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Tiyarattanachai T, Turco S, Eisenbrey JR, Wessner CE, Medellin-Kowalewski A, Wilson S, Lyshchik A, Kamaya A, Kaffas AE. A Comprehensive Motion Compensation Method for In-Plane and Out-of-Plane Motion in Dynamic Contrast-Enhanced Ultrasound of Focal Liver Lesions. ULTRASOUND IN MEDICINE & BIOLOGY 2022; 48:2217-2228. [PMID: 35970658 PMCID: PMC9529818 DOI: 10.1016/j.ultrasmedbio.2022.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 05/23/2022] [Accepted: 06/03/2022] [Indexed: 06/15/2023]
Abstract
Contrast-enhanced ultrasound (CEUS) acquisitions of focal liver lesions are affected by motion, which has an impact on contrast signal quantification. We therefore developed and tested, in a large patient cohort, a motion compensation algorithm called the Iterative Local Search Algorithm (ILSA), which can correct for both periodic and non-periodic in-plane motion and can reject frames with out-of-plane motion. CEUS cines of 183 focal liver lesions in 155 patients from three hospitals were used to develop and test ILSA. Performance was evaluated through quantitative metrics, including the root mean square error and R2 in fitting time-intensity curves and standard deviation value of B-mode intensities, computed across cine frames), and qualitative evaluation, including B-mode mean intensity projection images and parametric perfusion imaging. The median root mean square error significantly decreased from 0.032 to 0.024 (p < 0.001). Median R2 significantly increased from 0.88 to 0.93 (p < 0.001). The median standard deviation value of B-mode intensities significantly decreased from 6.2 to 5.0 (p < 0.001). B-Mode mean intensity projection images revealed improved spatial resolution. Parametric perfusion imaging also exhibited improved spatial detail and better differentiation between lesion and background liver parenchyma. ILSA can compensate for all types of motion encountered during liver CEUS, potentially improving contrast signal quantification of focal liver lesions.
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Affiliation(s)
- Thodsawit Tiyarattanachai
- Department of Radiology, Stanford University School of Medicine, Stanford, California, USA; Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Simona Turco
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - John R Eisenbrey
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Corinne E Wessner
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | | | - Stephanie Wilson
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Division of Gastroenterology, Department of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Andrej Lyshchik
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Aya Kamaya
- Department of Radiology, Stanford University School of Medicine, Stanford, California, USA
| | - Ahmed El Kaffas
- Department of Radiology, Stanford University School of Medicine, Stanford, California, USA.
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