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Article ; Online: Molecular Subtypes of Breast Cancer: A Review for Breast Radiologists.

Johnson, Karen S / Conant, Emily F / Soo, Mary Scott

Journal of breast imaging

2024 Volume 3, Issue 1, Page(s) 12–24

Abstract: Gene expression profiling has reshaped our understanding of breast cancer by identifying four molecular subtypes: (1) luminal A, (2) luminal B, (3) human epidermal growth factor receptor 2 (HER2)-enriched, and (4) basal-like, which have critical ... ...

Abstract	Gene expression profiling has reshaped our understanding of breast cancer by identifying four molecular subtypes: (1) luminal A, (2) luminal B, (3) human epidermal growth factor receptor 2 (HER2)-enriched, and (4) basal-like, which have critical differences in incidence, response to treatment, disease progression, survival, and imaging features. Luminal tumors are most common (60%-70%), characterized by estrogen receptor (ER) expression. Luminal A tumors have the best prognosis of all subtypes, whereas patients with luminal B tumors have significantly shorter overall and disease-free survival. Distinguishing between these tumors is important because luminal B tumors require more aggressive treatment. Both commonly present as irregular masses without associated calcifications at mammography; however, luminal B tumors more commonly demonstrate axillary involvement at diagnosis. HER2-enriched tumors are characterized by overexpression of the HER2 oncogene and low-to-absent ER expression. HER2+ disease carries a poor prognosis, but the development of anti-HER2 therapies has greatly improved outcomes for women with HER2+ breast cancer. HER2+ tumors most commonly present as spiculated masses with pleomorphic calcifications or as calcifications alone. Basal-like cancers (15% of all invasive breast cancers) predominate among "triple negative" cancers, which lack ER, progesterone receptor (PR), and HER2 expression. Basal-like cancers are frequently high-grade, large at diagnosis, with high rates of recurrence. Although imaging commonly reveals irregular masses with ill-defined or spiculated margins, some circumscribed basal-like tumors can be mistaken for benign lesions. Incorporating biomarker data (histologic grade, ER/PR/HER2 status, and multigene assays) into classic anatomic tumor, node, metastasis (TNM) staging can better inform clinical management of this heterogeneous disease.
Language	English
Publishing date	2024-02-29
Publishing country	United States
Document type	Journal Article
ISSN	2631-6129
ISSN (online)	2631-6129
DOI	10.1093/jbi/wbaa110
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Article ; Online: Opinions on the Assessment of Breast Density Among Members of the Society of Breast Imaging.

Zhang, Zi / Conant, Emily F / Zuckerman, Samantha

Journal of breast imaging

2024 Volume 4, Issue 5, Page(s) 480–487

Abstract: Objective: Dense breast decreases the sensitivity and specificity of mammography and is associated with an increased risk of breast cancer. We conducted a survey to assess the opinions of Society of Breast Imaging (SBI) members regarding density ... ...

Abstract	Objective: Dense breast decreases the sensitivity and specificity of mammography and is associated with an increased risk of breast cancer. We conducted a survey to assess the opinions of Society of Breast Imaging (SBI) members regarding density assessment. Methods: An online survey was sent to SBI members twice in September 2020. The survey included active members who were practicing radiologists, residents, and fellows. Mammograms from three patients were presented for density assessment based on routine clinical practice and BI-RADS fourth and fifth editions. Dense breasts were defined as heterogeneously or extremely dense. Frequencies were calculated for each survey response. Pearson's correlation coefficient was used to evaluate the correlation of density assessments by different definitions. Results: The survey response rate was 12.4% (357/2875). For density assessments, the Pearson correlation coefficients between routine clinical practice and BI-RADS fourth edition were 0.05, 0.43, and 0.12 for patients 1, 2, and 3, respectively; these increased to 0.65, 0.65, and 0.66 between routine clinical practice and BI-RADS fifth edition for patients 1, 2, and 3, respectively. For future density grading, 79.0% (282/357) of respondents thought it should reflect both potential for masking and overall dense tissue for risk assessment. Additionally, 47.1% (168/357) of respondents thought quantitative methods were of use. Conclusion: Density assessment varied based on routine clinical practice and BI-RADS fourth and fifth editions. Most breast radiologists agreed that density assessment should capture both masking and overall density. Moreover, almost half of respondents believed computer or artificial intelligence-assisted quantitative methods may help refine density assessment.
MeSH term(s)	Humans ; Female ; Breast Density ; Mammography/methods ; Breast Neoplasms/diagnosis ; Artificial Intelligence ; Breast/diagnostic imaging
Language	English
Publishing date	2024-02-28
Publishing country	United States
Document type	Journal Article
ISSN	2631-6129
ISSN (online)	2631-6129
DOI	10.1093/jbi/wbac047
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Article ; Online: Digital Breast Tomosynthesis: What Have We Learned?

Butler, Reni / Conant, Emily F / Philpotts, Liane

Journal of breast imaging

2024 Volume 1, Issue 1, Page(s) 9–22

Abstract: Digital breast tomosynthesis (DBT) is increasingly recognized as a superior breast imaging technology compared with 2D digital mammography (DM) alone. Accumulating data confirm increased sensitivity and specificity in the screening setting, resulting in ... ...

Abstract	Digital breast tomosynthesis (DBT) is increasingly recognized as a superior breast imaging technology compared with 2D digital mammography (DM) alone. Accumulating data confirm increased sensitivity and specificity in the screening setting, resulting in higher cancer detection rates and lower abnormal interpretation (recall) rates. In the diagnostic environment, DBT simplifies the diagnostic work-up and improves diagnostic accuracy. Initial concern about increased radiation exposure resulting from the DBT acquisition added onto a 2D mammogram has been largely alleviated by the development of synthesized 2D mammography (SM). Continued research is underway to reduce artifacts associated with SM, and improve its comparability to DM. Breast cancers detected with DBT are most often small invasive carcinomas with a preponderance for grade 1 histology and luminal A molecular characteristics. Recent data suggest that higher-grade cancers are also more often node negative when detected with DBT. A meta-analysis of early single-institution studies of the effect of DBT on interval cancers has shown a modest decrease when multiple data sets are combined. Because of the greater conspicuity of lesions on DBT imaging, detection of subtle architectural distortion is increased. Such findings include both spiculated invasive carcinomas and benign etiologies such as radial scars. The diagnostic evaluation of architectural distortion seen only with DBT can pose a challenge. When no sonographic correlate can be identified, DBT-guided biopsy and/or localization capability is essential. Initial experience with DBT-guided procedures suggests that DBT biopsy equipment may improve the efficiency of percutaneous breast biopsy with less radiation.
Language	English
Publishing date	2024-02-29
Publishing country	United States
Document type	Journal Article
ISSN	2631-6129
ISSN (online)	2631-6129
DOI	10.1093/jbi/wby008
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Article ; Online: Can AI Reduce the Harms of Screening Mammography?

McDonald, Elizabeth S / Conant, Emily F

Radiology. Artificial intelligence

2023 Volume 5, Issue 6, Page(s) e230304

Language	English
Publishing date	2023-10-25
Publishing country	United States
Document type	Journal Article
ISSN	2638-6100
ISSN (online)	2638-6100
DOI	10.1148/ryai.230304
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Book: Case review breast imaging

Conant, Emily F. / Brennecke, Cecilia M.

(Case review series)

2006

Title variant	Breast imaging
Author's details	Emily Conant ; Cecilia Brennecke
Series title	Case review series
Keywords	Mammography ; Breast Diseases / diagnosis ; Breast/Imaging
Subject code	618.190754
Language	English
Size	XVII, 311 S. : zahlr. Ill.
Publisher	Mosby Elsevier
Publishing place	Philadelphia, Pa
Publishing country	United States
Document type	Book
HBZ-ID	HT014538410
ISBN	978-0-323-01746-6 ; 0-323-01746-0
Database	Catalogue ZB MED Medicine, Health

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2006 A 3683	order for loan	Magazin

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Article ; Online: Impact of super-resolution and image acquisition on the detection of calcifications in digital breast tomosynthesis.

Barufaldi, Bruno / Acciavatti, Raymond J / Conant, Emily F / Maidment, Andrew D A

European radiology

2023 Volume 34, Issue 1, Page(s) 193–203

Abstract: Objectives: A virtual clinical trial (VCT) method is proposed to determine the limit of calcification detection in tomosynthesis.: Methods: Breast anatomy, focal findings, image acquisition, and interpretation (n = 14 readers) were simulated using ... ...

Abstract	Objectives: A virtual clinical trial (VCT) method is proposed to determine the limit of calcification detection in tomosynthesis. Methods: Breast anatomy, focal findings, image acquisition, and interpretation (n = 14 readers) were simulated using screening data (n = 660 patients). Calcifications (0.2-0.4 mm Results: Source motion and reconstructed voxel size demonstrated significant changes in the performance of imaging systems. Acquisition geometries that use 70 µm reconstruction voxel size and step-and-shoot motion significantly improved calcification detection. Comparing 70 with 100 µm reconstructed voxel size for step-and-shoot, the ΔAUC was 0.0558 (0.0647) and d' ratio was 1.27 (1.29) for 140 µm (70 µm) detector element size. Comparing step-and-shoot with a continuous motion for a 70 µm reconstructed voxel size, the ΔAUC was 0.0863 (0.0434) and the d' ratio was 1.40 (1.19) for 140 µm (70 µm) detector element. Small detector element sizes (e.g., 70 µm) did not significantly improve detection. The SNR results with the BR3D phantom show that calcification detection is dependent upon reconstructed voxel size and detector element size, supporting VCT results with comparable agreement (ratios: d' = 1.16 ± 0.11, SNR = 1.34 ± 0.13). Conclusion: DBT acquisition geometries that use super-resolution (smaller reconstructed voxels than the detector element size) combined with step-and-shoot motion have the potential to improve the detection of calcifications. Clinical relevance: Calcifications may not always be discernable in tomosynthesis because of differences in acquisition and reconstruction methods. VCTs can identify strategies to optimize acquisition and reconstruction parameters for calcification detection in tomosynthesis, most notably through super-resolution in the reconstruction. Key points: • Super-resolution improves calcification detection and SNR in tomosynthesis; specifically, with the use of smaller reconstruction voxels. • Calcification detection using step-and-shoot motion is superior to that using continuous tube motion. • A detector element size of 70 µm does not provide better detection than 140 µm for small calcifications at the threshold of detectability.
MeSH term(s)	Humans ; Female ; Mammography/methods ; Breast ; Phantoms, Imaging ; Calcinosis/diagnostic imaging ; Breast Neoplasms/diagnostic imaging ; Algorithms
Language	English
Publishing date	2023-08-12
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1085366-2
ISSN	1432-1084 ; 0938-7994 ; 1613-3749
ISSN (online)	1432-1084
ISSN	0938-7994 ; 1613-3749
DOI	10.1007/s00330-023-10103-6
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Zs.A 3300: Show issues

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Article ; Online: Beyond the

Gastounioti, Aimilia / Conant, Emily F

AJR. American journal of roentgenology

2020 Volume 216, Issue 6, Page(s) 1436

MeSH term(s)	Algorithms ; Artificial Intelligence ; Early Detection of Cancer ; Humans ; Mammography
Language	English
Publishing date	2020-12-09
Publishing country	United States
Document type	Journal Article ; Comment
ZDB-ID	82076-3
ISSN	1546-3141 ; 0361-803X ; 0092-5381
ISSN (online)	1546-3141
ISSN	0361-803X ; 0092-5381
DOI	10.2214/AJR.20.25196
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Article ; Online: Risk Assessment in Population-Based Breast Cancer Screening.

Eriksson, Mikael / Conant, Emily F / Kontos, Despina / Hall, Per

Journal of clinical oncology : official journal of the American Society of Clinical Oncology

2022 Volume 40, Issue 20, Page(s) 2279–2280

MeSH term(s)	Breast Neoplasms/diagnosis ; Breast Neoplasms/epidemiology ; Breast Neoplasms/prevention & control ; Early Detection of Cancer ; Female ; Humans ; Mammography ; Mass Screening ; Risk Assessment
Language	English
Publishing date	2022-04-22
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	604914-x
ISSN	1527-7755 ; 0732-183X
ISSN (online)	1527-7755
ISSN	0732-183X
DOI	10.1200/JCO.21.02827
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Zs.A 1847: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 650: Show issues

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Article ; Online: Mammographic Breast Density: Current Assessment Methods, Clinical Implications, and Future Directions.

Edmonds, Christine E / O'Brien, Sophia R / Conant, Emily F

Seminars in ultrasound, CT, and MR

2022 Volume 44, Issue 1, Page(s) 35–45

Abstract: Mammographic breast density is widely accepted as an independent risk factor for the development of breast cancer. In addition, because dense breast tissue may mask breast malignancies, breast density is inversely related to the sensitivity of screening ... ...

Abstract	Mammographic breast density is widely accepted as an independent risk factor for the development of breast cancer. In addition, because dense breast tissue may mask breast malignancies, breast density is inversely related to the sensitivity of screening mammography. Given the risks associated with breast density, as well as ongoing efforts to stratify individual risk and personalize breast cancer screening and prevention, numerous studies have sought to better understand the factors that impact breast density, and to develop and implement reproducible, quantitative methods to assess mammographic density. Breast density assessments have been incorporated into risk assessment models to improve risk stratification. Recently, novel techniques for analyzing mammographic parenchymal complexity, or texture, have been explored as potential means of refining mammographic tissue-based risk assessment beyond breast density.
MeSH term(s)	Humans ; Female ; Breast Density ; Breast Neoplasms/diagnostic imaging ; Mammography/methods ; Early Detection of Cancer/methods ; Risk Factors
Language	English
Publishing date	2022-11-04
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	1353113-x
ISSN	1558-5034 ; 0887-2171
ISSN (online)	1558-5034
ISSN	0887-2171
DOI	10.1053/j.sult.2022.11.001
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Article: A Clinical Risk Model for Personalized Screening and Prevention of Breast Cancer.

Eriksson, Mikael / Czene, Kamila / Vachon, Celine / Conant, Emily F / Hall, Per

Cancers

2023 Volume 15, Issue 12

Abstract: Background: Image-derived artificial intelligence (AI) risk models have shown promise in identifying high-risk women in the short term. The long-term performance of image-derived risk models expanded with clinical factors has not been investigated.: ... ...

Abstract	Background: Image-derived artificial intelligence (AI) risk models have shown promise in identifying high-risk women in the short term. The long-term performance of image-derived risk models expanded with clinical factors has not been investigated. Methods: We performed a case-cohort study of 8110 women aged 40-74 randomly selected from a Swedish mammography screening cohort initiated in 2010 together with 1661 incident BCs diagnosed before January 2022. The imaging-only AI risk model extracted mammographic features and age at screening. Additional lifestyle/familial risk factors were incorporated into the lifestyle/familial-expanded AI model. Absolute risks were calculated using the two models and the clinical Tyrer-Cuzick v8 model. Age-adjusted model performances were compared across the 10-year follow-up. Results: The AUCs of the lifestyle/familial-expanded AI risk model ranged from 0.75 (95%CI: 0.70-0.80) to 0.68 (95%CI: 0.66-0.69) 1-10 years after study entry. Corresponding AUCs were 0.72 (95%CI: 0.66-0.78) to 0.65 (95%CI: 0.63-0.66) for the imaging-only model and 0.62 (95%CI: 0.55-0.68) to 0.60 (95%CI: 0.58-0.61) for Tyrer-Cuzick v8. The increased performances were observed in multiple risk subgroups and cancer subtypes. Among the 5% of women at highest risk, the PPV was 5.8% using the lifestyle/familial-expanded model compared with 5.3% using the imaging-only model, Conclusions: The lifestyle/familial-expanded AI risk model showed higher performance for both long-term and short-term risk assessment compared with imaging-only and Tyrer-Cuzick models.
Language	English
Publishing date	2023-06-19
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527080-1
ISSN	2072-6694
ISSN	2072-6694
DOI	10.3390/cancers15123246
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