Venkatesh L Murthy1, Edward P Ficaro2,1, Alexis Poitrasson-Rivière3, Jonathan B Moody2, Tomoe Hagio2, Richard L Weinberg1, James R Corbett4. 1. Division of Cardiovascular Medicine, Department of Internal Medicine and Frankel Cardiovascular Center, University of Michigan, Ann Arbor, USA. 2. INVIA Medical Imaging Solutions, 3025 Boardwalk Dr. Suite 200, Ann Arbor, MI, 48108, USA. 3. INVIA Medical Imaging Solutions, 3025 Boardwalk Dr. Suite 200, Ann Arbor, MI, 48108, USA. apoitrasson@inviasolutions.com. 4. Division of Nuclear Medicine, Department of Radiology and Frankel Cardiovascular Center, University of Michigan, Ann Arbor, USA.
Abstract
BACKGROUND: Clinical use of myocardial blood flow (MBF) and flow reserve (MFR) is increasing. Motion correction is necessary to obtain accurate results but can introduce variability when performed manually. We sought to reduce that variability with an automated motion-correction algorithm. METHODS: A blinded randomized controlled trial of two technologists was performed on the motion correction of 100 dynamic 82Rb patient studies comparing manual motion correction with manual review and adjustment of automated motion correction. Inter-rater variability between technologists for MBF and MFR was the primary outcome with comparison made by analysis of the limits of agreement. Processing time was the secondary outcome. RESULTS: Limits of agreements between the two technologists decreased significantly for both MBF and MFR, going from [- 0.22, 0.22] mL/min/g and [- 0.31, 0.36] to [- 0.12, 0.15] mL/min/g and [- 0.15, 0.18], respectively (both P < .002). In addition, the average time spent on motion correcting decreased by 1 min per study from 5:21 to 4:21 min (P = .001). CONCLUSIONS: In this randomized controlled trial, the use of automated motion correction significantly decreased inter-user variability and reduced processing time.
BACKGROUND: Clinical use of myocardial blood flow (MBF) and flow reserve (MFR) is increasing. Motion correction is necessary to obtain accurate results but can introduce variability when performed manually. We sought to reduce that variability with an automated motion-correction algorithm. METHODS: A blinded randomized controlled trial of two technologists was performed on the motion correction of 100 dynamic 82Rb patient studies comparing manual motion correction with manual review and adjustment of automated motion correction. Inter-rater variability between technologists for MBF and MFR was the primary outcome with comparison made by analysis of the limits of agreement. Processing time was the secondary outcome. RESULTS: Limits of agreements between the two technologists decreased significantly for both MBF and MFR, going from [- 0.22, 0.22] mL/min/g and [- 0.31, 0.36] to [- 0.12, 0.15] mL/min/g and [- 0.15, 0.18], respectively (both P < .002). In addition, the average time spent on motion correcting decreased by 1 min per study from 5:21 to 4:21 min (P = .001). CONCLUSIONS: In this randomized controlled trial, the use of automated motion correction significantly decreased inter-user variability and reduced processing time.
Entities:
Keywords:
Image analysis; Myocardial blood flow; PET
Authors: Benjamin C Lee; Jonathan B Moody; Alexis Poitrasson-Rivière; Amanda C Melvin; Richard L Weinberg; James R Corbett; Venkatesh L Murthy; Edward P Ficaro Journal: J Nucl Cardiol Date: 2018-11-07 Impact factor: 5.952
Authors: Ran Klein; Jennifer M Renaud; Maria C Ziadi; Stephanie L Thorn; Andy Adler; Rob S Beanlands; Robert A deKemp Journal: J Nucl Cardiol Date: 2010-04-13 Impact factor: 5.952
Authors: Venkatesh L Murthy; Masanao Naya; Courtney R Foster; Jon Hainer; Mariya Gaber; Gilda Di Carli; Ron Blankstein; Sharmila Dorbala; Arkadiusz Sitek; Michael J Pencina; Marcelo F Di Carli Journal: Circulation Date: 2011-10-17 Impact factor: 29.690
Authors: Maria C Ziadi; Robert A Dekemp; Kathryn A Williams; Ann Guo; Benjamin J W Chow; Jennifer M Renaud; Terrence D Ruddy; Niroshi Sarveswaran; Rebecca E Tee; Rob S B Beanlands Journal: J Am Coll Cardiol Date: 2011-08-09 Impact factor: 24.094
Authors: Masanao Naya; Venkatesh L Murthy; Viviany R Taqueti; Courtney R Foster; Josh Klein; Mariya Garber; Sharmila Dorbala; Jon Hainer; Ron Blankstein; Frederick Resnic; Marcelo F Di Carli Journal: J Nucl Med Date: 2014-01-09 Impact factor: 10.057
Authors: Yang Zuo; Ramsey D Badawi; Cameron C Foster; Thomas Smith; Javier E López; Guobao Wang Journal: IEEE Trans Radiat Plasma Med Sci Date: 2020-10-15
Authors: Piotr J Slomka; Jonathan B Moody; Robert J H Miller; Jennifer M Renaud; Edward P Ficaro; Ernest V Garcia Journal: J Nucl Cardiol Date: 2020-10-16 Impact factor: 5.952
Authors: Jonathon A Nye; Marina Piccinelli; Doyeon Hwang; Charles David Cooke; Jin Chul Paeng; Joo Myung Lee; Sang-Geon Cho; Russell Folks; Hee-Seung Bom; Bon-Kwon Koo; Ernest V Garcia Journal: Med Phys Date: 2021-07-20 Impact factor: 4.506