Permutation Equivariant Graph Framelets for Heterophilous Graph Learning.

The nature of heterophilous graphs is significantly different from that of homophilous graphs, which causes difficulties in early graph neural network (GNN) models and suggests aggregations beyond the one-hop neighborhood. In this article, we develop a new way to implement multiscale extraction via constructing Haar-type graph framelets with desired properties of permutation equivariance, efficiency, and sparsity, for deep learning tasks on graphs. We further design a graph framelet neural network model permutation equivariant graph framelet augmented network (PEGFAN) based on our constructed graph framelets. The experiments are conducted on a synthetic dataset and nine benchmark datasets to compare the performance with other state-of-the-art models. The result shows that our model can achieve the best performance on certain datasets of heterophilous graphs (including the majority of heterophilous datasets with relatively larger sizes and denser connections) and competitive performance on the remaining.

Neoadjuvant Chemotherapy and Neoadjuvant Chemotherapy With Immunotherapy Result in Different Tumor Shrinkage Patterns in Triple-Negative Breast Cancer.

PURPOSE: This study aims to explore whether neoadjuvant chemotherapy with immunotherapy (NACI) leads to different tumor shrinkage patterns, based on magnetic resonance imaging (MRI), compared to neoadjuvant chemotherapy (NAC) alone in patients with triple-negative breast cancer (TNBC). Additionally, the study investigates the relationship between tumor shrinkage patterns and treatment efficacy was investigated. METHODS: This retrospective study included patients with TNBC patients receiving NAC or NACI from January 2019 until July 2021 at our center. Pre- and post-treatment MRI results were obtained for each patient, and tumor shrinkage patterns were classified into three categories as follows: 1) concentric shrinkage (CS); 2) diffuse decrease; and 3) no change. Tumor shrinkage patterns were compared between the NAC and NACI groups, and the relevance of the patterns to treatment efficacy was assessed. RESULTS: Of the 99 patients, 65 received NAC and 34 received NACI. The CS pattern was observed in 53% and 20% of patients in the NAC and NACI groups, respectively. Diffuse decrease pattern was observed in 36% and 68% of patients in the NAC and NACI groups. The association between the treatment regimens (NAC and NACI) and tumor shrinkage patterns was statistically significant (p = 0.004). The postoperative pathological complete response (pCR) rate was 45% and 82% in the NAC and NACI groups (p < 0.001), respectively. In the NACI group, 17% of patients with the CS pattern and 56% of those with the diffuse decrease pattern achieved pCR (p = 0.903). All tumor shrinkage patterns were associated with achieved a high pCR rate in the NACI group. CONCLUSION: Our study demonstrates that the diffuse decrease pattern of tumor shrinkage is more common following NACI than that following NAC. Furthermore, our findings suggest that all tumor shrinkage patterns are associated with a high pCR rate in patients with TNBC treated with NACI. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04909554.

Homologous recombination deficiency predicts the response to platinum-based neoadjuvant chemotherapy in early-stage triple-negative breast cancer patients: a systematic review and meta-analysis.

Background: Recent studies have shown that homologous recombination deficiency (HRD) may be correlated with the pathological complete response (pCR) rate. This meta-analysis aimed to determine the predictive value of HRD for the pCR rate in patients with triple-negative breast cancer (TNBC) receiving platinum-based neoadjuvant chemotherapy (NCT). Methods: Published articles were searched in the PubMed, Embase, Medline, Web of Science, and Cochrane databases up to 1 June 2021, and studies reporting the pCR rate for HRD carriers on platinum-based NCT were selected. Odds ratios (ORs) with 95% confidence intervals (CIs) were determined for the pCR rate, clinical response rate, and Grade 3 or higher adverse events (AEs) using the random-effects model. Bias risk was evaluated using the Cochrane Collaboration tool (PROSPERO, registration number CRD42021249874). Results: Seven studies were eligible. The results showed that HRD carriers had higher pCR rates than non-HRD carriers across all treatment arms (OR = 3.84, 95% CI = [1.93, 7.64], p = 0.0001). Among HRD carriers, the pCR rate was higher in patients on platinum-based NCT than in those without platinum exposure (OR = 1.95, 95% CI = [1.17, 3.23], p = 0.01). We did not observe marked pCR improvements in non-HRD carriers. Among HRD carriers, the pCR rates in the mutant and wild-type breast cancer susceptibility gene (BRCA) groups did not differ significantly (OR = 2.00, 95% CI = [0.77, 5.23], p = 0.16), but HRD carriers with wild-type BRCA had a significant advantage over non-HRD carriers on platinum-based NCT (OR = 3.64, 95% CI = [1.83, 7.21], p = 0.0002). Conclusion: HRD is an effective predictor of increased pCR rates in platinum-based NCT, especially in wild-type BRCA patients. Adding platinum to NCT for non-HRD carriers can increase the incidence of AEs but may not improve the therapeutic effect.

A Model Incorporating Axillary Tail Position on Mammography for Preoperative Prediction of Non-sentinel Lymph Node Metastasis in Patients with Initial cN+ Breast Cancer after Neoadjuvant Chemotherapy.

RATIONALE AND OBJECTIVES: This study aimed to develop a model incorporating axillary tail position on mammography (AT) for the prediction of non-sentinel Lymph Node (NSLN) metastasis in patients with initial clinical node positivity (cN+). METHODS AND MATERIALS: The study reviewed a total of 257 patients with cN+ breast cancer who underwent both sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) following neoadjuvant chemotherapy (NAC). A logistic regression model was developed based on these factors and the results of post-NAC AT and axillary ultrasound (AUS). RESULTS: Four clinical factors with p<0.1 in the univariate analysis, including ycT0(odds ratio [OR]: 4.84, 95% confidence interval [CI]: 2.13-11.91, p<0.001), clinical stage before NAC (OR: 2.68, 95%CI: 1.15-6.58, p=0.025), estrogen receptor (ER) expression (OR: 3.29, 95%CI: 1.39-8.39, p=0.009), and HER2 status (OR: 0.21, 95%CI: 0.08-0.50, p=0.001), were independent predictors of NSLN metastases. The clinical model based on the above four factors resulted in the area under the curve (AUC) of 0.82(95%CI: 0.76-0.88) in the training set and 0.83(95% CI: 0.74-0.92) in the validation set. The results of post-NAC AUS and AT were added to the clinical model to construct a clinical imaging model for the prediction of NSLN metastasis with AUC of 0.87(95%CI: 0.81-0.93) in the training set and 0.89(95%CI: 0.82-0.96) in the validation set. CONCLUSIONS: The study incorporated the results of post-NAC AT and AUS with other clinal factors to develop a model to predict NSLN metastasis in patients with initial cN+ before surgery. This model performed excellently, allowing physicians to select patients for whom unnecessary ALND could be avoided after NAC.

Convolutional Neural Networks for Spherical Signal Processing via Area-Regular Spherical Haar Tight Framelets.

In this article, we develop a general theoretical framework for constructing Haar-type tight framelets on any compact set with a hierarchical partition. In particular, we construct a novel area-regular hierarchical partition on the two spheres and establish its corresponding spherical Haar tight framelets with directionality. We conclude by evaluating and illustrate the effectiveness of our area-regular spherical Haar tight framelets in several denoising experiments. Furthermore, we propose a convolutional neural network (CNN) model for spherical signal denoising, which employs fast framelet decomposition and reconstruction algorithms. Experiment results show that our proposed CNN model outperforms threshold methods and processes strong generalization and robustness.

Visualization positioning-guided biopsy of suspicious breast microcalcifications: a retrospective cohort study.

BACKGROUND: At present, most histological evaluations of microcalcifications without a mass are performed using X-ray guided hook wire localization or vacuum-assisted stereotactic biopsy (VASB), but there are still several limitations to these techniques. Therefore, we designed a visualization positioning technique based on three directions of mammography to accurately locate suspected microcalcifications to guide the biopsy. METHODS: We retrospectively analyzed consecutive patients with suspicious microcalcifications who underwent visualization positioning-guided biopsy (VPB) from June 1, 2016, to June 1, 2021. The visualization positioning technique was performed using an electronic ruler to measure the vertical distance from the microcalcification core to the vertical lines on mammography. RESULTS: A total of 133 patients (median age 46 years; range, 22-87 years) who underwent VPB were included in our study. Among the 133 cases of microcalcifications based on pathological results, 104 were benign, 14 were high risk, and 15 were malignant. In 124 (93.2%) patients, microcalcification was confirmed during the first round of VPB specimen analysis. Only 6 (4.5%) and 3 (2.3%) patients underwent second and third extended resections, respectively, as the resected specimens did not contain microcalcifications. Four patients (3.0%) with malignant biopsy results underwent a subsequent operation. Two patients with DCIS underwent mastectomy and sentinel lymph node biopsy because of diffuse calcification. One patient had no residual cancer, and the other was upgraded to invasive ductal carcinoma (IDC). Two patients with IDC underwent breast-conserving surgery and mastectomy with sentinel lymph node biopsy. CONCLUSIONS: VPB can be used to evaluate breast microcalcifications when a mass is not present, making it an effective diagnostic technique.

Effects of Surgery on Prognosis of Young Women With Operable Breast Cancer in Different Marital Statuses: A Population-Based Cohort Study.

BACKGROUND: The influence of surgical approaches [including mastectomy, breast-conserving therapy (BCT) and post-mastectomy breast reconstruction (PMBR) on prognosis of young women (<40 years old) with operable breast cancer has not been determined yet, and this might vary in patients with different marital statuses. Therefore, we aimed to investigate the effect of surgery on survival outcomes for young women with operable breast cancer in different marital statuses. METHODS: We used the Surveillance, Epidemiology, and End Results (SEER) database to identify young women with operable breast cancer between 2004 and 2016, who underwent mastectomy, BCT or PMBR. We assessed overall survival (OS) and breast cancer-specific survival (BCSS) using the Kaplan-Meier method and hazard ratios using multivariate Cox proportional hazard regression. RESULTS: Compared to mastectomy, both of BCT and PMBR conferred better OS (BCT: HR = 0.79, 95%CI: 0.69-0.90, p <0.001; PMBR: HR = 0.70, 95%CI: 0.63-0.78, p <0.001) and BCSS (BCT: HR = 0.79, 95%CI: 0.69-0.91, p = 0.001; PMBR: HR = 0.73, 95%CI: 0.65-0.81, p <0.001), but there was no significant difference of survival between BCT and PMBR group. The survival benefit of BCT compared to mastectomy remained significant in unmarried young women (OS: HR = 0.68, 95%CI: 0.55-0.83, p <0.001; BCSS: HR = 0.69, 95%CI: 0.56-0.86, p = 0.001) but not in the married (OS: HR = 0.89, 95%CI: 0.75-1.05, p = 0.177; BCSS: HR = 0.89, 95%CI: 0.75-1.05, p = 0.161), while no matter married or not, PMBR group had better OS and BCSS than mastectomy group but not BCT group. CONCLUSION: Both of BCT and PMBR had improved survival compared to mastectomy for young women with operable breast cancer. The survival benefit of BCT compared to mastectomy remained significant in unmarried patients but not in married patients.

Survival outcomes after breast-conserving therapy compared with mastectomy for patients with early-stage metaplastic breast cancer: a population-based study of 2412 patients.

BACKGROUND: Previous studies revealed that patients with early-stage metaplastic breast cancer (MBC) underwent mastectomy more often than breast-conserving therapy (BCT) mainly due to the larger tumor size. This study was performed to compare the survival outcomes following BCT versus mastectomy for patients with early-stage MBC. METHODS: Surveillance, Epidemiology, and End Results (SEER) database was used to identify women diagnosed with early-stage MBC (T1-3N0-3M0) between 2001 and 2016, who were treated with either BCT or mastectomy. We assessed overall survival (OS) and breast cancer-specific survival (BCSS) using the Kaplan-Meier method and hazard ratios using Cox proportional hazards models. RESULTS: A total of 2412 MBC patients were identified, 881 (36.5%) of whom underwent BCT and 1531(63.5%) underwent mastectomy. The median follow-up time was 73 months. Most of patients had older age (≥50 years old), larger tumor size, higher American Joint Committee on Cancer (AJCC) stage and hormone receptor negativity. After adjustment for confounding variables, patients who underwent BCT had significantly improved OS (5-year OS: 84.3% vs 62.5%; 10-year OS: 73.0% vs 52.1%; adjusted HR = 0.76, 95%CI: 0.59-0.97, p = 0.028) and BCSS (5-year BCSS: 89.1% vs 70.8%; 10-year BCSS: 83.9% vs 67.5%; adjusted HR = 0.72, 95%CI: 0.53-0.96, p = 0.026) than those who underwent mastectomy, and this improvement remained significant for all T and N stages of MBC except for N2-3 stage. CONCLUSION: BCT conferred improved OS and BCSS compared with mastectomy for patients with early-stage MBC, and the improvement persisted in almost all of the subgroups of different T and N stages.

Multiparametric MRI-based radiomics analysis for the prediction of breast tumor regression patterns after neoadjuvant chemotherapy.

OBJECTIVES: Breast cancers show different regression patterns after neoadjuvant chemotherapy. Certain regression patterns are associated with more reliable margins in breast-conserving surgery. Our study aims to establish a nomogram based on radiomic features and clinicopathological factors to predict regression patterns in breast cancer patients. METHODS: We retrospectively reviewed 144 breast cancer patients who received neoadjuvant chemotherapy and underwent definitive surgery in our center from January 2016 to December 2019. Tumor regression patterns were categorized as type 1 (concentric regression + pCR) and type 2 (multifocal residues + SD + PD) based on pathological results. We extracted 1158 multidimensional features from 2 sequences of MRI images. After feature selection, machine learning was applied to construct a radiomic signature. Clinical characteristics were selected by backward stepwise selection. The combined prediction model was built based on both the radiomic signature and clinical factors. The predictive performance of the combined prediction model was evaluated. RESULTS: Two radiomic features were selected for constructing the radiomic signature. Combined with two significant clinical characteristics, the combined prediction model showed excellent prediction performance, with an area under the receiver operating characteristic curve of 0.902 (95% confidence interval 0.8343-0.9701) in the primary cohort and 0.826 (95% confidence interval 0.6774-0.9753) in the validation cohort. CONCLUSIONS: Our study established a unique model combining a radiomic signature and clinicopathological factors to predict tumor regression patterns prior to the initiation of NAC. The early prediction of type 2 regression offers the opportunity to modify preoperative treatments or aids in determining surgical options.

A nomogram to predict non-sentinel lymph node metastasis in patients with initial cN+ breast cancer that downstages to cN0 after neoadjuvant chemotherapy.

BACKGROUND AND OBJECTIVES: This study mainly explored the factors that influence non-sentinel lymph node (NSLN) metastasis in patients with breast cancer (BC) whose axillary lymph nodal status changed from clinically node positive (cN+) to clinically node negative (cN0) after neoadjuvant chemotherapy (NAC). METHODS: We retrospectively analyzed the clinicopathological factors affecting NSLN metastasis in a total of 179 patients with cN+ BC downstaged to cN0 (120 in the training set and 59 in the validation set) who underwent both sentinel lymph node (SLN) biopsy and axillary lymph node dissection following NAC. RESULTS: Among 179 patients enrolled, the overall NSLN metastatic rate was 24.0% (95% confidence interval [CI]: 17.7%-30.3%). In multivariate logistic regression analysis, the number of positive SLNs achieving a pathological complete remission of the breast and clinical node staging was independent predictors of NSLN metastasis. A nomogram was established based on these factors and displayed a good discriminatory capability, with an area under the curve of 0.919 (95% CI: 0.865-0.973) for the training set and 0.900 (95% CI: 0.812-0.988) for the validation set and its clinical utility was confirmed by the decision curve analysis. CONCLUSIONS: The nomogram established showed the ability to predict NSLN metastases in patients with initial cN+ BC that downstaged to cN0 after NAC.

Erratum: Analysis of Tau Protein Expression in Predicting Pathological Complete Response to Neoadjuvant Chemotherapy in Different Molecular Subtypes of Breast Cancer.

[This corrects the article on p. 47 in vol. 23, PMID: 32140269.].

Fast Haar Transforms for Graph Neural Networks.

Graph Neural Networks (GNNs) have become a topic of intense research recently due to their powerful capability in high-dimensional classification and regression tasks for graph-structured data. However, as GNNs typically define the graph convolution by the orthonormal basis for the graph Laplacian, they suffer from high computational cost when the graph size is large. This paper introduces a Haar basis, which is a sparse and localized orthonormal system for a coarse-grained chain on the graph. The graph convolution under Haar basis, called Haar convolution, can be defined accordingly for GNNs. The sparsity and locality of the Haar basis allow Fast Haar Transforms (FHTs) on the graph, by which one then achieves a fast evaluation of Haar convolution between graph data and filters. We conduct experiments on GNNs equipped with Haar convolution, which demonstrates state-of-the-art results on graph-based regression and node classification tasks.

Effect of levocetirizine hydrochloride on the growth of human dermal papilla cells: a preliminary study.

BACKGROUND: To conduct an in vitro investigation into the effect of different concentrations of levocetirizine hydrochloride on the growth of human dermal papilla cells (hDPCs) the underlying mechanisms involved. METHODS: hDPCs were cultured in Dulbecco's Modified Eagle Medium (DMEM) containing different concentrations of levocetirizine hydrochloride for 48 h. The growth of hDPCs was observed by immunofluorescence staining, and the cell proliferation was detected by MTT assay. After the hDPCs were cultured in DMEM containing 1, 10, 100, 1,000, and 10,000 ng/mL levocetirizine hydrochloride for 48 h, the mRNA expressions of cyclooxygenase 2 (COX-2), prostaglandin D2 synthase (PTGDS), prostaglandin E2 (PGE2), prostaglandin F2α (PGF2α), G protein-coupled receptor 44 (GPR44), protein kinase B (AKT), and glycogen synthase kinase 3ß (GSK3ß) were determined by real-time fluorescence-based quantitative polymerase chain reaction (PCR), and the protein expressions of PTGDS, phosphorylated protein kinase B (pAKT), and phosphorylated glycogen synthase kinase 3ß (pGSK3ß) were detected by Western blotting. After the hDPCs were cultured in DMEM containing 1, 10, 100, 1,000, 10,000 ng/mL levocetirizine hydrochloride for 24 h, the secretion levels of prostaglandin D2 (PGD2) and PGD2 receptor (PGD2R) in the culture supernatant were determined by enzyme-linked immunosorbent assay (ELISA). One-way analysis of variance (ANOVA) was performed using SPSS 17.0 software, and the LSD-t test was used for pairwise comparisons. RESULTS: Immunofluorescence staining showed that hDPCs in the 100 ng/mL group grew well, with over 90% confluency. Methyl thiazolyl tetrazolium (MTT) method showed that the proliferation rate of hDPCs significantly differed between different levocetirizine hydrochloride groups and the blank control group (F=42.22, P<0.05), while the proliferation rate was significantly higher in the 100 ng/mL group (115.80%±5.10%) than in the blank control group (100%) (t=28.26, P<0.05). The relative mRNA expressions of COX-2, PGF2a, PTGDS, GPR44, and AKT showed significant differences in different levocetirizine hydrochloride groups (the F values were 1.97, 3.66, 2.17, 2.66, and 7.32, respectively; all P<0.05), whereas the mRNA expressions of PGE2 and GSK3ß showed no significant difference (F=0.87, F=1.19, respectively; both P>0.05). The mRNA expressions of COX-2, PTGDS, and GPR44 in the 100 ng/mL group (0.840.08, 0.810.10, and 0.85±0.09, respectively) were significantly lower than those in the blank control group (t=1.97, t=2.17, and t=2.65, respectively; all P<0.05), whereas the mRNA expressions of PGF2α and AKT in the 100 ng/mL group (1.96±0.25 and 1.74±0.32, respectively) were significantly higher than those in the blank control group (t=3.662 and t=7.325, respectively; both P<0.05). There were significant differences in the levels of PTGDS, pAKT, pGSK3ß, PGD2, and PGD2R proteins between the different levocetirizine hydrochloride groups (the F values were 11.84, 3.89, 4.07, 66.15, and 44.33, respectively). The protein expressions of PTGDS, PGD2, and PGD2R in the 100 ng/mL group (0.32±0.05, 141.62±5.44, and 215.08±9.55, respectively) were significantly lower than those in the blank control group (0.73±0.06, 180.08±6.15, and 273.24±3.18, respectively) (the t values were 5.66, 45.07, and 92.05, respectively; all P<0.05), whereas the protein expressions of pAKT and pGSK3ß in the 100 ng/mL group (0.59±0.05 and 0.46±0.03, respectively) were significantly higher than those in the blank control group (0.46±0.02 and 0.35±0.042, respectively) (t=16.59, t=7.73, respectively; both P<0.05). CONCLUSIONS: Levocetirizine hydrochloride may promote the growth and proliferation of hDPC in vitro by inhibiting the PGD2-GPR44 pathway and activating the AKT signaling pathway.

Analysis of Tau Protein Expression in Predicting Pathological Complete Response to Neoadjuvant Chemotherapy in Different Molecular Subtypes of Breast Cancer.

PURPOSE: Tau is a microtubule-associated protein that can be found in both normal and abnormal breast cells. Whether the expression of Tau protein can predict the response to neoadjuvant chemotherapy (NACT) is still unclear. In this study, we assessed the role of Tau protein expression in predicting a pathological complete response (pCR) to NACT for different subtypes of breast cancer. METHODS: Four hundred and sixty-eight eligible patients were retrospectively recruited in our study. The relationship between clinicopathologic factors, including Tau protein expression, and pCR in different subtypes was evaluated using logistic regression analysis. Correlation between Tau and disease-free survival (DFS) and overall survival (OS) was performed using Kaplan-Meier analysis. RESULTS: The expression of Tau protein was negatively correlated with pCR, especially in triple-negative breast cancer (TNBC). No significant difference was observed in the luminal human epidermal growth factor receptor-2 (HER2)-negative subtype and HER2-positive subtype. Patients with pCR were associated with better DFS and OS (p < 0.05). However, Tau protein expression had no association with either DFS or OS (p > 0.05). CONCLUSION: Tau protein expression can predict pCR before NACT in TNBC, but there was no correlation between Tau expression and DFS or OS.

Multiparametric MRI-based radiomics analysis for prediction of breast cancers insensitive to neoadjuvant chemotherapy.

PURPOSE: To evaluate the value of multiparametric magnetic resonance imaging (MRI) in pretreatment prediction of breast cancers insensitive to neoadjuvant chemotherapy (NAC). METHODS: A total of 125 breast cancer patients (63 in the primary cohort and 62 in the validation cohort) who underwent MRI before receiving NAC were enrolled. All patients received surgical resection, and Miller-Payne grading system was applied to assess the response to NAC. Grade 1-2 cases were classified as insensitive to NAC. We extracted 1941 features in the primary cohort. After feature selection, the optimal feature set was used to construct a radiomic signature using machine learning. We built a combined prediction model incorporating the radiomic signature and independent clinical risk factors selected by multivariable logistic regression. The performance of the combined model was assessed with the results of independent validation. RESULTS: Four features were selected for the construction of the radiomic signature based on the primary cohort. Combining with independent clinical factors, the combined prediction model for identifying the Grade 1-2 group reached a better discrimination power than the radiomic signature, with an area under the receiver operating characteristic curve of 0.935 (95% confidence interval 0.848-1) in the validation cohort, and its clinical utility was confirmed by the decision curve analysis. CONCLUSION: The combined model based on radiomics and clinical variables has potential in predicting drug-insensitive breast cancers.

Mammography-based radiomic analysis for predicting benign BI-RADS category 4 calcifications.

PURPOSE: We developed and validated a radiomic model based on mammography and assessed its value for predicting the pathological diagnosis of Breast Imaging Reporting and Data System (BI-RADS) category 4 calcifications. MATERIALS AND METHODS: Patients with a total of 212 eligible calcifications were recruited (159 cases in the primary cohort and 53 cases in the validation cohort). In total, 8286 radiomic features were extracted from the craniocaudal (CC) and mediolateral oblique (MLO) images. Machine learning was used to select features and build a radiomic signature. The clinical risk factors were selected from the independent clinical factors through logistic regression analyses. The radiomic nomogram incorporated the radiomic signature and an independent clinical risk factor. The diagnostic performance of the radiomic model and the radiologists' empirical prediction model was evaluated by the area under the receiver operating characteristic curve (AUC). The differences between the various AUCs were compared with DeLong's test. RESULTS: Six radiomic features and the menopausal state were included in the radiomic nomogram, which discriminated benign calcifications from malignant calcifications with an AUC of 0.80 in the validation cohort. The difference between the classification results of the radiomic nomogram and that of radiologists was significant (p < 0.05). Particularly for patients with calcifications that are negative on ultrasounds but can be detected by mammography (MG+/US- calcifications), the identification ability of the radiomic nomogram was very strong. CONCLUSIONS: The mammography-based radiomic nomogram is a potential tool to distinguish benign calcifications from malignant calcifications.

Tumor location of the central and nipple portion is associated with impaired survival for women with breast cancer.

BACKGROUND: Tumor location in the breast varies, with the highest frequency in the upper outer quadrant and lowest frequency in the lower inner quadrant. Nevertheless, tumors in the central and nipple portion (TCNP) are poorly studied types of breast cancer; therefore, we aimed to clarify the clinicopathological characteristics and prognostic features of TCNP. METHODS: Using the Surveillance, Epidemiology, and End Results database, we identifed 105,037 patients diagnosed with tumor in the breast peripheral quadrant (TBPQ) (n=97,046) or TCNP (n=7,991). The chi-squared test was used to compare categorical variables across TCNP and TBPQ. Cox proportional hazard models with hazard ratios were applied to estimate the factors associated with prognosis. RESULTS: The median follow-up was over 43 months. Compared with TBPQ, TCNP patients were signifcantly older (age ≥66 years: 40.4% vs 34.1%, P<0.001), with larger tumor sizes (>20 mm size: 46.9% vs 37.3%, P<0.001), higher proportions of TNM stage II-III (18.6% vs 9.9%, P<0.001), and more mastectomies (58.1% vs 37.8%, P<0.001). The breast cancer-specifc survival (BCSS)/overall survival (OS) rate was signifcantly worse for TCNP than for TBPQ. Multivariate Cox analysis showed a higher hazard ratios for TCNP over TBPQ (BCSS: hazard ratios =1.160, P=0.005, 95% CI: 1.046-1.287; OS: hazard ratios =1.301, P<0.001, 95% CI: 1.211-1.398). A subgroup analysis revealed inferior outcomes for TCNP in TNM stage II-III and breast subtype subgroup. Multivariate logistic regression indicated that TCNP was an independent contributing factor to LN metastasis. CONCLUSIONS: TCNP was associated with older age, larger tumor size, higher TNM stage, and lymph node metastasis. Compared with TBPQ, TCNP had adverse impacts on BCSS and OS.

Digital Affine Shear Filter Banks with 2-Layer Structure and Their Applications in Image Processing.

Digital affine shear filter banks with 2-layer structure (DAS-2 filter banks) are constructed and are shown to be with the perfect reconstruction (PR) property. The implementation of digital affine shear transforms using the transition and subdivision operators are given. The redundancy rate analysis shows that our digital affine shear transforms have redundancy rate no more than 8 and it decreases with respect to the number of directional filters. Numerical experiments on image processing demonstrate the advantage of our DAS-2 filter banks over many other state-of-the-art frame-based transforms. The connection between DAS-2 filter banks and affine shear tight frames with 2-layer structure is established. Characterizations and constructions of affine shear tight frames with 2-layer structure are provided.

Quality of life in women with female pattern hair loss and the impact of topical minoxidil treatment on quality of life in these patients.

Female pattern hair loss (FPHL) is the most common hair loss disorder in women and it may impact on the psychological and social activities of patients, thereby reducing their quality of life (QoL). Topical minoxidil has been shown to be effective and safe in the treatment of patients with FPHL. The aim of this study was to assess the QoL of patients with FPHL and investigate whether topical minoxidil solution treatment improves the QoL of these patients. In this study, we enrolled 125 female patients aged 16-72 years to answer visual analog scale (VAS) and dermatology life quality index (DLQI) questionnaires. Of these patients, 31 were recruited for the follow-up study after 12 months of treatment with 2% minoxidil. Each index and the change in QoL prior to and following treatment were statistically analyzed. There was identified to be a correlation between clinical severity and the values of the indices in all patients. There was a statistically significant difference between the VAS and DLQI scores prior to and following treatment with 2% minoxidil. A comparison between the good responders (n=23) and the poor responders (n=8) revealed no significant difference in the improvement of VAS and DLQI scores. The QoL of the patients was severely impaired by FPHL. The DLQI and VAS used in this study were validated as useful indices for the evaluation of QoL due to their high reliability, sensitivity and simplicity. This evaluation is recommended for the management of FPHL treatment. The results of the study demonstrated that topical minoxidil improved the QoL of the patients.