Evidence map›Paper›PMID 34625872›Full record

ArticleInternational journal of computer assisted radiology and surgery2022

Validity and reliability of masseter muscles segmentation from the transverse sections of Cone-Beam CT scans compared with MRI scans.

Yichen Pan, Yinghui Wang, Gang Li, Si Chen, Tianmin Xu

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. 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.

Yichen PanDepartment of Orthodontics, Peking University School and Hospital of Stomatology, 22 Zhongguancun Avenue South, Haidian District, 100081, Beijing, People's Republic of China.
Yinghui WangDepartment of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology, 22 Zhongguancun Avenue South, Haidian District, Beijing, 100081, People's Republic of China.
Gang LiDepartment of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology, 22 Zhongguancun Avenue South, Haidian District, Beijing, 100081, People's Republic of China.
Si ChenDepartment of Orthodontics, Peking University School and Hospital of Stomatology, 22 Zhongguancun Avenue South, Haidian District, 100081, Beijing, People's Republic of China. elisa02@163.com.
Tianmin XuDepartment of Orthodontics, Peking University School and Hospital of Stomatology, 22 Zhongguancun Avenue South, Haidian District, 100081, Beijing, People's Republic of China. tmxuortho@163.com.

Funding

beijing natural science foundation 7192227national natural science foundation of china 81200806national natural science foundation of china 81671034peking university medicine seed fund for interdisciplinary research BMU 2018MI013
6 · The paper itself

Abstract

backgroundTo evaluate the validity and reliability of cone-beam computed tomography (CBCT) masseter muscle segmentation by comparing with the magnetic resonance imaging (MRI) masseter muscle segmentation of the same patients.

methodsSeventeen volunteers were included in this study. CBCT and MRI scans of the volunteers were taken, respectively, within one month. The masseter muscles in the CBCT scans were segmented by a generative adversarial network (GAN)-based framework combined with manual check. The masseter muscles in the MRI scans were segmented manually. The segmentations were repeated by the first examiner and a second examiner. For cross-sectional area (CSA), paired t-test, intraclass correlation coefficient (ICC) and standard error of measurement (SEM) were calculated to evaluate the validity and reliability of the segmentations. The validity and reliability were also calculated by Dice similarity coefficient (DSC) and average Hausdorff distance (aHD) between different segmentations. Seventeen volunteers were included in this study. CBCT and MRI scans of the volunteers were taken, respectively, within one month. The masseter muscles in the CBCT scans were segmented by a generative adversarial network (GAN)-based framework combined with manual check. The masseter muscles in the MRI scans were segmented manually. The segmentations were repeated by the first examiner and a second examiner. For cross-sectional area (CSA), paired t-test, intraclass correlation coefficient (ICC) and standard error of measurement (SEM) were calculated to evaluate the validity and reliability of the segmentations. The validity and reliability were also calculated by Dice similarity coefficient (DSC) and average Hausdorff distance (aHD) between different segmentations.

resultsPaired t-test showed that there was no significant difference in CSA between CBCT and MRI masseter segmentations. The ICCs were all larger than 0.95 and the SEM was less than 4.85 mm

conclusionMasseter muscle segmentation from CBCT scans was not significantly different from the segmentation from MRI scans. CBCT muscle segmentation showed great validity compared with MRI scans, and great reliability in retests.

Indexed as

Image Processing, Computer-AssistedMasseter MuscleCone-Beam Computed TomographyHumansMagnetic Resonance ImagingReproducibility of ResultsComputer-assisted image processingCone-beam computed tomographyMagnetic resonance imagingMasseter muscleReliability and validity

Identifiers

PMID34625872

What OpenQuestion holds

Textmetadata
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.