Performance of DWI as a Rapid Unenhanced Technique for Detecting Mammographically Occult Breast Cancer in Elevated-Risk Women With Dense Breasts

A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI

BACKGROUND

Breast MRI has been recommended as supplemental screening tool to mammography and breast ultrasound of breast cancer by international guidelines, but its long examination time and use of contrast material remains concerning.

PURPOSE

To develop an unenhanced radiomics model with using non-gadolinium based sequences for detecting breast cancer based on T2-weighted (T2W) and diffusion-weighted (DW) MRI.

STUDY TYPE

Retrospective analysis followed by retrospective and prospective cohorts study.

POPULATION

1760 patients: Of these, 1293 for model construction (n = 775 for training and 518 for validation). The remaining patients for model testing in internal retrospective (n = 167), internal prospective (n = 188), and external retrospective (n = 112) cohorts.

FIELD STRENGTH/SEQUENCE

3.0T MR scanners from two institution. T2WI, DWI, and first contrast-enhanced T1-weighted sequence.

ASSESSMENT

AUCs in distinguishing breast cancer were compared between combined model with gadolinium agent sequence and unenhanced model. Subsequently, the AUCs in testing cohorts of unenhanced model was compared with two radiologists' diagnosis for this research. Finally, patient subgroup analysis in testing cohorts was performed based on clinical subgroups and different types of malignancies.

STATISTICAL TESTS

Mann-Whitney U test, Kruskal-Wallis H test, chi-square test, weighted kappa test, and DeLong's test.

RESULTS

The unenhanced radiomics model performed best under Gaussian process (GP) classifiers (AUC: training, 0.893; validation, 0.848) compared to support vector machine (SVM) and logistic, showing favorable prediction in testing cohorts (AUCs, 0.818-0.840). The AUCs for the unenhanced radiomics model were not statistically different in five cohorts from those of the combined radiomics model (P, 0.317-0.816), as well as the two radiologists (P, 0.181-0.918). The unenhanced radiomics model was least successful in identifying ductal carcinoma in situ, whereas did not show statistical significance in other subgroups.

DATA CONCLUSION

An unenhanced radiomics model based on T2WI and DWI has comparable diagnostic accuracy to the combined model using the gadolinium agent.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

Non-contrast-enhanced breast MRI for evaluation of tumor volume change after neoadjuvant chemotherapy

PURPOSE

Three-dimensional contrast-enhanced magnetic resonance imaging (3D-Ce-MRI) is a most powerful tool for evaluation of neoadjuvant chemotherapy (NAC). However, the use of contrast agent is invasive, expensive, and time consuming, Thus, contrast agent-free imaging is preferable. We aimed to investigate the tumor volume change after NAC using maximum intensity projection diffusion-weighted image (MIP-DWI) and 3D-Ce-MRI.

METHOD

We finally enrolled 55 breast cancer patients who underwent NAC in 2018. All MRI analyses were performed using SYNAPSE VINCENT® medical imaging system (Fujifilm Medical, Tokyo, Japan). We evaluated the tumor volumes before, during, and after NAC. Tumor volume before NAC on 3D-Ce-MRI was termed Pre-CE and those during and after NAC were termed Post-CE. The observer raised the lower end of the window width until the tumor was clearly visible and then manually deleted the non-tumor tissues. A month thereafter, the same observer who was blinded to the 3D-Ce-MRI results randomly evaluated the tumor volumes (Pre-DWI and Post-DWI) using MIP-DWI with the same method. Tumor volume change between ΔCE (Pre-CE - Post-CE/Pre-CE) and ΔDWI (Pre-DWI - Post-DWI/Pre-DWI) and the processing time for both methods (Time-DWI and Time-CE) were compared.

RESULTS

We enrolled 55 patients. Spearman's rho between ΔDWI and ΔCE for pure mass lesions, and non-mass enhancement (NME) was 0.89 (p < 0.01), 0.63(p < 0.01) respectively. Time-DWI was significantly shorter than Time-CE (41.3 ± 21.2 and 199.5 ± 98.3 respectively, p < 0.01).

CONCLUSIONS

Non-contrast-enhanced Breast MRI enables appropriate and faster evaluation of tumor volume change after NAC than 3D-Ce-MRI especially for mass lesions.

Utility of Echo-planar Imaging with Compressed Sensitivity Encoding (EPICS) in the Evaluation of Small Breast Cancers Using Diffusion-weighted Imaging with Background Suppression (DWIBS)

PURPOSE

High b-value acquisition and diffusion-weighted imaging with background suppression (DWIBS) are desirable in high-specificity breast cancer diagnosis on non-contrast-enhanced magnetic resonance imaging; however, this inherently results in a lower signal-to-noise ratio (SNR). Compressed sensitivity encoding (C-SENSE), which combines SENSE with compressed sensing, improves the SNR by reducing noise. Recent technological improvements allow us to incorporate this acceleration technique into echo-planar imaging, called echo-planar imaging with C-SENSE (EPICS). This study aimed to compare image quality and reliability of the apparent diffusion coefficient (ADC) between DWIBS obtained using SENSE and EPICS in patients with small breast cancers.

METHODS

Thirty-seven patients with pathologically confirmed breast cancer underwent DWIBS, and images were reconstructed using both conventional SENSE (SENSE-DWIBS) and EPICS (EPICS-DWIBS). Two board-certified radiologists independently evaluated lesion conspicuity (LC) and noise using a 5-point grading scale. The same 2 radiologists independently measured SNR, contrast-to-noise ratio (CNR), and the mean cancer ADC. The Pearson coefficient and Bland-Altman plot were applied to assess the accuracy of ADCs.

RESULTS

LC scores were higher with EPICS than with SENSE, reaching significance for one reviewer but not the other reviewer. Noise ratings on visual evaluation were significantly lower with EPICS than with SENSE (P < 0.001 for both reviewers). SNR was significantly higher with EPICS than with SENSE (P < 0.005 for both reviewers). CNR was significantly higher with EPICS than with SENSE (P < 0.001 for both reviewers). Bland-Altman plots of cancer ADCs using EPICS-DWIBS and SENSE-DWIBS showed excellent concordance, with a bias of 0.026 × 10-3 mm2/s and limits of agreement ranging 0.054 × 10-3 mm2/s; the Pearson's correlation coefficient was 0.997 (P < 0.0001).

CONCLUSION

EPICS enhances breast DWIBS image quality, with improved SNR and CNR and reduced noise levels. The ADCs of breast cancers obtained using EPICS were almost perfectly correlated with those obtained using conventional SENSE.

Enabling AI-Generated Content for Gadolinium-Free Contrast-Enhanced Breast Magnetic Resonance Imaging

BACKGROUND

There is increasing interest in utilizing AI-generated content for gadolinium-free contrast-enhanced breast MRI.

PURPOSE

To develop a generative model for gadolinium-free contrast-enhanced breast MRI and evaluate the diagnostic utility of the generated scans.

STUDY TYPE

Retrospective.

POPULATION

Two hundred seventy-six women with 304 breast MRI examinations (49 ± 13 years, 243/61 for training/testing).

FIELD STRENGTH/SEQUENCE

ZOOMit diffusion-weighted imaging (DWI), T1-weighted volumetric interpolated breath-hold examination (T1W VIBE), and axial T2 3D SPACE at 3.0 T.

ASSESSMENT

A generative model was developed to generate contrast-enhanced scans using precontrast T1W VIBE and DWI images. The generated and real images were quantitatively compared using the structural similarity index (SSIM), mean absolute error (MAE), and Dice similarity coefficient. Three radiologists with 8, 5, and 5 years of experience independently rated the image quality and lesion visibility on AI-generated and real images within various subgroups using a five-point scale. Four breast radiologists, with 8, 8, 5, and 5 years of experience, independently and blindly interpreted four reading protocols: unenhanced MRI protocol alone and combined with AI-generated scans, abbreviated MRI protocol, and full-MRI protocol.

STATISTICAL ANALYSIS

Results were assessed using t-tests and McNemar tests. Using pathology diagnosis as reference standard, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each reading protocol. A P value <0.05 was considered significant.

RESULTS

In the test set, the generated images showed similarity to the real images (SSIM: 0.935 ± 0.047 [SD], MAE: 0.015 ± 0.012 [SD], and Dice coefficient: 0.726 ± 0.177 [SD]). No significant difference in lesion visibility was observed between real and AI-generated scans of the mass, non-mass, and benign lesion subgroups. Adding AI-generated scans to the unenhanced MRI protocol slightly improved breast cancer detection (sensitivity: 92.86% vs. 85.71%, NPV: 76.92% vs. 70.00%); achieved non-inferior diagnostic utility compared to the AB-MRI protocol and full-protocol (sensitivity: 92.86%, 95.24%; NPV: 75.00%, 81.82%).

DATA CONCLUSION

AI-generated gadolinium-free contrast-enhanced breast MRI has potential to improve the sensitivity of unenhanced MRI in detecting breast cancer.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 3.

Non-contrast Breast MR Imaging

Considering the high cost of dynamic contrast-enhanced MR imaging and various contraindications and health concerns related to administration of intravenous gadolinium-based contrast agents, there is emerging interest in non-contrast-enhanced breast MR imaging. Diffusion-weighted MR imaging (DWI) is a fast, unenhanced technique that has wide clinical applications in breast cancer detection, characterization, prognosis, and predicting treatment response. It also has the potential to serve as a non-contrast MR imaging screening method. Standardized protocols and interpretation strategies can help to enhance the clinical utility of breast DWI. A variety of other promising non-contrast MR imaging techniques are in development, but currently, DWI is closest to clinical integration, while others are still mostly used in the research setting.

Bridging Gaps: Analyzing Breast Imaging-Reporting and Data System (BI-RADS) 0 Rates and Associated Risk Factors in Disproportionally Affected Communities

Introduction Disparities in access to breast cancer screening led to the creation of the Linda Fenner 3D Mobile Mammography Center (LFMMC), successfully increasing screening for uninsured women in Miami-Dade. However, a higher-than-expected rate of inconclusive mammograms (Breast Imaging-Reporting and Data System (BI-RADS) 0) was found, which could lead to unnecessary procedures, stress, costs, and radiation. Methods In this retrospective cross-sectional study, we analyzed data from 3,044 uninsured women aged over 40 (younger if positive family history of breast cancer) from Miami-Dade without breast symptoms or breast cancer history. Women's demographic characteristics, primary language spoken, body mass index (BMI), use of hormone replacement therapy and birth control, history of benign biopsy, breast surgery, family breast cancer, and menopausal status were assessed as potential risk factors for an inconclusive (BI-RADS 0) screening mammogram result. Multivariable logistic regression analyses were used to evaluate associations. Results The average age of women was 51 years (SD = 9); 59% were White, and 30% were African American. The overall frequency of BI-RADS 0 was 35%. Higher odds of BI-RADS 0 were found for women who were younger, single, premenopausal, and with benign biopsy history. Conversely, obesity and breast implant history decreased the odds of BI-RADS 0. Conclusion We found a high frequency of BI-RADS 0 in the LFMMC sample. Potential reasons include a higher risk for breast cancer or a younger sample of women screened. Future research should explore radiologists' reasoning for assigning BI-RADS 0 results and testing alternative screening strategies for younger women.

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.

Unenhanced Breast MRI With Diffusion-Weighted Imaging for Breast Cancer Detection: Effects of Training on Performance and Agreement of Subspecialty Radiologists

OBJECTIVE

To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm² was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive. The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC).

RESULTS

Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4-79.9), 90.8% (95% CI: 85.6-94.2), and 83.5% (95% CI: 78.6-87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8-97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9-89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1-79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52-0.63) before training and 0.68 (95% CI: 0.62-0.74) after training, with a difference of 0.11 (95% CI: 0.02-0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69-0.74) before training and 0.79 (95% CI: 0.76-0.80) after training (P = 0.002).

CONCLUSION

Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.

Update on DWI for Breast Cancer Diagnosis and Treatment Monitoring

DWI is a noncontrast MRI technique that measures the diffusion of water molecules within biologic tissue. DWI is increasingly incorporated into routine breast MRI examinations. Currently, the main applications of DWI are breast cancer detection and characterization, prognostication, and prediction of treatment response to neoadjuvant chemotherapy. In addition, DWI is promising as a noncontrast MRI alternative for breast cancer screening. Problems with suboptimal resolution and image quality have restricted the mainstream use of DWI for breast imaging, but these shortcomings are being addressed through several technologic advancements. In this review, we present an up-to-date assessment of the use of DWI for breast cancer imaging, including a summary of the clinical literature and recommendations for future use.

Accelerated Diffusion-Weighted Imaging in 3 T Breast MRI Using a Deep Learning Reconstruction Algorithm With Superresolution Processing: A Prospective Comparative Study

OBJECTIVES

Diffusion-weighted imaging (DWI) enhances specificity in multiparametric breast MRI but is associated with longer acquisition time. Deep learning (DL) reconstruction may significantly shorten acquisition time and improve spatial resolution. In this prospective study, we evaluated acquisition time and image quality of a DL-accelerated DWI sequence with superresolution processing (DWI DL ) in comparison to standard imaging including analysis of lesion conspicuity and contrast of invasive breast cancers (IBCs), benign lesions (BEs), and cysts.

MATERIALS AND METHODS

This institutional review board-approved prospective monocentric study enrolled participants who underwent 3 T breast MRI between August and December 2022. Standard DWI (DWI STD ; single-shot echo-planar DWI combined with reduced field-of-view excitation; b-values: 50 and 800 s/mm 2 ) was followed by DWI DL with similar acquisition parameters and reduced averages. Quantitative image quality was analyzed for region of interest-based signal-to-noise ratio (SNR) on breast tissue. Apparent diffusion coefficient (ADC), SNR, contrast-to-noise ratio, and contrast (C) values were calculated for biopsy-proven IBCs, BEs, and for cysts. Two radiologists independently assessed image quality, artifacts, and lesion conspicuity in a blinded independent manner. Univariate analysis was performed to test differences and interrater reliability.

RESULTS

Among 65 participants (54 ± 13 years, 64 women) enrolled in the study, the prevalence of breast cancer was 23%. Average acquisition time was 5:02 minutes for DWI STD and 2:44 minutes for DWI DL ( P < 0.001). Signal-to-noise ratio measured in breast tissue was higher for DWI STD ( P < 0.001). The mean ADC values for IBC were 0.77 × 10 -3 ± 0.13 mm 2 /s in DWI STD and 0.75 × 10 -3 ± 0.12 mm 2 /s in DWI DL without significant difference when sequences were compared ( P = 0.32). Benign lesions presented with mean ADC values of 1.32 × 10 -3 ± 0.48 mm 2 /s in DWI STD and 1.39 × 10 -3 ± 0.54 mm 2 /s in DWI DL ( P = 0.12), and cysts presented with 2.18 × 10 -3 ± 0.49 mm 2 /s in DWI STD and 2.31 × 10 -3 ± 0.43 mm 2 /s in DWI DL . All lesions presented with significantly higher contrast in the DWI DL ( P < 0.001), whereas SNR and contrast-to-noise ratio did not differ significantly between DWI STD and DWI DL regardless of lesion type. Both sequences demonstrated a high subjective image quality (29/65 for DWI STD vs 20/65 for DWI DL ; P < 0.001). The highest lesion conspicuity score was observed more often for DWI DL ( P < 0.001) for all lesion types. Artifacts were scored higher for DWI DL ( P < 0.001). In general, no additional artifacts were noted in DWI DL . Interrater reliability was substantial to excellent (k = 0.68 to 1.0).

CONCLUSIONS

DWI DL in breast MRI significantly reduced scan time by nearly one half while improving lesion conspicuity and maintaining overall image quality in a prospective clinical cohort.

Computed diffusion-weighted imaging with a low-apparent diffusion coefficient-pixel cut-off technique for breast cancer detection

OBJECTIVE

This study aimed to compare the image quality and diagnostic performance of computed diffusion-weighted imaging (DWI) with low-apparent diffusion coefficient (ADC)-pixel cut-off technique (cDWI cut-off) and actual measured DWI (mDWI).

METHODS

Eighty-seven consecutive patients with malignant breast lesions and 72 with negative breast lesions who underwent breast MRI were retrospectively evaluated. Computed DWI with high b-values of 800, 1200, and 1500 s/mm2 and ADC cut-off thresholds of none, 0, 0.3, and 0.6 (×10-3 mm2/s) were generated from DWI with two b-values (0 and 800 s/mm2). To identify the optimal conditions, two radiologists evaluated the fat suppression and lesion reduction failure using a cut-off technique. The contrast between breast cancer and glandular tissue was evaluated using region of interest analysis. Three other board-certified radiologists independently assessed the optimised cDWI cut-off and mDWI data sets. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis.

RESULTS

When an ADC cut-off threshold of 0.3 or 0.6 (× 10-3 mm2/s) was applied, fat suppression improved significantly (p < .05). The contrast of the cDWI cut-off with a b-value of 1200 or 1500 s/mm2 was better than the mDWI (p < .01). The ROC area under the curve for breast cancer detection was 0.837 for the mDWI and 0.909 for the cDWI cut-off (p < .01).

CONCLUSION

The cDWI cut-off provided better diagnostic performance than mDWI for breast cancer detection.

ADVANCES IN KNOWLEDGE

Using the low-ADC-pixel cut-off technique, computed DWI can improve diagnostic performance by increasing contrast and eliminating un-suppressed fat signals.

Abbreviated magnetic resonance imaging protocols in oncology: improving accessibility in precise diagnostics

Cancer, as the second leading cause of death in the world, is one of the major public health concerns today. Accurate diagnosis and prompt initiation of adequate treatment are of key importance for prognosis. Abbreviated magnetic resonance protocols (AMRI) are promising techniques based on magnetic resonance imaging (MRI) protocols that shorten acquisition time without significant loss of examination quality. Faster protocols that focus on detection of suspicious lesions with most precise sequences, can contribute to comparable diagnostic performance of a full MRI protocol. The purpose of this article was to review the current application of AMRI protocols in several oncological diseases.

Comparison of Fused Diffusion-Weighted Imaging Using Unenhanced MRI and Abbreviated Post-Contrast-Enhanced MRI in Patients with Breast Cancer

Background and Objectives: To determine the percentage of breast cancers detectable by fused diffusion-weighted imaging (DWI) using unenhanced magnetic resonance imaging (MRI) and abbreviated post-contrast-enhanced MRI. Materials and Methods: Between October 2016 and October 2017, 194 consecutive women (mean age, 54.2 years; age range, 28-82 years) with newly diagnosed unilateral breast cancer, who underwent preoperative 3.0 T breast MRI with DWI, were evaluated. Both fused DWI and abbreviated MRI were independently reviewed by two radiologists for the detection of index cancer (which showed the most suspicious findings in both breasts), location, lesion conspicuity, lesion type, and lesion size. Moreover, the relationship between cancer detection and histopathological results of surgical specimens was evaluated. Results: Index cancer detection rates were comparable between fused DWI and abbreviated MRI (radiologist 1: 174/194 [89.7%] vs. 184/194 [94.8%], respectively, p = 0.057; radiologist 2: 174/194 [89.7%] vs. 183/194 [94.3%], respectively, p = 0.092). In both radiologists, abbreviated MRI showed a significantly higher lesion conspicuity than fused DWI (radiologist 1: 9.37 ± 2.24 vs. 8.78 ± 3.03, respectively, p < 0.001; radiologist 2: 9.16 ± 2.32 vs. 8.39 ± 2.93, respectively, p < 0.001). The κ value for the interobserver agreement of index cancer detection was 0.67 on fused DWI and 0.85 on abbreviated MRI. For lesion conspicuity, the intraclass correlation coefficients were 0.72 on fused DWI and 0.82 on abbreviated MRI. Among the histopathological factors, tumor invasiveness was associated with cancer detection on both fused DWI (p = 0.011) and abbreviated MRI (p = 0.004, radiologist 1), lymphovascular invasion on abbreviated MRI (p = 0.032, radiologist 1), and necrosis on fused DWI (p = 0.031, radiologist 2). Conclusions: Index cancer detection was comparable between fused DWI and abbreviated MRI, although abbreviated MRI showed a significantly better lesion conspicuity.

Dynamic contrast-enhanced magnetic resonance imaging features and apparent diffusion coefficient value of HER2-positive/HR-negative breast carcinoma

Background

According to hormone receptor (HR) status, human epidermal growth factor 2 positive (HER2+) breast carcinoma can be divided into HR- and HR+, with different treatment and prognosis. We analyzed the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) findings, apparent diffusion coefficient (ADC) value and the combination of DCE-MRI and ADC value of HER2+/HR- breast carcinoma.

Methods

Totally 259 cases (96 HR-, 163 HR+) of pathologically verified HER2+ breast carcinoma were collected. Patients underwent DCE-MRI and diffusion weighted imaging (DWI). The morphological characteristics, internal enhancement characteristics, early enhancement rate (EER), and time-signal intensity curves (TIC) were recorded, and ADC values were measured. The relationship between each feature and HER2+/HR- breast cancer was analyzed. Area under the cures (AUC) was used to compare diagnostic performance of DCE-MRI, ADC value and the combination of DCE-MRI and ADC value.

Results

HER2+/HR- breast cancer presented as non-mass enhancement (NME), mass with NME, whereas HER2+/HR+ breast cancer presented as mass (P<0.001). HR- cases showed a round or oval shape with circumscribed margins, whereas HR+ cases showed an irregular mass with irregular or spiculated margins (P=0.001, P=0.028). The size of the mass, the internal enhancement characteristics, EER, and TIC did not differ significantly between the two HER2+ breast carcinomas. The ADC values for HR- and HR+ breast cancers were [1.2 (1.14, 1.33)] ×10-3 mm2/s and [1.0 (0.89, 1.11)] ×10-3 mm2/s, respectively, which were statistically significant (Z=-9.119, P<0.001). The ADC value can be used for diagnosing HER2+/HR- breast carcinoma, with the threshold value of 1.095×10-3 mm2/s [negative predictive value (NPV) of 89.8%, sensitivity of 86.5% and specificity of 70.6%]. The AUCs of ADC value, DCE-MRI, and DCE-MRI combined with ADC value were 0.839, 0.689 and 0.860, respectively. AUC of the DCE-MRI combined with ADC value was significantly higher than DCE-MRI alone (P<0.0001).

Conclusions

The diagnostic performance of the DCE-MRI combined with ADC value was good in diagnosing HER2+/HR- breast cancers. MRI is an effective tool in diagnosing HER2+/HR- breast carcinoma, which will help select the clinical treatment plan and determine the prognosis.

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

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

Advanced Diffusion-Weighted Imaging Sequences for Breast MRI: Comprehensive Comparison of Improved Sequences and Ultra-High B-Values to Identify the Optimal Combination

This study investigated the image quality and choice of ultra-high b-value of two DWI breast-MRI research applications. The study cohort comprised 40 patients (20 malignant lesions). In addition to s-DWI with two m-b-values (b50 and b800) and three e-b-values (e-b1500, e-b2000, and e-b2500), z-DWI and IR m-b1500 DWI were applied. z-DWI was acquired with the same measured b-values and e-b-values as the standard sequence. For IR m-b1500 DWI, b50 and b1500 were measured, and e-b2000 and e-b2500 were mathematically extrapolated. Three readers used Likert scales to independently analyze all ultra-high b-values (b1500-b2500) for each DWI with regards to scan preference and image quality. ADC values were measured in all 20 lesions. z-DWI was the most preferred (54%), followed by IR m-b1500 DWI (46%). b1500 was significantly preferred over b2000 for z-DWI and IR m-b1500 DWI (p = 0.001 and p = 0.002, respectively). Lesion detection was not significantly different among sequences or b-values (p = 0.174). There were no significant differences in measured ADC values within lesions between s-DWI (ADC: 0.97 [±0.09] × 10^-3 mm²/s) and z-DWI (ADC: 0.99 [±0.11] × 10^-3 mm²/s; p = 1.000). However, there was a trend toward lower values in IR m-b1500 DWI (ADC: 0.80 [±0.06] × 10^-3 mm²/s) than in s-DWI (p = 0.090) and z-DWI (p = 0.110). Overall, image quality was superior and there were fewer image artifacts when using the advanced sequences (z-DWI + IR m-b1500 DWI) compared with s-DWI. Considering scan preferences, we found that the optimal combination was z-DWI with a calculated b1500, especially regarding examination time.

Development and validation of a four-dimensional registration technique for DCE breast MRI

BACKGROUND

Patient motion can degrade image quality of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) due to subtraction artifacts. By objectively and subjectively assessing the impact of principal component analysis (PCA)-based registration on pretreatment DCE-MRIs of breast cancer patients, we aim to validate four-dimensional registration for DCE breast MRI.

RESULTS

After applying a four-dimensional, PCA-based registration algorithm to 154 pretreatment DCE-MRIs of histopathologically well-described breast cancer patients, we quantitatively determined image quality in unregistered and registered images. For subjective assessment, we ranked motion severity in a clinical reading setting according to four motion categories (0: no motion, 1: mild motion, 2: moderate motion, 3: severe motion with nondiagnostic image quality). The median of images with either moderate or severe motion (median category 2, IQR 0) was reassigned to motion category 1 (IQR 0) after registration. Motion category and motion reduction by registration were correlated (Spearman's rho: 0.83, p < 0.001). For objective assessment, we performed perfusion model fitting using the extended Tofts model and calculated its volume transfer coefficient K^trans as surrogate parameter for motion artifacts. Mean K^trans decreased from 0.103 (± 0.077) before registration to 0.097 (± 0.070) after registration (p < 0.001). Uncertainty in perfusion quantification was reduced by 7.4% after registration (± 15.5, p < 0.001).

CONCLUSIONS

Four-dimensional, PCA-based image registration improves image quality of breast DCE-MRI by correcting for motion artifacts in subtraction images and reduces uncertainty in quantitative perfusion modeling. The improvement is most pronounced when moderate-to-severe motion artifacts are present.

The road to breast cancer screening with diffusion MRI

Breast cancer is the leading cause of cancer in women with a huge medical, social and economic impact. Mammography (MMG) has been the gold standard method until now because it is relatively inexpensive and widely available. However, MMG suffers from certain limitations, such as exposure to X-rays and difficulty of interpretation in dense breasts. Among other imaging methods, MRI has clearly the highest sensitivity and specificity, and breast MRI is the gold standard for the investigation and management of suspicious lesions revealed by MMG. Despite this performance, MRI, which does not rely on X-rays, is not used for screening except for a well-defined category of women at risk, because of its high cost and limited availability. In addition, the standard approach to breast MRI relies on Dynamic Contrast Enhanced (DCE) MRI with the injection of Gadolinium based contrast agents (GBCA), which have their own contraindications and can lead to deposit of gadolinium in tissues, including the brain, when examinations are repeated. On the other hand, diffusion MRI of breast, which provides information on tissue microstructure and tumor perfusion without the use of contrast agents, has been shown to offer higher specificity than DCE MRI with similar sensitivity, superior to MMG. Diffusion MRI thus appears to be a promising alternative approach to breast cancer screening, with the primary goal of eliminating with a very high probability the existence of a life-threatening lesion. To achieve this goal, it is first necessary to standardize the protocols for acquisition and analysis of diffusion MRI data, which have been found to vary largely in the literature. Second, the accessibility and cost-effectiveness of MRI examinations must be significantly improved, which may become possible with the development of dedicated low-field MRI units for breast cancer screening. In this article, we will first review the principles and current status of diffusion MRI, comparing its clinical performance with MMG and DCE MRI. We will then look at how breast diffusion MRI could be implemented and standardized to optimize accuracy of results. Finally, we will discuss how a dedicated, low-cost prototype of breast MRI system could be implemented and introduced to the healthcare market.

MRI Breast: Current Imaging Trends, Clinical Applications, and Future Research Directions

Magnetic Resonance Imaging (MRI) is the most sensitive and advanced imaging technique in diagnosing breast cancer and is essential in improving cancer detection, lesion characterization, and determining therapy response. In addition to the dynamic contrast-enhanced (DCE) technique, functional techniques such as magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) further characterize and differentiate benign and malignant lesions thus, improving diagnostic accuracy. There is now an increasing clinical usage of MRI breast, including screening in high risk and supplementary screening tools in average-risk patients. MRI is becoming imperative in assisting breast surgeons in planning breast-conserving surgery for preoperative local staging and evaluation of neoadjuvant chemotherapy response. Other clinical applications for MRI breast include occult breast cancer detection, investigation of nipple discharge, and breast implant assessment. There is now an abundance of research publications on MRI Breast with several areas that still remain to be explored. This review gives a comprehensive overview of the clinical trends of MRI breast with emphasis on imaging features and interpretation using conventional and advanced techniques. In addition, future research areas in MRI breast include developing techniques to make MRI more accessible and costeffective for screening. The abbreviated MRI breast procedure and an area of focused research in the enhancement of radiologists' work with artificial intelligence have high impact for the future in MRI Breast.

Performance of abbreviated protocols versus unenhanced MRI in detecting occult breast lesions of mammography in patients with dense breasts

To assess the diagnostic ability of abbreviated protocols of MRI (AP-MRI) compared with unenhanced MRI (UE-MRI) in mammographically occult cancers in patients with dense breast tissue. The retrospective analysis consisted of 102 patients without positive findings on mammography who received preoperative MRI full diagnostic protocols (FDP) between January 2015 and December 2018. Two breast radiologists read the UE, AP, and FDP. The interpretation times were recorded. The comparisons of the sensitivity, specificity and area under the curve of each MRI protocol, and the sensitivity of these protocols in each subgroup of different size tumors used the Chi-square test. The paired sample t-test was used for evaluating the difference of reading time of the three protocols. Among 102 women, there were 68 cancers and two benign lesions in 64 patients and 38 patients had benign or negative findings. Both readers found the sensitivity and specificity of AP and UE-MRI were similar (p > 0.05), whereas compared with FDP, UE had lower sensitivity (Reader 1/Reader 2: p = 0.023, 0.004). For different lesion size groups, one of the readers found that AP and FDP had higher sensitivities than UE-MRI for detecting the lesions ≤ 10 mm in diameter (p = 0.041, p = 0.023). Compared with FDP, the average reading time of UE-MRI and AP was remarkably reduced (p < 0.001). AP-MRI had more advantages than UE-MRI to detect mammographically occult cancers, especially for breast tumors ≤ 10 mm in diameter.

Diffusion Breast MRI: Current Standard and Emerging Techniques

The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics.

Screening MRI in Women at Intermediate Breast Cancer Risk: An Update of the Recent Literature

Guidelines issued by the American Cancer Society (ACS) in 2007 recommend neither for nor against screening MRI in women at intermediate breast cancer risk (15%-20%), including those with dense breast tissue, a history of lobular neoplasia or atypical ductal hyperplasia (ADH), or a prior breast cancer, because of scarce supporting evidence about the utility of MRI in these specific patient populations. However, since the issuance of the ACS guidelines in 2007, multiple investigations have found that women at intermediate risk may be suitable candidates for screening MRI, given the high detection rates of early-stage cancers and acceptable false-positive rates. For women with dense breast tissue, the Dense Tissue and Early Breast Neoplasm Screening trial reported that the incremental cancer detection rate (CDR) by MRI exceeded 16 cancers per 1000 examinations but decreased in the second round of screening; this decrease in CDR, however, occurred alongside a marked decrease in the false-positive rate. For women with lobular neoplasia or ADH, single-institution retrospective analyses have shown CDRs mostly ranging from 11 to 16 cancers per 1000 MRI examinations, with women with lobular carcinoma in situ benefitting more than women with atypical lobular hyperplasia or ADH. For patients with a prior breast cancer, the cancer yield by MRI varies widely but mostly ranges from 8 to 20 cancers per 1000 examinations, with certain subpopulations more likely to benefit, such as those with dense breasts. This article reviews and summarizes more recent studies on MRI screening of intermediate-risk women.

Diffusion-weighted imaging of breast invasive lobular carcinoma: comparison with invasive carcinoma of no special type using a histogram analysis

BACKGROUND

To investigate the imaging findings and visibility of breast invasive lobular carcinoma (ILC) on diffusion-weighted imaging (DWI) and compare quantitative apparent diffusion coefficient (ADC) metrics of ILC and invasive carcinoma of no special type (NST) using a histogram analysis.

METHODS

We performed an observational retrospective study of 629 consecutive women with pathologically proven ILC and invasive ductal carcinoma of NST, who underwent 3-T MRI including DWI, between January 2017 and August 2020.

RESULTS

After propensity score matching, 71 women were allocated to each group. On DWI, 9 (12.7%) lesions of ILC and 4 (5.6%) invasive carcinomas of the NST were not visualized. For the tumor visibility on DWI, tumor size, tumor ADC value, and background diffusion grade were significantly associated with the visibility score in both groups (all P<0.05), whereas the mean background ADC value was not significant (P>0.05). The mean ADC (1.226×10^-3 vs. 1.052×10^-3 mm²/s, P<0.001), median ADC (1.222×10^-3 vs. 1.051×10^-3 mm²/s, P=0.002), maximum ADC (1.758×10^-3 vs. 1.504×10^-3 mm²/s, P<0.001), minimum ADC (0.717×10^-3 vs. 0.649×10^-3 mm²/s, P=0.003), 90th percentile ADC (1.506×10^-3 vs. 1.292×10^-3 mm²/s, P<0.001) and 10th percentile ADC (0.956×10^-3 vs. 0.818×10^-3 mm²/s, P=0.008) were higher in ILC than in invasive carcinoma of NST. Additionally, the ADC difference value of the ILC was higher than that of invasive carcinoma of NST (1.04×10^-3 vs. 0.855×10^-3 mm²/s, P=0.027).

CONCLUSIONS

On DWI, the visibility of ILC was lower compared to invasive carcinoma of NST. ILC showed higher quantitative ADC values and higher ADC difference values.

Screening Breast MRI Primer: Indications, Current Protocols, and Emerging Techniques

Breast dynamic contrast-enhanced MRI (DCE-MRI) is the most sensitive imaging modality for the detection of breast cancer. Screening MRI is currently performed predominantly in patients at high risk for breast cancer, but it could be of benefit in patients at intermediate risk for breast cancer and patients with dense breasts. Decreasing scan time and image interpretation time could increase cost-effectiveness, making screening MRI accessible to a larger group of patients. Abbreviated breast MRI (Ab-MRI) reduces scan time by decreasing the number of sequences obtained, but as multiple delayed contrast enhanced sequences are not obtained, no kinetic information is available. Ultrafast techniques rapidly acquire multiple sequences during the first minute of gadolinium contrast injection and provide information about both lesion morphology and vascular kinetics. Diffusion-weighted imaging is a noncontrast MRI technique with the potential to detect mammographically occult cancers. This review article aims to discuss the current indications of breast MRI as a screening tool, examine the standard breast DCE-MRI technique, and explore alternate screening MRI protocols, including Ab-MRI, ultrafast MRI, and noncontrast diffusion-weighted MRI, which can decrease scan time and interpretation time.

Diffusion-weighted double-echo steady-state with a three-dimensional cones trajectory for non-contrast-enhanced breast MRI

The image quality limitations of echo-planar diffusion-weighted imaging (DWI) are an obstacle to its widespread adoption in the breast. Steady-state DWI is an alternative DWI method with more robust image quality but its contrast for imaging breast cancer is not well-understood. The aim of this study was to develop and evaluate diffusion-weighted double-echo steady-state imaging with a three-dimensional cones trajectory (DW-DESS-Cones) as an alternative to conventional DWI for non-contrast-enhanced MRI in the breast. This prospective study included 28 women undergoing clinically indicated breast MRI and six asymptomatic volunteers. In vivo studies were performed at 3 T and included DW-DESS-Cones, DW-DESS-Cartesian, DWI, and CE-MRI acquisitions. Phantom experiments (diffusion phantom, High Precision Devices) and simulations were performed to establish framework for contrast of DW-DESS-Cones in comparison to DWI in the breast. Motion artifacts of DW-DESS-Cones were measured with artifact-to-noise ratio in volunteers and patients. Lesion-to-fibroglandular tissue signal ratios were measured, lesions were categorized as hyperintense or hypointense, and an image quality observer study was performed in DW-DESS-Cones and DWI in patients. Effect of DW-DESS-Cones method on motion artifacts was tested by mixed-effects generalized linear model. Effect of DW-DESS-Cones on signal in phantom was tested by quadratic regression. Correlation was calculated between DW-DESS-Cones and DWI lesion-to-fibroglandular tissue signal ratios. Inter-observer agreement was assessed with Gwet's AC. Simulations predicted hyperintensity of lesions with DW-DESS-Cones but at a 3% to 67% lower degree than with DWI. Motion artifacts were reduced with DW-DESS-Cones versus DW-DESS-Cartesian (p < 0.05). Lesion-to-fibroglandular tissue signal ratios were not correlated between DW-DESS-Cones and DWI (r = 0.25, p = 0.38). Concordant hyperintensity/hypointensity was observed between DW-DESS-Cones and DWI in 11/14 lesions. DW-DESS-Cones improved sharpness, distortion, and overall image quality versus DWI. DW-DESS-Cones may be able to eliminate motion artifacts in the breast allowing for investigation of higher degrees of steady-state diffusion weighting. Malignant breast lesions in DW-DESS-Cones demonstrated hyperintensity with respect to surrounding tissue without an injection of contrast. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 1.

Detection of Contralateral Breast Cancer Using Diffusion-Weighted Magnetic Resonance Imaging in Women with Newly Diagnosed Breast Cancer: Comparison with Combined Mammography and Whole-Breast Ultrasound

Objective

To compare the screening performance of diffusion-weighted (DW) MRI and combined mammography and ultrasound (US) in detecting clinically occult contralateral breast cancer in women with newly diagnosed breast cancer.

Materials and Methods

Between January 2017 and July 2018, 1148 women (mean age ± standard deviation, 53.2 ± 10.8 years) with unilateral breast cancer and no clinical abnormalities in the contralateral breast underwent 3T MRI, digital mammography, and radiologist-performed whole-breast US. In this retrospective study, three radiologists independently and blindly reviewed all DW MR images (b = 1000 s/mm² and apparent diffusion coefficient map) of the contralateral breast and assigned a Breast Imaging Reporting and Data System category. For combined mammography and US evaluation, prospectively assessed results were used. Using histopathology or 1-year follow-up as the reference standard, cancer detection rate and the patient percentage with cancers detected among all women recommended for tissue diagnosis (positive predictive value; PPV₂) were compared.

Results

Of the 30 cases of clinically occult contralateral cancers (13 invasive and 17 ductal carcinoma in situ [DCIS]), DW MRI detected 23 (76.7%) cases (11 invasive and 12 DCIS), whereas combined mammography and US detected 12 (40.0%, five invasive and seven DCIS) cases. All cancers detected by combined mammography and US, except two DCIS cases, were detected by DW MRI. The cancer detection rate of DW MRI (2.0%; 95% confidence interval [CI]: 1.3%, 3.0%) was higher than that of combined mammography and US (1.0%; 95% CI: 0.5%, 1.8%; p = 0.009). DW MRI showed higher PPV₂ (42.1%; 95% CI: 26.3%, 59.2%) than combined mammography and US (18.5%; 95% CI: 9.9%, 30.0%; p = 0.001).

Conclusion

In women with newly diagnosed breast cancer, DW MRI detected significantly more contralateral breast cancers with fewer biopsy recommendations than combined mammography and US.

Detection and Classification of Breast Lesions With Readout-Segmented Diffusion-Weighted Imaging in a Large Chinese Cohort

Objectives: To evaluate the performance of readout-segmented echo-planar imaging DWI (rs-EPI DWI) in detecting and characterizing breast cancers in a large Chinese cohort with comparison to dynamic contrast-enhanced MRI (DCE-MRI). Methods: The institutional review board approved this retrospective study with waived written informed consent. A total of 520 women (mean age, 43.1- ± 10.5-years) were included from July 2013 to October 2019. First, the ability of rs-EPI DWI in detecting breast lesions identified by DCE-MRI was evaluated. The lesion conspicuity of rs-EPI-DWI and DCE-MRI was compared using the Wilcoxon signed rank test. With pathology as a reference, the performance of rs-EPI DWI and DCE-MRI in distinguishing breast cancers was evaluated and compared using the Chi-square test. Results: Of 520 women, 327/520 (62.9%) patients had 423 lesions confirmed by pathology with 203 benign and 220 malignant lesions. The rs-EPI DWI can detect 90.8% (659/726) (reader 1) and 90.6% (663/732) (reader 2) of lesions identified by DCE-MRI. The lesion visibility was superior for DCE-MRI than rs-EPI-DWI (all p < 0.05). With pathology as a reference, the sensitivities and specificities of rs-EPI DWI in diagnosing breast cancers were 95.9% (211/220) and 85.7% (174/203) for reader 1 and 97.7% (215/220) and 86.2% (175/203) for reader 2. No significant differences were found for the performance of DCE-MRI and rs-EPI DWI in discriminating breast cancers (all p > 0.05). Conclusions: Although with an inferior lesion visibility, rs-EPI DWI can detect about 90% of breast lesions identified by DCE-MRI and has comparable diagnostic capacity to that of DCE-MRI in identifying breast cancer.

Qualitative characterization of breast tumors with diffusion-weighted imaging has comparable accuracy to quantitative analysis

PURPOSE

To evaluate the applicability and accuracy of a new qualitative diffusion-weighted imaging (DWI) assessment method in the characterization of breast tumors compared to quantitative ADC measurement and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI).

MATERIALS AND METHODS

After review board approval, MRIs of 216 consecutive women with final diagnoses (131 malignant, 85 benign) were retrospectively analyzed. Two radiologists independently scored DWI and dynamic contrast-enhanced MRI (DCE-MRI) according to malignancy probability. Qualitative assessments were performed by combined analysis of tumor morphology and diffusion signal. Quantitative data was obtained from apparent diffusion coefficient (ADC) measurements. Lastly, descriptive DWI features were evaluated and recorded. Cohen's kappa, receiver operating characteristic and multivariate analyzes were applied.

RESULTS

Of malignant tumors, 97% were visible on DWI. Qualitative and quantitative DWI assessments provided comparable sensitivities of 89-94% and 88-92% and specificities of 51-61% and 59-67%, respectively. There was no statistical difference between the accuracies of qualitative and quantitative DWI (p ≥ 0.105). Best diagnostic values were obtained with DCE-MRI (sensitivity, 99-100%; specificity, 69-71%). Inter-reader agreement was moderate (kappa = 0.597) for qualitative DWI and substantial (kappa = 0.689) for DCE-MRI (p < 0.001). Agreement between qualitative DWI and DCE-MRI scores was moderate (kappa = 0.536 and 0.442). Visual diffusion signal, mass margin and shape were the most predictive features of malignancy on multivariate analysis of qualitative assessment.

CONCLUSION

Qualitative characterization of breast tumors on DWI has comparable accuracy to quantitative ADC analysis. This method might be used to make DWI more widely available with eliminating the need to a predetermined ADC threshold in tumor characterization. However, lower accuracy and inter-reader agreement of it compared to DCE-MRI should be considered.

Fusion of high b-value diffusion-weighted and unenhanced T1-weighted images to diagnose invasive breast cancer: factors associated with false-negative results

OBJECTIVES

We sought factors associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast breast magnetic resonance imaging (MRI) using fused high b-value diffusion-weighted imaging (DWI) and unenhanced T1-weighted images (T1WI).

METHODS

Between 2018 and 2019, 316 consecutive women (mean age, 54.6 years) with invasive breast cancer who underwent preoperative breast MRI, including fused high b-value DWI and unenhanced T1WI, were retrospectively evaluated. Malignancy confidence ratings of the most suspicious breast lesions evident on fused DWI were derived by two radiologists using a 6-point Likert-type scale. Both clinicopathological and imaging features were analyzed. Multivariate regression analysis was performed to identify factors associated with false-negative DWI results in the diagnosis of invasive breast cancer.

RESULTS

Of the 316 breast cancers, fused DWI yielded 289 (91.5%) true-positive and 27 (8.5%) false-negative results. Multivariate analysis showed that small tumor size (≤ 1 cm) (odds ratio [OR], 5.95; 95% confidence interval [CI], 2.11, 16.81; p = 0.001), presence of calcifications in the tumor (OR, 3.41; 95% CI, 1.27, 9.15; p = 0.015), and a moderate/marked background diffusion signal (ORs, 4.23 and 19.18; 95% CI, 1.31, 13.67 and 6.51, 56.46; p = 0.016 and p < 0.001, respectively) were significantly associated with false-negative results. In subgroup analysis of 141 screening-detected cancers, a marked background diffusion signal (OR, 7.94; 95% CI, 2.30, 27.35; p = 0.001) remained significantly associated with false-negative results in the multivariate analysis.

CONCLUSIONS

In addition to histopathological features, a higher background diffusion signal was associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast MRI using fused high b-value DWI and unenhanced T1WI.

KEY POINTS

• Subcentimeter tumors and presence of calcifications in the tumor are associated with false-negative diffusion-weighted imaging results in the diagnosis of invasive breast cancer. • A higher degree of background diffusion signal may lead to false-negative interpretation of diffusion-weighted imaging in patients with invasive breast cancer.

Abbreviated MR Imaging for Breast Cancer

Breast MR imaging is the most sensitive imaging method for the detection of breast cancer and detects more aggressive malignancies than mammography and ultrasound examination. Despite these advantages, breast MR imaging has low use rates for breast cancer screening. Abbreviated breast MR imaging, in which a limited number of breast imaging sequences are obtained, has been proposed as a way to solve cost and patient tolerance issues while preserving the high cancer detection rate of breast MR imaging. This review discusses abbreviated breast MR imaging, including protocols, multicenter clinical trial results, clinical workflow implementation challenges, and future directions.

Diffusion-Weighted Magnetic Resonance Imaging for Breast Cancer Screening in High-Risk Women: Design and Imaging Protocol of a Prospective Multicenter Study in Korea

Purpose

Interest in unenhanced magnetic resonance imaging (MRI) screening for breast cancer is growing due to concerns about gadolinium deposition in the brain and the high cost of contrast-enhanced MRI. The purpose of this report is to describe the protocol of the Diffusion-Weighted Magnetic Resonance Imaging Screening Trial (DWIST), which is a prospective, multicenter, intraindividual comparative cohort study designed to compare the performance of mammography, ultrasonography, dynamic contrast-enhanced (DCE) MRI, and diffusion-weighted (DW) MRI screening in women at high risk of developing breast cancer.

Methods

A total of 890 women with BRCA mutation or family history of breast cancer and lifetime risk ≥ 20% are enrolled. The participants undergo 2 annual breast screenings with digital mammography, ultrasonography, DCE MRI, and DW MRI at 3.0 T. Images are independently interpreted by trained radiologists. The reference standard is a combination of pathology and 12-month follow-up. Each image modality and their combination will be compared in terms of sensitivity, specificity, accuracy, positive predictive value, rate of invasive cancer detection, abnormal interpretation rate, and characteristics of detected cancers. The first participant was enrolled in April 2019. At the time of manuscript submission, 5 academic medical centers in South Korea are actively enrolling eligible women and a total of 235 women have undergone the first round of screening. Completion of enrollment is expected in 2022 and the results of the study are expected to be published in 2026.

Discussion

DWIST is the first prospective multicenter study to compare the performance of DW MRI and conventional imaging modalities for breast cancer screening in high-risk women. DWIST is currently in the patient enrollment phase.

Trial Registration

ClinicalTrials.gov Identifier: NCT03835897

Diffusion-Weighted Imaging as a Stand-Alone Breast Imaging Modality

확산강조영상은 유방암의 진단과 스크리닝에 있어 독립적 검사 방법으로서의 기대되는 결과를 보여주는 빠른 비조영증강 검사 방법이다. 현재까지의 연구 결과 유방암 진단에 있어 독립적 검사 방법으로서 확산강조영상의 민감도는 역동적 조영증강 검사보다는 낮으나 유방촬영술보다는 높으며, 이로써 유방암 스크리닝에 대한 유용한 대안이 될 수 있을 것으로 보인다. 확산강조영상의 표준화된 영상 획득과 판독을 통해 영상 화질이 개선될 수 있고, 판독 결과의 다양성도 감소할 것으로 기대된다. 또한, 최신 기법과 후처리 기법을 사용한 고해상도 확산강조영상을 시행함으로써 1 cm 미만의 작은 암의 발견율을 증가시킬 수 있고, 가음성 및 가양성 결과를 감소시킬 것으로 보인다. 현재 한국에서 진행 중인 고위험군 여성에서의 확산강조영상 스크리닝에 대한 다기관 연구 결과가 나온다면 독립적 검사로서의 확산강조영상의 사용을 촉진시킬 수 있을 것으로 기대된다.

Simultaneous Multislice Readout-Segmented Echo Planar Imaging for Diffusion-Weighted MRI in Patients With Invasive Breast Cancers

BACKGROUND

In diffusion-weighted imaging (DWI) of breast MRI, simultaneous multislice acceleration techniques can be used for readout-segmented echo planar imaging (rs-EPI) to shorten the scan time.

PURPOSE

To compare the image quality, apparent diffusion coefficient (ADC) value, and scan time of rs-EPI and simultaneous multislice rs-EPI (SMS rs-EPI) sequences.

STUDY TYPE

Retrospective.

SUBJECTS

In all, 134 consecutive women (mean age: 55.3 years) with invasive breast cancer who underwent preoperative MRI.

FIELD STRENGTH/ SEQUENCES

3.0T; rs-EPI sequence, prototypic SMS rs-EPI sequence and dynamic contrast-enhanced MRI (DCE-MRI) sequence ASSESSMENT: For quantitative comparison, two radiologists independently measured the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), lesion contrast, and apparent diffusion coefficient (ADC). For qualitative comparison, image quality, lesion conspicuity, and reader preference were assessed with a reference of DCE-MRI.

STATISTICAL TESTS

Paired t-tests and Mann-Whitney tests were used.

RESULTS

For SNR and CNR, there were no differences between the sequences (P = 0.342 and 0.665 for reader 1; P = 0.606 and P = 0.116 for reader 2). Lesion contrast of SMS rs-EPI was higher than that of rs-EPI (P < 0.05 for both reader 1 and reader 2). Mean tumor ADC was similar in rs-EPI and SMS rs-EPI sequences (0.98 ± 0.22 vs. 1.00 ± 0.22; P = 0.291 for reader 1, 0.98 ± 0.21 vs. 1.00 ± 0.22; P = 0.418 for reader 2). Regarding qualitative comparison, image quality and lesion conspicuity were higher in SMS rs-EPI than in rs-EPI (both P < 0.05 for both readers). The two readers regarded SMS rs-EPI as superior or equal to rs-EPI in over 90% of cases. The acquisition time was 4:30 minutes for rs-EPI and 2:31 minutes for SMS rs-EPI.

DATA CONCLUSION

The SMS rs-EPI sequence resulted in a similar ADC value and better image quality than the rs-EPI sequence in a 44.1% reduced scan time.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: 3.

Diffusion-Weighted Magnetic Resonance Imaging of the Breast: Standardization of Image Acquisition and Interpretation

Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a rapid, unenhanced imaging technique that measures the motion of water molecules within tissues and provides information regarding the cell density and tissue microstructure. DW MRI has demonstrated the potential to improve the specificity of breast MRI, facilitate the evaluation of tumor response to neoadjuvant chemotherapy and can be employed in unenhanced MRI screening. However, standardization of the acquisition and interpretation of DW MRI is challenging. Recently, the European Society of Breast Radiology issued a consensus statement, which described the acquisition parameters and interpretation of DW MRI. The current article describes the basic principles, standardized acquisition protocols and interpretation guidelines, and the clinical applications of DW MRI in breast imaging.

Diagnostic value of diffusion-weighted imaging with synthetic b-values in breast tumors: comparison with dynamic contrast-enhanced and multiparametric MRI

Objectives

To assess DWI for tumor visibility and breast cancer detection by the addition of different synthetic b-values.

Methods

Eighty-four consecutive women who underwent a breast-multiparametric-MRI (mpMRI) with enhancing lesions on DCE-MRI (BI-RADS 2–5) were included in this IRB-approved retrospective study from September 2018 to March 2019. Three readers evaluated DW acquired b-800 and synthetic b-1000, b-1200, b-1500, and b-1800 s/mm² images for lesion visibility and preferred b-value based on lesion conspicuity. Image quality (1–3 scores) and breast composition (BI-RADS) were also recorded. Diagnostic parameters for DWI were determined using a 1–5 malignancy score based on qualitative imaging parameters (acquired + preferred synthetic b-values) and ADC values. BI-RADS classification was used for DCE-MRI and quantitative ADC values + BI-RADS were used for mpMRI.

Results

Sixty-four malignant (average = 23 mm) and 39 benign (average = 8 mm) lesions were found in 80 women. Although b-800 achieved the best image quality score, synthetic b-values 1200–1500 s/mm² were preferred for lesion conspicuity, especially in dense breast. b-800 and synthetic b-1000/b-1200 s/mm² values allowed the visualization of 84–90% of cancers visible with DCE-MRI performing better than b-1500/b-1800 s/mm². DWI was more specific (86.3% vs 65.7%, p < 0.001) but less sensitive (62.8% vs 90%, p < 0.001) and accurate (71% vs 80.7%, p = 0.003) than DCE-MRI for breast cancer detection, where mpMRI was the most accurate modality accounting for less false positive cases.

Conclusion

The addition of synthetic b-values enhances tumor conspicuity and could potentially improve tumor visualization particularly in dense breast. However, its supportive role for DWI breast cancer detection is still not definite.

Key Points

• The addition of synthetic b-values (1200–1500 s/mm²) to acquired DWI afforded a better lesion conspicuity without increasing acquisition time and was particularly useful in dense breasts.

• Despite the use of synthetic b-values, DWI was less sensitive and accurate than DCE-MRI for breast cancer detection.

• A multiparametric MRI modality still remains the best approach having the highest accuracy for breast cancer detection and thus reducing the number of unnecessary biopsies.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07094-z) contains supplementary material, which is available to authorized users.

Abbreviated Protocol Breast MRI

OBJECTIVE. Patients with dense breast tissue are seeking supplemental screening because of the limited sensitivity of mammography. Abbreviated protocol (AP) breast MRI is attractive because it offers a higher cancer detection rate, shorter scan time, and lower cost than full MRI. This article explores the issues of balancing the benefits of AP MRI with safety concerns about gadolinium-based contrast agents, lack of standardization of protocols and field strengths, potential decrease in performance metrics, and potential for overdiagnosis. CONCLUSION. Important questions need to be addressed before AP MRI can be used routinely for breast cancer screening. Evidence is lacking from well-designed prospective trials that can confirm the accuracy and efficacy of AP MRI are comparable with those of other breast imaging modalities. Determining which patients benefit most from AP MRI will help shape future screening guidelines.

Screening in patients with increased risk of breast cancer (part 2). Where are we now? Actual MRI screening controversies

For women with a high risk of breast cancer, early detection plays an important role. Due to the high incidence of breast cancer, and at a younger age than in the general population, screening begins earlier, and there is considerable evidence that magnetic resonance is the most sensitive diagnostic tool, and the principal American and European guidelines agree on the recommendation to perform annual magnetic resonance (with supplemental annual mammography) as an optimal mode of screening. In addition to the absence of current consensus on which patients should be included in the recommendation for magnetic resonance screening (widely discussed in the introduction of part 1 of this work), there are other aspects that are different between guidelines, that are not specified, or that are susceptible to change based on the evidence of several years of experience, that we have called «controversies», such as the age to begin screening, the possible advisability of using a different strategy in different subgroups, performing alternate versus synchronous magnetic resonance and mammography, the age at which to terminate the two techniques, or how to follow up after risk reduction surgery.The aim of the second part of the paper is, by reviewing the literature, to provide an update in relation to some of the main «controversies» in high risk screening with magnetic resonance. And finally, based on all this, to propose a possible model of optimal and updated screening protocol.

Abbreviated Breast MRI: Road to Clinical Implementation

Breast MRI offers high sensitivity for breast cancer detection, with preferential detection of high-grade invasive cancers when compared to mammography and ultrasound. Despite the clear benefits of breast MRI in cancer screening, its cost, patient tolerance, and low utilization remain key issues. Abbreviated breast MRI, in which only a select number of sequences and postcontrast imaging are acquired, exploits the high sensitivity of breast MRI while reducing table time and reading time to maximize availability, patient tolerance, and accessibility. Worldwide studies of varying patient populations have demonstrated that the comparable diagnostic accuracy of abbreviated breast MRI is comparable to a full diagnostic protocol, highlighting the emerging role of abbreviated MRI screening in patients with an intermediate and high lifetime risk of breast cancer. The purpose of this review is to summarize the background and current literature relating to abbreviated MRI, highlight various protocols utilized in current multicenter clinical trials, describe workflow and clinical implementation issues, and discuss the future of abbreviated protocols, including advanced MRI techniques.

Diffusion-weighted MRI at 3.0 T for detection of occult disease in the contralateral breast in women with newly diagnosed breast cancer

PURPOSE

Diffusion-weighted magnetic resonance imaging (DW-MRI) offers unenhanced method to detect breast cancer without cost and safety concerns associated with dynamic contrast-enhanced (DCE) MRI. Our purpose was to evaluate the performance of DW-MRI at 3.0T in detection of clinically and mammographically occult contralateral breast cancer in patients with unilateral breast cancer.

METHODS

Between 2017 and 2018, 1130 patients (mean age 53.3 years; range 26-84 years) with newly diagnosed unilateral breast cancer who underwent breast MRI and had no abnormalities on clinical and mammographic examinations of contralateral breast were included. Three experienced radiologists independently reviewed DW-MRI (b = 0 and 1000 s/mm²) and DCE-MRI and assigned a BI-RADS category. Using histopathology or 1-year clinical follow-up, performance measures of DW-MRI were compared with DCE-MRI.

RESULTS

A total of 21 (1.9%, 21/1130) cancers were identified (12 ductal carcinoma in situ and 9 invasive ductal carcinoma; mean invasive tumor size, 8.0 mm) in the contralateral breast. Cancer detection rate of DW-MRI was 13-15 with mean of 14 per 1000 examinations (95% confidence interval [CI] 9-23 per 1000 examinations), which was lower than that of DCE-MRI (18-19 with mean of 18 per 1000 examinations, P = 0.01). A lower abnormal interpretation rate (14.0% versus 17.0%, respectively, P < 0.001) with higher specificity (87.3% versus 84.6%, respectively, P < 0.001) but lower sensitivity (77.8% versus 96.8%, respectively, P < 0.001) was noted for DW-MRI compared to DCE-MRI.

CONCLUSIONS

DW-MRI at 3.0T has the potential as a cost-effective tool for evaluation of contralateral breast in women with newly diagnosed breast cancer.

Impact of Background Parenchymal Enhancement on Diagnostic Performance in Screening Breast MRI

RATIONALE AND OBJECTIVES

To evaluate the impact of background parenchymal enhancement (BPE) on diagnostic performance in screening breast magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Consecutive screening breast MRIs performed at our institution from 2011 to 2014 were reviewed in a HIPAA-compliant manner with institutional review board approval. BPE was extracted from radiology reports and examinations grouped into minimal/mild (lower) or moderate/marked (higher) BPE. Performance measures were compared between the two groups with Pearson's χ2 test and with logistic regression to adjust for possible confounders of age, screening indication, mammographic density, available prior MRI, and examination year, using lower BPE as the reference group.

RESULTS

For 4686 screening MRIs performed in 2446 women, BPE was reported as minimal or mild for 3975 (85%) examinations and moderate or marked for 711(15%). Following logistic regression to adjust for multiple confounders, abnormal interpretation rate (AIR) significantly differed between the two BPE groups. AIR was 13% (89/711) in the higher BPE group versus 7% (295/3975) in the lower BPE group with an adjusted odds ratio of 1.37 (95% confidence interval: 1.03, 1.82). After adjustment, all other performance metrics, including cancer detection rate, positive predictive value, sensitivity, and specificity did not significantly differ between the two BPE groups (P > 0.05).

CONCLUSION

Higher BPE on screening MRI is associated with higher abnormal interpretation rate, with no impact on cancer detection rate, sensitivity, or specificity.

Correlations of female hormone levels with background parenchymal enhancement and apparent diffusion coefficient values in premenopausal breast cancer patients: Effects on cancer visibility

PURPOSE

To evaluate the relationships between female hormone levels and background parenchymal enhancement (BPE) or apparent diffusion coefficient (ADC) values of breast parenchyma, as well as the effects of BPE and ADC values on cancer visibility.

METHODS

This prospective study was performed in 164 consecutive premenopausal patients who were diagnosed with invasive breast cancer from November 2016 to December 2018. Two radiologists analyzed the qualitative, quantitative BPE and ADC values of normal contralateral breast parenchyma. We also analyzed the cancer visibility using a three-point scale (0: no visibility, 1: slight visibility, 2: excellent visibility).

RESULTS

The progesterone level was significantly correlated with qualitative BPE grade and quantitative values of the BPE, as well as with the mean ADC. On contrast enhanced image (CEI), the visibility score was significantly associated with tumor size, qualitative and quantitative BPE. On diffusion weighted image (DWI), tumor size was significantly associated with the visibility score, whereas the ADC value was not. Of four lesions with a score of 0 on CEI, three had a score of 2 and one a score of 1 on DWI. Regarding the visibility score on DWI, tumor size and histologic type were significantly different among the three groups.

CONCLUSIONS

Qualitative or quantitative BPE of breast parenchyma was positively correlated with the progesterone level and the mean ADC was negatively correlated. The cancer visibility was affected by BPE on CEI, but not by ADC on DWI. Small-sized cancer and invasive lobular cancer could be the causes of false-negative diagnoses on DWI.

Double reading of diffusion-weighted magnetic resonance imaging for breast cancer detection

PURPOSE

To estimate the performance of diffusion-weighted imaging (DWI) for breast cancer detection.

METHODS

Consecutive breast magnetic resonance imaging examinations performed from January to September 2016 were retrospectively evaluated. Examinations performed before/after neoadjuvant therapy, lacking DWI sequences or reference standard were excluded; breasts after mastectomy were also excluded. Two experienced breast radiologists (R1, R2) independently evaluated only DWI. Final pathology or > 1-year follow-up served as reference standard. Mc Nemar, χ², and κ statistics were applied.

RESULTS

Of 1,131 examinations, 672 (59.4%) lacked DWI sequence, 41 (3.6%) had no reference standard, 30 (2.7%) were performed before/after neoadjuvant therapy, and 10 (0.9%) had undergone bilateral mastectomy. Thus, 378 women aged 49 ± 11 years (mean ± standard deviation) were included, 51 (13%) with unilateral mastectomy, totaling 705 breasts. Per-breast cancer prevalence was 96/705 (13.6%). Per-breast sensitivity was 83/96 (87%, 95% confidence interval 78-93%) for both R1 and R2, 89/96 (93%, 86-97%) for double reading (DR) (p = 0.031); per-lesion DR sensitivity for cancers ≤ 10 mm was 22/31 (71%, 52-86%). Per-breast specificity was 562/609 (93%, 90-94%) for R1, 538/609 (88%, 86-91%) for R2, and 526/609 (86%¸ 83-89%) for DR (p < 0.001). Inter-observer agreement was substantial (κ = 0.736). Acquisition time varied from 3:00 to 6:22 min:s. Per-patient median interpretation time was 46 s (R1) and 51 s (R2).

CONCLUSIONS

DR DWI showed a 93% sensitivity and 88% specificity, with 71% sensitivity for cancers ≤ 10 mm, pointing out a potential for DWI as stand-alone screening method.

Preoperative assessment of breast cancer: Multireader comparison of contrast-enhanced MRI versus the combination of unenhanced MRI and digital breast tomosynthesis

PURPOSE

To compare the sensitivity for breast cancer (BC) and BC size estimation of preoperative contrast-enhanced magnetic resonance imaging (CEMRI) versus combined unenhanced magnetic resonance imaging (UMRI) and digital breast tomosynthesis (DBT).

PATIENTS AND METHODS

We retrospectively included 56 women who underwent DBT and preoperative 1.5 T CEMRI between January 2016-February 2017. Three readers with 2-10 years of experience in CEMRI and DBT, blinded to pathology, independently reviewed CEMRI (diffusion-weighted imaging [DWI], T2-weighted imaging, pre- and post-contrast T1-weighted imaging) and a combination of UMRI (DWI and pre-contrast T1-weighted imaging) and DBT. We calculated per-lesion sensitivity of CEMRI and UMRI + DBT, and the agreement between CEMRI, UMRI and DBT versus pathology in assessing cancer size (Bland-Altman analysis). Logistic regression was performed to assess features predictive of cancer missing.

RESULTS

We included 70 lesions (64% invasive BC, 36% ductal carcinoma in situ or invasive BC with in situ component). UMRI + DBT showed lower sensitivity (86-89%) than CEMRI (94-100%), with a significant difference for the most experienced reader only (p = 0.008). False-positives were fewer with UMRI + DBT (4-5) than with CEMRI (18-25), regardless of the reader (p = 0.001-0.005). For lesion size, UMRI showed closer limits of agreement with pathology than CEMRI or DBT. Cancer size ≤1 cm was the only independent predictor for cancer missing for both imaging strategies (Odds ratio 8.62 for CEMRI and 19.16 for UMRI + DBT).

CONCLUSIONS

UMRI + DBT showed comparable sensitivity and less false-positives than CEMRI in the preoperative assessment of BC. UMRI was the most accurate tool to assess cancer size.

Diffusion-weighted MRI for Unenhanced Breast Cancer Screening

Diffusion-weighted (DW) MRI is a rapid technique that measures the mobility of water molecules within tissue, reflecting the cellular microenvironment. At DW MRI, breast cancers typically exhibit reduced diffusivity and appear hyperintense to surrounding tissues. On the basis of this characteristic, DW MRI may offer an unenhanced method to detect breast cancer without the costs and safety concerns associated with dynamic contrast material-enhanced MRI, the current reference standard in the setting of high-risk screening. This application of DW MRI has not been widely explored but is particularly timely given the growing health concerns related to the long-term use of gadolinium-based contrast material. Moreover, increasing breast density notification legislation across the United States is raising awareness of the limitations of mammography in women with dense breasts, emphasizing the need for additional cost-effective supplemental screening examinations. Preliminary studies suggest unenhanced MRI with DW MRI may provide higher sensitivity than screening mammography for the detection of breast malignancies. Larger prospective multicenter trials are needed to validate single-center findings and assess the performance of DW MRI for generalized breast cancer screening. Standardization of DW MRI acquisition and interpretation is essential to ensure reliable sensitivity and specificity, and an optimal approach for screening using readily available techniques is proposed here.

Fast MRI breast cancer screening - Ready for prime time

OBJECTIVE

The manuscript discusses landmark studies using abbreviated MRI for breast cancer screening. This includes abbreviated dynamic contrast enhanced MRI and diffusion weighted imaging. Our institutional experience with abbreviated MR protocol for breast cancer screening is also described.

CONCLUSION

Abbreviated MRI protocols were found to demonstrate value for screening of breast cancer. It has been shown that abbreviated protocol MRI provides similar diagnostic sensitivities to full protocol MRI for breast cancer in women with increased lifetime risk. Our institutional abbreviated MRI protocol for breast cancer offers improved time and workflow efficiencies and has the potential to increase the number of breast cancers detected and the detection of pathologically relevant invasive breast cancer at earlier stages.

Role of Breast MRI in the Evaluation and Detection of DCIS: Opportunities and Challenges

Historically, breast magnetic resonance imaging (MRI) was not considered an effective modality in the evaluation of ductal carcinoma in situ (DCIS). Over the past decade this has changed, with studies demonstrating that MRI is the most sensitive imaging tool for detection of all grades of DCIS. It has been suggested that not only is breast MRI the most sensitive imaging tool for detection but it may also detect the most clinically relevant DCIS lesions. The role and outcomes of MRI in the preoperative setting for patients with DCIS remains controversial; however, several studies have shown benefit in the preoperative evaluation of extent of disease as well as predicting an underlying invasive component. The most common presentation of DCIS on MRI is nonmass enhancement (NME) in a linear or segmental distribution pattern. Maximizing breast MRI spatial resolution is therefore beneficial, given the frequent presentation of DCIS as NME on MRI. Emerging MRI techniques, such as diffusion-weighted imaging (DWI), have shown promising potential to discriminate DCIS from benign and invasive lesions. Future opportunities including advanced imaging visual techniques, radiomics/radiogenomics, and machine learning / artificial intelligence may also be applicable to the detection and treatment of DCIS. Level of Evidence: 3 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2020;52:697-709.

Diffusion MRI of the breast: Current status and future directions

Diffusion-weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non-Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characterization of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:70-90.

Non-contrast MRI for breast screening: preliminary study on detectability of benign and malignant lesions in women with dense breasts

PURPOSE

The importance of breast cancer screening has long been known. Unfortunately, there is no imaging modality for screening women with dense breasts that is both sensitive and without concerns regarding potential side effects. The purpose of this study is to explore the possibility of combined diffusion-weighted imaging and turbo inversion recovery magnitude MRI (DWI + TIRM) to overcome the difficulty of detection sensitivity and safety.

METHODS

One hundred and seventy-six breast lesions from 166 women with dense breasts were retrospectively evaluated. The lesion visibility, area under the curve (AUC), sensitivity and specificity of cancer detection by MG, DWI + TIRM, and clinical MRI were evaluated and compared. MG plus clinical MRI served as the gold standard for lesion detection and pathology served as the gold standard for cancer detection.

RESULTS

Lesion visibility of DWI + TIRM (96.6%) was significantly superior to MG (67.6%) in women with dense breasts (p < 0.001). There was no significant difference compared with clinical MRI. DWI + TIRM showed higher accuracy (AUC = 0.935) and sensitivity (93.68%) for breast cancer detection than MG (AUC = 0.783, sensitivity = 46.32%), but was comparable to clinical MRI (AUC = 0.944, sensitivity = 93.68%). The specificity of DWI + TIRM (83.95%) was lower than MG (98.77%), but higher than clinical MRI (77.78%).

CONCLUSIONS

DWI combined with TIRM could be a safe, sensitive, and practical alternative for screening women with dense breasts.