Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology

Central Nervous System Neoplasms Clinical Trial

Official title:

A Multi-center, Prospective, Self-Controlled Diagnostic Accuracy Comparative Studies of Artificial Intelligence Diagnostic System for Surgical Neuropathology

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT04671368
• Other study ID #: PAAI2020
• Status: Not yet recruiting
• Phase: N/A
• Start date: February 2021
• Est. completion date: February 2022

Study information

• Verified date: December 2020
• Source: Huashan Hospital
• Contact: Lei Jin, DR
• Phone: 0086-13817841756
• Email: ozlei91[@]126.com
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

This is a multi-center, prospective, self-controlled, diagnostic accuracy comparative study of Artificial Intelligence Diagnostic System for Surgical Neuropathology. The investigators will compare the diagnostic efficiency of Artificial Intelligence with that of practicing pathologists, and suppose that the diagnostic efficiency of artificial intelligence in prospective clinical data is no less than that of pathologists.

Description:

In this study, 141 patients will be recruited. After being enrolled, the patients will accept surgery and specimens for pathological analysis will be taken according to the routine treatment process.

The histopathologic slides will then be digitized by a whole-slide scanner. The images will be reviewed by gold standard committee for evaluation of ground truth. And then be separately diagnosed by Artificial Intelligence Diagnostic System and practicing pathologists. So the investigators can compare the diagnostic efficiency of Artificial Intelligence with that of pathologists, thus understand the gap between artificial intelligence and actual clinical practice.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 141
• Est. completion date: February 2022
• Est. primary completion date: February 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

1. Patients or their guardians understand the research process, agree to use their data, and sign the informed consent form;

2. Aged >=18 years;

3. MRI shows intracranial spaceoccupying lesions;

4. The clinical diagnosis is glioma, metastasis or lymphoma thus requiring surgical treatment;

5. The patient is willing to accept the surgery.

Exclusion Criteria:

1. The patient has serious underlying diseases thus is not suitable for surgery;

2. After further clinical evaluation, surgical treatment was not the best choice;

3. The patient participate in clinical research of other drugs or devices;

4. The researchers believe that there are other factors that will make the patients unable to complete the study.

Related Conditions & MeSH terms

• Central Nervous System Neoplasms
• Nervous System Neoplasms

Intervention

Diagnostic Test:
• Artificial Intelligence
The investigators will use the Artificial Intelligence Diagnostic System to review the H&E stained slide of each patient and then report the classification of the tumor on a 10-type scale.
• Practicing Pathologists
The ordinary pathologist will review the H&E stained slide of each patient(without additional informations such as: Immunohistochemistry et al.) and then report the classification of the tumor on a 10-type scale only bases on the slide images
• Gold Standard
Firstly, the two expert pathologist(>=10 years of experience) will review the H&E stained slide of each patient on their own (with additional informations such as: Immunohistochemistry et al.) and then report the classification of the tumor on a 10-type scale.If they report the same opinion, that opinion will perform as the ground truth; while if their opinion clash with each other, the expert pathologist(>=15 years of experience) will get involved and the agreement of three experts will perform as the ground truth

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Jinsong Wu

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Diagnostic Accuracy of Study Arms	The number of correctly diagnosed participants by study arms divided by the total number of participants	1 week after the last patient's diagnosis is completed
Secondary	Sensitivity and specificity of Study Arms	Sensitivity and specificity of study arms for each type calculated by 2x2 tables	1 week after the last patient's diagnosis is completed
Secondary	Spearman Coefficient of Study Arms related to Gold Standard	Spearman Correlation Analysis between Study Arms and Gold Standard	1 week after the last patient's diagnosis is completed