Application Value of Deep Learning in Diagnosis of Cervical Spondylosis

NCT04952233 | Unknown

• 1 other identifier: M2020499
• Study Type: observational
• Target: 2,000
• Locations: 1 country
• Sites: 1

Brief Summary

Compared with the personal experience judgment of physicians, deep learning can identify something more quickly, efficiently, and accurately The identification and diagnosis of diseases save the energy of clinical and imaging doctors and achieve an individualized diagnosis of patients Diagnosis and evaluation are beneficial to the formulation of clinical surgical methods and the improvement of patients' prognoses. This study uses deep learning technology, through the big data of cervical spondylosis cases learn, to explore the use of deep learning The feasibility of identifying and analyzing the characteristic imaging findings of cervical CT images that may be suggestive of a diagnosis It is attempted to reach the level of artificial intelligence-assisted diagnosis of cervical spondylosis.

Conditions

Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• Compare the consistency between AI and clinicians in identifying cervical CT features (cervical curvature, alignment, intervertebral space, disc herniation, ossification of the posterior longitudinal ligament, spinal stenosis)

  Compare the consistency between AI and clinicians in identifying cervical CT features (cervical curvature, alignment, intervertebral space, disc herniation, ossification of the posterior longitudinal ligament, spinal stenosis)

  2019-2021

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Age 18 to 80 years old, no surgical treatment before imaging scan; Patients with cervical spondylosis confirmed by imaging report and clinical diagnosis and patients with cervical vertebra imaging CT without any obvious abnormality.

You may qualify if:

• No surgical treatment was performed before the imaging scan. Imaging report and clinical diagnosis of cervical spondylosis with or without ossification of the posterior longitudinal ligament.
• Patients who visited the orthopedics department and emergency department of our hospital without any surgical treatment before image scan and no obvious abnormalities were found in cervical imaging CT.

You may not qualify if:

• Surgery before image data acquisition;
• Cervical cancer, tuberculosis, and fracture;
• The lack of image data, the image is not clear.

Sponsors & Collaborators

• Peking University Third Hospital: lead

Study Sites (1)

Peking University Third Hospital

Beijing, Beijing Municipality, 010, China

RECRUITING

Study Officials

• huishu yuan

  Peking University Third Hospital

  STUDY CHAIR

Central Study Contacts

huishu yuan

CONTACT

13521627288; chunjiewang17@126.com

chunjie wang

CONTACT

13521627288; chunjiewang17@126.com

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 28, 2021
• First Posted: July 7, 2021
• Study Start: January 30, 2021
• Primary Completion: June 30, 2021
• Study Completion: July 30, 2021
• Last Updated: July 7, 2021

Record last verified: 2021-06

Locations

CN (1)