Disrupting nociceptive information processing flow through transcranial focused ultrasound neuromodulation of thalamic nuclei.

BACKGROUND: MRI-guided transcranial focused ultrasound (MRgFUS) as a next-generation neuromodulation tool can precisely target and stimulate deep brain regions with high spatial selectivity. Combined with MR-ARFI (acoustic radiation force imaging) and using fMRI BOLD signal as functional readouts, our previous studies have shown that low-intensity FUS can excite or suppress neural activity in the somatosensory cortex. OBJECTIVE: To investigate whether low-intensity FUS can suppress nociceptive heat stimulation-induced responses in thalamic nuclei during hand stimulation, and to determine how this suppression influences the information processing flow within nociception networks. FINDINGS: BOLD fMRI activations evoked by 47.5 °C heat stimulation of hand were detected in 24 cortical regions, which belong to sensory, affective, and cognitive nociceptive networks. Concurrent delivery of low-intensity FUS pulses (650 kHz, 550 kPa) to the predefined heat nociceptive stimulus-responsive thalamic centromedial_parafascicular (CM_para), mediodorsal (MD), ventral_lateral (VL_ and ventral_lateral_posteroventral (VLpv) nuclei suppressed their heat responses. Off-target cortical areas exhibited reduced, enhanced, or no significant fMRI signal changes, depending on the specific areas. Differentiable thalamocortical information flow during the processing of nociceptive heat input was observed, as indicated by the time to reach 10% or 30% of the heat-evoked BOLD signal peak. Suppression of thalamic heat responses significantly altered nociceptive processing flow and direction between the thalamus and cortical areas. Modulation of contralateral versus ipsilateral areas by unilateral thalamic activity differed. Signals detected in high-order cortical areas, such as dorsal frontal (DFC) and ventrolateral prefrontal (vlPFC) cortices, exhibited faster response latencies than sensory areas. CONCLUSIONS: The concurrent delivery of FUS suppressed nociceptive heat response in thalamic nuclei and disrupted the nociceptive network. This study offers new insights into the causal functional connections within the thalamocortical networks and demonstrates the modulatory effects of low-intensity FUS on nociceptive information processing.

Low-rank plus sparse compressed sensing for accelerated proton resonance frequency shift MR temperature imaging.

PURPOSE: To improve multichannel compressed sensing (CS) reconstruction for MR proton resonance frequency (PRF) shift thermography, with application to MRI-induced RF heating evaluation and MR guided high intensity focused ultrasound (MRgFUS) temperature monitoring. METHODS: A new compressed sensing reconstruction is proposed that enforces joint low rank and sparsity of complex difference domain PRF data between post heating and baseline images. Validations were performed on 4 retrospectively undersampled dynamic data sets in PRF applications, by comparing the proposed method to a previously described L1 and total variation- (TV-) based CS approach that also operates on complex difference domain data, and to a conventional low rank plus sparse (L+S) separation-based CS reconstruction applied to the original domain data. RESULTS: In all 4 retrospective validations, the proposed reconstruction method outperformed the conventional L+S and L1 +TV CS reconstruction methods with a 3.6× acceleration ratio in terms of temperature accuracy with respect to fully sampled data. For RF heating evaluation, the proposed method achieved RMS error of 12%, compared to 19% for the L+S method and 17% for the L1 +TV method. For in vivo MRgFUS thalamotomy, the peak temperature reconstruction errors were 19%, 31%, and 35%, respectively. CONCLUSION: The complex difference-based low rank and sparse model enhances compressibility for dynamic PRF temperature imaging applications. The proposed multichannel CS reconstruction method enables high acceleration factors for PRF applications including RF heating evaluation and MRgFUS sonication.

Hybrid referenceless and multibaseline subtraction MR thermometry for monitoring thermal therapies in moving organs.

PURPOSE: Magnetic resonance thermometry using the proton resonance frequency (PRF) shift is a promising technique for guiding thermal ablation. For temperature monitoring in moving organs, such as the liver and the heart, problems with motion must be addressed. Multi-baseline subtraction techniques have been proposed, which use a library of baseline images covering the respiratory and cardiac cycle. However, main field shifts due to lung and diaphragm motion can cause large inaccuracies in multi-baseline subtraction. Referenceless thermometry methods based on polynomial phase regression are immune to motion and susceptibility shifts. While referenceless methods can accurately estimate temperature within the organ, in general, the background phase at organ/tissue interfaces requires large polynomial orders to fit, leading to increased danger that the heated region itself will be fitted by the polynomial and thermal dose will be underestimated. In this paper, a hybrid method for PRF thermometry in moving organs is presented that combines the strengths of referenceless and multi-baseline thermometry. METHODS: The hybrid image model assumes that three sources contribute to image phase during thermal treatment: Background anatomical phase, spatially smooth phase deviations, and focal, heat-induced phase shifts. The new model and temperature estimation algorithm were tested in the heart and liver of normal volunteers, in a moving phantom HIFU heating experiment, and in numerical simulations of thermal ablation. The results were compared to multi-baseline and referenceless methods alone. RESULTS: The hybrid method allows for in vivo temperature estimation in the liver and the heart with lower temperature uncertainty compared to multi-baseline and referenceless methods. The moving phantom HIFU experiment showed that the method accurately estimates temperature during motion in the presence of smooth main field shifts. Numerical simulations illustrated the method's sensitivity to algorithm parameters and hot spot features. CONCLUSIONS: This new hybrid method for MR thermometry in moving organs combines the strengths of both multi-baseline subtraction and referenceless thermometry and overcomes their fundamental weaknesses.