PCA-based magnetic field modeling: application for on-line MR temperature monitoring

Improved cardiac magnetic resonance thermometry and dosimetry for monitoring lesion formation during catheter ablation

PURPOSE

A new real-time MR-thermometry pipeline was developed to measure multiple temperature images per heartbeat with 1.6×1.6×3 mm³ spatial resolution. The method was evaluated on 10 healthy volunteers and during radiofrequency ablation (RFA) in sheep.

METHODS

Multislice, electrocardiogram-triggered, echo-planar imaging was combined with parallel imaging, under free breathing conditions. In-plane respiratory motion was corrected on magnitude images by an optical flow algorithm. Motion-related susceptibility artifacts were compensated on phase images by an algorithm based on Principal Component Analysis. Correction of phase drift and temporal filter were included in the pipeline implemented in the Gadgetron framework. Contact electrograms were recorded simultaneously with MR thermometry by an MR-compatible ablation catheter.

RESULTS

The temporal standard deviation of temperature in the left ventricle remained below 2 °C on each volunteer. In sheep, focal heated regions near the catheter tip were observed on temperature images (maximal temperature increase of 38 °C) during RFA, with contact electrograms of acceptable quality. Thermal lesion dimensions at gross pathology were in agreement with those observed on thermal dose images.

CONCLUSION

This fully automated MR thermometry pipeline (five images/heartbeat) provides direct assessment of lesion formation in the heart during catheter-based RFA, which may improve treatment of cardiac arrhythmia by ablation. Magn Reson Med 77:673-683, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

MR-guided thermotherapy of abdominal organs using a robust PCA-based motion descriptor

Thermotherapies can now be guided in real-time using magnetic resonance imaging (MRI). This technique is rapidly gaining importance in interventional therapies for abdominal organs such as liver and kidney. An accurate online estimation and characterization of organ displacement is mandatory to prevent misregistration and correct for motion related thermometry artifacts. In addition, when the ablation is performed with an extracorporal heating device such as high intensity focused ultrasound (HIFU), the continuous estimation of the organ displacement is the basis for the dynamic adjustment of the focal point position to track the targeted pathological tissue. In this paper, we describe the use of an optimized principal component analysis (PCA)-based motion descriptor to characterize in real-time the complex organ deformation during the therapy. The PCA was used to detect, in a preparative learning step, spatio-temporal coherences in the motion of the targeted organ. During hyperthermia, incoherent motion patterns could be discarded, which enabled improvements in motion estimation robustness, the compensation of motion related errors in thermal maps, and the adjustment of the beam position. The suggested method was evaluated for a moving phantom, and tested in vivo in the kidney and the liver of 12 healthy volunteers under free breathing conditions. The ability to perform a MR-guided thermotherapy in vivo during HIFU intervention was finally demonstrated on a porcine kidney.