| Project/Area Number |
20K08122
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Review Section |
Basic Section 52040:Radiological sciences-related
|
|---|
| Research Institution | University of Occupational and Environmental Health, Japan |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2020-04-01 – 2023-03-31
|
| Project Status |
Completed (Fiscal Year 2022)
|
| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2022: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2021: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2020: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
|
|---|
| Keywords | CT / 骨折 / 検診 / 生活習慣病 / 骨密度 / 健康診断 / 生活習慣 / 骨粗鬆症 |
|---|
| Outline of Research at the Start |
CTによる肺がん検診を行った逐年検診受診者を対象として、CT画像で評価可能な多くの生活習慣病関連画像データ、および同時に施行した生活習慣および生活習慣病と関連する血液検査や呼吸機能検査のデータを用いて、種々の骨折関連因子と実際に生じた骨折との関連性を明らかにする。また、効率よく骨折予防対策を行うべき対象を絞り込むことができるように、人工知能を取り入れて、簡便かつ精度の高い骨折リスク評価法を構築することを目指す。
|
| Outline of Final Research Achievements |
Osteoporosis is defined as a systemic skeletal disease characterized by low bone mass and micro-architectural deterioration of bone tissue leading to bone fragility, The aim of this study is to investigate whether vertebral fracture (VF) can be predicted by CT-based quantifications using long-termed CT lung cancer screening data. The CT-derived quantifications for bone health included CT-derived BMD, COPD related metrics, visceral adipose tissue, muscle size/attenuation. Demographic and clinical data (age, BMI, HbA1c, smoking index, and pulmonary functional test parameter (FEV%) were retrospectively evaluated, and the correlation between these demographic/clinical data and VFs was assessed statistically. On multivariate analysis, age, CT-BMD, and COPD related CT metrics were the independent risk factors for VF (p < 0.01). Based on our data from CT lung cancer screening beyond 10 years, combined CT-derived quantifications would help the discrimination of patients at risk for VF.
|
| Academic Significance and Societal Importance of the Research Achievements |
本研究によって、年齢とCTデータから得られる骨密度および肺野のCT定量的データの組み合わせによって精度の高い骨折リスク評価法を確立できる可能性が示唆された。生活習慣病が骨折リスク因子であることを考慮した新たな骨折リスク評価法の確立によって、骨折予防対策を行うべき対象を効率よく絞り込むことができ、これまでよりも正確な薬物治療開始の判断が可能になると考える。
|
