Literature DB >> 27273694

Quantitative DWI implemented after DCE-MRI yields increased specificity for BI-RADS 3 and 4 breast lesions.

Hildebrand Dijkstra1,2, Monique D Dorrius1,2, Mirjam Wielema1,2, Ruud M Pijnappel3, Matthijs Oudkerk1, Paul E Sijens2.   

Abstract

PURPOSE: To assess if specificity can be increased when semiautomated breast lesion analysis of quantitative diffusion-weighted imaging (DWI) is implemented after dynamic contrast-enhanced (DCE-) magnetic resonance imaging (MRI) in the workup of BI-RADS 3 and 4 breast lesions larger than 1 cm.
MATERIALS AND METHODS: In all, 120 consecutive patients (mean-age, 48 years; age range, 23-75 years) with 139 breast lesions (≥1 cm) were examined (2010-2014) with 1.5T DCE-MRI and DWI (b = 0, 50, 200, 500, 800, 1000 s/mm2 ) and the BI-RADS classification and histopathology were obtained. For each lesion malignancy was excluded using voxelwise semiautomated breast lesion analysis based on previously defined thresholds for the apparent diffusion coefficient (ADC) and the three intravoxel incoherent motion (IVIM) parameters: molecular diffusion (Dslow ), microperfusion (Dfast ), and the fraction of Dfast (ffast ). The sensitivity (Se), specificity (Sp), and negative predictive value (NPV) based on only IVIM parameters combined in parallel (Dslow , Dfast , and ffast ), or the ADC or the BI-RADS classification by DCE-MRI were compared. Subsequently, the Se, Sp, and NPV of the combination of the BI-RADS classification by DCE-MRI followed by the IVIM parameters in parallel (or the ADC) were compared.
RESULTS: In all, 23 of 139 breast lesions were benign. Se and Sp of DCE-MRI was 100% and 30.4% (NPV = 100%). Se and Sp of IVIM parameters in parallel were 92.2% and 52.2% (NPV = 57.1%) and for the ADC 95.7% and 17.4%, respectively (NPV = 44.4%). In all, 26 of 139 lesions were classified as BI-RADS 3 (n = 7) or BI-RADS 4 (n = 19). DCE-MRI combined with ADC (Se = 99.1%, Sp = 34.8%) or IVIM (Se = 99.1%, Sp = 56.5%) did significantly improve (P = 0.016) Sp of DCE-MRI alone for workup of BI-RADS 3 and 4 lesions (NPV = 92.9%).
CONCLUSION: Quantitative DWI has a lower NPV compared to DCE-MRI for evaluation of breast lesions and may therefore not be able to replace DCE-MRI; when implemented after DCE-MRI as problem solver for BI-RADS 3 and 4 lesions, the combined specificity improves significantly. J. Magn. Reson. Imaging 2016;44:1642-1649.
© 2016 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  breast; cancer; diagnostic techniques and procedures; diffusion weighted MRI

Mesh:

Year:  2016        PMID: 27273694     DOI: 10.1002/jmri.25331

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


  27 in total

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6.  Intratumoral and peritumoral radiomics based on dynamic contrast-enhanced MRI for preoperative prediction of intraductal component in invasive breast cancer.

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7.  Utility of Diffusion-weighted Imaging to Decrease Unnecessary Biopsies Prompted by Breast MRI: A Trial of the ECOG-ACRIN Cancer Research Group (A6702).

Authors:  Habib Rahbar; Zheng Zhang; Thomas L Chenevert; Justin Romanoff; Averi E Kitsch; Lucy G Hanna; Sara M Harvey; Linda Moy; Wendy B DeMartini; Basak Dogan; Wei T Yang; Lilian C Wang; Bonnie N Joe; Karen Y Oh; Colleen H Neal; Elizabeth S McDonald; Mitchell D Schnall; Constance D Lehman; Christopher E Comstock; Savannah C Partridge
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8.  Simultaneous whole-body and breast 18F-FDG PET/MRI examinations in patients with breast cancer: a comparison of apparent diffusion coefficients and maximum standardized uptake values.

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9.  Diagnostic performance of initial enhancement analysis using ultra-fast dynamic contrast-enhanced MRI for breast lesions.

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10.  Factors Affecting Image Quality and Lesion Evaluability in Breast Diffusion-weighted MRI: Observations from the ECOG-ACRIN Cancer Research Group Multisite Trial (A6702).

Authors:  Jennifer G Whisenant; Justin Romanoff; Habib Rahbar; Averi E Kitsch; Sara M Harvey; Linda Moy; Wendy B DeMartini; Basak E Dogan; Wei T Yang; Lilian C Wang; Bonnie N Joe; Lisa J Wilmes; Nola M Hylton; Karen Y Oh; Luminita A Tudorica; Colleen H Neal; Dariya I Malyarenko; Elizabeth S McDonald; Christopher E Comstock; Thomas E Yankeelov; Thomas L Chenevert; Savannah C Partridge
Journal:  J Breast Imaging       Date:  2020-12-24
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