UMIN-ICDS Clinical Trial
| Unique ID issued by UMIN | UMIN000061814 |
|---|---|
| Receipt number | R000070735 |
| Scientific Title | Development and Validation of a Machine Learning-Based Skeletal Muscle Mass Estimation Model Using Smartphone-Captured Lower-Leg Images: Comparison with Calf Circumference |
| Date of disclosure of the study information | 2026/06/05 |
| Last modified on | 2026/06/05 23:51:19 |
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Basic information
Public title
Development and Validation of a Skeletal Muscle Mass Estimation Model Using Smartphone-Captured Lower-Leg Images
Acronym
Smartphone-based Muscle Index from Lower-leg Study
Scientific Title
Development and Validation of a Machine Learning-Based Skeletal Muscle Mass Estimation Model Using Smartphone-Captured Lower-Leg Images: Comparison with Calf Circumference
Scientific Title:Acronym
Lower-Leg Image SMI Study
Region
| Japan |
Condition
Condition
Healthy adults
Classification by specialty
| Rehabilitation medicine | Adult |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
The purpose of this study is to validate a deep learning-based method for estimating skeletal muscle index (SMI) using lateral and posterior lower-leg images captured with smartphones and digital cameras. In addition, differences in predictive performance according to imaging device and imaging direction will be investigated, and comparison with calf circumference, a conventional surrogate measure of skeletal muscle mass, will be performed to evaluate the usefulness of image-based assessment.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Confirmatory
Trial characteristics_2
Explanatory
Developmental phase
Not applicable
Assessment
Primary outcomes
Concordance between skeletal muscle mass estimated from lower-leg images and skeletal muscle mass measured by bioelectrical impedance analysis (InBody 470), assessed using Lin's concordance correlation coefficient (CCC)
Key secondary outcomes
1. Prediction error of the skeletal muscle mass estimation model using smartphone-captured lower-leg images, assessed by mean absolute percentage error (MAPE) and root mean squared error (RMSE)
2. Agreement between skeletal muscle mass estimated from smartphone-captured lower-leg images and skeletal muscle mass measured by bioelectrical impedance analysis, assessed using Bland-Altman analysis (mean difference and 95% limits of agreement)
3. Comparison of predictive performance (CCC, MAPE, and RMSE) between the smartphone image-based skeletal muscle mass estimation model and the calf circumference-based estimation model
4. Comparison of skeletal muscle mass estimation performance according to imaging device (smartphone or digital camera) and imaging direction (lateral or posterior lower-leg view), assessed using CCC, MAPE, and RMSE
Base
Study type
Interventional
Study design
Basic design
Single arm
Randomization
Non-randomized
Randomization unit
Blinding
Open -no one is blinded
Control
Uncontrolled
Stratification
NO
Dynamic allocation
NO
Institution consideration
Institution is not considered as adjustment factor.
Blocking
NO
Concealment
No need to know
Intervention
No. of arms
1
Purpose of intervention
Prevention
Type of intervention
| Device,equipment |
Interventions/Control_1
Lateral and posterior lower-leg images will be captured once using a smartphone and a digital camera. On the same day, skeletal muscle mass will be measured once using bioelectrical impedance analysis (InBody 470), and calf circumference will be measured once.
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
| Not applicable |
Gender
Male and Female
Key inclusion criteria
1. Individuals who provide written informed consent to participate in the study
2. Healthy adults aged 18 years or older
3. Individuals capable of maintaining standing and sitting positions during assessment
4. Individuals able to undergo lower-leg image acquisition and bioelectrical impedance analysis
Key exclusion criteria
1. Individuals who have difficulty maintaining a standing position
2. Individuals with edema or other conditions affecting the lower leg
3. Individuals with implanted medical devices such as cardiac pacemakers
4. Individuals with any limb amputation
5. Individuals with metallic implants or fixation devices in the body
6. Individuals who are pregnant or may be pregnant
7. Individuals with a history of fractures or ligament injuries of the lower limbs
8. Individuals with a history of central or peripheral nervous system disorders
9. Individuals deemed unsuitable for participation in the study by the principal investigator or co-investigators
Target sample size
100
Research contact person
Name of lead principal investigator
| 1st name | Hiroo |
| Middle name | |
| Last name | Matsuse |
Organization
Kurume University Hospital
Division name
Department of Rehabilitation
Zip code
830-0011
Address
67 Asahi-machi, Kurume-shi, Fukuoka 830-0011, Japan
TEL
0942-35-3311
matsuse_hiroh@kurume-u.ac.jp
Public contact
Name of contact person
| 1st name | Hiroo |
| Middle name | |
| Last name | Matsuse |
Organization
Kurume University Hospital
Division name
Department of Rehabilitation
Zip code
830-0011
Address
67 Asahi-machi, Kurume-shi, Fukuoka 830-0011, Japan
TEL
0942-35-3311
Homepage URL
matsuse_hiroh@kurume-u.ac.jp
Sponsor or person
Institute
Kurume University
Institute
Department
Personal name
Funding Source
Organization
None
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
Clinical Research Center, Kurume University Hospital
Address
67 Asahi-machi, Kurume-shi, Fukuoka 830-0011, Japan
Tel
0942-65-3749
i_rinri@kurume-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 | 05 | 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
100
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
No longer recruiting
Date of protocol fixation
| 2025 | Year | 01 | Month | 30 | Day |
Date of IRB
| 2025 | Year | 01 | Month | 30 | Day |
Anticipated trial start date
| 2025 | Year | 02 | Month | 14 | Day |
Last follow-up date
| 2025 | Year | 08 | Month | 31 | Day |
Date of closure to data entry
| 2025 | Year | 08 | Month | 31 | Day |
Date trial data considered complete
Date analysis concluded
Other
Other related information
Management information
Registered date
| 2026 | Year | 06 | Month | 05 | Day |
Last modified on
| 2026 | Year | 06 | Month | 05 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000070735
