Resting-State Brain Temperature: Dynamic Fluctuations in Brain Temperature and the Brain-Body Temperature Gradient.

BACKGROUND: While fluctuations in healthy brain temperature have been investigated over time periods of weeks to months, dynamics over shorter time periods are less clear. PURPOSE: To identify physiological fluctuations in brain temperature in healthy volunteers over time scales of approximately 1 hour. STUDY TYPE: Prospective. SUBJECTS: A total of 30 healthy volunteers (15 female; 26 ± 4 years old). SEQUENCE AND FIELD STRENGTH: 3 T; T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) and semi-localized by adiabatic selective refocusing (sLASER) single-voxel spectroscopy. ASSESSMENTS: Brain temperature was calculated from the chemical shift difference between N-acetylaspartate and water. To evaluate within-scan repeatability of brain temperature and the brain-body temperature difference, 128 spectral transients were divided into two sets of 64-spectra. Between-scan repeatability was evaluated using two time periods, ~1-1.5 hours apart. STATISTICAL TESTS: A hierarchical linear mixed model was used to calculate within-scan and between-scan correlations (Rw and Rb , respectively). Significance was determined at P ≤ .05. Values are reported as the mean ± standard deviation. RESULTS: A significant difference in brain temperature was observed between scans (-0.4 °C) but body temperature was stable (P = .59). Brain temperature (37.9 ± 0.7 °C) was higher than body temperature (36.5 ± 0.5 °C) for all but one subject. Within-scan correlation was high for brain temperature (Rw  = 0.95) and brain-body temperature differences (Rw  = 0.96). Between scans, variability was high for both brain temperature (Rb  = 0.30) and brain-body temperature differences (Rb  = 0.41). DATA CONCLUSION: Significant changes in brain temperature over time scales of ~1 hour were observed. High short-term repeatability suggests temperature changes appear to be due to physiology rather than measurement error. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Optimized truncation to integrate multi-channel MRS data using rank-R singular value decomposition.

Multi-channel phased receive arrays have been widely adopted for magnetic resonance imaging (MRI) and spectroscopy (MRS). An important step in the use of receive arrays for MRS is the combination of spectra collected from individual coil channels. The goal of this work was to implement an improved strategy termed OpTIMUS (i.e., optimized truncation to integrate multi-channel MRS data using rank-R singular value decomposition) for combining data from individual channels. OpTIMUS relies on spectral windowing coupled with a rank-R decomposition to calculate the optimal coil channel weights. MRS data acquired from a brain spectroscopy phantom and 11 healthy volunteers were first processed using a whitening transformation to remove correlated noise. Whitened spectra were then iteratively windowed or truncated, followed by a rank-R singular value decomposition (SVD) to empirically determine the coil channel weights. Spectra combined using the vendor-supplied method, signal/noise2 weighting, previously reported whitened SVD (rank-1), and OpTIMUS were evaluated using the signal-to-noise ratio (SNR). Significant increases in SNR ranging from 6% to 33% (P ≤ 0.05) were observed for brain MRS data combined with OpTIMUS compared with the three other combination algorithms. The assumption that a rank-1 SVD maximizes SNR was tested empirically, and a higher rank-R decomposition, combined with spectral windowing prior to SVD, resulted in increased SNR.

An Update on MR Spectroscopy in Cancer Management: Advances in Instrumentation, Acquisition, and Analysis.

MR spectroscopy (MRS) is a noninvasive imaging method enabling chemical and molecular profiling of tissues in a localized, multiplexed, and nonionizing manner. As metabolic reprogramming is a hallmark of cancer, MRS provides valuable metabolic and molecular information for cancer diagnosis, prognosis, treatment monitoring, and patient management. This review provides an update on the use of MRS for clinical cancer management. The first section includes an overview of the principles of MRS, current methods, and conventional metabolites of interest. The remainder of the review is focused on three key areas: advances in instrumentation, specifically ultrahigh-field-strength MRI scanners and hybrid systems; emerging methods for acquisition, including deuterium imaging, hyperpolarized carbon 13 MRI and MRS, chemical exchange saturation transfer, diffusion-weighted MRS, MR fingerprinting, and fast acquisition; and analysis aided by artificial intelligence. The review concludes with future recommendations to facilitate routine use of MRS in cancer management. Keywords: MR Spectroscopy, Spectroscopic Imaging, Molecular Imaging in Oncology, Metabolic Reprogramming, Clinical Cancer Management © RSNA, 2024.

Effects of orientation-dependent susceptibility on MR chemical shift brain thermometry.

PURPOSE: The presence of orientation-dependent susceptibility artifacts in magnetic resonance chemical shift thermometry (CST) can confound accurate temperature calculations. Here, we quantify the effect of white matter (WM) tract orientation on CST due to tissue-specific susceptibility. METHODS: Twenty-nine healthy volunteers (27 ± 4 years old) were scanned on a 3 T MR scanner with a 32-channel head coil. Diffusion tensor imaging (DTI), T1-weighted imaging, and single voxel spectroscopy (SVS) for CST were acquired. Participants were then asked to rotate their head ∼3-5° (yaw or roll) to alter the orientation of WM tracts relative to the external magnetic field. After head rotation, a second SVS scan and T1-weighted imaging were acquired. The WM-fraction-normalized DTI principal eigenvector (V1) images were used to calculate the length of the x-y component of V1, which was used as a surrogate for WM tracts perpendicular to B0. A linear regression model was used to determine the relationship between the perpendicular WM tracts and brain temperature. RESULTS: Significant temperature differences between post- and pre-head rotation scans were observed for brain (-0.72 °C ± 1.36 °C, p = 0.01) but not body (0.012 °C ± 0.07 °C, p = 0.37) temperatures. The difference in brain temperature was positively associated with the corresponding change in perpendicular WM tracts after head rotation (R2 = 0.26, p = 0.005). CONCLUSION: Our results indicate WM tract orientation affects temperature calculations, suggesting artifacts from orientation-dependent susceptibility may be present in CST.

Predicting brain temperature in humans using bioheat models: Progress and outlook.

Brain temperature, regulated by the balance between blood circulation and metabolic heat generation, is an important parameter related to neural activity, cerebral hemodynamics, and neuroinflammation. A key challenge for integrating brain temperature into clinical practice is the lack of reliable and non-invasive brain thermometry. The recognized importance of brain temperature and thermoregulation in both health and disease, combined with limited availability of experimental methods, has motivated the development of computational thermal models using bioheat equations to predict brain temperature. In this mini-review, we describe progress and the current state-of-the-art in brain thermal modeling in humans and discuss potential avenues for clinical applications.

Comparisons of healthy human brain temperature predicted from biophysical modeling and measured with whole brain MR thermometry.

Brain temperature is an understudied parameter relevant to brain injury and ischemia. To advance our understanding of thermal dynamics in the human brain, combined with the challenges of routine experimental measurements, a biophysical modeling framework was developed to facilitate individualized brain temperature predictions. Model-predicted brain temperatures using our fully conserved model were compared with whole brain chemical shift thermometry acquired in 30 healthy human subjects (15 male and 15 female, age range 18-36 years old). Magnetic resonance (MR) thermometry, as well as structural imaging, angiography, and venography, were acquired prospectively on a Siemens Prisma whole body 3 T MR scanner. Bland-Altman plots demonstrate agreement between model-predicted and MR-measured brain temperatures at the voxel-level. Regional variations were similar between predicted and measured temperatures (< 0.55 °C for all 10 cortical and 12 subcortical regions of interest), and subcortical white matter temperatures were higher than cortical regions. We anticipate the advancement of brain temperature as a marker of health and injury will be facilitated by a well-validated computational model which can enable predictions when experiments are not feasible.

Changes in brain metabolites and resting-state connectivity in collegiate basketball players as a function of play time.

BACKGROUND AND PURPOSE: Magnetic resonance (MR) biomarkers are emerging for sports-related traumatic brain injury (TBI), but the effect of play time has not been characterized. Our goal was to characterize brain and inflammatory marker changes as a function of play time. METHODS: Nine male players (21±2 years old) from a single collegiate basketball team were included. MR imaging (MRI), MR spectroscopy, and plasma were collected pre, mid, and postseason. Game time played was calculated for each subject. Changes in brain volume, diffusion tensor imaging (DTI), metabolites (normalized to total creatine, tCr), temperature, structural and functional connectivity, and inflammatory markers were quantified. RESULTS: Myo-inositol/tCr in the left frontal white matter and brain temperature in the left frontal lobe varied significantly between time points. Glutamate (Glu/tCr) in the right frontal white matter and N-acetylaspartate in the posterior cingulate cortex (PCC) were negatively associated with minutes played. Midseason play time was associated with stronger blood-oxygen-level-dependent correlations between PCC and occipital areas, and weaker correlations between PCC and superior frontal connectivity. PCC Glu/tCr was positively associated with connectivity between the PCC and posterior supramarginal gyrus at preseason and with connectivity across time points among several right hemisphere regions. Volume, DTI, and inflammatory markers did not vary significantly. CONCLUSION: Given that MR parameters vary with game play time in the absence of diagnosed injury, play time should be considered as a factor in sports-related TBI research.