Literature DB >> 26732403

Statistical estimation of T1 relaxation times using conventional magnetic resonance imaging.

Amanda F Mejia1, Elizabeth M Sweeney2, Blake Dewey3, Govind Nair3, Pascal Sati3, Colin Shea3, Daniel S Reich2, Russell T Shinohara4.   

Abstract

Quantitative T1 maps estimate T1 relaxation times and can be used to assess diffuse tissue abnormalities within normal-appearing tissue. T1 maps are popular for studying the progression and treatment of multiple sclerosis (MS). However, their inclusion in standard imaging protocols remains limited due to the additional scanning time and expert calibration required and susceptibility to bias and noise. Here, we propose a new method of estimating T1 maps using four conventional MR images, which are intensity-normalized using cerebellar gray matter as a reference tissue and related to T1 using a smooth regression model. Using cross-validation, we generate statistical T1 maps for 61 subjects with MS. The statistical maps are less noisy than the acquired maps and show similar reproducibility. Tests of group differences in normal-appearing white matter across MS subtypes give similar results using both methods.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Image synthesis; Magnetic resonance imaging; Multiple sclerosis; T1 relaxation time

Mesh:

Year:  2015        PMID: 26732403      PMCID: PMC4889526          DOI: 10.1016/j.neuroimage.2015.12.037

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  49 in total

1.  Towards quantitative measurements of relaxation times and other parameters in the brain.

Authors:  P S Tofts; E P du Boulay
Journal:  Neuroradiology       Date:  1990       Impact factor: 2.804

2.  Evaluation of reference regions for (R)-[(11)C]PK11195 studies in Alzheimer's disease and mild cognitive impairment.

Authors:  Marc A Kropholler; Ronald Boellaard; Bart N M van Berckel; Alie Schuitemaker; Reina W Kloet; Mark J Lubberink; Cees Jonker; Philip Scheltens; Adriaan A Lammertsma
Journal:  J Cereb Blood Flow Metab       Date:  2007-04-04       Impact factor: 6.200

3.  High-resolution T1 mapping of the brain at 3T with driven equilibrium single pulse observation of T1 with high-speed incorporation of RF field inhomogeneities (DESPOT1-HIFI).

Authors:  Sean C L Deoni
Journal:  J Magn Reson Imaging       Date:  2007-10       Impact factor: 4.813

4.  N4ITK: improved N3 bias correction.

Authors:  Nicholas J Tustison; Brian B Avants; Philip A Cook; Yuanjie Zheng; Alexander Egan; Paul A Yushkevich; James C Gee
Journal:  IEEE Trans Med Imaging       Date:  2010-04-08       Impact factor: 10.048

5.  Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators.

Authors:  Amanda F Mejia; Mary Beth Nebel; Haochang Shou; Ciprian M Crainiceanu; James J Pekar; Stewart Mostofsky; Brian Caffo; Martin A Lindquist
Journal:  Neuroimage       Date:  2015-02-28       Impact factor: 6.556

6.  Deep gray matter and fatigue in MS: a T1 relaxation time study.

Authors:  G Niepel; Ch R Tench; P S Morgan; N Evangelou; D P Auer; C S Constantinescu
Journal:  J Neurol       Date:  2006-03-13       Impact factor: 4.849

7.  Evolution of cortical and thalamus atrophy and disability progression in early relapsing-remitting MS during 5 years.

Authors:  R Zivadinov; N Bergsland; O Dolezal; S Hussein; Z Seidl; M G Dwyer; M Vaneckova; J Krasensky; J A Potts; T Kalincik; E Havrdová; D Horáková
Journal:  AJNR Am J Neuroradiol       Date:  2013-04-11       Impact factor: 3.825

8.  Deep gray matter involvement on brain MRI scans is associated with clinical progression in multiple sclerosis.

Authors:  Mohit Neema; Ashish Arora; Brian C Healy; Zachary D Guss; Steven D Brass; Yang Duan; Guy J Buckle; Bonnie I Glanz; Lynn Stazzone; Samia J Khoury; Howard L Weiner; Charles R G Guttmann; Rohit Bakshi
Journal:  J Neuroimaging       Date:  2009-01       Impact factor: 2.486

9.  OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI.

Authors:  Elizabeth M Sweeney; Russell T Shinohara; Navid Shiee; Farrah J Mateen; Avni A Chudgar; Jennifer L Cuzzocreo; Peter A Calabresi; Dzung L Pham; Daniel S Reich; Ciprian M Crainiceanu
Journal:  Neuroimage Clin       Date:  2013-03-15       Impact factor: 4.881

10.  Multiple sclerosis deep grey matter: the relation between demyelination, neurodegeneration, inflammation and iron.

Authors:  Lukas Haider; Constantina Simeonidou; Günther Steinberger; Simon Hametner; Nikolaos Grigoriadis; Georgia Deretzi; Gabor G Kovacs; Alexandra Kutzelnigg; Hans Lassmann; Josa M Frischer
Journal:  J Neurol Neurosurg Psychiatry       Date:  2014-06-04       Impact factor: 10.154

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  5 in total

1.  Experimental design and sample size considerations in longitudinal magnetic resonance imaging-based biomarker detection for multiple sclerosis.

Authors:  Menghan Hu; Matthew K Schindler; Blake E Dewey; Daniel S Reich; Russell T Shinohara; Ani Eloyan
Journal:  Stat Methods Med Res       Date:  2020-02-19       Impact factor: 3.021

2.  A Spatio-Temporal Model for Longitudinal Image-on-Image Regression.

Authors:  Arnab Hazra; Brian J Reich; Daniel S Reich; Russell T Shinohara; Ana-Maria Staicu
Journal:  Stat Biosci       Date:  2017-10-23

3.  MIMoSA: An Automated Method for Intermodal Segmentation Analysis of Multiple Sclerosis Brain Lesions.

Authors:  Alessandra M Valcarcel; Kristin A Linn; Simon N Vandekar; Theodore D Satterthwaite; John Muschelli; Peter A Calabresi; Dzung L Pham; Melissa Lynne Martin; Russell T Shinohara
Journal:  J Neuroimaging       Date:  2018-03-08       Impact factor: 2.486

4.  A LAG FUNCTIONAL LINEAR MODEL FOR PREDICTION OF MAGNETIZATION TRANSFER RATIO IN MULTIPLE SCLEROSIS LESIONS.

Authors:  Gina-Maria Pomann; Ana-Maria Staicu; Edgar J Lobaton; Amanda F Mejia; Blake E Dewey; Daniel S Reich; Elizabeth M Sweeney; Russell T Shinohara
Journal:  Ann Appl Stat       Date:  2017-01-05       Impact factor: 1.959

5.  Joint Intensity Fusion Image Synthesis Applied to Multiple Sclerosis Lesion Segmentation.

Authors:  Greg M Fleishman; Alessandra Valcarcel; Dzung L Pham; Snehashis Roy; Peter A Calabresi; Paul Yushkevich; Russell T Shinohara; Ipek Oguz
Journal:  Brainlesion       Date:  2018-02-17
  5 in total

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