Literature DB >> 21225368

Intraobserver and interobserver variability in the calculation of apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (DW-MRI) of breast tumours.

G Petralia1, L Bonello, P Summers, L Preda, A Malasevschi, S Raimondi, R Di Filippi, M Locatelli, G Curigliano, G Renne, M Bellomi.   

Abstract

PURPOSE: This study evaluated intraobserver and interobserver variability in the measurement of apparent diffusion coefficient (ADC) values in breast carcinomas.
MATERIALS AND METHODS: Twenty-eight patients with solid breast lesions >10 mm underwent conventional contrast-enhanced magnetic resonance imaging (MRI) and diffusion-weighted MRI (DW-MRI). Two observers (expert and trainee) segmented the lesion from the surrounding breast tissue on DW images with high b-value (1,000 s/mm(2)). This analysis was repeated by the expert reader after 6 months. Volumes were analysed to obtain mean, median and standard deviation (SD) of the ADC values. Interobserver and intraobserver variation was analysed using the Bland-Altman graph.
RESULTS: All lesions were breast carcinomas, with a mean ADC value of 1.07 × 10(-3) mm(2)/s. The mean of the differences was 0.012 × 10(-3) mm(2)/s, corresponding to an intraobserver variability of 1.1% (limits of agreement: -5%/+8%). The mean interobserver difference was 0.022 × 10(-3) mm(2)/s, corresponding to an interobserver variability of 2% (limits of agreement: -9%/+14%).
CONCLUSIONS: We found a low intraobserver and interobserver variability in calculating ADC in breast carcinomas, which supports its potential use in routine clinical practice.

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Year:  2011        PMID: 21225368     DOI: 10.1007/s11547-011-0616-z

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


  13 in total

1.  In vivo diffusion-weighted MRI of the breast: potential for lesion characterization.

Authors:  Shantanu Sinha; Flora Anne Lucas-Quesada; Usha Sinha; Nanette DeBruhl; Lawrence W Bassett
Journal:  J Magn Reson Imaging       Date:  2002-06       Impact factor: 4.813

2.  Quantitative diffusion imaging in breast cancer: a clinical prospective study.

Authors:  Erika Rubesova; Anne-Sophie Grell; Viviane De Maertelaer; Thierry Metens; Shih-Li Chao; Marc Lemort
Journal:  J Magn Reson Imaging       Date:  2006-08       Impact factor: 4.813

3.  Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer.

Authors:  Martin D Pickles; Peter Gibbs; Martin Lowry; Lindsay W Turnbull
Journal:  Magn Reson Imaging       Date:  2006-04-27       Impact factor: 2.546

Review 4.  Advances in functional and structural MR image analysis and implementation as FSL.

Authors:  Stephen M Smith; Mark Jenkinson; Mark W Woolrich; Christian F Beckmann; Timothy E J Behrens; Heidi Johansen-Berg; Peter R Bannister; Marilena De Luca; Ivana Drobnjak; David E Flitney; Rami K Niazy; James Saunders; John Vickers; Yongyue Zhang; Nicola De Stefano; J Michael Brady; Paul M Matthews
Journal:  Neuroimage       Date:  2004       Impact factor: 6.556

5.  Indications for breast magnetic resonance imaging. Consensus document "Attualità in senologia", Florence 2007.

Authors:  F Sardanelli; G M Giuseppetti; G Canavese; L Cataliotti; S Corcione; E Cossu; M Federico; L Marotti; L Martincich; P Panizza; F Podo; M Rosselli Del Turco; C Zuiani; C Alfano; M Bazzocchi; P Belli; S Bianchi; A Cilotti; M Calabrese; L Carbonaro; L Cortesi; C Di Maggio; A Del Maschio; A Esseridou; A Fausto; M Gennaro; R Girometti; R Ienzi; A Luini; S Manoukian; S Morassutt; D Morrone; J Nori; A Orlacchio; F Pane; P Panzarola; R Ponzone; G Simonetti; P Torricelli; G Valeri
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6.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
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Review 7.  Concepts for differential diagnosis in breast MR imaging.

Authors:  Christiane K Kuhl
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8.  Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging.

Authors:  Yong Guo; You-Quan Cai; Zu-Long Cai; Yuan-Gui Gao; Ning-Yu An; Lin Ma; Srikanth Mahankali; Jia-Hong Gao
Journal:  J Magn Reson Imaging       Date:  2002-08       Impact factor: 4.813

Review 9.  Magnetic resonance (MR) differential diagnosis of breast tumors using apparent diffusion coefficient (ADC) on 1.5-T.

Authors:  Yoshito Tsushima; Ayako Takahashi-Taketomi; Keigo Endo
Journal:  J Magn Reson Imaging       Date:  2009-08       Impact factor: 4.813

10.  Diffusion-weighted imaging of breast cancer: correlation of the apparent diffusion coefficient value with prognostic factors.

Authors:  Sung Hun Kim; Eun Suk Cha; Hyeon Sook Kim; Bong Joo Kang; Jae Jeong Choi; Ji Han Jung; Yong Gyu Park; Young Jin Suh
Journal:  J Magn Reson Imaging       Date:  2009-09       Impact factor: 4.813

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  11 in total

1.  Region of interest demarcation for quantification of the apparent diffusion coefficient in breast lesions and its interobserver variability.

Authors:  Luísa Nogueira; Sofia Brandão; Eduarda Matos; Rita Gouveia Nunes; Hugo Alexandre Ferreira; Joana Loureiro; Isabel Ramos
Journal:  Diagn Interv Radiol       Date:  2015 Mar-Apr       Impact factor: 2.630

2.  Interobserver agreement of semi-automated and manual measurements of functional MRI metrics of treatment response in hepatocellular carcinoma.

Authors:  David Bonekamp; Susanne Bonekamp; Vivek Gowdra Halappa; Jean-Francois H Geschwind; John Eng; Celia Pamela Corona-Villalobos; Timothy M Pawlik; Ihab R Kamel
Journal:  Eur J Radiol       Date:  2013-12-03       Impact factor: 3.528

3.  Diagnostic Value of Diffusion-weighted Imaging and Apparent Diffusion Coefficient Values in the Differentiation of Breast Lesions, Histpathologic Subgroups and Correlatıon with Prognostıc Factors using 3.0 Tesla MR.

Authors:  Yasin Akın; M Ümit Uğurlu; Handan Kaya; Erkin Arıbal
Journal:  J Breast Health       Date:  2016-07-01

4.  Combining standardized uptake value of FDG-PET and apparent diffusion coefficient of DW-MRI improves risk stratification in head and neck squamous cell carcinoma.

Authors:  Lorenzo Preda; Giorgio Conte; Luke Bonello; Caterina Giannitto; Laura L Travaini; Sara Raimondi; Paul E Summers; Ansarin Mohssen; Daniela Alterio; Maria Cossu Rocca; Chiara Grana; Francesca Ruju; Massimo Bellomi
Journal:  Eur Radiol       Date:  2016-03-10       Impact factor: 5.315

5.  MR mammography using diffusion-weighted imaging in evaluating breast cancer: a correlation with proliferation index.

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

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Journal:  J Magn Reson Imaging       Date:  2018-10-22       Impact factor: 4.813

7.  MR scanner systems should be adequately characterized in diffusion-MRI of the breast.

Authors:  Marco Giannelli; Roberto Sghedoni; Chiara Iacconi; Mauro Iori; Antonio Claudio Traino; Maria Guerrisi; Mario Mascalchi; Nicola Toschi; Stefano Diciotti
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8.  Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions.

Authors:  Alexey Surov; Hans Jonas Meyer; Andreas Wienke
Journal:  BMC Cancer       Date:  2019-10-15       Impact factor: 4.430

9.  Development of a diagnostic test set to assess agreement in breast pathology: practical application of the Guidelines for Reporting Reliability and Agreement Studies (GRRAS).

Authors:  Natalia V Oster; Patricia A Carney; Kimberly H Allison; Donald L Weaver; Lisa M Reisch; Gary Longton; Tracy Onega; Margaret Pepe; Berta M Geller; Heidi D Nelson; Tyler R Ross; Aanna N A Tosteson; Joann G Elmore
Journal:  BMC Womens Health       Date:  2013-02-05       Impact factor: 2.809

10.  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
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