Ultra-low-dose Whole-body CT Using AI-based CT Reconstruction in Patients With Multiple Myeloma

Sponsor

Seoul National University Hospital (Other)

Overall Status

Recruiting

CT.gov ID

NCT05577884

Collaborator

(none)

Enrollment

Location

4.8

Anticipated Duration (Months)

6.3

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

This prospective study aims to perform intra-individual comparison of the image quality between ultra-low-dose whole-body CT with deep learning reconstruction and conventional low-dose whole-body CT with iterative reconstruction in patients with suspected multiple myeloma.

Condition or Disease	Intervention/Treatment	Phase
Multiple Myeloma	Diagnostic Test: noncontrast-enhanced whole-body CT

Study Design

Study Type:

Observational

Anticipated Enrollment :

30 participants

Observational Model:

Cohort

Time Perspective:

Prospective

Official Title:

Noise Reduction and Image Quality Improvement in Ultra-low-dose Whole-body CT Scans Using AI-based CT Reconstruction Program (ClariCT.AI) in Patients With Multiple Myeloma: A Prospective, Single-center Study

Actual Study Start Date :

Oct 6, 2022

Anticipated Primary Completion Date :

Dec 31, 2022

Anticipated Study Completion Date :

Feb 28, 2023

Arms and Interventions

Arm	Intervention/Treatment
Multiple myeloma Patients with suspicion of multiple myeloma and scheduled for CT	Diagnostic Test: noncontrast-enhanced whole-body CT noncontrast-enhanced low-dose whole-body CT using dual-source CT scanner using A-tube (75% radiation) and B-tube (25% radiation). conventional low-dose CT data (A +B tubes, 100% dose) are reconstructed with iterative reconstruction ultra-low dose CT data (B-tube only, 25% dose) are reconstructed with deep learning commercially available software.

Arm

Intervention/Treatment

Multiple myeloma

Patients with suspicion of multiple myeloma and scheduled for CT

Diagnostic Test: noncontrast-enhanced whole-body CT

noncontrast-enhanced low-dose whole-body CT using dual-source CT scanner using A-tube (75% radiation) and B-tube (25% radiation). conventional low-dose CT data (A +B tubes, 100% dose) are reconstructed with iterative reconstruction ultra-low dose CT data (B-tube only, 25% dose) are reconstructed with deep learning commercially available software.

Outcome Measures

Primary Outcome Measures

Contrast-to-noise ratio [3 months after the CT scan]
Contrast-to-noise ratio (CNR) of the vertebral body and paraspinal muscle obtained at L1 vertebra level

Other Outcome Measures

Noise [3 months after the CT scan]
Noise at paraspinal muscle
Signal-to-noise ratio (SNR) [3 months after the CT scan]
Signal-to-noise ratio (SNR) at paraspinal muscle
Edge rising distance [3 months after the CT scan]
Edge rising distance at vertebral cortex
Subjective overall image quality [3 months after the CT scan]
Subjective overall image quality on four-point scale (1: worst, 4: excellent, representative value is average score)
Conspicuity of bone structure [3 months after the CT scan]
Conspicuity of bone structure on four-point scale (1: worst, 4: excellent, representative value is average score)
Conspicuity of soft tissue [3 months after the CT scan]
Conspicuity of soft tissue on four-point scale (1: worst, 4: excellent, representative value is average score)
Lesion detectability [3 months after the CT scan]
Myeloma lesion detection rate on conventional low-dose CT and ultra-low-dose CT by blinded reviewers

Eligibility Criteria

Criteria

Ages Eligible for Study:

19 Years to 85 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

signed informed consent
patients with suspected multiple myeloma and scheduled for noncontrast-enhanced low-dose whole-body CT
patients who have no previous history of chemotherapy for multiple myeloma

Exclusion Criteria:

patients who do not agree to the protocol
non-Korean patients
pregnancy

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Seoul National University Hospital	Seoul		Korea, Republic of	03080

Sponsors and Collaborators

Seoul National University Hospital

Investigators

Principal Investigator: Hee-Dong Chae, MD, Seoul National University Hospital

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Hee-Dong Chae, Clinical Professor, Seoul National University Hospital

ClinicalTrials.gov Identifier:

NCT05577884

Other Study ID Numbers:

SNUH-2021-4317

First Posted:

Oct 13, 2022

Last Update Posted:

Nov 8, 2022

Last Verified:

Nov 1, 2022

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Yes

Additional relevant MeSH terms:

Multiple Myeloma

Neoplasms, Plasma Cell

Study Results

No Results Posted as of Nov 8, 2022