Status:

COMPLETED

Accuracy of Deep-learning Algorithm for Detection and Risk Stratification of Lung Nodules

Lead Sponsor:

Chinese University of Hong Kong

Collaborating Sponsors:

IBM China/Hong Kong Limited

Conditions:

Osteogenic Sarcoma

Eligibility:

All Genders

Up to 18 years

Brief Summary

Osteosarcoma is regarded as most common malignant bone tumor in children and adolescents. Approximately 15% to 20% of patients with osteosarcoma present with detectable metastatic disease, and the maj...

Eligibility Criteria

Inclusion

  • Patients with histologically confirmed osteogenic sarcoma
  • With an age younger than 18 years old.
  • Patients who underwent thin-section thoracic CT examinations for pre-treatment staging and/or subsequent post-treatment follow-up.
  • With suspicious lung nodules detected on thoracic CT images.

Exclusion

  • Patients with concurring lesions that may influence analysis of lung nodules.

Key Trial Info

Start Date :

November 6 2019

Trial Type :

OBSERVATIONAL

Allocation :

ACTUAL

End Date :

January 31 2024

Estimated Enrollment :

100 Patients enrolled

Trial Details

Trial ID

NCT04022512

Start Date

November 6 2019

End Date

January 31 2024

Last Update

February 7 2024

Active Locations (1)

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Page 1 of 1 (1 locations)

1

The Chinese University of Hong Kong, Prince of Wale Hospital

Hong Kong, Shatin, Hong Kong

Accuracy of Deep-learning Algorithm for Detection and Risk Stratification of Lung Nodules | DecenTrialz