Magnetic resonance elastography: evaluation of new inversion algorithm and quantitative analysis method
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| 008 | 210128e20150401xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00261-015-0372-5 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00261-015-0372-5 | ||
| 245 | 0 | 0 | |a Magnetic resonance elastography: evaluation of new inversion algorithm and quantitative analysis method |h [Elektronische Daten] |c [Annelise Silva, Roger Grimm, Kevin Glaser, Yinlin Fu, Teresa Wu, Richard Ehman, Alvin Silva] |
| 520 | 3 | |a Purpose: To assess mean shear hepatic stiffness calculations using various region of interest (ROI) techniques, a new inversion algorithm, and a confidence threshold mask. Methods: Seventy-three patients (49 with abnormal liver function tests/known chronic liver disease and 24 healthy liver transplant donors) underwent liver biopsy and magnetic resonance elastography (MRE). MRE data processed with the current inversion algorithm [multiscale direct inversion (MSDI)] was assessed using 2 ROI methods (single vs. triple). The data were then reprocessed using the new inversion algorithm (multimodel direct inversion [MMDI]) Hepatic stiffness calculations were performed using a single (70%) ROI method, with/without a 95% confidence threshold mask, and compared with MSDI. Results: For MSDI, average stiffness difference between single and triple ROI methods was not statistically significant by the 2-sample t test [0.15 kilopascals (kPa); P=.77]. For the 2 algorithms, there was little difference in average stiffness measurements of MSDI and MMDI (mean, 0.32kPa; 9%) using a confidence mask with good agreement [intraclass correlation coefficient (ICC), 0.986 (95% CI 0.975-0.994)]. Use of the confidence mask showed excellent consistency and less variance [ICC, 0.995 (95% CI 0.993-0.998)] compared to either the inter-observer or intra-observer freehand technique. Conclusion: MRE analysis showed no significant difference between the 2 freehand ROI techniques. With a 9% average kPa variance, stiffness measurements for MSDI and MMDI were also not significantly different. The use of the confidence mask reduces calculated stiffness variability, which impacts the use of MRE for assessing therapy response and initial/longitudinal assessment of chronic liver disease. | |
| 540 | |a Springer Science+Business Media New York, 2015 | ||
| 690 | 7 | |a Cirrhosis |2 nationallicence | |
| 690 | 7 | |a Liver donor |2 nationallicence | |
| 690 | 7 | |a Liver elastography |2 nationallicence | |
| 690 | 7 | |a Magnetic resonance elastography |2 nationallicence | |
| 690 | 7 | |a Magnetic resonance imaging |2 nationallicence | |
| 690 | 7 | |a ICC : Intraclass correlation coefficient |2 nationallicence | |
| 690 | 7 | |a kPA : Kilopascals |2 nationallicence | |
| 690 | 7 | |a MMDI : Multimodel direct inversion |2 nationallicence | |
| 690 | 7 | |a MRE : Magnetic resonance elastography |2 nationallicence | |
| 690 | 7 | |a MSDI : Multiscale direct inversion |2 nationallicence | |
| 690 | 7 | |a ROI : Region of interest |2 nationallicence | |
| 700 | 1 | |a Silva |D Annelise |u Barrett, The Honors College, Arizona State University, Tempe, AZ, USA |4 aut | |
| 700 | 1 | |a Grimm |D Roger |u Department of Radiology, Mayo Clinic, Rochester, MN, USA |4 aut | |
| 700 | 1 | |a Glaser |D Kevin |u Department of Radiology, Mayo Clinic, Rochester, MN, USA |4 aut | |
| 700 | 1 | |a Fu |D Yinlin |u School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA |4 aut | |
| 700 | 1 | |a Wu |D Teresa |u School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA |4 aut | |
| 700 | 1 | |a Ehman |D Richard |u Department of Radiology, Mayo Clinic, Rochester, MN, USA |4 aut | |
| 700 | 1 | |a Silva |D Alvin |u Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, 85259, Scottsdale, AZ, USA |4 aut | |
| 773 | 0 | |t Abdominal Imaging |d Springer US; http://www.springer-ny.com |g 40/4(2015-04-01), 810-817 |x 0942-8925 |q 40:4<810 |1 2015 |2 40 |o 261 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00261-015-0372-5 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00261-015-0372-5 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Silva |D Annelise |u Barrett, The Honors College, Arizona State University, Tempe, AZ, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Grimm |D Roger |u Department of Radiology, Mayo Clinic, Rochester, MN, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Glaser |D Kevin |u Department of Radiology, Mayo Clinic, Rochester, MN, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Fu |D Yinlin |u School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Wu |D Teresa |u School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Ehman |D Richard |u Department of Radiology, Mayo Clinic, Rochester, MN, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Silva |D Alvin |u Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, 85259, Scottsdale, AZ, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Abdominal Imaging |d Springer US; http://www.springer-ny.com |g 40/4(2015-04-01), 810-817 |x 0942-8925 |q 40:4<810 |1 2015 |2 40 |o 261 | ||