Investigation of imaging features in contrast-enhanced magnetic resonance imaging of benign and malignant breast lesions.

PURPOSE: This study aimed to enhance the diagnostic accuracy of contrast-enhanced breast magnetic resonance imaging (MRI) using gadobutrol for differentiating benign breast lesions from malignant ones. Moreover, this study sought to address the limitations of current imaging techniques and criteria based on the Breast Imaging Reporting and Data System (BI-RADS). MATERIALS AND METHODS: In a multicenter retrospective study conducted in Japan, 200 women were included, comprising 100 with benign lesions and 100 with malignant lesions, all classified under BI-RADS categories 3 and 4. The MRI protocol included 3D fast gradient echo T1- weighted images with fat suppression, with gadobutrol as the contrast agent. The analysis involved evaluating patient and lesion characteristics, including age, size, location, fibroglandular tissue, background parenchymal enhancement (BPE), signal intensity, and the findings of mass and non-mass enhancement. In this study, univariate and multivariate logistic regression analyses were performed, along with decision tree analysis, to identify significant predictors for the classification of lesions. RESULTS: Differences in lesion characteristics were identified, which may influence malignancy risk. The multivariate logistic regression model revealed age, lesion location, shape, and signal intensity as significant predictors of malignancy. Decision tree analysis identified additional diagnostic factors, including lesion margin and BPE level. The decision tree models demonstrated high diagnostic accuracy, with the logistic regression model showing an area under the curve of 0.925 for masses and 0.829 for non-mass enhancements. CONCLUSION: This study underscores the importance of integrating patient age, lesion location, and BPE level into the BI-RADS criteria to improve the differentiation between benign and malignant breast lesions. This approach could minimize unnecessary biopsies and enhance clinical decision-making in breast cancer diagnostics, highlighting the effectiveness of gadobutrol in breast MRI evaluations.

Characteristics of Suspicious Breast Lesions Visible Only on MR Imaging: Is It Possible to Classify into Immediate Biopsy and Careful Observation Groups?

PURPOSE: To investigate the characteristics of suspicious MRI-only visible lesions and to explore the validity of subcategorizing these lesions into the following two groups: lesions that would require immediate biopsy (4Bi) and lesions for which careful clinical follow-up could be recommended (4Fo). METHODS: A retrospective review of 108 MRI-only visible lesions in 106 patients who were diagnosed as Breast Imaging Reporting and Data System (BI-RADS) category 4 between June 2018 and June 2022 at our institution was performed by two radiologists. The breast MR images were evaluated according to BI-RADS and additional MRI descriptors (linear ductal, branching, and apparent diffusion coefficient values). The lesions were categorized by previously reported classification systems, and the positive predictive values (PPVs) for the different categories were determined and compared. Subsequently, a new classification system was developed in this study. RESULTS: The total malignancy rate was 31% (34/108). No significant differences between benign and malignant lesions were identified for focus and mass lesions. For non-mass lesions, linear ductal and heterogeneous internal enhancement suggested a benign lesion (P = 0.0013 and P = 0.023, respectively), and branching internal enhancement suggested malignancy (P = 0.0066). Segmental distribution suggested malignancy (P = 0.0097). However, the PPV of segmental distribution with heterogeneous enhancement was significantly lower than that of category 4 segmental lesions with other enhancement patterns (11% vs. 59%; P = 0.0198).As a new classification, the distribution of focal, linear, and segmental was given a score of 0, 1, or 2, and the internal enhancement of heterogeneous, linear-ductal, clumped, branching, and clustered-ring enhancement was given a score of 0, 1, 2, 3, and 4, respectively. When categorized using a scoring system, a statistically significant difference in PPV was observed between 4Fo (n = 27) and 4Bi (n = 33) (7% vs. 61%, P = 0.000029). CONCLUSION: The new classification system was found to be highly capable of subcategorizing BI-RADS category 4 MRI-only visible non-mass lesions into 4Fo and 4Bi.

Intra- and Interobserver Reliability of Shear Wave Elastography in Breast Cancer Diagnosis.

OBJECTIVES: Shear wave elastography (SWE) is increasingly used in breast cancer diagnostics. However, large, prospective, multicenter data evaluating the reliability of SWE is missing. We evaluated the intra- and interobserver reliability of SWE in patients with breast lesions categorized as BIRADS 3 or 4. METHODS: We used data of 1288 women at 12 institutions in 7 countries with breast lesions categorized as BIRADS 3 to 4 who underwent conventional B-mode ultrasound and SWE. 1243 (96.5%) women had three repetitive conventional B-mode ultrasounds as well as SWE measurements performed by a board-certified senior physician. 375 of 1288 (29.1%) women received an additional ultrasound examination with B-mode and SWE by a second physician. Intraclass correlation coefficients (ICC) were calculated to examine intra- and interobserver reliability. RESULTS: ICC for intraobserver reliability showed an excellent correlation with ICC >0.9, while interobserver reliability was moderate with ICC of 0.7. There were no clinically significant differences in intraobserver reliability when SWE was performed in lesions categorized as BI-RADS 3 or 4 as well as in histopathologically benign or malignant lesions. CONCLUSION: Reliability of additional SWE was evaluated on a study cohort consisting of 1288 breast lesions categorized as BI-RADS 3 and 4. SWE shows an excellent intraobserver reliability and a moderate interobserver reliability in the evaluation of solid breast masses.

Potential of Lesion-to-Fat Elasticity Ratio Measured by Shear Wave Elastography to Reduce Benign Biopsies in BI-RADS 4 Breast Lesions.

OBJECTIVES: We evaluated whether lesion-to-fat ratio measured by shear wave elastography in patients with Breast Imaging Reporting and Data System (BI-RADS) 3 or 4 lesions has the potential to further refine the assessment of B-mode ultrasound alone in breast cancer diagnostics. METHODS: This was a secondary analysis of an international diagnostic multicenter trial (NCT02638935). Data from 1288 women with breast lesions categorized as BI-RADS 3 and 4a-c by conventional B-mode ultrasound were analyzed, whereby the focus was placed on differentiating lesions categorized as BI-RADS 3 and BI-RADS 4a. All women underwent shear wave elastography and histopathologic evaluation functioning as reference standard. Reduction of benign biopsies as well as the number of missed malignancies after reclassification using lesion-to-fat ratio measured by shear wave elastography were evaluated. RESULTS: Breast cancer was diagnosed in 368 (28.6%) of 1288 lesions. The assessment with conventional B-mode ultrasound resulted in 53.8% (495 of 1288) pathologically benign lesions categorized as BI-RADS 4 and therefore false positives as well as in 1.39% (6 of 431) undetected malignancies categorized as BI-RADS 3. Additional lesion-to-fat ratio in BI-RADS 4a lesions with a cutoff value of 1.85 resulted in 30.11% biopsies of benign lesions which correspond to a reduction of 44.04% of false positives. CONCLUSIONS: Adding lesion-to-fat ratio measured by shear wave elastography to conventional B-mode ultrasound in BI-RADS 4a breast lesions could help reduce the number of benign biopsies by 44.04%. At the same time, however, 1.98% of malignancies were missed, which would still be in line with American College of Radiology BI-RADS 3 definition of <2% of undetected malignancies.

The Potential of Shear Wave Elastography to Reduce Unnecessary Biopsies in Breast Cancer Diagnosis: An International, Diagnostic, Multicenter Trial.

PURPOSE: In this prospective, multicenter trial we evaluated whether additional shear wave elastography (SWE) for patients with BI-RADS 3 or 4 lesions on breast ultrasound could further refine the assessment with B-mode breast ultrasound for breast cancer diagnosis. MATERIALS AND METHODS: We analyzed prospective, multicenter, international data from 1288 women with breast lesions rated by conventional 2 D B-mode ultrasound as BI-RADS 3 to 4c and undergoing 2D-SWE. After reclassification with SWE the proportion of undetected malignancies should be < 2 %. All patients underwent histopathologic evaluation (reference standard). RESULTS: Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6 %). The assessment with B-mode breast ultrasound resulted in 1.39 % (6 of 431) undetected malignancies (malignant lesions in BI-RADS 3) and 53.80 % (495 of 920) unnecessary biopsies (biopsies in benign lesions). Re-classifying BI-RADS 4a patients with a SWE cutoff of 2.55 m/s resulted in 1.98 % (11 of 556) undetected malignancies and a reduction of 24.24 % (375 vs. 495) of unnecessary biopsies. CONCLUSION: A SWE value below 2.55 m/s for BI-RADS 4a lesions could be used to downstage these lesions to follow-up, and therefore reduce the number of unnecessary biopsies by 24.24 %. However, this would come at the expense of some additionally missed cancers compared to B-mode breast ultrasound (rate of undetected malignancies 1.98 %, 11 of 556, versus 1.39 %, 6 of 431) which would, however, still be in line with the ACR BI-RADS 3 definition (< 2 % of undetected malignancies).

Intelligent multi-modal shear wave elastography to reduce unnecessary biopsies in breast cancer diagnosis (INSPiRED 002): a retrospective, international, multicentre analysis.

BACKGROUND: Breast ultrasound identifies additional carcinomas not detected in mammography but has a higher rate of false-positive findings. We evaluated whether use of intelligent multi-modal shear wave elastography (SWE) can reduce the number of unnecessary biopsies without impairing the breast cancer detection rate. METHODS: We trained, tested, and validated machine learning algorithms using SWE, clinical, and patient information to classify breast masses. We used data from 857 women who underwent B-mode breast ultrasound, SWE, and subsequent histopathologic evaluation at 12 study sites in seven countries from 2016 to 2019. Algorithms were trained and tested on data from 11 of the 12 sites and externally validated using the additional site's data. We compared findings to the histopathologic evaluation and compared the diagnostic performance between B-mode breast ultrasound, traditional SWE, and intelligent multi-modal SWE. RESULTS: In the external validation set (n = 285), intelligent multi-modal SWE showed a sensitivity of 100% (95% CI, 97.1-100%, 126 of 126), a specificity of 50.3% (95% CI, 42.3-58.3%, 80 of 159), and an area under the curve of 0.93 (95% CI, 0.90-0.96). Diagnostic performance was significantly higher compared to traditional SWE and B-mode breast ultrasound (P < 0.001). Unlike traditional SWE, positive-predictive values of intelligent multi-modal SWE were significantly higher compared to B-mode breast ultrasound. Unnecessary biopsies were reduced by 50.3% (79 versus 159, P < 0.001) without missing cancer compared to B-mode ultrasound. CONCLUSION: The majority of unnecessary breast biopsies might be safely avoided by using intelligent multi-modal SWE. These results may be helpful to reduce diagnostic burden for patients, providers, and healthcare systems.

The importance of multi-modal imaging and clinical information for humans and AI-based algorithms to classify breast masses (INSPiRED 003): an international, multicenter analysis.

OBJECTIVES: AI-based algorithms for medical image analysis showed comparable performance to human image readers. However, in practice, diagnoses are made using multiple imaging modalities alongside other data sources. We determined the importance of this multi-modal information and compared the diagnostic performance of routine breast cancer diagnosis to breast ultrasound interpretations by humans or AI-based algorithms. METHODS: Patients were recruited as part of a multicenter trial (NCT02638935). The trial enrolled 1288 women undergoing routine breast cancer diagnosis (multi-modal imaging, demographic, and clinical information). Three physicians specialized in ultrasound diagnosis performed a second read of all ultrasound images. We used data from 11 of 12 study sites to develop two machine learning (ML) algorithms using unimodal information (ultrasound features generated by the ultrasound experts) to classify breast masses which were validated on the remaining study site. The same ML algorithms were subsequently developed and validated on multi-modal information (clinical and demographic information plus ultrasound features). We assessed performance using area under the curve (AUC). RESULTS: Of 1288 breast masses, 368 (28.6%) were histopathologically malignant. In the external validation set (n = 373), the performance of the two unimodal ultrasound ML algorithms (AUC 0.83 and 0.82) was commensurate with performance of the human ultrasound experts (AUC 0.82 to 0.84; p for all comparisons > 0.05). The multi-modal ultrasound ML algorithms performed significantly better (AUC 0.90 and 0.89) but were statistically inferior to routine breast cancer diagnosis (AUC 0.95, p for all comparisons ≤ 0.05). CONCLUSIONS: The performance of humans and AI-based algorithms improves with multi-modal information. KEY POINTS: • The performance of humans and AI-based algorithms improves with multi-modal information. • Multimodal AI-based algorithms do not necessarily outperform expert humans. • Unimodal AI-based algorithms do not represent optimal performance to classify breast masses.

Combined Use of Texture Features and Morphological Classification Based on Dynamic Contrast-enhanced MR Imaging: Differentiating Benign and Malignant Breast Masses with High Negative Predictive Value.

PURPOSE: We evaluated the diagnostic performance of the texture features of dynamic contrast-enhanced (DCE) MRI for breast cancer diagnosis in which the discriminator was optimized, so that the specificity was maximized via the restriction of the negative predictive value (NPV) to greater than 98%. METHODS: Histologically proven benign and malignant mass lesions of DCE MRI were enrolled retrospectively. Training and testing sets consist of 166 masses (49 benign, 117 malignant) and 50 masses (15 benign, 35 malignant), respectively. Lesions were classified via MRI review by a radiologist into 4 shape types: smooth (S-type, 34 masses in training set and 8 masses in testing set), irregular without rim-enhancement (I-type, 60 in training and 14 in testing), irregular with rim-enhancement (R-type, 56 in training and 22 in testing), and spicula (16 in training and 6 in testing). Spicula were immediately classified as malignant. For the remaining masses, 298 texture features were calculated using a parametric map of DCE MRI in 3D mass regions. Masses were classified into malignant or benign using two thresholds on a feature pair. On the training set, several feature pairs and their thresholds were selected and optimized for each mass shape type to maximize specificity with the restriction of NPV > 98%. NPV and specificity were computed using the testing set by comparison with histopathologic results and averaged on the selected feature pairs. RESULTS: In the training set, 27, 12, and 15 texture feature pairs are selected for S-type, I-type, and R-type masses, respectively, and thresholds are determined. In the testing set, average NPV and specificity using the selected texture features were 99.0% and 45.2%, respectively, compared to the NPV (85.7%) and specificity (40.0%) in visually assessed MRI category-based diagnosis. CONCLUSION: We, therefore, suggest that the NPV of our texture-based features method described performs similarly to or greater than the NPV of the MRI category-based diagnosis.

The potential of combined shear wave and strain elastography to reduce unnecessary biopsies in breast cancer diagnostics - An international, multicentre trial.

BACKGROUND: Shear wave elastography (SWE) and strain elastography (SE) have shown promising potential in breast cancer diagnostics by evaluating the stiffness of a lesion. Combining these two techniques could further improve the diagnostic performance. We aimed to exploratorily define the cut-offs at which adding combined SWE and SE to B-mode breast ultrasound could help reclassify Breast Imaging Reporting and Data System (BI-RADS) 3-4 lesions to reduce the number of unnecessary breast biopsies. METHODS: We report the secondary results of a prospective, multicentre, international trial (NCT02638935). The trial enrolled 1288 women with BI-RADS 3 to 4c breast masses on conventional B-mode breast ultrasound. All patients underwent SWE and SE (index test) and histopathologic evaluation (reference standard). Reduction of unnecessary biopsies (biopsies in benign lesions) and missed malignancies after recategorising with SWE and SE were the outcome measures. RESULTS: On performing histopathologic evaluation, 368 of 1288 breast masses were malignant. Following the routine B-mode breast ultrasound assessment, 53.80% (495 of 920 patients) underwent an unnecessary biopsy. After recategorising BI-RADS 4a lesions (SWE cut-off ≥3.70 m/s, SE cut-off ≥1.0), 34.78% (320 of 920 patients) underwent an unnecessary biopsy corresponding to a 35.35% (320 versus 495) reduction of unnecessary biopsies. Malignancies in the new BI-RADS 3 cohort were missed in 1.96% (12 of 612 patients). CONCLUSION: Adding combined SWE and SE to routine B-mode breast ultrasound to recategorise BI-RADS 4a patients could help reduce the number of unnecessary biopsies in breast diagnostics by about 35% while keeping the rate of undetected malignancies below the 2% ACR BI-RADS 3 definition.

Effects of gadobutrol on background parenchymal enhancement and differential diagnosis between benign and malignant lesions in dynamic magnetic resonance imaging of the breast.

BACKGROUND: The high concentration of gadolinium in gadobutrol, which is widely used in Japan, helps visualize signal enhancement of neoplastic lesions, however, there was concern that high T1 relaxivity could decrease the contrast between the lesion and the background mammary gland. We evaluate the effect of gadobutrol on background parenchymal enhancement (BPE) and differential diagnosis between benign and malignant lesions in dynamic MRI of the breast. METHODS: Ninety-nine patients were enrolled prospectively. Measurements of the following signal intensities (SIs) were obtained: breast tissue on a pre-contrast image (SIpre) and an early-phase image (SIearly); and the SIs of breast cancer on a pre-contrast image (SIpre-cancer) and an early-phase image (SIearly-cancer). We calculated the BPE ratio, i.e., (SIearly - SIpre)/SIpre and the cancer/BPE ratio, i.e., (SIearly-cancer - SIpre-cancer)/(SIearly on the affected side - SIpre on the affected side). These quantitative assessments were compared with the data from the recently published multicenter study (reference study without use of gadobutrol). In addition, two radiologists reinterpreted each of the MR images, and a third radiologist set the ROIs in the lesions and performed kinetic analysis as a Reader 3. RESULTS: While there was no significant difference in the SI of breast cancer in the premenopausal patients between the two studies, that in postmenopausal patients was significantly higher in the present study than in the reference study (p = 0.002). Although there was no significant difference in the cancer/BPE ratio in the postmenopausal patients between the two studies, the cancer/BPE ratio in the premenopausal patients was significantly higher in the reference study than in the present study (p = 0.028). For differentiation between benign and malignant masses, the mass margin was found to be the most important term (p < 0.001). According to the data of Reader 3, visual washout was observed in all 18 patients in whom the interpretation was changed from "plateau" to "washout". CONCLUSIONS: Gadobutrol may decrease the contrast between breast cancer and background parenchyma in premenopausal patients, and it may have a characteristic that "washout" does not easily occur, leading to "plateau" in patients with breast cancer.

Current status of breast cancer screening in high-risk women in Japan.

Overseas, the importance for breast MRI screening for high-risk groups has been shown. However, the evidence among Japanese population was lacking. Therefore, we collaborated with the "Study on clinical and genetic characterization of hereditary breast and ovarian cancer and improvement in prognosis using genetic information in Japan" group, as part of the Comprehensive Research Project on the Promotion of Cancer Control, Health and Labour Sciences Research, and have been conducting the study entitled, "Study of the usefulness of MRI surveillance of BRCA1/2 mutation carriers" since 2014. In addition, we found that in the Japanese population also, the pathological and imaging characteristics differ between BRCA1 and BRCA2 mutation carriers, like in non-Japanese populations by the several reports. In high-risk females, risk categories such as BRCA1 or BRCA2 mutation carriers are very important. Furthermore, in the future, the optimal surveillance modalities and examination intervals would also vary according to the age, thinness of the breast (constitution), breast density (individual differences on mammography), etc.; this would be "personalized surveillance", and quality-assured MRI examination is of the essence. This review will present clinical trial data of prospective MRI surveillance in Japan, and summarize the current status of breast cancer screening in high-risk Japanese women.

Current status of MRI-guided vacuum-assisted breast biopsy in Japan.

In April 2018, the national health insurance coverage of MRI-guided vacuum-assisted breast biopsy (VAB) was instituted with the application of the Japan Breast Cancer Society. Although MRI-guided VAB has been considered as a special procedure for a long time, having an access to this procedure should be recommended for facilities performing breast MRI as in Western countries. From now on, relevant societies should make efforts in data collection and quality control of MRI-guided VAB in Japan. We must avoid the following. To delay the early diagnosis of breast cancer in the judgment of an inaccurate indication, perform unnecessary biopsy due to overestimation of diagnosis, and reduce the success rate of MRI-guided VAB with immature techniques. This review explains the current status of MRI-guided VAB in Japan and shares procedure and biopsy data as a future reference from an experienced facility.

Artificial intelligence for breast cancer detection in mammography: experience of use of the ScreenPoint Medical Transpara system in 310 Japanese women.

BACKGROUND: To compare the breast cancer detection performance in digital mammograms of a panel of three unaided human readers (HR) versus a stand-alone artificial intelligence (AI)-based Transpara system in a population of Japanese women. METHODS: The subjects were 310 Japanese female outpatients who underwent digital mammographic examinations between January 2018 and October 2018. A panel of three HR provided a Breast Imaging Reporting and Data System (BI-RADS) score, and Transpara system provided an interactive decision support score and an examination-based cancer likelihood score. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were compared under each of reading conditions. RESULTS: The AUC was higher for human readers than with stand-alone Transpara system (human readers 0.816; Transpara system 0.706; difference 0.11; P < 0.001). The sensitivity of the unaided HR for diagnosis was 89% and specificity was 86%. The sensitivity of stand-alone Transpara system for cutoff scores of 4 and 7 were 93% and 85%, and specificities were 45% and 67%, respectively. CONCLUSIONS: Although the diagnostic performance of Transpara system was statistically lower than that of HR, the recent advances in AI algorithms are expected to reduce the difference between computers and human experts in detecting breast cancer.

Correlation between 18F-FDG uptake on PET/MRI and the level of tumor-infiltrating lymphocytes (TILs) in triple-negative and HER2-positive breast cancer.

PURPOSE: The tumor microenvironment is related to the metabolism of cancer cells and local immune reactions. Previous studies have established TILs could be a significant prognostic factor, especially for triple-negative breast cancers (TNBC) and human epithelial growth factor receptor 2 (HER2)-positive breast cancers. We explore the association between metabolic information on PET/MRI with TILs in TNBC and HER2-positive breast cancer. METHOD: We retrospectively reviewed the cases of 55 women with triple-negative or HER2-positive invasive ductal carcinomas who had undergone 18F-FDG PET/MRI without neo-adjuvant treatment for pre-operative evaluation. FDG uptake was quantified as standardized uptake value (SUV) max. The existence of peritumoral edema on PET/MRI was also recorded. The TIL score of the breast cancers was defined histologically on the basis of the proportion of the area infiltrated by lymphocytes, and classified as low (<10 %), intermediate (10-50 %), and high (>50 %). The association between PET/MRI findings and TILs was assessed using Kruskal-Wallis test and Wilcoxon signed-rank test. RESULTS: There were 14 high TIL, 20 intermediate TIL and 21 low TIL lesions. Higher values of SUVmax were found in the high and intermediate TIL group as compared to the low TIL group (P = 0.013). On the other hand, the lesions with peritumoral edema in the low TIL group tended to show high SUVmax (P = 0.014). CONCLUSIONS: 18F-FDG uptake on PET/MRI correlated with TIL levels in patients with TNBC and HER2-positive breast cancer. This finding suggests that preoperative PET/MRI may be useful as a non-invasive tool for guiding the treatment plan.

The clinical impact of MRI screening for BRCA mutation carriers: the first report in Japan.

BACKGROUND: There is no consensus on the appropriate surveillance for high-risk women with breast cancer in Japan. We investigated their imaging features and pathological characteristics to build a proper surveillance system for asymptomatic high-risk individuals in the future. METHODS: We retrospectively reviewed 93 female (median age 43 years) BRCA1 and BRCA2 mutation carriers from our institutional clinical database from 2011 to 2017. The study population was composed of 112 breast cancers. Mammography and MRI were reviewed by examiners blinded to patients' clinical history. Final surgical or biopsy histopathology served as the reference standard in all the patients. RESULTS: Fifty-nine breast cancers met selection criteria; of these, 30 were BRCA1-associated tumors, and 29 were BRCA2-associated tumors. Invasive ductal carcinoma was the most prevalent type in both BRCA1 and BRCA2. There were statistically significant differences in phenotype, nuclear grade, and Ki-67 labeling index between BRCA1 and BRCA2 mutation carriers. Additionally, imaging findings on mammography and MRI were statistically different. Tumors in BRCA2 carriers demonstrated mammographic calcifications more frequently, while those in BRCA1 carriers demonstrated a mass or architectural distortion (P < 0.001). Enhancement pattern on MRI also significantly differed between the two subgroups (P = 0.006). The size of MRI-detected lesions was statistically smaller than the size of those detected by other modalities (P = 0.004). CONCLUSIONS: The imaging and histological characteristics of BRCA1/2 mutation carriers were consistent with other countries' studies. MRI-detected lesions were significantly smaller than lesions detected by non-MRI modality. All lesions in BRCA1 mutation carriers could be detected by MRI.

Effects of menstrual cycle on background parenchymal enhancement and detectability of breast cancer on dynamic contrast-enhanced breast MRI: A multicenter study of an Asian population.

PURPOSE: To evaluate the effect of the menstrual cycle on BPE and cancer detectability in an Asian population. MATERIAL AND METHODS: 266 premenopausal patients with regular menstrual cycles from 24 centers were included, and 176 of them were diagnosed by pathology as having breast cancer. Thirty-five patients were examined in the menstrual phase (days 1-4), 105 in the proliferative phase (days 5-14), and 126 in the secretory phase (days 15-30). Measurement of the following signal intensities (SIs) were obtained: breast tissue on the unaffected side on a pre-contrast image (SI1) and an early-phase image (SI2); the SIs of breast tissue on the affected side on a pre-contrast image (SI3) and an early-phase image (SI4); and the SIs of breast cancer on a pre-contrast image (SI5) and an early-phase image (SI6). We calculated the BPE ratio, i.e., (SI2- SI1)/SI1 and the cancer/background enhancement ratio (C/B) ratio, i.e., (SI6- SI5) / (SI4- SI3). The BPE was classified as minimal, mild, moderate, or marked, and the cancer detectability was classified as excellent, good, or poor independently by two radiologists. RESULTS: The average C/B ratio was 20.1, 15.7, and 9.1 at the menstrual, proliferative, and secretory phases (p < 0.001). BPE was determined as moderate or marked in 0% and 5.4% at the menstrual phase, 10.3% and 11.0% at the proliferative phase, and 17.5% and 21.7% at the secretory phase by the two observers, respectively (p = 0.01, p = 0.01). The detectability of breast cancer was classified as poor in 0% and 0%, 1.4% and 13.0%, and 8.0% and 22.1% at the menstrual, proliferative, and secretory phases by the two observers, respectively (p = 0.07, p = 0.02). CONCLUSION: The menstrual phase and the proliferative phase seem to be suitable for breast MRI of Asian women.

Does integrated shimming improve lesion detection in whole-body diffusion-weighted examinations of patients with breast cancer?

PURPOSE: To evaluate the feasibility of proposed integrated slice-by-slice shimming (iShim) for whole-body diffusion weighted imaging (WB-DWI) in comparison to conventional 3D shim in patients with breast cancer. MATERIALS AND METHODS: Retrospective analysis of 116 consecutive patients (116 lesions) who underwent whole-body PET/MR using iShim (iShim group) were performed and compared with historical control of 103 patients (105 lesions) using 3D Shim (3D Shim group). RESULTS: As compared with dynamic contrast-enhanced (DCE) breast MRI, the apparent diffusion coefficient (ADC) value could not be determined for 15 (14%) of the 105 lesions of the 3D shim group and for 10 (9%) of the 116 lesions on iShim group. The intergroup difference failed to reach statistical significance (P = 0.1843). On the other hand, there was a significant difference in the frequencies of PET-positive and DWI-negative lesions between the 3D shim and iShim group (8.6% vs. 1.7%, respectively, P = 0.01942). CONCLUSION: In regard to detectability of breast cancers by DWI, iShim may allow improved detectability as compared to conventional 3D shim.

Shear Wave Speed of the Lesion in Preoperative Breast Ultrasonography: Association with Disease-free Survival of Patients with Primary Operable Invasive Breast Cancer.

RATIONALE AND OBJECTIVES: We aimed to investigate the relationship between shear wave speed (SWS) of the lesion on preoperative breast ultrasonography (US) and disease-free survival of patients with primary operable invasive breast cancer. MATERIALS AND METHODS: This retrospective study was approved by our Institutional Review Board. The requirement for informed consent was waived. A total of 195 consecutive newly diagnosed invasive breast cancer patients (age 33-83 years; mean 54.0 years) with preoperative breast US with SWS measurement of the lesion were identified. They underwent surgery between May 2012 and May 2013. SWS was measured at the center and three marginal zones in the main tumors, and the maximum value was used for analyses. For 35 patients who underwent primary systemic therapy (PST), the maximum SWS before PST was used. Cox proportional hazards modeling was used to identify the relationship between clinical-pathologic factors and disease-free survival. RESULTS: Fourteen recurrences occurred at 6-47 months (mean 22.3 months) after surgery. On multivariate analysis, a positive history of PST (hazard ratio [HR] = 4.93; 95% confidence interval [CI]: 1.66, 14.70; P = .004), adjuvant chemotherapy (HR = 3.67; 95% CI: 1.11, 12.1; P = .033), and higher maximum SWS (HR = 1.55; 95% CI: 1.07, 2.23; P = .020) were associated with poorer disease-free survival. CONCLUSION: Higher maximum SWS on preoperative US, in addition to a positive history of PST and adjuvant chemotherapy, was significantly associated with poorer disease-free survival of patients with invasive breast cancer.

Simultaneous whole-body and breast 18F-FDG PET/MRI examinations in patients with breast cancer: a comparison of apparent diffusion coefficients and maximum standardized uptake values.

PURPOSE: To compare standardized uptake value (SUV) and apparent diffusion coefficient (ADC) values acquired using a PET/MRI scanner in breast cancer patients. MATERIALS AND METHODS: Whole-body PET/MRI and breast PET/MRI were performed in 108 consecutive patients. Ninety-four patients who had a total of 100 breast cancers were analyzed. SUVmax and ADCmean acquired using breast PET/MRI were compared with pathologic prognostic factors. RESULTS: All the lesions were visually detectable using PET and diffusion-weighted imaging (DWI) on breast PET/MRI; however, lesions were visually undetectable on whole-body DWI in 13 patients (13%) or on whole-body PET in 7 patients (7%). An analysis of ADCmean and SUVmax demonstrated a statistically significant correlation between whole-body imaging and breast imaging (rho = 0.613, p < 0.001 and rho = 0.928, p < 0.001, respectively). In a univariate analysis, SUVmax was significantly correlated with HER2 status (p < 0.001), Ki-67 (p = 0.014), tumor size (p = 0.0177), and nuclear grade (p = 0.0448). In multiple regression analysis, only tumor size (p = 0.00701) was shown to independently influence SUVmax. CONCLUSION: Prone breast imaging was more sensitive than whole-body PET/MRI for detection of breast cancers. Both SUVmax and ADCmean showed limited correlation with pathologic prognostic factors.