assessment of maxillary sinus wall thickness with paranasal sinus digital tomosynthesis and ct
Clicks: 324
ID: 157194
2017
Article Quality & Performance Metrics
Overall Quality
Improving Quality
0.0
/100
Combines engagement data with AI-assessed academic quality
Reader Engagement
Emerging Content
3.0
/100
10 views
10 readers
Trending
AI Quality Assessment
Not analyzed
Abstract
Purpose
This study was performed to compare paranasal sinus tomosynthesis with computed tomography (CT) imaging as a radiologic tool to evaluate the paranasal sinuses, using measurement of the soft tissue thickness of the maxillary sinus.
Materials and Methods
A total of 114 patients with sinusitis who underwent both paranasal sinus digital tomosynthesis (DT) and CT were enrolled in this retrospective study. Two observers independently assessed soft tissue thickness in both maxillary sinus chambers using both DT and CT images.
Results
The mean difference in soft tissue thickness measured by each observer was −0.31 mm on CT and 0.15 mm on DT. The mean differences in soft tissue thickness measured with DT and CT were −0.15 by observer 1 and −0.31 by observer 2. Evaluation of the agreement in measurement of soft tissue thickness in the maxillary sinus using DT and CT showed a high intraclass correlation, with the 95% limit of agreement ranging from −3.36 mm to 3.06 mm [intraclass correlation coefficient (ICC), 0.994: p<0.01] for observer 1 and from −5.56 mm to 4.95 mm (ICC, 0.984: p<0.01) for observer 2.
Conclusion
As an imaging tool, DT is comparable to CT for assessing the soft tissue thickness of maxillary sinuses in patients with sinusitis.
Abstract Quality Issue:
This abstract appears to be incomplete or contains metadata (154 words).
Try re-searching for a better abstract.
| Reference Key |
byun2017assessment
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Jieun Byun;Sung Shine Shim;Yookyung Kim;Kyoung Ae Kong |
| Journal | journal of chemical education |
| Year | 2017 |
| DOI |
https://doi.org/10.3348/jksr.2017.76.5.314
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.