Central Nervous System Neoplasms
Conditions
Keywords
Artificial Intelligence, CNS Tumor, Surgical Pathology, Diagnostic Accuracy Study
Brief 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.
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.
Interventions
DIAGNOSTIC_TESTArtificial 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.
DIAGNOSTIC_TESTPracticing 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
DIAGNOSTIC_TESTGold 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
Sponsors
Jinsong Wu
Study design
Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Outcomes Assessor)
Masking description
The AI group, ordinary pathologists and gold standard group will not be informed of each other's results
Intervention model description
All patients will be diagnosed by both AI and ordinary pathologists, thus performing a self-controlled study
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic Accuracy of Study Arms | 1 week after the last patient's diagnosis is completed | The number of correctly diagnosed participants by study arms divided by the total number of participants |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity and specificity of Study Arms | 1 week after the last patient's diagnosis is completed | Sensitivity and specificity of study arms for each type calculated by 2x2 tables |
| Spearman Coefficient of Study Arms related to Gold Standard | 1 week after the last patient's diagnosis is completed | Spearman Correlation Analysis between Study Arms and Gold Standard |
Contacts
Primary ContactLei Jin, DR
Backup ContactYixin Ma, BA
Outcome results
None listed