Literature DB >> 23701102

Accuracy and interpretation time of computer-aided detection among novice and experienced breast MRI readers.

Constance D Lehman1, Jeffrey D Blume, Wendy B DeMartini, Nola M Hylton, Benjamin Herman, Mitchell D Schnall.   

Abstract

OBJECTIVE: The purpose of this study was to compare the diagnostic accuracy and interpretation times of breast MRI with and without use of a computer-aided detection (CAD) system by novice and experienced readers. SUBJECTS AND METHODS: A reader study was undertaken with 20 radiologists, nine experienced and 11 novice. Each radiologist participated in two reading sessions spaced 6 months apart that consisted of 70 cases (27 benign, 43 malignant), read with and without CAD assistance. Sensitivity, specificity, negative predictive value, positive predictive value, and overall accuracy as measured by the area under the receiver operating characteristic curve (AUC) were reported for each radiologist. Accuracy comparisons across use of CAD and experience level were examined. Time to interpret and report on each case was recorded.
RESULTS: CAD improved sensitivity for both experienced (AUC, 0.91 vs 0.84; 95% CI on the difference, 0.04, 0.11) and novice readers (AUC, 0.83 vs 0.77; 95% CI on the difference, 0.01, 0.10). The increase in sensitivity was statistically higher for experienced readers (p = 0.01). Diagnostic accuracy, measured by AUC, for novices without CAD was 0.77, for novices with CAD was 0.79, for experienced readers without CAD was 0.80, and for experienced readers with CAD was 0.83. An upward trend was noticed, but the differences were not statistically significant. There were no significant differences in interpretation times.
CONCLUSION: MRI sensitivity improved with CAD for both experienced readers and novices with no overall increase in time to evaluate cases. However, overall accuracy was not significantly improved. As the use of breast MRI with CAD increases, more attention to the potential contributions of CAD to the diagnostic accuracy of MRI is needed.

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Year:  2013        PMID: 23701102      PMCID: PMC4511702          DOI: 10.2214/AJR.11.8394

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


  25 in total

1.  MRI-detected suspicious breast lesions: predictive values of kinetic features measured by computer-aided evaluation.

Authors:  Lilian C Wang; Wendy B DeMartini; Savannah C Partridge; Sue Peacock; Constance D Lehman
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2.  Statistical comparison of two ROC-curve estimates obtained from partially-paired datasets.

Authors:  C E Metz; B A Herman; C A Roe
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3.  Sample size determination for diagnostic accuracy studies involving binormal ROC curve indices.

Authors:  N A Obuchowski; D K McClish
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4.  MRI detection of distinct incidental cancer in women with primary breast cancer studied in IBMC 6883.

Authors:  Mitchell D Schnall; Jeffery Blume; David A Bluemke; Gia A Deangelis; Nanette Debruhl; Steven Harms; Sylvia H Heywang-Köbrunner; Nola Hylton; Christiane K Kuhl; Etta D Pisano; Petrina Causer; Stuart J Schnitt; Stanley F Smazal; Carol B Stelling; Constance Lehman; Paul T Weatherall; Constantine A Gatsonis
Journal:  J Surg Oncol       Date:  2005-10-01       Impact factor: 3.454

5.  Computing sample size for receiver operating characteristic studies.

Authors:  N A Obuchowski
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6.  Screening women at high risk for breast cancer with mammography and magnetic resonance imaging.

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Authors:  U Fischer; L Kopka; U Brinck; M Korabiowska; A Schauer; E Grabbe
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Authors:  Constance D Lehman; Constantine Gatsonis; Christiane K Kuhl; R Edward Hendrick; Etta D Pisano; Lucy Hanna; Sue Peacock; Stanley F Smazal; Daniel D Maki; Thomas B Julian; Elizabeth R DePeri; David A Bluemke; Mitchell D Schnall
Journal:  N Engl J Med       Date:  2007-03-28       Impact factor: 91.245

10.  Can breast MRI computer-aided detection (CAD) improve radiologist accuracy for lesions detected at MRI screening and recommended for biopsy in a high-risk population?

Authors:  T Arazi-Kleinman; P A Causer; R A Jong; K Hill; E Warner
Journal:  Clin Radiol       Date:  2009-10-21       Impact factor: 2.350

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  13 in total

1.  Evaluation of Kinetic Entropy of Breast Masses Initially Found on MRI using Whole-lesion Curve Distribution Data: Comparison with the Standard Kinetic Analysis.

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Journal:  Eur Radiol       Date:  2015-02-20       Impact factor: 5.315

2.  Breast cancer molecular subtype classifier that incorporates MRI features.

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3.  A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women.

Authors:  Jacob E D Levman; Cristina Gallego-Ortiz; Ellen Warner; Petrina Causer; Anne L Martel
Journal:  J Digit Imaging       Date:  2016-02       Impact factor: 4.056

4.  Computer-aided evaluation as an adjunct to revised BI-RADS Atlas: improvement in positive predictive value at screening breast MRI.

Authors:  Hye Mi Gweon; Nariya Cho; Mirinae Seo; A Jung Chu; Woo Kyung Moon
Journal:  Eur Radiol       Date:  2014-05-02       Impact factor: 5.315

5.  Fully automated detection of breast cancer in screening MRI using convolutional neural networks.

Authors:  Mehmet Ufuk Dalmış; Suzan Vreemann; Thijs Kooi; Ritse M Mann; Nico Karssemeijer; Albert Gubern-Mérida
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6.  Should abbreviated breast MRI be compliant with American College of Radiology requirements for MRI accreditation?

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7.  Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging.

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Review 8.  Abbreviated Magnetic Resonance Imaging for Breast Cancer Screening: Concept, Early Results, and Considerations.

Authors:  Eun Sook Ko; Elizabeth A Morris
Journal:  Korean J Radiol       Date:  2019-04       Impact factor: 3.500

Review 9.  Advances in managing breast cancer: a clinical update.

Authors:  Ayca Gucalp; Gaorav P Gupta; Melissa L Pilewskie; Elizabeth J Sutton; Larry Norton
Journal:  F1000Prime Rep       Date:  2014-08-01

10.  Features of Undiagnosed Breast Cancers at Screening Breast MR Imaging and Potential Utility of Computer-Aided Evaluation.

Authors:  Mirinae Seo; Nariya Cho; Min Sun Bae; Hye Ryoung Koo; Won Hwa Kim; Su Hyun Lee; Ajung Chu
Journal:  Korean J Radiol       Date:  2016-01-06       Impact factor: 3.500

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