Establishing Automatic Method of Counting and Classify Bone Marrow and Peripheral Blood Cells

NCT04551235 | Unknown

• 1 other identifier: 202007086RIPB
• Study Type: observational
• Target: 900
• Locations: 1 country
• Sites: 1

Brief Summary

Counting and classification of blood cells in a bone marrow smear and peripheral blood smear are essential to clinical hematology. To this date, this procedure has been carried out in a manual manner in the great majority of clinical settings. There is often inconsistency in the counting result between different operators largely due to its manual nature. There has not been an effective and standard method for blood smear preparation and automatic counting and classification. The recent advent of deep neural network for medical image processing introduced new opportunities for an effective solution of this long-standing problem. Numerous results have been published on the effectiveness of convolutional neural network in clinical image recognition task.

Conditions

Hematologic Diseases; Artificial Intelligence; Acute Leukemia

Outcome Measures

Primary Outcomes (1)

• Evaluate the accuracy of cell counting and classifying between automatic method and manual method through digital microscopic photos of bone marrow smear and peripheral blood smear using deep convolutional neural networks

  3 years

Interventions

there are not any interventions in this study OTHER

there are not any interventions in this study

Eligibility Criteria

• Age: 20 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients who have suspected or confirmed hematological diseases and receive bone marrow or peripheral blood cell morphological examination in National Taiwan University Cancer Center

You may qualify if:

• Patients who have suspected or confirmed hematological diseases and receive bone
• marrow or peripheral blood cell morphological examination in National Taiwan University Cancer Center
• Patients who are aged more than 20 y/o

You may not qualify if:

• Patients who are not willing to sign informed consents

Sponsors & Collaborators

• National Taiwan University Hospital: lead
• National Taiwan University Tai-Chen Cell Therapy Center, Biomdcare Corporation: collaborator

Study Sites (1)

National Taiwan University Tai-Chen Cell Therapy Center

Taipei, Taiwan

RECRUITING

MeSH Terms

Conditions

Hematologic Diseases

Condition Hierarchy (Ancestors)

Hemic and Lymphatic Diseases

Central Study Contacts

Bor-Sheng Ko

CONTACT

886-0-72651297; kevinkomd@gmail.com

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 27, 2020
• First Posted: September 16, 2020
• Study Start: August 28, 2020
• Primary Completion: December 31, 2023
• Study Completion: December 31, 2023
• Last Updated: March 10, 2022

Record last verified: 2022-03

Locations

TW (1)