Using CT scans to predict outcomes after lung blood clots

This trial studies a tool that uses CT scan results and heart blood tests to predict the chance of serious outcomes after an acute pulmonary embolism (a blood clot in the lung). It may help doctors identify higher-risk patients sooner.

This study uses artificial intelligence to look at CT scans of the lungs to help find blood clots (pulmonary embolism). By participating, you help improve how these scans are read, which may lead to faster and more accurate diagnosis in the future.

This study uses artificial intelligence to look at imaging scans from people who might have a pulmonary embolism (a blood clot in the lungs). It aims to help doctors better diagnose and treat this condition.

This study tests a new, non-invasive imaging method called pulsatile electrical impedance tomography (EIT) to help diagnose and monitor acute pulmonary embolism (blood clots in the lungs). It may provide a faster or safer way to detect clots compared to standard CT scans, especially for patients who cannot have contrast dye.

This study tests a new type of CT scan (photon-counting CT) to see if it's better at finding small blood clots in the lungs. If you have symptoms like sudden shortness of breath, chest pain, or fainting and doctors suspect a blood clot, this trial may help confirm the diagnosis with clearer images.

This study looks at people with interstitial lung disease (a lung scarring condition) who have new or worsening symptoms that might be caused by a blood clot in the lungs (pulmonary embolism). Doctors want to find better ways to predict which patients actually have a clot, which could lead to earlier and more accurate treatment.