Literature DB >> 34107440

Empirical validation of gradient field models for an accurate ADC measured on clinical 3T MR systems in body oncologic applications.

Yuxi Pang1, Dariya I Malyarenko2, Ghoncheh Amouzandeh2, Enzo Barberi3, Michael Cole3, Axel Vom Endt4, Johannes Peeters5, Ek T Tan6, Thomas L Chenevert2.   

Abstract

PURPOSE: To empirically corroborate vendor-provided gradient nonlinearity (GNL) characteristics and demonstrate efficient GNL bias correction for human brain apparent diffusion coefficient (ADC) across 3T MR systems and spatial locations.
METHODS: Spatial distortion vector fields (DVF) were mapped in 3D using a surface fiducial array phantom for individual gradient channels on three 3T MR platforms from different vendors. Measured DVF were converted into empirical 3D GNL tensors and compared with their theoretical counterparts derived from vendor-provided spherical harmonic (SPH) coefficients. To illustrate spatial impact of GNL on ADC, diffusion weighted imaging using three orthogonal gradient directions was performed on a volunteer brain positioned at isocenter (as a reference) and offset superiorly by 10-17 cm (>10% predicted GNL bias). The SPH tensor-based GNL correction was applied to individual DWI gradient directions, and derived ADC was compared with low-bias reference for human brain white matter (WM) ROIs.
RESULTS: Empiric and predicted GNL errors were comparable for all three studied 3T MR systems, with <1.0% differences in the median and width of spatial histograms for individual GNL tensor elements. Median (±width) of ADC (10-3mm2/s) histograms measured at isocenter in WM reference ROIs from three MR systems were: 0.73 ± 0.11, 0.71 ± 0.14, 0.74 ± 0.17, and at off-isocenters (before versus after GNL correction) were respectively 0.63 ± 0.14 versus 0.72 ± 0.11, 0.53 ± 0.16 versus 0.74 ± 0.18, and 0.65 ± 0.16 versus 0.76 ± 0.18.
CONCLUSION: The phantom-based spatial distortion measurements validated vendor-provided gradient fields, and accurate WM ADC was recovered regardless of spatial locations and clinical MR platforms using system-specific tensor-based GNL correction for routine DWI. Crown
Copyright © 2021. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Apparent diffusion coefficient; Diffusion weighted imaging; Gradient nonlinearity correction; Spherical harmonic coefficients; Surface-grid geometric distortion phantom

Mesh:

Year:  2021        PMID: 34107440      PMCID: PMC8268998          DOI: 10.1016/j.ejmp.2021.05.030

Source DB:  PubMed          Journal:  Phys Med        ISSN: 1120-1797            Impact factor:   3.119


  28 in total

1.  Practical estimate of gradient nonlinearity for implementation of apparent diffusion coefficient bias correction.

Authors:  Dariya I Malkyarenko; Thomas L Chenevert
Journal:  J Magn Reson Imaging       Date:  2014-12       Impact factor: 4.813

2.  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

3.  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

4.  The adverse effect of gradient nonlinearities on diffusion MRI: From voxels to group studies.

Authors:  Hamed Y Mesri; Szabolcs David; Max A Viergever; Alexander Leemans
Journal:  Neuroimage       Date:  2019-08-30       Impact factor: 6.556

5.  Toward Precision and Reproducibility of Diffusion Tensor Imaging: A Multicenter Diffusion Phantom and Traveling Volunteer Study.

Authors:  E M Palacios; A J Martin; M A Boss; F Ezekiel; Y S Chang; E L Yuh; M J Vassar; D M Schnyer; C L MacDonald; K L Crawford; A Irimia; A W Toga; P Mukherjee
Journal:  AJNR Am J Neuroradiol       Date:  2016-12-22       Impact factor: 3.825

6.  Demonstration of nonlinearity bias in the measurement of the apparent diffusion coefficient in multicenter trials.

Authors:  Dariya I Malyarenko; David Newitt; Lisa J Wilmes; Alina Tudorica; Karl G Helmer; Lori R Arlinghaus; Michael A Jacobs; Guido Jajamovich; Bachir Taouli; Thomas E Yankeelov; Wei Huang; Thomas L Chenevert
Journal:  Magn Reson Med       Date:  2015-05-02       Impact factor: 4.668

7.  Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations.

Authors:  Anwar R Padhani; Guoying Liu; Dow Mu Koh; Thomas L Chenevert; Harriet C Thoeny; Taro Takahara; Andrew Dzik-Jurasz; Brian D Ross; Marc Van Cauteren; David Collins; Dima A Hammoud; Gordon J S Rustin; Bachir Taouli; Peter L Choyke
Journal:  Neoplasia       Date:  2009-02       Impact factor: 5.715

8.  A straightforward multiparametric quality control protocol for proton magnetic resonance spectroscopy: Validation and comparison of various 1.5 T and 3 T clinical scanner systems.

Authors:  Roberto Sghedoni; Angela Coniglio; Lorenzo Nicola Mazzoni; Simone Busoni; Giacomo Belli; Roberto Tarducci; Luca Nocetti; Luca Fedeli; Marco Esposito; Antonio Ciccarone; Luisa Altabella; Alessandro Bellini; Luca Binotto; Rocchina Caivano; Marco Carnì; Alessandra Ricci; Sara Cimolai; Davide D'Urso; Chiara Gasperi; Fabrizio Levrero; Paola Mangili; Sabrina Morzenti; Andrea Nitrosi; Nadia Oberhofer; Nicoletta Parruccini; Alessandra Toncelli; Lucia Maria Valastro; Cesare Gori; Gianni Gobbi; Marco Giannelli
Journal:  Phys Med       Date:  2018-09-28       Impact factor: 2.685

9.  Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial.

Authors:  Savannah C Partridge; Zheng Zhang; David C Newitt; Jessica E Gibbs; Thomas L Chenevert; Mark A Rosen; Patrick J Bolan; Helga S Marques; Justin Romanoff; Lisa Cimino; Bonnie N Joe; Heidi R Umphrey; Haydee Ojeda-Fournier; Basak Dogan; Karen Oh; Hiroyuki Abe; Jennifer S Drukteinis; Laura J Esserman; Nola M Hylton
Journal:  Radiology       Date:  2018-09-04       Impact factor: 29.146

Review 10.  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

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  2 in total

1.  Perfusion-Diffusion Ratio: A New IVIM Approach in Differentiating Solid Benign and Malignant Primary Lesions of the Liver.

Authors:  Joanna Podgórska; Katarzyna Pasicz; Witold Skrzyński; Bogumił Gołębiewski; Piotr Kuś; Jakub Jasieniak; Anna Kiliszczyk; Agnieszka Rogowska; Thomas Benkert; Jakub Pałucki; Iwona Grabska; Ewa Fabiszewska; Beata Jagielska; Paweł Kukołowicz; Andrzej Cieszanowski
Journal:  Biomed Res Int       Date:  2022-01-15       Impact factor: 3.411

2.  Long-Term Stability of Gradient Characteristics Warrants Model-Based Correction of Diffusion Weighting Bias.

Authors:  Yuxi Pang; Dariya I Malyarenko; Lisa J Wilmes; Ajit Devaraj; Ek T Tan; Luca Marinelli; Axel Vom Endt; Johannes Peeters; Michael A Jacobs; David C Newitt; Thomas L Chenevert
Journal:  Tomography       Date:  2022-02-04
  2 in total

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