A Study on Vertebral Bone Strength by Micro-CT-Like Image

A Study on Vertebral Bone Strength by Micro-CT-Like Image: An Approach Based on Conditional Generative Adversarial Nets

In this study, we use conditional generation adversarial network to enhance the resolution of MSCT images and obtain micro-CT-like images. Based on this, we measure the bone structure indexes of micro-CT-like images and analyzed the correlation between bone structure and bio-mechanical indexes.

Study Overview

• Status: Recruiting
• Conditions: Osteoporosis
• Intervention / Treatment: Diagnostic test: Radiological scanning; Other: Deep learning; Procedure: Bio-mechanical testing

Detailed Description

In this study, we expect to collect 10 sets of vertebrae (between T6 and L5) from 10 formalin-fixed human cadavers. The study protocol was reviewed and approved by the local Institutional Review Boards.The collected specimens subject to normalized Micro-CT and MSCT image scanning, image reconstruction using standard algorithms, and bone structure observation using bone algorithms to obtain high-quality, standardized axial images. We will use a conditional generation adversarial network-based image mapping technique to train the mapping model between MSCT images and Micro-CT images, find the correspondence between the image information contained in each of MSCT and Micro-CT, and finally obtain high-resolution micro-CT-like images. After obtaining the Micro-CT-like images of the samples, we will segment and annotate the images (including different structures such as vertebral body, bone cortex) and train the Teacher-Student & U-Net++ deep learning architecture to achieve accurate segmentation of vertebral body regions, and obtain cancellous bone regions of interest. Based on this, we will analyze the bone structure characteristics of each spatial region in the images, including the thickness, spacing, orientation and distribution pattern of bone trabeculae and other indicators. Ultimately, we will cut a standardized cubic sample from the vertebral cancellous bone , obtain the bio-mechanical performance index of this cancellous bone sample by mechanical experiments, and analyze the correlation between bone structure of Micro-CT-like images and bio-mechanical index.

• Study Type: Observational
• Enrollment (Anticipated): 100

Contacts and Locations

• Study Contact: Name: Dan Jin; Phone Number: +8613161525366; Email: jindan1418@bjmu.edu.cn

Study Locations

• China
  • Beijing
    • Beijing, Beijing, China, 010
      • Recruiting
      • Peking University Third Hospital
      • Contact: Huishu Yuan, Dr; Email: huishuy@bjmu.edu.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

The specimens for this experiment were obtained from formalin-fixed human cadavers.The donors had dedicated their body for educational and research purposes to the local Institute of Anatomy prior to death, in compliance with local institutional and legislative requirements.

Description

Inclusion Criteria:

• We will collect human formalin-fixed vertebral specimens provided by the Department of Anatomy, Peking University School of Medicine. The expected number of enrolled specimens is approximately 100 vertebrae (between T6 and L5) .

Exclusion Criteria:

• The vertebrae with significant compression fractures, bone neoplasms, or other causes of significant bone destruction.

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Crossover
• Time Perspectives: Cross-Sectional

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
MSCT image; Scanning of the vertebral body using MSCT	Diagnostic test: Radiological scanning; The collected specimens subject to normalized Micro-CT and MSCT image acquisition, image reconstruction using standard algorithms, and bone structure observation using bone algorithms to obtain high-quality, standardized axial images.; Other: Deep learning; We will use a conditional generation adversarial network-based image mapping technique to train the mapping model between MSCT images and Micro-CT images, find the correspondence between the image information contained in each of MSCT and Micro-CT, and finally obtain high-resolution micro-CT-like images.; Procedure: Bio-mechanical testing; we will cut a standardized cubic sample from the vertebral cancellous bone , obtain the bio-mechanical performance index of this cancellous bone sample by mechanical experiments, and analyze the correlation between bone structure of Micro-CT-like images and bio-mechanical index.
micro-CT image; Scanning of the vertebral body using micro-CT	Diagnostic test: Radiological scanning; The collected specimens subject to normalized Micro-CT and MSCT image acquisition, image reconstruction using standard algorithms, and bone structure observation using bone algorithms to obtain high-quality, standardized axial images.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Consistency or correlation	Analyze the consistency or correlation between micro-CT and micro-CT-like bone structure indexes; analyze the correlation between micro-CT-like bone structure indexes and bio-mechanical indexes	From the beginning of the experiment to 8 months

Collaborators and Investigators

• Sponsor: Peking University Third Hospital
• Investigators: Study Chair: huishu Yuan, Department of Radiology Peking University Third Hospital Beijing, China,

Study record dates

Study Major Dates

• Study Start (Actual): May 1, 2021
• Primary Completion (Anticipated): December 30, 2021
• Study Completion (Anticipated): December 30, 2021

Study Registration Dates

• First Submitted: June 29, 2021
• First Submitted That Met QC Criteria: June 29, 2021
• First Posted (Actual): July 8, 2021

Study Record Updates

• Last Update Posted (Actual): July 8, 2021
• Last Update Submitted That Met QC Criteria: June 29, 2021
• Last Verified: June 1, 2021

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Metabolic Diseases; Musculoskeletal Diseases; Bone Diseases; Bone Diseases, Metabolic; Osteoporosis
• Other Study ID Numbers: M2021179

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No