Sean Tenant1, Chun Lap Pang2, Prageeth Dissanayake2, Varut Vardhanabhuti3,4, Colin Stuckey5, Catherine Gutteridge5, Christopher Hyde6, Carl Roobottom3,5. 1. Peninsula Radiology Academy, William Prance Rd, Plymouth, PL6 5WR, UK. sean.tenant@nhs.net. 2. Peninsula Radiology Academy, William Prance Rd, Plymouth, PL6 5WR, UK. 3. Plymouth University Peninsula Schools of Medicine and Dentistry, John Bull Building, Plymouth, PL6 8BU, UK. 4. Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Pokfulam, Hong Kong. 5. Plymouth Hospitals NHS Trust, Derriford Rd, Plymouth, PL6 8DH, UK. 6. University of Exeter Medical School, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK.
Abstract
OBJECTIVES: To evaluate the accuracy of reduced-dose CT scans reconstructed using a new generation of model-based iterative reconstruction (MBIR) in the imaging of urinary tract stone disease, compared with a standard-dose CT using 30% adaptive statistical iterative reconstruction. METHODS: This single-institution prospective study recruited 125 patients presenting either with acute renal colic or for follow-up of known urinary tract stones. They underwent two immediately consecutive scans, one at standard dose settings and one at the lowest dose (highest noise index) the scanner would allow. The reduced-dose scans were reconstructed using both ASIR 30% and MBIR algorithms and reviewed independently by two radiologists. Objective and subjective image quality measures as well as diagnostic data were obtained. RESULTS: The reduced-dose MBIR scan was 100% concordant with the reference standard for the assessment of ureteric stones. It was extremely accurate at identifying calculi of 3 mm and above. The algorithm allowed a dose reduction of 58% without any loss of scan quality. CONCLUSIONS: A reduced-dose CT scan using MBIR is accurate in acute imaging for renal colic symptoms and for urolithiasis follow-up and allows a significant reduction in dose. KEY POINTS: • MBIR allows reduced CT dose with similar diagnostic accuracy • MBIR outperforms ASIR when used for the reconstruction of reduced-dose scans • MBIR can be used to accurately assess stones 3 mm and above.
OBJECTIVES: To evaluate the accuracy of reduced-dose CT scans reconstructed using a new generation of model-based iterative reconstruction (MBIR) in the imaging of urinary tract stone disease, compared with a standard-dose CT using 30% adaptive statistical iterative reconstruction. METHODS: This single-institution prospective study recruited 125 patients presenting either with acute renal colic or for follow-up of known urinary tract stones. They underwent two immediately consecutive scans, one at standard dose settings and one at the lowest dose (highest noise index) the scanner would allow. The reduced-dose scans were reconstructed using both ASIR 30% and MBIR algorithms and reviewed independently by two radiologists. Objective and subjective image quality measures as well as diagnostic data were obtained. RESULTS: The reduced-dose MBIR scan was 100% concordant with the reference standard for the assessment of ureteric stones. It was extremely accurate at identifying calculi of 3 mm and above. The algorithm allowed a dose reduction of 58% without any loss of scan quality. CONCLUSIONS: A reduced-dose CT scan using MBIR is accurate in acute imaging for renal colic symptoms and for urolithiasis follow-up and allows a significant reduction in dose. KEY POINTS: • MBIR allows reduced CT dose with similar diagnostic accuracy • MBIR outperforms ASIR when used for the reconstruction of reduced-dose scans • MBIR can be used to accurately assess stones 3 mm and above.
Authors: Yoshiko Sagara; Amy K Hara; William Pavlicek; Alvin C Silva; Robert G Paden; Qing Wu Journal: AJR Am J Roentgenol Date: 2010-09 Impact factor: 3.959
Authors: Varut Vardhanabhuti; Robert J Loader; Grant R Mitchell; Richard D Riordan; Carl A Roobottom Journal: AJR Am J Roentgenol Date: 2013-03 Impact factor: 3.959
Authors: Aaron Sodickson; Pieter F Baeyens; Katherine P Andriole; Luciano M Prevedello; Richard D Nawfel; Richard Hanson; Ramin Khorasani Journal: Radiology Date: 2009-04 Impact factor: 11.105
Authors: Daniele Marin; Rendon C Nelson; Sebastian T Schindera; Samuel Richard; Richard S Youngblood; Terry T Yoshizumi; Ehsan Samei Journal: Radiology Date: 2010-01 Impact factor: 11.105