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Purpose: The safety and effectiveness of laser interstitial thermal therapy (LITT) relies critically on the ability to continuously monitor the ablation based on real-time temperature mapping using magnetic resonance thermometry (MRT). This technique uses gradient recalled echo (GRE) sequences that are especially sensitive to susceptibility effects from air and blood. LITT for brain tumors is often preceded by a biopsy and is anecdotally associated with artifact during ablation. Thus, we reviewed our experience and describe the qualitative signal dropout that can interfere with ablation. Methods: We retrospectively reviewed all LITT cases performed in our intraoperative MRI suite for tumors between 2017 and 2020. We identified a total of 17 LITT cases. Cases were reviewed for age, sex, pathology, presence of artifact, operative technique, and presence of blood/air on post-operative scans. Results: We identified six cases that were preceded by biopsy, all six had artifact present during ablation, and all six were noted to have air/blood on their post-operative MRI or CT scans. In two of those cases, the artifactual signal dropout qualitatively interfered with thermal damage thresholds at the borders of the tumor. There was no artifact in the 11 non-biopsy cases and no obvious blood or air was noted on the post-ablation scans. Conclusion: Additional consideration should be given to pre-LITT biopsies. The presence of air/blood caused an artifactual signal dropout effect in cases with biopsy that was severe enough to interfere with ablation in a significant number of those cases. Additional studies are needed to identify modifying strategies. [ABSTRACT FROM AUTHOR]

Multi-echo fMRI data acquisition has been widely investigated and suggested to optimize sensitivity for detecting the BOLD signal. Several methods have also been proposed for the combination of data with different echo times. The aim of the present study was to investigate how these advance echo combination methods provide advantages over the simple averaging of echoes when state-of-the-art group-level random-effect analyses are performed. Both resting-state and task-based dual-echo fMRI data were collected from 27 healthy adult individuals (14 male, mean age = 25.75 years) using standard echo-planar acquisition methods at 3T. Both resting-state and task-based data were subjected to a standard image pre-processing pipeline. Subsequently the two echoes were combined as a weighted average, using four different strategies for calculating the weights: (1) simple arithmetic averaging, (2) BOLD sensitivity weighting, (3) temporal-signal-to-noise ratio weighting and (4) temporal BOLD sensitivity weighting. Our results clearly show that the simple averaging of data with the different echoes is sufficient. Advanced echo combination methods may provide advantages on a single-subject level but when considering random-effects group level statistics they provide no benefit regarding sensitivity (i.e. group-level t-values) compared to the simple echo-averaging approach. One possible reason for the lack of clear advantages may be that apart from increasing the average BOLD sensitivity at the single-subject level, the advanced weighted averaging methods also inflate the inter-subject variance. As the echo combination methods provide very similar results, the recommendation is to choose between them depending on the availability of time for collecting additional resting-state data or whether subject-level or group-level analyses are planned.

Multi-echo fMRI data acquisition has been widely investigated and suggested to optimize sensitivity for detecting the BOLD signal. Several methods have also been proposed for the combination of data with different echo times. The aim of the present study was to investigate whether these advanced echo combination methods provide advantages over the simple averaging of echoes when state-of-the-art group-level random-effect analyses are performed. Both resting-state and task-based dual-echo fMRI data were collected from 27 healthy adult individuals (14 male, mean age = 25.75 years) using standard echo-planar acquisition methods at 3T. Both resting-state and task-based data were subjected to a standard image pre-processing pipeline. Subsequently the two echoes were combined as a weighted average, using four different strategies for calculating the weights: (1) simple arithmetic averaging, (2) BOLD sensitivity weighting, (3) temporal-signal-to-noise ratio weighting and (4) temporal BOLD sensitivity weighting. Our results clearly show that the simple averaging of data with the different echoes is sufficient. Advanced echo combination methods may provide advantages on a single-subject level but when considering random-effects group level statistics they provide no benefit regarding sensitivity (i.e., group-level t-values) compared to the simple echo-averaging approach. One possible reason for the lack of clear advantages may be that apart from increasing the average BOLD sensitivity at the single-subject level, the advanced weighted averaging methods also inflate the inter-subject variance. As the echo combinationmethods provide very similar results, the recommendation is to choose between them depending on the availability of time for collecting additional resting-state data or whether subject-level or group-level analyses are planned. [ABSTRACT FROM AUTHOR]

Purpose To design hyperbolic secant (HS) excitation pulses to reduce signal dropout in the orbitofrontal and inferior temporal regions in gradient-echo echo-planar imaging (GE-EPI) for functional MRI (fMRI) applications. Methods An algorithm based on Bloch simulations optimizes the HS pulse parameters needed to give the desired signal response across the range of susceptibility gradients observed in the human head (approximately ±250 μT·m−1). The impact of the HS pulse on the signal, temporal signal-to-noise ratio, blood oxygen level-dependent (BOLD) sensitivity, and ability to detect resting state BOLD signal changes was assessed in six healthy male volunteers at 3T. Results The optimized HS pulse (μ = 4.25, β = 3040 Hz, A0 = 12.3 μT, Δf = 4598 Hz) had a near uniform signal response for through-plane susceptibility gradients in the range ±250 μT·m−1. Signal, temporal signal-to-noise ratio, BOLD sensitivity, and the detectability of resting state networks were all partially recovered in the orbitofrontal and inferior temporal regions; however, there were signal losses of up to 50% in regions of homogeneous field (and signal loss from in-plane susceptibility gradients remained). Conclusion The HS pulse reduced signal dropout and could be used to acquire task and resting state fMRI data without loss of spatial coverage or temporal resolution. Magn Reson Med 74:661-672, 2015. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Abstract: T1-weighted anatomical brain scans are routinely used in neuroimaging studies, for example, as anatomical reference for functional data and in brain morphometry studies. Subject motion can degrade the quality of these images. An additional problem is the occurrence of signal dropouts in the case of long echo times and low receiver bandwidths. These problems are addressed in two different studies. In the first study, it is shown that the high scalp signal, which results from the low T1 value of fat, may cause a typical ringing artefact in the presence of head motion. This problem may be enhanced if phased array coils are used for signal reception due to their increased sensitivity in the peripheral head regions. It is shown that this artefact can be avoided by combining certain fat suppression techniques that reduce the scalp signal. In the second study, it is shown that signal dropout affects mainly the orbitofrontal cortex and the temporal lobes, and that a bandwidth of 100 Hz/pixel should be chosen for the investigation of these areas to avoid signal losses while maintaining an acceptable signal-to-noise ratio. Experimental results are based on the MDEFT sequence but can be applied to other T1-weighted sequences like FLASH and MP-RAGE. Furthermore, the presented methods for improving the image quality can be combined with other artefact reduction techniques. [Copyright &y& Elsevier]