Validation of AI Lumbar Spine Anatomy Measureing Function (Spinal cord)

Functionality Assessment of RadiSpine, an Artificial Intelligence Software as Medical Device for Lumbar Spine Quantification System

Spinal degeneration and its associated clinical diseases are common ailments in aging societies. With the advent of a super-aging society, the importance of assistive technologies for spinal image interpretation is increasingly significant to enhance care efficiency and reduce medical personnel expenditure. Recently, due to the rapid development of artificial intelligence (AI) algorithm, AI-based computer-assisted detection (CADe) devices gradiually become a convenient method for spinal anatomy measurement. However, the accuracy of these devices has not been fully established. This study aims to validate the performance of RadiSpine (an application program) in spinal anatomy segmentation and measurement.

Study Overview

• Status: Completed
• Conditions: Spinal Cord Compression

• Study Type: Observational
• Enrollment (Actual): 150

Contacts and Locations

Study Locations

• Taiwan
  • Taipei, Taiwan, 112
    • Taipei Veterans General Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

The subjects should be aged 20 or older and younger than 75, with an equal gender distribution of 50% male and 50% female. From this group, 150 subjects with reasonable datavalues will be selected, with a requirement that at least 30% of them are male and at least 30% are female.

Description

Inclusion Criteria:

The subjects should be aged 20 or older and younger than 75, with an equal gender distribution of 50% male and 50% female. From this group, 150 subjects with reasonable datavalues will be selected, with a requirement that at least 30% of them are male and at least 30% are female.

Exclusion Criteria:

1. With history of spinal surgery
2. Spinal trauma
3. Spinal osteoporosis
4. Spinal metastasis or infection

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Segmentation accuracy (Mean)	The minimum Mean Dice Coefficient (MDC), defined as the lower limit of the 95% confidence interval (CI) for MDC, is above a predetermined allowable limit equal to 0.8	30 mins per individual

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Measurement accuracy	The maximum Mean Absolute Error (MAE), defined as the upper limit of the 95% CI for MAE, is below a predetermined allowable error limit equal to 2 mm	30 mins per individual

Collaborators and Investigators

• Sponsor: RadiRad Co., Ltd.
• Collaborators: Taipei Veterans General Hospital, Taiwan

Study record dates

Study Major Dates

• Study Start (Actual): September 12, 2024
• Primary Completion (Actual): March 31, 2025
• Study Completion (Actual): March 31, 2025

Study Registration Dates

• First Submitted: April 10, 2025
• First Submitted That Met QC Criteria: April 24, 2025
• First Posted (Actual): April 30, 2025

Study Record Updates

• Last Update Posted (Actual): April 30, 2025
• Last Update Submitted That Met QC Criteria: April 24, 2025
• Last Verified: April 1, 2025

More Information

Terms related to this study

• Keywords: Artificial Intelligence(AI) Algorithm Spinal anatomy
• Additional Relevant MeSH Terms: Central Nervous System Diseases; Nervous System Diseases; Wounds and Injuries; Spinal Cord Diseases; Spinal Cord Injuries; Spinal Cord Compression
• Other Study ID Numbers: Validation of Spinal Anatomy

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No