Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology

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

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.

Study Overview

• Status: Unknown
• Conditions: Central Nervous System Neoplasms
• Intervention / Treatment: Diagnostic test: Artificial Intelligence; Diagnostic test: Practicing Pathologists; Diagnostic test: Gold Standard

Detailed 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.

• Study Type: Interventional
• Enrollment (Anticipated): 141
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Lei Jin, DR; Phone Number: 0086-13817841756; Email: ozlei91@126.com
• Study Contact Backup: Name: Yixin Ma, BA; Phone Number: 0086-18001781531; Email: 14301050150@fudan.edu.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

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.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Non-Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Artificial Intelligence; A deep learning based artificial intelligence diagnostic system(DOI:10.1093/neuonc/noaa163)	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.
Active Comparator: Practicing Pathologists; One pathologist who has at least 5 years of experience	Diagnostic test: 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
Other: Gold Standard; A committee composed of two expert pathologists who has at least 10 years of experience and one expert pathologist who has at least 15 years of experience	Diagnostic test: 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

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
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
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

Collaborators and Investigators

• Sponsor: Jinsong Wu
• Investigators: Study Director: Cuiyun Wu, Ph.D, Huashan Hospital

Study record dates

Study Major Dates

• Study Start (Anticipated): February 1, 2021
• Primary Completion (Anticipated): February 1, 2022
• Study Completion (Anticipated): February 1, 2022

Study Registration Dates

• First Submitted: December 4, 2020
• First Submitted That Met QC Criteria: December 15, 2020
• First Posted (Actual): December 17, 2020

Study Record Updates

• Last Update Posted (Actual): December 17, 2020
• Last Update Submitted That Met QC Criteria: December 15, 2020
• Last Verified: December 1, 2020

More Information

Terms related to this study

• Keywords: Artificial Intelligence; CNS Tumor; Surgical Pathology; Diagnostic Accuracy Study
• Additional Relevant MeSH Terms: Nervous System Diseases; Neoplasms; Neoplasms by Site; Nervous System Neoplasms; Central Nervous System Neoplasms
• Other Study ID Numbers: PAAI2020

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No