RESUMO
PURPOSE: A hybrid principal component analysis and projection onto dipole fields (PCA-PDF) MR thermometry motion compensation algorithm was optimized with atlas image augmentation and validated. METHODS: Experiments were conducted on a 3T Philips MRI and Profound V1 Sonalleve high intensity focused ultrasound (high intensity focused ultrasound system. An MR-compatible robot was configured to induce motion on custom gelatin phantoms. Trials with periodic and sporadic motion were introduced on phantoms while hyperthermia was administered. The PCA-PDF algorithm was augmented with a predictive atlas to better compensate for larger sporadic motion. RESULTS: During periodic motion, the temperature SD in the thermometry was improved from 1 . 1 ± 0 . 1 $$ 1.1\pm 0.1 $$ to 0 . 5 ± 0 . 1 ∘ $$ 0.5\pm 0.{1}^{\circ } $$ C with both the original and augmented PCA-PDF application. For large sporadic motion, the augmented atlas improved the motion compensation from the original PCA-PDF correction from 8 . 8 ± 0 . 5 $$ 8.8\pm 0.5 $$ to 0 . 7 ± 0 . 1 ∘ $$ 0.7\pm 0.{1}^{\circ } $$ C. CONCLUSION: The PCA-PDF algorithm improved temperature accuracy to <1°C during periodic motion, but was not able to adequately address sporadic motion. By augmenting the PCA-PDF algorithm, temperature SD during large sporadic motion was also reduced to <1°C, greatly improving the original PCA-PDF algorithm.
