New parameters of ultrafast dynamic contrast-enhanced breast MRI using compressed sensing.

BACKGROUND: Ultrafast dynamic contrast-enhanced (UF-DCE) breast MRI is considered a promising method of accelerated breast MRI. However, the value of new kinetic parameters derived from UF-DCE need clinical evaluation. PURPOSE: To evaluate the diagnostic performance of the maximum slope (MS), time to enhancement (TTE), and time interval between arterial and venous visualization (AVI) derived from UF-DCE MRI using compressed sensing (CS). STUDY TYPE: Retrospective. POPULATION: Seventy-five patients with histologically proven breast lesions. The total number of analyzed lesions was 90 (61 malignant and 29 benign). FIELD STRENGTH/SEQUENCE: 3T MRI with UF-DCE MRI based on the 3D gradient-echo volumetric interpolated breath-hold examination (VIBE) sequence using incoherent k-space sampling combined with a CS reconstruction followed by conventional DCE MRI. ASSESSMENT: The diagnostic performance of the MS, TTE, AVI, and conventional kinetic analysis was analyzed and compared with histology. STATISTICAL TESTS: Wilcoxon rank sum test, receiver operating characteristic analysis. RESULTS: The MS was larger and the TTE and AVI were smaller for malignant lesions compared with benign lesions: MS: 29.3%/s and 18.4%/s (P < 0.001), TTE: 7.0 and 12.0 seconds (P < 0.001), AVI: 2.7 and 4.4 frames (P = 0.006) for malignant and benign lesions. The discriminating power of the MS (area under the curve [AUC], 0.76) was slightly better than that of conventional kinetic analysis (AUC, 0.69) and comparable to that of the TTE and AVI (AUC, 0.78 and 0.76 for TTE and AVI, respectively). Invasive lobular carcinoma had smaller MS (21.8%/s) among malignant lesions (29.3%/s). DATA CONCLUSION: The MS, TTE, and AVI can be used to evaluate breast lesions with clinical performance equivalent to that of conventional kinetic analysis. These parameters vary among histologies. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:164-174.

Real-time surveillance of left atrial appendage thrombus during contrast computed tomography imaging for catheter ablation: THe Reliability of cOMputed tomography Beyond UltraSound in THROMBUS detection (THROMBUS) study.

Left atrial contrast computed tomography (LA-CT) as well as transesophageal echocardiography (TEE) can exclude left atrial appendage (LAA) thrombus, but is sometimes unable to evaluate LAA due to incomplete LAA filling. The aim of the current study was to validate the utility of real-time approach of LA-CT with real-time surveillance of LAA-filling defect (FD). We enrolled consecutive 894 patients with LA-CT studies acquired for catheter ablation and compared the diagnostic accuracy in demonstrating LAA-FD between conventional protocol (N = 474) and novel protocol with real-time surveillance of LAA-FD immediately after the initial scanning and, when necessary, adding delayed scanning in the supine or prone position (N = 420). Primary endpoint was severity of LAA-FD classified into the 3 groups: "Grade-0" for complete filling of contrast, "Grade-1" for incomplete filling of contrast, and "Grade-2" for complete FD of contrast. The prevalence of Grade-1 and Grade-2 FD was 17.3% and 11.2% in conventional protocol, whereas there was no patient with Grade-2 FD, and only 1 patient with Grade-1 FD after the additional scanning in novel protocol. In 5 patients with suspected LAA thrombus both by TEE and Grade-2 FD in LA-CT by the conventional protocol, ablation procedure was canceled due to diagnosis of LAA thrombus. Conversely, 4 patients with suspected LAA thrombus by TEE in novel protocol group was proved to have intact LAA by LA-CT with and without additional scanning. This novel approach with real-time surveillance improved the diagnostic accuracy of LA-CT in detecting LAA-FD, suggesting potential superiority of LA-CT over TEE in excluding LAA thrombus.

Impact of physiological hormonal fluctuations on 18F-fluorodeoxyglucose uptake in breast cancer.

PURPOSE: Premenopausal physiologic steroid levels change cyclically, in contrast to steady state low levels seen in postmenopausal patients. The purpose of this study was to evaluate whether 18F-fluorodeoxyglucose (18F-FDG) uptake in breast cancer is influenced by physiological hormonal fluctuations. METHODS: A total of 160 primary invasive breast cancers from 155 females (54 premenopausal, 101 postmenopausal) who underwent 18F-FDG positron emission tomography/computed tomography before therapy were retrospectively analyzed. The maximal standardized uptake values (SUVmax) of tumors were compared with menstrual phases and menopausal status according to the following subgroups: 'luminal A-like,' 'luminal B-like,' and 'non-luminal.' Additionally, the effect of estradiol (E2) on 18F-FDG uptake in breast cancer cells was evaluated in vitro. RESULTS: Among premenopausal patients, SUVmax during the periovulatory-luteal phase was significantly higher than that during the follicular phase in luminal A-like tumors (n = 25, p = 0.004), while it did not differ between the follicular phase and the periovulatory-luteal phase in luminal B-like (n = 24) and non-luminal tumors (n = 7). Multiple regression analysis showed menstrual phase, tumor size, and Ki-67 index are independent predictors for SUVmax in premenopausal luminal A-like tumors. There were no significant differences in SUVmax between pre- and postmenopausal patients in any of the subgroups. In in vitro studies, uptake in estrogen receptor-positive cells was significantly augmented when E2 concentration was increased from 0.01 to ≥ 1 nM. CONCLUSIONS: Our data suggest that 18F-FDG uptake may be impacted by physiological hormonal fluctuations during menstrual cycle in luminal A-like cancers, and that E2 could be partly responsible for these events.

Intravoxel Incoherent Motion and Quantitative Non-Gaussian Diffusion MR Imaging: Evaluation of the Diagnostic and Prognostic Value of Several Markers of Malignant and Benign Breast Lesions.

Purpose To investigate the performance of integrated approaches that combined intravoxel incoherent motion (IVIM) and non-Gaussian diffusion parameters compared with the Breast Imaging and Reporting Data System (BI-RADS) to establish multiparameter thresholds scores or probabilities by using Bayesian analysis to distinguish malignant from benign breast lesions and their correlation with molecular prognostic factors. Materials and Methods Between May 2013 and March 2015, 411 patients were prospectively enrolled and 199 patients (allocated to training [n = 99] and validation [n = 100] sets) were included in this study. IVIM parameters (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion parameters (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) by using IVIM and kurtosis models were estimated from diffusion-weighted image series (16 b values up to 2500 sec/mm2), as well as a synthetic ADC (sADC) calculated by using b values of 200 and 1500 (sADC200-1500) and a standard ADC calculated by using b values of 0 and 800 sec/mm2 (ADC0-800). The performance of two diagnostic approaches (combined parameter thresholds and Bayesian analysis) combining IVIM and diffusion parameters was evaluated and compared with BI-RADS performance. The Mann-Whitney U test and a nonparametric multiple comparison test were used to compare their performance to determine benignity or malignancy and as molecular prognostic biomarkers and subtypes of breast cancer. Results Significant differences were found between malignant and benign breast lesions for IVIM and non-Gaussian diffusion parameters (ADC0, K, fIVIM, fIVIM · D*, sADC200-1500, and ADC0-800; P < .05). Sensitivity and specificity for the validation set by radiologists A and B were as follows: sensitivity, 94.7% and 89.5%, and specificity, 75.0% and 79.2% for sADC200-1500, respectively; sensitivity, 94.7% and 96.1%, and specificity, 75.0% and 66.7%, for the combined thresholds approach, respectively; sensitivity, 92.1% and 92.1%, and specificity, 83.3% and 66.7%, for Bayesian analysis, respectively; and sensitivity and specificity, 100% and 79.2%, for BI-RADS, respectively. The significant difference in values of sADC200-1500 in progesterone receptor status (P = .002) was noted. sADC200-1500 was significantly different between histologic subtypes (P = .006). Conclusion Approaches that combined various IVIM and non-Gaussian diffusion MR imaging parameters may provide BI-RADS-equivalent scores almost comparable to BI-RADS categories without the use of contrast agents. Non-Gaussian diffusion parameters also differed by biologic prognostic factors. © RSNA, 2017 Online supplemental material is available for this article.

Ultrafast dynamic contrast-enhanced mri of the breast using compressed sensing: breast cancer diagnosis based on separate visualization of breast arteries and veins.

PURPOSE: To evaluate the feasibility of ultrafast dynamic contrast-enhanced (UF-DCE) magnetic resonance imaging (MRI) with compressed sensing (CS) for the separate identification of breast arteries/veins and perform temporal evaluations of breast arteries and veins with a focus on the association with ipsilateral cancers. MATERIALS AND METHODS: Our Institutional Review Board approved this study with retrospective design. Twenty-five female patients who underwent UF-DCE MRI at 3T were included. UF-DCE MRI consisting of 20 continuous frames was acquired using a prototype 3D gradient-echo volumetric interpolated breath-hold sequence including a CS reconstruction: temporal resolution, 3.65 sec/frame; spatial resolution, 0.9 × 1.3 × 2.5 mm. Two readers analyzed 19 maximum intensity projection images reconstructed from subtracted images, separately identified breast arteries/veins and the earliest frame in which they were respectively visualized, and calculated the time interval between arterial and venous visualization (A-V interval) for each breast. RESULTS: In total, 49 breasts including 31 lesions (breast cancer, 16; benign lesion, 15) were identified. In 39 of the 49 breasts (breasts with cancers, 16; breasts with benign lesions, 10; breasts with no lesions, 13), both breast arteries and veins were separately identified. The A-V intervals for breasts with cancers were significantly shorter than those for breasts with benign lesions (P = 0.043) and no lesions (P = 0.007). CONCLUSION: UF-DCE MRI using CS enables the separate identification of breast arteries/veins. Temporal evaluations calculating the time interval between arterial and venous visualization might be helpful in the differentiation of ipsilateral breast cancers from benign lesions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:97-104.

The role of breast tomosynthesis in a predominantly dense breast population at a tertiary breast centre: breast density assessment and diagnostic performance in comparison with MRI.

OBJECTIVES: To compare breast density measured on digital breast tomosynthesis (DBT) (BI-RADS-based breast composition and fully-automatic estimation) and magnetic resonance imaging (MRI) (BI-RADS amount of fibroglandular tissue), and to evaluate the diagnostic performance in terms of sensitivity and specificity of DBT and MRI in a predominantly dense breast population. METHODS: Between 2015 and 2016, 152 women with 103 breast malignancies, who underwent 3-T breast MRI and DBT within 2 months' time, were enrolled in this study. Breast composition/fibroglandular tissue and findings on DBT (two readers) and MRI were reported using BI-RADS 5th edition. Digital mammography images were analysed for breast percent density (PD) using the Libra software tool. RESULTS: A majority of women had dense breasts as categorised by breast composition c (heterogeneously dense) (68%) and d (extremely dense) (15%). The mean PD was 44% (range, 18-89%) and the correlation between breast composition and PD was r = 0.6. The diagnostic performance of MRI was significantly higher compared to DBT for one reader as described by the area under the receiver operating characteristic (ROC) curve (p = 0.004) and of borderline significance for the other reader (p = 0.052). CONCLUSIONS: MRI had higher diagnostic performance than DBT in a dense breast population in the tertiary setting. KEY POINTS: • MRI had higher diagnostic performance than DBT in a dense breast population • Diagnostic performance of DBT was comparable to MRI in women with fatty breasts • MRI was superior to DBT in preoperative breast cancer size assessment.

Analysis of the microvascular morphology and hemodynamics of breast cancer in mice using SPring-8 synchrotron radiation microangiography.

Tumor vasculature is characterized by morphological and functional abnormalities. However, analysis of the dynamics in blood flow is still challenging because of limited spatial and temporal resolution. Synchrotron radiation (SR) microangiography above the K-edge of the iodine contrast agent can provide high-contrast imaging of microvessels in time orders of milliseconds. In this study, mice bearing the human breast cancer cell lines MDAMB231 and NOTCH4 overexpression in MDAMB231 (MDAMB231NOTCH4+) and normal mice were assessed using SR microangiography. NOTCH is transmembrane protein that has crucial roles for vasculogenesis, angiogenesis and tumorigenesis, and NOTCH4 is considered to be a cause of high-flow arteriovenous shunting. A subgroup of mice received intravenous eribulin treatment, which is known to improve intratumor core circulation (MDAMB231_eribulin). Microvessel branches from approximately 200 µm to less than 20 µm in diameter were observed within the same visual field. The mean transition time (MTT) was measured as a dynamic parameter and quantitative analysis was performed. MTT in MDAMB231 was longer than that in normal tissue, and MDAMB231NOTCH4+ showed shorter MTT [5.0 ± 1.4 s, 3.6 ± 1.0 s and 3.6 ± 1.1 s (mean ± standard deviation), respectively]. After treatment, average MTT was correlated to tumor volume (r = 0.999) in MDAMB231_eribulin, while in contrast there was no correlation in MDAMB231 (r = -0.026). These changes in MTT profile are considered to be driven by the modulation of intratumoral circulation dynamics. These results demonstrate that a SR microangiography approach enables quantitative analysis of morphological and dynamic characteristics of tumor vasculature in vivo. Further studies will reveal new findings concerning vessel function in tumors.

Apparent diffusion coefficient as a potential surrogate marker for Ki-67 index in mucinous breast carcinoma.

PURPOSE: To examine the association between apparent diffusion coefficient (ADC), cellularity, and Ki-67 index in mucinous breast carcinoma (MBC) compared with invasive carcinoma of no special type (NST). ADC's ability to identify lesions with highly proliferating MBC was also examined. MATERIALS AND METHODS: Pathologically confirmed MBCs (mucinous group, n = 18) and NSTs (control group, n = 18) were retrospectively analyzed. ADC was calculated from signal intensity of diffusion-weighted imaging at b values of 0 and 1000 sec/mm(2) . The Ki-67 index and cellularity were histopathologically evaluated. The mucinous group was classified into high Ki-67 mucinous group (Ki-67 index ≥14%, highly proliferating) and low Ki-67 mucinous group. RESULTS: In the mucinous group, minimum ADC (ADCmin) showed an inverse correlation with cellularity (r = -0.802, P < 0.0001) and Ki-67 index (r = -0.825, P < 0.0001). In the control group, ADCmin showed inverse correlation with cellularity (r = -0.537 P = 0.022), but no correlation with Ki-67 index (r = 0.035, P = 0.892). ADCmin of high Ki-67 mucinous group was significantly lower than that of low Ki-67 mucinous group (P = 0.005). CONCLUSION: This study demonstrates an inverse correlation between ADC and Ki-67 index in MBC and the ability of ADC to identify highly proliferating MBC. Considering that ADC can evaluate whole lesions noninvasively, ADC may be a promising noninvasive surrogate marker for Ki-67 index in the risk stratification of MBC.

Journal Club: Diagnostic value of (18)F-FDG PET/CT and MRI in predicting the clinicopathologic subtypes of invasive breast cancer.

OBJECTIVE: The purpose of this study was to assess the diagnostic value of (18)F-FDG PET/CT and MRI in predicting the clinicopathologic subtypes of breast cancer. MATERIALS AND METHODS: The cases of 89 patients with mass-type invasive breast cancer who underwent FDG PET/CT and MRI before therapy were retrospectively analyzed. Eight imaging variables-maximum standardized uptake value (SUVmax), apparent diffusion coefficient, size, shape, margin, intratumoral enhancement, dynamic kinetics, and high intratumoral signal intensity on T2-weighted images-were compared with results for the pathologic markers Ki-67 antibody, estrogen receptor (ER), progesterone receptor (PR), and ERBB2 (formerly HER2 or HER2/neu). The diagnostic performance of the imaging variables for sub-typing was evaluated, and the predictors of the subtypes were elucidated. RESULTS: Higher SUVmax was significantly associated with a high Ki-67 index (p < 0.0001), ER-negative status (p = 0.0001), and PR-negative status (p = 0.047). Significant correlation was also found between size and ER status (p = 0.002) and between shape and PR status (p = 0.044). The AUC exceeded 0.7 only in identification of the luminal A sub-type by application of cutoff values for SUVmax (AUC, 0.751). When smaller tumors were excluded, AUC increased (AUC, 0.803 for tumors > 16 mm). Multivariate analysis showed that SUVmax was the sole independent predictor of luminal A subtype (odds ratio per SD, 0.291; p < 0.0001). SUVmax was significantly lower for luminal A (4.4 ± 2.2) than non-luminal A (8.1 ± 4.4; p < 0.0001) tumors. A cutoff value of 5.4 yielded 79% sensitivity and 68% specificity for prediction that a tumor was the luminal A subtype. CONCLUSION: FDG PET/CT findings may contribute to differentiation of the luminal A and non-luminal A subtypes of invasive breast cancer.

Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features.

BACKGROUND: Texture features reflecting tumour heterogeneity enable us to investigate prognostic factors. The R package ComBat can harmonize the quantitative texture features among several positron emission tomography (PET) scanners. We aimed to identify prognostic factors among harmonized PET radiomic features and clinical information from pancreatic cancer patients who underwent curative surgery. METHODS: Fifty-eight patients underwent preoperative enhanced dynamic computed tomography (CT) scanning and fluorodeoxyglucose PET/CT using four PET scanners. Using LIFEx software, we measured PET radiomic parameters including texture features with higher order and harmonized these PET parameters. For progression-free survival (PFS) and overall survival (OS), we evaluated clinical information, including age, TNM stage, and neural invasion, and the harmonized PET radiomic features based on univariate Cox proportional hazard regression. Next, we analysed the prognostic indices by multivariate Cox proportional hazard regression (1) by using either significant (p < 0.05) or borderline significant (p = 0.05-0.10) indices in the univariate analysis (first multivariate analysis) or (2) by using the selected features with random forest algorithms (second multivariate analysis). Finally, we checked these multivariate results by log-rank test. RESULTS: Regarding the first multivariate analysis for PFS after univariate analysis, age was the significant prognostic factor (p = 0.020), and MTV and GLCM contrast were borderline significant (p = 0.051 and 0.075, respectively). Regarding the first multivariate analysis of OS, neural invasion, Shape sphericity and GLZLM LZLGE were significant (p = 0.019, 0.042 and 0.0076). In the second multivariate analysis, only MTV was significant (p = 0.046) for PFS, whereas GLZLM LZLGE was significant (p = 0.047), and Shape sphericity was borderline significant (p = 0.088) for OS. In the log-rank test, age, MTV and GLCM contrast were borderline significant for PFS (p = 0.08, 0.06 and 0.07, respectively), whereas neural invasion and Shape sphericity were significant (p = 0.03 and 0.04, respectively), and GLZLM LZLGE was borderline significant for OS (p = 0.08). CONCLUSIONS: Other than the clinical factors, MTV and GLCM contrast for PFS and Shape sphericity and GLZLM LZLGE for OS may be prognostic PET parameters. A prospective multicentre study with a larger sample size may be warranted.

Preoperative systemic therapy in locoregional management of early breast cancer: highlights from the Kyoto Breast Cancer Consensus Conference.

Data reviewed at the Kyoto Breast Cancer Consensus Conference (KBCCC) showed that preoperative systemic therapy (PST) could optimize surgery through the utilization of information relating to pre- and post-PST tumor stage, therapeutic sensitivity, and treatment-induced changes in the biological characteristics of the tumor. As such, it was noted that the biological characteristics of the tumor, such as hormone receptors, human epidermal growth factor receptor-2, histological grade, cell proliferative activity, mainly defined by the Ki67 labeling index, and the tumor's multi-gene signature, should be considered in the planning of both systemic and local therapy. Furthermore, the timing of axillary sentinel lymph node diagnosis (i.e., before or after the PST) was also noted to be critical in that it may influence the likelihood of axillary preservation, even in node positive cases. In addition, axillary diagnosis with ultrasound and concomitant fine needle aspiration cytology or core needle biopsy (CNB) was reported to contribute to the construction of a treatment algorithm for patient-specific or individualized axillary surgery. Following PST, planning for breast surgery should therefore be based on tumor subtype, tumor volume and extent, therapeutic response to PST, and patient preference. Nomograms for predicting nodal status and drug sensitivity were also recognized as a tool to support decision-making in the selection of surgical treatment. Overall, review of data at the KBCCC showed that PST increases the likelihood of patients receiving localized surgery and individualized treatment regimens.

Apparent diffusion coefficient as an MR imaging biomarker of low-risk ductal carcinoma in situ: a pilot study.

PURPOSE: To evaluate the potential of apparent diffusion coefficients (ADCs) obtained at quantitative diffusion-weighted magnetic resonance (MR) imaging of the breast as a biomarker of low-grade ductal carcinoma in situ (DCIS). MATERIALS AND METHODS: This retrospective study was approved by an institutional review board, and the requirement to obtain informed consent was waived. Twenty-two women (age range, 36-75 years; mean age, 56.4 years) with pure DCIS (seven with low-grade DCIS, five with intermediate-grade DCIS, and seven with high-grade DCIS) and three with microinvasion underwent breast MR imaging at 1.5 T between January 2008 and November 2010. MR examinations included contrast material-enhanced (gadoteridol) T1-weighted imaging and diffusion-weighted MR imaging with b values of 0 and 1000 sec/mm(2). ADC maps were generated. The distributions of the ADCs in regions of interest covering the lesions were compared among the three grades by using linear mixed-model analysis, and the discriminatory power of the lesion minimum ADC was determined with receiver operating characteristic analysis. RESULTS: The mean ADC was 1.42 × 10(-3) mm(2)/sec (95% confidence interval [CI]: 1.31 × 10(-3) mm(2)/sec, 1.54 × 10(-3) mm(2)/sec) for low-grade DCIS, 1.23 × 10(-3) mm(2)/sec (95% CI: 1.10 × 10(-3) mm(2)/sec, 1.36 × 10(-3) mm(2)/sec) for intermediate-grade DCIS, 1.19 × 10(-3) mm(2)/sec (95% CI: 1.08 × 10(-3) mm(2)/sec, 1.30 × 10(-3) mm(2)/sec) for high-grade DCIS, and 2.06 × 10(-3) mm(2)/sec (95% CI: 1.94 × 10(-3) mm(2)/sec, 2.18 × 10(-3) mm(2)/sec) for normal breast tissue. The mean ADCs for high- and intermediate-grade DCIS were significantly lower than that for low-grade DCIS (P < .01 and P = .03, respectively), and the mean ADC for low-grade DCIS was significantly lower than that for normal tissue (P < .001). The lesion minimum ADC for low-grade DCIS was also significantly higher than that for high- and intermediate-grade DCIS (P < .01). A threshold of 1.30 × 10(-3) mm(2)/sec for the minimum ADC in the diagnosis of low-grade DCIS had a specificity of 100% (12 of 12 patients; 95% CI: 73.5%, 100%) and a positive predictive value of 100% (four of four patients; 95% CI: 39.8%, 100%). CONCLUSION: These preliminary results suggest that quantitative diffusion-weighted MR imaging could be used to identify patients with low-grade DCIS with very high specificity. If the results of this study are confirmed, this approach could potentially spare those patients from invasive approaches such as mastectomy or axillary lymph node excision.

A multiparametric approach to diagnosing breast lesions using diffusion-weighted imaging and ultrafast dynamic contrast-enhanced MRI.

PURPOSE: To evaluate the diagnostic performance of a multiparametric approach to breast lesions including apparent diffusion coefficient (ADC) from diffusion-weighted images (DWI), maximum slope (MS) from ultrafast dynamic contrast enhanced (UF-DCE) MRI, lesion size, and patient's age. MATERIALS AND METHODS: In total, 96 lesions (73 malignant, 23 benign) were evaluated. UF-DCE MRI was acquired using a prototype 3D-gradient-echo volumetric interpolated breath-hold examination (VIBE) with compressed sensing. Images were obtained up to 1 min after gadolinium injection. MS was calculated as the percentage relative enhancement/s. An ADC map was automatically generated from DWI at b = 0 and b = 1000 s/mm2. MS and ADC values were measured by two radiologists independently. Interrater agreement was evaluated using intraclass correlation coefficients. Univariate and multivariate logistic regression analyses were performed using MS, ADC, lesion size, and the patient's age. The parameters of the prediction model were generated from the results of the multivariate logistic regression analysis. Area under the curve (AUC) was used to compare diagnostic performance of the prediction model and each parameter. RESULTS: Interrater agreements on MS and ADC were excellent (ICC 0.99 and 0.88, respectively). MS, ADC, and patient's age remained as significant parameters after univariate and multivariate logistic regression analysis. The prediction model using these significant parameters yielded an AUC of 0.90, significantly higher than that of MS (AUC 0.74, p = 0.01). The AUCs of ADC, MS, patient's age were 0.87, 0.74 and 0.73, respectively. CONCLUSIONS: A multiparametric model using ADC from DWI, MS from UF-DCE MRI, and patient's age showed excellent diagnostic performance, with greater contribution of ADC. Combining DWI and UF-DCE MRI might reduce scanning time while preserving diagnostic performance.

Diagnostic performance of maximum slope: A kinetic parameter obtained from ultrafast dynamic contrast-enhanced magnetic resonance imaging of the breast using k-space weighted image contrast (KWIC).

PURPOSE: To compare the diagnostic performance of the kinetic parameter maximum slope (MS) in breast lesions obtained by ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) of the contrast wash-in period with that of the washout index (WI) derived from standard DCE MRI and that of the Breast Imaging Reporting and Data System (BI-RADS) category. MATERIALS AND METHODS: In total, 138 contrast enhanced lesions (90 malignant, 48 benign) were evaluated. Ultrafast DCE MRI images were acquired using a k-space-weighted image contrast (KWIC), obtained 0-1 min after gadolinium injection (3.75 s/frame; 16 frames) and followed by standard DCE MRI (60 s/frame, 3 frames). MS was calculated for the KWIC time series as percentage relative enhancement per second (%/s). As a semi-quantitative parameter for the standard DCE MRI time series, WI was evaluated using the change in signal intensity between early and delayed phases. The diagnostic performance (malignant/benign differentiation) of MS, WI, and BI-RADS category was compared by ROC analysis using the area under the curve (AUC). RESULTS: The AUC of MS was as good as that of WI (0.81 vs. 0.79, respectively; P = 0.81), yet inferior to the BI-RADS category (0.81 vs. 0.96, respectively; <0.001). MS tended to have higher sensitivity (91.1% [82/90]) compared with WI (87.8% [79/90]) with same specificity (62.5% [30/48]). CONCLUSIONS: MS obtained by ultrafast DCE MRI of the breast is a promising kinetic parameter in the differential diagnosis of malignant and benign breast lesions with decreased scanning time.

Distribution pattern of FDG uptake using ring-type dedicated breast PET in comparison to whole-body PET/CT scanning in invasive breast cancer.

PURPOSE: This study aimed to investigate the incidence of rim uptake (RU) or multifocal uptake (MU) by invasive breast cancers on a ring-type dedicated breast positron emission tomography (dbPET) scanner compared with whole-body PET (wbPET) scanner imaging and to correlate uptake patterns with pathological features and prognosis. METHODS: Between 2009 and 2011, 76 lesions in 74 patients with primary invasive breast cancers were included. Each patient underwent dbPET and wbPET scanning on the same day after administration of 18F-fluorodeoxyglucose (FDG). The images were evaluated to identify specific uptake patterns (RU and MU). Their association with pathological characteristics and prognosis was analyzed. RESULTS: On dbPET, RU and MU patterns were observed in 18 lesions (24%) and 28 lesions (37%), respectively. On wbPET, RU and MU patterns were observed in six lesions (8%) and 17 lesions (22%), respectively. Lesions with RU on dbPET were of higher grade than lesions without RU (P = 0.024) and a higher Ki-67 index (mean; 31% vs. 18%, P = 0.015). They tended to be triple-negative (33% vs. 12%, P = 0.046) and less likely to be luminal A subtype (17% vs. 47%, P = 0.020). On wbPET, however, no significant differences in these markers were seen between RU and non-RU. The MU pattern did not correlate with pathological characteristics in either scanner. Lesions with RU or MU were not significantly associated with disease-free survival. CONCLUSIONS: DbPET can identify detailed FDG distribution patterns of breast cancer better than wbPET. Breast cancer with RU on dbPET was associated with higher grade and triple-negative subtype.

Impact of the Number of Iterations in Compressed Sensing Reconstruction on Ultrafast Dynamic Contrast-enhanced Breast MR Imaging.

PURPOSE: To assess the impact of the number of iterations of compressed sensing (CS) reconstruction on the kinetic parameters and image quality in dynamic contrast-enhanced (DCE)-MRI of the breast, with prospectively undersampled CS-accelerated scans. MATERIALS AND METHODS: Breast examinations including ultrafast DCE-MRI using CS were conducted for 21 patients. Images were reconstructed with different numbers of iterations. The peak enhancement ratio of the aorta and wash-in slope, initial area under the curve, and Ktrans of the breast lesions were measured. The root mean square error and structural similarity between the images using 50 iterations and images with a lower number of iterations were evaluated as criterion for quantitative image evaluation. RESULTS: Using an insufficient number of iterations, the contrast-enhanced effect was highly underestimated. In all semi-quantitative parameters, the number of iterations that stabilized the parameters in malignant lesions was higher than that in benign lesions. At least 15 iterations were needed for semi-quantitative parameters. For Ktrans, there were no significant differences between 10 and 50 iterations in both malignant and benign lesions. CONCLUSION: The kinetic parameters using ultrafast DCE-MRI with CS are affected by the number of iterations, especially in malignant lesions. However, if the images are reconstructed with an adequate number of iterations, ultrafast DCE-MRI with CS can be a powerful technique having high temporal and spatial resolution.

Left ventricular functional analysis using 64-slice multidetector row computed tomography: comparison with left ventriculography and cardiovascular magnetic resonance.

OBJECTIVE: The progress in computed tomography (CT) has improved temporal resolution and shortened the acquisition time. We compared cardiac function using 64-slice CT with left ventriculography (LVG) and cardiovascular magnetic resonance (CMR). METHODS: A head-to-head comparison between CT, LVG and CMR was performed in 41 patients. In global LV function, CMR served as the reference. Regional wall motion was compared in a 5-point scoring system. RESULTS: CT had excellent intra- and interobserver reproducibility. Ejection fraction, end-diastolic and end-systolic volumes by CT were closely correlated with CMR (r = 0.95, 0.96 and 0.98, respectively), while LVG underestimated LV volumes (p < 0.01). The standard deviation of ejection fraction difference between CT and CMR was significantly lower than that between LVG and CMR (p = 0.0015). In regional function, there were good agreements of 94.8% (kappa = 0.82) between CT and LVG and 94.5% (kappa = 0.84) between CT and CMR. The intermethod agreements in mild hypokinesis using CT tended to be lower. CONCLUSION: An excellent correlation was observed between CT and CMR in the LV function over a wide range of heart rates. However, even though 64-slice CT tended to be less sensitive in detecting mild hypokinesis, it still showed excellent concordance in advanced regional abnormalities.

[A case of primary breast cancer who responded remarkably to the neoadjuvant chemotherapy with the combination of docetaxel and cyclophosphamide].

A 67-year-old woman visited our hospital with suspicion of right breast cancer. She underwent core needle biopsy, and her disease was diagnosed as breast cancer (invasive ductal carcinoma, ER- and PgR- positive, HER2-negative). We chose neoadjuvant chemotherapy, because the tumor size was over 3 cm in diameter and she wished to conserve her breast. She was elderly, and so without anthracycline base, we used a combination of docetaxel (75 mg/m(2)) and cyclophosphamide (600 mg/m(2)) q3w 6 cycles followed by breast-conserving therapy. During treatment, the patient remained very well and showed no major side effects except grade 4 neutropenia on an outpatient basis. After 6 cycles, ultrasonography and mammography indicated the residual tumor, but breast MRI did not detect any tumor. Pathological examination showed absence of invasive tumor or only focal residual tumor cells (QpCR). We concluded that the combination of docetaxel and cyclophosphamide was a good option for neoadjuvant chemotherapy for early breast cancer.

Differentiating benign and malignant inflammatory breast lesions: Value of T2 weighted and diffusion weighted MR images.

OBJECTIVES: Benign and malignant inflammatory breast lesions demonstrate similar findings on both T2 weighted imaging (T2WI) and dynamic contrast enhanced (DCE) images. We hypothesized that benign inflammatory lesions might be differentiated form malignancies using a combination of apparent diffusion coefficient (ADC) values derived from diffusion weighted images (DWI) and T2WI. MATERIALS AND METHODS: We retrospectively reviewed 162 patients undergoing breast MRI (T2WI, DWI and DCE images) between 2008 and 2015 who had breast lesions with high T2WI signal intensity (High T2 SI) including 14 benign inflammatory lesions, 69 benign non-inflammatory lesions, 16 malignant inflammatory lesions and 63 malignant non-inflammatory lesions. On the High T2 SI and low T2WI signal intensity (Low T2 SI) areas in these breast lesions, we calculated ADC values from b values of 0 and 1000 s/mm2. RESULTS: The mean ADC values ±â€¯standard deviation (10-3 mm2/s) of the High T2 SI areas in benign inflammatory, benign non-inflammatory, malignant inflammatory and malignant non-inflammatory breast lesions were 0.75 ±â€¯0.18, 1.77 ±â€¯0.33, 2.06 ±â€¯0.32 and 1.88 ±â€¯0.41, respectively. Those of the Low T2 SI areas in benign inflammatory, benign non-inflammatory, malignant inflammatory and malignant non-inflammatory lesions were 0.89 ±â€¯0.15, 1.31 ±â€¯0.28, 0.87 ±â€¯0.20 and 0.94 ±â€¯0.27 respectively. ADC values of High T2 SI areas of the benign inflammatory lesions were significantly lower than those of benign non-inflammatory, malignant inflammatory, and malignant non-inflammatory lesions (p < 0.001). ADC values of Low T2 SI areas in benign inflammatory lesions were not significantly different from those of malignant inflammatory (p = 0.99) or malignant non-inflammatory lesions (p = 0.72). CONCLUSION: For breast lesions with High T2 SI, segmenting the High T2 SI for ADC mapping distinguishes benign from malignant inflammatory conditions. Using ADC mapping of the Low T2 SI areas will not result in this distinction.

The Value of Lesion Size as an Adjunct to the BI-RADS-MRI 2013 Descriptors in the Diagnosis of Solitary Breast Masses.

PURPOSE: This study aimed to evaluate the MRI findings of breast solitary masses in diagnostic procedures to decide the appropriate category based on American College of Radiology (ACR) BI-RADS-MRI 2013, with the focus on lesion size. METHODS: A retrospective review of 2,603 consecutive breast MRI reports identified 250 pathologically-proven solitary breast masses. Dynamic-contrast enhanced images and diffusion-weighted images were performed on a 3.0/1.5 Tesla Scanner with a 16/4 channel dedicated breast coil. MRI findings were re-evaluated according to ACR BI-RADS-MRI 2013. BI-RADS-MRI descriptors, lesion size and minimum apparent diffusion coefficient (ADC) value were statistically analyzed using univariate/multivariate logistic regression analysis and receiver operator characteristic (ROC) analysis. Based on the results, a diagnostic decision tree was constructed. RESULTS: Of the 250 lesions, 152 (61%) were malignant and 98 (39%) were benign. In univariate logistic regression analysis, most of the BI-RADS descriptors, lesion size, and ADC value were significant. Lesion size and ADC value were binarized with optimal cut-off values of 12 mm and 1.1 × 10-3 mm2/s, respectively. Multivariate logistic regression analysis showed that lesion size (≥12 mm or not), margin (circumscribed or not), kinetics (washout or not) and internal enhancement characteristics (IEC) (rim enhancement present or absent) significantly contributed to the diagnosis (P < 0.05). Using these four significant parameters, a decision tree was constructed to categorize lesions into detailed assessment categories/subcategories (Category 4A, 4B, 4C and 5). CONCLUSION: Lesion size is an independent contributor in diagnosing solitary breast masses. Adding the information of lesion size to BI-RADS-MRI 2013 descriptors will allow more detailed categorizations.