Try a new search

Format these results:

Searched for:

person:gaoy02

in-biosketch:true

Total Results:

50


Advances in Abbreviated Breast MRI and Ultrafast Imaging

Patel, Shalin; Heacock, Laura; Gao, Yiming; Elias, Kristin; Moy, Linda; Heller, Samantha
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. Sequences selected for abbreviated MRI protocols allow for preserved accuracy in breast cancer detection and characterization. Novel techniques such as ultrafast imaging are being used to provide kinetic information from early post-contrast imaging.
PMID: 35523528
ISSN: 1558-4658
CID: 5213942

Multiple Bilateral Circumscribed Masses at Screening Breast Ultrasound: Outcomes of New or Enlarging Masses at Follow-Up

Wolfson, Stacey; Heller, Samantha L; Gao, Yiming
PMID: 34549605
ISSN: 1546-3141
CID: 5171812

Non-BRCA Early-Onset Breast Cancer in Young Women

Gao, Yiming; Samreen, Naziya; Heller, Samantha L
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. Further contributing to the higher number of early-onset breast cancers is pregnancy-associated breast cancer (PABC), which is attributed to persistent increases in maternal age over time. Although guidelines for screening of patients who carry a BRCA1 or BRCA2 gene mutation are well established, this population comprises only a fraction of those with early-onset breast cancer. A lack of screening in most young patients precludes timely diagnosis, underscoring the importance of early education and awareness. The disproportionate disease burden in young women of certain racial and ethnic groups, which is further exacerbated by socioeconomic disparity in health care, results in worse outcomes. An invited commentary by Monticciolo is available online. ©RSNA, 2022.
PMID: 34990317
ISSN: 1527-1323
CID: 5107282

Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams

Shen, Yiqiu; Shamout, Farah E; Oliver, Jamie R; Witowski, Jan; Kannan, Kawshik; Park, Jungkyu; Wu, Nan; Huddleston, Connor; Wolfson, Stacey; Millet, Alexandra; Ehrenpreis, Robin; Awal, Divya; Tyma, Cathy; Samreen, Naziya; Gao, Yiming; Chhor, Chloe; Gandhi, Stacey; Lee, Cindy; Kumari-Subaiya, Sheila; Leonard, Cindy; Mohammed, Reyhan; Moczulski, Christopher; Altabet, Jaime; Babb, James; Lewin, Alana; Reig, Beatriu; Moy, Linda; Heacock, Laura; Geras, Krzysztof J
Though consistently shown to detect mammographically occult cancers, breast ultrasound has been noted to have high false-positive rates. In this work, we present an AI system that achieves radiologist-level accuracy in identifying breast cancer in ultrasound images. Developed on 288,767 exams, consisting of 5,442,907 B-mode and Color Doppler images, the AI achieves an area under the receiver operating characteristic curve (AUROC) of 0.976 on a test set consisting of 44,755 exams. In a retrospective reader study, the AI achieves a higher AUROC than the average of ten board-certified breast radiologists (AUROC: 0.962 AI, 0.924 ± 0.02 radiologists). With the help of the AI, radiologists decrease their false positive rates by 37.3% and reduce requested biopsies by 27.8%, while maintaining the same level of sensitivity. This highlights the potential of AI in improving the accuracy, consistency, and efficiency of breast ultrasound diagnosis.
PMCID:8463596
PMID: 34561440
ISSN: 2041-1723
CID: 5039442

Digital Mammography Is Similar to Screen-Film Mammography for Women with Personal History of Breast Cancer [Comment]

Moy, Linda; Gao, Yiming
PMID: 34003061
ISSN: 1527-1315
CID: 4878682

Breast MRI for Evaluation of Response to Neoadjuvant Therapy

Reig, Beatriu; Lewin, Alana A; Du, Linda; Heacock, Laura; Toth, Hildegard K; Heller, Samantha L; Gao, Yiming; Moy, Linda
Neoadjuvant therapy is increasingly being used to treat early-stage triple-negative and human epidermal growth factor 2-overexpressing breast cancers, as well as locally advanced and inflammatory breast cancers. The rationales for neoadjuvant therapy are to shrink tumor size and potentially decrease the extent of surgery, to serve as an in vivo test of response to therapy, and to reveal prognostic information for the patient. MRI is the most accurate modality to demonstrate response to therapy and to help ensure accurate presurgical planning. Changes in lesion diameter, volume, and enhancement are used to predict complete response, partial response, or nonresponse to therapy. However, residual disease may be overestimated or underestimated at MRI. Fibrosis, necrotic tumors, and residual benign masses may be causes of overestimation of residual disease. Nonmass lesions, invasive lobular carcinoma, hormone receptor-positive tumors, nonconcentric shrinkage patterns, the use of antiangiogenic therapy, and late-enhancing foci may be causes of underestimation of residual disease. In patients with known axillary lymph node metastasis, neoadjuvant therapy may be followed by targeted axillary dissection to avoid the potential morbidity associated with an axillary lymph node dissection. Diffusion-weighted imaging, radiomics, machine learning, and deep learning methods are under investigation to improve MRI accuracy in predicting treatment response.©RSNA, 2021.
PMID: 33939542
ISSN: 1527-1323
CID: 4858892

Supplemental MRI in Extremely Dense Breasts: Sharp Reduction in False-Positive Rate in the Second Screening Round of the DENSE Trial [Comment]

Moy, Linda; Gao, Yiming
PMID: 33729010
ISSN: 1527-1315
CID: 4823502

Comparison of Narrow-angle and Wide-angle Digital Breast Tomosynthesis Systems in Clinical Practice

Winter, Andrea M.; Moy, Linda; Gao, Yiming; Bennett, Debbie L.
Digital breast tomosynthesis (DBT) is a pseudo 3D mammography imaging technique that has become widespread since gaining Food and Drug Administration approval in 2011. With this technology, a variable number of tomosynthesis projection images are obtained over an angular range between 15° and 50° for currently available clinical DBT systems. The angular range impacts various aspects of clinical imaging, such as radiation dose, scan time, and image quality, including visualization of calcifications, masses, and architectural distortion. This review presents an overview of the differences between narrow- and wide-angle DBT systems, with an emphasis on their applications in clinical practice. Comparison examples of patients imaged on both narrow- and wide-angle DBT systems illustrate these differences. Understanding the potential variable appearance of imaging findings with narrow- and wide-angle DBT systems is important for radiologists, particularly when comparison images have been obtained on a different DBT system. Furthermore, knowledge about the comparative strengths and limitations of DBT systems is needed for appropriate equipment selection.
SCOPUS:85104839970
ISSN: 2631-6110
CID: 4895712

Ductal Carcinoma in Situ and Progression to Invasive Cancer: A Review of the Evidence

Heller, Samantha L.; Plaunova, Anastasia; Gao, Yiming
Ductal carcinoma in situ (DCIS), breast cancer confined to the milk ducts, is a heterogeneous entity. The question of how and when a case of DCIS will extend beyond the ducts to become invasive breast cancer has implications for both patient prognosis and optimal treatment approaches. The natural history of DCIS has been explored through a variety of methods, from mouse models to biopsy specimen reviews to population-based screening data to modeling studies. This article will review the available evidence regarding progression pathways and will also summarize current trials designed to assess DCIS progression.
SCOPUS:85104834046
ISSN: 2631-6110
CID: 4895692

Digital Breast Tomosynthesis: Update on Technology, Evidence, and Clinical Practice

Gao, Yiming; Moy, Linda; Heller, Samantha L
Digital breast tomosynthesis (DBT) has been widely adopted in breast imaging in both screening and diagnostic settings. The benefits of DBT are well established. Compared with two-dimensional digital mammography (DM), DBT preferentially increases detection of invasive cancers without increased detection of in-situ cancers, maximizing identification of biologically significant disease, while mitigating overdiagnosis. The higher sensitivity of DBT for architectural distortion allows increased diagnosis of invasive cancers overall and particularly improves the visibility of invasive lobular cancers. Implementation of DBT has decreased the number of recalls for false-positive findings at screening, contributing to improved specificity at diagnostic evaluation. Integration of DBT in diagnostic examinations has also resulted in an increased percentage of biopsies with positive results, improving diagnostic confidence. Although individual DBT examinations have a longer interpretation time compared with that for DM, DBT has streamlined the diagnostic workflow and minimized the need for short-term follow-up examinations, redistributing much-needed time resources to screening. Yet DBT has limitations. Although improvements in cancer detection and recall rates are seen for patients in a large spectrum of age groups and breast density categories, these benefits are minimal in women with extremely dense breast tissue, and the extent of these benefits may vary by practice environment and by geographic location. Although DBT allows detection of more invasive cancers than does DM, its incremental yield is lower than that of US and MRI. Current understanding of the biologic profile of DBT-detected cancers is limited. Whether DBT improves breast cancer-specific mortality remains a key question that requires further investigation. ©RSNA, 2021.
PMID: 33544665
ISSN: 1527-1323
CID: 4777152