Evaluation of Musculoskeletal Aging and Related Disorders Via Advanced Clinical Imaging

March 17, 2026 updated by: Yuhui Kou, Peking University People's Hospital

A Comprehensive Evaluation of Musculoskeletal Aging and Degenerative Pathologies Using Multi-modal Clinical Imaging and Quantitative Analysis.

Study Overview This clinical research focuses on the development and validation of a multimodal artificial intelligence (AI) platform designed for the automated diagnosis and precise staging of two major musculoskeletal conditions: Osteoporosis (OP) and Osteoarthritis (OA). By integrating diverse clinical imaging data, the study aims to provide a more objective and standardized approach to assessing bone and joint degeneration.

Technological Core: Intelligent Staging

Traditional diagnosis often relies on manual interpretation, which can lead to inter-observer variability. This study employs deep learning and multimodal imaging to:

For Osteoporosis: Automatically quantify bone mineral density and micro-architectural changes to determine the stage of bone loss and evaluate fracture risk.

For Osteoarthritis: Identify subtle radiological markers such as joint space narrowing and osteophyte formation to categorize the severity of joint degeneration according to international staging standards (e.g., Kellgren-Lawrence scale).

Why This Matters Early Intervention: By identifying early-stage changes in bone density and joint integrity, clinicians can implement preventive treatments before significant disability occurs.

Standardized Care: The intelligent diagnostic model provides a "digital second opinion," ensuring consistent staging across different healthcare settings.

Efficiency: The automated workflow reduces the workload of radiologists while maintaining high diagnostic accuracy.

Ethical Compliance The study is conducted at Peking University People's Hospital under the supervision of the Institutional Review Board (Approval No. 2026PHB097-001). It strictly adheres to international ethical standards, including the Declaration of Helsinki and Good Clinical Practice (GCP) guidelines, to ensure patient data privacy and safety.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.

Detailed Description

  1. Research Rationale and Goals Musculoskeletal aging often presents as a complex interplay between Osteoporosis (OP) and Osteoarthritis (OA). Despite their prevalence, current diagnostic workflows frequently treat these conditions in isolation, often relying on manual radiological staging that is prone to inter-observer variability. This study aims to develop and validate a multimodal artificial intelligence (AI) platform capable of simultaneous detection and precise disease staging for both OP and OA. By integrating diverse data sources-including clinical laboratory markers, patient history, and multiple imaging modalities (X-ray, CT, and MRI)-the project seeks to provide a holistic and objective assessment of skeletal health.

  2. Study Design and Population The research employs a bidirectional observational cohort study design. Retrospective Cohort (Model Development): Data will be collected from approximately 1,500 patients who visited the Peking University People's Hospital (PKUPH) between November 2005 and November 2025.

    Prospective Cohort (External Validation): At least 500 new participants will be recruited starting from December 2025 to test the model's performance in a real-world clinical setting.

    The study targets adults aged 18 to 90 who have completed relevant musculoskeletal imaging scans.

  3. Methodology and AI PipelineThe study is divided into three strategic phases:Phase I: Multimodal Data Integration: Collection of de-identified imaging (X-ray/CT/MR), laboratory indices (e.g., bone turnover markers, calcium-phosphorus metabolism), and clinical demographics (Age, BMI, medical history).Phase II: Intelligent Diagnostic Staging: Leveraging Convolutional Neural Networks (CNN) for image feature extraction and machine learning algorithms (e.g., XGBoost, SVM) for clinical feature fusion.For Osteoporosis: The model will categorize bone health stages (Normal, Osteopenia, Osteoporosis) using DXA T-scores as the gold standard.For Osteoarthritis: The system will automate grading based on the Kellgren-Lawrence (KL) scale, identifying joint space narrowing and osteophytic progression.Phase III: Validation and Explainability: Internal cross-validation and independent external testing using the prospective cohort. SHAP (Shapley Additive Explanations) analysis will be applied to quantify the contribution of each modality to the final diagnostic decision, ensuring clinical transparency.
  4. Outcome Measures The primary outcome is the diagnostic accuracy (AUC, Sensitivity, Specificity) of the AI model for both conditions. Secondary outcomes focus on long-term clinical utility, including the incidence of new fragility fractures and changes in functional scores (e.g., VAS or OKS) during the follow-up periods (6, 12, 24, and 36 months).
  5. Ethical Oversight and Data Safety The study is conducted at Peking University People's Hospital under the approval of the Institutional Review Board (Approval No. 2026PHB097-001). It adheres to GCP principles and the Declaration of Helsinki. All imaging and clinical data are strictly de-identified (anonymized) before being entered into the secure, encrypted research database to protect patient privacy.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Estimated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
2000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

Study Population DescriptionThe study population consists of adult patients seeking medical consultation or treatment at the Department of Orthopaedic Trauma, Peking University People's Hospital. This population represents a diverse clinical spectrum of musculoskeletal aging, ranging from healthy skeletal status to various stages of Osteoporosis (OP) and Osteoarthritis (OA).The research employs a bidirectional cohort structure:Retrospective Cohort: Includes approximately 1,500 patients treated between November 2005 and November 2025, primarily used for model training and internal algorithm validation.Prospective Cohort: Includes at least 500 patients recruited starting from December 2025, used for independent external validation of the model's diagnostic accuracy and staging robustness in a real-world clinical setting.Participants are characterized by their availability of multimodal data, including radiological images (X-ray, CT, MRI) and clinical laboratory indicators (e.g., bone tur

Description

Inclusion Criteria:

  • Age: Adults aged at least 18 years.
  • Gender: No gender restrictions; both male and female participants are eligible.
  • Imaging Data: Participants must have completed relevant clinical imaging scans of skeletal sites, including but not limited to X-ray, CT (plain scan), or MRI (plain scan).
  • Anatomical Integrity: The skeletal structure of the target area must be free from congenital or acquired deformities.
  • Absence of Implants: No internal fixation materials or orthopedic implants in the skeletal areas being assessed.

Exclusion Criteria:

  • Pathological History: Patients with a history of prior pathological fractures.
  • Malignancy: Patients seeking treatment or diagnosed with bone tumors or other systemic malignancies.
  • Medication History: Patients with a history of long-term steroid use, which may significantly affect bone density and joint structure.
  • Recent Treatment: Patients who have undergone radiotherapy or chemotherapy within the past six months.
  • Data Quality: Patients whose imaging data is of insufficient quality for AI analysis or lacks clear clinical diagnostic "gold standard" references (e.g., missing DXA results for osteoporosis staging).

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.
Peking University People's Hospital cohort 1
participants with osteoarthritis
Other: No Interventions
No Interventions
Peking University People's Hospital cohort 2
participants with osteoporosis
Other: No Interventions
No Interventions
Sun yat-sen memorial hospital 1
participants with osteoarthritis
Other: No Interventions
No Interventions
Sun yat-sen memorial hospital 2
participants with osteoporosis
Other: No Interventions
No Interventions
Peking University People's Hospital cohort 3
participants without osteoporosis and osteoarthritis
Other: No Interventions
No Interventions
Sun yat-sen memorial hospital 3
participants without osteoporosis and osteoarthritis
Other: No Interventions
No Interventions

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
Bone age status
Time Frame: From enrollment to the initial treatment at 2 years
Bone mineral density and osteoarthitis
From enrollment to the initial treatment at 2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Peking University People's Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
November 1, 2005

Primary Completion (Estimated)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
December 1, 2026

Study Completion (Estimated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
December 31, 2026

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
March 11, 2026

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
March 11, 2026

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
March 16, 2026

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
March 19, 2026

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
March 17, 2026

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
March 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • 2026PHB097-001

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Privacy and Confidentiality Risks: The study involves sensitive clinical imaging (X-ray, CT, MRI) and laboratory data from patients at Peking University People's Hospital. Even after de-identification, there is a risk that high-resolution medical images could be re-identified, violating patient privacy agreements .Institutional Data Policy: The protocol states that data processing and export are restricted to computers registered within the hospital, and "data does not leave the hospital". This strict internal data management policy is designed to maintain security and hospital-level control over clinical assets.Ethical Constraints: The Institutional Review Board (IRB) approved the study based on strict data protection measures. Sharing raw IPD externally might require additional informed consent from participants or further ethical amendments that were not part of the original approval (2026PHB097-001).Intellectual Property and Proprietary Algorithms: Since this study involves

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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