Literature DB >> 29392245

EMR-Radiological Phenotypes in Diseases of the Optic Nerve and their Association with Visual Function.

Shikha Chaganti1, Jamie R Robinson2, Camilo Bermudez3, Thomas Lasko4, Louise A Mawn5, Bennett A Landman6.   

Abstract

Multi-modal analyses of diseases of the optic nerve, that combine radiological imaging with other electronic medical records (EMR), improve understanding of visual function. We conducted a study of 55 patients with glaucoma and 32 patients with thyroid eye disease (TED). We collected their visual assessments, orbital CT imaging, and EMR data. We developed an image-processing pipeline that segmented and extracted structural metrics from CT images. We derive EMR phenotype vectors with the help of PheWAS (from diagnostic codes) and ProWAS (from treatment codes). Next, we performed a principal component analysis and multiple-correspondence analysis to identify their association with visual function scores. We find that structural metrics derived from CT imaging are significantly associated with functional visual score for both glaucoma (R2=0.32) and TED (R2=0.4). Addition of EMR phenotype vectors to the model significantly improved (p<1E-04) the R2 to 0.4 for glaucoma and 0.54 for TED.

Entities:  

Keywords:  CT imaging; EMR; MCA; Optic nerve; PCA; Regression

Year:  2017        PMID: 29392245      PMCID: PMC5790176          DOI: 10.1007/978-3-319-67558-9_43

Source DB:  PubMed          Journal:  Deep Learn Med Image Anal Multimodal Learn Clin Decis Support (2017)


  8 in total

1.  Structural-Functional Relationships Between Eye Orbital Imaging Biomarkers and Clinical Visual Assessments.

Authors:  Xiuya Yao; Shikha Chaganti; Kunal P Nabar; Katrina Nelson; Andrew Plassard; Rob L Harrigan; Louise A Mawn; Bennett A Landman
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2017-02-24

2.  Variation in electronic health record adoption and readiness for meaningful use: 2008-2011.

Authors:  Vaishali Patel; Eric Jamoom; Chun-Ju Hsiao; Michael F Furukawa; Melinda Buntin
Journal:  J Gen Intern Med       Date:  2013-02-01       Impact factor: 5.128

3.  The rise of electronic health record adoption among family physicians.

Authors:  Imam M Xierali; Chun-Ju Hsiao; James C Puffer; Larry A Green; Jason C B Rinaldo; Andrew W Bazemore; Mathew T Burke; Robert L Phillips
Journal:  Ann Fam Med       Date:  2013 Jan-Feb       Impact factor: 5.166

4.  The economic burden of major adult visual disorders in the United States.

Authors:  David B Rein; Ping Zhang; Kathleen E Wirth; Paul P Lee; Thomas J Hoerger; Nancy McCall; Ronald Klein; James M Tielsch; Sandeep Vijan; Jinan Saaddine
Journal:  Arch Ophthalmol       Date:  2006-12

5.  Structural Functional Associations of the Orbit in Thyroid Eye Disease: Kalman Filters to Track Extraocular Rectal Muscles.

Authors:  Shikha Chaganti; Katrina Nelson; Kevin Mundy; Yifu Luo; Robert L Harrigan; Steve Damon; Daniel Fabbri; Louise Mawn; Bennett Landman
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2016-03-21

6.  Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain.

Authors:  B B Avants; C L Epstein; M Grossman; J C Gee
Journal:  Med Image Anal       Date:  2007-06-23       Impact factor: 8.545

7.  Non-local statistical label fusion for multi-atlas segmentation.

Authors:  Andrew J Asman; Bennett A Landman
Journal:  Med Image Anal       Date:  2012-11-29       Impact factor: 8.545

8.  Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data.

Authors:  Joshua C Denny; Lisa Bastarache; Marylyn D Ritchie; Robert J Carroll; Raquel Zink; Jonathan D Mosley; Julie R Field; Jill M Pulley; Andrea H Ramirez; Erica Bowton; Melissa A Basford; David S Carrell; Peggy L Peissig; Abel N Kho; Jennifer A Pacheco; Luke V Rasmussen; David R Crosslin; Paul K Crane; Jyotishman Pathak; Suzette J Bielinski; Sarah A Pendergrass; Hua Xu; Lucia A Hindorff; Rongling Li; Teri A Manolio; Christopher G Chute; Rex L Chisholm; Eric B Larson; Gail P Jarvik; Murray H Brilliant; Catherine A McCarty; Iftikhar J Kullo; Jonathan L Haines; Dana C Crawford; Daniel R Masys; Dan M Roden
Journal:  Nat Biotechnol       Date:  2013-12       Impact factor: 54.908

  8 in total
  4 in total

1.  AI in MRI: A case for grassroots deep learning.

Authors:  Kurt G Schilling; Bennett A Landman
Journal:  Magn Reson Imaging       Date:  2019-07-05       Impact factor: 2.546

2.  Anatomical context improves deep learning on the brain age estimation task.

Authors:  Camilo Bermudez; Andrew J Plassard; Shikha Chaganti; Yuankai Huo; Katherine S Aboud; Laurie E Cutting; Susan M Resnick; Bennett A Landman
Journal:  Magn Reson Imaging       Date:  2019-06-24       Impact factor: 2.546

3.  Contextual Deep Regression Network for Volume Estimation in Orbital CT.

Authors:  Shikha Chaganti; Cam Bermudez; Louise A Mawn; Thomas Lasko; Bennett A Landman
Journal:  Med Image Comput Comput Assist Interv       Date:  2019-10-10

4.  pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis.

Authors:  Cailey I Kerley; Shikha Chaganti; Tin Q Nguyen; Camilo Bermudez; Laurie E Cutting; Lori L Beason-Held; Thomas Lasko; Bennett A Landman
Journal:  Neuroinformatics       Date:  2022-01-03
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.