Detecting Breast Cancer with Non-contrast MR Imaging: Combining Diffusion-weighted and STIR Imaging

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.

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.

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.

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.

Characterization of Effects of Compressed Sensing on High Spectral and Spatial Resolution (HiSS) MRI with Comparison to SENSE

High Spectral and Spatial resolution (HiSS) MRI shows high diagnostic performance in the breast. Acceleration methods based on k-space undersampling could allow stronger T2*-based image contrast and/or higher spectral resolution, potentially increasing diagnostic performance. An agar/oil phantom was prepared with water-fat boundaries perpendicular to the readout and phase encoding directions in a breast coil. HiSS MRI was acquired at 3T, at sensitivity encoding (SENSE) acceleration factors R of up to 10, and the R = 1 dataset was used to simulate corresponding compressed sensing (CS) accelerations. Image quality was evaluated by quantifying noise and artifact levels. Effective spatial resolution was determined via modulation transfer function analysis. Dispersion vs. absorption (DISPA) analysis and full width at half maximum (FWHM) quantified spectral lineshape changes. Noise levels remained constant with R for CS but amplified with SENSE. SENSE preserved the spatial resolution of HiSS MRI, while CS reduced it in the phase encoding direction. SENSE showed no effect on FWHM or DISPA markers, while CS increased FWHM. Thus, CS might perform better in noise-limited or geometrically constrained applications, but in geometric configurations specific to breast MRI, spectral analysis might be compromised, decreasing the diagnostic performance of HiSS MRI.

Surgical treatment trends and identification of primary breast tumors after surgery in occult breast cancer: a study based on the Japanese National Clinical Database-Breast Cancer Registry

BACKGROUND

Occult breast cancer (OBC) is classified as carcinoma of an unknown primary site, and the adequate therapy for OBC remains controversial. This retrospective study aimed to reveal the transition in breast cancer therapy and the frequency of primary breast tumors after resection in clinical OBC (cT0N+) patients using the Japanese Breast Cancer Registry database.

METHODS

We enrolled OBC patients with cT0N+ from the registry between 2010 and 2018. On the basis of the period of diagnosis, OBC patients were divided into the following two groups: 2010-2014 and 2015-2018. We described the transition in treatments and tumor characteristics. After breast resection, the frequency of pathological identification of primary tumors and tumor sizes was assessed.

RESULTS

Of the 687,468 patients registered, we identified 148 cT0N+ patients with a median age of 61 years. Of these patients, 64.2% (n = 95) received breast surgery (2010-2014: 79.1%, 2015-2018: 50.0%). Axillary lymph node dissection was performed in 92.6% (n = 137, 2010-2014: 91.6%, 2015-2018: 93.4%). The breast tumor size in the resected breast was 0-7.0 cm (median: 0 cm, 2010-2014: 0-7.0 cm [median: 0 cm], 2015-2018: 0-6.2 cm [median: 0 cm]). The pathological identification rate of the primary tumor was 41.1% (n = 39, 2010-2014: 40.4%, 2015-2018: 42.1%).

CONCLUSIONS

Breast surgery for cT0N+ decreased between 2010 and 2018. Despite the high identification rate of primary tumors, most tumors were small, and there was no significant change in the identification rate or invasive diameter of the identified tumors after 2010.

Characterization of the diffusion signal of breast tissues using multi-exponential models

PURPOSE

Restriction spectrum imaging (RSI) decomposes the diffusion-weighted MRI signal into separate components of known apparent diffusion coefficients (ADCs). The number of diffusion components and optimal ADCs for RSI are organ-specific and determined empirically. The purpose of this work was to determine the RSI model for breast tissues.

METHODS

The diffusion-weighted MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxels in cancer and control ROIs. Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative-fitting residuals and Bayesian information criterion were assessed. Contrast-to-noise ratio between cancer and fibroglandular tissue in RSI-derived signal contribution maps was compared to DCE imaging.

RESULTS

A total of 74 women with breast cancer were scanned at 3.0 Tesla MRI. The fitting residuals of conventional ADC and Bayesian information criterion suggest that a 3-component model improves the characterization of the diffusion signal over a biexponential model. Estimated ADCs of triexponential model were D_1,3 = 0, D_2,3 = 1.5 × 10^-3 , and D_3,3 = 10.8 × 10^-3 mm² /s. The RSI-derived signal contributions of the slower diffusion components were larger in tumors than in fibroglandular tissues. Further, the contrast-to-noise and specificity at 80% sensitivity of DCE and a subset of RSI-derived maps were equivalent.

CONCLUSION

Breast diffusion-weighted MRI signal was best described using a triexponential model. Tumor conspicuity in breast RSI model is comparable to that of DCE without the use of exogenous contrast. These data may be used as differential features between healthy and malignant breast tissues.

Triexponential Diffusion Analysis of Diffusion-weighted Imaging for Breast Ductal Carcinoma in Situ and Invasive Ductal Carcinoma

Purpose

To obtain detailed information in breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) using triexponential diffusion analysis.

Methods

Diffusion-weighted images (DWI) of the breast were obtained using single-shot diffusion echo-planar imaging with 15 b-values. Mean signal intensities at each b-value were measured in the DCIS and IDC lesions and fitted with the triexponential function based on a two-step approach: slow-restricted diffusion coefficient (D_s) was initially determined using a monoexponential function with b-values > 800 s/mm². The diffusion coefficient of free water at 37°C was assigned to the fast-free diffusion coefficient (D_f). Finally, the perfusion-related diffusion coefficient (D_p) was derived using all the b-values. Furthermore, biexponential analysis was performed to obtain the perfusion-related diffusion coefficient (D^*) and the perfusion-independent diffusion coefficient (D). Monoexponential analysis was performed to obtain the apparent diffusion coefficient (ADC). The sensitivity and specificity of the aforementioned diffusion coefficients for distinguishing between DCIS and IDC were evaluated using the pathological results.

Results

The D_s, D, and ADC of DCIS were significantly higher than those of IDC (P < 0.01 for all). There was no significant correlation between D_p and D_s, but there was a weak correlation between D^* and D. The combination of D_p and D_s showed higher sensitivity and specificity (85.9% and 71.4%, respectively), compared to the combination of D^* and D (81.5% and 33.3%, respectively).

Conclusion

Triexponential analysis can provide detailed diffusion information for breast tumors that can be used to differentiate between DCIS and IDC.

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.

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.

Correlation between ultrasound-guided percutaneous breast biopsy and diffusion-weighted magnetic resonance imaging of the breast for evaluation of solid breast lesions

Background

MRI’s role had been increasing in breast imaging. In this study, we evaluated the role of diffusion-weighted MRI in correlation with ultrasound-guided percutaneous breast biopsy for diagnosis of solid breast lesions.

Results

Sixty female patients were diagnosed by clinical examination and mammography and planned for ultrasound-guided breast biopsy. Diffusion-weighted MRI was done before the biopsy for results correlation. It was found that the diffusion-weighted MRI was valuable in evaluating solid female breast lesions, showing a sensitivity of 96%, specificity of 91.4%, positive predictive value of 100%, negative predictive value of 97%, and accuracy of 93.3% % compared to pathological results.

Conclusion

Diffusion-weighted MRI has a great role in evaluating solid breast lesions.

Confounding factors in breast magnetic resonance fingerprinting: B 1 + , slice profile, and diffusion effects

PURPOSE

Magnetic resonance fingerprinting (MRF) offers rapid quantitative imaging but may be subject to confounding effects (CE) if these are not included in the model-based reconstruction. This study characterizes the influence of in-plane B 1 + , slice profile and diffusion effects on T₁ and T₂ estimation in the female breast at 1.5T.

METHODS

Simulations were used to predict the influence of each CE on the accuracy of MRF and to investigate the influence of electronic noise and spiral aliasing artefacts. The experimentally observed bias in regions of fibroglandular tissue (FGT) and fatty tissue (FT) was analyzed for undersampled spiral breast MRF data of 6 healthy volunteers by performing MRF reconstruction with and without a CE.

RESULTS

Theoretic analysis predicts T₁ under-/T₂ overestimation if the nominal flip angles are underestimated and inversely, T₁ under-/T₂ overestimation if omitting slice profile correction, and T₁ under-/T₂ underestimation if omitting diffusion in the signal model. Averaged over repeated signal simulations, including spiral aliasing artefacts affected precision more than accuracy. Strong in-plane B 1 + effects occurred in vivo, causing T₂ left-right inhomogeneity between both breasts. Their correction decreased the T₂ difference from 29 to 5 ms in FGT and from 29 to 9 ms in FT. Slice profile correction affected FGT T₂ most strongly, resulting in -22% smaller values. For the employed spoiler gradient strengths, diffusion did not affect the parameter maps, corresponding well with theoretic predictions.

CONCLUSION

Understanding CEs and their relative significance for an MRF sequence is important when defining an MRF signal model for accurate parameter mapping.

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.

Measurement of apparent diffusion coefficient in discrimination of benign and malignant axillary lymph nodes

Purpose

We aimed to determine the contribution of the apparent diffusion coefficient (ADC) value in the detection of axillary lymph node metastasis.

Material and methods

Breast magnetic resonance of 58 patients, performed in the radiology clinic of our hospital between 2015 and 2017 were examined retrospectively, and 43 lymph nodes in 43 patients were included in the study. They were evaluated morphologically on T1W and T2W sequences, and the lymph nodes showing rounded shape, focal or diffuse cortical thickness of more than 3 mm, and partial or total effacement of fatty hilum were included in the study. Subsequently, their ADC values were measured.

Results

There were 43 lymph nodes, 20 of which were malignant and 23 of which were benign. While the mean ADC value of malignant axillary lymph nodes was 0.749 10^-3 mm²/s (0.48-1.342), it was 0.982 10^-3 mm²/s (0.552-1.986) for benign lymph nodes. When the ADC cut-off value was taken as ≤ 0.753 × 10^-3 mm²/s, its discrimination power between benign and malignant axillary lymph nodes was as follows: sensitivity - 60%; specificity - 91.3%; accuracy - 76.7%; positive predictive value - 85.7%; and negative predictive value - 72.4%.

Conclusions

There was no significant difference between mean ADC value of 12 lymphadenopathies (LAP) associated with inflammatory breast diseases (granulomatous mastitis and acute suppurative mastitis) and mean ADC value of metastatic lymph nodes. However, the ADC value of lymph nodes showing thickened cortex due to systemic inflammatory diseases was over 1, and there was a statistically significant difference when compared with metastatic lymph nodes.

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.

A Clinical Approach to Diffusion-Weighted Magnetic Resonance Imaging in Evaluating Chest Wall Invasion of Breast Tumors

Objective:

The purpose of this study is to evaluate diffusion weighted magnetic rsonance imaging (MRI) acquisitions in delineating posterior extent of breast tumors and in predicting chest wall invasion prior to treatment. To our knowledge, there has not been any literature specifically evaluating the utility of diffusion-weighted acquisitions in chest wall invasion of breast tumors.

Materials and Methods:

A retrospective review of our breast imaging database for keywords “chest wall invasion” and “breast MRI” was performed over the last 14 years. Diffusion sequences, T1 sequences (pre and post contrast), and T2 sequences were evaluated. Apparent diffusion coefficient (ADC) values in tumor and chest wall were assessed. Imaging findings were correlated with surgical pathology.

Results:

23 patients met inclusion criteria. All 23 had loss of fat plane on T2 sequences. 22/23 had loss of fat plane on postcontrast T1 sequences. Pectoralis muscle enhancement was present in 19/23 (83%) tumors and chest wall enhancement was present 9/23 (39%) tumors. Qualitative restricted diffusion within the pectoralis muscle was present in 18/23 (71%) tumors and in the chest wall was present in 8/23 (35%) tumors. Mean ADC values were 1.15 s/mm² in the tumor and 1.29 s/mm² in the chest wall. Sensitivity, specificity, positive predictive value and negative predictive value were 100%, 36%, 63%, and 100% for chest wall enhancement respectively and 69%, 36%, 61%, and 80% for chest wall diffusion-weighted imaging restriction respectively.

Conclusion:

Diffusion weighted sequences can be helpful in characterizing chest wall invasion of breast tumors.

Diffusion-weighted imaging of the breast: current status as an imaging biomarker and future role

Diffusion-weighted imaging (DWI) of the breast is a MRI sequence that shows several advantages when compared to the dynamic contrast-enhanced sequence: it does not need intravenous contrast, it is relatively quick and easy to implement (artifacts notwithstanding). In this review, the current applications of DWI for lesion characterization and prognosis as well as for response evaluation are analyzed from the point of view of the necessary steps to become a useful surrogate of underlying biological processes (tissue architecture and cellularity): from the proof of concept, to the proof of mechanism, the proof of principle and finally the proof of effectiveness. Future applications of DWI in screening, DWI modeling and radiomics are also discussed.

Potential of Noncontrast Magnetic Resonance Imaging With Diffusion-Weighted Imaging in Characterization of Breast Lesions: Intraindividual Comparison With Dynamic Contrast-Enhanced Magnetic Resonance Imaging

OBJECTIVES

The aim of this study was to assess the potential of noncontrast magnetic resonance imaging (NC-MRI) with diffusion-weighted imaging (DWI) in characterization of breast lesions in comparison to dynamic contrast-enhanced MRI (DCE-MRI) at 3 T.

MATERIALS AND METHODS

Consecutive patients with conventional imaging (mammography, ultrasound) BI-RADS 4/5 findings were included in this institutional review board-approved single-center study. All underwent 3 T breast MRI including readout-segmented DWI, DCE, and T2-weighted sequences. Final diagnosis was defined by histopathology or follow-up (>24 months). Two experienced radiologists (R1, R2) independently assigned lesion conspicuity (0 = minimal to 3 = excellent) and BI-RADS scores to NC-MRI (readout-segmented DWI including apparent diffusion coefficient maps) and DCE-MRI (DCE and T2-weighted). Receiver operating characteristics, κ statistics, and visual grading characteristics analysis were applied.

RESULTS

Sixty-seven malignant and 56 benign lesions were identified in 113 patients (mean age, 54 ± 14 years). Areas under the receiver operating characteristics curves were similar: DCE-MRI: 0.901 (R1), 0.905 (R2); NC-MRI: 0.882 (R1), 0.854 (R2); P > 0.05, respectively. The κ agreement was 0.968 (DCE-MRI) and 0.893 (NC-MRI). Visual grading characteristics analysis revealed superior lesion conspicuity by DCE-MRI (0.661, P < 0.001).

CONCLUSIONS

Diagnostic performance and interreader agreement of both NC-MRI and DCE-MRI is high, indicating a potential use of NC-MRI as an alternative to DCE-MRI. However, inferior lesion conspicuity and lower interreader agreement of NC-MRI need to be considered.

Occult breast cancer may originate from ectopic breast tissue present in axillary lymph nodes

PURPOSE

Occult breast cancer (OBC) is classified as a carcinoma of unknown primary, and involves axillary lymphadenopathy and is histologically consistent with metastatic breast cancer. OBC has been conventionally considered as a metastatic lymph node lesion, the origin of which is an undetectable breast tumor. Therefore, OBC patients would usually have undergone axillary lymph node dissection, and mastectomy or whole breast radiotherapy (WBRT). However, majority of OBC reports have been based on cases that were diagnosed during a period when diagnostics was still relatively primitive, and when magnetic resonance imaging was not yet a standard preoperative assessment. Therefore, there have been many false negatives in the breast based on preoperative assessment.

METHODS

We herein hypothesize that the origin of OBC is ectopic breast tissue present in axillary lymph nodes (ALNs). If our hypothesis is true, mastectomy and WBRT may be unnecessary for OBC patients.

RESULTS

Our hypothesis is supported by several findings. First, advances in radiological imaging have suggested that a primary breast tumor is absent in OBC patients. Second, proliferative breast lesions arising from ectopic breast present in ALNs have been reported. Lastly, cellular subtypes in OBC based on immunohistochemistry are of various types including ordinary breast cancer and the prognosis is not worse than stage II breast cancer.

CONCLUSION

It is important to distinguish between "primary" OBC in ALNs and "metastatic" OBC from micro-primary breast tumor. Further studies are required to determine if omission of mastectomy and WBRT is acceptable.

Diffusion-weighted breast imaging

Magnetic resonance imaging (MRI) of the breast represents one of the most sensitive imaging modalities in breast cancer detection. Diffusion-weighted imaging (DWI) is a sequence variation introduced as a complementary MRI technique that relies on mapping the diffusion process of water molecules thereby providing additional information about the underlying tissue. Since water diffusion is more restricted in most malignant tumors than in benign ones owing to the higher cellularity of the rapidly proliferating neoplasia, DWI has the potential to contribute to the identification and characterization of suspicious breast lesions. Thus, DWI might increase the diagnostic accuracy of breast MRI and its clinical value. Future applications including optimized DWI sequences, technical developments in MR devices, and the application of radiomics/artificial intelligence algorithms may expand the potential of DWI in breast imaging beyond its current supplementary role.

Impact of Advancing Technology on Diagnosis and Treatment of Breast Cancer

New emerging breast imaging techniques have shown great promise in breast cancer screening, evaluation of extent of disease, and response to neoadjuvant therapy. Tomosynthesis, allows 3-dimensional imaging of the breast, and increases breast cancer detection. Fast abbreviated MRI has reduced time and costs associated with traditional breast MRI while maintaining cancer detection. Diffusion-weighted imaging is a functional MRI technique that does not require contrast and has shown potential in screening, lesion characterization and also evaluation of treatment response. New image-guided preoperative localizations are available that have increased patient satisfaction and decreased operating room delays.

Comparison of detectability of breast cancer by abbreviated breast MRI based on diffusion-weighted images and postcontrast MRI

PURPOSE

To compare the detectability of unenhanced abbreviated magnetic resonance imaging (MRI) based on diffusion-weighted imaging (DWI) and abbreviated postcontrast MRI for breast cancer.

METHODS

The study population consisted of 87 patients undergoing breast MRI between December 2016 and March 2017 in a clinical setting. All breast MRIs were performed using a 1.5-T MRI scanner with a 16-channel breast radiofrequency coil. The abbreviated protocols based on DWI (AP1) and postcontrast MRI (AP2) were assessed independently by two radiologists. Sensitivity and specificity were calculated. Receiver operating characteristic analysis was performed and the areas under the curves (AUCs) were compared between AP1 and AP2.

RESULTS

The study included 87 patients with 89 breast cancer lesions ≤ 2 cm in diameter. The sensitivity/specificity for AP1 and AP2 for reader 1 was 89.9/97.6% and 95.5/90.6%, respectively, and those for reader 2 was 95.5/94.1% and 98.9/94.1%, respectively. The AUCs for AP1 and AP2 for reader 1 were 0.9629 and 0.9640 (p = 0.95), respectively, and those for reader 2 were 0.9755 and 0.9843 (p = 0.46), respectively.

CONCLUSIONS

The detectability of the unenhanced abbreviated protocol based on DWI would be comparable to that of abbreviated postcontrast MRI for breast cancer.

Diffusion-Weighted Imaging for the Discrimination of Benign and Malignant Breast Masses; Utility of ADC and Relative ADC

Purpose:

To determine the contribution of apparent diffusion coefficient (ADC), and relative ADC (rADC) values to differentiate between benign and malignant breast masses.

Materials and Methods:

Magnetic resonance imaging (MRI) of the breast with diffusion-weighted imaging (DWI) of patients with benign or malignant breast masses diagnosed either by histopathological findings or by follow-up imaging were evaluated retrospectively. Histopathological analyses were performed for 71 lesions (80.7%) while the remaining were followed up every six months for one year. DWI was performed using b-values of 0 and 1000 sec/mm², and ADC and rADC were calculated and compared. A receiver operating characteristic (ROC) curve and Youden index were used to evaluate the parameter’s optimal threshold and diagnostic value. Statistical significance was set as p < 0.05.

Results:

Eighty-eight lesions from a total of 81 patients, aged between 16 and 73 (mean age 42 ± 11.3) years were obtained and evaluated. Pathological results of 34 (38.6%) out of 71 lesions were malignant and 37 lesions (42%) were benign. Seventeen (19.3%) lesions remained stable at one-year follow-up and were accepted as benign breast masses. Mean ADC values of benign and malignant lesions were 1.584 × 10^–3mm²/sec and 0.884 × 10^–3mm²/sec (p < 0.05), respectively. Sensitivity and specificity of ADC were 88% and 87%, respectively at a cut-off value of 1.04 × 10^–3mm²/sec. Mean rADC was 0.931 for benign lesions and 0.557 for malignant lesions (p < 0.05). Sensitivity and specificity were 82% and 83% at a cut-off value of 0.639. No prominent superiority of rADC over ADC is identified in the differentiation of breast masses.

Conclusion:

ADC and rADC values derived from DWI can be equally useful in clinical setting to differentiate benign from malignant breast masses.

Breast cancer diagnosis: Imaging techniques and biochemical markers

Breast cancer is a complex disease which is found as the second cause of cancer-associated death among women. Accumulating of evidence indicated that various factors (i.e., gentical and envirmental factors) could be associated with initiation and progression of breast cancer. Diagnosis of breast cancer patients in early stages is one of important aspects of breast cancer treatment. Among of various diagnosis platforms, imaging techniques are main diagnosis approaches which could provide valuable data on patients with breast cancer. It has been showed that various imaging techniques such as mammography, magnetic resonance imaging (MRI), positron-emission tomography (PET), Computed tomography (CT), and single-photon emission computed tomography (SPECT) could be used for diagnosis and monitoring patients with breast cancer in various stages. Beside, imaging techniques, utilization of biochemical biomarkers such as proteins, DNAs, mRNAs, and microRNAs could be employed as new diagnosis and therapeutic tools for patients with breast cancer. Here, we summarized various imaging techniques and biochemical biomarkers could be utilized as diagnosis of patients with breast cancer. Moreover, we highlighted microRNAs and exosomes as new diagnosis and therapeutic biomarkers for monitoring patients with breast cancer.

MR Imaging Features of Tubular Carcinoma: Preliminary Experience in Twelve Masses

Objective

We retrospectively analyzed the magnetic resonance (MR) imaging features and diffusion-weighted imaging findings of the 12 masses of 10 patients with tubular carcinoma (TC), including mammography and sonography findings.

Materials and Methods

Mammographic, sonographic and magnetic resonance imaging features in 12 histopathologically confirmed masses diagnosed as TC of the breast within 10 patients were evaluated. Morphologic characteristics, enhancement features, apparent diffusion coefficient (ADC) values were reviewed.

Results

On mammography (n=5), TC appeared as high density masses with indistinct, spiculated or obscured margins. Sonographically, TC appeared as a hypoechoic appearance (n=12) with posterior acoustic shadowing in nine. On MR imaging, the margins of ten of twelve masses were irregular. Internal enhancement patterns were heterogeneous in 10 patients. Dynamic enhancement patterns illustrated plateau kinetics (n=8). On the T2-weighted images 4 masses were hypointense, and 8 were hyperintense; hypointense internal septation was found in seven of these. Tubular carcinoma appeared as hyperintense on diffusion-weighted imaging with ADC values of 0.85±0.16×10-3 mm²/s that was lower than the normal parenchyma of 1.25±0.25×10-3 mm²/s.

Conclusion

According to our study with a limited number of cases, tubular carcinomas can be described as hyperintense breast carcinomas with or without dark internal septation like appearance on T2-weighted images. Low ADC values from DW imaging can be used to differentiate TC from hyperintense benign breast lesions.

Addition of T2-guided optical tomography improves noncontrast breast magnetic resonance imaging diagnosis

Background

While dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) is recognized as the most sensitive examination for breast cancer detection, it has a substantial false positive rate and gadolinium (Gd) contrast agents are not universally well tolerated. As a result, alternatives to diagnosing breast cancer based on endogenous contrast are of growing interest. In this study, endogenous near-infrared spectral tomography (NIRST) guided by T2 MRI was evaluated to explore whether the combined imaging modality, which does not require contrast injection or involve ionizing radiation, can achieve acceptable diagnostic performance.

Methods

Twenty-four subjects—16 with pathologically confirmed malignancy and 8 with benign abnormalities—were simultaneously imaged with MRI and NIRST prior to definitive pathological diagnosis. MRIs were evaluated independently by three breast radiologists blinded to the pathological results. Optical image reconstructions were constrained by grayscale values in the T2 MRI. MRI and NIRST images were used, alone and in combination, to estimate the diagnostic performance of the data. Outcomes were compared to DCE results.

Results

Sensitivity, specificity, accuracy, and area under the curve (AUC) of noncontrast MRI when combined with T2-guided NIRST were 94%, 100%, 96%, and 0.95, respectively, whereas these values were 94%, 63%, 88%, and 0.81 for DCE MRI alone, and 88%, 88%, 88%, and 0.94 when DCE-guided NIRST was added.

Conclusion

In this study, the overall accuracy of imaging diagnosis improved to 96% when T2-guided NIRST was added to noncontrast MRI alone, relative to 88% for DCE MRI, suggesting that similar or better diagnostic accuracy can be achieved without requiring a contrast agent.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0902-x) contains supplementary material, which is available to authorized users.

MRI-guided breast interventions

Magnetic resonance imaging (MRI)-guided interventions, including biopsies and wire localizations, are fundamental to any breast imaging practice due to the high sensitivity but limited specificity of breast MRI. The basic steps of MRI-guided biopsies are similar regardless of the vendor or platform, and technical considerations include approach planning, patient preparation and positioning, lesion targeting, and directional sampling using a vacuum-assisted biopsy technique. Unique challenges related to MRI-guided biopsies include vanishing lesions due to contrast washout, obscuration of the biopsy site due to susceptibility artifacts, and limited access to posteromedial lesions. A careful approach to planning, patient positioning, and lesion targeting will maximize the chances for a successful biopsy. Due to overlapping imaging features between benign and malignant lesions, radiologic-pathologic concordance is difficult and essential for further patient management.

LEVEL OF EVIDENCE

5 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:631-645.

Differentiation of malignant and benign breast lesions: Added value of the qualitative analysis of breast lesions on diffusion-weighted imaging (DWI) using readout-segmented echo-planar imaging at 3.0 T

Objective

To determine the added value of qualitative analysis as an adjunct to quantitative analysis for the discrimination of benign and malignant lesions in patients with breast cancer using diffusion-weighted imaging (DWI) with readout-segmented echo-planar imaging (rs-EPI).

Methods

A total of 99 patients with 144 lesions were reviewed from our prospectively collected database. DWI data were obtained using rs-EPI acquired at 3.0 T. The diagnostic performances of DWI in the qualitative, quantitative, and combination analyses were compared with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Additionally, the effect of lesion size on the diagnostic performance of the DWI combination analysis was evaluated.

Results

The strongest indicators of malignancy on DWI were a heterogeneous pattern (P = 0.005) and an apparent diffusion coefficient (ADC) value <1.0 × 10–3 mm2/sec (P = 0.002). The area under the curve (AUC) values for the qualitative analysis, quantitative analysis, and combination analysis on DWI were 0.732 (95% CI, 0.651–0.803), 0.780 (95% CI, 0.703–0.846), and 0.826 (95% CI, 0.754–0.885), respectively (P<0.0001). The AUC for the combination analysis on DWI was superior to that for DCE-MRI alone (0.651, P = 0.003) but inferior to that for DCE-MRI plus the ADC value (0.883, P = 0.03). For the DWI combination analysis, the sensitivity was significantly lower in the size ≤1 cm group than in the size >1 cm group (80% vs. 95.6%, P = 0.034).

Conclusions

Qualitative analysis of tumor morphology was diagnostically applicable on DWI using rs-EPI. This qualitative analysis adds value to quantitative analyses for lesion characterization in patients with breast cancer.

Fast bilateral breast coverage with high spectral and spatial resolution (HiSS) MRI at 3T

PURPOSE

To develop and assess a full-coverage, sensitivity encoding (SENSE)-accelerated breast high spatial and spectral resolution (HiSS) magnetic resonance imaging (MRI) within clinically reasonable times as a potential nonenhanced MRI protocol for breast density measurement or breast cancer screening.

MATERIALS AND METHODS

Sixteen women with biopsy-proven cancer or suspicious lesions, and 13 women who were healthy volunteers or were screened for breast cancer, received 3T breast MRI exams, including SENSE-accelerated HiSS MRI, which was implemented as a submillimeter spatial resolution echo-planar spectroscopic imaging (EPSI) sequence. In postprocessing, fat and water resonance peak height and integral images were generated from EPSI data. The postprocessing software was custom-designed, and new algorithms were developed to enable processing of whole-coverage axial HiSS datasets. Water peak height HiSS images were compared to pre- and postcontrast T₁ -weighted images. Fat suppression was quantified as parenchymal-to-suppressed-fat signal ratio in HiSS water peak height and nonenhanced T₁ -weighted images, and artifact levels were scored.

RESULTS

Approximately a 4-fold decrease in acquisition speed, with a concurrent 2.5-fold decrease in voxel size, was achieved, with low artifact levels, and with spectral signal-to-noise ratio (SNR) of 45:1. Fat suppression was 1.9 times more effective (P < 0.001) in HiSS images than in T₁ -weighted images (SPAIR), and HiSS images showed higher SNR in the axilla. HiSS MRI visualized 10 of 13 malignant lesions identified on dynamic contrast-enhanced (DCE)-MRI, and did not require skin removal in postprocessing to generate maximum intensity projection images.

CONCLUSION

We demonstrate full-coverage, SENSE-accelerated breast HiSS MRI within clinically reasonable times, as a potential protocol for breast density measurement or breast cancer screening.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1341-1348.

Can unenhanced breast MRI be used to decrease negative biopsy rates?

PURPOSE

We aimed to determine whether low-risk breast masses can be effectively managed with unenhanced magnetic resonance imaging (MRI) combining T2-weighted sequences with diffusion-weighted imaging (DWI) instead of immediate biopsy to decrease negative biopsy rates.

METHODS

After institutional review board and patient approvals, 141 consecutive women with 156 low-risk breast masses, who underwent unenhanced MRI and later on received a final diagnosis, were included in the study. There were 72 BI-RADS 3 masses in women with relative risk factors and 84 BI-RADS 4A masses, all referred for biopsy. Apparent diffusion coefficient (ADC) cutoff was 0.90×10-3 mm2/s. According to ADC values and T2-weighted imaging characteristics, masses were classified as either malignant or benign. Unenhanced MRI results were compared with final diagnoses obtained by histopathology or imaging surveillance, and diagnostic values were calculated.

RESULTS

Of 156 masses, 112 underwent biopsy. Four malignancies were diagnosed, three of which having ADC values lower than the cutoff. In women who rejected the biopsy, masses were stable during a follow-up of at least two years (n=44). MRI revealed 91% specificity and 99% negative predictive value (NPV) for detection of breast cancer.

CONCLUSION

Combination of T2-weighted imaging with DWI is a feasible method to further characterize breast masses with a low probability of malignancy. With the use of unenhanced MRI instead of immediate biopsy, it might be possible to decrease negative biopsy rates of low-risk breast masses.

Value of Apparent Diffusion Coefficient Values in Differentiating Malignant and Benign Breast Lesions

BACKGROUND

Magnetic resonance imaging (MRI) has become a diagnostic and problem solving method for the breast examinations in addition to conventional breast examination methods. Diffusion-weighted imaging (DWI) adds valuable information to conventional MRI.

AIMS

Our aim was to show the impact of apparent diffusion coefficient (ADC) values acquired with DWI to differentiate benign and malignant breast lesions.

STUDY DESIGN

Diagnostic accuracy study.

METHODS

Forty-six women with 58 breast masses (35 malignant, 23 benign) were examined on a 1.5 T clinical MRI scanner. The morphologic characteristics of the lesions on conventional MRI sequences and contrast uptake pattern were assessed. ADC values of both lesions and normal breast parenchyma were measured. The ADC values obtained were statistically compared with the histopathologic results using Paired Samples t-Test.

RESULTS

Multiple lesions were detected in 12 (26%) of the patients, while only one lesion was detected in 34 (74%). Overall, 35 lesions out of 58 were histopathologically proven to be malignant. In the dynamic contrast-enhanced series, 5 of the malignant lesions were type 1, while 8 benign lesions revealed either type 2 or 3 time signal intensity curves (85% sensitivity, 56% spesifity). Mean ADC values were significantly different in malignant vs. benign lesions. (1.04±0.29×10(-3) cm(2)/sec vs. 1.61±0.50×10(-3) cm(2)/sec for the malignant and benign lesions, respectively, p=0.03). A cut-off value of 1.30×10(-3) mm(2)/sec for ADC detected with receiver operating characteristic analysis yielded 89.1% sensitivity and 100% specificity for the differentiation between benign and malignant lesions.

CONCLUSION

ADC values improve the diagnostic accuracy of solid breast lesions when evaluated with the conventional MRI sequences. Therefore, DWI should be incorporated to routine breast MRI protocol.

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

OBJECTIVE

The objective of our study was to evaluate the performance of DWI to detect mammographically occult breast cancer in elevated-risk women with dense breasts.

MATERIALS AND METHODS

We retrospectively reviewed all women who underwent screening breast MRI at our institution from January 2007 through May 2013. We created a case-control cohort composed of 48 subjects with mammographically dense breasts: 24 with mammographically occult cancer detected on MRI and 24 healthy women with negative MRI findings who were matched to the subjects with breast cancer patients for age, breast density, and MRI protocol. The contrast-to-noise ratio (CNR), apparent diffusion coefficient (ADC), and conspicuity score (range, 1-5) were assessed on DWI for all malignancies. Lesions and normal tissue were compared using the Wilcoxon signed rank test; associations with clinical characteristics were evaluated using the Mann-Whitney U test. Three experienced breast imagers who were blinded to medical records and contrast-enhanced MRI findings independently evaluated the unenhanced MRI scans of the 48 women for the presence of cancer.

RESULTS

Mammographically occult breast cancers (invasive carcinoma, n = 16; ductal carcinoma in situ, n = 8) in women with dense breasts typically exhibited higher signal intensity on DWI than normal parenchyma (median CNR of cancers, 1.4; median conspicuity score of cancers, 4) and a lower ADC (median, 1.31 vs 1.79 × 10(-3) mm(2)/s, respectively) (p < 0.0001). The conspicuity score, CNR, and ADC were not associated with patient age, menopausal status, lesion size, morphologic type, or histology (p > 0.05). Average reader performance using unenhanced MRI was 45% sensitivity, 91% specificity, 62% positive predictive value, and 83% negative predictive value.

CONCLUSION

In elevated-risk women with dense breasts, DWI can reveal cancers in addition to those detected on mammography alone with a low false-positive rate; these results suggest that DWI may have potential as a rapid supplemental screening tool.

Diagnostic Performance of Fused Diffusion-Weighted Imaging Using Unenhanced or Postcontrast T1-Weighted MR Imaging in Patients With Breast Cancer

To evaluate the diagnostic performance of fused diffusion-weighted imaging (DWI) using either unenhanced (UFMR) or early postcontrast T1-weighted imaging (PCFMR) to detect and characterize breast lesions in patients with breast cancer.This retrospective observational study was approved by institutional review board in our hospital and informed consents were waived. We retrospectively selected 87 consecutive patients who underwent preoperative breast magnetic resonance imaging, including DWI and definitive surgery. Both UFMR and PCFMR were reviewed by 5 radiologists for detection, lesion size, Breast Imaging Reporting and Data System final assessment, the probability of malignancy, lesion conspicuity, and apparent diffusion coefficients.A total of 129 lesions were identified by at least 2 readers on UFMR or PCFMR. Of 645 potentially detected lesions, there were 528 (82%) with UFMR and 554 (86%) with PCFMR. Malignant lesions or index cancers showed significantly higher detection rates than benign or additional lesions on both UFMR and PCFMR (P < 0.05). Area under the characteristic curves (AUCs) for predicting malignancy ranged 0.927 to 0.986 for UFMR, and 0.936 to 0.993 for PCFMR, which was not significantly different. Lesion conspicuity was significantly higher on PCFMR than UFMR (8.59 ± 1.67 vs 9.19 ± 1.36, respectively; P < 0.05) across 5 readers. Mean intraclass correlation coefficients for lesion size on UFMR and PCFMR were 0.89 and 0.92, respectively.Detection rates of index malignant lesions were similar for UFMR and PCFMR. Interobserver agreement for final assessments was reliable across 5 readers. Diagnostic accuracy for predicting malignancy with UFMR versus PCFMR was similar, although lesion conspicuity was significantly greater with the latter.

Correlation of the SUVmax of FDG-PET and ADC values of diffusion-weighted MR imaging with pathologic prognostic factors in breast carcinoma

PURPOSE

To correlate both primary lesion maximum standardized uptake values (SUVmax) of FDG-PET/CT, and apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI) with clinicopathologic prognostic factors in patients with breast carcinoma.

MATERIALS AND METHODS

214 patients with 216 mass-type invasive breast carcinomas underwent whole-body FDG-PET/CT and 3-Tesla breast MRI including DWI before initial therapy. The primary tumor's SUVmax and ADC values were measured using FDG-PET/CT and DWI, respectively. Histologic analysis parameters included tumor size, expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67, nuclear grade, histology subtype, and axillary lymph node (LN) metastasis. The relationships among SUVmax, ADC values, and pathologic prognostic factors were evaluated.

RESULTS

The mean SUVmax and ADCmean were 5.63±3.79 (range, 1.2-24.17) and 894±204×10(-6)mm(2)/s (range, 452-1550×10(-6)), respectively. There was a significant but weak inverse correlation between the SUVmax and ADCmean values (correlation coefficient r=-0.30, p<0.0001). SUVmax was associated with numerous prognostic factors such as tumor size (p<0.0001), expression levels of ER (p=0.00041), PR (p=0.00028), HER2 (p=0.00021), and Ki-67 (p<0.0001), nuclear grade (p<0.0001), histology subtype (p=0.00061), axillary LN metastasis (p<0.0001), and TNM staging (p<0.0001). Meanwhile, ADCmean value was associated with tumor size (p=0.013), expression of Ki-67 (p=0.0010), histology subtype (p=0.00013), axillary LN metastasis (p=0.00059), and TNM staging (p=0.0011).

CONCLUSIONS

Primary tumor SUVmax on FDG-PET/CT has a stronger relationship with known prognostic parameters and may be a more useful for predicting the prognosis of breast carcinoma than ADC values.

Apparent diffusion coefficient in differentiation between malignant and benign breast masses: does size matter?

AIM

To determine whether lesion size affects the diagnostic performance of apparent diffusion coefficient (ADC) in the evaluation of breast masses.

MATERIALS AND METHODS

Consecutive breast lesions detected at magnetic resonance imaging (MRI) from June 2010 to July 2013 were retrospectively reviewed. Differences in the ADCs of benign and malignant mass lesions were compared. Receiver operating characteristics analysis was performed to evaluate diagnostic performance of ADC regarding lesion size (≤ 1 cm or >1 cm) and their T2W signal intensities.

RESULTS

Seventy-four malignant lesions (77.9%) and 21 (22.1%) benign lesions were included. Twenty-two of the 95 (23.2%) masses measured ≤ 1 cm (mean 0.73 ± 0.4; range 0.51-0.8 cm) and 73/95 (76.9%) masses measured >1 cm (mean 2.11 ± 0.1; range 1.1-3.3 cm). The mean ADC was significantly lower for malignant than for benign lesions (mean for malignant lesion, 0.89 ± 0.29 × 10(-3) mm(2)/s; mean for benign lesions, 1.27 ± 0.42 × 10(-3) mm(2)/s; p<0.01). The optimal ADC cut-off for differentiating benign and malignant lesion was 1.088 × 10(-3) mm(2)/s with a sensitivity of 85.9% and specificity of 77% for lesions >1 cm. The sensitivity and specificity were lowered to 60% and 50%, respectively, for lesions of size ≤ 1. Maximal sensitivity and specificity were reached when the ADC value was used to evaluate T2-dark lesions.

CONCLUSION

Diffusion-weighted MRI is useful for characterizing masses that are hypointense on T2-weighted images. Lower sensitivity and specificity were found for breast lesions ≤ 1 cm.

Sonography of Invasive Apocrine Carcinoma of the Breast in Five Cases

OBJECTIVE

To evaluate the sonographic features of invasive apocrine carcinoma (IAC) of the breast.

MATERIALS AND METHODS

This study included five pathologically proven cases of IAC, and their sonographic features were retrospectively analyzed according to the Breast Imaging Reporting and Data System (BI-RADS) lexicon.

RESULTS

All five lesions involved the left breast and were seen as irregularly shaped masses. All lesions, except one, had a parallel orientation to the chest wall. All five lesions showed noncircumscribed margins and heterogeneous echotexture; however, they showed various posterior features. One lesion had edema as an associated feature. Sonographic assessments were classified as BI-RADS category 4 in all five cases.

CONCLUSION

Invasive apocrine carcinoma sonographic findings are difficult to differentiate from those of invasive ductal carcinoma of no special type.

Breast magnetic resonance imaging performance: safety, techniques, and updates on diffusion-weighted imaging and magnetic resonance spectroscopy

Dynamic contrast-enhanced breast magnetic resonance imaging (MRI) is a well-established, highly sensitive technique for the detection and evaluation of breast cancer. Optimal performance of breast MRI continues to evolve. This article addresses breast MRI applications, covers emerging breast MRI safety concerns; outlines the technical aspects of breast MRI, including equipment and protocols at 3 T and 1.5 T; and describes current promising areas of research including diffusion-weighted imaging and magnetic resonance spectroscopy.

Diffusion weighted imaging and apparent diffusion coefficient in 3 tesla magnetic resonance imaging of breast lesions

OBJECTIVE

To evaluate the utility of diffusion-weighted-imaging (DWI) and apparent-diffusion-coefficient (ADC) in a 3T magnetic-resonance-imaging (MRI) study of breast cancer. In particular, the study aims to classify ADC-values according to histology either for benign or malignant lesions.

METHODS

110 Breast MRI with MRI-DWI sequences and quantitative evaluation of the ADC were retrospectively reviewed. Results obtained with MRI-DWI and with biopsy were analyzed and ADC values were compared to histological results.

RESULTS

MRI showed a 95.5% sensitivity and a 83.7% specificity. The mean ADC values of benign and malignant lesions were 2.06 ± 0.19 and 1.03 ± 0.07 mm(2)/s, respectively (p < .05).

CONCLUSIONS

DWI and ADC-values could help distinguishing malignant and benign breast masses.

Fat suppression techniques (STIR vs. SPAIR) on diffusion-weighted imaging of breast lesions at 3.0 T: preliminary experience

PURPOSE

The aim of this work was to perform a qualitative and quantitative comparison of the performance of two fat suppression techniques on breast diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

Fifty-one women underwent clinical breast magnetic resonance imaging, including DWI with short TI inversion recovery (STIR) and spectral attenuated inversion recovery (SPAIR). Four were excluded from the analysis due to image artefacts. Rating of fat suppression uniformity and lesion visibility were performed. Agreement between the two sequences was evaluated. Additionally, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values for normal gland, benign and malignant lesions were compared. Receiver operating characteristic analysis was also performed.

RESULTS

From the 52 lesions found, 47 were detected by both sequences. DWI-STIR evidenced more homogeneous fat suppression (p = 0.03). Although these lesions were seen with both techniques, DWI-SPAIR evidenced higher score for lesion visibility in nine of them. SNR and CNR were comparable, except for SNR in benign lesions (p < 0.01), which was higher for DWI-SPAIR. Mean ADC values for lesions were similar. ADC for normal fibroglandular tissue was higher when using DWI-STIR (p = 0.006). Sensitivity, specificity, accuracy and area under the curve values were alike: 84.0 % for both; 77.3, 71.4 %; 80.9, 78.3 %; 82.5, 81.3 % for DWI-SPAIR and DWI-STIR, respectively.

CONCLUSION

DWI-STIR showed superior fat suppression homogeneity. No differences were found for SNR and CNR, except for SNR in benign lesions. ADCs for lesions were comparable. Findings in this study are consistent with previous studies at 1.5 T, meaning that both fat suppression techniques are appropriate for breast DWI at 3.0 T.

The diagnostic value of diffusion-weighted imaging and the apparent diffusion coefficient values in the differentiation of benign and malignant breast lesions

INTRODUCTION

The goal of our study was to evaluate the diagnostic efficacy of diffusion-weighted imaging (DWI) in the differentiation of benign and malignant breast lesions.

METHODS

Between June 2012 and March 2013, 60 patients with 63 lesions (age range 29-70 years, mean age 48.6 years) were included in our study. All lesions, except complicated cysts and intra-mammary lymph nodes, were confirmed histopathologically. The patients were evaluated with a 1.5 Tesla MR scanner using dedicated bilateral breast coil. DWI images were obtained by echo planar imaging sequence and 'b' values were selected as 200, 600 and 1000 s/mm(2). Apparent diffusion coefficient (ADC) values of both breast lesions and the normal fibroglandular tissue of the contralateral breast were calculated and statistically compared using Shapiro-Wilk test, Student's t-test, Mann-Whitney U test, chi-square test and the receiver operating curve.

RESULTS

Of 63 lesions, 22 were malignant and 41 were benign. In malignant lesions, the mean ADC values were 1.40 ± 0.41 × 10(-3) mm(2)/s for b = 200, 1.05 ± 0.28 × 10(-3) mm(2)/s for b = 600 and 0.91 ± 0.20 × 10(-3) mm(2)/s for b = 1000 and in benign lesions, the mean ADC values were 2.13 ± 0.85 × 10(-3) mm(2)/s for b = 200, 1.64 ± 0.47 × 10(-3) mm(2)/s for b = 600 and 1.40 ± 0.43 × 10(-3) mm(2)/s for b = 1000. The success of ADC values in differentiation of benign and malignant lesions was statistically significant (P = 0.0001). The threshold values were determined to be 1.50 × 10(-3) mm(2)/s for b = 200, 1.22 × 10(-3) mm(2)/s for b = 600 and 0.98 × 10(-3) mm(2)/s for b = 1000 (P < 0.05).

CONCLUSION

DWI can be an effective radiological method in the differentiation of benign and malignant breast lesions.

[Diffusion-weighted breast imaging. Clinical implementation procedure]

Diffusion-weighted imaging (DWI) of the breast provides additional contrast information in breast magnetic resonance imaging (MRI). The DWI procedure can easily be implemented in the routine breast MRI protocol with little time expenditure regarding image acquisition and evaluation. Evaluation of the DW images can be performed with or without the routine breast MRI sequences (T2w and T1w with contrast material) but evaluation in combination with the routine program is highly recommended. Objective analysis of the tissue diffusion can be achieved by calculating the apparent diffusion coefficient (ADC) value with the scanner software. The choice of the DW sequence, evaluation and determination of the ADC threshold to differentiate between benign and malignant lesions should be scanner adapted. The use of DW imaging qualifies for routine use regarding the differentiation between malignant and benign breast lesions. Non-mass-like lesions and monitoring neoadjuvant chemotherapy can also be evaluated with DW sequences. The benefit of the additional information from DW-MR mammography to characterize non-mass-like lesions and in the course of neoadjuvant chemotherapy remains unclear to date.

Investigation of the optimal b-value to detect breast tumors with diffusion weighted imaging by 1.5-T MRI

Background

Previous studies have reported that the signal attenuation of diffusion-weighted magnetic resonance imaging (DWI) for normal breast tissue and tumor were well fitted by a monoexponential and a biexponential function, respectively. The aim of this study was to investigate the optimal b-value to detect breast tumors from DWI signal attenuations.

Methods

Sixty-four subjects with breast cancer underwent DWI using six b-values up to 3500 s/mm². The signal attenuations of normal breast and tumor were fitted by mono- and biexponential functions, respectively. The maximum contrast b-values were estimated and compared in terms of frequency.

Results

In almost all cases, the contrast increased with a b-value from 0 to approximately 1500 s/mm². For b > 1500 s/mm², the contrast decreased. The highest contrast b-value in the range of 0 to 2500 s/mm² most frequently was b = 1500 and the next most frequent was 1400 s/mm². Comparing sensitivity and specificity between b = 700 and b = 1400 s/mm², b =1400 s/mm² was slightly superior.

Conclusion

Based on these results, DWI with a b-value of approximately 1400-1500 s/mm² is recommended for optimizing breast tumor detectability.