Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

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

Conditions
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Central Nervous System Neoplasms

Intervention / Treatment
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* Diagnostic Test: Artificial Intelligence
* Diagnostic Test: Practicing Pathologists
* Diagnostic Test: Gold Standard


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients or their guardians understand the research process, agree to use their data, and sign the informed consent form; Aged >=18 years; MRI shows intracranial spaceoccupying lesions; The clinical diagnosis is glioma, metastasis or lymphoma thus requiring surgical treatment; The patient is willing to accept the surgery. Exclusion Criteria: The patient has serious underlying diseases thus is not suitable for surgery; After further clinical evaluation, surgical treatment was not the best choice; The patient participate in clinical research of other drugs or devices; The researchers believe that there are other factors that will make the patients unable to complete the study.

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Allocation: Non-Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: All patients will be diagnosed by both AI and ordinary pathologists, thus performing a self-controlled study
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Artificial Intelligence<br>A deep learning based artificial intelligence diagnostic system(DOI:10.1093/neuonc/noaa163) | Diagnostic Test: Artificial Intelligence<br>* 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.<br>|
| Active Comparator: Practicing Pathologists<br>One pathologist who has at least 5 years of experience | Diagnostic Test: Practicing Pathologists<br>* 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<br>|
| Other: Gold Standard<br>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<br>* 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<br>|

What is the study measuring?
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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 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Artificial Intelligence, CNS Tumor, Surgical Pathology, Diagnostic Accuracy Study