Literature DB >> 27008431

Variability and bias assessment in breast ADC measurement across multiple systems.

Kathryn E Keenan1, Adele P Peskin2, Lisa J Wilmes3, Sheye O Aliu3, Ella F Jones3, Wen Li3, John Kornak4, David C Newitt3, Nola M Hylton3.   

Abstract

PURPOSE: To assess the ability of a recent, anatomically designed breast phantom incorporating T1 and diffusion elements to serve as a quality control device for quantitative comparison of apparent diffusion coefficient (ADC) measurements calculated from diffusion-weighted MRI (DWI) within and across MRI systems.
MATERIALS AND METHODS: A bilateral breast phantom incorporating multiple T1 and diffusion tissue mimics and a geometric distortion array was imaged with DWI on 1.5 Tesla (T) and 3.0T scanners from two different manufacturers, using three different breast coils (three configurations total). Multiple measurements were acquired to assess the bias and variability of different diffusion weighted single-shot echo-planar imaging sequences on the scanner-coil systems.
RESULTS: The repeatability of ADC measurements was mixed: the standard deviation relative to baseline across scanner-coil-sequences ranged from low variability (0.47, 95% confidence interval [CI]: 0.22-1.00) to high variability (1.69, 95% CI: 0.17-17.26), depending on material, with the lowest and highest variability from the same scanner-coil-sequence. Assessment of image distortion showed that right/left measurements of the geometric distortion array were 1 to 16% larger on the left coil side compared with the right coil side independent of scanner-coil systems, diffusion weighting, and phase-encoding direction.
CONCLUSION: This breast phantom can be used to measure scanner-coil-sequence bias and variability for DWI. When establishing a multisystem study, this breast phantom may be used to minimize protocol differences (e.g., due to available sequences or shimming technique), to correct for bias that cannot be minimized, and to weigh results from each system depending on respective variability. J. Magn. Reson. Imaging 2016. J. MAGN. RESON. IMAGING 2016;44:846-855.
© 2016 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  EPI; apparent diffusion coefficient; breast MRI; phantoms; quality control; tissue mimic

Mesh:

Year:  2016        PMID: 27008431      PMCID: PMC5098898          DOI: 10.1002/jmri.25237

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


  25 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.  Strategies for shimming the breast.

Authors:  Nimrod Maril; Christopher M Collins; Robert L Greenman; Robert E Lenkinski
Journal:  Magn Reson Med       Date:  2005-11       Impact factor: 4.668

3.  Correction for geometric distortion in echo planar images from B0 field variations.

Authors:  P Jezzard; R S Balaban
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Review 4.  What's wrong with Bonferroni adjustments.

Authors:  T V Perneger
Journal:  BMJ       Date:  1998-04-18

5.  Improved correction for gradient nonlinearity effects in diffusion-weighted imaging.

Authors:  Ek T Tan; Luca Marinelli; Zachary W Slavens; Kevin F King; Christopher J Hardy
Journal:  J Magn Reson Imaging       Date:  2012-11-21       Impact factor: 4.813

6.  Apparent diffusion coefficient values for discriminating benign and malignant breast MRI lesions: effects of lesion type and size.

Authors:  Savannah C Partridge; Christiane D Mullins; Brenda F Kurland; Michael D Allain; Wendy B DeMartini; Peter R Eby; Constance D Lehman
Journal:  AJR Am J Roentgenol       Date:  2010-06       Impact factor: 3.959

7.  Gradient nonlinearity correction to improve apparent diffusion coefficient accuracy and standardization in the american college of radiology imaging network 6698 breast cancer trial.

Authors:  David C Newitt; Ek T Tan; Lisa J Wilmes; Thomas L Chenevert; John Kornak; Luca Marinelli; Nola Hylton
Journal:  J Magn Reson Imaging       Date:  2015-03-11       Impact factor: 4.813

8.  Dynamic slice-dependent shim and center frequency update in 3 T breast diffusion weighted imaging.

Authors:  Seung-Kyun Lee; Ek Tsoon Tan; Ambey Govenkar; Ileana Hancu
Journal:  Magn Reson Med       Date:  2013-06-24       Impact factor: 4.668

9.  An anthropomorphic phantom for quantitative evaluation of breast MRI.

Authors:  Melanie Freed; Jacco A de Zwart; Jennifer T Loud; Riham H El Khouli; Kyle J Myers; Mark H Greene; Jeff H Duyn; Aldo Badano
Journal:  Med Phys       Date:  2011-02       Impact factor: 4.071

10.  Improved diagnostic accuracy of breast MRI through combined apparent diffusion coefficients and dynamic contrast-enhanced kinetics.

Authors:  S C Partridge; H Rahbar; R Murthy; X Chai; B F Kurland; W B DeMartini; C D Lehman
Journal:  Magn Reson Med       Date:  2011-01-19       Impact factor: 4.668

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2.  Additive value of diffusion-weighted MRI in the I-SPY 2 TRIAL.

Authors:  Wen Li; David C Newitt; Lisa J Wilmes; Ella F Jones; Vignesh Arasu; Jessica Gibbs; Bo La Yun; Elizabeth Li; Savannah C Partridge; John Kornak; Laura J Esserman; Nola M Hylton
Journal:  J Magn Reson Imaging       Date:  2019-04-26       Impact factor: 4.813

3.  Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs.

Authors:  Kathryn E Keenan; Joshua R Biller; Jana G Delfino; Michael A Boss; Mark D Does; Jeffrey L Evelhoch; Mark A Griswold; Jeffrey L Gunter; R Scott Hinks; Stuart W Hoffman; Geena Kim; Riccardo Lattanzi; Xiaojuan Li; Luca Marinelli; Gregory J Metzger; Pratik Mukherjee; Robert J Nordstrom; Adele P Peskin; Elena Perez; Stephen E Russek; Berkman Sahiner; Natalie Serkova; Amita Shukla-Dave; Michael Steckner; Karl F Stupic; Lisa J Wilmes; Holden H Wu; Huiming Zhang; Edward F Jackson; Daniel C Sullivan
Journal:  J Magn Reson Imaging       Date:  2019-01-24       Impact factor: 4.813

4.  Technical note: Temperature and concentration dependence of water diffusion in polyvinylpyrrolidone solutions.

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Journal:  Med Phys       Date:  2022-03-03       Impact factor: 4.506

5.  Temperature and concentration calibration of aqueous polyvinylpyrrolidone (PVP) solutions for isotropic diffusion MRI phantoms.

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Journal:  PLoS One       Date:  2017-06-19       Impact factor: 3.240

Review 6.  Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives.

Authors:  N M deSouza; J M Winfield; J C Waterton; A Weller; M-V Papoutsaki; S J Doran; D J Collins; L Fournier; D Sullivan; T Chenevert; A Jackson; M Boss; S Trattnig; Y Liu
Journal:  Eur Radiol       Date:  2017-09-27       Impact factor: 5.315

Review 7.  Factors affecting the value of diffusion-weighted imaging for identifying breast cancer patients with pathological complete response on neoadjuvant systemic therapy: a systematic review.

Authors:  Kay J J van der Hoogt; Robert J Schipper; Gonneke A Winter-Warnars; Leon C Ter Beek; Claudette E Loo; Ritse M Mann; Regina G H Beets-Tan
Journal:  Insights Imaging       Date:  2021-12-18

8.  Tri-Compartmental Restriction Spectrum Imaging Breast Model Distinguishes Malignant Lesions from Benign Lesions and Healthy Tissue on Diffusion-Weighted Imaging.

Authors:  Alexandra H Besser; Lauren K Fang; Michelle W Tong; Maren M Sjaastad Andreassen; Haydee Ojeda-Fournier; Christopher C Conlin; Stéphane Loubrie; Tyler M Seibert; Michael E Hahn; Joshua M Kuperman; Anne M Wallace; Anders M Dale; Ana E Rodríguez-Soto; Rebecca A Rakow-Penner
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  8 in total

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