Evidence map›Paper›PMID 26743921›Full record

ArticleChild's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery2016

Computer-assisted shape descriptors for skull morphology in craniosynostosis.

Kyu Won Shim, Min Jin Lee, Myung Chul Lee, Eun Kyung Park, Dong Seok Kim, Helen Hong, Yong Oock Kim

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In one paragraph

Article in Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 20% of its field
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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Review
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

7 authors at 3 institutions in 1 country.

Kyu Won ShimDepartment of Pediatric Neurosurgery, Craniofacial Reforming and Reconstruction Clinic, Yonsei University College of Medicine, Severance Children's Hospital, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Korea.
Min Jin LeeDepartment of Multimedia Engineering, Seoul Women's University, 621 Hwarangro Nowon-gu, Seoul, 01797, Korea.
Myung Chul LeeDepartment of Plastic and Reconstructive Surgery, Konkuk University School of Medicine, 120-1 Neungdong-ro Gwangjin-gu, Seoul, 05030, Korea.
Eun Kyung ParkDepartment of Pediatric Neurosurgery, Craniofacial Reforming and Reconstruction Clinic, Yonsei University College of Medicine, Severance Children's Hospital, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Korea.
Dong Seok KimDepartment of Pediatric Neurosurgery, Craniofacial Reforming and Reconstruction Clinic, Yonsei University College of Medicine, Severance Children's Hospital, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Korea.
Helen HongDepartment of Multimedia Engineering, Seoul Women's University, 621 Hwarangro Nowon-gu, Seoul, 01797, Korea. hlhong@swu.ac.kr.
Yong Oock KimDepartment of Plastic and Reconstructive Surgery, Craniofacial Reforming and Reconstruction Clinic, Yonsei University College of Medicine, Severance Hospital, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Korea. sgm625@yuhs.ac.
Yonsei University · KRSeoul Women's University · KRKonkuk University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeOur aim was to develop a novel method for characterizing common skull deformities with high sensitivity and specificity, based on two-dimensional (2D) shape descriptors in computed tomography (CT) images.

methodsBetween 2003 and 2014, 44 normal subjects and 39 infants with craniosynostosis (sagittal, 29; bicoronal, 10) enrolled for analysis. Mean age overall was 16 months (range, 1-120 months), with a male:female ratio of 56:29. Two reference planes, sagittal (S-plane: through top of lateral ventricle) and coronal (C-plane: at maximum dimension of fourth ventricle), were utilized to formulate three 2D shape descriptors (cranial index [CI], cranial radius index [CR], and cranial extreme spot index [CES]), which were then applied to S- and C-plane target images of both groups.

resultsIn infants with sagittal craniosynostosis, CI in S-plane (S-CI) usually was <1.0 (mean, 0.78; range, 0.67-0.95), with CR consistently at 3 and a characteristic CES pattern of two discrete hot spots oriented diagonally. In the bicoronal craniosynostosis subset, CI was >1.0 (mean 1.11; range, 1.04-1.25), with CR at -3 and a CES pattern of four discrete diagonally oriented hot spots. Scatter plots underscored the highly intuitive joint performance of CI and CES in distinguishing normal and deformed states. Altogether, these novel 2D shape descriptors enabled effective discrimination of sagittal and bicoronal skull deformities.

conclusionsNewly developed 2D shape descriptors for cranial CT imaging enabled recognition of common skull deformities with statistical significance, perhaps providing impetus for automated CT-based diagnosis of craniosynostosis.

Indexed as

CephalometryChildChild, PreschoolCraniosynostosesFemaleHumansImaging, Three-DimensionalInfantMaleSkullTomography, X-Ray ComputedCranial indexCranial spectrumCraniosynostosisScaphocephaly severity indexShape descriptor

Identifiers

PMID26743921
OpenAlexW2222191267

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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.