Evidence map›Paper›PMID 34531630›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2021

Establishing Surface Correspondence for Post-surgical Cortical Thickness Changes in Temporal Lobe Epilepsy.

Yue Liu, Dario J Englot, Victoria L Morgan, Warren D Taylor, Ying Wei, Ipek Oguz, Bennett A Landman, Ilwoo Lyu

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Yue LiuCollege of Information Science and Engineering, Northeastern University, Shenyang, China.
Dario J EnglotNeurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA.
Victoria L MorganRadiology & Radiological Science, Vanderbilt University Medical Center, Nashville, TN, USA.
Warren D TaylorPsychiatry & Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
Ying WeiCollege of Information Science and Engineering, Northeastern University, Shenyang, China.
Ipek OguzElectrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.
Bennett A LandmanElectrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.
Ilwoo LyuElectrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.

Funding

Overall: Eunice Kennedy Shriver Intellectual and Developmental Disabilities Research Center at VanderbiltP50HD103537 · NICHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Lea K Davis · 2020 to 2026
$10.3M
Relating Vigilance to Connectivity and Neurocognition in Temporal Lobe EpilepsyR01NS112252 · NINDS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ENGLOT, DARIO J · 2019 to 2023
$3.0M
The Role of Network Connectivity in Post-Surgical Seizure Recurrence in Temporal Lobe EpilepsyR01NS110130 · NINDS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MORGAN, VICTORIA L · 2018 to 2023
$2.5M
MRI Connectivity Biomarkers of Treatment Response in Focal EpilepsyR01NS108445 · NINDS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MORGAN, VICTORIA L · 2019 to 2024
$2.5M
MRI Structural and Functional Connectivity Changes in Temporal Lobe EpilepsyR01NS075270 · NINDS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MORGAN, VICTORIA L · 2012 to 2016
$1.7M
Early detection of Huntington's Disease: Longitudinal analysis of basal ganglia and cortical thicknessR01NS094456 · NINDS · VANDERBILT UNIVERSITY · PI OGUZ, IPEK · 2016 to 2019
$1.3M
MULTIMODAL MAPPING OF SUBCORTICAL AND CORTICAL FUNCTIONAL NETWORK DISTURBANCES IN FOCAL EPILEPSYR00NS097618 · NINDS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ENGLOT, DARIO J · 2017 to 2019
$743k
NICHD NIH HHS P50 HD103537NINDS NIH HHS R00 NS097618NINDS NIH HHS R01 NS075270NINDS NIH HHS R01 NS094456NINDS NIH HHS R01 NS108445NINDS NIH HHS R01 NS110130NINDS NIH HHS R01 NS112252
6 · The paper itself

Abstract

In pre- and post-surgical surface shape analysis, establishing shape correspondence is necessary to investigate the postoperative surface changes. However, structural absence after the operation accompanies focal non-rigid changes, which leads to challenges in existing surface registration methods. In this paper, we present a fully automatic particle-based method to establish surface correspondence that can handle partial structural abnormality in the temporal lobe resection. Our method optimizes the coordinates of points which are modeled as particles on surfaces in a hierarchical way to reduce a chance of being trapped in a local minimum during the optimization. In the experiments, we evaluate the effectiveness of our method in comparison with conventional spherical registration (FreeSurfer) on two scenarios: cortical thickness changes in healthy controls within a short scan-rescan time window and patients with temporal lobe resection. The post-surgical scan is acquired at least 1 year after the presurgical scan. In region of interest-wise (ROI-wise) analysis, no changes on cortical thickness are found in both methods on the healthy control group. In patients, since there is no ground truth available, we instead investigated the disagreement between our method and FreeSurfer. We see poorly matched ROIs and large cortical thickness changes using FreeSurfer. On the contrary, our method shows well-matched ROIs and subtle cortical thickness changes. This suggests that the proposed method can establish a stable shape correspondence, which is not fully captured in a conventional spherical registration.

Indexed as

cortical thicknessshape correspondencesurfacetemporal lobe epilepsy

Identifiers

PMID34531630
PMCPMC8442832

What OpenQuestion holds

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Registered trials

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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.