Predicting ablation zones with multislice volumetric 2-D magnetic resonance thermal imaging

Intraoperative Ablation Control Based on Real-Time Necrosis Monitoring Feedback: Numerical Evaluation

Ablation therapy is a type of minimally invasive treatment, utilized for various organs including the brain, heart, and kidneys. The accuracy of the ablation process is critically important to avoid both insufficient and excessive ablation, which may result in compromised efficacy or complications. The thermal ablation is formulated by two theoretical models: the heat transfer (HT) and necrosis formation (NF) models. In modern medical practices, feed-forward (FF) and temperature feedback (TFB) controls are primarily used as ablation control methodologies. FF involves pre-therapy procedure planning based on previous experiences and theoretical knowledge without monitoring the intraoperative tissue response, hence, it can't compensate for discrepancies in the assumed HT or NF models. These discrepancies can arise due to individual patient's tissue characteristic differences and specific environmental conditions. Conversely, TFB control is based on the intraoperative temperature profile. It estimates the resulting heat damage based on the monitored temperature distribution and assumed NF model. Therefore, TFB can make necessary adjustments even if there is an error in the assumed HT model. TFB is thus seen as a more robust control method against modeling errors in the HT model. Still, TFB is limited as it assumes a fixed NF model, irrespective of the patient or the ablation technique used. An ideal solution to these limitations would be to actively monitor heat damage to the tissue during the operation and utilize this data to control ablation. This strategy is defined as necrosis feedback (NFB) in this study. Such real-time necrosis monitoring modalities making NFB possible are emerging, however, there is an absence of a generalized study that discusses the integration and quantifies the significance of the real-time necrosis monitor techniques for ablation therapy. Such an investigation is expected to clarify the universal principles of how these techniques would improve ablation therapy. In this study, we examine the potential of NFB in suppressing errors associated with the NF model as NFB is theoretically capable of monitoring and suppressing the errors associated with the NF models in its closed control loop. We simulate and compare the performances of TFB and NFB with artificially generated modeling errors using the finite element method (FEM). The results show that NFB provides more accurate ablation control than TFB when NF-oriented errors are applied, indicating NFB's potential to improve the ablation control accuracy and highlighting the value of the ongoing research to make real-time necrosis monitoring a clinically viable option.

Intraoperative Ablation Control Based on Real-time Necrosis Monitoring Feedback: Numerical Evaluation

Ablation therapy is a type of minimally invasive treatment, utilized for various organs including the brain, heart, and kidneys. The accuracy of the ablation process is critically important to avoid both insufficient and excessive ablation, which may result in compromised efficacy or complications. The thermal ablation is formulated by two theoretical models: the heat transfer (HT) and necrosis formation (NF) models. In modern medical practices, feed-forward (FF) and temperature feedback (TFB) controls are primarily used as ablation control methodologies. FF involves pre-therapy procedure planning based on previous experiences and theoretical knowledge without monitoring the intraoperative tissue response, hence, it can't compensate for discrepancies in the assumed HT or NF models. These discrepancies can arise due to individual patient's tissue characteristic differences and specific environmental conditions. Conversely, TFB control is based on the intraoperative temperature profile. It estimates the resulting heat damage based on the monitored temperature distribution and assumed NF model. Therefore, TFB can make necessary adjustments even if there is an error in the assumed HT model. TFB is thus seen as a more robust control method against modeling errors in the HT model. Still, TFB is limited as it assumes a fixed NF model, irrespective of the patient or the ablation technique used. An ideal solution to these limitations would be to actively monitor heat damage to the tissue during the operation and utilize this data to control ablation. This strategy is defined as necrosis feedback (NFB) in this study. Such real-time necrosis monitoring modalities making NFB possible are emerging, however, there is an absence of a generalized study that discusses the integration and quantifies the significance of the real-time necrosis monitor techniques for ablation therapy. Such an investigation is expected to clarify the universal principles of how these techniques would improve ablation therapy. In this study, we examine the potential of NFB in suppressing errors associated with the NF model as NFB is theoretically capable of monitoring and suppressing the errors associated with the NF models in its closed control loop. We simulate and compare the performances of TFB and NFB with artificially generated modeling errors using the finite element method (FEM). The results show that NFB provides more accurate ablation control than TFB when NF-oriented errors are applied, indicating NFB's potential to improve the ablation control accuracy and highlighting the value of the ongoing research to make real-time necrosis monitoring a clinically viable option.

MR thermometry imaging for low intensity focused ultrasound modulation of spinal nervous tissue

OBJECTIVES

Previously in rodent and swine models, we have shown that external low intensity focused ultrasound (liFUS) can be used to modulate pain responses. To ensure no adverse heating events occur with liFUS modulation in a non-invasive manner, we perform initial work in swine to show that magnetic resonance thermometry imaging (MRTI) is capable of measuring <2.0 °C changes at the L5 DRG. Further, we show that our device can be constructed in an MR-compatible fashion to minimize artifact.

METHODS

Three MRTI techniques (referenceless, corrected proton resonance frequency shift (PRFS), and PRFS) were applied to assess accuracy of detecting thermal changes at the L5 DRG in unheated euthanized swine. A region of interest (ROI) that includes the L5 DRG was delineated, within which MRTI temperature changes were spatially averaged (ground truth 0 °C). In separate experiments with phantoms, B0 field-inhomogeneity, RF transmit (B1+) and fast gradient echo (fSPGR) magnitude images were acquired to downselect liFUS device materials that produce the least MRI artifacts.

RESULTS

Referenceless, corrected PRFS, and PRFS MRTI resulted in temperature measurements of 0.8 ± 1.1 °C, 1.1 ± 1.3 °C and 5.2 ± 5 °C, respectively. Both materials caused B0 perturbation but minimal B1+ and MRTI artifacts. The presence of imaging artifacts did not preclude thermal imaging of the region.

SIGNIFICANCE

We provide preliminary data suggesting that referenceless MRTI can adequately detect small thermal changes at the DRG that may occur with neuromodulation, which is one of the first steps in creating a table of safe parameters for liFUS therapy in humans.

What happens to brain outside the thermal ablation zones? An assessment of needle-based therapeutic ultrasound in survival swine

BACKGROUND

In stereotactic radiosurgery, isodose lines must be considered to determine how surrounding tissue is affected. In thermal ablative therapy, such as laser interstitial thermal therapy (LITT), transcranial MR-guided focused ultrasound (tcMRgFUS), and needle-based therapeutic ultrasound (NBTU), how the surrounding area is affected has not been well studied.

OBJECTIVE

We aimed to quantify the transition zone surrounding the ablation core created by magnetic resonance-guided robotically-assisted (MRgRA) delivery of NBTU using multi-slice volumetric 2-D magnetic resonance thermal imaging (MRTI) and subsequent characterization of the resultant tissue damage using histopathologic analysis.

METHODS

Four swine underwent MRgRA NBTU using varying duration and wattage for treatment delivery. Serial MRI images were obtained, and the most representative were overlaid with isodose lines and compared to brain tissue acquired postmortem which underwent histopathologic analysis. These results were also compared to predicted volumes using a finite element analysis model. Contralateral brain tissue was used for control data.

RESULTS

Intraoperative MRTI thermal isodose contours were characterized and comprehensively mapped to post-operative MRI images and qualitatively compared with histological tissue sections postmortem. NBTU 360° ablations induced smaller lesion volumes (33.19 mm³; 120 s, 3 W; 30.05 mm³, 180 s, 4 W) versus 180° ablations (77.20 mm³, 120 s, 3 W; 109.29 mm³; 180 s; 4 W). MRTI/MRI overlay demonstrated the lesion within the proximal isodose lines. The ablation-zone was characterized by dense macrophage infiltration and glial/neuronal loss as demonstrated by glial fibrillary acidic protein (GFAP) and neurofilament (NF) absence and avid CD163 staining. The transition-zone between lesion and normal brain demonstrated decreased macrophage infiltration and measured ∼345 microns (n - 3). We did not detect overt hemorrhages or signs of edema in the adjacent spared tissue.

CONCLUSION

We successfully performed MRgRA NBTU ablation in swine and demonstrated minimal histologic changes extended past the ablation-zone. The lesion was characterized by macrophage infiltration and glial/neuronal loss which decreased through the transition-zone.

Comparison study of reconstruction algorithms for volumetric necrosis maps from 2D multi-slice GRE thermometry images

Cancer is a disease which requires a significant amount of careful medical attention. For minimally-invasive thermal ablation procedures, the monitoring of heat distribution is one of the biggest challenges. In this work, three approaches for volumetric heat map reconstruction (Delauney triangulation, minimum volume enclosing ellipsoids (MVEE) and splines) are presented based on uniformly distributed 2D MRI phase images rotated around the applicator’s main axis. We compare them with our previous temperature interpolation method with respect to accuracy, robustness and adaptability. All approaches are evaluated during MWA treatment on the same data sets consisting of 13 ex vivo bio protein phantoms, including six phantoms with simulated heat sink effects. Regarding accuracy, the DSC similarity results show a strong trend towards the MVEE (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.80\pm 0.03$$\end{document}0.80±0.03) and the splines (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.77\pm 0.04$$\end{document}0.77±0.04) method compared to the Delauney triangulation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.75\pm 0.02$$\end{document}0.75±0.02) or the temperature interpolation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.73\pm 0.07$$\end{document}0.73±0.07). Robustness is increased for all three approaches and the adaptability shows a significant trend towards the initial interpolation method and the splines. To overcome local inhomogeneities in the acquired data, the use of adaptive simulations should be considered in the future. In addition, the transfer to in vivo animal experiments should be considered to test for clinical applicability.

State of the Art and Future Opportunities in MRI-Guided Robot-Assisted Surgery and Interventions

Magnetic resonance imaging (MRI) can provide high-quality 3-D visualization of target anatomy, surrounding tissue, and instrumentation, but there are significant challenges in harnessing it for effectively guiding interventional procedures. Challenges include the strong static magnetic field, rapidly switching magnetic field gradients, high-power radio frequency pulses, sensitivity to electrical noise, and constrained space to operate within the bore of the scanner. MRI has a number of advantages over other medical imaging modalities, including no ionizing radiation, excellent soft-tissue contrast that allows for visualization of tumors and other features that are not readily visible by other modalities, true 3-D imaging capabilities, including the ability to image arbitrary scan plane geometry or perform volumetric imaging, and capability for multimodality sensing, including diffusion, dynamic contrast, blood flow, blood oxygenation, temperature, and tracking of biomarkers. The use of robotic assistants within the MRI bore, alongside the patient during imaging, enables intraoperative MR imaging (iMRI) to guide a surgical intervention in a closed-loop fashion that can include tracking of tissue deformation and target motion, localization of instrumentation, and monitoring of therapy delivery. With the ever-expanding clinical use of MRI, MRI-compatible robotic systems have been heralded as a new approach to assist interventional procedures to allow physicians to treat patients more accurately and effectively. Deploying robotic systems inside the bore synergizes the visual capability of MRI and the manipulation capability of robotic assistance, resulting in a closed-loop surgery architecture. This article details the challenges and history of robotic systems intended to operate in an MRI environment and outlines promising clinical applications and associated state-of-the-art MRI-compatible robotic systems and technology for making this possible.