Fat-enlarged axillary lymph nodes are associated with node-positive breast cancer in obese patients

Lymph Node Adiposity and Metabolic Dysfunction-Associated Steatotic Liver Disease

Objective: Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as the most common chronic liver disease, is soon to be the leading indication for liver transplantation; however, the diagnosis may remain occult for decades. There is a need for biomarkers that identify patients at risk for MASLD and patients at risk for disease progression to optimize patient management and outcomes. Lymph node adiposity (LNA) is a novel marker of adiposity identified within axillary lymph nodes on screening mammography. Recent studies have demonstrated a correlation between LNA and cardiometabolic disease and cardiovascular disease risk. This study aimed to investigate the association between MASLD and LNA to evaluate the potential of mammographic LNA to serve as an imaging biomarker of MASLD. Methods: We identified women with pathology-proven MASLD who had a liver biopsy and a screening mammogram within 12 months of the liver biopsy. This resulted in a sample size of 161 women for final analysis that met the inclusion criteria. We evaluated lymph node adiposity through multiple measurements of the largest axillary lymph node visualized on mammography and correlated LNA with MASLD histology. Statistical analysis using univariable and multivariable logistic regression and odds ratios was performed using R version 4.1.0 (2021), the R Foundation for Statistical Computing Platform. Results: We found a significant association between MASLD and mammographic LNA, defined as lymph node (LN) length > 16 mm (p = 0.0004) that remained significant after adjusting for clinical factors, including body mass index (BMI). We additionally found a significant association between LNA and metabolic dysfunction-associated steatohepatitis (MASH), identified via liver biopsy (p = 0.0048). Conclusions: Mammographic lymph node adiposity may serve as a helpful imaging biomarker of MASLD in women who have an elevated risk for the development of MASH.

Development and Validation of a Nomogram for Axillary Lymph Node Metastasis Risk in Breast Cancer

Purpose: Preoperative assessment of axillary lymph node (ALN) status is essential for breast cancer treatment planning. This study prospectively analyzed risk factors for ALN metastasis by comparing high-resolution computed tomography (HRCT) imaging with pathology and developed a nomogram to aid in diagnosis. Methods: From April 2023 to May 2024, breast cancer patients confirmed by pathology participated in the study. All had chest HRCT before surgery, and ALN samples were anatomically matched to HRCT imaging and pathology. The least absolute shrinkage and selection operator (LASSO) regression helped refine metastasis features, and a nomogram was constructed using the final selected features determined by multivariate logistic regression. The nomogram's performance was evaluated with concordance index (C-index), calibration plot, and decision curve analysis, with internal validation through bootstrapping. Results: A total of 302 ALN from 98 patients were included in this study. The predictors included in the nomogram encompassed the mean CT value, short diameter, border, and shape of ALN, as well as the Ki-67 status and histological grade of the primary tumor. The model exhibited satisfactory discrimination, with a C-index of 0.869 (95% CI: 0.826-0.912) and an AUC of 0.862 (95% CI, 0.815-0.909). The calibration curve demonstrated a high degree of concordance between the predicted and actual probabilities. The decision curve analysis demonstrated that the nomogram was clinically useful when the threshold for intervention was set at the metastasis possibility range of 1% to 86%. Conclusion: The nomogram combined with preoperative pathology and HRCT imaging have the potential to improve the evaluation of ALN status.

Body mass index and altered lipid profile as major risk markers for breast cancer progression: a cross-sectional study of postmenopausal women in Pakistan

BACKGROUND

In Pakistan, the death rate for post-menopausal women with breast cancer is significant due to late detection and delayed referral to proper facilities. There are a few reports on Pakistan's epidemiology and breast cancer risk factors. There are modifiable and non-modifiable risk factors associated with the development of breast carcinoma; of which body mass index (BMI), central obesity, and lipid profile are considered as major risk markers.

METHODS

This was a cross-sectional analytical study. A total of 384 women constituted the present study sample. Purposive sampling was used to collect 192 confirmed new breast cancer cases throughout the study. By using basic random sampling, an equal number of controls were chosen. Studied parameters included age, fasting blood sugar, cholesterol, triglyceride, serum high-density lipoprotein, cholesterol, serum low-density lipoprotein cholesterol, weight, height, BMI, waist circumference, and waist-to-hip ratio. The inclusion criteria of this study were post-menopausal women (45-65 years) in Pakistan. The confirmation of breast carcinoma was done through histopathology. Breast cancer occurrence was taken as a dependent variable, whereas BMI, central obesity, and lipid profile were taken as independent variables.

RESULTS

Studied risk factors (cholesterol, BMI, and central obesity) significantly correlated with breast cancer. Cholesterol has a significantly high positive correlation (0.646) with breast cancer. BMI has a positive significant correlation (0.491) with breast cancer, and central obesity has a low but positive significant correlation (0.266) with breast cancer. Moreover, the binary logistic regression model also showed a significant association between biochemical factors and breast cancer occurrence. Regression analysis depicted a linear relationship between a dependent variable (breast cancer occurrence) and independent variables (central obesity, cholesterol, BMI).

CONCLUSION

Postmenopausal overweight (central obesity), increased BMI and high cholesterol levels are major risk factors for breast cancer. Moreover, high total cholesterol proved to be the most significant risk marker for the occurrence of breast cancer in post-menopausal women of Pakistan.

Automated classification of fat-infiltrated axillary lymph nodes on screening mammograms

OBJECTIVE

Fat-infiltrated axillary lymph nodes (LNs) are unique sites for ectopic fat deposition. Early studies showed a strong correlation between fatty LNs and obesity-related diseases. Confirming this correlation requires large-scale studies, hindered by scarce labeled data. With the long-term goal of developing a rapid and generalizable tool to aid data labeling, we developed an automated deep learning (DL)-based pipeline to classify the status of fatty LNs on screening mammograms.

METHODS

Our internal data set included 886 mammograms from a tertiary academic medical institution, with a binary status of the fat-infiltrated LNs based on the size and morphology of the largest visible axillary LN. A two-stage DL model training and fine-tuning pipeline was developed to classify the fat-infiltrated LN status using the internal training and development data set. The model was evaluated on a held-out internal test set and a subset of the Digital Database for Screening Mammography.

RESULTS

Our model achieved 0.97 (95% CI: 0.94-0.99) accuracy and 1.00 (95% CI: 1.00-1.00) area under the receiver operator characteristic curve on 264 internal testing mammograms, and 0.82 (95% CI: 0.77-0.86) accuracy and 0.87 (95% CI: 0.82-0.91) area under the receiver operator characteristic curve on 70 external testing mammograms.

CONCLUSION

This study confirmed the feasibility of using a DL model for fat-infiltrated LN classification. The model provides a practical tool to identify fatty LNs on mammograms and to allow for future large-scale studies to evaluate the role of fatty LNs as an imaging biomarker of obesity-associated pathologies.

ADVANCES IN KNOWLEDGE

Our study is the first to classify fatty LNs using an automated DL approach.

The prognostic value of the histological shape of tumor negative sentinel nodes in breast cancer

Introduction

Sentinel lymph node (SLN) metastasis is an important predictor of prognosis in breast cancer (BC) patients, guiding treatment decisions. However, patients with the same BC subtype and tumor negative SLN (SLNneg) can have different survival outcomes. We hypothesized that the host anti-tumor immune reaction in SLNneg is important and results in morphometrically measurable changes in SLN size or shape which are related to patient prognosis.

Methods

Surface area, circumference, long axis and short axis were histologically measured in 694 SLNneg from 356 cases of invasive BC and 67 ductal carcinoma in situ cases. The area occupied by fat was categorized as less or more than 50%. The long to short axis (L/S) ratio was calculated. The relationship between SLNneg morphometries and clinicopathological variables like tumor-infiltrating lymphocytes (TILs) within the primary tumor, as well as prognosis at 10 years follow up were analyzed.

Results

The mean SLNneg surface area was 78.7mm2, circumference 40.3mm, long axis 13.1mm, short axis 8.2mm and L/S ratio 1.7. Larger surface area, long axis and short axis, including age >55 years were associated with higher body mass index (BMI) and SLN fat over 50% (p<0.003). In invasive BC, a high SLNneg L/S ratio (≥1.9) was related to poorer disease-free (HR=1.805, 95%CI 1.182-2.755, p=0.006) and overall (HR=2.389, 95%CI 1.481-3.851, p<0.001) survival. A low SLNneg L/S ratio (<1.9) was associated with high TILs in the primary BC (≥10%) (p=0.005). However a high TIL count was not of prognostic relevance.

Conclusions

This is the first study to suggest that morphometric characteristics of axillary SLNneg, like L/S ratio, could be used to predict prognosis in patients with SLNneg invasive BC of all subtypes. The association between low L/S ratio and high TILs suggest that SLN shape is related to immunological functioning of the SLN and could be used in addition to TIL evaluation. Regarding the dubious role of TILs in hormone receptor positive breast cancer, SLNneg morphometry to gain information about host immune status could especially be of benefit in this subtype. Further studies are warranted to better understand the underlying biological mechanisms.

Association between fat-infiltrated axillary lymph nodes on screening mammography and cardiometabolic disease

Objective

Ectopic fat deposition within and around organs is a stronger predictor of cardiometabolic disease status than body mass index (BMI). Fat deposition within the lymphatic system is poorly understood. This study examined the association between the prevalence of cardiometabolic disease and ectopic fat deposition within axillary lymph nodes (LNs) visualized on screening mammograms.

Methods

A cross-sectional study was conducted on 834 women presenting for full-field digital screening mammography. The status of fat-infiltrated LNs was assessed based on the size and morphology of axillary LNs from screening mammograms. The prevalence of cardiometabolic disease was retrieved from the electronic medical records, including type 2 diabetes mellitus (T2DM), hypertension, dyslipidemia, high blood glucose, cardiovascular disease, stroke, and non-alcoholic fatty liver disease.

Results

Fat-infiltrated axillary LNs were associated with a high prevalence of T2DM among all women (adjusted odds ratio: 3.92, 95% CI: [2.40, 6.60], p-value < 0.001) and in subgroups of women with and without obesity. Utilizing the status of fatty LNs improved the classification of T2DM status in addition to age and BMI (1.4% improvement in the area under the receiver operating characteristic curve).

Conclusion

Fat-infiltrated axillary LNs visualized on screening mammograms were associated with the prevalence of T2DM. If further validated, fat-infiltrated axillary LNs may represent a novel imaging biomarker of T2DM in women undergoing screening mammography.

Decrease in the Size of Fat-Enlarged Axillary Lymph Nodes and Serum Lipids after Bariatric Surgery

BACKGROUND

Ectopic fat deposition in obesity is associated with organ dysfunction; however, little is known about fat deposition within the lymphatic system and associated lymphatic dysfunction.

METHODS

One hundred fifty-five women who underwent routine screening mammography before and after a Roux-en-y gastric bypass or a sleeve gastrectomy were retrospectively reviewed and after excluding women without visible nodes both before and after bariatric surgery, 84 patients were included in the final analysis. Axillary lymph node size, patient weight in kilograms, body mass index, and a diagnosis of hypertension, type 2 diabetes, and dyslipidemia were evaluated before and after surgery. Binary linear regression models and Fischer's exact test were used to evaluate the relationship between the size of fat-infiltrated axillary lymph nodes, patient age, change in patient weight, and diagnosis of hypertension, type 2 diabetes, and dyslipidemia.

RESULTS

Fat-infiltrated axillary lymph nodes demonstrated a statistically significant decrease in size after bariatric surgery with a mean decrease of 4.23 mm (95% CI: 3.23 to 5.2, p < 0.001). The resolution of dyslipidemia was associated with a decrease in lymph node size independent of weight loss (p = 0.006).

CONCLUSIONS

Mammographically visualized fat-infiltrated axillary lymph nodes demonstrated a statistically significant decrease in size after bariatric surgery. The decrease in lymph node size was significantly associated with the resolution of dyslipidemia, independent of weight loss, age, and type of surgery.