Establishing a Cohort and a Biorepository to Identify Biomarkers for Early Detection of Lung Cancer: The Nashville Lung Cancer Screening Trial Cohort.

Rationale: A prospective longitudinal cohort of individuals at high risk of developing lung cancer was established to build a biorepository of carefully annotated biological specimens and low-dose computed tomography (LDCT) chest images for derivation and validation of candidate biomarkers for early detection of lung cancer.Objectives: The goal of this study is to characterize individuals with high risk for lung cancer, accumulating valuable biospecimens and LDCT chest scans longitudinally over 5 years.Methods: Participants 55-80 years of age with a 5-year estimated risk of developing lung cancer >1.5% were recruited and enrolled from clinics at the Vanderbilt University Medical Center, Veteran Affairs Medical Center, and Meharry Medical Center. Individual demographic characteristics were assessed via questionnaire at baseline. Participants underwent an LDCT scan, spirometry, sputum cytology, and research bronchoscopy at the time of enrollment. Participants will be followed yearly for 5 years. Positive LDCT scans are followed-up according to standard of care. The clinical, imaging, and biospecimen data are collected prospectively and stored in a biorepository. Participants are offered smoking cessation counseling at each study visit.Results: A total of 480 participants were enrolled at study baseline and consented to sharing their data and biospecimens for research. Participants are followed with yearly clinic visits to collect imaging data and biospecimens. To date, a total of 19 cancers (13 adenocarcinomas, four squamous cell carcinomas, one large cell neuroendocrine, and one small-cell lung cancer) have been identified.Conclusions: We established a unique prospective cohort of individuals at high risk for lung cancer, enrolled at three institutions, for whom full clinical data, well-annotated LDCT scans, and biospecimens are being collected longitudinally. This repository will allow for the derivation and independent validation of clinical, imaging, and molecular biomarkers of risk for diagnosis of lung cancer.Clinical trial registered with ClinicalTrials.gov (NCT01475500).

Evaluation of Quantra Hologic Volumetric Computerized Breast Density Software in Comparison With Manual Interpretation in a Diverse Population.

OBJECTIVE: Increased mammographic breast density is a well-established risk factor for breast cancer development, regardless of age or ethnic background. The current gold standard for categorizing breast density consists of a radiologist estimation of percent density according to the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) criteria. This study compares paired qualitative interpretations of breast density on digital mammograms with quantitative measurement of density using Hologic's Food and Drug Administration-approved R2 Quantra volumetric breast density assessment tool. Our goal was to find the best cutoff value of Quantra-calculated breast density for stratifying patients accurately into high-risk and low-risk breast density categories. METHODS: Screening digital mammograms from 385 subjects, aged 18 to 64 years, were evaluated. These mammograms were interpreted by a radiologist using the ACR's BI-RADS density method, and had quantitative density measured using the R2 Quantra breast density assessment tool. The appropriate cutoff for breast density-based risk stratification using Quantra software was calculated using manually determined BI-RADS scores as a gold standard, in which scores of D3/D4 denoted high-risk densities and D1/D2 denoted low-risk densities. RESULTS: The best cutoff value for risk stratification using Quantra-calculated breast density was found to be 14.0%, yielding a sensitivity of 65%, specificity of 77%, and positive and negative predictive values of 75% and 69%, respectively. Under bootstrap analysis, the best cutoff value had a mean ± SD of 13.70% ± 0.89%. CONCLUSIONS: Our study is the first to publish on a North American population that assesses the accuracy of the R2 Quantra system at breast density stratification. Quantitative breast density measures will improve accuracy and reliability of density determination, assisting future researchers to accurately calculate breast cancer risks associated with density increase.

Increased vitamin D and calcium intake associated with reduced mammographic breast density among premenopausal women.

Vitamin D has been identified as a weak protective factor for postmenopausal breast cancer (relative risk, ~0.9), whereas high breast density has been identified as a strong risk factor (relative risk, ~4-6). To test the hypothesis that there is an association between vitamin D intake, but not circulating vitamin D levels, and mammographic breast density among women in our study, we conducted a cross-sectional study of 165 screening mammography patients at Nashville General Hospital's Breast Health Center, a public facility serving medically indigent and underserved women. Dietary and total (dietary plus supplements) vitamin D and calcium intakes were estimated by the Harvard African American Food Frequency Questionnaire, and blood samples were analyzed for 25-hydroxyvitamin D. Average percent breast density for the left and right breasts combined was estimated from digitized films using an interactive thresholding method available through Cumulus software. After statistical adjustment for age, race, and body mass index, the results revealed that there were significant trends of decreasing breast density with increasing vitamin D and calcium intake among premenopausal but not among postmenopausal women. There was no association between serum vitamin D and breast density in premenopausal or postmenopausal women. Confirmation of our findings in larger studies may assist in clarifying the role of vitamin D in breast density.

Type 2 diabetes and mammographic breast density among underserved women.

PURPOSE: We conducted a study of women recruited at Meharry Medical College, a historically black medical school, to investigate the relationship between diabetes and mammographic breast density. METHODS: A total of 476 women completed in-person interviews, body measurements, and full-field digital mammograms on a Hologic mammography unit from December 2011 to February 2014. Average percent breast density for the left and right breasts combined was estimated using Quantra, an automated algorithm for volumetric assessment of breast tissue. The prevalence of type 2 diabetes was determined by self-report. RESULTS: After adjustment for confounding variables, the mean percent breast density among premenopausal women with type 2 diabetes [[Formula: see text] 13.8 %, 95 % confidence interval (CI) 11.6-15.9] was nonsignificantly lower than that of women without type 2 diabetes ([Formula: see text] 15.9 %, 95 % CI 15.0-16.8) (p = 0.07); however, there was no association among postmenopausal women. The effect of type 2 diabetes in severely obese women (BMI ≥ 35) appeared to differ by menopausal status with a reduction in mean percent breast density in premenopausal women, but an increase in mean percent breast density in postmenopausal women which could have been due to chance. CONCLUSIONS: Confirmation of our findings in larger studies may assist in clarifying the role of the insulin signaling breast cancer pathway in women with high breast density.

Pulmonary imaging during pregnancy.

The diagnosis of pulmonary disorders associated with pregnancy is complicated by concerns about maternal/fetal radiation exposure, administration of contrast media, and medicolegal issues. This article reviews diagnostic imaging modalities, radiation exposure policy statements and provides a brief review of radiographic findings in selected pulmonary disorders associated with pregnancy. Clinicians should familiarize themselves with the benefit/risk of imaging modalities. Institution-specific imaging algorithms that minimize maternal/fetal radiation exposure are recommended. Institutional system-wide protocols would minimize confusion among healthcare providers.

The "Got D'ViBE?" study: an inter-institutional project assessing vitamin D and mammographic breast density.

A multi-institutional collaboration was forged to implement a study of the relationship between Vitamin D and breast density among medically underserved women. This effort resulted in techniques to measure vitamin D levels, breast density, and sunlight exposure. Outcomes from this collaboration may provide insight to researchers conducting similar investigations.