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

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

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

Conditions
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Idiopathic Interstitial Pneumonia

Intervention / Treatment
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* Radiation: high resolution CT


Participation Criteria
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Eligibility Criteria
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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.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 90 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Hormone sensitive group<br>Prednisone, 0.5mg/kgqd, 3-6months | Radiation: high resolution CT<br>* Ground glass，honeycomb，reticulation, consolidation<br>|
| Hormone insensitivity group<br>Prednisone, 0.5mg/kgqd, 3-6months | Radiation: high resolution CT<br>* Ground glass，honeycomb，reticulation, consolidation<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Hormone sensitivity, imaging features, artificial intelligence