Literature DB >> 33446565

Diffusion-weighted Imaging Allows for Downgrading MR BI-RADS 4 Lesions in Contrast-enhanced MRI of the Breast to Avoid Unnecessary Biopsy.

Paola Clauser1, Barbara Krug2, Hubert Bickel1, Matthias Dietzel3, Katja Pinker4, Victor-Frederic Neuhaus2, Maria Adele Marino5, Marco Moschetta6, Nicoletta Troiano6, Thomas H Helbich1, Pascal A T Baltzer7.   

Abstract

PURPOSE: Diffusion-weighted imaging with the calculation of an apparent diffusion coefficient (ADC) has been proposed as a quantitative biomarker on contrast-enhanced MRI (CE-MRI) of the breast. There is a need to approve a generalizable ADC cutoff. The purpose of this study was to evaluate whether a predefined ADC cutoff allows downgrading of BI-RADS 4 lesions on CE-MRI, avoiding unnecessary biopsies. EXPERIMENTAL
DESIGN: This was a retrospective, multicentric, cross-sectional study. Data from five centers were pooled on the individual lesion level. Eligible patients had a BI-RADS 4 rating on CE-MRI. For each center, two breast radiologists evaluated the images. Data on lesion morphology (mass, non-mass), size, and ADC were collected. Histology was the standard of reference. A previously suggested ADC cutoff (≥1.5 × 10-3 mm2/second) was applied. A negative likelihood ratio of 0.1 or lower was considered as a rule-out criterion for breast cancer. Diagnostic performance indices were calculated by ROC analysis.
RESULTS: There were 657 female patients (mean age, 42; SD, 14.1) with 696 BI-RADS 4 lesions included. Disease prevalence was 59.5% (414/696). The area under the ROC curve was 0.784. Applying the investigated ADC cutoff, sensitivity was 96.6% (400/414). The potential reduction of unnecessary biopsies was 32.6% (92/282).
CONCLUSIONS: An ADC cutoff of ≥1.5 × 10-3 mm2/second allows downgrading of lesions classified as BI-RADS 4 on breast CE-MRI. One-third of unnecessary biopsies could thus be avoided. ©2021 American Association for Cancer Research.

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Year:  2021        PMID: 33446565      PMCID: PMC8406278          DOI: 10.1158/1078-0432.CCR-20-3037

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  39 in total

1.  Apparent diffusion coefficient and beyond: what diffusion MR imaging can tell us about tissue structure.

Authors:  Denis Le Bihan
Journal:  Radiology       Date:  2013-08       Impact factor: 11.105

2.  Utility of Breast MRI for Further Evaluation of Equivocal Findings on Digital Breast Tomosynthesis.

Authors:  Bethany L Niell; Kandarp Bhatt; Pragya Dang; Kathryn Humphrey
Journal:  AJR Am J Roentgenol       Date:  2018-09-12       Impact factor: 3.959

3.  Combined contrast-enhanced magnetic resonance and diffusion-weighted imaging reading adapted to the "Breast Imaging Reporting and Data System" for multiparametric 3-T imaging of breast lesions.

Authors:  K Pinker; H Bickel; T H Helbich; S Gruber; P Dubsky; U Pluschnig; M Rudas; Z Bago-Horvath; M Weber; S Trattnig; W Bogner
Journal:  Eur Radiol       Date:  2013-03-16       Impact factor: 5.315

Review 4.  Effect of b value and pre-admission of contrast on diagnostic accuracy of 1.5-T breast DWI: a systematic review and meta-analysis.

Authors:  Monique D Dorrius; Hildebrand Dijkstra; Matthijs Oudkerk; Paul E Sijens
Journal:  Eur Radiol       Date:  2014-08-09       Impact factor: 5.315

5.  Can breast MRI accurately exclude malignancy in mammographic architectural distortion?

Authors:  Yoav Amitai; Anabel Scaranelo; Tehillah S Menes; Rachel Fleming; Supriya Kulkarni; Sandeep Ghai; Vivianne Freitas
Journal:  Eur Radiol       Date:  2020-01-30       Impact factor: 5.315

Review 6.  Overview of the role of pre-operative breast MRI in the absence of evidence on patient outcomes.

Authors:  Francesco Sardanelli
Journal:  Breast       Date:  2010-02       Impact factor: 4.380

7.  BI-RADS lesion characteristics predict likelihood of malignancy in breast MRI for masses but not for nonmasslike enhancement.

Authors:  Robert L Gutierrez; Wendy B DeMartini; Peter R Eby; Brenda F Kurland; Sue Peacock; Constance D Lehman
Journal:  AJR Am J Roentgenol       Date:  2009-10       Impact factor: 3.959

8.  MRI-only lesions: application of diffusion-weighted imaging obviates unnecessary MR-guided breast biopsies.

Authors:  Claudio Spick; Katja Pinker-Domenig; Margaretha Rudas; Thomas H Helbich; Pascal A Baltzer
Journal:  Eur Radiol       Date:  2014-04-05       Impact factor: 5.315

Review 9.  Diagnostic Performance of Breast Magnetic Resonance Imaging in Non-Calcified Equivocal Breast Findings: Results from a Systematic Review and Meta-Analysis.

Authors:  Barbara Bennani-Baiti; Nabila Bennani-Baiti; Pascal A Baltzer
Journal:  PLoS One       Date:  2016-08-02       Impact factor: 3.240

10.  Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis.

Authors:  M Wielema; M D Dorrius; R M Pijnappel; G H De Bock; P A T Baltzer; M Oudkerk; P E Sijens
Journal:  PLoS One       Date:  2020-05-06       Impact factor: 3.240

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  9 in total

1.  Combined diagnosis of multiparametric MRI-based deep learning models facilitates differentiating triple-negative breast cancer from fibroadenoma magnetic resonance BI-RADS 4 lesions.

Authors:  Hao-Lin Yin; Yu Jiang; Zihan Xu; Hui-Hui Jia; Guang-Wu Lin
Journal:  J Cancer Res Clin Oncol       Date:  2022-06-30       Impact factor: 4.553

2.  A survey by the European Society of Breast Imaging on the implementation of breast diffusion-weighted imaging in clinical practice.

Authors:  Laura Martincich; Katja Pinker; Roberto Lo Gullo; Varadan Sevilimedu; Pascal Baltzer; Denis Le Bihan; Julia Camps-Herrero; Paola Clauser; Fiona J Gilbert; Mami Iima; Ritse M Mann; Savannah C Partridge; Andrew Patterson; Eric E Sigmund; Sunitha Thakur; Fabienne E Thibault
Journal:  Eur Radiol       Date:  2022-05-04       Impact factor: 7.034

3.  A Comparative Assessment of MR BI-RADS 4 Breast Lesions With Kaiser Score and Apparent Diffusion Coefficient Value.

Authors:  Lingsong Meng; Xin Zhao; Lin Lu; Qingna Xing; Kaiyu Wang; Yafei Guo; Honglei Shang; Yan Chen; Mengyue Huang; Yongbing Sun; Xiaoan Zhang
Journal:  Front Oncol       Date:  2021-12-02       Impact factor: 6.244

4.  Non-Mass Enhancements on DCE-MRI: Development and Validation of a Radiomics-Based Signature for Breast Cancer Diagnoses.

Authors:  Yan Li; Zhenlu L Yang; Wenzhi Z Lv; Yanjin J Qin; Caili L Tang; Xu Yan; Yihao H Guo; Liming M Xia; Tao Ai
Journal:  Front Oncol       Date:  2021-09-22       Impact factor: 6.244

5.  Differentiation of Benign and Malignant Breast Lesions Using ADC Values and ADC Ratio in Breast MRI.

Authors:  Silvia Tsvetkova; Katya Doykova; Anna Vasilska; Katya Sapunarova; Daniel Doykov; Vladimir Andonov; Petar Uchikov
Journal:  Diagnostics (Basel)       Date:  2022-01-27

6.  Breast Lesion Classification with Multiparametric Breast MRI Using Radiomics and Machine Learning: A Comparison with Radiologists' Performance.

Authors:  Isaac Daimiel Naranjo; Peter Gibbs; Jeffrey S Reiner; Roberto Lo Gullo; Sunitha B Thakur; Maxine S Jochelson; Nikita Thakur; Pascal A T Baltzer; Thomas H Helbich; Katja Pinker
Journal:  Cancers (Basel)       Date:  2022-03-29       Impact factor: 6.575

7.  Breast Cancer Classification on Multiparametric MRI - Increased Performance of Boosting Ensemble Methods.

Authors:  Alexandros Vamvakas; Dimitra Tsivaka; Andreas Logothetis; Katerina Vassiou; Ioannis Tsougos
Journal:  Technol Cancer Res Treat       Date:  2022 Jan-Dec

8.  Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding.

Authors:  Alan Penn; Milica Medved; Hiroyuki Abe; Vandana Dialani; Gregory S Karczmar; David Brousseau
Journal:  BMC Med Imaging       Date:  2022-09-29       Impact factor: 2.795

9.  Radiomics and Machine Learning with Multiparametric Breast MRI for Improved Diagnostic Accuracy in Breast Cancer Diagnosis.

Authors:  Isaac Daimiel Naranjo; Peter Gibbs; Jeffrey S Reiner; Roberto Lo Gullo; Caleb Sooknanan; Sunitha B Thakur; Maxine S Jochelson; Varadan Sevilimedu; Elizabeth A Morris; Pascal A T Baltzer; Thomas H Helbich; Katja Pinker
Journal:  Diagnostics (Basel)       Date:  2021-05-21
  9 in total

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