Artificial Intelligent Image Processing and Diagnosis of Pulmonary Vessels in CT

NCT06589843 | Not Yet Recruiting

• 1 other identifier: NCCT-CTPA AI
• Study Type: observational
• Target: 15,000
• Locations: 0 countries
• Sites: N/A

Brief Summary

In this study, patients with chest pain, lung cancer, pulmonary embolism, and routine inpatient physical examination were selected as the research objects, and the experimental design of retrospective cohort study was adopted to carry out artificial intelligence analysis related to pulmonary vascular diseases in patients with multi-dimensional big data. The multi-modal CT acquisition process included plain scan CT(NCCT) and CT pulmonary angiography (CTPA). Ctpa-like image effects can be simulated or reconstructed by non-enhanced plain scan CT images, so that CTPA-like image quality can be obtained without injecting contrast agent. The synthetic CTPA images were further analyzed by artificial intelligence to assist doctors in the intelligent diagnosis of pulmonary vascular diseases.

Conditions

Radiology; Vascular Diseases

Outcome Measures

Primary Outcomes (1)

• The performance of deep enhanced imaging in lesion detection and diagnosis

  The performance of deep enhanced imaging in lesion detection and diagnosis, including imaging quality, accuracy, sensitivity and specificity in lesion detection and imaging diagnosis.

  2 year

Interventions

Deep learning imaging enhancement DIAGNOSTIC_TEST

Conventional imaging or down-sampling imaging from CT or MR are enhanced by approved deep learning method.

Eligibility Criteria

• Age: 18 Years - 100 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with chest pain, lung cancer, pulmonary embolism, and routine inpatient physical examination were studied

You may qualify if:

• Age ≥18≤100 years old Scan the pulmonary artery and its major branches Patients with suspected pulmonary embolism who received CTPA had a set of CTPA and CT scans The image quality meets the requirements of diagnosis and post-processing Patients who completed the examination in accordance with the data collection criteria Clinical data and follow-up were complete

You may not qualify if:

• Age \<18 years or age \>100 years The image is incomplete or incorrect Pulmonary artery absent or underenhanced Severe motion artifacts or image noise affect evaluation of pulmonary embolism History of aortic reconstruction, replacement, or stent implantation Congenital variations in the whole or important branches of the aorta in adults (e.g. bovine aortic arch, abnormal right subclavian artery) Severe hypovolemia and hemodynamic instability Severe heart failure with low ejection fraction Dialysis patient

Sponsors & Collaborators

• Xin Lou: lead

MeSH Terms

Conditions

Vascular Diseases

Condition Hierarchy (Ancestors)

Cardiovascular Diseases

Study Officials

• Xin Lou

  Chinese PLA General Hospital

  STUDY CHAIR

Central Study Contacts

Ling Liu

CONTACT

+8618601288132; 1179143043@qq.com

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Chairman

Study Record Dates

• First Submitted: September 6, 2024
• First Posted: September 19, 2024
• Study Start: September 10, 2024
• Primary Completion (Estimated): September 1, 2029
• Study Completion (Estimated): September 1, 2029
• Last Updated: September 19, 2024

Record last verified: 2024-09