Literature DB >> 22523324

Undiagnosed breast cancer at MR imaging: analysis of causes.

Emmanuelle Bouic Pages1, Ingrid Millet, Denis Hoa, Fernanda Curros Doyon, Patrice Taourel.   

Abstract

PURPOSE: To retrospectively review the causes of false-negative results on prior magnetic resonance (MR) imaging studies in patients who developed breast cancer as revealed on a follow-up MR imaging study and to determine the presumptive causes of these false-negative findings.
MATERIALS AND METHODS: Fifty-eight pairs of MR imaging studies from one institution were assessed, consisting of a prior study without a diagnosis of cancer and a diagnostic study with subsequent findings of 60 cancers in 58 women at MR imaging (mean interval between prior and diagnostic MR examinations, 13.8 months). Two radiologists reviewed in consensus, in a nonblinded fashion, each pair of MR studies, comparing the diagnostic and the prior MR imaging studies to evaluate the rate of false-negative findings. The prospective reports were then analyzed to classify false-negatives findings in breast enhancement of breast cancers not identified at the time of imaging, potentially misinterpreted, and mismanaged. False-negative results on prior MR studies were retrospectively reassessed to identify possibly reasons why cancers had been not recognized, potentially misinterpreted, or mismanaged.
RESULTS: Twenty-eight (47% [95% confidence interval {CI}: 34%, 59%]) of the 60 cancers were retrospectively diagnosed as Breast Imaging Reporting and Data System grade 3, 4, or 5 lesions. Analysis of the prospective reports showed that six lesions (10% [95% CI: 2%, 18%]) had been not identified at the time of diagnosis, 15 lesions (25% [95% CI: 14%, 36%]) were potentially misinterpreted, and seven lesions (12% [95% CI: 3%, 20%]) were mismanaged. The main causes of misinterpretation were smooth margins of a mass (n=4), stability in size (n=3), and location of a nonmass in a postsurgical area (n=5). Mismanagement was mainly due to inadequate correlations between MR imaging and ultrasonographic (US) features, with inaccurate sampling with US guidance in five cases.
CONCLUSION: In patients with breast cancer seen at MR imaging, retrospective evaluation of the prior MR imaging studies showed potential observer error in 47% of cases, resulting more from misinterpretation than from nonrecognition or mismanagement of cancers. © RSNA, 2012.

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Year:  2012        PMID: 22523324     DOI: 10.1148/radiol.12111917

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  12 in total

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

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Journal:  J Med Imaging (Bellingham)       Date:  2018-01-11

2.  A modified source-detector configuration for the discrimination between normal and diseased human breast based on the continuous-wave diffuse optical imaging approach: a simulation study.

Authors:  Shimaa Mahdy; Omnia Hamdy; Mohammed A Hassan; Mohamed A A Eldosoky
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4.  Estimation of T2* Relaxation Time of Breast Cancer: Correlation with Clinical, Imaging and Pathological Features.

Authors:  Mirinae Seo; Jung Kyu Ryu; Geon-Ho Jahng; Yu-Mee Sohn; Sun Jung Rhee; Jang-Hoon Oh; Kyu-Yeoun Won
Journal:  Korean J Radiol       Date:  2017-01-05       Impact factor: 3.500

5.  Tensor based multichannel reconstruction for breast tumours identification from DCE-MRIs.

Authors:  X-X Yin; S Hadjiloucas; J-H Chen; Y Zhang; J-L Wu; M-Y Su
Journal:  PLoS One       Date:  2017-03-10       Impact factor: 3.240

6.  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

7.  The Spatial Relationship of Malignant and Benign Breast Lesions with Respect to the Fat-Gland Interface on Magnetic Resonance Imaging.

Authors:  Won Hwa Kim; MuLan Li; Wonshik Han; Han Suk Ryu; Woo Kyung Moon
Journal:  Sci Rep       Date:  2016-12-14       Impact factor: 4.379

8.  Large Non-enhancing Breast Cancer on Breast Magnetic Resonance Imaging: A Case Report.

Authors:  Johannes Peters; Wei Che Tsai; Gudrun Peters
Journal:  Cureus       Date:  2018-03-15

9.  The frequency of missed breast cancers in women participating in a high-risk MRI screening program.

Authors:  S Vreemann; A Gubern-Merida; S Lardenoije; P Bult; N Karssemeijer; K Pinker; R M Mann
Journal:  Breast Cancer Res Treat       Date:  2018-01-31       Impact factor: 4.872

10.  Automated Detection and Segmentation of Nonmass-Enhancing Breast Tumors with Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Authors:  Katja Pinker; Anke Meyer-Baese; Ignacio Alvarez Illan; Javier Ramirez; J M Gorriz; Maria Adele Marino; Daly Avendano; Thomas Helbich; Pascal Baltzer
Journal:  Contrast Media Mol Imaging       Date:  2018-10-24       Impact factor: 3.161

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