Validation of a Multitask Deep Learning System at Spine Metastasis CT

Shanghai Jiao Tong University

Status: Completed

Conditions: To Evaluate Performance of the DLS

Treatments: Diagnostic Test: Deep Learning System

Study type: Observational

Funder types: Other

Identifiers

NCT05156567

DLS01

Details and patient eligibility

About

15 resident oncologists were conducted to evaluate the clinical efficacy of DLS in multicenter. They were 1:1 randomly asked to independently read the test images without the assistance of DLS software or with the assistance. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of the DLS were calculated with professional graders as the reference standard.

Enrollment: 280 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. pathology-proven diagnosis of solid tumor;
2. spinal CT scan indicating spinal metastasis with at least one lesion;
3. no previous surgery for spinal metastasis

Exclusion criteria

1. spinal CT scans with no sagittal reconstruction;
2. the radiologist considered that the quality of CT image was unqualified.

Trial design

280 participants in 2 patient groups

routine physicians

DLS

Treatment:

Diagnostic Test: Deep Learning System