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Objective: To construct a multi-region MRI radiomics model for predicting pathological complete response (pCR) in breast cancer (BCa) patients who received neoadjuvant chemotherapy (NACT) and provide a theoretical basis for the peritumoral microenvironment affecting the efficacy of NACT. Methods: A total of 133 BCa patients who received NACT, including 49 with confirmed pCR, were retrospectively analyzed. The radiomics features of the intratumoral region, peritumoral region, and background parenchymal enhancement (BPE) were extracted, and the most relevant features were obtained after dimensional reduction. Then, combining different areas, multivariate logistic regression analysis was used to select the optimal feature set, and six different machine learning models were used to predict pCR. The optimal model was selected, and its performance was evaluated using receiver operating characteristic (ROC) analysis. SHAP analysis was used to examine the relationship between the features of the model and pCR. Results: For signatures constructed using three individual regions, BPE provided the best predictions of pCR, and the diagnostic performance of the intratumoral and peritumoral regions improved after adding the BPE signature. The radiomics signature from the combination of all the three regions with the XGBoost machine learning algorithm provided the best predictions of pCR based on AUC (training set: 0.891, validation set: 0.861), sensitivity (training set: 0.882, validation set: 0.800), and specificity (training set: 0.847, validation set: 0.84). SHAP analysis demonstrated that LZ_log.sigma.2.0.mm.3D_glcm_ClusterShade_T12 made the greatest contribution to the predictions of this model. Conclusion: The addition of the BPE MRI signature improved the prediction of pCR in BCa patients who received NACT. These results suggest that the features of the peritumoral microenvironment are related to the efficacy of NACT. [ABSTRACT FROM AUTHOR]

Objective: To construct and validate a multi-dimensional model based on multiple machine leaning algorithms to predict PCLM using multi-parameter magnetic resonance (MRI) sequences with clinical and imaging parameters. Methods: A total of 148 PDAC retrospectively examined patients were classified as metastatic or non-metastatic based on results at 3 months after surgery. The radiomics features of the primary tumor were extracted from T2WI images, followed by dimension reduction. Then, multiple machine learning methods were used to construct models. Independent predictors were also screened using multifactor logistic regression and a nomogram was constructed in combination with the radiomics model. Area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to assess the accuracy and reliability of the nomogram. Results: The diagnostic efficacy of the radiomics model in the training and test set was 0.822 and 0.803, sensitivity was 0.742 and 0.692, and specificity was 0.792 and 0.875, respectively. The diagnostic efficacy of the nomogram in the training and test set was 0.866 and 0.832. Conclusion: A radiomics nomogram based on machine learning improved the accuracy of predicting PCLM and may be useful for early preoperative diagnosis. [ABSTRACT FROM AUTHOR]

A "hardenability" experiment which contained solution treatment followed by single-side quenching and aging afterward of a cylinder specimen was carried out to research on the choice of cooling method considering temperature distribution, hardness and microstructure for a newly developed high-strength heat resistant rare-earth wrought magnesium alloy Mg–Gd–Y–Zr–Ag–Er. The results revealed that the closer the sample was to the quenching surface, the faster the temperature decreased. The largest measured temperature difference was 320°C. The hardness was ranging from 76 to 86 HV in the quenched state, and 110 to 119 HV in the aged state. The various cooling rates had little effect on the hardness, the grains and precipitates of this kind of magnesium alloy, solution treatment followed by a lower cooling process like air cooling may be a better choice. [ABSTRACT FROM AUTHOR]

Background: This study aimed to predict myocardial ischemia (MIS) by constructing models with imaging features, CT-fractional flow reserve (CT-FFR), pericoronary fat attenuation index (pFAI), and radiomics based on coronary computed tomography angiography (CCTA). Methods and results: This study included 96 patients who underwent CCTA and single photon emission computed tomography-myocardial perfusion imaging (SPECT-MPI). According to SPECT-MPI results, there were 72 vessels with MIS in corresponding supply area and 105 vessels with no-MIS. The conventional model [lesion length (LL), MDS (maximum stenosis diameter × 100% / reference vessel diameter), MAS (maximum stenosis area × 100% / reference vessel area) and CT value], radiomics model (radiomics features), and multi-faceted model (all features) were constructed using support vector machine. Conventional and radiomics models showed similar predictive efficacy [AUC: 0.76, CI 0.62–0.90 vs. 0.74, CI 0.61–0.88; p > 0.05]. Adding pFAI to the conventional model showed better predictive efficacy than adding CT-FFR (AUC: 0.88, CI 0.79–0.97 vs. 0.80, CI 0.68–0.92; p < 0.05). Compared with conventional and radiomics model, the multi-faceted model showed the highest predictive efficacy (AUC: 0.92, CI 0.82–0.98, p < 0.05). Conclusion: pFAI is more effective for predicting MIS than CT-FFR. A multi-faceted model combining imaging features, CT-FFR, pFAI, and radiomics is a potential diagnostic tool for MIS. [ABSTRACT FROM AUTHOR]

Purpose: To establish a model for predicting mild cognitive impairment (MCI) progression to Alzheimer's disease (AD) using morphological features extracted from a joint analysis of voxel-based morphometry (VBM) and surface-based morphometry (SBM). Methods: We analyzed data from 121 MCI patients from the Alzheimer's Disease Neuroimaging Initiative, 32 of whom progressed to AD during a 4-year follow-up period and were classified as the progression group, while the remaining 89 were classified as the non-progression group. Patients were divided into a training set (n = 84) and a testing set (n = 37). Morphological features measured by VBM and SBM were extracted from the cortex of the training set and dimensionally reduced to construct morphological biomarkers using machine learning methods, which were combined with clinical data to build a multimodal combinatorial model. The model's performance was evaluated using receiver operating characteristic curves on the testing set. Results: The Alzheimer's Disease Assessment Scale (ADAS) score, apolipoprotein E (APOE4), and morphological biomarkers were independent predictors of MCI progression to AD. The combinatorial model based on the independent predictors had an area under the curve (AUC) of 0.866 in the training set and 0.828 in the testing set, with sensitivities of 0.773 and 0.900 and specificities of 0.903 and 0.747, respectively. The number of MCI patients classified as high-risk for progression to AD was significantly different from those classified as low-risk in the training set, testing set, and entire dataset, according to the combinatorial model (P < 0.05). Conclusion: The combinatorial model based on cortical morphological features can identify high-risk MCI patients likely to progress to AD, potentially providing an effective tool for clinical screening. [ABSTRACT FROM AUTHOR]

In order to get flow behavior of a deformation state magnesium alloy Mg–Gd–Y–Zr–Ag–Er, hot compression tests were performed on a Gleeble-3500 thermo-simulation machine ranging from 623 to 773 K and at strain rates of 0.001–1 s−1. Hyperbolic sine model and feed-forward back propagation (BP) artificial neural network (ANN) model were used to predict flow behavior through different temperature, strain and strain rate. The correlation coefficient (R2) between the experimental and predicted flow stress in Hyperbolic sine model and BP-ANN model are 0.9700, 0.9996, respectively, the average relative error (AARE) corresponding to Hyperbolic sine model and BP-ANN model are 7.084 and 1.785%, the relative errors distribution range of BP-ANN model are more centralized than that of Hyperbolic sine model. Cross-validation approach was applied to analyze the predictability of the two models. The predictability of BP-ANN model is more accurate than Hyperbolic sine model. [ABSTRACT FROM AUTHOR]

Simulation model accuracy of quench induced residual stress in wrought magnesium alloy Mg‒Gd–Y–Zr–Ag–Er is tested by applying both isotropic and anisotropic criteria models in residual stress FEM simulation. Both hexagonal close-packed (HCP) lattice structure and asymmetry are considered in the manufacturing process. The distributions of residual stress in isotropic and anisotropic criteria models differ both in distribution and in value, which is due to stress-strain nonuniformity in extrusion direction (ED) and long transverse direction (LTD). Comparing the experimental and predicted errors of the two models, the anisotropic model improves the prediction accuracy by 8.3% in ED and 4.8% in LTD. Residual stress in LTD is always larger than that in ED by the XRD method, and the average deviation between the XRD method and the hole-drilling method is reduced through electropolishing. [ABSTRACT FROM AUTHOR]

Purpose: Ovarian function is important for optimizing endocrine treatment in patients with hormone receptor-positive (HR+) early breast cancer (eBC). The aim of the study was to determine whether patients' pretreatment levels of anti-Mullerian hormone (AMH) were associated with menses status after chemotherapy and to build a predictive nomogram model for amenorrhea in women with HR+ eBC.Methods: Between August 2013 and December 2014, 120 premenopausal patients with HR+ eBC were included retrospectively. The associations among age, prechemotherapy levels of AMH, follicle-stimulating hormone (FSH),and estradiol (E2) and the 2-year postchemotherapy menses status were analyzed. We determined the cutoff values of hormone levels by using the biostatistical tool (Cutoff Finder). A novel nomogram was established to predict the 2-year amenorrhea status based on the logistic analysis. Concordance index (C-index) was used to validate the capacity.Results: One hundred nine women (90.8%) experienced amenorrhea after chemotherapy. AMH < 0.965 ng/ml predicted amenorrhea at 2 years (AUC 0.84, sensitivity 74% and specificity 81.8%), independent of age. The predictive nomogram based on age and pretreatment AMH and FSH levels was developed to predict the probability of 2-year postchemotherapy amenorrhea with a C-index of 0.88 (95% CI 0.84-0.91).Conclusions: In premenopausal patients with HR+ eBC, prechemotherapy AMH concentration was associated with the patient's 2-year amenorrhea status, independent of age. The nomogram model based on age and pretreatment AMH and FSH levels accurately predicted the 2-year amenorrhea status. [ABSTRACT FROM AUTHOR]

Purpose: Endocrine therapy is associated with improved disease-free survival (DFS) in hormone receptor-positive breast cancer, but it is also associated with many adverse events. The aim of this study was to clarify the association between endocrine treatment-related symptoms and treatment efficacy in patients receiving adjuvant endocrine therapy. Method: EMBASE, Web of Science, PubMed, and CENTRAL databases were searched for studies that compared treatment efficacy between patients in whom adverse events did and did not occur during hormone therapy. Hazard ratios (HRs) and associated 95 % confidence intervals (CIs) for DFS and overall survival were estimated and pooled using random-effects models. Results: Of 4665 citations identified, ten studies incorporating 32,192 patients were included in the meta-analysis. The presence of endocrine treatment-related symptoms was associated with improved DFS (HR 0.76; 95 % CI 0.68-0.85). Similar results were observed in patients with vasomotor symptoms (HR 0.76; 95 % CI 0.66-0.87) or musculoskeletal symptoms (HR 0.75; 95 % CI 0.60-0.94), in patients taking an aromatase inhibitor (HR 0.69; 95 % CI 0.57-0.85) or tamoxifen (HR 0.74; 95 % CI 0.60-0.93), and in patients with symptoms at 3-month (HR 0.74; 95 % CI 0.66-0.83), 6-month (HR 0.80; 95 % CI 0.66-0.96), or 12-month follow-up visits (HR 0.75; 95 % CI 0.68-0.83). However, no significant difference in overall survival was observed between patients with or without endocrine treatment-related symptoms (HR 0.82; 95 % CI 0.60-1.11). Sensitivity analysis excluding studies with heterogeneous factors yielded consistent results. No evidence of publication bias was observed. Conclusion: In our meta-analysis, endocrine treatment-related symptoms were shown to correlate with superior DFS and may therefore be useful in predicting treatment efficacy in patients with breast cancer receiving hormone therapy. [ABSTRACT FROM AUTHOR]

The aim of this study is to analyze the prognostic value of androgen receptor (AR) expression for patients with triple-negative breast cancer (TNBC). Clinical data of these patients were collected and analyzed, and immunohistochemical staining for AR was performed on tissue microarrays of operable breast cancer from 287 patients with TNBC, who were treated at Sun Yat-sen University Cancer Center from January 1995 to December 2008. AR expression was found in 25.8% of the cases with TNBC. TNBC patients with AR negative have a higher proportion of positive lymph node. A significant correlation was found between AR expression and disease-free survival (DFS) and overall survival (OS). Univariated analysis indicated that AR expression had a significant prognostic value in TNBC patients, whereas multivariate analysis indicated that AR was a significant independent prognostic factor of DFS ( P = 0.032) in all patients. Our results suggested that AR was a favorable prognostic factor of DFS and OS in patients with TNBC. Therefore, TNBC may be further divided into two subtypes according to AR status. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyze the prognostic value of EGFR expression for patients with triple-negative breast cancer (TNBC). Clinical data of these patients were collected and analyzed, and immunohistochemical staining for EGFR was performed on tissue microarrays of operable breast cancer from 287 patients with TNBC, who were treated at Sun Yat-sen University Cancer Center from January 1995 to December 2008. EGFR expression was found in 36.2% of the cases with TNBC. A significant correlation was found between EGFR expression and disease-free survival (DFS). Univariated analysis indicated that EGFR expression had a significant prognostic value in TNBC patients, whereas multivariate analysis indicated that EGFR was a significant independent prognostic factor of DFS ( P = 0.011) in all patients. Our results suggested that EGFR was an independent prognostic factor of DFS in patients with TNBC. Therefore, EGFR could become a good therapeutic target in the treatment of TNBC. [ABSTRACT FROM AUTHOR]

Patients suffering from triple-negative breast cancer (TNBC) have poor prognosis mainly because no standard treatment is currently available. Our objectives were to explore the prognostic factors for first relapse of patients with TNBC. A cohort of 687 patients with TNBC, diagnosed and treated between January 1995 and December 2008 at Sun Yat-sen University Cancer Center, were retrospectively analyzed. Cox proportional hazards models were fitted to explore factors that predict relapse development. Survival rate was computed using the Kaplan-Meier product limit method. The median age of the 687 patients was 46 (range 16-76 years), and 64.8% of the patients were pre-menopausal. The median follow-up time was 56 months (range 14-156 months), in which 194 patients had recurrence, and 115 died. The median recurrence-free time was 25 months (range 4-143 months), with 118 (60.8%) of the cases first relapsing at a single site. The three- and five-year disease-free survival rates were 79.7 and 72.6%, respectively. Primary tumor size at diagnosis, lymph node status, and type of regimen used in the (neo)adjuvant chemotherapy were considered independent predictors of first relapse. CMF-containing adjuvant chemotherapy significantly decreased recurrence compared with the anthracycline- or taxane-based regimens (RR = 0.66, 95%; CI 0.45-0.96; P = 0.030). The median time from first relapse to death was 26 months (range 2-121 months). The two- and five-year survival rates were 60.6 and 36.6%, respectively. Liver metastasis at first recurrence and progression-free survival over 12 months after first-line therapy were two important factors that affected survival rate after recurrence. The median relapse time of TNBC was about 2 years after diagnosis. CMF regimens for TNBC patients may be more effective than anthracycline- or taxane-based regimens. Liver metastasis at first recurrence signifies unfavorable prognosis. [ABSTRACT FROM AUTHOR]

The extremely low incidence of male breast cancer (MBC) leads to lack of prospective randomized phase III studies worldwide. Especially in China, all studies on Chinese patients with MBC were based on small sample size and single institute experience. The aim of this study was to provide overall view of characteristics of Chinese patients with MBC by means of summarizing all related papers published in Chinese journals. An online search was made in CBM, VIP, CNKI, and CBA databases to find all published articles of interest on Chinese patients with MBC. And eight subjects including the proportion of MBC in all breast cancer, age, tumor location, clinical stages, pathological subtypes, treatment modalities, ER/PR expression, and 5-year survival rate were selected to calculate the proportion and their 95% interval confidence. There were 122 papers with 2584 patients enrolled. The basic features of Chinese patients with MBC included: (1) MBC only with a proportion of 1.06% of all the breast cancer; (2) The mean age at diagnosis was 57.6 years old; (3) Tumor mainly located in the areolar region (74.83%) with obvious nipple and/or skin involvement; (4) Nearly 62.62% patients were in early stage before accepting treatment; (5) Infiltrating ductal carcinoma accounted for 79.05% of all pathological subtypes; (6) ER/PR expression rate was 65.86%; (7) Radical resection was up to 86.06% in all surgical modalities; (8) The 5-year survival rate was 57.33%. The results showed in this study were an overall view of Chinese patients with MBC whose characteristics were similar to that reported in the West. Though this study provided a little bit stronger confidence than a single study collected in this paper, studies with more powerful evidence are urgently demanding in China. [ABSTRACT FROM AUTHOR]