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

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

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05577884
Enrollment
30
Registered
2022-10-13
Start date
2022-10-06
Completion date
2023-02-28
Last updated
2022-11-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Multiple Myeloma

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.

Interventions

DIAGNOSTIC_TESTnoncontrast-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.

Sponsors

Seoul National University Hospital
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
19 Years to 85 Years
Healthy volunteers
No

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

Design outcomes

Primary

MeasureTime frameDescription
Contrast-to-noise ratio3 months after the CT scanContrast-to-noise ratio (CNR) of the vertebral body and paraspinal muscle obtained at L1 vertebra level

Other

MeasureTime frameDescription
Signal-to-noise ratio (SNR)3 months after the CT scanSignal-to-noise ratio (SNR) at paraspinal muscle
Edge rising distance3 months after the CT scanEdge rising distance at vertebral cortex
Subjective overall image quality3 months after the CT scanSubjective overall image quality on four-point scale (1: worst, 4: excellent, representative value is average score)
Noise3 months after the CT scanNoise at paraspinal muscle
Conspicuity of soft tissue3 months after the CT scanConspicuity of soft tissue on four-point scale (1: worst, 4: excellent, representative value is average score)
Lesion detectability3 months after the CT scanMyeloma lesion detection rate on conventional low-dose CT and ultra-low-dose CT by blinded reviewers
Conspicuity of bone structure3 months after the CT scanConspicuity of bone structure on four-point scale (1: worst, 4: excellent, representative value is average score)

Countries

South Korea

Contacts

Primary ContactHee-Dong Chae, MD
hdchae02@gmail.com82-2-2072-4209
Backup ContactJeong Hoon Park, BS
gns02066@naver.com82-2-2072-3610

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026