Patient-specific temperature distribution prediction in laser interstitial thermal therapy: single-irradiation data-driven method

Laser interstitial thermal therapy (LITT) is popular for treating brain tumours and epilepsy. The strict control of tissue thermal damage extent is crucial for LITT. Temperature prediction is useful for predicting thermal damage extent. Accurately predictingin vivobrain tissue temperature is challenging due to the temperature dependence and the individual variations in tissue properties. Considering these factors is essential for improving the temperature prediction accuracy.Objective. To present a method for predicting patient-specific tissue temperature distribution within a target lesion area in the brain during LITT.Approach. A magnetic resonance temperature imaging (MRTI) data-driven estimation model was constructed and combined with a modified Pennes bioheat transfer equation (PBHE) to predict patient-specific temperature distribution. In the PBHE for temperature prediction, the individual specificity and temperature dependence of thermal tissue properties and blood perfusion, as well as the individual specificity of optical tissue properties were considered. Only MRTI data during one laser irradiation were required in the method. This enables the prediction of patient-specific temperature distribution and the resulting thermal damage region for subsequent ablations.Main results. Patient-specific temperature prediction was evaluated based on clinical data acquired during LITT in the brain, using intraoperative MRTI data as the reference standard. Our method significantly improved the prediction performance of temperature distribution and thermal damage region. The average root mean square error was decreased by 69.54%, the average intraclass correlation coefficient was increased by 37.5%, the average Dice similarity coefficient was increased by 43.14% for thermal damage region prediction.Significance. The proposed method can predict temperature distribution and thermal damage region at an individual patient level during LITT, providing a promising approach to assist in patient-specific treatment planning for LITT in the brain.

Effects of T2 * on accuracy and precision of dynamic T1 measurements using the single reference variable flip angle method - a simulation study

PURPOSE

To study in simulation and in theory the accuracy and precision of dynamic T₁ measurements obtained using the previously published single-reference variable flip angle (SR-VFA) technique, with a focus on the effects of dynamic changes in T₂ * on the calculation.

METHODS

Monte Carlo simulations were performed over 1000 noisy iterations for the VFA method, the SR-VFA method, and a proposed method, SR-VFA with a T₂ * correction (SR-VFA-T₂ *). Dynamic T₁ estimates were calculated analytically for each method, with signals modeled by the steady-state spoiled gradient echo equation. The mean and standard deviation of these estimates were calculated and compared to truth, while varying repetition time (TR), baseline and dynamic T₁ , echo time (TE), baseline and dynamic T₂ *, flip angles, and the number of averages on baseline scans. Additionally, the variance of T₁ in the SR-VFA and SR-VFA-T₂ * methods was derived analytically based on the theory of propagation of errors. This equation was used to produce an inverse-variance weighted linear combination to improve T₁ mapping precision in the SR-VFA-T₂ * method. Flip angle sensitivity of dynamic T₁ precision in the SR-VFA and SR-VFA-T₂ * methods was also performed.

RESULTS

Substantial bias can be produced by the SR-VFA method when the ratio of the T₂ * decay of the dynamic signal versus that of the baseline signals deviates from 1, with a 0.01 deviation leading to approximately a 1% bias in cases of high SNR and TR ≫ T₁ . This bias can be corrected by estimating the baseline and dynamic T₂ * values in this ratio via multi-echo measurements. The bias and precision of the SR-VFA-T₂ * method, when normalized to scan time, is found to rival and sometimes improve upon the two flip angle VFA method when an inverse variance weighted linear combination is applied across its multi-echo T₁ maps. The analytic variance equation presented is found to be accurate within 1% relative to the Monte Carlo simulations over a broad parameter space. Flip angle ranges that maximize SR-VFA and SR-VFA-T₂ * T₁ precision over a broad parameter space are given, and each is defined relative to TR and T₁ .

CONCLUSIONS

Multi-echo SR-VFA-T₂ * T₁ mapping is found in simulation and theory to be a promising alternative to the VFA method that maintains speed of the SR-VFA method with accuracy and precision similar to the VFA method. This article is protected by copyright. All rights reserved.

Effects of Intraoperative Magnetic Resonance Thermal Imaging Signal Artifact During Laser Interstitial Thermal Therapy on Thermal Damage Estimate and Postoperative Magnetic Resonance Imaging Ablative Area Concordance

BACKGROUND

Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive procedure that utilizes intraoperative magnetic resonance thermal imaging (MRTI) to generate a thermal damage estimate (TDE) of the ablative area. In select cases, the MRTI contains a signal artifact or defect that distorts the ablative region. No study has considered the impact of this artifact on TDE accuracy.

OBJECTIVE

To determine the effect of intraoperative MRTI signal artifact on postoperative magnetic resonance imaging (MRI)-predicted ablative area.

METHODS

All ablations were performed using the Visualase MRI-Guided Laser Ablation System (Medtronic). Patients were grouped based on whether the intraoperative MRTI contained signal artifact that distorted the ablative region. Cross-sectional area of the ablative lesion from the MRI image was measured, and the difference between intraoperative TDE and postoperative MRI cross-sectional area was calculated and compared between groups with and without intraoperative MRTI artifact.

RESULTS

A total of 91 patients undergoing MRgLITT for various surgical indications were examined. MRTI artifact was observed in 43.9% of cases overall. The mean absolute difference between TDE and the postoperative MRI cross-sectional area was 94.8 mm2 (SEM = 11.6) in the group with intraoperative MRTI artifact and 54.4 mm2 (SEM = 5.5) in the nonartifact group.

CONCLUSION

MRTI signal artifact is common during LITT. The presence of signal artifact during intraoperative MRTI results in higher variation between intraoperative TDE and postoperative MRI cross-sectional ablative area. In cases in which intraoperative MRTI artifact is observed, there may be a larger degree of variation between observed intraoperative TDE and measured postoperative MRTI ablative area.

Characterization of Magnetic Resonance Thermal Imaging Signal Artifact During Magnetic Resonance Guided Laser-Induced Thermal Therapy

BACKGROUND

Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive procedure that utilizes intraoperative magnetic resonance thermal imaging (MRTI) to generate a thermal damage estimate (TDE) of the ablative area. In select cases, the MRTI contains a signal artifact or defect that distorts the ablative region. No study has attempted to characterize this artifact.

OBJECTIVE

To characterize MRTI signal the artifact in select cases to better understand its potential relevance and impact on the ablation procedure.

METHODS

All ablations were performed using the Visualase magnetic resonance imaging-guided laser ablation system (Medtronic). Patients were included if the MRTI contained signal artifact that distorted the ablative region during the first thermal dose delivered. Ablation artifact was quantified using MATLAB version R2018a (Mathworks Inc, Natick, Massachusetts).

RESULTS

A total of 116 patients undergoing MRgLITT for various surgical indications were examined. MRTI artifact was observed in 37.0% of cases overall. Incidence of artifact was greater at higher powers (P < .001) and with longer ablation times (P = .024), though artifact size did not correlate with laser power or ablation duration.

CONCLUSION

MRTI signal artifact is common during LITT. Higher powers and longer ablation times result in greater incidence of ablation artifact, though artifact size is not correlated with power or duration. Future studies should aim to evaluate effects of artifact on postoperative imaging and, most notably, patient outcomes.

Simultaneous proton resonance frequency shift thermometry and T1 measurements using a single reference variable flip angle T1 method

PURPOSE

Implement simultaneous proton resonance frequency (PRF) shift and T₁ measurements with equivalent temporal resolution using a single reference variable flip angle method. This novel method allows for simultaneous thermometry in both aqueous and fatty tissue.

METHODS

This method acquires a single reference image at the lower flip angle and all dynamic images at the higher angle. T₁ is calculated using a single reference variable flip angle method, which accounts for the reference image temperature remaining constant. Monte Carlo simulations determined the optimal dynamic flip angle for combined PRF and T₁ measurements. This method was evaluated in MR-guided focused ultrasound heating experiments using a gelatin phantom and human cadaver breasts. In vivo measurement precision was demonstrated in healthy female volunteers under nonheating conditions.

RESULTS

Temperature rise during MR-guided focused ultrasound heating was measured in aqueous tissue with both PRF and T₁ . Both measures show good qualitative agreement in both space and time in aqueous tissue. The T₁ change due to temperature increase was measured in fat, demonstrating the expected temporal response. The dynamic flip angle that produces optimal SNR for PRF measurements is lower than the optimal angle for T₁ measurements, necessitating the selection of a compromise angle.

CONCLUSION

The single reference variable flip angle method provides a reliable way to simultaneously measure PRF temperature and T₁ change and overcomes PRF's inability to simultaneously monitor temperature in aqueous and adipose tissues. Future work will calibrate T₁ change to temperature, enabling real-time temperature in fat and increasing patient safety and treatment efficacy during thermal interventional treatments.

Effect of k-space-weighted image contrast and ultrasound focus size on the accuracy of proton resonance frequency thermometry

PURPOSE

To construct a predictive model that describes how the duration and symmetry of a k-space-weighted image contrast (KWIC) window affects the temporal resolution of differently sized ultrasound foci when using a pseudo-golden angle stack-of-stars acquisition.

METHODS

We performed a modulation analysis of proton resonance frequency temperature measurements to create the temporal modulation transfer function for KWIC windows of different symmetry and temporal duration. We reconstructed simulated ultrasound heating trajectories and stack-of-stars k-space data as well as experimental phantom data using the same trajectories. Images were reconstructed using symmetric and asymmetric KWIC windows of 3 different temporal durations. Simulated results were compared against temporal modulation transfer function predictions, experimental results, and the original simulated temperatures.

RESULTS

The temporal modulation transfer function shows that temporal resolution with KWIC reconstructions depend on the object size. The KWIC window duration affected SNR and severity of undersampling artifacts. Accuracy and response delay improved as the KWIC window duration decreased or the size of the heated region within the KWIC plane increased. Precision worsened as the window duration decreased. Using a symmetric window eliminated the response delay to heated region size but introduced a large reconstruction delay.

CONCLUSION

The accuracy and precision of proton resonance frequency temperature measurements from a stack-of-stars acquisition using a sliding KWIC window reconstruction are dependent on the size of the KWIC window and the size and shape of the heated region. The temporal modulation transfer function of KWIC reconstructions for any object size can predict the temporal response to changes in signal being acquired, such as temperature and contrast enhancement.

Model predictive filtering MR thermometry: Effects of model inaccuracies, k-space reduction factor, and temperature increase rate

PURPOSE

Evaluate effects of model parameter inaccuracies (thermal conductivity, k, and ultrasound power deposition density, Q), k-space reduction factor (R), and rate of temperature increase ( T˙) in a thermal model-based reconstruction for MR-thermometry during focused-ultrasound heating.

METHODS

Simulations and ex vivo experiments were performed to investigate the accuracy of the thermal model and the model predictive filtering (MPF) algorithm for varying R and T˙, and their sensitivity to errors in k and Q. Ex vivo data was acquired with a segmented EPI pulse sequence to achieve large field-of-view (192 × 162 × 96 mm) four-dimensional temperature maps with high spatiotemporal resolution (1.5 × 1.5 × 2.0 mm, 1.7 s).

RESULTS

In the simulations, 50% errors in k and Q resulted in maximum temperature root mean square errors (RMSE) of 6 °C for model only and 3 °C for MPF. Using recently developed methods, estimates of k and Q were accurate to within 3%. The RMSE between MPF and true temperature increased with R and T˙. In the ex vivo study the RMSE remained below 0.7 °C for R ranging from 4 to 12 and T˙ of 0.28-0.75 °C/s.

CONCLUSION

Errors in MPF temperatures occur due to errors in k and Q. These MPF temperature errors increase with increase in R and T˙, but are smaller than those obtained using the thermal model alone.