2020
DOI: 10.1177/1753466620968496
|View full text |Cite
|
Sign up to set email alerts
|

HRCT evaluation of patients with interstitial lung disease: comparison of the 2018 and 2011 diagnostic guidelines

Abstract: Background and aims: Chest high-resolution computed tomography (HRCT) is the central diagnostic tool in discerning idiopathic pulmonary fibrosis (IPF) from other interstitial lung disease (ILDs). In 2018, new guidelines were published and the nomenclature for HRCT interpretation was changed. We sought to evaluate how clinicians’ interpretation would change based on reading HRCTs under the framework of the old versus new categorization. Materials and methods: We collated HRCTs from 50 random cases evaluated in … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
11
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
10

Relationship

0
10

Authors

Journals

citations
Cited by 16 publications
(11 citation statements)
references
References 15 publications
(22 reference statements)
0
11
0
Order By: Relevance
“…In the classification process, the HRCT images are regarded as a complete knowledge system, the classification is performed according to the unique medical attribute and image pixel attribute "knowledge" of HRCT, the HRCT images are segmented into different regions, and the image enhancement processing is performed to highlight the local target region. The large amount of data information contained in the HRCT is reduced to obtain relatively small image data without affecting the quality of the target region in the image, assisting the physician to locate the region of interest until the accurate quantitative analysis, which can greatly improve the accuracy and accuracy of clinical diagnosis [14]. The approach involved in the algorithm is the conditional attribute S is defined according to Equation (1).…”
Section: Basic Methods Of Image Enhancement Algorithmmentioning
confidence: 99%
“…In the classification process, the HRCT images are regarded as a complete knowledge system, the classification is performed according to the unique medical attribute and image pixel attribute "knowledge" of HRCT, the HRCT images are segmented into different regions, and the image enhancement processing is performed to highlight the local target region. The large amount of data information contained in the HRCT is reduced to obtain relatively small image data without affecting the quality of the target region in the image, assisting the physician to locate the region of interest until the accurate quantitative analysis, which can greatly improve the accuracy and accuracy of clinical diagnosis [14]. The approach involved in the algorithm is the conditional attribute S is defined according to Equation (1).…”
Section: Basic Methods Of Image Enhancement Algorithmmentioning
confidence: 99%
“…However, their sample included normal examinations, which could have increased the level of agreement among the raters. In another study that analyzed interobserver agreement based on the most recent (2018) Fleischner Society criteria, the authors found only moderate agreement (κ = 0.50) among six ILD experts, although only one of them was a chest radiologist, the five other raters being pulmonologists ( 15 ) .…”
Section: Discussionmentioning
confidence: 99%
“…According to the 2018 New Evidence-based Guidelines for Diagnosis and Treatment of IPF [ 31 ], High-Resolution CT (HRCT) is the most important way to diagnose IPF at present [ 32 ]. The HRCT of the subjects before and after the trial is evaluated according to the “HRCT Efficacy Evaluation Table” and “HRCT Clinical Symptoms and Signs Efficacy Evaluation Table”.…”
Section: Methodsmentioning
confidence: 99%