Diagnosis of pleural adhesion using dynamic-ventilation CT

JRCT ID: jRCTs072180070

Registered date:20/03/2019

Basic Information

• Recruitment status: Complete
• Health condition(s) or Problem(s) studied: Pleaural adhesion
• Date of first enrollment: 18/01/2018
• Target sample size: 300
• Study type: Interventional
• Intervention(s): Undergoing dynamic-ventilation CT

Outcome(s)

Primary Outcome

1 diagnostic accuracy of dynamic-ventilation CT under free breathing for detecting pleural adhesions, including comparisons and investigations with general chest CT
2 diagnostic accuracy of dynamic-ventilation CT under free breathing for detecting pleural adhesions/invasions by subpleural lung cancer, including comparisons and investigations with general chest CT

Secondary Outcome

1 assessment of radiation exposure by dynamic-ventilation CT
2 influence of various lung diseases on respiratory movement
3 diagnostic accuracy of pleural adhesions in patients with probable pleuritis
4 preverance of pleural adhesions and imaging findings
5 characteristics of the patients who cannot be diagnosed with pleural adhesions on dynamic-ventilation CT
6 relationships of the data from dynamic-ventilation CT with conventional pulmonary function tests

Key inclusion & exclusion criteria

• Age minimum: >= 20age old
• Age maximum: Not applicable
• Gender: Both

Include criteria

1) Patients who are planned to receive a surgical operation by thoracic surgeons
2) Patients who will undergo preoperative chest CT
3) Adult patients (20 years-old or older)

• Exclude criteria: 1) Patients who are younger than 20 years-old, disagree for or withdraw informed consent. 2) Patients who cannot complete dynamic-ventilation CT. 3) Patients who have medical devices in the targeted pleural cavity. 4) Patients who have metallic devices that make severe artifacts on CT

Related Information

• Primary Sponsor: Yamashiro Tsuneo
• Source(s) of Monetary Support: Canon Medical Systems CT Development Division