Literature DB >> 27553252

Diffusion-weighted MRI of breast lesions: a prospective clinical investigation of the quantitative imaging biomarker characteristics of reproducibility, repeatability, and diagnostic accuracy.

Claudio Spick1, Hubert Bickel1, Katja Pinker1, Maria Bernathova1, Panagiotis Kapetas1, Ramona Woitek1, Paola Clauser1, Stephan H Polanec1, Margaretha Rudas2, Rupert Bartsch3, Thomas H Helbich1, Pascal A Baltzer4.   

Abstract

Diffusion-weighted MRI (DWI) provides insights into tissue microstructure by visualization and quantification of water diffusivity. Quantitative evaluation of the apparent diffusion coefficient (ADC) obtained from DWI has been proven helpful for differentiating between malignant and benign breast lesions, for cancer subtyping in breast cancer patients, and for prediction of response to neoadjuvant chemotherapy. However, to further establish DWI of breast lesions it is important to evaluate the quantitative imaging biomarker (QIB) characteristics of reproducibility, repeatability, and diagnostic accuracy. In this intra-individual prospective clinical study 40 consecutive patients with suspicious findings, scheduled for biopsy, underwent an identical 3T breast MRI protocol of the breast on two consecutive days (>24 h). Mean ADC of target lesions was assessed (two independent readers) in four separate sessions. Reproducibility, repeatability, and diagnostic accuracy between examinations (E1, E2), readers (R1, R2), and measurements (M1, M2) were assessed with intraclass correlation coefficients (ICCs), coefficients of variation (CVs), Bland-Altman plots, and receiver operating characteristic (ROC) analysis with calculation of the area under the ROC curve (AUC). The standard of reference was either histopathology (n = 38) or imaging follow-up of up to 24 months (n = 2). Eighty breast MRI examinations (median E1-E2, 2 ± 1.7 days, 95% confidence interval (CI) 1-2 days, range 1-11 days) in 40 patients (mean age 56, standard deviation (SD) ±14) were evaluated. In 55 target lesions (mean size 25.2 ± 20.8 (SD) mm, range 6-106 mm), mean ADC values were significantly (P < 0.0001) higher in benign (1.38, 95% CI 1.27-1.49 × 10(-3)  mm(2) /s) compared with malignant (0.86, 95% CI 0.81-0.91 × 10(-) (3)  mm(2) /s) lesions. Reproducibility and repeatability showed high agreement for repeated examinations, readers, and measurements (all ICCs >0.9, CVs 3.2-8%), indicating little variation. Bland-Altman plots demonstrated no systematic differences, and diagnostic accuracy was not significantly different in the two repeated examinations (all ROC curves >0.91, P > 0.05). High reproducibility, repeatability, and diagnostic accuracy of DWI provide reliable characteristics for its use as a potential QIB, to further improve breast lesion detection, characterization, and treatment monitoring of breast lesions.
Copyright © 2016 John Wiley & Sons, Ltd.

Entities:  

Keywords:  DWI; breast cancer; diagnostic accuracy; diffusion-weighted imaging; quantitative imaging biomarker; repeatability; reproducibility

Mesh:

Substances:

Year:  2016        PMID: 27553252     DOI: 10.1002/nbm.3596

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  18 in total

1.  Clinical experience of tensor-valued diffusion encoding for microstructure imaging by diffusional variance decomposition in patients with breast cancer.

Authors:  Eun Cho; Hye Jin Baek; Filip Szczepankiewicz; Hyo Jung An; Eun Jung Jung; Ho-Joon Lee; Joonsung Lee; Sung-Min Gho
Journal:  Quant Imaging Med Surg       Date:  2022-03

2.  Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial.

Authors:  David C Newitt; Zheng Zhang; Jessica E Gibbs; Savannah C Partridge; Thomas L Chenevert; Mark A Rosen; Patrick J Bolan; Helga S Marques; Sheye Aliu; Wen Li; Lisa Cimino; Bonnie N Joe; Heidi Umphrey; Haydee Ojeda-Fournier; Basak Dogan; Karen Oh; Hiroyuki Abe; Jennifer Drukteinis; Laura J Esserman; Nola M Hylton
Journal:  J Magn Reson Imaging       Date:  2018-10-22       Impact factor: 4.813

3.  Potential of Noncontrast Magnetic Resonance Imaging With Diffusion-Weighted Imaging in Characterization of Breast Lesions: Intraindividual Comparison With Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Authors:  Pascal A T Baltzer; Hubert Bickel; Claudio Spick; Georg Wengert; Ramona Woitek; Panagiotis Kapetas; Paola Clauser; Thomas H Helbich; Katja Pinker
Journal:  Invest Radiol       Date:  2018-04       Impact factor: 6.016

4.  Variability of non-Gaussian diffusion MRI and intravoxel incoherent motion (IVIM) measurements in the breast.

Authors:  Mami Iima; Masako Kataoka; Shotaro Kanao; Makiko Kawai; Natsuko Onishi; Sho Koyasu; Katsutoshi Murata; Akane Ohashi; Rena Sakaguchi; Kaori Togashi
Journal:  PLoS One       Date:  2018-03-01       Impact factor: 3.240

5.  Multiparametric Analysis of Longitudinal Quantitative MRI data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer.

Authors:  Anum K Syed; Jennifer G Whisenant; Stephanie L Barnes; Anna G Sorace; Thomas E Yankeelov
Journal:  Cancers (Basel)       Date:  2020-06-24       Impact factor: 6.639

6.  Apparent diffusion coefficient values in borderline breast lesions upgraded and not upgraded at definitive histopathological examination after surgical excision.

Authors:  Corrado Tagliati; Paola Piccinni; Paola Ercolani; Elisabetta Marconi; Barbara Franca Simonetti; Gian Marco Giuseppetti; Andrea Giovagnoni
Journal:  Pol J Radiol       Date:  2021-04-30

Review 7.  New diagnostic tools for breast cancer.

Authors:  Pascal A T Baltzer; Panagiotis Kapetas; Maria Adele Marino; Paola Clauser
Journal:  Memo       Date:  2017-06-28

8.  Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network.

Authors:  David C Newitt; Dariya Malyarenko; Thomas L Chenevert; C Chad Quarles; Laura Bell; Andriy Fedorov; Fiona Fennessy; Michael A Jacobs; Meiyappan Solaiyappan; Stefanie Hectors; Bachir Taouli; Mark Muzi; Paul E Kinahan; Kathleen M Schmainda; Melissa A Prah; Erin N Taber; Christopher Kroenke; Wei Huang; Lori R Arlinghaus; Thomas E Yankeelov; Yue Cao; Madhava Aryal; Yi-Fen Yen; Jayashree Kalpathy-Cramer; Amita Shukla-Dave; Maggie Fung; Jiachao Liang; Michael Boss; Nola Hylton
Journal:  J Med Imaging (Bellingham)       Date:  2017-10-10

9.  Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial.

Authors:  David C Newitt; Ghoncheh Amouzandeh; Savannah C Partridge; Helga S Marques; Benjamin A Herman; Brian D Ross; Nola M Hylton; Thomas L Chenevert; Dariya I Malyarenko
Journal:  Tomography       Date:  2020-06

10.  Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index.

Authors:  Yuan Guo; Qing-Cong Kong; Li-Qi Li; Wen-Jie Tang; Wan-Li Zhang; Guan-Yuan Ning; Jun Xue; Qian-Wei Zhou; Ying-Ying Liang; Mei Wu; Xin-Qing Jiang
Journal:  Biomed Res Int       Date:  2021-06-24       Impact factor: 3.411

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