Validation of a Multitask Deep Learning System at Spine Metastasis CT

Multicenter Validation of a Multitask Deep Learning System for Spinal Instability at Spine Metastasis CT

The multitask deep learning system (DLS) with five algorithms detecting five quantitative factors of Spinal Instability Neoplastic Score (SINS) was developed. Radiologists and oncologists from multicenter will be recruited to read the CT scans in picture archiving and communication system (PACS) independently, comparing with the DLS. One month after reading the CT scans in PACS, the participants will also asked to perform a web-based test in the DLS website using the same CT scans. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of the DLS were calculated with professional graders as the reference standard.

Study Overview

• Status: Not yet recruiting
• Conditions: To Evaluate the Spinal Instability Detection Performance of the DLS
• Intervention / Treatment: Diagnostic test: Deep Learning System

• Study Type: Observational
• Enrollment (Anticipated): 420

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 16 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Patients with Spine Metastasis

Description

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.

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Prospective

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
routine physicians	Diagnostic test: Deep Learning System; The multitask DLS with five algorithms detecting five quantitative factors of SINS
DLS	Diagnostic test: Deep Learning System; The multitask DLS with five algorithms detecting five quantitative factors of SINS

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AUC	Area under the receiver operating characteristic curve (AUC) of spinal instability detection	1 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
sensitivity	sensitivity of spinal instability detection	1 months
specificity	specificity of spinal instability detection	1 months

Collaborators and Investigators

• Sponsor: Shanghai 6th People's Hospital

Study record dates

Study Major Dates

• Study Start (Anticipated): July 1, 2022
• Primary Completion (Anticipated): December 31, 2023
• Study Completion (Anticipated): December 31, 2023

Study Registration Dates

• First Submitted: December 12, 2021
• First Submitted That Met QC Criteria: December 12, 2021
• First Posted (Actual): December 14, 2021

Study Record Updates

• Last Update Posted (Actual): June 1, 2022
• Last Update Submitted That Met QC Criteria: May 31, 2022
• Last Verified: May 1, 2022

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Neoplasms; Neoplastic Processes; Neoplasm Metastasis
• Other Study ID Numbers: DLS01

Drug and device information, study documents

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