Gender and cytoarchitecture differences: Functional connectivity of the hippocampal sub-regions.

Introduction: The hippocampus plays a significant role in learning, memory encoding, and spatial navigation. Typically, the hippocampus is investigated as a whole region of interest. However, recent work has developed fully detailed atlases based on cytoarchitecture properties of brain regions, and the hippocampus has been sub-divided into seven sub-areas that have structural differences in terms of distinct numbers of cells, neurons, and other structural and chemical properties. Moreover, gender differences are of increasing concern in neuroscience research. Several neuroscience studies have found structural and functional variations between the brain regions of females and males, and the hippocampus is one of these regions. Aim: The aim of this study to explore whether the cytoarchitecturally distinct sub-regions of the hippocampus have varying patterns of functional connectivity with different networks of the brain and how these functional connections differ in terms of gender differences. Method: This study investigated 200 healthy participants using seed-based resting-state functional magnetic resonance imaging (rsfMRI). The primary aim of this study was to explore the resting connectivity and gender distinctions associated with specific sub-regions of the hippocampus and their relationship with major functional brain networks. Results: The findings revealed that the majority of the seven hippocampal sub-regions displayed functional connections with key brain networks, and distinct patterns of functional connectivity were observed between the hippocampal sub-regions and various functional networks within the brain. Notably, the default and visual networks exhibited the most consistent functional connections. Additionally, gender-based analysis highlighted evident functional resemblances and disparities, particularly concerning the anterior section of the hippocampus. Conclusion: This study highlighted the functional connectivity patterns and involvement of the hippocampal sub-regions in major brain functional networks, indicating that the hippocampus should be investigated as a region of multiple distinct functions and should always be examined as sub-regions of interest. The results also revealed clear gender differences in functional connectivity.

Increased Risk of Breast Fibroadenomas Among Obese and Postmenopausal Women With Uterine Fibroids.

Introduction Uterine fibroids and breast fibroadenomas are common female benign neoplasms that are similarly derived from a single clonal origin and are modulated by estradiol concentration in blood. However, the association between these neoplasms has not yet been explored. Hence, this study aims to investigate the relationship between uterine fibroids and breast fibroadenomas.  Methods A total of 199 women (cases: 72 women with uterine fibroids, control: 127 women without uterine fibroids) were included in this study. Ultrasound was used to screen for uterine fibroids, and both ultrasound and biopsy were utilized to diagnose breast fibroadenomas. Logistic regression analysis was used to investigate the association between uterine fibroids and breast fibroadenomas and the factors associated with the relationship. Results Women with uterine fibroids have more than two times higher odds of having breast fibroadenomas among older women (p=0.03), more than twofold increased odds of breast fibroadenomas among obese females (p=0.05), and higher odds of having breast fibroadenomas among postmenopausal transition participant groups (OR=9.6; 95% CI 1.98-30.14; p-value=0.005).  Conclusion The association between uterine fibroids and breast fibroadenomas is significantly pronounced among older, obese, and postmenopausal women. This relationship might be driven by the indirect stimulation of estrogen hormone receptors via adipose tissue or other lifestyle as well as genetic factors. Therefore, further larger prospective studies considering these factors are needed to replicate the current findings.

Clinicopathologic breast cancer characteristics: predictions using global textural features of the ipsilateral breast mammogram.

Radiomic features from mammograms have been shown to predict breast cancer (BC) risk; however, their contribution to BC characteristics has not yet been explored. This study included 184 women with BC between January 2012 and April 2017. A set of 33 global radiomic features were extracted from the ipsilateral breast mammogram. Associations between radiomic features and BC characteristics were investigated by univariate logistic regression analysis, and receiver-operating characteristic curve analysis was employed to evaluate the predictive performance of radiomic features. Histogram-based features (mean, 70th percentile, and 30th percentile) weakly differentiated progesterone status and tumor size (AUC range: 0.627-0.652, p ≤ 0.007). One gray level run length matrix (GLRLM)-based feature achieved an AUC of 0.68 in discriminating lymph-node status, and the fractal dimension achieved an AUC of 0.65 in predicting tumor size. After stratifying by age at BC diagnosis and baseline percent density (PD), the average predictive performance of the abovementioned features improved from 0.652 to 0.707 for baseline PD adjustment, and from 0.652 to 0.674 for age at BC diagnosis. Higher predictive performances were found for GLRLM-based features in predicting lymph-node status among younger women with high baseline PD (AUC range: 0.710-0.863), and for fractal features in predicting tumor size among patients with low PD (AUC: 0.704). Global radiomic features from the ipsilateral breast mammogram can predict lymph-node status and tumor size among certain categories of women and should be considered as a non-invasive tool for clinical decision-making in BC-affected women and for forecasting disease progression.

Mammographic density changes following BC treatment.

BACKGROUND: Mammographic density (MD) reduction is associated with lower risk of breast cancer (BC) recurrence and may be used as a marker of treatment outcome; however, trends in MD following BC therapies and the factors associated with such trends are poorly understood. The aim of this study was to investigate MD changes following BC treatment and the factors associated with these changes. METHODS: A total of 226 BC-affected patients who received BC treatments were examined. MD was assessed by the Laboratory for individualized Radiodensity Assessment (LIBRA) software. A Wilcoxon ranked signed test was used to investigate the differences in MD before and after treatment and median independent test to assess the associated factors. RESULTS: Significant differences in MD between baseline and follow-up mammograms were observed for all MD measures: percent density (p ≤ 0.005), dense area (p ≤ 0.004), and nondense area (p ≤ 0.02). After adjustment, these differences were more pronounced among younger at BC diagnosis (p ≤ 0.001), premenopausal (p ≤ 0.003), and obese women (p ≤ 0.05). Changes in MD were evident regardless of the treatment regimen. MD reduction was observed among patients with high baseline MD (p < 0.001), younger at BC diagnosis (p ≤ 0.04), premenopausal (p < 0.001), and normal body mass index (p = 0.04). Patients who experienced an increase in nondense area had high percent density at baseline (p ≤ 0.001). CONCLUSION: Two different MD changes were observed over time: MD increase and decrease. Baseline MD, menopausal status, age at BC diagnosis, and body mass index influenced these changes.

Is mammographic density a marker of breast cancer phenotypes?

PURPOSE: To investigate the association between mammographic density (MD) phenotypes and both clinicopathologic features of breast cancer (BC) and tumor location. METHODS: MD was measured for 297 BC-affected females using qualitative (visual method) and quantitative (fully automated area-based method) approaches. Radiologists' description, visible external markers, and surgical scar were used to establish the location of tumors. Binary logistic regression models were used to assess the association between MD phenotypes and BC clinicopathologic features. RESULTS: Categorical and numerical MD measures showed no association with clinicopathologic features of BC (p > 0.05). Participants with higher BI-RADS scores [(51-75% glandular) and (> 75% glandular)] (p < 0.001), and percent density (PD) categories [PD (21-49%) and PD ≥ 50%] (p = 0.01) were more likely to have tumors emanating from dense areas. Additionally, tumors were commonly found in dense regions of the breast among patients with higher medians of PD (p = 0.001), dense area (DA) (p = 0.02), and lower medians of non-dense area (NDA) (p < 0.001). Adjusted logistic regression models showed that high BI-RADS density (> 75% glandular) has an almost fivefold increased odds of tumors developing within dense areas (OR 4.99, 95% CI 0.93-25.9; p = 0.05. PD (OR 1.02, 95% CI 1-1.03, p = 0.002) and NDA (OR 0.99, 95% CI 0.991-0.997, p < 0.001) had very small effect on tumor location. Compared to tumors within non-dense areas, tumors in dense areas tended to exhibit human epidermal growth factor receptor 2 positive (p = 0.05) and carcinoma in situ (p = 0.01) characteristics. CONCLUSION: MD shows no significant association with clinicopathologic features of BC. However, BC was more likely to originate from dense tissue, with tumors in dense regions having human epidermal growth receptor 2 positive and carcinoma in situ characteristics.

Are mammographic density phenotypes associated with breast cancer treatment response and clinical outcomes? A systematic review and meta-analysis.

Mammographic density (MD) increases breast cancer (BC) risk, however, its association with patient outcomes is unclear. We examined the association of baseline MD (BMD), and MD reduction (MDR) following BC treatment with patient outcomes. Six databases (CINAHL, Scopus, PubMed, Web of Science, MEDLINE, and Embase) were used to identify relevant articles. The PRISMA strategy was used to extract relevant details. Study quality and risk of bias were assessed using the "Quality In Prognosis Studies" (QUIPS) tool. A Meta-analysis and pooled risk estimates were performed. Results showed that BMD is associated with contralateral breast cancer (CBC) risk (HR = 1.9; 95%CI: 1.3-3.0, p = 0.0007), recurrence (HR = 2.0; 95%CI: 1.0-4.0, p = 0.04), and mortality (HR = 1.4; 95%CI: 1.1-1.9, p = 0.003). No association was found between BMD and prognosis (HR = 3.2; 95%CI: 0.9-11.2, p = 0.06). Data on risk estimates (95%CI) from BMD for survival [RR: 1.75; 0.99-3.1 to 2.4; 1.4-4.1], ipsilateral BC [HR: 1; 0.6-1.6 to 3; 1.2-7.5], and treatment response (OR, 1.8; 0.98-3.3) are limited. MDR showed no association with mortality (HR = 0.5; 95%CI: 0.2-1.2, p = 0.13). MDR is associated with a reduced risk of recurrence [HR/RR: 0.35; 0.17-0.68 to 1.33; 0.67-2.65)], however data on MDR and outcomes such as mortality [HR/RR: 0.5; 0.27-0.93 to 0.59; 0.22-0.88], and CBC risk [RR/HR: 0.53; 0.24-0.84 to 1.3; 0.6-2.7] are limited. Evidence, although sparse, demonstrates that high BMD is associated with an increased risk of recurrence, CBC, and mortality. Conversely, MDR is associated with a reduced risk of BC recurrence, CBC, and BC-related mortality.