Literature DB >> 19620460

Digital breast tomosynthesis: observer performance study.

David Gur1, Gordon S Abrams, Denise M Chough, Marie A Ganott, Christiane M Hakim, Ronald L Perrin, Grace Y Rathfon, Jules H Sumkin, Margarita L Zuley, Andriy I Bandos.   

Abstract

OBJECTIVE: The purpose of this study was to compare in a retrospective observer study the diagnostic performance of full-field digital mammography (FFDM) with that of digital breast tomosynthesis.
MATERIALS AND METHODS: Eight experienced radiologists interpreted images from 125 selected examinations, 35 with verified findings of cancer and 90 with no finding of cancer. The four display conditions included FFDM alone, 11 low-dose projections, reconstructed digital breast tomosynthesis images, and a combined display mode of FFDM and digital breast tomosynthesis images. Observers rated examinations using the screening BI-RADS rating scale and the free-response receiver operating characteristic paradigm. Observer performance levels were measured as the proportion of examinations prompting recall of patients for further diagnostic evaluation. The results were presented in terms of true-positive fraction and false-positive fraction. Performance levels were compared among the acquisitions and reading modes. Time to view and interpret an examination also was evaluated.
RESULTS: Use of the combination of digital breast tomosynthesis and FFDM was associated with 30% reduction in recall rate for cancer-free examinations that would have led to recall if FFDM had been used alone (p < 0.0001 for the participating radiologists, p = 0.047 in the context of a generalized population of radiologists). Use of digital breast tomosynthesis alone also tended to reduce recall rates, an average of 10%, although the observed decrease was not statistically significant (p = 0.09 for the participating radiologists). There was no convincing evidence that use of digital breast tomosynthesis alone or in combination with FFDM results in a substantial improvement in sensitivity.
CONCLUSION: Use of digital breast tomosynthesis for breast imaging may result in a substantial decrease in recall rate.

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Year:  2009        PMID: 19620460     DOI: 10.2214/AJR.08.2031

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  106 in total

1.  Digital breast tomosynthesis: computer-aided detection of clustered microcalcifications on planar projection images.

Authors:  Ravi K Samala; Heang-Ping Chan; Yao Lu; Lubomir M Hadjiiski; Jun Wei; Mark A Helvie
Journal:  Phys Med Biol       Date:  2014-11-13       Impact factor: 3.609

2.  Computer-aided detection of clustered microcalcifications in digital breast tomosynthesis: a 3D approach.

Authors:  Berkman Sahiner; Heang-Ping Chan; Lubomir M Hadjiiski; Mark A Helvie; Jun Wei; Chuan Zhou; Yao Lu
Journal:  Med Phys       Date:  2012-01       Impact factor: 4.071

3.  Image quality of microcalcifications in digital breast tomosynthesis: effects of projection-view distributions.

Authors:  Yao Lu; Heang-Ping Chan; Jun Wei; Mitch Goodsitt; Paul L Carson; Lubomir Hadjiiski; Andrea Schmitz; Jeffrey W Eberhard; Bernhard E H Claus
Journal:  Med Phys       Date:  2011-10       Impact factor: 4.071

4.  Digital breast tomosynthesis is comparable to mammographic spot views for mass characterization.

Authors:  Mitra Noroozian; Lubomir Hadjiiski; Sahand Rahnama-Moghadam; Katherine A Klein; Deborah O Jeffries; Renee W Pinsky; Heang-Ping Chan; Paul L Carson; Mark A Helvie; Marilyn A Roubidoux
Journal:  Radiology       Date:  2011-10-13       Impact factor: 11.105

5.  Characterization of masses in digital breast tomosynthesis: comparison of machine learning in projection views and reconstructed slices.

Authors:  Heang-Ping Chan; Yi-Ta Wu; Berkman Sahiner; Jun Wei; Mark A Helvie; Yiheng Zhang; Richard H Moore; Daniel B Kopans; Lubomir Hadjiiski; Ted Way
Journal:  Med Phys       Date:  2010-07       Impact factor: 4.071

Review 6.  [Digital breast tomosynthesis : technical principles, current clinical relevance and future perspectives].

Authors:  K Hellerhoff
Journal:  Radiologe       Date:  2010-11       Impact factor: 0.635

7.  Evaluating imaging and computer-aided detection and diagnosis devices at the FDA.

Authors:  Brandon D Gallas; Heang-Ping Chan; Carl J D'Orsi; Lori E Dodd; Maryellen L Giger; David Gur; Elizabeth A Krupinski; Charles E Metz; Kyle J Myers; Nancy A Obuchowski; Berkman Sahiner; Alicia Y Toledano; Margarita L Zuley
Journal:  Acad Radiol       Date:  2012-02-03       Impact factor: 3.173

8.  Comparison study of reconstruction algorithms for prototype digital breast tomosynthesis using various breast phantoms.

Authors:  Ye-seul Kim; Hye-suk Park; Haeng-Hwa Lee; Young-Wook Choi; Jae-Gu Choi; Hak Hee Kim; Hee-Joung Kim
Journal:  Radiol Med       Date:  2015-09-18       Impact factor: 3.469

9.  Full Field Digital Mammography (FFDM) versus CMOS Technology, Specimen Radiography System (SRS) and Tomosynthesis (DBT) - Which System Can Optimise Surgical Therapy?

Authors:  R Schulz-Wendtland; G Dilbat; M Bani; P A Fasching; K Heusinger; M P Lux; C R Loehberg; B Brehm; M Hammon; M Saake; P Dankerl; S M Jud; C Rauh; C M Bayer; M W Beckmann; M Uder; M Meier-Meitinger
Journal:  Geburtshilfe Frauenheilkd       Date:  2013-05       Impact factor: 2.915

10.  Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography.

Authors:  Kayla Mendel; Hui Li; Deepa Sheth; Maryellen Giger
Journal:  Acad Radiol       Date:  2018-08-01       Impact factor: 3.173

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