Abstract：
OBJECTIVE: 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.
CONCLUSIONS: 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.
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.
CONCLUSIONS: 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.
摘要：
目的：通过图集图像增强对MR测温运动补偿算法进行了优化和验证。
方法：在3TPhilipsMRI和ProfiedV1Sonalleve高强度聚焦超声（高强度聚焦超声系统。MR兼容的机器人被配置为在定制明胶体模上引起运动。在进行热疗的同时，在体模上引入了周期性和零星运动的试验。PCA-PDF算法用预测图集增强，以更好地补偿较大的零星运动。
结果：在周期性运动期间，测温中的温度SD从1提高。1±0。1$1.1\\pm0.1$$到0。5±0。1○$0.5\\pm0。{1}^{\\circ}$$C与原始和增强PCA-PDF应用程序。对于大的零星运动，增强图集从8改进了原始PCA-PDF校正的运动补偿。8±0。5$8.8\\pm0.5$$到0。7±0。1○$0.7\\pm0。{1}^{\\circ}$$C.
结论：PCA-PDF算法在周期性运动期间将温度精度提高到<1°C，但未能充分解决零星运动。通过增强PCA-PDF算法，大的零星运动过程中的温度SD也降低到<1°C，大大改进了原有的PCA-PDF算法。
方法：在3TPhilipsMRI和ProfiedV1Sonalleve高强度聚焦超声（高强度聚焦超声系统。MR兼容的机器人被配置为在定制明胶体模上引起运动。在进行热疗的同时，在体模上引入了周期性和零星运动的试验。PCA-PDF算法用预测图集增强，以更好地补偿较大的零星运动。
结果：在周期性运动期间，测温中的温度SD从1提高。1±0。1$1.1\\pm0.1$$到0。5±0。1○$0.5\\pm0。{1}^{\\circ}$$C与原始和增强PCA-PDF应用程序。对于大的零星运动，增强图集从8改进了原始PCA-PDF校正的运动补偿。8±0。5$8.8\\pm0.5$$到0。7±0。1○$0.7\\pm0。{1}^{\\circ}$$C.
结论：PCA-PDF算法在周期性运动期间将温度精度提高到<1°C，但未能充分解决零星运动。通过增强PCA-PDF算法，大的零星运动过程中的温度SD也降低到<1°C，大大改进了原有的PCA-PDF算法。
