Literature DB >> 30325549

Evaluation of Breast Cancer Morphology Using Diffusion-Weighted and Dynamic Contrast-Enhanced MRI: Intermethod and Interobserver Agreement.

Niko Radovic1, Gordana Ivanac1, Eugen Divjak1, Iva Biondic1, Antonio Bulum1, Boris Brkljacic1.   

Abstract

BACKGROUND: The capability of diffusion-weighted imaging (DWI) for morphological analysis of breast lesions is underexplored.
PURPOSE: To evaluate the utility of DWI for assessment of morphological features of breast cancer by comparing DWI and dynamic contrast-enhanced (DCE) MRI findings to determine intermethod and interobserver agreement. STUDY TYPE: Retrospective. POPULATION: Seventy-eight women with pathohistologically proven breast cancer. FIELD STRENGTH/SEQUENCE: 1.5T. DWI and DCE images. ASSESSMENT: Diffusion-weighted and DCE images were placed in two separate case sets. Three radiologists, blinded to all other information, independently evaluated each case set on two separate occasions. Lesions were interpreted according to the fifth edition of the ACR BI-RADS lexicon. STATISTICAL ANALYSIS: Kappa (κ) statistics were calculated in order to assess intermethod and interobserver agreement.
RESULTS: For values that attained statistical significance (P < 0.05), intermethod agreement ranged from fair (κ = 0.22) for nonmass internal patterns to significant (κ = 0.8) for lesion type. On DWI, interobserver agreement varied from fair (κ = 0.34) for mass shape to significant (κ = 0.75) for lesion type. On DCE MRI, interobserver agreement varied from fair (κ = 0.27) for irregular vs. spiculated mass margin to perfect (κ = 1) for circumscribed vs. noncircumscribed mass margin. DATA
CONCLUSION: On the whole, there was moderate intermethod agreement. The values of interobserver agreement were mostly similar between DWI and DCE MRI. This suggests that DWI is applicable for morphological assessment of breast cancer, notwithstanding substantially inferior spatial resolution compared to DCE MRI. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:1381-1390.
© 2018 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  breast cancer; contrast agent; diffusion weighted MRI; magnetic resonance imaging; observer variation

Mesh:

Substances:

Year:  2018        PMID: 30325549     DOI: 10.1002/jmri.26332

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  6 in total

1.  Diffusion-weighted MRI for Unenhanced Breast Cancer Screening.

Authors:  Nita Amornsiripanitch; Sebastian Bickelhaupt; Hee Jung Shin; Madeline Dang; Habib Rahbar; Katja Pinker; Savannah C Partridge
Journal:  Radiology       Date:  2019-10-08       Impact factor: 11.105

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.  Evaluation of Malignant Breast Lesions Using High-resolution Readout-segmented Diffusion-weighted Echo-planar Imaging: Comparison with Pathology.

Authors:  Ayami Ohno Kishimoto; Masako Kataoka; Mami Iima; Maya Honda; Kanae Kawai Miyake; Akane Ohashi; Rie Ota; Tatsuki Kataoka; Takaki Sakurai; Masakazu Toi; Kaori Togashi
Journal:  Magn Reson Med Sci       Date:  2020-07-02       Impact factor: 2.471

Review 4.  Diffusion-Weighted Magnetic Resonance Imaging of the Breast: Standardization of Image Acquisition and Interpretation.

Authors:  Su Hyun Lee; Hee Jung Shin; Woo Kyung Moon
Journal:  Korean J Radiol       Date:  2020-08-28       Impact factor: 3.500

5.  Application of MRI Image Based on Computer Semiautomatic Segmentation Algorithm in the Classification Prediction of Breast Cancer Histology.

Authors:  Aizhu Sheng; Aijing Li; Jianbi Xia; Yizhai Ye
Journal:  J Healthc Eng       Date:  2021-11-24       Impact factor: 2.682

6.  Agreement between dynamic contrast-enhanced magnetic resonance imaging and pathologic tumour size of breast cancer and analysis of the correlation with BI-RADS descriptors.

Authors:  Aysegul Akdogan Gemici; Ercan Inci
Journal:  Pol J Radiol       Date:  2019-12-27
  6 in total

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