Quantitative characterization of breast lesions and normal fibroglandular tissue using compartmentalized diffusion-weighted model: comparison of intravoxel incoherent motion and restriction spectrum imaging.

BACKGROUND: To compare the compartmentalized diffusion-weighted models, intravoxel incoherent motion (IVIM) and restriction spectrum imaging (RSI), in characterizing breast lesions and normal fibroglandular tissue. METHODS: This prospective study enrolled 152 patients with 157 histopathologically verified breast lesions (41 benign and 116 malignant). All patients underwent a full-protocol preoperative breast MRI, including a multi-b-value DWI sequence. The diffusion parameters derived from the mono-exponential model (ADC), IVIM model (Dt, Dp, f), and RSI model (C1, C2, C3, C1C2, F1, F2, F3, F1F2) were quantitatively measured and then compared among malignant lesions, benign lesions and normal fibroglandular tissues using Kruskal-Wallis test. The Mann-Whitney U-test was used for the pairwise comparisons. Diagnostic models were built by logistic regression analysis. The ROC analysis was performed using five-fold cross-validation and the mean AUC values were calculated and compared to evaluate the discriminative ability of each parameter or model. RESULTS: Almost all quantitative diffusion parameters showed significant differences in distinguishing malignant breast lesions from both benign lesions (other than C2) and normal fibroglandular tissue (all parameters) (all P < 0.0167). In terms of the comparisons of benign lesions and normal fibroglandular tissues, the parameters derived from IVIM (Dp, f) and RSI (C1, C2, C1C2, F1, F2, F3) showed significant differences (all P < 0.005). When using individual parameters, RSI-derived parameters-F1, C1C2, and C2 values yielded the highest AUCs for the comparisons of malignant vs. benign, malignant vs. normal tissue and benign vs. normal tissue (AUCs = 0.871, 0.982, and 0.863, respectively). Furthermore, the combined diagnostic model (IVIM + RSI) exhibited the highest diagnostic efficacy for the pairwise discriminations (AUCs = 0.893, 0.991, and 0.928, respectively). CONCLUSIONS: Quantitative parameters derived from the three-compartment RSI model have great promise as imaging indicators for the differential diagnosis of breast lesions compared with the bi-exponential IVIM model. Additionally, the combined model of IVIM and RSI achieves superior diagnostic performance in characterizing breast lesions.

Assessment of Prognostic Factors and Molecular Subtypes of Breast Cancer With a Continuous-Time Random-Walk MR Diffusion Model: Using Whole Tumor Histogram Analysis.

BACKGROUND: The continuous-time random-walk (CTRW) diffusion model to evaluate breast cancer prognosis is rarely reported. PURPOSE: To investigate the correlations between apparent diffusion coefficient (ADC) and CTRW-specific parameters with prognostic factors and molecular subtypes of breast cancer. STUDY TYPE: Retrospective. POPULATION: One hundred fifty-seven women (median age, 50 years; range, 26-81 years) with histopathology-confirmed breast cancer. FIELD STRENGTH/SEQUENCE: Simultaneous multi-slice readout-segmented echo-planar imaging at 3.0T. ASSESSMENT: The histogram metrics of ADC, anomalous diffusion coefficient (D), temporal diffusion heterogeneity (α), and spatial diffusion heterogeneity (ß) were calculated for whole-tumor volume. Associations between histogram metrics and prognostic factors (estrogen receptor [ER], progesterone receptor [PR], human epidermal growth factor receptor 2 [HER2], and Ki-67 proliferation index), axillary lymph node metastasis (ALNM), and tumor grade were assessed. The performance of histogram metrics, both alone and in combination, for differentiating molecular subtypes (HER2-positive, Luminal or triple negative) was also assessed. STATISTICAL TESTS: Comparisons were made using Mann-Whitney test between different prognostic factor statuses and molecular subtypes. Receiver operating characteristic curve analysis was used to assess the performance of mean and median histogram metrics in differentiating the molecular subtypes. A P value <0.05 was considered statistically significant. RESULTS: The histogram metrics of ADC, D, and α differed significantly between ER-positive and ER-negative status, and between PR-positive and PR-negative status. The histogram metrics of ADC, D, α, and ß were also significantly different between the HER2-positive and HER2-negative subgroups, and between ALNM-positive and ALNM-negative subgroups. The histogram metrics of α and ß significantly differed between high and low Ki-67 proliferation subgroups, and between histological grade subgroups. The combination of αmean and ßmean achieved the highest performance (AUC = 0.702) to discriminate the Luminal and HER2-positive subtypes. DATA CONCLUSION: Whole-tumor histogram analysis of the CTRW model has potential to provide additional information on the prognosis and intrinsic subtyping classification of breast cancer. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Intraobserver and Interobserver Reproducibility of Breast Diffusion-Weighted Imaging Quantitative Parameters: Readout-Segmented vs. Single-Shot Echo-Planar Imaging.

BACKGROUND: The recommended technique for breast diffusion-weighted imaging (DWI) acquisitions is not sufficiently standardized in clinical practice. PURPOSE: To investigate the intraobserver and interobserver reproducibility of DWI measurements, diffusion-kurtosis imaging (DKI) parameters, and image quality evaluation in breast lesions between single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI). STUDY TYPE: Prospective. POPULATION: A total of 295 women with 209 malignant and 86 benign breast lesions. FIELD STRENGTH/SEQUENCE: A 3-T; fat-saturated T2-weighted MR imaging (T2WI); multi-b-value DWI with both ss-EPI and rs-EPI readouts; T1-weighted dynamic contrast-enhanced MRI (DCE-MRI). ASSESSMENT: Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were measured for each lesion on ss-EPI and rs-EPI, respectively. Image quality was visually evaluated regarding image sharpness, geometric distortion, lesion conspicuity, visualization of anatomic structures, and overall quality. Quantitative and qualitative analyses were performed twice with a time interval of 2 weeks. STATISTICAL TESTS: Intraobserver and interobserver reproducibility were evaluated using intra-class correlation coefficients (ICC), within-subject coefficient of variation (wCV), and Bland-Altman plots. RESULTS: MK, MD, and ADC quantitative parameters for breast lesions showed excellent intraobserver and interobserver reproducibility, with ICCs >0.75 and wCV values ranging from 2.51% to 7.08% for both sequences. The wCV values in both intraobserver and interobserver measurements were higher in the ss-EPI sequence (3.63%-7.08%) than that of the rs-EPI sequence (2.51%-3.62%). The wCV values differed in subgroups with different histopathological types of lesions, breast density, lesion morphology, and lesion sizes, respectively. Furthermore, rs-EPI (ICCs, 0.76-0.97; wCV values, 2.41%-6.04%) had better intraobserver and interobserver reproducibility than ss-EPI (ICCs, 0.54-0.90; wCV values, 6.18%-13.69%) with regard to image quality. DATA CONCLUSION: Compared to the ss-EPI, the rs-EPI sequence showed higher intraobserver and interobserver reproducibility for quantitative diffusion-related parameters and image quality assessments measured in breast DWI and DKI. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

Quantitative Assessment of Restriction Spectrum MR Imaging for the Diagnosis of Breast Cancer and Association With Prognostic Factors.

BACKGROUND: Restriction spectrum imaging (RSI) is an advanced quantitative diffusion-weighted magnetic resonance imaging (DWI) technique to assess breast cancer. PURPOSE: To investigate the ability of RSI to differentiate the benign and malignant breast lesions and the association with prognostic factors of breast cancer. STUDY TYPE: Retrospective. POPULATION: Seventy women (mean age, 49.6 ± 12.3 years) with 56 malignant and 19 benign breast lesions. FIELD STRENGTH/SEQUENCE: 3-T; RSI-based DWI sequence with echo-planar imaging technique. ASSESSMENT: The apparent diffusion coefficient (ADC) and RSI parameters (restricted diffusion f1 , hindered diffusion f2 , free diffusion f3 , and signal fractions f1 f2 ) were calculated by two readers for the whole lesion volume and compared between the benign and malignant groups and the subgroups with different statuses of prognostic factors in breast cancer. STATISTICAL TESTS: Mann-Whitney U test or Student's t-test was applied to compare the quantitative parameters between the different groups. Intraclass correlation coefficient (ICC) was used to assess readers' reproducibility. Binary logistic regression was used to combine parameters. Area under the curve (AUC) of receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of parameters to distinguish benign from malignant breast lesions. A P-value <0.05 was considered statistically significant. RESULTS: Malignant breast lesions showed significantly lower ADC and f3 values, and significantly higher f1 and f1 f2 values than the benign lesions, with AUC of 0.951, 0.877, 0.868, and 0.860, respectively. When RSI-derived parameters and ADC were combined, the diagnostic performance was superior to either single parameter (AUC = 0.973). The f3 value was significantly differed between estrogen receptor (ER)-positive and ER-negative tumors. The ADC, f1 , f3 , and f1 f2 values were significantly different progesterone receptor (PR)-positive and PR-negative status. DATA CONCLUSION: The RSI-derived parameters (f1 , f3 , and f1 f2 ) may facilitate the differential diagnosis between benign and malignant breast lesions. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Tanshinone IIA ameliorates experimental diabetic cardiomyopathy by inhibiting endoplasmic reticulum stress in cardiomyocytes via SIRT1.

Diabetic cardiomyopathy (DCM) is a common complication in patients with diabetes, and ultimately leads to heart failure. Endoplasmic reticulum stress (ERS) induced by abnormal glycolipid metabolism is a critical factor that affects the occurrence and development of DCM. Additionally, the upregulation/activation of silent information regulation 2 homolog-1 (SIRT1) has been shown to protect against DCM. Tanshinone II A (Tan IIA), the main active component of Salviae miltiorrhizae radix et rhizome (a valuable Chinese medicine), has protective effects against cardiovascular disease and diabetes. However, its role and mechanisms in diabetes-induced cardiac dysfunction remain unclear. Therefore, we explored whether Tan IIA alleviates ERS-mediated DCM via SIRT1 and elucidated the underlying mechanism. The results suggested that Tan IIA alleviated the pathological changes in the hearts of diabetic mice, ameliorated the cytopathological morphology of cardiomyocytes, reduced the cell death rate, and inhibited the expression of ERS-related proteins and mRNA. The SIRT1 agonist inhibited the activities of glucose-regulated protein 78 (GRP78). Furthermore, the opposite results under the SIRT1 inhibitor. SIRT1 knockdown was induced by siRNA-SIRT1 transfection, and the degree of GRP78 acetylation was increased. Cumulatively, Tan IIA ameliorated DCM by inhibiting ERS and upregulating SIRT1 expression.

Pre-operative MRI in evaluating pathologic complete response to neoadjuvant chemotherapy in patients with breast cancer: a study focused on influencing factors of baseline clinical-pathological and imaging features.

Purpose: To investigate what pre-treatment clinical-pathological features and MRI characteristics influence the performance of breast MRI in assessing the pathologic complete response (pCR) of breast cancer patients to Neoadjuvant Chemotherapy (NAC). Methods: A total of 225 patients with pathologically-confirmed breast cancer who underwent pre- and post-NAC breast MRI between January 2020 and April 2023 were retrospectively analyzed. All patients were categorized into radiologic complete response (rCR) and non-rCR groups based on pre-operative MRI. Univariable and multivariable logistic regression were used to identify independent clinicopathological and imaging features associated with imaging-pathological discordance. The performance of pre-operative MRI for predicting pCR to NAC was assessed according to the baseline characteristics of the clinicopathological data and pre-NAC MRI. In addition, the discrepancy between the pre-operative MRI and post-operative pathological findings was further analyzed by a case-control approach. Results: Among 225 patients, 99 (44.0%) achieved pCR after NAC. MRI showed the overall sensitivity of 97.6%, specificity of 58.6%, accuracy of 80.4%, a positive predictive value (PPV) of 75.0%, and a negative predictive value (NPV) of 95.1% in identifying pCR. Of baseline features, presence of ductal carcinoma in situ (DCIS) (OR, 3.975 [95% CI: 1.448-10.908], p = 0.007), luminal B (OR, 5.076 [95% CI: 1.401-18.391], p = 0.013), HER2-enriched subtype (OR, 10.949 [95% CI: 3.262-36.747], p < 0.001), multifocal or multicentric lesions (OR, 2.467 [95% CI: 1.067-5.706], p = 0.035), segmental or regional distribution of NME (OR, 8.514 [95% CI: 1.049-69.098], p = 0.045) and rim enhancement of mass (OR, 4.261 [95% CI: 1.347-13.477], p = 0.014) were significantly associated with the discrepancy between MRI and pathology. Conclusion: Presence of DCIS, luminal B or HER2-enriched subtype, multicentric or multifocal lesions, segmental or regional distribution of NME and rim enhancement of mass may lead to a decrease in diagnostic accuracy of MRI in patients of breast cancer treated with NAC.

Histogram analysis comparison of readout-segmented and single-shot echo-planar imaging for differentiating luminal from non-luminal breast cancer.

To compare diffusion-kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) parameters of single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI) in the differentiation of luminal vs. non-luminal breast cancer using histogram analysis. One hundred and sixty women with 111 luminal and 49 non-luminal breast lesions were enrolled in this study. All patients underwent ss-EPI and rs-EPI sequences on a 3.0T scanner. Histogram metrics were derived from mean kurtosis (MK), mean diffusion (MD) and the apparent diffusion coefficient (ADC) maps of two DWI sequences respectively. Student's t test or Mann-Whitney U test was performed for differentiating luminal subtype from non-luminal subtype. The ROC curves were plotted for evaluating the diagnostic performances of significant histogram metrics in differentiating luminal from non-luminal BC. The histogram metrics MKmean, MK50th, MK75th of luminal BC were significantly higher than those of non-luminal BC for both two DWI sequences (all P<0.05). Histogram metrics from rs-EPI sequence had better diagnostic performance in differentiating luminal from non-Luminal breast cancer compared to those from ss-EPI sequence. MK75th derived from rs-EPI sequence was the most valuable single metric (AUC, 0.891; sensitivity, 78.4%; specificity, 87.8%) for differentiating luminal from non-luminal BC among all the histogram metrics. Histogram metrics of MK derived from rs-EPI yielded better diagnostic performance for distinguishing luminal from non-luminal BC than that from ss-EPI. MK75th was the most valuable metric among all the histogram metrics.

Comparison of continuous-time random walk and fractional order calculus models in characterizing breast lesions using histogram analysis.

OBJECTIVE: To compare the diagnostic performance of different mathematical models for DWI and explore whether parameters reflecting spatial and temporal heterogeneity can demonstrate better diagnostic accuracy than the diffusion coefficient parameter in distinguishing benign and malignant breast lesions, using whole-tumor histogram analysis. METHODS: This retrospective study was approved by the institutional ethics committee and included 104 malignant and 42 benign cases. All patients underwent breast magnetic resonance imaging (MRI) with a 3.0 T MR scanner using the simultaneous multi-slice (SMS) readout-segment ed echo-planar imaging (rs-EPI). Histogram metrics of Mono- apparent diffusion coefficient (ADC), CTRW, and FROC-derived parameters were compared between benign and malignant breast lesions, and the diagnostic performance of each diffusion parameter was evaluated. Statistical analysis was performed using Mann-Whitney U test and receiver operating characteristic (ROC) curve. RESULTS: The DFROC-median exhibited the highest AUC for distinguishing benign and malignant breast lesions (AUC = 0.965). The temporal heterogeneity parameter αCTRW-median generated a statistically higher AUC compared to the spatial heterogeneity parameter ßCTRW-median (AUC = 0.850 and 0.741, respectively; p = 0.047). Finally, the combination of median values of CTRW parameters displayed a slightly higher AUC than that of FROC parameters, with no significant difference however (AUC = 0.971 and 0.965, respectively; p = 0.172). CONCLUSIONS: The diffusion coefficient parameter exhibited superior diagnostic performance in distinguishing breast lesions when compared to the temporal and spatial heterogeneity parameters.

Primary angiosarcoma of the breast: Two case reports and brief review of the literature.

Angiosarcoma is a rare but very aggressive tumor. It occurs in all organs of the body, and approximately 8% of all angiosarcomas arise in the breast. We reported 2 cases of primary breast angiosarcomas in young women. The 2 patients showed similar clinical features, but were quite different in dynamic contrast-enhanced MR imaging. The 2 patients were treated with mastectomy and axillary sentinel lymph node dissection and confirmed by post-operative pathological test. We suggested that dynamic contrast-enhanced MR imaging was the most helpful imaging tool in the diagnosis and pre-operative evaluation of the breast angiosarcoma.

1,8-Cineole ameliorates endothelial injury and hypertension induced by L-NAME through regulation of autophagy via PI3K/mTOR signaling pathway.

Our previous data confirmed that 1,8-Cineole had an antihypertensive effect in animal models. However, it is unclear whether antihypertension is dependent on the protective effect of 1,8-Cineole on endothelial function and structure. At present, the purpose was to investigate the protective effects of 1,8-Cineole on vascular endothelial tissue in hypertensive rats and human umbilical vein endothelial cells (HUVECs). Our results showed that 1,8-Cineole significantly reduced the blood pressure and improved the vascular endothelial lesion, attenuated vascular oxidative stress and inflammation induced by Nω-Nitro-L-arginine methyl ester hydrochloride (L-NAME) in rats. Pretreatment with 1,8-Cineole was able to inhibit the increase in malondialdehyde (MDA) and reactive oxygen species (ROS) induced by L-NAME, and increased the release and expression of superoxide dismutase (SOD) and nitric oxide (NO). In addition, 1,8-Cineole also reversed the increase of autophagy-associated protein LC3Ⅱ/LC3Ⅰ and the decrease of P62 in vivo and in vitro respectively. There was a synergistic effect between PI3K agonists and drugs, while PI3K inhibitors blocked the efficacy of 1,8-Cineole. The addition of autophagy inhibitor chloroquine increases the expression of eNOS. Taken together, our results indicate that 1,8-Cineole has potential beneficial promising antihypertension depending on the integrity of vascular endothelial structure and function induced by L-NAME, and the mechanism involves ameliorating autophagy by regulating of PI3K/mTOR.

Histogram analysis of multi-model high-resolution diffusion-weighted MRI in breast cancer: correlations with molecular prognostic factors and subtypes.

Objective: To investigate the correlations between quantitative diffusion parameters and prognostic factors and molecular subtypes of breast cancer, based on a single fast high-resolution diffusion-weighted imaging (DWI) sequence with mono-exponential (Mono), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) models. Materials and Methods: A total of 143 patients with histopathologically verified breast cancer were included in this retrospective study. The multi-model DWI-derived parameters were quantitatively measured, including Mono-ADC, IVIM-D, IVIM-D*, IVIM-f, DKI-Dapp, and DKI-Kapp. In addition, the morphologic characteristics of the lesions (shape, margin, and internal signal characteristics) were visually assessed on DWI images. Next, Kolmogorov-Smirnov test, Mann-Whitney U test, Spearman's rank correlation, logistic regression, receiver operating characteristic (ROC) curve, and Chi-squared test were utilized for statistical evaluations. Results: The histogram metrics of Mono-ADC, IVIM-D, DKI-Dapp, and DKI-Kapp were significantly different between estrogen receptor (ER)-positive vs. ER-negative groups, progesterone receptor (PR)-positive vs. PR-negative groups, Luminal vs. non-Luminal subtypes, and human epidermal receptor factor-2 (HER2)-positive vs. non-HER2-positive subtypes. The histogram metrics of Mono-ADC, DKI-Dapp, and DKI-Kapp were also significantly different between triple-negative (TN) vs. non-TN subtypes. The ROC analysis revealed that the area under the curve considerably improved when the three diffusion models were combined compared with every single model, except for distinguishing lymph node metastasis (LNM) status. For the morphologic characteristics of the tumor, the margin showed substantial differences between ER-positive and ER-negative groups. Conclusions: Quantitative multi-model analysis of DWI showed improved diagnostic performance for determining the prognostic factors and molecular subtypes of breast lesions. The morphologic characteristics obtained from high-resolution DWI can be identifying ER statuses of breast cancer.

Diagnostic value of multi-model high-resolution diffusion-weighted MR imaging in breast lesions: Based on simultaneous multi-slice readout-segmented echo-planar imaging.

PURPOSE: To investigate the diagnostic value of multi-model high-resolution diffusion-weighted MR imaging (DWI) in breast lesions, with a comparison of simultaneous multi-slice readout-segmented echo-planar imaging (SMS rs-EPI) and single-shot EPI (ss-EPI). MATERIALS AND METHODS: This retrospective study was approved by the institutional ethics committee and included 120 patients with 122 breast lesions (25 benign and 97 malignant). All patients underwent breast DWI with multi-b values (0, 50, 100, 200, 400, 800, 1200, and 2000 s/mm2) based on both SMS rs-EPI and ss-EPI on a 3.0 T MR scanner. Quantitative DWI-derived parameters including ADC, MK, MD, D, D*, and f were calculated based on mono-exponential (Mono), intravoxel incoherent motion (IVIM), diffusion kurtosis (DKI) models. Meanwhile, both DWI sequences were qualitatively evaluated with respect to overall image quality, lesion conspicuity, image artifact, geometric distortion, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and lesion contrast. The differences in DW-derived parameters, image quality, and diagnostic performance were statistically compared between SMS rs-EPI and ss-EPI groups. RESULTS: The SMS rs-EPI produced higher Contrast, CNR and lower SNR than ss-EPI (p < 0.01). The image quality of SMS rs-EPI was superior to ss-EPI either in subjective or objective evaluation. There was no significant difference between the SMS rs-EPI and ss-EPI for either MD or the D* (p > 0.05). However, the MK and f between the two sequences showed significant differences (p < 0.05). Spearman's correlation coefficient displayed good linear correlation for MK values (r = 0.73, 95% CI 0.617-0.857), MD values (r = 0.88, 95% CI 0.814-0.926), ADC values (r = 0.93, 95% CI 0.869-0.948) and D values (r = 0.93, 95% CI 0.856-0.948) between SMS rs-EPI and ss-EPI. Spearman's correlation coefficient for f values (r = 0.25, 95% CI 0.226-0.559) and D* values (r = 0.22, 95% CI 0.025-0.348) were fair and no correlation between the two sequences. MK values have the highest diagnostic value in differentiating benign and malignant breast lesions. CONCLUSIONS: High-resolution multi-model DWI based on SMS rs-EPI technique can provide superior image quality and lesion characterization, with comparable diagnostic performance as compared with ss-EPI DWI in differentiating benign and malignant breast lesions. Of different DWI-derived parameters, MK values showed the best diagnostic performance.

Comparison of multi-walled carbon nanotubes and halloysite nanotubes on lipid profiles in human umbilical vein endothelial cells.

Tubular nanomaterials (NMs), such as multi-walled carbon nanotubes (MWCNTs) and halloysite nanotubes (HNTs), may be used in biomedicine, but previous studies showed that MWCNTs induced toxicity to endothelial cells (ECs). However, the influence of tubular NMs on EC lipid profiles has gained little attention, probably because ECs are not traditionally considered to be involved in regulating lipid homeostasis. This study compared the different effects of MWCNTs and HNTs on lipid profile changes in human umbilical vein ECs (HUVECs). The results showed that MWCNTs but not HNTs of the same mass concentrations induced cytotoxicity, ultrastuctural changes and intracellular thiol depletion. Meanwhile, only MWCNTs promoted lipid accumulation due to the induction of ER stress leading to up-regulation of fatty acid synthase (FASN). Interestingly, lipidomics results showed that the main lipid classes induced by MWCNTs but not HNTs were ceramide (Cer) and phosphatidylinositol (PI), with most of the lipid classes unaltered or even decreased after NM exposure. Then, extra Cer and PI were added to explore the implications of increase of these lipids. Adding Cer promoted the cytotoxicity of MWCNTs to HUVECs, indicating the lipotoxic role of Cer. Whereas adding PI partially increased intracellular NO and decreased interleukin-6 (IL-6) release due to MWCNT exposure, indicating the signaling role of PI. These results indicated novel roles of lipid dysfunction in NM-induced toxicity to ECs, even though ECs are not the professional cells for controlling lipid homeostasis.