A Prospective Observational Study of Artificial Intelligence Morphometric Evaluation of Vertebral Fractures

NCT ID: NCT06449742

Last Updated: 2025-02-21

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

250 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-03-01

Study Completion Date

2027-03-01

Brief Summary

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The study will be conducted as a monocentric observational prospective study design wants to evaluate the prevalence of vertebral fractures in the cohort of patients that perform a chest-abdomen CT for medical indication other than osteometabolic pathologies.

Detailed Description

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This study aimed to evaluate the prevalence of vertebral fractures in a cohort of patients that perform a chest-abdomen CT for medical indication other than osteometabolic pathologies.It is estimated that 250 patients will be enrolled (Patients will be enrolled in retrospective and prospective way between 01/03/2025 and 28/02/2026. The presence of one or more vertebral fractures will be evaluated through the radiological medical assessment with automatic 3D reconstruction of the thoracic and lumbar spine and by application of the AI software NanoxAIHealthVCF NANO-X IMAGING LTD on abdomen-chest CT studies.

Clinical, anthropometric, and anamnestic data will be collected from patients undergoing CT assessments. These data will be collected on the day of the radiological examination.

There will be only one evaluation at the time of the CT scan. Only in case of fracture detection, via radiological medical assessment and/or via AI software, the patient will be subsequently evaluated in the Endocrinology Unit as for standard of care.

Conditions

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Vertebral Fracture Osteoporosis

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Patients undergoing to CT abdomen-chest

Patients undergoing to CT abdomen-chest study at the UO of Radiology of the IRCCS San Raffaele Hospital for clinical indications not related to osteo-metabolic pathology.

Patients will be evaluated for vertebral fractures both through the radiological medical evaluation with automatic 3D reconstruction of the thoracic and lumbar spine and through application of the AI software NanoxAIHealthVCF, NANO-X IMAGING LTD on abdomen-chest CT studies.

AI software and automatic 3D reconstruction

Intervention Type DIAGNOSTIC_TEST

Radiological medical evaluation with automatic 3D reconstruction of the thoracic and lumbar spine and through application of the AI software NanoxAIHealthVCF, NANO-X IMAGING LTD on abdomen-chest CT studies.

Interventions

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AI software and automatic 3D reconstruction

Radiological medical evaluation with automatic 3D reconstruction of the thoracic and lumbar spine and through application of the AI software NanoxAIHealthVCF, NANO-X IMAGING LTD on abdomen-chest CT studies.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

1. Male subjects
2. Age ≥ 50 years
3. Clinical and medical history data available at abdomen-chest CT evaluation
4. Signature of informed consent to the study

Exclusion Criteria

1. Hospitalized patients
2. Patients known to have osteo-metabolic diseases.
3. with primary and/or acquired immunodeficiency states, and/or severe impairment of general clinical condition (e.g. metastatic neoplasms; immunosuppressive therapies; worsening/reacute/compensated chronic diseases; moderate-severe renal failure)
4. Patients unable to understand and sign the Informed Consent.
Minimum Eligible Age

50 Years

Eligible Sex

MALE

Accepts Healthy Volunteers

No

Sponsors

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IRCCS San Raffaele

OTHER

Sponsor Role lead

Responsible Party

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Luigi Di Filippo

Medical Physician Specialist in Endocrinology

Responsibility Role PRINCIPAL_INVESTIGATOR

Central Contacts

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Luigi Di Filippo, MD

Role: CONTACT

0226435062

Gabriela Felipe, research nurse

Role: CONTACT

0226435062

Other Identifiers

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SMORFIA

Identifier Type: -

Identifier Source: org_study_id

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