Development of an AI-based spinal CT analysis system for identifying optimal puncture points for epidural anesthesia

Development of an AI-based spinal CT analysis system for identifying optimal puncture points for epidural anesthesia - AI Spinal CT Analysis for Epidural Anesthesia Study

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000061844

Enrollment

Registered

2026-06-10

Start date

2026-06-10

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Patients aged 18 years or older who have already undergone CT imaging including the spine at Yamagata University Hospital and who have provided written consent to participate in this study

Exclusion criteria

Exclusion criteria: Cases for which consent was not obtained

Design outcomes

Primary

Measure	Time frame
Agreement between the puncture window area (puncturable region between the vertebral arches) automatically calculated by AI and the area measured by manual pixel counting at each vertebral level	—

Secondary

Measure	Time frame
Difference between the AI-calculated values and the manually counted values at each vertebral level (absolute error and relative error, including pixel counts)	—

Countries

Japan

Contacts

Public ContactTatsuya Hayasaka

Yamagata University Faculty of Medicine Department of Anesthesia

hayasakatatsuya1101@gmail.com023-628-5400

Outcome results