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- Title
PRFS-Based MR Thermometry Versus an Alternative T1 Magnitude Method – Comparative Performance Predicting Thermally Induced Necrosis in Hepatic Tumor Ablation.
- Authors
Rosenberg, Christian; Kickhefel, Antje; Mensel, Birger; Pickartz, Tilman; Puls, Ralf; Roland, Joerg; Hosten, Norbert
- Abstract
Objective:To compare the accuracy of a semi-quantitative proton resonance frequency shift (PRFS) thermal mapping interface and an alternative qualitative T1 thermometry model in predicting tissue necrosis in an established routine setting of MRI-guided laser ablation in the human liver. Materials and Methods:34 cases of PRFS-guided (GRE) laser ablation were retrospectively matched with 34 cases from an earlier patient population of 73 individuals being monitored through T1 magnitude image evaluation (FLASH 2D). The model-specific real-time estimation of necrotizing thermal impact (above 54 °C zone and T1 signal loss, respectively) was correlated in size with the resulting necrosis as shown by lack of enhancement on the first-day contrast exam (T1). Matched groups were compared using the Mann-Whitney test. Results:Online PRFS guidance was available in 33 of 34 cases. Positive size correlation between calculated impact zone and contrast defect at first day was evident in both groups (p < 0.0004). The predictive error estimating necrosis was median 21 % (range 1 % - 52 %) in the PRFS group and 61 % (range 22 - 84 %) in the T1 magnitude group. Differences in estimating lethal impact were significant (p = 0.004), whereas the real extent of therapy-induced necrosis showed no significant difference (p > 0.28) between the two groups. Conclusion:PRFS thermometry is feasible in a clinical setting of thermal hepatic tumor ablation. As an interference-free MR-tool for online therapy monitoring its accuracy to predict tissue necrosis is superior to a competing model of thermally induced alteration of the T1 magnitude signal.
- Subjects
THERMOMETRY; NECROSIS; ABLATION techniques; TUMOR treatment; LIVER tumors; MAGNETIC resonance imaging; STATISTICAL correlation; U-statistics
- Publication
PLoS ONE, 2013, Vol 8, Issue 10, p1
- ISSN
1932-6203
- Publication type
Article
- DOI
10.1371/journal.pone.0078559