Seung Hyun Lee1, Young Han Lee2, Jin-Suck Suh3. 1. Department of Radiology, Research Institute of Radiological Science, YUHS-KRIBB Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea; Department of Radiology, National Health Insurance Service Ilsan Hospital, 100 Ilsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do 10444, Republic of Korea. Electronic address: circle1128@nhimc.or.kr. 2. Department of Radiology, Research Institute of Radiological Science, YUHS-KRIBB Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea. Electronic address: sando@yuhs.ac. 3. Department of Radiology, Research Institute of Radiological Science, YUHS-KRIBB Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea. Electronic address: jss@yuhs.ac.
Abstract
PURPOSE: To compare image quality between compressed sensing (CS)-3D-fast spin-echo (FSE) and conventional 3D-FSE sequences for knee magnetic resonance imaging (MRI). METHODS: Knee MRI of 43 patients (male:female, 14:29; mean age, 53years) were acquired using conventional and CS-3D-FSE with an acceleration factor of 1.5. Overall image quality was assessed by correlation coefficient, root-mean-square error (RMSE), and structural similarity (SSIM) index. Regional image quality was evaluated using signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs). Subjective image quality was evaluated using a four-point scale. Diagnostic agreement for meniscal lesions between the two sequences was evaluated. RESULTS: The scan time was reduced from 7:14-8:08 to 4:53-5:08 with CS. A strong positive correlation was observed between data of the two sequences (mean r=0.880). The RMSE (mean, 126.861) and SSIM index (mean, 0.987) were acceptable. The SNRs and CNRs were not significantly different between the two sequences (P>0.05, each). There were no significant differences in the evaluation of the menisci and cruciate ligaments, while the CS images demonstrated inferior quality of cartilage-subchondral bone delineation. Diagnostic agreement for meniscal lesions between the two sequences was very good (κ=0.943-1). CONCLUSION: Compressed sensing-3D-FSE knee MRI produces images of acceptable quality while reducing scan time.
PURPOSE: To compare image quality between compressed sensing (CS)-3D-fast spin-echo (FSE) and conventional 3D-FSE sequences for knee magnetic resonance imaging (MRI). METHODS: Knee MRI of 43 patients (male:female, 14:29; mean age, 53years) were acquired using conventional and CS-3D-FSE with an acceleration factor of 1.5. Overall image quality was assessed by correlation coefficient, root-mean-square error (RMSE), and structural similarity (SSIM) index. Regional image quality was evaluated using signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs). Subjective image quality was evaluated using a four-point scale. Diagnostic agreement for meniscal lesions between the two sequences was evaluated. RESULTS: The scan time was reduced from 7:14-8:08 to 4:53-5:08 with CS. A strong positive correlation was observed between data of the two sequences (mean r=0.880). The RMSE (mean, 126.861) and SSIM index (mean, 0.987) were acceptable. The SNRs and CNRs were not significantly different between the two sequences (P>0.05, each). There were no significant differences in the evaluation of the menisci and cruciate ligaments, while the CS images demonstrated inferior quality of cartilage-subchondral bone delineation. Diagnostic agreement for meniscal lesions between the two sequences was very good (κ=0.943-1). CONCLUSION: Compressed sensing-3D-FSE knee MRI produces images of acceptable quality while reducing scan time.
Authors: Jessica R Mann; Ged G Wieschhoff; Ryan Tai; William C Wrobel; Nehal Shah; Jacob C Mandell Journal: Skeletal Radiol Date: 2019-08-17 Impact factor: 2.199
Authors: Jonathan I Tamir; Valentina Taviani; Marcus T Alley; Becki C Perkins; Lori Hart; Kendall O'Brien; Fidaa Wishah; Jesse K Sandberg; Michael J Anderson; Javier S Turek; Theodore L Willke; Michael Lustig; Shreyas S Vasanawala Journal: J Magn Reson Imaging Date: 2019-01-13 Impact factor: 4.813
Authors: Su Min Lee; Hye Jung Choo; Sun Joo Lee; Sung Kwan Kim; In Sook Lee; Dong Wook Kim; Jin Wook Baek; Young Jin Heo Journal: Korean J Radiol Date: 2019-03 Impact factor: 3.500