Literature DB >> 28371107

Using clinically acquired MRI to construct age-specific ADC atlases: Quantifying spatiotemporal ADC changes from birth to 6-year old.

Yangming Ou1,2,3,4, Lilla Zöllei2, Kallirroi Retzepi1,2, Victor Castro5,6, Sara V Bates7, Steve Pieper8, Katherine P Andriole9, Shawn N Murphy5,6, Randy L Gollub1,2, Patricia Ellen Grant4.   

Abstract

Diffusion imaging is critical for detecting acute brain injury. However, normal apparent diffusion coefficient (ADC) maps change rapidly in early childhood, making abnormality detection difficult. In this article, we explored clinical PACS and electronic healthcare records (EHR) to create age-specific ADC atlases for clinical radiology reference. Using the EHR and three rounds of multiexpert reviews, we found ADC maps from 201 children 0-6 years of age scanned between 2006 and 2013 who had brain MRIs with no reported abnormalities and normal clinical evaluations 2+ years later. These images were grouped in 10 age bins, densely sampling the first 1 year of life (5 bins, including neonates and 4 quarters) and representing the 1-6 year age range (an age bin per year). Unbiased group-wise registration was used to construct ADC atlases for 10 age bins. We used the atlases to quantify (a) cross-sectional normative ADC variations; (b) spatiotemporal heterogeneous ADC changes; and (c) spatiotemporal heterogeneous volumetric changes. The quantified age-specific whole-brain and region-wise ADC values were compared to those from age-matched individual subjects in our study and in multiple existing independent studies. The significance of this study is that we have shown that clinically acquired images can be used to construct normative age-specific atlases. These first of their kind age-specific normative ADC atlases quantitatively characterize changes of myelination-related water diffusion in the first 6 years of life. The quantified voxel-wise spatiotemporal ADC variations provide standard references to assist radiologists toward more objective interpretation of abnormalities in clinical images. Our atlases are available at https://www.nitrc.org/projects/mgh_adcatlases. Hum Brain Mapp 38:3052-3068, 2017.
© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  atlas construction; big data informatics; clinical images; diffusion MRI; neurodevelopment

Mesh:

Year:  2017        PMID: 28371107      PMCID: PMC5426959          DOI: 10.1002/hbm.23573

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


  76 in total

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Journal:  Neuroimage       Date:  2011-01-26       Impact factor: 6.556

2.  Quantitative apparent diffusion coefficient measurements in term neonates for early detection of hypoxic-ischemic brain injury: initial experience.

Authors:  R L Wolf; R A Zimmerman; R Clancy; J H Haselgrove
Journal:  Radiology       Date:  2001-03       Impact factor: 11.105

3.  Unbiased average age-appropriate atlases for pediatric studies.

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Journal:  Neuroimage       Date:  2010-07-23       Impact factor: 6.556

Review 4.  Neuroimaging of the Philadelphia neurodevelopmental cohort.

Authors:  Theodore D Satterthwaite; Mark A Elliott; Kosha Ruparel; James Loughead; Karthik Prabhakaran; Monica E Calkins; Ryan Hopson; Chad Jackson; Jack Keefe; Marisa Riley; Frank D Mentch; Patrick Sleiman; Ragini Verma; Christos Davatzikos; Hakon Hakonarson; Ruben C Gur; Raquel E Gur
Journal:  Neuroimage       Date:  2013-08-03       Impact factor: 6.556

5.  Highly accurate segmentation of brain tissue and subcortical gray matter from newborn MRI.

Authors:  Neil I Weisenfeld; Andrea U J Mewes; Simon K Warfield
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Review 6.  The growth rate and size of the mastoid air cell system and mastoid bone: a review and reference.

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Journal:  Eur Arch Otorhinolaryngol       Date:  2009-03-13       Impact factor: 2.503

7.  Diffusion tensor imaging assessment of brain white matter maturation during the first postnatal year.

Authors:  James M Provenzale; Luxia Liang; David DeLong; Leonard E White
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8.  Infant brain atlases from neonates to 1- and 2-year-olds.

Authors:  Feng Shi; Pew-Thian Yap; Guorong Wu; Hongjun Jia; John H Gilmore; Weili Lin; Dinggang Shen
Journal:  PLoS One       Date:  2011-04-14       Impact factor: 3.240

9.  Age-specific average head template for typically developing 6-month-old infants.

Authors:  Lisa F Akiyama; Todd R Richards; Toshiaki Imada; Stephen R Dager; Liv Wroblewski; Patricia K Kuhl
Journal:  PLoS One       Date:  2013-09-12       Impact factor: 3.240

10.  The construction of MRI brain/head templates for Chinese children from 7 to 16 years of age.

Authors:  Wanze Xie; John E Richards; Du Lei; Hongyan Zhu; Kang Lee; Qiyong Gong
Journal:  Dev Cogn Neurosci       Date:  2015-08-28       Impact factor: 6.464

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  14 in total

1.  Voxelwise and Regional Brain Apparent Diffusion Coefficient Changes on MRI from Birth to 6 Years of Age.

Authors:  Susan Sotardi; Randy L Gollub; Sara V Bates; Rebecca Weiss; Shawn N Murphy; P Ellen Grant; Yangming Ou
Journal:  Radiology       Date:  2020-12-08       Impact factor: 11.105

2.  Field of View Normalization in Multi-Site Brain MRI.

Authors:  Yangming Ou; Lilla Zöllei; Xiao Da; Kallirroi Retzepi; Shawn N Murphy; Elizabeth R Gerstner; Bruce R Rosen; P Ellen Grant; Jayashree Kalpathy-Cramer; Randy L Gollub
Journal:  Neuroinformatics       Date:  2018-10

Review 3.  Fetal brain growth portrayed by a spatiotemporal diffusion tensor MRI atlas computed from in utero images.

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Journal:  Neuroimage       Date:  2018-08-30       Impact factor: 6.556

Review 4.  A Role for Data Science in Precision Nutrition and Early Brain Development.

Authors:  Sarah U Morton; Brian J Leyshon; Eleonora Tamilia; Rutvi Vyas; Michaela Sisitsky; Imran Ladha; John B Lasekan; Matthew J Kuchan; P Ellen Grant; Yangming Ou
Journal:  Front Psychiatry       Date:  2022-06-23       Impact factor: 5.435

Review 5.  How Machine Learning is Powering Neuroimaging to Improve Brain Health.

Authors:  Nalini M Singh; Jordan B Harrod; Sandya Subramanian; Mitchell Robinson; Ken Chang; Suheyla Cetin-Karayumak; Adrian Vasile Dalca; Simon Eickhoff; Michael Fox; Loraine Franke; Polina Golland; Daniel Haehn; Juan Eugenio Iglesias; Lauren J O'Donnell; Yangming Ou; Yogesh Rathi; Shan H Siddiqi; Haoqi Sun; M Brandon Westover; Susan Whitfield-Gabrieli; Randy L Gollub
Journal:  Neuroinformatics       Date:  2022-03-28

6.  Multi-channel attention-fusion neural network for brain age estimation: Accuracy, generality, and interpretation with 16,705 healthy MRIs across lifespan.

Authors:  Sheng He; Diana Pereira; Juan David Perez; Randy L Gollub; Shawn N Murphy; Sanjay Prabhu; Rudolph Pienaar; Richard L Robertson; P Ellen Grant; Yangming Ou
Journal:  Med Image Anal       Date:  2021-04-30       Impact factor: 13.828

7.  Mining multi-site clinical data to develop machine learning MRI biomarkers: application to neonatal hypoxic ischemic encephalopathy.

Authors:  Rebecca J Weiss; Sara V Bates; Ya'nan Song; Yue Zhang; Emily M Herzberg; Yih-Chieh Chen; Maryann Gong; Isabel Chien; Lily Zhang; Shawn N Murphy; Randy L Gollub; P Ellen Grant; Yangming Ou
Journal:  J Transl Med       Date:  2019-11-21       Impact factor: 5.531

8.  Correlations between apparent diffusion coefficient values of WB-DWI and clinical parameters in multiple myeloma.

Authors:  Bei Zhang; Bingyang Bian; Zhiwei Zhao; Fang Lin; Zining Zhu; Mingwu Lou
Journal:  BMC Med Imaging       Date:  2021-06-08       Impact factor: 1.930

9.  Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts.

Authors:  Ralica Dimitrova; Sophie Arulkumaran; Olivia Carney; Andrew Chew; Shona Falconer; Judit Ciarrusta; Thomas Wolfers; Dafnis Batalle; Lucilio Cordero-Grande; Anthony N Price; Rui P A G Teixeira; Emer Hughes; Alexia Egloff; Jana Hutter; Antonios Makropoulos; Emma C Robinson; Andreas Schuh; Katy Vecchiato; Johannes K Steinweg; Russell Macleod; Andre F Marquand; Grainne McAlonan; Mary A Rutherford; Serena J Counsell; Stephen M Smith; Daniel Rueckert; Joseph V Hajnal; Jonathan O'Muircheartaigh; A David Edwards
Journal:  Cereb Cortex       Date:  2021-07-05       Impact factor: 5.357

10.  Modelling brain development to detect white matter injury in term and preterm born neonates.

Authors:  Jonathan O'Muircheartaigh; Emma C Robinson; Maximillian Pietsch; Thomas Wolfers; Paul Aljabar; Lucilio Cordero Grande; Rui P A G Teixeira; Jelena Bozek; Andreas Schuh; Antonios Makropoulos; Dafnis Batalle; Jana Hutter; Katy Vecchiato; Johannes K Steinweg; Sean Fitzgibbon; Emer Hughes; Anthony N Price; Andre Marquand; Daniel Reuckert; Mary Rutherford; Joseph V Hajnal; Serena J Counsell; A David Edwards
Journal:  Brain       Date:  2020-02-01       Impact factor: 13.501

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