UMIN-ICDS Clinical Trial
| Unique ID issued by UMIN | UMIN000061844 |
|---|---|
| Receipt number | R000070770 |
| Scientific Title | Development of an AI-based spinal CT analysis system for identifying optimal puncture points for epidural anesthesia |
| Date of disclosure of the study information | 2026/06/10 |
| Last modified on | 2026/06/09 13:02:20 |
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Basic information
Public title
Development of an AI-based spinal CT analysis system for identifying optimal puncture points for epidural anesthesia
Acronym
AI Spinal CT Analysis for Epidural Anesthesia Study
Scientific Title
Development of an AI-based spinal CT analysis system for identifying optimal puncture points for epidural anesthesia
Scientific Title:Acronym
AI Spinal CT Analysis for Epidural Anesthesia Study
Region
| Japan |
Condition
Condition
None
Classification by specialty
| Anesthesiology |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
This study aims to develop a system that uses AI to analyze spinal CT images and automatically calculate the location, angle, and area of the puncture window between the vertebral arches that is suitable for epidural anesthesia. As the first step, the study verifies the accuracy of the AI by comparing the puncture window area automatically calculated by the AI at each vertebral level with the area measured manually by pixel-level counting on the same CT image.
Basic objectives2
Others
Basic objectives -Others
Validation of measurement accuracy of AI-based analysis
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
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
Key secondary outcomes
Difference between the AI-calculated values and the manually counted values at each vertebral level (absolute error and relative error, including pixel counts)
Base
Study type
Observational
Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment
Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10
Eligibility
Age-lower limit
| 18 | years-old | < |
Age-upper limit
| 99 | years-old | > |
Gender
Male and Female
Key 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
Key exclusion criteria
Cases for which consent was not obtained
Target sample size
1
Research contact person
Name of lead principal investigator
| 1st name | Hiroaki |
| Middle name | |
| Last name | Toyama |
Organization
Yamagata University Faculty of Medicine
Division name
Department of Anesthesia
Zip code
9909585
Address
2-2-2 Iida-nishi, Yamagata city, Yamagata
TEL
023-628-5400
hayasakatatsuya1101@gmail.com
Public contact
Name of contact person
| 1st name | Tatsuya |
| Middle name | |
| Last name | Hayasaka |
Organization
Yamagata University Faculty of Medicine
Division name
Department of Anesthesia
Zip code
9909585
Address
-2-2 Iida-nishi, Yamagata city, Yamagata
TEL
023-628-5400
Homepage URL
hayasakatatsuya1101@gmail.com
Sponsor or person
Institute
Yamagata University Faculty of Medicine
Institute
Department
Personal name
Funding Source
Organization
Yamagata University Faculty of Medicine
Organization
Division
Category of Funding Organization
Other
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
The Ethical Review Committee of Yamagata University Faculty of Medicine
Address
2-2-2 Iida-nishi, Yamagata City, Yamagata 990-9585, Japan
Tel
0236285015
ikekenkyu@jm.kj.yamagata-u.ac.jp
Secondary IDs
Secondary IDs
NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW
Institutions
Institutions
Other administrative information
Date of disclosure of the study information
| 2026 | Year | 06 | Month | 10 | Day |
Related information
URL releasing protocol
Publication of results
Unpublished
Result
URL related to results and publications
Number of participants that the trial has enrolled
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description
Progress
Recruitment status
Preinitiation
Date of protocol fixation
| 2026 | Year | 05 | Month | 01 | Day |
Date of IRB
Anticipated trial start date
| 2026 | Year | 06 | Month | 10 | Day |
Last follow-up date
| 2030 | Year | 03 | Month | 31 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
Epidural anesthesia is the gold standard for postoperative analgesia but is technically difficult, with a certain rate of difficult or failed catheter insertion that prolongs patient discomfort. Because it is performed blindly, visualization and teaching are difficult. We have previously evaluated the usefulness of projecting the spine onto the patient's back using AR technology, but quantitative analysis to optimize the puncture itself, such as which point and angle to puncture and how large the puncture window between the vertebral arches is, has not yet been achieved. In this study, AI analyzes spinal CT images at the pixel level to automatically calculate the area of the puncturable region at each vertebral level (about 12 thoracic and lumbar vertebrae in total), and the result is compared with the area measured by manual pixel counting on the same image to verify the accuracy of the AI. Analysis is performed using correlation coefficients (Pearson and Spearman), Bland-Altman analysis, and the t-test or Wilcoxon signed-rank test, with a significance level of P<0.05. This is a retrospective study using only existing CT images and medical records, and no new physical burden or invasiveness is imposed on the participants. The data are anonymized and analyzed in an offline environment.
Management information
Registered date
| 2026 | Year | 06 | Month | 09 | Day |
Last modified on
| 2026 | Year | 06 | Month | 09 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000070770
