Literature DB >> 34455593

Challenges in ensuring the generalizability of image quantitation methods for MRI.

Kathryn E Keenan1, Jana G Delfino2, Kalina V Jordanova1, Megan E Poorman1, Prathyush Chirra3, Akshay S Chaudhari4,5, Bettina Baessler6, Jessica Winfield7,8, Satish E Viswanath3, Nandita M deSouza7,8.   

Abstract

Image quantitation methods including quantitative MRI, multiparametric MRI, and radiomics offer great promise for clinical use. However, many of these methods have limited clinical adoption, in part due to issues of generalizability, that is, the ability to translate methods and models across institutions. Researchers can assess generalizability through measurement of repeatability and reproducibility, thus quantifying different aspects of measurement variance. In this article, we review the challenges to ensuring repeatability and reproducibility of image quantitation methods as well as present strategies to minimize their variance to enable wider clinical implementation. We present possible solutions for achieving clinically acceptable performance of image quantitation methods and briefly discuss the impact of minimizing variance and achieving generalizability towards clinical implementation and adoption.
© 2021 American Association of Physicists in Medicine. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Entities:  

Keywords:  magnetic resonance imaging; multiparametric MRI; quantitative MRI; radiomics

Mesh:

Year:  2021        PMID: 34455593      PMCID: PMC8882689          DOI: 10.1002/mp.15195

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.506


  149 in total

1.  Rapid magnetic resonance quantification on the brain: Optimization for clinical usage.

Authors:  J B M Warntjes; O Dahlqvist Leinhard; J West; P Lundberg
Journal:  Magn Reson Med       Date:  2008-08       Impact factor: 4.668

2.  Robustness and Reproducibility of Radiomics in Magnetic Resonance Imaging: A Phantom Study.

Authors:  Bettina Baeßler; Kilian Weiss; Daniel Pinto Dos Santos
Journal:  Invest Radiol       Date:  2019-04       Impact factor: 6.016

3.  Exploring breast cancer response prediction to neoadjuvant systemic therapy using MRI-based radiomics: A systematic review.

Authors:  R W Y Granzier; T J A van Nijnatten; H C Woodruff; M L Smidt; M B I Lobbes
Journal:  Eur J Radiol       Date:  2019-11-06       Impact factor: 3.528

4.  T2w-MRI signal normalization affects radiomics features reproducibility.

Authors:  Elisa Scalco; Antonella Belfatto; Alfonso Mastropietro; Tiziana Rancati; Barbara Avuzzi; Antonella Messina; Riccardo Valdagni; Giovanna Rizzo
Journal:  Med Phys       Date:  2020-02-14       Impact factor: 4.071

Review 5.  Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease.

Authors:  François De Guio; Eric Jouvent; Geert Jan Biessels; Sandra E Black; Carol Brayne; Christopher Chen; Charlotte Cordonnier; Frank-Eric De Leeuw; Martin Dichgans; Fergus Doubal; Marco Duering; Carole Dufouil; Emrah Duzel; Franz Fazekas; Vladimir Hachinski; M Arfan Ikram; Jennifer Linn; Paul M Matthews; Bernard Mazoyer; Vincent Mok; Bo Norrving; John T O'Brien; Leonardo Pantoni; Stefan Ropele; Perminder Sachdev; Reinhold Schmidt; Sudha Seshadri; Eric E Smith; Luciano A Sposato; Blossom Stephan; Richard H Swartz; Christophe Tzourio; Mark van Buchem; Aad van der Lugt; Robert van Oostenbrugge; Meike W Vernooij; Anand Viswanathan; David Werring; Frank Wollenweber; Joanna M Wardlaw; Hugues Chabriat
Journal:  J Cereb Blood Flow Metab       Date:  2016-05-11       Impact factor: 6.200

6.  New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

Authors:  E A Eisenhauer; P Therasse; J Bogaerts; L H Schwartz; D Sargent; R Ford; J Dancey; S Arbuck; S Gwyther; M Mooney; L Rubinstein; L Shankar; L Dodd; R Kaplan; D Lacombe; J Verweij
Journal:  Eur J Cancer       Date:  2009-01       Impact factor: 9.162

7.  A novel DTI-QA tool: Automated metric extraction exploiting the sphericity of an agar filled phantom.

Authors:  Sofia Chavez; Joseph Viviano; Mojdeh Zamyadi; Peter B Kingsley; Peter Kochunov; Stephen Strother; Aristotle Voineskos
Journal:  Magn Reson Imaging       Date:  2017-10-17       Impact factor: 2.546

8.  Whole-Tumor Quantitative Apparent Diffusion Coefficient Histogram and Texture Analysis to Predict Gleason Score Upgrading in Intermediate-Risk 3 + 4 = 7 Prostate Cancer.

Authors:  Radu Rozenberg; Rebecca E Thornhill; Trevor A Flood; Shaheed W Hakim; Christopher Lim; Nicola Schieda
Journal:  AJR Am J Roentgenol       Date:  2016-02-02       Impact factor: 3.959

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.  Myocardial T1 and T2 Mapping: Techniques and Clinical Applications.

Authors:  Pan Ki Kim; Yoo Jin Hong; Dong Jin Im; Young Joo Suh; Chul Hwan Park; Jin Young Kim; Suyon Chang; Hye-Jeong Lee; Jin Hur; Young Jin Kim; Byoung Wook Choi
Journal:  Korean J Radiol       Date:  2017-01-05       Impact factor: 3.500

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  2 in total

1.  Editorial: Fast Multi-Parameter Magnetic Resonance Neuroimaging.

Authors:  Jiazheng Wang; Shuhui Cai; Zhiyong Zhang; Congbo Cai
Journal:  Front Neurosci       Date:  2022-06-29       Impact factor: 5.152

Review 2.  The Road Toward Reproducibility of Parametric Mapping of the Heart: A Technical Review.

Authors:  Augustin C Ogier; Aurelien Bustin; Hubert Cochet; Juerg Schwitter; Ruud B van Heeswijk
Journal:  Front Cardiovasc Med       Date:  2022-05-06
  2 in total

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