Evidence map›Paper›PMID 26551261›Full record

ArticleNeuroImage2016

Automated retinofugal visual pathway reconstruction with multi-shell HARDI and FOD-based analysis.

Alexandra Kammen, Meng Law, Bosco S Tjan, Arthur W Toga, Yonggang Shi

Abstract read
In one paragraph

Article in NeuroImage, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Tractometry of Human Visual White Matter Pathways in Health and Disease.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024
    Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Parallel Transport Tractography.IEEE transactions on medical imaging · 2021
    Article
  13. Article
  14. Article
  15. Review
  16. Topographic Filtering of Tractograms as Vector Field Flows.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2019
    Article
  17. Article
  18. Article
  19. Article
  20. GIFE: Efficient and Robust Group-wise Isometric Fiber Embedding.Connectomics in neuroImaging : second international workshop, CNI 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 20, 2018 : proceedings. CNI (Workshop) (2nd : 2018 : Granada, Spain) · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Alexandra KammenLaboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA.
Meng LawDepartment of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA.
Bosco S TjanNeuroscience Graduate Program, University of Southern California, Los Angeles, CA 90089, USA; Department of Psychology, University of Southern California, Los Angeles, CA 90089, USA.
Arthur W TogaLaboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA.
Yonggang ShiLaboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA. Electronic address: yshi@loni.usc.edu.

Funding

VASCULAR RISK AND COGNITIVE STATUS IN A LATINO POPULATIONP50AG005142 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ARANDA, MARIA P. · 1985 to 2019
$41.0M
TR&D3: Intrinsic Surface MappingP41EB015922 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI VAN HORN, JOHN DARRELL · 2012 to 2022
$14.1M
Human Connectomes for Low Vision, Blindness, and Sight RestorationU01EY025864 · NEI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI AGUIRRE, GEOFFREY KARL, PATEL, VIVEK R. · 2015 to 2018
$4.0M
Intrinsic Modeling and Tracking of Neuroanatomy in Alzheimer's DiseaseK01EB013633 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI SHI, YONGGANG · 2012 to 2016
$833k
NEI NIH HHS U01 EY025864NEI NIH HHS U01EY025864NIA NIH HHS P50 AG005142NIA NIH HHS P50AG005142NIBIB NIH HHS K01 EB013633NIBIB NIH HHS K01EB013633NIBIB NIH HHS P41 EB015922NIBIB NIH HHS P41EB015922
6 · The paper itself

Abstract

Diffusion MRI tractography provides a non-invasive modality to examine the human retinofugal projection, which consists of the optic nerves, optic chiasm, optic tracts, the lateral geniculate nuclei (LGN) and the optic radiations. However, the pathway has several anatomic features that make it particularly challenging to study with tractography, including its location near blood vessels and bone-air interface at the base of the cerebrum, crossing fibers at the chiasm, somewhat-tortuous course around the temporal horn via Meyer's Loop, and multiple closely neighboring fiber bundles. To date, these unique complexities of the visual pathway have impeded the development of a robust and automated reconstruction method using tractography. To overcome these challenges, we develop a novel, fully automated system to reconstruct the retinofugal visual pathway from high-resolution diffusion imaging data. Using multi-shell, high angular resolution diffusion imaging (HARDI) data, we reconstruct precise fiber orientation distributions (FODs) with high order spherical harmonics (SPHARM) to resolve fiber crossings, which allows the tractography algorithm to successfully navigate the complicated anatomy surrounding the retinofugal pathway. We also develop automated algorithms for the identification of ROIs used for fiber bundle reconstruction. In particular, we develop a novel approach to extract the LGN region of interest (ROI) based on intrinsic shape analysis of a fiber bundle computed from a seed region at the optic chiasm to a target at the primary visual cortex. By combining automatically identified ROIs and FOD-based tractography, we obtain a fully automated system to compute the main components of the retinofugal pathway, including the optic tract and the optic radiation. We apply our method to the multi-shell HARDI data of 215 subjects from the Human Connectome Project (HCP). Through comparisons with post-mortem dissection measurements, we demonstrate the retinotopic organization of the optic radiation including a successful reconstruction of Meyer's loop. Then, using the reconstructed optic radiation bundle from the HCP cohort, we construct a probabilistic atlas and demonstrate its consistency with a post-mortem atlas. Finally, we generate a shape-based representation of the optic radiation for morphometry analysis.

Indexed as

AdultConnectomeDiffusion Tensor ImagingFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleVisual PathwaysYoung AdultFODHARDIMulti-shellRetinofugal pathwayTractographyVision

Identifiers

PMID26551261
PMCPMC4691391

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.