The Relationship Between Hormone Sensitivity and Imaging of Idiopathic Interstitial Pneumonia by Artificial Intelligence

Idiopathic Interstitial Pneumonia Clinical Trial

— IIP  

Official title:

The Relationship Between Hormone Sensitivity and Imaging of Idiopathic Interstitial Pneumonia by Artificial Intelligence

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05146934
• Other study ID #: LM2019173
• Status: Completed
• Start date: December 30, 2019
• Est. completion date: June 30, 2021

Study information

• Verified date: June 2021
• Source: Peking University Third Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Application of artificial intelligence deep learning algorithm to analyze the relationship between hormone sensitivity of idiopathic interstitial pneumonia and imaging features of high resolution CT.

Description:

Methods: the medical records and chest high-resolution CT images of patients with idiopathic interstitial pneumonia admitted to the respiratory department of the Third Hospital of Peking University from June 1, 2012 to December 31, 2020 were retrospectively analyzed.Application of artificial intelligence deep learning neural convolution network method to create recognition technology of different imaging features.Including ground glass, mesh, honeycomb, nodule or consolidation, the model was established. IIP patients were divided into hormone sensitive group and hormone insensitive group according to whether the use of hormone was effective or not.Logistic regression analysis was used to analyze the correlation between statistically significant parameters and hormone sensitivity.Artificial intelligence was used to establish the correlation model between imaging features and clinical data and hormone sensitivity.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 150
• Est. completion date: June 30, 2021
• Est. primary completion date: June 1, 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 90 Years

Eligibility

Inclusion Criteria:

Clinical-pathological-radiology diagnosis of idiopathic interstitial pneumonia Hormone therapy was used; The follow-up data were complete, and the effect of hormone use could be judged. Exclusion Criteria: Lung infection disease; Heart failure; Connective tissue disease; IIP Without hormone therapy ; IIP but the follow-up data were incomplete, and the effect of hormone use could not be judged.

Related Conditions & MeSH terms

• Hypersensitivity
• Idiopathic Interstitial Pneumonia
• Idiopathic Interstitial Pneumonias
• Lung Diseases, Interstitial
• Pneumonia
• Pulmonary Fibrosis

Intervention

Radiation:
• high resolution CT
Ground glass,honeycomb,reticulation, consolidation

Locations

Country	Name	City	State
China	Peking University Third Hospital	Beijing	Beijing

Sponsors (1)

Lead Sponsor	Collaborator
Peking University Third Hospital

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	development of artificial intelligence algorithm model	The U-net method of deep learning convolutional neural network (CNN) was used to create the recognition model of different imaging features. Imaging features include ground-glass opacity, reticulation, honeycomb and consolidation. With the area ratio of imaging features of the two groups as the input and hormone efficacy as the output, the correlation model between imaging features and hormone sensitivity was established by using artificial intelligence k nearest neighbor (KNN) algorithm and support vector machine (SVM) algorithm.	3-6 months after medication
Primary	clinical data and imaging feature ratios in both groups	clinical data including ages,gender,symptoms,signs,smoking history,complications,laboratory examination,lung function. Imaging feature including ground-glass opacity, reticulation, honeycomb and consolidation.	3-6 months after medication
Secondary	the relationship between imaging feature ratios and hormone sensibility	Logistic regression analyzing the relationship between imaging feature ratios and hormone sensibility.	3-6 months after medication