Literature DB >> 22915432

Assessing the stand-alone sensitivity of computer-aided detection with cancer cases from the Digital Mammographic Imaging Screening Trial.

Elodia B Cole1, Zheng Zhang, Helga S Marques, Robert M Nishikawa, R Edward Hendrick, Martin J Yaffe, Wittaya Padungchaichote, Cherie Kuzmiak, Jatuporn Chayakulkheeree, Emily F Conant, Laurie L Fajardo, Janet Baum, Constantine Gatsonis, Etta Pisano.   

Abstract

OBJECTIVE: The purpose of this study was to assess the sensitivities and false-detection rates of two computer-aided detection (CADe) systems when applied to digital or film-screen mammograms in detecting the known breast cancer cases from the Digital Mammographic Imaging Screening Trial (DMIST) breast cancer screening population.
MATERIALS AND METHODS: Available film-screen and digital mammograms of 161 breast cancer cases from DMIST were analyzed by two CADe systems, iCAD Second-Look and R2 ImageChecker. Three experienced breast-imaging radiologists reviewed the CADe marks generated for each available cancer case, recording the number and locations of CADe marks and whether each CADe mark location corresponded with the known location of the cancer.
RESULTS: For the 161 cancer cases included in this study, the sensitivities of the DMIST reader without CAD were 0.43 (69/161, 95% CI 0.35-0.51) for digital and 0.41 (66/161, 0.33-0.49) for film-screen mammography. The sensitivities of iCAD were 0.74 (119/161, 0.66-0.81) for digital and 0.69 (111/161, 0.61-0.76) for film-screen mammography, both significantly higher than the DMIST study sensitivities (p < 0.0001 for both). The average number of false CADe marks per case of iCAD was 2.57 (SD, 1.92) for digital and 3.06(1.72) for film-screen mammography. The sensitivity of R2 was 0.74 (119/161, 0.66-0.81) for digital, and 0.60 (97/161, 0.52-0.68) for film-screen mammography, both significantly higher than the DMIST study sensitivities (p < 0.0001 for both). The average number of false CADe marks per case of R2 was 2.07 (1.57) for digital and 1.52 (1.45) for film-screen mammography.
CONCLUSION: Our results suggest the use of CADe in interpretation of digital and film-screen mammograms could lead to improvements in cancer detection.

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Year:  2012        PMID: 22915432      PMCID: PMC3649852          DOI: 10.2214/AJR.11.7255

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


  21 in total

1.  American College of Radiology Imaging Network digital mammographic imaging screening trial: objectives and methodology.

Authors:  Etta D Pisano; Constantine A Gatsonis; Martin J Yaffe; R Edward Hendrick; Anna N A Tosteson; Dennis G Fryback; Lawrence W Bassett; Janet K Baum; Emily F Conant; Roberta A Jong; Murray Rebner; Carl J D'Orsi
Journal:  Radiology       Date:  2005-06-16       Impact factor: 11.105

2.  Comparison of full-field digital mammography with screen-film mammography for cancer detection: results of 4,945 paired examinations.

Authors:  J M Lewin; R E Hendrick; C J D'Orsi; P K Isaacs; L J Moss; A Karellas; G A Sisney; C C Kuni; G R Cutter
Journal:  Radiology       Date:  2001-03       Impact factor: 11.105

3.  Computer-aided detection (CAD) in mammography: does it help the junior or the senior radiologist?

Authors:  Corinne Balleyguier; Karen Kinkel; Jacques Fermanian; Sebastien Malan; Germaine Djen; Patrice Taourel; Olivier Helenon
Journal:  Eur J Radiol       Date:  2005-04       Impact factor: 3.528

4.  Effect of case selection on the performance of computer-aided detection schemes.

Authors:  R M Nishikawa; M L Giger; K Doi; C E Metz; F F Yin; C J Vyborny; R A Schmidt
Journal:  Med Phys       Date:  1994-02       Impact factor: 4.071

5.  Diagnostic performance of digital versus film mammography for breast-cancer screening.

Authors:  Etta D Pisano; Constantine Gatsonis; Edward Hendrick; Martin Yaffe; Janet K Baum; Suddhasatta Acharyya; Emily F Conant; Laurie L Fajardo; Lawrence Bassett; Carl D'Orsi; Roberta Jong; Murray Rebner
Journal:  N Engl J Med       Date:  2005-09-16       Impact factor: 91.245

6.  Computer-aided detection system applied to full-field digital mammograms.

Authors:  Alfonso Vega Bolivar; Sonia Sánchez Gomez; Paula Merino; Pilar Alonso-Bartolomé; Estrella Ortega Garcia; Pedro Muñoz Cacho; Jeffrey W Hoffmeister
Journal:  Acta Radiol       Date:  2010-10-01       Impact factor: 1.990

7.  Effect of computer-aided detection on mammographic performance: experimental study on readers with different levels of experience.

Authors:  K Hukkinen; T Vehmas; M Pamilo; L Kivisaari
Journal:  Acta Radiol       Date:  2006-04       Impact factor: 1.990

8.  Breast lesion detection and classification: comparison of screen-film mammography and full-field digital mammography with soft-copy reading--observer performance study.

Authors:  Per Skaane; Corinne Balleyguier; Felix Diekmann; Susanne Diekmann; Jean-Charles Piguet; Kari Young; Loren T Niklason
Journal:  Radiology       Date:  2005-08-11       Impact factor: 11.105

9.  Population-based mammography screening: comparison of screen-film and full-field digital mammography with soft-copy reading--Oslo I study.

Authors:  Per Skaane; Kari Young; Arnulf Skjennald
Journal:  Radiology       Date:  2003-10-23       Impact factor: 11.105

10.  Screen-film mammography versus full-field digital mammography with soft-copy reading: randomized trial in a population-based screening program--the Oslo II Study.

Authors:  Per Skaane; Arnulf Skjennald
Journal:  Radiology       Date:  2004-05-20       Impact factor: 11.105

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  5 in total

1.  Using breast radiographers' reports as a second opinion for radiologists' readings of microcalcifications in digital mammography.

Authors:  R Tanaka; M Takamori; Y Uchiyama; R M Nishikawa; J Shiraishi
Journal:  Br J Radiol       Date:  2014-12-23       Impact factor: 3.039

2.  Effect of radiologists' diagnostic work-up volume on interpretive performance.

Authors:  Diana S M Buist; Melissa L Anderson; Robert A Smith; Patricia A Carney; Diana L Miglioretti; Barbara S Monsees; Edward A Sickles; Stephen H Taplin; Berta M Geller; Bonnie C Yankaskas; Tracy L Onega
Journal:  Radiology       Date:  2014-06-24       Impact factor: 11.105

Review 3.  Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.

Authors:  Krzysztof J Geras; Ritse M Mann; Linda Moy
Journal:  Radiology       Date:  2019-09-24       Impact factor: 11.105

4.  Impact of computer-aided detection systems on radiologist accuracy with digital mammography.

Authors:  Elodia B Cole; Zheng Zhang; Helga S Marques; R Edward Hendrick; Martin J Yaffe; Etta D Pisano
Journal:  AJR Am J Roentgenol       Date:  2014-10       Impact factor: 3.959

5.  Palpable Breast Lump Triage by Minimally Trained Operators in Mexico Using Computer-Assisted Diagnosis and Low-Cost Ultrasound.

Authors:  Susan M Love; Wendie A Berg; Christine Podilchuk; Ana Lilia López Aldrete; Aarón Patricio Gaxiola Mascareño; Krishnamohan Pathicherikollamparambil; Ananth Sankarasubramanian; Leah Eshraghi; Richard Mammone
Journal:  J Glob Oncol       Date:  2018-08
  5 in total

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