scored for image quality, sharpness, artifacts, contrast, noise, and diagnostic confidence with a Likert-scale from 1 (non-diagnostic) to 5 (excellent). The lesion diameter was evaluated on b 800 DWI, apparent diffusion coefficient (ADC), and the second subtraction (SUB) of the contrast-enhanced T1 VIBE. SNR was also calculated. Statistics included correlation analyses and paired t-tests. High-resolution DWIDL offered significantly superior image quality, sharpness, noise, contrast, and diagnostic confidence (each p < 0.02)). Artifacts were significantly higher in DWIDL by one reader (M = 4.62 vs. 4.36 Likert scale, p < 0.01) without affecting the diagnostic confidence. SNR was higher in DWIDL for b 50 and ADC maps (each p = 0.07). Acquisition time was reduced by 22% in DWIDL. The lesion diameters in DWI b 800DL and Std and ADCDL and Std were respectively 6% lower compared to the 2nd SUB. A DL-based diffusion sequence at 1.5 T in breast MRI offers a higher resolution and a faster acquisition, including only minimally more artefacts without affecting the diagnostic confidence.

Evaluation of tumor microvasculature with 3D ultrasound localization microscopy based on 2D matrix array

OBJECTIVE

Evaluation of tumor microvascular morphology is of great significance in tumor diagnosis, therapeutic effect prediction, and surgical planning. Recently, two-dimensional ultrasound localization microscopy (2DULM) has demonstrated its superiority in the field of microvascular imaging. However, it suffers from planar dependence and is unintuitive. We propose a novel three-dimensional ultrasound localization microscopy (3DULM) to avoid these limitations.

METHODS

We investigated 3DULM based on a 2D array for tumor microvascular imaging. After intravenous injection of contrast agents, all elements of the 2D array transmit and receive signals to ensure a high and stable frame rate. Microbubble signal extraction, filtering, positioning, tracking, and other processing were used to obtain a 3D vascular map, flow velocity, and flow direction. To verify the effectiveness of 3DULM, it was validated on double helix tubes and rabbit VX2 tumors. Cisplatin was used to verify the ability of 3DULM to detect microvascular changes during tumor treatment.

RESULTS

In vitro, the sizes measured by 3DULM at 3 mm and 13 mm were 178 μ m and 182 μ m , respectively. In the rabbit tumors, we acquired 9000 volumes to reveal vessels about 30 μ m in diameter, which surpasses the diffraction limit of ultrasound in traditional ultrasound imaging, and the results matched with micro-angiography. In addition, there were significant changes in vascular density and curvature between the treatment and control groups.

CONCLUSIONS

The effectiveness of 3DULM was verified in vitro and in vivo. Hence, 3DULM may have potential applications in tumor diagnosis, tumor treatment evaluation, surgical protocol guidance, and cardiovascular disease.

CLINICAL RELEVANCE STATEMENT

3D ultrasound localization microscopy is highly sensitive to microvascular changes; thus, it has clinical potential for tumor diagnosis and treatment evaluation.

KEY POINTS

• 3D ultrasound localization microscopy is demonstrated on double helix tubes and rabbit VX2 tumors. • 3D ultrasound localization microscopy can reveal vessels about 30 μ m in diameter-far smaller than traditional ultrasound. • This form of imaging has potential applications in tumor diagnosis, tumor treatment evaluation, surgical protocol guidance, and cardiovascular disease.

Radiology of fibrosis. Part I: Thoracic organs

Sustained injury from factors such as hypoxia, infection, or physical damage may provoke improper tissue repair and the anomalous deposition of connective tissue that causes fibrosis. This phenomenon may take place in any organ, ultimately leading to their dysfunction and eventual failure. Tissue fibrosis has also been found to be central in both the process of carcinogenesis and cancer progression. Thus, its prompt diagnosis and regular monitoring is necessary for implementing effective disease-modifying interventions aiming to reduce mortality and improve overall quality of life. While significant research has been conducted on these subjects, a comprehensive understanding of how their relationship manifests through modern imaging techniques remains to be established. This work intends to provide a comprehensive overview of imaging technologies relevant to the detection of fibrosis affecting thoracic organs as well as to explore potential future advancements in this field.

Cancer detection rate of breast-MR in supplemental screening after negative mammography in women with dense breasts. Preliminary results of the MA-DETECT-Study after 200 participants

BACKGROUND

Due to increased cancer detection rates (CDR), breast MR (breast MRI) can reduce underdiagnosis of breast cancer compared to conventional imaging techniques, particularly in women with dense breasts. The purpose of this study is to report the additional breast cancer yield by breast MRI in women with dense breasts after receiving a negative screening mammogram.

METHODS

For this study we invited consecutive participants of the national German breast cancer Screening program with breast density categories ACR C & D and a negative mammogram to undergo additional screening by breast MRI. Endpoints were CDR and recall rates. This study reports interim results in the first 200 patients. At a power of 80% and considering an alpha error of 5%, this preliminary population size is sufficient to demonstrate a 4/1000 improvement in CDR.

RESULTS

In 200 screening participants, 8 women (40/1000, 17.4-77.3/1000) were recalled due to positive breast MRI findings. Image-guided biopsy revealed 5 cancers in 4 patients (one bilateral), comprising four invasive cancers and one case of DCIS. 3 patients revealed 4 invasive cancers presenting with ACR C breast density and one patient non-calcifying DCIS in a woman with ACR D breast density, resulting in a CDR of 20/1000 (95%-CI 5.5-50.4/1000) and a PPV of 50% (95%-CI 15.7-84.3%).

CONCLUSION

Our initial results demonstrate that supplemental screening using breast MRI in women with heterogeneously dense and very dense breasts yields an additional cancer detection rate in line with a prior randomized trial on breast MRI screening of women with extremely dense breasts. These findings are highly important as the population investigated constitutes a much higher proportion of women and yielded cancers particularly in women with heterogeneously dense breasts.

Enhancing the Kaiser score for lesion characterization in unenhanced breast MRI

PURPOSE

To adapt the methodology of the Kaiser score, a clinical decision rule for lesion characterization in breast MRI, for unenhanced protocols.

METHOD

In this retrospective IRB-approved cross-sectional study, we included 93 consecutive patients who underwent breast MRI between 2021 and 2023 for further work-up of BI-RADS 0, 3-5 in conventional imaging or for staging purposes (BI-RADS 6). All patients underwent biopsy for histologic verification or were followed for a minimum of 12 months. MRI scans were conducted using 1.5 T or 3 T scanners using dedicated breast coils and a protocol in line with international recommendations including DWI and ADC. Lesion characterization relied solely on T2w and DWI/ADC-derived features (such as lesion type, margins, shape, internal signal, surrounding tissue findings, ADC value). Statistical analysis was done using decision tree analysis aiming to distinguish benign (histology/follow-up) from malignant outcomes.

RESULTS

We analyzed a total of 161 lesions (81 of them non-mass) with a malignancy rate of 40%. Lesion margins (spiculated, irregular, or circumscribed) were identified as the most important criterion within the decision tree, followed by the ADC value as second most important criterion. The resulting score demonstrated a strong diagnostic performance with an AUC of 0.840, providing both rule-in and rule-out criteria. In an independent test set of 65 lesions the diagnostic performance was verified by two readers (AUC 0.77 and 0.87, kappa: 0.62).

CONCLUSIONS

We developed a clinical decision rule for unenhanced breast MRI including lesion margins and ADC value as the most important criteria, achieving high diagnostic accuracy.

Optimized, Person-Centered Workflow Design for a High-Throughput Breast MRI Screening Facility-A Simulation Study

OBJECTIVES

This project aims to model an optimal scanning environment for breast magnetic resonance imaging (MRI) screening based on real-life data to identify to what extent the logistics of breast MRI can be optimized.

MATERIALS AND METHODS

A novel concept for a breast MRI screening facility was developed considering layout of the building, workflow steps, used resources, and MRI protocols. The envisioned screening facility is person centered and aims for an efficient workflow-oriented design. Real-life data, collected from existing breast MRI screening workflows, during 62 scans in 3 different hospitals, were imported into a 3D simulation software for designing and testing new concepts. The model provided several realistic, virtual, logistical pathways for MRI screening and their outcome measures: throughput, waiting times, and other relevant variables.

RESULTS

The total average appointment time in the baseline scenario was 25:54 minutes, with 19:06 minutes of MRI room occupation. Simulated improvements consisted of optimizing processes and resources, facility layout, and scanning protocol. In the simulation, time spent in the MRI room was reduced by introducing an optimized facility layout, dockable tables, and adoption of an abbreviated MRI scanning protocol. The total average appointment time was reduced to 19:36 minutes, and in this scenario, the MRI room was occupied for 06:21 minutes. In the most promising scenario, screening of about 68 people per day (10 hours) on a single MRI scanner could be feasible, compared with 36 people per day in the baseline scenario.

CONCLUSIONS

This study suggests that by optimizing workflow MRI for breast screening total appointment duration and MRI occupation can be reduced. A throughput of up to 6 people per hour may be achieved, compared with 3 people per hour in the current setup.

Interval Cancers in Understanding Screening Outcomes

Interval breast cancers are not detected at routine screening and are diagnosed in the interval between screening examinations. A variety of factors contribute to interval cancers, including patient and tumor characteristics as well as the screening technique and frequency. The interval cancer rate is an important metric by which the effectiveness of screening may be assessed and may serve as a surrogate for mortality benefit.

Awareness, Knowledge, and Current Practice of Breast Cancer Among Surgeons in Jordan

PURPOSE

Breast cancer (BC) is the most prevalent cancer in Jordan. De-escalation in treatment reflects a paradigm shift in BC treatment. More tailored strategies and the adoption of a multidisciplinary approach are essential to apply recent changes in management. In the era of breast surgery fellowship, adopting well-structured training is essential to apply recent therapeutic guidelines and meet patients' expectations.

METHODS

A cross-sectional study using a customized, self-reported questionnaire was used. Data collection occurred anonymously using a link via WhatsApp in the period between February 2023 and April 2023.

RESULTS

A total of 89 surgeons were involved in this study, and only 14 (15.7%) completed a subspecialty in breast surgery. About 58.4% considered the age of 40 years as the starting point for screening, and 84.3% reported that mammogram screening is associated with improved BC survival. Only 10.1% and 28.1% acknowledged the applicability of both tomosynthesis and breast magnetic resonance imaging in screening, respectively. A significant difference in the mean knowledge score about BC is observed between general surgeon and those with subspecialty. Varying levels of awareness concerning different risk factors and their correlation with the likelihood of BC occurrence observed. Although 56.2% of participants could offer breast conserving surgery and consider it oncological safe, only 48.3% defined it correctly. Of the participants, 61.8% and 76.4% stated that sentinel lymph node biopsy can be safely applied in clinically negative or suspicious axillary nodes, respectively, with <50% of surgeon performing it in their practice.

CONCLUSION

More efforts are required to enhance the knowledge and practice of surgeons in the field of breast surgery. Adopting national guidelines can facilitate the acceptance and improvement of current practices among surgeons in Jordan.

Decoding the Prevalent High-Risk Breast Cancers: Demographics, Pathological, Imaging Insights, and Long-Term Outcome

Objective: To investigate the features and outcomes of breast cancer in high-risk subgroups. Materials and Methods: REB approved an observational study of women diagnosed with breast cancer from 2010 to 2019. Three radiologists, using the BI-RADS lexicon, blindly reviewed mammogram and MRI screenings without a washout period. Consensus was reached with 2 additional reviewers. Inter-rater agreement was measured by Fleiss Kappa. Statistical analysis included Mann-Whitney U, Chi-square tests for cohort analysis, and Kaplan-Meier for survival rates, with a Cox model for comparative analysis using gene mutation as a reference. Results: The study included 140 high-risk women, finding 155 malignant lesions. Significant age differences noted: chest radiation therapy (median age 44, IQR: 37.0-46.2), gene mutation (median age 49, IQR: 39.8-58.0), and familial risk (median age 51, IQR: 44.5-56.0) (P = .007). Gene mutation carriers had smaller (P = .01), higher-grade tumours (P = .002), and more triple-negative ER- (P = .02), PR- (P = .002), and HER2- (P = .02) cases. MRI outperformed mammography in all subgroups. Substantial to near-perfect inter-rater agreement observed. Over 10 years, no deaths occurred in chest radiation group, with no significant survival difference between gene mutation and familial risk groups, HR = 0.93 (95% CI: 0.27, 3.26), P = .92. Conclusion: The study highlights the importance of age and specific tumour characteristics in identifying high-risk breast cancer subgroups. MRI is confirmed as an effective screening tool. Despite the aggressive nature of cancers in gene mutation carriers, early detection is crucial for survival outcomes. These insights, while necessitating further validation with larger studies, advocate for a move toward personalized medical care, strengthening the existing healthcare guidelines.

Performance of Diffusion-weighted Imaging-based Noncontrast MRI Protocols for Diagnosis of Breast Cancer: A Systematic Review and Meta-Analysis

Background Diffusion-weighted imaging (DWI) is increasingly recognized as a powerful diagnostic tool and tested alternative to contrast-enhanced (CE) breast MRI. Purpose To perform a systematic review and meta-analysis that assesses the diagnostic performance of DWI-based noncontrast MRI protocols (ncDWI) for the diagnosis of breast cancer. Materials and Methods A systematic literature search in PubMed for articles published from January 1985 to September 2023 was performed. Studies were excluded if they investigated malignant lesions or selected patients and/or lesions only, used DWI as an adjunct technique to CE MRI, or were technical studies. Statistical analysis included pooling of diagnostic accuracy and investigating between-study heterogeneity. Additional subgroup comparisons of ncDWI to CE MRI and standard mammography were performed. Results A total of 28 studies were included, with 4406 lesions (1676 malignant, 2730 benign) in 3787 patients. The pooled sensitivity and specificity of ncDWI were 86.5% (95% CI: 81.4, 90.4) and 83.5% (95% CI: 76.9, 88.6), and both measures presented with high between-study heterogeneity (I 2 = 81.6% and 91.6%, respectively; P < .001). CE MRI (18 studies) had higher sensitivity than ncDWI (95.1% [95% CI: 92.9, 96.7] vs 88.9% [95% CI: 82.4, 93.1], P = .004) at similar specificity (82.2% [95% CI: 75.0, 87.7] vs 82.0% [95% CI: 74.8, 87.5], P = .97). Compared with ncDWI, mammography (five studies) showed no evidence of a statistical difference for sensitivity (80.3% [95% CI: 56.3, 93.3] vs 56.7%; [95% CI: 41.9, 70.4], respectively; P = .09) or specificity (89.9% [95% CI: 85.5, 93.1] vs 90% [95% CI: 61.3, 98.1], respectively; P = .62), but ncDWI had a higher area under the summary receiver operating characteristic curve (0.93 [95% CI: 0.91, 0.95] vs 0.78 [95% CI: 0.74, 0.81], P < .001). Conclusion A direct comparison with CE MRI showed a modestly lower sensitivity at similar specificity for ncDWI, and higher diagnostic performance indexes for ncDWI than standard mammography. Heterogeneity was high, thus these results must be interpreted with caution. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kataoka and Iima in this issue.

Long-term outcome of 9G MRI-guided vacuum-assisted breast biopsy: results of 293 single-center procedures and underestimation rate of high-risk lesions over 12 years

PURPOSE

Breast magnetic resonance imaging (MRI) can detect some malignant lesions that are not visible on mammography (MX) or ultrasound (US). If a targeted, second-look fails, MRI-guided breast biopsy is the only available tool to obtain a tissue sample and pathological proof of these "MRI-only lesions". The aim of this study is to report the performance and underestimation rate of 9G MRI-guided vacuum-assisted breast biopsy (VABB) over 12 years at a single center.

MATERIAL AND METHODS

All 9G MRI-VABB procedures performed from January 2010 to December 2021 were retrospectively reviewed. Two MRI scanners (1.5 T and 3 T) were used with the same image resolution and contrast media. All suspicious lesions detected only by breast MRI underwent biopsy. Reference standard was histological diagnosis or at least 1-year negative follow-up. All malignant and atypical lesions underwent surgery, which was used as the reference standard.

RESULTS

A total of 293 biopsies were retrospectively reviewed. Histopathological VABB results revealed 142/293 (48.4%) benign lesions, 77/293 (26.2%) high-risk lesions, and 74/293 (25.2%) malignant lesions. No significant complications were observed. Surgical pathology results allowed for the reclassification of n = 7/48 B3b lesions: n = 4 were ductal carcinoma in situ, while n = 3 presented invasive features at surgical histology (2 IDC; 1 ILC). B3b underestimation occurred overall in 14.6% of B3 cases. Breast follow-up was achieved for all benign VABB results, and only one false-negative case was observed.

CONCLUSION

Our results confirm that 1.5 T and 3 T MRI-guided VABB is an accurate and safe procedure for histopathologic final diagnosis of MRI-only lesions. Critical issues remain the potential high-risk underestimation rate of B3b VABB results and management of follow-up of benign lesions.

Breast imaging with an ultra-low field MRI scanner: a pilot study

Breast cancer screening is necessary to reduce mortality due to undetected breast cancer. Current methods have limitations, and as a result many women forego regular screening. Magnetic resonance imaging (MRI) can overcome most of these limitations, but access to conventional MRI is not widely available for routine annual screening. Here, we used an MRI scanner operating at ultra-low field (ULF) to image the left breasts of 11 women (mean age, 35 years ±13 years) in the prone position. Three breast radiologists reviewed the imaging and were able to discern the breast outline and distinguish fibroglandular tissue (FGT) from intramammary adipose tissue. Additionally, the expert readers agreed on their assessment of the breast tissue pattern including fatty, scattered FGT, heterogeneous FGT, and extreme FGT. This preliminary work demonstrates that ULF breast MRI is feasible and may be a potential option for comfortable, widely deployable, and low-cost breast cancer diagnosis and screening.

Abbreviated breast magnetic resonance imaging (MRI) or digital breast tomosynthesis for breast cancer detection in dense breasts? A retrospective preliminary study with comparable results

AIM

To compare the diagnostic performance of abbreviated breast magnetic resonance (AB-MR) imaging (MRI) and digital breast tomosynthesis (DBT) for breast cancer detection in Malaysian women with dense breasts, using histopathology as the reference standard.

MATERIALS AND METHODS

This was a single-centre cross-sectional study of 115 women with American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BIRADS) breast density C and D on DBT with breast lesions who underwent AB-MR from June 2018 to December 2021. AB-MR was performed on a 3 T MRI system with an imaging protocol consisting of three sequences: axial T1 fat-saturated unenhanced; axial first contrast-enhanced; and subtracted first contrast-enhanced with maximum intensity projection (MIP). DBT and AB-MR images were evaluated by two radiologists blinded to the histopathology and patient outcomes. Diagnostic accuracy (sensitivity, specificity, positive predictive value [PPV] and negative predictive value [NPV]) was assessed.

RESULT

Of the 115 women, the mean age was 50.6 years. There were 48 (41.7%) Malay, 54 (47%) Chinese, and 12 (10.4%) Indian women. The majority (n=87, 75.7%) were from the diagnostic population. Sixty-one (53.1%) were premenopausal and 54 (46.9%) postmenopausal. Seventy-eight (72.4%) had an increased risk of developing breast cancer. Ninety-one (79.1%) women had density C and 24 (20.9%) had density D. There were 164 histopathology-proven lesions; 69 (42.1%) were malignant and 95 (57.9%) were benign. There were 62.8% (n=103/164) lesions detected at DBT. All the malignant lesions 100% (n=69) and 35.7% (n=34) of benign lesions were detected. Of the 61 lesions that were not detected, 46 (75.4%) were in density C, and 15 (24.6%) were in density D. The sensitivity, specificity, PPV, and NPV for DBT were 98.5%, 34.6%, 66.3%, and 94.7%, respectively. There were 65.2% (n=107/164) lesions detected on AB-MR, with 98.6% (n=68) malignant and 41.1% (39) benign lesions detected. The sensitivity, specificity, PPV, and NPV for AB-MR were 98.5%, 43.9%, 67.2%, and 96.2%, respectively. One malignant lesion (0.6%), which was a low-grade ductal carcinoma in-situ (DCIS), was missed on AB-MR.

CONCLUSION

The present findings suggest that both DBT and AB-MR have comparable effectiveness as an imaging method for detecting breast cancer and have high NPV for low-risk lesions in women with dense breasts.

The Convergence of Radiology and Genomics: Advancing Breast Cancer Diagnosis with Radiogenomics

Despite significant progress in the prevention, screening, diagnosis, prognosis, and therapy of breast cancer (BC), it remains a highly prevalent and life-threatening disease affecting millions worldwide. Molecular subtyping of BC is crucial for predictive and prognostic purposes due to the diverse clinical behaviors observed across various types. The molecular heterogeneity of BC poses uncertainties in its impact on diagnosis, prognosis, and treatment. Numerous studies have highlighted genetic and environmental differences between patients from different geographic regions, emphasizing the need for localized research. International studies have revealed that patients with African heritage are often diagnosed at a more advanced stage and exhibit poorer responses to treatment and lower survival rates. Despite these global findings, there is a dearth of in-depth studies focusing on communities in the African region. Early diagnosis and timely treatment are paramount to improving survival rates. In this context, radiogenomics emerges as a promising field within precision medicine. By associating genetic patterns with image attributes or features, radiogenomics has the potential to significantly improve early detection, prognosis, and diagnosis. It can provide valuable insights into potential treatment options and predict the likelihood of survival, progression, and relapse. Radiogenomics allows for visual features and genetic marker linkage that promises to eliminate the need for biopsy and sequencing. The application of radiogenomics not only contributes to advancing precision oncology and individualized patient treatment but also streamlines clinical workflows. This review aims to delve into the theoretical underpinnings of radiogenomics and explore its practical applications in the diagnosis, management, and treatment of BC and to put radiogenomics on a path towards fully integrated diagnostics.

Atypical Ductal Hyperplasia and Lobular In Situ Neoplasm: High-Risk Lesions Challenging Breast Cancer Prevention

This retrospective study investigates the histopathological outcomes, upgrade rates, and disease-free survival (DFS) of high-risk breast lesions, including atypical ductal hyperplasia (ADH or DIN1b) and lobular in situ neoplasms (LIN), following Vacuum-Assisted Breast Biopsy (VABB) and surgical excision. The study addresses the challenge posed by these lesions due to their association with synchronous or adjacent Breast Cancer (BC) and increased future BC risk. The research, comprising 320 patients who underwent stereotactic VABB, focuses on 246 individuals with a diagnosis of ADH (120) or LIN (126) observed at follow-up. Pathological assessments, categorized by the UK B-coding system, were conducted, and biopsy samples were compared with corresponding excision specimens to determine upgrade rates for in situ or invasive carcinoma. Surgical excision was consistently performed for diagnosed ADH or LIN. Finally, patient follow-ups were assessed and compared between LIN and ADH groups to identify recurrence signs, defined as histologically confirmed breast lesions on either the same or opposite side. The results reveal that 176 (71.5%) patients showed no upgrade post-surgery, with ADH exhibiting a higher upgrade rate to in situ pathology than LIN1 (Atypical Lobular Hyperplasia, ALH)/LIN2 (Low-Grade Lobular in situ Carcinoma, LCIS) (38% vs. 20%, respectively, p-value = 0.002). Considering only patients without upgrade, DFS at 10 years was 77%, 64%, and 72% for ADH, LIN1, and LIN2 patients, respectively (p-value = 0.92). The study underscores the importance of a multidisciplinary approach, recognizing the evolving role of VABB. It emphasizes the need for careful follow-up, particularly for lobular lesions, offering valuable insights for clinicians navigating the complex landscape of high-risk breast lesions. The findings advocate for heightened awareness and vigilance in managing these lesions, contributing to the ongoing refinement of clinical strategies in BC care.