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Cancer cases from ACRIN digital mammographic imaging screening trial: radiologist analysis with use of a logistic regression model.

Publication ,  Journal Article
Pisano, ED; Acharyya, S; Cole, EB; Marques, HS; Yaffe, MJ; Blevins, M; Conant, EF; Hendrick, RE; Baum, JK; Fajardo, LL; Jong, RA; Koomen, MA ...
Published in: Radiology
August 2009

PURPOSE: To determine which factors contributed to the Digital Mammographic Imaging Screening Trial (DMIST) cancer detection results. MATERIALS AND METHODS: This project was HIPAA compliant and institutional review board approved. Seven radiologist readers reviewed the film hard-copy (screen-film) and digital mammograms in DMIST cancer cases and assessed the factors that contributed to lesion visibility on both types of images. Two multinomial logistic regression models were used to analyze the combined and condensed visibility ratings assigned by the readers to the paired digital and screen-film images. RESULTS: Readers most frequently attributed differences in DMIST cancer visibility to variations in image contrast--not differences in positioning or compression--between digital and screen-film mammography. The odds of a cancer being more visible on a digital mammogram--rather than being equally visible on digital and screen-film mammograms--were significantly greater for women with dense breasts than for women with nondense breasts, even with the data adjusted for patient age, lesion type, and mammography system (odds ratio, 2.28; P < .0001). The odds of a cancer being more visible at digital mammography--rather than being equally visible at digital and screen-film mammography--were significantly greater for lesions imaged with the General Electric digital mammography system than for lesions imaged with the Fischer (P = .0070) and Fuji (P = .0070) devices. CONCLUSION: The significantly better diagnostic accuracy of digital mammography, as compared with screen-film mammography, in women with dense breasts demonstrated in the DMIST was most likely attributable to differences in image contrast, which were most likely due to the inherent system performance improvements that are available with digital mammography. The authors conclude that the DMIST results were attributable primarily to differences in the display and acquisition characteristics of the mammography devices rather than to reader variability.

Duke Scholars

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

August 2009

Volume

252

Issue

2

Start / End Page

348 / 357

Location

United States

Related Subject Headings

  • Young Adult
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Regression Analysis
  • Radiographic Image Enhancement
  • Observer Variation
  • Nuclear Medicine & Medical Imaging
  • Middle Aged
  • Mass Screening
  • Mammography
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Pisano, E. D., Acharyya, S., Cole, E. B., Marques, H. S., Yaffe, M. J., Blevins, M., … Gatsonis, C. (2009). Cancer cases from ACRIN digital mammographic imaging screening trial: radiologist analysis with use of a logistic regression model. Radiology, 252(2), 348–357. https://doi.org/10.1148/radiol.2522081457
Pisano, Etta D., Suddhasatta Acharyya, Elodia B. Cole, Helga S. Marques, Martin J. Yaffe, Meredith Blevins, Emily F. Conant, et al. “Cancer cases from ACRIN digital mammographic imaging screening trial: radiologist analysis with use of a logistic regression model.Radiology 252, no. 2 (August 2009): 348–57. https://doi.org/10.1148/radiol.2522081457.
Pisano ED, Acharyya S, Cole EB, Marques HS, Yaffe MJ, Blevins M, et al. Cancer cases from ACRIN digital mammographic imaging screening trial: radiologist analysis with use of a logistic regression model. Radiology. 2009 Aug;252(2):348–57.
Pisano, Etta D., et al. “Cancer cases from ACRIN digital mammographic imaging screening trial: radiologist analysis with use of a logistic regression model.Radiology, vol. 252, no. 2, Aug. 2009, pp. 348–57. Pubmed, doi:10.1148/radiol.2522081457.
Pisano ED, Acharyya S, Cole EB, Marques HS, Yaffe MJ, Blevins M, Conant EF, Hendrick RE, Baum JK, Fajardo LL, Jong RA, Koomen MA, Kuzmiak CM, Lee Y, Pavic D, Yoon SC, Padungchaichote W, Gatsonis C. Cancer cases from ACRIN digital mammographic imaging screening trial: radiologist analysis with use of a logistic regression model. Radiology. 2009 Aug;252(2):348–357.

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

August 2009

Volume

252

Issue

2

Start / End Page

348 / 357

Location

United States

Related Subject Headings

  • Young Adult
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Regression Analysis
  • Radiographic Image Enhancement
  • Observer Variation
  • Nuclear Medicine & Medical Imaging
  • Middle Aged
  • Mass Screening
  • Mammography