3D MR thermometry of frozen tissue: Feasibility and accuracy during cryoablation at 3T
SourceJournal of Magnetic Resonance Imaging, 44, 6, (2016), pp. 1572-1579
Article / Letter to editor
Display more detailsDisplay less details
Journal of Magnetic Resonance Imaging
SubjectRadboudumc 15: Urological cancers RIHS: Radboud Institute for Health Sciences
PURPOSE: To assess the feasibility and accuracy of 3D ultrashort echo time (UTE) magnetic resonance (MR) thermometry of frozen tissue during cryoablation on a clinical 3T MR system. MATERIALS AND METHODS: Ex vivo porcine muscle specimens (n = 4) were imaged during two cycles of 10:3 minutes freeze-thaw on a 3T clinical MR scanner. Continuous MR monitoring was performed using a 3D radial ramp-sampled UTE sequence with a shortest TE of 70 mus. Fiber optic sensors were used for temperature reference. Data of three experiments were used as reference sets. Signal intensity values were normalized to baseline before cooling and related to temperature. Data for subzero temperatures were fit to a monoexponential function. In the separate validation set, the obtained fit was used to generate 3D MR temperature maps of frozen tissue at each imaging timepoint. Statistical analysis was performed to assess accuracy of the MR temperature maps. RESULTS: With 3D UTE imaging, MR signal was measured from frozen tissue down to temperatures as low as -40 degrees C. Temperatures predicted from the MR temperature maps strongly correlated with sensor recorded values (r = 0.977, P < 0.001). Bland-Altman analysis demonstrated a mean difference between MR-estimated temperatures and sensor readings of -1.2 +/- 2.7 degrees C with upper and lower limits of agreement of +4.1 and -6.5 degrees C, respectively. CONCLUSION: 3D MR thermometry of frozen tissue using UTE signal intensity was feasible during cryoablation on a clinical 3T MR system. Down to temperatures as low as -40 degrees C, accuracy of the MR temperature maps was within clinically acceptable limits. J. Magn. Reson. Imaging 2016;44:1572-1579.
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.