Evaluation of the image quality of deep learning image reconstruction on low-dose and ultralow dose chest CT

Prospective evaluation of the performance of deep learning image reconstruction on low-dose and ultralow dose chest CT

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

CRIS

Registry ID

KCT0004692

Enrollment

Registered

2020-02-04

Start date

2020-02-11

Completion date

Unknown

Last updated

2021-01-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

Medical Device : Participants who plan to undergo a low dose chest CT scan will undergo additional an ultra-low-dose chest CT scan immediately after the low dose CT scan.

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: (1) Adults with the age of 20 or older. (2) Patients who visit the pulmonology outpatient clinic for respiratory disease.

Exclusion criteria

Exclusion criteria: (1) Pregnant women (2) Chest CT scan not possible due to breathing difficulty (3) Patients who have undergone surgery or procedure that may affect chest CT image quality, including central venous tube, implantable cardioverter-defibrillator, and valve replacement. (4) BMI over 30

Design outcomes

Primary

Measure	Time frame
Objective image quality assessment - noise measurement, lung nodule evaluation	—

Secondary

Measure	Time frame
Subjective image quality assessment - 5 point grading of image quality by radiologists;Radiation dose evaluation - CTDIvol, DLP, estimated effective radiation dose	—

Countries

Korea, Republic of

Contacts

Public ContactSoon Ho Yoon

Seoul National University Hospital

Outcome results