Tokyo, Dec. 23 -- UMIN Clinical Trials Registry (UMIN-CTR) received information related to the study (UMIN000060169) titled 'Non-invasive Assessment of Pulmonary Circulation using Deep Learning on dynamic chest radiography' on Dec. 22.
Study Type:
Observational
Primary Sponsor:
Institute - Mie University Graduate School of Medicine
Condition:
Condition - Pulmonary vascular diseases
Classification by malignancy - Others
Genomic information - NO
Objective:
Narrative objectives1 - The objective of this study is to develop a deep learning based artificial intelligence model that enables minimally invasive and quantitative prediction of pulmonary circulatory hemodynamics using pulmonary circulation images derived from X ray fluoroscopic videos.
Basic objectives2 - Efficacy
Eligibility:
Age-lower limit - 20
years-old
<=
Age-upper limit - Not applicable
Gender - Male and Female
Key inclusion criteria - Patients aged 20 years or older who underwent right heart catheterization.
Key exclusion criteria - Pregnant women or women who may be pregnant.
Patients in whom acquisition of dynamic images is difficult due to inability to maintain a relatively regular cardiac rhythm, such as atrial fibrillation.
Target Size - 2000
Recruitment Status:
Recruitment status - Preinitiation
Date of protocol fixation - 2025 Year 12 Month 04 Day
Date of IRB - 2025 Year 12 Month 16 Day
Anticipated trial start date - 2025 Year 12 Month 24 Day
Last follow-up date - 2035 Year 12 Month 31 Day
To know more, visit https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000068800
Disclaimer: Curated by HT Syndication.
