Publications by authors named "Samantha Heller"

: To help consumers make healthier choices, the US Food and Drug Administration (FDA) has been charged with developing a front-of-package label (FOPL) to appear on US packaged foods and beverages. One option being explored is the use of "high-in" FOPLs for added sugar, sodium, and saturated fat using a threshold of ≥20% of the recommended daily value (%DV) per portion/serving size to define "high-in". While research has addressed what FOPL designs are most effective at visually communicating "high-in", less attention has been paid to the nutrient profile model (NPM) used to decide which products should receive these labels.

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Objective: Healthy food retail programmes (HFRP) in the USA generally aim to increase healthy foods access to improve diet quality and health, yet the impact is mixed. These programmes primarily target adults, even though adolescents frequently and independently visit stores to purchase snacks. This study's aims are to explore successes and challenges of implementing HFRP (Aim 1) and examine how HFRP can be tailored to adolescents (Aim 2).

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Current breast cancer screening relies on mammography, digital breast tomosynthesis and breast ultrasound. In select populations, breast MRI is also of great utility. However, multiple factors limit widespread use of breast MRI for screening.

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Breast cancer screening has been highly successful in women in reducing mortality through early detection. In comparison, clinical detection of breast cancer remains the norm in men, and delay in diagnosis is reflected by a persistent survival disparity compared to women despite advances in modern therapy. Male breast cancer presents an interesting dilemma.

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Lobular neoplasia (LN) is a histopathologic entity that encompasses both lobular carcinoma in situ (LCIS) and atypical lobular hyperplasia (ALH). Management of LN is known to be variable and institutionally dependent. The variability in approach after a diagnosis of LN at percutaneous breast biopsy derives in part from heterogeneity in the literature, resulting in a range of reported upgrade rates to malignancy after initial identification at percutaneous biopsy, and also from historical shifts in understanding of the natural history of LN.

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Objective: To test the performance of a novel machine learning-based breast density tool. The tool utilizes a convolutional neural network to predict the BI-RADS based density assessment of a study. The clinical density assessments of 33,000 mammographic examinations (164,000 images) from one academic medical center (Site A) were used for training.

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Breast cancer is the most common cancer in women, with the incidence rising substantially with age. Older women are a vulnerable population at increased risk of developing and dying from breast cancer. However, women aged 75 years and older were excluded from all randomized controlled screening trials, so the best available data regarding screening benefits and risks in this age group are from observational studies and modeling predictions.

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Women who survived childhood cancers or cancers at a young age are at high risk for breast cancer later in life. The accentuated risk is notable among those treated at a young age with a high radiation dose but also extends to survivors treated with therapies other than or in addition to radiation therapy. The predisposing risk factors are complex.

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Introduction: Women with neurofibromatosis type 1 (NF1) have up to a 5-fold increased risk for breast cancer before age 50 and a 3.5-fold increased risk of breast cancer overall. The purpose of our study was to assess breast cancer screening utilization and outcomes in this population.

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Biopsy-proven ductal carcinoma in situ (DCIS) lesions are often upgraded to invasive cancer at surgery. Therefore, accurate prediction of the likelihood of invasion is helpful for surgical planning, including the need for sentinel lymph node biopsy (SLNB). The purpose of the present study was to investigate whether kinetic features of clinically available ultrafast MRI (UF-MRI) can predict upgrade of biopsy-proven DCIS to invasive cancer at surgical excision.

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The use of digital breast tomosynthesis (DBT) in breast cancer screening has become widely accepted, facilitating increased cancer detection and lower recall rates compared with those achieved by using full-field digital mammography (DM). However, the use of DBT, as compared with DM, raises new challenges, including a larger number of acquired images and thus longer interpretation times. While most current artificial intelligence (AI) applications are developed for DM, there are multiple potential opportunities for AI to augment the benefits of DBT.

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Health disparities in Asian women are complex and multifactorial. Screening attendance is low among Asian women, regardless of nativity or acculturation, and breast cancer detection has decreased by more than half in this population during the COVID-19 pandemic. The follow-up rate after abnormal screening results is similarly poor among Asian women compared with that among other groups, often resulting in a delay of cancer diagnosis.

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Abbreviated breast MRI is an emerging technique that is being incorporated into clinical practice for breast cancer imaging and screening. Conventional breast MRI includes barriers such as high examination cost and lengthy examination times which make its use in the screening setting challenging. Abbreviated MRI aims to address these pitfalls by reducing overall examination time and increasing accessibility to MRI while preserving diagnostic accuracy.

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The incidence of breast cancer in younger women is rising. Although early-onset breast cancer is highly associated with biologically aggressive tumors such as triple-negative and human epidermal growth factor 2 (HER2)-positive cancers, the more recent increase is disproportionately driven by an increase in the incidence of luminal cancer. In particular, the increase in de novo stage IV disease and the inherent age-based poorer survival rate among younger women with even early-stage luminal cancers suggest underlying distinct biologic characteristics that are not well understood.

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Breast cancer screening recommendations for transgender and gender nonconforming individuals are based on the sex assigned at birth, risk factors, and use of exogenous hormones. Insufficient evidence exists to determine whether transgender people undergoing hormone therapy have an overall lower, average, or higher risk of developing breast cancer compared to birth-sex controls. Furthermore, there are no longitudinal studies evaluating the efficacy of breast cancer screening in the transgender population.

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