Radiomics in cone-beam breast CT for the prediction of axillary lymph node metastasis in breast cancer: a multi-center multi-device study.

OBJECTIVES: To develop a radiomics model in contrast-enhanced cone-beam breast CT (CE-CBBCT) for preoperative prediction of axillary lymph node (ALN) status and metastatic burden of breast cancer. METHODS: Two hundred and seventy-four patients who underwent CE-CBBCT examination with two scanners between 2012 and 2021 from two institutions were enrolled. The primary tumor was annotated in each patient image, from which 1781 radiomics features were extracted with PyRadiomics. After feature selection, support vector machine models were developed to predict ALN status and metastatic burden. To avoid overfitting on a specific patient subset, 100 randomly stratified splits were made to assign the patients to either training/fine-tuning or test set. Area under the receiver operating characteristic curve (AUC) of these radiomics models was compared to those obtained when training the models only with clinical features and combined clinical-radiomics descriptors. Ground truth was established by histopathology. RESULTS: One hundred and eighteen patients had ALN metastasis (N + (≥ 1)). Of these, 74 had low burden (N + (1~2)) and 44 high burden (N + (≥ 3)). The remaining 156 patients had none (N0). AUC values across the 100 test repeats in predicting ALN status (N0/N + (≥ 1)) were 0.75 ± 0.05 (0.67~0.93, radiomics model), 0.68 ± 0.07 (0.53~0.85, clinical model), and 0.74 ± 0.05 (0.67~0.88, combined model). For metastatic burden prediction (N + (1~2)/N + (≥ 3)), AUC values were 0.65 ± 0.10 (0.50~0.88, radiomics model), 0.55 ± 0.10 (0.40~0.80, clinical model), and 0.64 ± 0.09 (0.50~0.90, combined model), with all the ranges spanning 0.5. In both cases, the radiomics model was significantly better than the clinical model (both p < 0.01) and comparable with the combined model (p = 0.56 and 0.64). CONCLUSIONS: Radiomics features of primary tumors could have potential in predicting ALN metastasis in CE-CBBCT imaging. CLINICAL RELEVANCE STATEMENT: The findings support potential clinical use of radiomics for predicting axillary lymph node metastasis in breast cancer patients and addressing the limited axilla coverage of cone-beam breast CT. KEY POINTS: • Contrast-enhanced cone-beam breast CT-based radiomics could have potential to predict N0 vs. N + (≥ 1) and, to a limited extent, N + (1~2) vs. N + (≥ 3) from primary tumor, and this could help address the limited axilla coverage, pending future verifications on larger cohorts. • The average AUC of radiomics and combined models was significantly higher than that of clinical models but showed no significant difference between themselves. • Radiomics features descriptive of tumor texture were found informative on axillary lymph node status, highlighting a higher heterogeneity for tumor with positive axillary lymph node.

Radiomics nomogram for predicting axillary lymph node metastasis-a potential method to address the limitation of axilla coverage in cone-beam breast CT: a bi-center retrospective study.

PURPOSE: Cone-beam breast CT (CBBCT) has an inherent limitation that the axilla cannot be imaged in its entirety. We aimed to develop and validate a nomogram based on clinical factors and contrast-enhanced (CE) CBBCT radiomics features to predict axillary lymph node (ALN) metastasis and complement limited axilla coverage. MATERIAL AND METHODS: This retrospective study included 312 patients with breast cancer from two hospitals who underwent CE-CBBCT examination in a clinical trial (NCT01792999) during 2012-2020. Patients from TCIH comprised training set (n = 176) and validation set (n = 43), and patients from SYSUCC comprised external test set (n = 93). 3D ROIs were delineated manually and radiomics features were extracted by 3D Slicer software. RadScore was calculated and radiomics model was constructed after feature selection. Clinical model was built on independent predictors. Nomogram was developed with independent clinical predictors and RadScore. Diagnostic performance was compared among three models by ROC curve, and decision curve analysis (DCA) was used to evaluate the clinical utility of nomogram. RESULTS: A total of 139 patients were ALN positive and 173 patients were negative. Twelve radiomics features remained after feature selection. Location and focality were selected as independent predictors for ALN status. The AUC of nomogram in external test set was higher than that of clinical model (0.80 vs. 0.66, p = 0.012). DCA demonstrated that the nomogram had higher overall net benefit than that of clinical model. CONCLUSION: The nomogram combined CE-CBBCT-based radiomics features and clinical factors could have potential in distinguishing ALN positive from negative and addressing the limitation of axilla coverage in CBBCT.

[Latest Findings on the Mechanism of the Interaction Between Multiple Myeloma Cells and Bone Marrow Microenvironment].

Multiple myeloma (MM) is a hematologic malignancy of terminally differentiated plasma cells. The mechanisms of the pathogenesis and progression of MM include genetic abnormalities of the MM cells and the interaction between MM cells and bone marrow microenvironment (BMME). MM cells start malignant proliferation in BMME and contribute to the pathogenesis and progression of MM through direct or indirect interactions between cells and the extracellular matrix. Exploring the mechanism of interaction between MM cells and the microenvironment is crucial to improving our understanding of the pathogenesis and progression of MM and early diagnosis and treatment. In addition, the metabolic reprogramming of tumors is one of the key issues of oncology research. Herein, we summarized published findings on the the altered metabolic reprogramming of MM and the characteristics of MM metabolic-microbial interactions in order to gain an in-depth understanding of MM pathogenesis and progression and drug resistance mechanisms, and ultimately to explore for new strategies for MM treatment.

Cone-beam breast CT-guided surface location facilitates breast-conserving surgery in breast cancer patients with extensive calcifications: A pilot study.

Background: Extensive malignant-appearing calcifications have traditionally been considered a contraindication for breast-conserving surgery. The evaluation of calcifications largely depends on mammography, which is limited by tissue superimposition and is unable to reveal spatial information about extensive calcifications. Three-dimensional imaging modality is needed to reveal the architecture of extensive calcifications. In the present study, a novel cone-beam breast CT-guided surface location technique was investigated to facilitate breast-conserving surgery in breast cancer patients with extensive malignant breast calcifications. Methods: Biopsy-proved early breast cancer patients with extensive malignant-appearing breast calcifications were included. A patient will be considered suitable for breast-conserving surgery if the spatial segmental distribution of calcifications is found by 3D images of cone-beam breast CT. Then, the margins of the calcifications were located in contrast-enhanced cone-beam breast CT images. Next, skin markers were located using radiopaque materials, and cone-beam breast CT was reperformed to confirm the accuracy of surface location. During breast-conserving surgery, lumpectomy was performed according to the previous surface location, and an intraoperative specimen x-ray was applied to double-check that the entire lesion was removed. Margin assessment was made for both intraoperative frozen section and postoperative pathology examination. Results: From May 2019 to Jun 2022, 11 eligible breast cancer patients in our institution were included. Breast-conserving surgery was performed successfully in all patients using the surface location approach mentioned before. All patients achieved negative margins and satisfied cosmetic results. Conclusion: This study proved the feasibility of cone-beam breast CT-guided surface location for facilitating breast-conserving surgery in breast cancer patients with extensive malignant breast calcifications.

Effect of Emulsifiers on the Quality of Palm Oil Based Shortening during Variable Temperature Storage.

The quality and processing characters of shortening are strongly influenced by the temperature fluctuation during storage and handling. Some chemical components, especially the presence of emulsifiers in shortening formula might be attributed to the quality change of shortening in response to temperature fluctuation. In this work, the effect of emulsifiers on the mechanical properties, crystalline structure, and crystalline transformation of fat was investigated with a palm oil-based shortening under varied storage temperature (4°C, 12 h - 28°C, 12 h, cycle reciprocating). Results show that the shortening without emulsifiers deteriorated easily with a severe separation of liquid oil and reduction of hardness, which was owing to the aggregation of crystals, and the appearance to high proportion of ß crystals at the later stage in storage (day 7 and day 14). However, the addition of the emulsifiers such as sorbitan monopalmitate (SMP), Glyceryl monostearate (GMS), and Glycerol monopalmitate (GMP) ameliorated the production of ß crystals effectively. Among the tested emulsifiers, the shortening adding GMS showed the best quality, which remained stable in multiple cycles up to 14 times. The findings will guide the use of emulsifiers in palm fat processing.

Mechanisms for Bile Acids CDCA- and DCA-Stimulated Hepatic Spexin Expression.

Spexin (SPX) is a novel peptide involved in glucose and lipid metabolism and suppresses hepatic total bile acid levels by inhibiting hepatic cholesterol 7α-hydroxylase 1 expression. As important mediators for glycolysis/gluconeogenesis and lipid metabolism, the effects of bile acids on SPX expression is yet to be understood. By using SMMC7721 and BEL-7402 cell lines, we screened the effects of bile acids and found that chenodeoxycholic acid (CDCA) and deoxycholic acid (DCA) can stimulate SPX gene transcription. Both CDCA and DCA were able to stimulate SPX mRNA expression in the liver but not colon and ileum in mice. In SMMC7721 and BEL-7402 cells, CDCA- and DCA-induced SPX promoter activity was mimicked by bile acid receptor FXR and TGR5 activation and suppressed by FXR and TGR5 silencing. Adenylate cyclase (AC)/cyclic adenosine monophosphate (cAMP) activators significantly increased SPX promoter activity whereas the inhibitors for AC/CAMP/protein kinase A (PKA) and mitogen-activated protein kinases (MAPK) pathway attenuated CDCA- and DCA-induced SPX transcription. Thus, CDCA and DCA stimulate SPX expression at the hepatic level through FXR and TGR5 mediated AC/cAMP/PKA and MAPK cascades.

Assessment of Cone-Beam Breast Computed Tomography for Predicting Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer: A Prospective Study.

Background: Response surveillance of neoadjuvant chemotherapy is needed to facilitate treatment decisions. We aimed to assess the imaging features of cone-beam breast computed tomography (CBBCT) for predicting the pathologic response of breast cancer after neoadjuvant chemotherapy. Methods: This prospective study included 81 women with locally advanced breast cancer who underwent neoadjuvant chemotherapy from August 2017 to January 2021. All patients underwent CBBCT before treatment, and 55 and 65 patients underwent CT examinations during the midtreatment (3 cycles) and late-treatment phases (7 cycles), respectively. Clinical information and quantitative parameters such as the diameter, volume, surface area, and CT density were compared between pathologic responders and nonresponders using the T-test and the Mann-Whitney U test. The performance of meaningful parameters was evaluated with the receiver operating characteristic curve, sensitivity, and specificity. Results: The quantitative results for the segmented volume, segmented surface area, segmented volume reduction, maximum enhancement ratio, wash-in rate and two-minute enhancement value in the mid- and late-treatment periods had predictive value for pathologic complete response. The area under the curve for the prediction model after multivariate regression analysis was 0.874. Conclusion: After comparing the outcomes of each timepoint, mid- and late-treatment parameters can be used to predict pathologic outcome. The late-treatment parameters showed significant value with a predictive model.

Correlation between contrast-enhanced cone-beam breast computed tomography features and prognostic staging in breast cancer.

OBJECTIVE: To evaluate whether contrast-enhanced cone-beam breast CT (CE-CBBCT) features can risk-stratify prognostic stage in breast cancer. METHODS: Overall, 168 biopsy-proven breast cancer patients were analysed: 115 patients in the training set underwent scanning using v. 1.5 CE-CBBCT between August 2019 and December 2019, whereas 53 patients in the test set underwent scanning using v. 1.0 CE-CBBCT between May 2012 and August 2014. All patients were restaged according to the American Joint Committee on Cancer eighth edition prognostic staging system. Following the combination of CE-CBBCT imaging parameters and clinicopathological factors, predictors that were correlated with stratification of prognostic stage via logistic regression were analysed. Predictive performance was assessed according to the area under the receiver operating characteristic curve (AUC). Goodness-of-fit of the models was assessed using the Hosmer-Lemeshow test. RESULTS: As regards differentiation between prognostic stage (PS) I and II/III, increased tumour-to-breast volume ratio (TBR), rim enhancement pattern, and the presence of penetrating vessels were significant predictors for PS II/III disease (p < 0.05). The AUCs in the training and test sets were 0.967 [95% confidence interval (CI) 0.938-0.996; p < 0.001] and 0.896 (95% CI, 0.809-0.983; p = 0.001), respectively. Two features were selected in the training set of PS II vs III, including tumour volume [odds ratio (OR)=1.817, p = 0.019] and calcification (OR = 4.600, p = 0.040), achieving an AUC of 0.790 (95% CI, 0.636-0.944, p = 0.001). However, there was no significant difference in the test set of PS II vs III (P＞0.05). CONCLUSION: CE-CBBCT imaging biomarkers may provide a large amount of anatomical and radiobiological information for the pre-operative distinction of prognostic stage. ADVANCES IN KNOWLEDGE: CE-CBBCT features have distinctive promise for stratification of prognostic stage in breast cancer.

Distinguishing benign and malignant lesions on contrast-enhanced breast cone-beam CT with deep learning neural architecture search.

PURPOSE: To utilize a neural architecture search (NAS) approach to develop a convolutional neural network (CNN) method for distinguishing benign and malignant lesions on breast cone-beam CT (BCBCT). METHOD: 165 patients with 114 malignant and 86 benign lesions were collected by two institutions from May 2012 to August 2014. The NAS method autonomously generated a CNN model using one institution's dataset for training (patients/lesions: 71/91) and validation (patients/lesions: 20/23). The model was externally tested on another institution's dataset (patients/lesions: 74/87), and its performance was compared with fine-tuned ResNet-50 models and two breast radiologists who independently read the lesions in the testing dataset without knowing lesion diagnosis. RESULTS: The lesion diameters (mean ± SD) were 18.8 ± 12.9 mm, 22.7 ± 10.5 mm, and 20.0 ± 11.8 mm in the training, validation, and external testing set, respectively. Compared to the best ResNet-50 model, the NAS-generated CNN model performed three times faster and, in the external testing set, achieved a higher (though not statistically different) AUC, with sensitivity (95% CI) and specificity (95% CI) of 0.727, 80% (66-90%), and 60% (42-75%), respectively. Meanwhile, the performances of the NAS-generated CNN and the two radiologists' visual ratings were not statistically different. CONCLUSIONS: Our preliminary results demonstrated that a CNN autonomously generated by NAS performed comparably to pre-trained ResNet models and radiologists in predicting malignant breast lesions on contrast-enhanced BCBCT. In comparison to ResNet, which must be designed by an expert, the NAS approach may be used to automatically generate a deep learning architecture for medical image analysis.

The diagnostic performance of quantitative mapping in breast cancer patients: a preliminary study using synthetic MRI.

BACKGROUND: Previous studies have indicated that quantitative MRI (qMR) is beneficial for diagnosis of breast cancer. As a novel qMR technology, synthetic MRI (syMRI) may be advantageous by offering simultaneous generation of T1 and T2 mapping in one scan within a few minutes and without concern to the deposition of the gadolinium contrast agent in cell nucleus. In this study, the potential of quantitative mapping derived from Synthetic MRI (SyMRI) to diagnose breast cancer was investigated. METHODS: From April 2018 to May 2019, a total of 87 patients with suspicious breast lesions underwent both conventional and SyMRI before treatment. The quantitative metrics derived from SyMRI, including T1 and T2 values, were measured in breast lesions. The diagnostic performance of SyMRI was evaluated with unpaired Student's t-tests, receiver operating characteristic curve analysis and multivariate logistic regression analysis. The AUCs of quantitative values were compared using Delong test. RESULTS: Among 77 patients who met the inclusion criteria, 48 were diagnosed with histopathological confirmed breast cancers, and the rest had benign lesions. The breast cancers showed significantly higher T1 (1611.61 ± 215.88 ms) values and lower T2 (80.93 ± 7.51 ms) values than benign lesions. The area under the ROC curve (AUC) values were 0.931 (95% CI: 0.874-0.989) and 0.883 (95% CI: 0.810-0.956) for T1 and T2 maps, respectively, in diagnostic discrimination between breast cancers and benign lesions. A slightly increased AUC of 0.978 (95% CI: 0.915-0.993) was achieved by combining those two relaxation-based quantitative metrics. CONCLUSION: In conclusion, our preliminary study showed that the quantitative T1 and T2 values obtained by SyMRI could distinguish effectively between benign and malignant breast lesions, and T1 relaxation time showed the highest diagnostic efficiency. Furthermore, combining the two quantitative relaxation metrics further improved their diagnostic performance.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Quantitative Differentiation of Breast Tumors: A Meta-Analysis.

Objectives: The diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in the differential diagnosis of breast tumors remains debatable among published studies. Therefore, this meta-analysis aimed to pool relevant evidence regarding the diagnostic performance of IVIM-DWI in the differential diagnosis of breast tumors. Methods: Studies on the differential diagnosis of breast lesions using IVIM-DWI were systemically searched in the PubMed, Embase and Web of Science databases in recent 10 years. The standardized mean difference (SMD) and 95% confidence intervals of the apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudodiffusivity (D*), and perfusion fraction (f) were calculated using Review Manager 5.3, and Stata 12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC), as well as assess publication bias and heterogeneity. Fagan's nomogram was used to predict the posttest probabilities. Results: Sixteen studies comprising 1,355 malignant and 362 benign breast lesions were included. Most of these studies showed a low to unclear risk of bias and low concerns regarding applicability. Breast cancer had significant lower ADC (SMD = -1.38, P < 0.001) and D values (SMD = -1.50, P < 0.001), and higher f value (SMD = 0.89, P = 0.001) than benign lesions, except D* value (SMD = -0.30, P = 0.20). Invasive ductal carcinoma showed lower ADC (SMD = 1.34, P = 0.01) and D values (SMD = 1.04, P = 0.001) than ductal carcinoma in situ. D value demonstrated the best diagnostic performance (sensitivity = 86%, specificity = 86%, AUC = 0.91) and highest post-test probability (61, 48, 46, and 34% for D, ADC, f, and D* values) in the differential diagnosis of breast tumors, followed by ADC (sensitivity = 76%, specificity = 79%, AUC = 0.85), f (sensitivity = 80%, specificity = 76%, AUC = 0.85) and D* values (sensitivity = 84%, specificity = 59%, AUC = 0.71). Conclusion: IVIM-DWI parameters are adequate and superior to the ADC in the differentiation of breast tumors. ADC and D values can further differentiate invasive ductal carcinoma from ductal carcinoma in situ. IVIM-DWI is also superior in identifying lymph node metastasis, histologic grade, and hormone receptors, and HER2 and Ki-67 status.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging Used to Detect Prostate Cancer and Stratify Tumor Grade: A Meta-Analysis.

Objectives: Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) is a promising non-invasive imaging technique to detect and grade prostate cancer (PCa). However, the results regarding the diagnostic performance of IVIM-DWI in the characterization and classification of PCa have been inconsistent among published studies. This meta-analysis was performed to summarize the diagnostic performance of IVIM-DWI in the differential diagnosis of PCa from non-cancerous tissues and to stratify the tumor Gleason grades in PCa. Materials and Methods: Studies concerning the differential diagnosis of prostate lesions using IVIM-DWI were systemically searched in PubMed, Embase, and Web of Science without time limitation. Review Manager 5.3 was used to calculate the standardized mean difference (SMD) and 95% confidence intervals of the apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudodiffusivity (D*), and perfusion fraction (f). Stata 12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC), as well as publication bias and heterogeneity. Fagan's nomogram was used to predict the post-test probabilities. Results: Twenty studies with 854 patients confirmed with PCa were included. Most of the included studies showed a low to unclear risk of bias and low concerns regarding applicability. PCa showed a significantly lower ADC (SMD = -2.34; P < 0.001) and D values (SMD = -1.86; P < 0.001) and a higher D* value (SMD = 0.29; P = 0.01) than non-cancerous tissues, but no difference was noted with the f value (SMD = -0.16; P = 0.50). Low-grade PCa showed higher ADC (SMD = 0.63; P < 0.001) and D values (SMD = 0.80; P < 0.001) than the high-grade lesions. ADC showed comparable diagnostic performance (sensitivity = 86%; specificity = 86%; AUC = 0.87) but higher post-test probabilities (60, 53, 36, and 36% for ADC, D, D*, and f values, respectively) compared with the D (sensitivity = 82%; specificity = 82%; AUC = 0.85), D* (sensitivity = 70%; specificity = 70%; AUC = 0.75), and f values (sensitivity = 73%; specificity = 68%; AUC = 0.76). Conclusion: IVIM parameters are adequate to differentiate PCa from non-cancerous tissues with good diagnostic performance but are not superior to the ADC value. Diffusion coefficients can further stratify the tumor Gleason grades in PCa.

Differentiating the lung lesions using Intravoxel incoherent motion diffusion-weighted imaging: a meta-analysis.

BACKGROUND AND OBJECTIVES: The diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in the differential diagnosis of pulmonary tumors remained debatable among published studies. This study aimed to pool and summary the relevant results to provide more robust evidence in this issue using a meta-analysis method. MATERIALS AND METHODS: The researches regarding the differential diagnosis of lung lesions using IVIM-DWI were systemically searched in Pubmed, Embase, Web of science and Wangfang database without time limitation. Review Manager 5.3 was used to calculate the standardized mean difference (SMD) and 95% confidence intervals of apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f). Stata 12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC), as well as publication bias and heterogeneity. Fagan's nomogram was used to predict the post-test probabilities. RESULTS: Eleven studies with 481 malignant and 258 benign lung lesions were included. Most include studies showed a low to unclear risk of bias and low concerns regarding applicability. Lung cancer demonstrated a significant lower ADC (SMD = -1.17, P < 0.001), D (SMD = -1.02, P < 0.001) and f values (SMD = -0.43, P = 0.005) than benign lesions, except D* value (SMD = 0.01, P = 0.96). D value demonstrated the best diagnostic performance (sensitivity = 89%, specificity = 71%, AUC = 0.90) and highest post-test probability (57, 57, 43 and 43% for D, ADC, f and D* values) in the differential diagnosis of lung tumors, followed by ADC (sensitivity = 85%, specificity = 72%, AUC = 0.86), f (sensitivity = 71%, specificity = 61%, AUC = 0.71) and D* values (sensitivity = 70%, specificity = 60%, AUC = 0.66). CONCLUSION: IVIM-DWI parameters show potentially strong diagnostic capabilities in the differential diagnosis of lung tumors based on the tumor cellularity and perfusion characteristics, and D value demonstrated better diagnostic performance compared to mono-exponential ADC.

Comparison of comfort between cone beam breast computed tomography and digital mammography.

PURPOSE: To compare the comfort levels of cone beam breast computed tomography (CBBCT) and digital mammography. MATERIALS AND METHODS: On 409 patients, CBBCT was performed within 1 week after conventional mammography. Patients evaluated their comfort by using an 11-point numerical rating scale (NRS-11) after completing the two examinations. The lower the score was, the more comfortable the examination modality was. The data was divided into different groups according to CBBCT scan mode (non-contrast mode, contrast-enhanced mode), age (≤44, 45∼59 and ≥60), body mass index (BMI) (<18.5 kg/m2, 18.5∼23.9 kg/m2, 24∼27.9 kg/m2 and ≥28 kg/m2), and breast density (fatty-breast, dense-breast) to evaluate the performance of CBBCT comfort in different groups and to analyse the influencing factor of patient comfort. The paired rank sum test was used to compare the comfort between CBBCT and mammography. RESULTS: Overall, the comfort of CBBCT was better than mammography (P < 0.05). CBBCT was more comfortable than mammography in both non-contrast and contrast-enhanced groups (P < 0.05). CBBCT was more comfortable than mammography in the ≤44, 45∼59 age groups (P < 0.05). There was no significant difference in the ≥60 age group (P = 0.5433). CBBCT was more comfortable than mammography in the BMI groups of 18.5∼23.9 kg/m2, 24∼27.9 kg/m2and ≥28 kg/m2 (P < 0.05). There was no significant difference in the <18.5 kg/m2 group (P = 0.43). CBBCT was more comfortable than mammography in both the fatty-breast and dense-breast groups (P < 0.05). CONCLUSION: The comfort of CBBCT was better than mammography.

Biosurfactant surfactin with pH-regulated emulsification activity for efficient oil separation when used as emulsifier.

In the present study, the pH-regulated emulsification activity of surfactin was studied and its potential application in oil separation towards enhanced oil recovery (EOR) was investigated. As demonstrated, surfactin can stabilize emulsions quite well beyond pH 7.4. An oil emulsification ratio of about 98% was obtained at pH 11.0; while this emulsification activity was rapidly and completely lost when pH decreased to below 3.0, having an oil separation ratio of over 98%. This pH-sensitive property is probably due to surfactin dissolution-precipitation induced by the ionization-protonation of a carboxyl group in its structure under alkaline or acidic conditions. This property allows oil emulsification or oil separation to be readily achieved via simple pH adjustments when surfactin is used as an emulsifier. Furthermore, surfactin sustained its activity after demulsification and can be readily reused many times. The above obtained results indicated surfactin-based EOR processes have great application feasibility.

PCSK9 Promotes oxLDL-Induced PC12 Cell Apoptosis Through the Bcl-2/Bax-Caspase 9/3 Signaling Pathway.

BACKGROUND: Hyperlipidemia is a risk factor for neurodegenerative diseases. Proprotein convertase subtilisin / Kexin type 9 (PCSK9) degrades hepatic low-density lipoprotein receptor (LDLR) to regulate lipid metabolism. It is unclear if PCSK9 plays a role in neurodegenerative diseases. OBJECTIVE: This study was designed to determine whether PCSK9 is crucial between hyperlipidemia and Alzheimer's disease. The interrelationship between PCSK9 and neuronal apoptosis was explored in PC12 cells in response to treatment with oxidized low-density lipoprotein (oxLDL). METHODS: Cultured PC12 cells were serum-starved and incubated with different concentrations of oxLDL for 24 h. Intracytoplasmic lipid droplets were observed by oil red O staining. Morphological assessment of apoptotic cells was performed using Hoechst 33258 staining and flow cytometry analysis. The expression of mRNA and protein was detected by reverse-transcription polymerase chain reaction (RT-PCR) and western blot analyses, respectively. Transfection of small interfering RNA (siRNA) into PC12 cells was conducted using HiperFect Transfection Reagent. Concentrations of Aß40 and Aß42 were detected by enzyme-linked immunosorbent assay (ELISA) kit. RESULTS: Intracellular lipid content, the number of apoptotic cells, and PCSK9 expression were increased in PC12 cells after oxLDL treatment. Transfection with PCSK9 siRNA reduced the oxLDL-induced apoptosis of PC12 cells. We further confirmed the involvement of Bcl-2/Bax-Caspase (9, 3) signaling pathway in the regulation of PC12 cells apoptosis.ß-Secretase 1, another target gene of PCSK9, was downregulated in PC12 cells in response to oxLDL treatment. Aß40 and Aß42 contents were also decreased. CONCLUSION: PCSK9 promotes oxLDL-induced PC12 cell apoptosis through the Bcl-2/Bax-Caspase 9/3 signaling pathway.

Functional regulatory roles of microRNAs in atherosclerosis.

MicroRNAs are a group of endogenously small non-coding RNA molecules that downregulate gene expression at the post-transcriptional level through binding to the 3'UTR of target mRNAs. Recent findings have revealed a key role for microRNAs in the pathophysiological processes of atherosclerosis. As a complex disease, atherosclerosis is influenced by a combination of multiple genes and environmental factors. Both of them play a role in atherogenesis by affecting different types of cells (such as endothelial cell, vascular smooth muscle cell and monocyte/macrophage) function. MicroRNAs control the senescence and dysfunction of endothelial cells, proliferation and migration of vascular smooth muscle cells, and macrophage-driven cytokine production and polarization. By these effects, microRNAs can influence the processes of atherosclerosis and may represent new molecular targets for therapy.

The utility of breast cone-beam computed tomography, ultrasound, and digital mammography for detecting malignant breast tumors: A prospective study with 212 patients.

PURPOSE: Breast cone-beam computed tomography (BCBCT) is a flat-panel detector (FPD)-based X-ray imaging system that provides high-quality images of the breast. The purpose of this study was to investigate the ability to detect breast abnormalities using non-contrast BCBCT and contrast-enhanced BCBCT (BCBCT and CE-BCBCT) compared to ultrasound (US) and digital mammography (MG). MATERIALS AND METHODS: A prospective study was performed from May 2012 to August 2014. Ninety-two patients (172 lesions) underwent BCBCT alone, and 120 patients (270 lesions) underwent BCBCT and CE-BCBCT, all the patients underwent US and MG. RESULTS: Cancer diagnosis was confirmed pathologically in 102 patients (110 lesions). BCBCT identified 97 of 110 malignant lesions, whereas 93 malignant lesions were identified using MG and US. The areas under the receiver operating curves (AUCs) for breast cancer diagnosis were 0.861 (BCBCT), 0.856 (US), and 0.829 (MG). CE-BCBCT improved cancer diagnostic sensitivity by 20.3% (78.4-98.7%). The AUC values were 0.869 (CE-BCBCT), 0.846 (BCBCT), 0.834 (US), and 0.782 (MG). CONCLUSION: In this preliminary study, BCBCT was found to accurately identify malignant breast lesions in a diagnostic setting. CE-BCBCT provided additional information and improved cancer diagnosis in style c or d breasts compared to the use of BCBCT, US, or MG alone.

The number of tumor-free axillary lymph nodes removed as a prognostic parameter for node-negative breast cancer.

Recently, there has been controversy about the relationship between the number of lymph nodes removed and survival of patients diagnosed with lymph node-negative breast cancer. To assess this relationship, 603 cases of lymph node-negative breast cancer with a median of 126 months of follow-up data were studied. Patients were stratified into two groups (Group A, 10 or fewer tumor-free lymph nodes removed; Group B, more than 10 tumor-free lymph nodes removed). The number of tumor-free lymph nodes in ipsilateral axillary resections as well as 5 other disease parameters were analyzed for prognostic value. Our results revealed that the risk of death from breast cancer was significantly associated with patient age, marital status, histologic grade, tumor size, and adjuvant therapy. The 5- and 10-year survival rates for patients with 10 or fewer tumor-free lymph nodes removed was 88.0% and 66.4%, respectively, compared with 69.2% and 51.1%, respectively, for patients with more than 10 tumor-free lymph nodes removed. For patients with 10 or fewer tumor-free lymph nodes removed, the adjusted hazard ratio (HR) for risk of death from breast cancer was 0.579 (95% confidence interval, 0.492-0.687, P < 0.001), independent of patient age, marital status, histologic grade, tumor size, and adjuvant therapy. Our study suggests that the number of tumor-free lymph nodes removed is an independent predictor in cases of lymph node-negative breast cancer.

Effect of vascular haemoglobin concentrations on ultrasound-guided diffuse optical tomography in differentiating benign from malignant breast lesions.

OBJECTIVES: Ultrasound-guided diffuse optical tomography (US-DOT) can potentially detect breast carcinomas by measuring total tumour haemoglobin concentrations (TTHC). The purpose of this study was to evaluate whether vascular haemoglobin concentrations (VHC) affect the ability of US-DOT to distinguish breast carcinomas from benign. MATERIALS AND METHODS: In 85 women (97 palpable lesions) referred for core breast biopsy, we measured VHC with a complete blood count and calculated TTHCs for each lesion with US-DOT. Anaemia was defined as a VHC less than 120.0 g/L. RESULTS: Mean TTHCs were significantly higher in malignant lesions (n = 53) than in benign lesions (n = 44), regardless of whether the lesions were from women with anaemia (TTHC, 248.5 vs. 123.3 µmol/L; P = 0.001) or from those without (TTHC, 229.7 vs. 173.9 µmol/L; P = 0.016). A cut-off TTHC of 155.1 µmol/L provided 81.3 % sensitivity, 81.8 % specificity and 81.5 % accuracy for detecting malignant tumours in women with anaemia and 78.4 % sensitivity, 54.5 % specificity and 67.1 % accuracy for women without. There was no significant difference in sensitivity (P = 0.813), specificity (P = 0.108) and accuracy (P = 0.162) between the anaemic group and the non-anaemic group. CONCLUSIONS: Vascular haemoglobin concentrations did not affect the ability of US-DOT to differentiate breast carcinomas from benign lesions. KEY POINTS: • US-DOT can differentiate benign from malignant breast lesions by measuring TTHC. • No difference in TTHC between the anaemia and non-anaemia group. • Vascular haemoglobin concentrations do not affect the diagnostic ability of US-DOT.