Validity of Pleural Effusion Detection Software

Pleural Effusion Clinical Trial

Official title:

A Study to Evaluate Accuracy and Validity of Chang Gung Pleural Effusion Detection Software Compared With Reference by Qualified Physicians

Clinical Trial Details — Status: Enrolling by invitation

Administrative data

• NCT number: NCT05903287
• Other study ID #: 202300606A5
• Status: Enrolling by invitation
• Start date: June 17, 2023
• Est. completion date: August 12, 2024

Study information

• Verified date: June 2023
• Source: Chang Gung Memorial Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The Chang Gung Pleural Effusion Detection Software is a medical software that can automatically detect whether there is a pleural effusion in Chest X-Ray. The purpose of this study is to verify whether the Chang Gung Pleural Effusion Detection Software can correctly identify patients with pleural effusion in Chest X-Ray. The results of the software analysis will be used for the performance of the software on the primary and secondary outcomes.

Description:

This clinical trial is a retrospective study. DICOM images of de-identified Chest X-Ray were collected from 6 hospitals of Chang Gung Memorial Hospital from January 1, 2018 to December 31, 2020. After confirming that the Chest X-Ray that meet the inclusion and exclusion criteria are correct, 282 samples will be sampled for this test, including 141 images with pleural effusion and 141 images without pleural effusion. The image must be in DICOM format.

Then, 3 specialists physicians interpret 282 samples whether there were pleural effusion, and the result was the standard of this study (Reference standard). After determining the reference standard of each Chest X-Ray, the 282 samples were input into the Chang Gung Pleural Effusion Detection Software, and analyzed by the primary and secondary outcomes.

Recruitment information / eligibility

• Status: Enrolling by invitation
• Enrollment: 282
• Est. completion date: August 12, 2024
• Est. primary completion date: November 23, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 20 Years to 100 Years

Eligibility

Inclusion Criteria:

• The case were over 20 years old and under 100 years old.

• DICOM format.

• Brand model of Canon.

• DICOM resolution length range (700-3400 pixels), width range (490-3600 pixels).

• poster-anterior view(PA-view) of chest X-ray

Exclusion Criteria:

• The chest X-ray contains items that affect interpretation, such as chest tubes, endotracheal tubes, and heart rhythm regulators, but does not include patches and circuits used in electrocardiograms.

• The chest X-ray that are difficult to interpret due to poor image quality.

Related Conditions & MeSH terms

• Pleural Effusion

Intervention

Device:
• Chang Gung Pleural Effusion Detection Software
The Chang Gung Pleural Effusion Detection Software is an independent software as a medical device, which inputs digital Chest X-Ray to automatically detect whether there is a pleural effusion. The inferred results output by this software can assist clinicians or professional medical personnel to identify whether a patient has pleural effusion. This product is only used to analyze the digitized Chest X-Ray DICOM of patients over 20 years old and under 100 years old.

Locations

Country	Name	City	State
Taiwan	Chang Gung memorial hospital	Taoyuan City

Sponsors (1)

Lead Sponsor	Collaborator
Chang Gung Memorial Hospital

Country where clinical trial is conducted

Taiwan, 

References & Publications (4)

Ahn JS, Ebrahimian S, McDermott S, Lee S, Naccarato L, Di Capua JF, Wu MY, Zhang EW, Muse V, Miller B, Sabzalipour F, Bizzo BC, Dreyer KJ, Kaviani P, Digumarthy SR, Kalra MK. Association of Artificial Intelligence-Aided Chest Radiograph Interpretation With Reader Performance and Efficiency. JAMA Netw Open. 2022 Aug 1;5(8):e2229289. doi: 10.1001/jamanetworkopen.2022.29289. — View Citation

Lachin JM. Properties of simple randomization in clinical trials. Control Clin Trials. 1988 Dec;9(4):312-26. doi: 10.1016/0197-2456(88)90046-3. — View Citation

Lim CY, In J. Randomization in clinical studies. Korean J Anesthesiol. 2019 Jun;72(3):221-232. doi: 10.4097/kja.19049. Epub 2019 Apr 1. Erratum In: Korean J Anesthesiol. 2019 Aug;72(4):396. — View Citation

Suresh K. An overview of randomization techniques: An unbiased assessment of outcome in clinical research. J Hum Reprod Sci. 2011 Jan;4(1):8-11. doi: 10.4103/0974-1208.82352. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Sensitivity	The rate of test results that correctly indicate the presence.	baseline
Secondary	Specificity	The rate of test results that correctly indicate the absence.	baseline
Secondary	Area Under the receiver operating characteristic Curve	A graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied.	baseline