Reliability of MRSI brain temperature mapping at 1.5 and 3 T

Selective head cooling in the acute phase of concussive injury: a neuroimaging study

Introduction

Neurovascular decoupling is a common consequence after brain injuries like sports-related concussion. Failure to appropriately match cerebral blood flow (CBF) with increases in metabolic demands of the brain can lead to alterations in neurological function and symptom presentation. Therapeutic hypothermia has been used in medicine for neuroprotection and has been shown to improve outcome. This study aimed to examine the real time effect of selective head cooling on healthy controls and concussed athletes via magnetic resonance spectroscopy (MRS) and arterial spin labeling (ASL) measures.

Methods

24 participants (12 controls; 12 concussed) underwent study procedures including the Post-Concussion Symptom Severity (PCSS) Rating Form and an MRI cooling protocol (pre-cooling (T1 MPRAGE, ASL, single volume spectroscopy (SVS)); during cooling (ASL, SVS)).

Results

Results showed general decreases in brain temperature as a function of time for both groups. Repeated measures ANOVA showed a significant main effect of time (F = 7.94, p < 0.001) and group (F = 22.21, p < 0.001) on temperature, but no significant interaction of group and time (F = 1.36, p = 0.237). CBF assessed via ASL was non-significantly lower in concussed individuals at pre-cooling and generalized linear mixed model analyses demonstrated a significant main effect of time for the occipital left ROI (F = 11.29, p = 0.002) and occipital right ROI (F = 13.39, p = 0.001). There was no relationship between any MRI metric and PCSS symptom burden.

Discussion

These findings suggest the feasibility of MRS thermometry to monitor alterations of brain temperature in concussed athletes and that metabolic responses in response to cooling after concussion may differ from controls.

Investigation of post mortem brain, rectal and forehead temperature relations

It is well known that magnetic resonance (MR) imaging is temperature sensitive, which is highly relevant for post mortem examinations. Therefore, the determination of the exact temperature of the investigated body site, e.g. the brain, is crucial. However, direct temperature measurements are invasive and inconvenient. Thus, in view of post mortem MR imaging of the brain, this study aims at investigating the relation between the brain and the forehead temperature for modelling the brain temperature based on the non-invasive forehead temperature. In addition, the brain temperature will be compared to the rectal temperature. Brain temperature profiles measured in the longitudinal fissure between the brain hemispheres, as well as rectal and forehead temperature profiles of 16 deceased were acquired continuously. Linear mixed, linear, quadratic and cubic models were fitted to the relation between the longitudinal fissure and the forehead and between the longitudinal fissure and the rectal temperature, respectively. Highest adjusted R2 values were found between the longitudinal fissure and the forehead temperature, as well as between the longitudinal fissure and the rectal temperature using a linear mixed model including the sex, environmental temperature and humidity as fixed effects. The results indicate that the forehead, as well as the rectal temperature, can be used to model the brain temperature measured in the longitudinal fissure. Comparable fit results were observed for the longitudinal fissure-forehead temperature relation and for the longitudinal fissure-rectal temperature relation. Combined with the fact that the forehead temperature overcomes the problem of measurement invasiveness, the results suggest using the forehead temperature for modelling the brain temperature in the longitudinal fissure.

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.

Brain temperature in healthy and diseased conditions: A review on the special implications of MRS for monitoring brain temperature

Brain temperature determines not only an individual's cognitive functionality but also the prognosis and mortality rates of many brain diseases. More specifically, brain temperature not only changes in response to different physiological events like yawning and stretching, but also plays a significant pathophysiological role in a number of neurological and neuropsychiatric illnesses. Here, we have outlined the function of brain hyperthermia in both diseased and healthy states, focusing particularly on the amyloid beta aggregation in Alzheimer's disease.

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.

Brain temperature remains stable during the day: a study of diffusion-weighted imaging thermometry in healthy individuals

PURPOSE

To investigate the daily fluctuations in brain temperature in healthy individuals using magnetic resonance (MR) diffusion-weighted imaging (DWI) thermometry and to clarify the associations between the brain and body temperatures and sex.

METHODS

Thirty-two age-matched healthy male and female volunteers (male = 16, 20-38 years) were recruited between July 2021 and January 2022. Brain MR examinations were performed in the morning and evening phases on the same day to calculate the brain temperatures using DWI thermometry. Body temperature was also measured in each MR examination. Group comparisons of body and brain temperatures between the two phases were performed using paired t-tests. A multiple linear regression model was used to predict the morning brain temperature using sex, evening brain temperature, and the interaction between sex and evening brain temperature as covariates.

RESULTS

Body temperatures were significantly higher in the evening than in the morning in all participants, male group, and female group (p < 0.001, = 0001, and < 0.001, respectively). Meanwhile, no significant difference was observed between the morning and evening brain temperatures in each analysis (p = 0.23, 0.70, and 0.16, respectively). Multiple linear regression analysis showed significant associations of morning brain temperature with sex (p = 0.038), evening brain temperature (p < 0.001), and the interaction between sex and evening brain temperature (p = 0.036).

CONCLUSION

Unlike body temperature, brain temperature showed no significant daily fluctuations; however, daily fluctuations in brain temperature may vary depending on sex.

Improving the reproducibility of proton magnetic resonance spectroscopy brain thermometry: Theoretical and empirical approaches

In proton magnetic resonance spectroscopy (¹ H MRS)-based thermometry of brain, averaging temperatures measured from more than one reference peak offers several advantages, including improving the reproducibility (i.e., precision) of the measurement. This paper proposes theoretically and empirically optimal weighting factors to improve the weighted average of temperatures measured from three references. We first proposed concepts of equivalent noise and equivalent signal-to-noise ratio in terms of frequency measurement and a concept of relative frequency that allows the combination of different peaks in a spectrum for improving the precision of frequency measurement. Based on these, we then derived a theoretically optimal weighting factor and proposed an empirical weighting factor, both involving equivalent noise levels, for a weighted average of temperatures measured from three references (i.e., the singlets of NAA, Cr, and Ch in the ¹ H MR spectrum). We assessed these two weighting factors by comparing their errors in measurement of temperatures with the errors of temperatures measured from individual references; we also compared these two new weighting factors with two previously proposed weighting factors. These errors were defined as the standard deviations in repeated measurements or in Monte Carlo studies. Both the proposed theoretical and empirical weighting factors outperformed the two previously proposed weighting factors as well as the three individual references in all phantom and in vivo experiments. In phantom experiments with 4- or 10-Hz line broadening, the theoretical weighting factor outperformed the empirical one, but the latter was superior in all other repeated and Monte Carlo tests performed on phantom and in vivo data. The proposed weighting factors are superior to the two previously proposed weighting factors and can improve the reproducibility of temperature measurement using ¹ H MRS-based thermometry.

A daily temperature rhythm in the human brain predicts survival after brain injury

Patients undergo interventions to achieve a 'normal' brain temperature; a parameter that remains undefined for humans. The profound sensitivity of neuronal function to temperature implies the brain should be isothermal, but observations from patients and non-human primates suggest significant spatiotemporal variation. We aimed to determine the clinical relevance of brain temperature in patients by establishing how much it varies in healthy adults. We retrospectively screened data for all patients recruited to the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) High Resolution Intensive Care Unit Sub-Study. Only patients with direct brain temperature measurements and without targeted temperature management were included. To interpret patient analyses, we prospectively recruited 40 healthy adults (20 males, 20 females, 20-40 years) for brain thermometry using magnetic resonance spectroscopy. Participants were scanned in the morning, afternoon, and late evening of a single day. In patients (n = 114), brain temperature ranged from 32.6 to 42.3°C and mean brain temperature (38.5 ± 0.8°C) exceeded body temperature (37.5 ± 0.5°C, P < 0.0001). Of 100 patients eligible for brain temperature rhythm analysis, 25 displayed a daily rhythm, and the brain temperature range decreased in older patients (P = 0.018). In healthy participants, brain temperature ranged from 36.1 to 40.9°C; mean brain temperature (38.5 ± 0.4°C) exceeded oral temperature (36.0 ± 0.5°C) and was 0.36°C higher in luteal females relative to follicular females and males (P = 0.0006 and P < 0.0001, respectively). Temperature increased with age, most notably in deep brain regions (0.6°C over 20 years, P = 0.0002), and varied spatially by 2.41 ± 0.46°C with highest temperatures in the thalamus. Brain temperature varied by time of day, especially in deep regions (0.86°C, P = 0.0001), and was lowest at night. From the healthy data we built HEATWAVE-a 4D map of human brain temperature. Testing the clinical relevance of HEATWAVE in patients, we found that lack of a daily brain temperature rhythm increased the odds of death in intensive care 21-fold (P = 0.016), whilst absolute temperature maxima or minima did not predict outcome. A warmer mean brain temperature was associated with survival (P = 0.035), however, and ageing by 10 years increased the odds of death 11-fold (P = 0.0002). Human brain temperature is higher and varies more than previously assumed-by age, sex, menstrual cycle, brain region, and time of day. This has major implications for temperature monitoring and management, with daily brain temperature rhythmicity emerging as one of the strongest single predictors of survival after brain injury. We conclude that daily rhythmic brain temperature variation-not absolute brain temperature-is one way in which human brain physiology may be distinguished from pathophysiology.

Proton magnetic resonance spectroscopy thermometry: Impact of separately acquired full water or partially suppressed water data on quantification and measurement error

In proton magnetic resonance spectroscopy (¹ H MRS) thermometry, separately acquired full water and partially suppressed water are commonly used for measuring temperature. This paper compares these two approaches. Single-voxel ¹ H MRS data were collected on a 3-T GE scanner from 26 human subjects. Every subject underwent five continuous MRS sessions, each separated by a 2-min phase. Each MRS session lasted 13 min and consisted of two free induction decays (FIDs) without water suppression (with full water [FW or w]) and 64 FIDs with partial water suppression (with partially suppressed water [PW or w']). Frequency differences between the two FWs, the first two PWs, the second FW and the first PW (FW₂ , PW₁ ), or between averaged water ( wav' ) and N-acetylaspartate (NAA), were measured. Intrasubject and intersubject variations of the frequency differences were used as a metric for the error in temperature measurement. The intrasubject variations of frequency differences between FW₂ and PW₁fw2-fw1' , calculated from the five MRS sessions for each subject, were larger than those between the two FWs or between the first two PWs (p = 1.54 x 10^-4 and p = 1.72 x 10^-4 , respectively). The mean values of intrasubject variations of fw2-fw1' for all subjects were 4.7 and 4.5 times those of fw2-fw1 and fw2'-fw1' , respectively. The intrasubject variations of the temperatures based on frequency differences, fw2-fNAA or ( fw1'-fNAA ), were about 2.5 times greater than those based on averaged water and NAA frequencies (fwav'-fNAA ). The mean temperature measured from (fwav'-fNAA ) (n = 26) was 0.29°C lower than that measured from fw2-fNAA and was 0.83°C higher than that from ( fw1'-fNAA ). It was concluded that the use of separately acquired unsuppressed or partially suppressed water signals may result in large errors in frequency and, consequently, temperature measurement.

Brain temperature as an indicator of neuroinflammation induced by typhoid vaccine: Assessment using whole-brain magnetic resonance spectroscopy in a randomised crossover study

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MRSI-derived whole-brain temperature did not detect low-level neuroinflammation.

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Regional brain temperature was a more sensitive measure of neuroinflammation.

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MRSI/EPSI might be a useful measure of neuroinflammation in psychiatric disorders.

Prior studies indicate a pathogenic role of neuroinflammation in psychiatric disorders; however, there are no accepted methods that can reliably measure low-level neuroinflammation non-invasively in these individuals. Magnetic resonance spectroscopic imaging (MRSI) is a versatile, non-invasive neuroimaging technique that demonstrates sensitivity to brain inflammation. MRSI in conjunction with echo-planar spectroscopic imaging (EPSI) measures brain metabolites to derive whole-brain and regional brain temperatures, which may increase in neuroinflammation. The validity of MRSI/EPSI for measurement of low level neuroinflammation was tested using a safe experimental model of human brain inflammation – intramuscular administration of typhoid vaccine. Twenty healthy volunteers participated in a double-blind, placebo-controlled crossover study including MRSI/EPSI scans before and 3 h after vaccine/placebo administration. Body temperature and mood, assessed using the Profile of Mood States, were measured every hour up to four hours post-treatment administration. A mixed model analysis of variance was used to test for treatment effects. A significant proportion of brain regions (44/47) increased in temperature post-vaccine compared to post-placebo (p < 0.0001). For temperature change in the brain as a whole, there was no significant treatment effect. Significant associations were seen between mood scores assessed at 4 h and whole brain and regional temperatures post-treatment. Findings indicate that regional brain temperature may be a more sensitive measure of low-level neuroinflammation than whole-brain temperature. Future work where these measurement techniques are applied to populations with psychiatric disorders would be of clinical interest.

Brain Temperature Measured by Magnetic Resonance Spectroscopy to Predict Clinical Outcome in Patients with Infarction

Acute ischemic stroke is characterized by dynamic changes in metabolism and hemodynamics, which can affect brain temperature. We used proton magnetic resonance (MR) spectroscopy under everyday clinical settings to measure brain temperature in seven patients with internal carotid artery occlusion to explore the relationship between lesion temperature and clinical course. Regions of interest were selected in the infarct area and the corresponding contralateral region. Single-voxel MR spectroscopy was performed using the following parameters: 2000-ms repetition time, 144-ms echo time, and 128 excitations. Brain temperature was calculated from the chemical shift between water and N-acetyl aspartate, choline-containing compounds, or creatine phosphate. Within 48 h of onset, compared with the contralateral region temperature, brain temperature in the ischemic lesion was lower in five patients and higher in two patients. Severe brain swelling occurred subsequently in three of the five patients with lower lesion temperatures, but in neither of the two patients with higher lesion temperatures. The use of proton MR spectroscopy to measure brain temperature in patients with internal carotid artery occlusion may predict brain swelling and subsequent motor deficits, allowing for more effective early surgical intervention. Moreover, our methodology allows for MR spectroscopy to be used in everyday clinical settings.

Repeatability and Reproducibility of in-vivo Brain Temperature Measurements

Background: Magnetic resonance spectroscopic imaging (MRSI) is a neuroimaging technique that may be useful for non-invasive mapping of brain temperature (i.e., thermometry) over a large brain volume. To date, intra-subject reproducibility of MRSI-based brain temperature (MRSI-t) has not been investigated. The objective of this repeated measures MRSI-t study was to establish intra-subject reproducibility and repeatability of brain temperature, as well as typical brain temperature range. Methods: Healthy participants aged 23-46 years (N = 18; 7 females) were scanned at two time points ~12-weeks apart. Volumetric MRSI data were processed by reconstructing metabolite and water images using parametric spectral analysis. Brain temperature was derived using the frequency difference between water and creatine (TCRE) for 47 regions of interest (ROIs) delineated by the modified Automated Anatomical Labeling (AAL) atlas. Reproducibility was measured using the coefficient of variation for repeated measures (COVrep), and repeatability was determined using the standard error of measurement (SEM). For each region, the upper and lower bounds of Minimal Detectable Change (MDC) were established to characterize the typical range of TCRE values. Results: The mean global brain temperature over all subjects was 37.2°C with spatial variations across ROIs. There was a significant main effect for time [F (1, 1,591) = 37.0, p < 0.0001] and for brain region [F (46, 1,591) = 2.66, p < 0.0001]. The time*brain region interaction was not significant [F (46, 1,591) = 0.80, p = 0.83]. Participants' TCRE was stable for each ROI across both time points, with ROIs' COVrep ranging from 0.81 to 3.08% (mean COVrep = 1.92%); majority of ROIs had a COVrep <2.0%. Conclusions: Brain temperature measurements were highly consistent between both time points, indicating high reproducibility and repeatability of MRSI-t. MRSI-t may be a promising diagnostic, prognostic, and therapeutic tool for non-invasively monitoring brain temperature changes in health and disease. However, further studies of healthy participants with larger sample size(s) and numerous repeated acquisitions are imperative for establishing a reference range of typical brain TCRE, as well as the threshold above which TCRE is likely pathological.

Reproducibility of whole-brain temperature mapping and metabolite quantification using proton magnetic resonance spectroscopy

Assessing brain temperature can provide important information about disease processes (e.g., stroke, trauma) and therapeutic effects (e.g., cerebral hypothermia treatment). Whole-brain magnetic resonance spectroscopic imaging (WB-MRSI) is increasingly used to quantify brain metabolites across the entire brain. However, its feasibility and reliability for estimating brain temperature needs further validation. Therefore, the present study evaluates the reproducibility of WB-MRSI for temperature mapping as well as metabolite quantification across the whole brain in healthy volunteers. Ten healthy adults were scanned on three occasions 1 week apart. Brain temperature, along with four commonly assessed brain metabolites-total N-acetyl-aspartate (tNAA), total creatine (tCr), total choline (tCho) and myo-inositol (mI)-were measured from WB-MRSI data. Reproducibility was evaluated using the coefficient of variation (CV). The measured mean (range) of the intra-subject CVs was 0.9% (0.6%-1.6%) for brain temperature mapping, and 4.7% (2.5%-15.7%), 6.4% (2.4%-18.9%) and 14.2% (4.4%-52.6%) for tNAA, tCho and mI, respectively, with reference to tCr. Consistently larger variability was found when using H₂ O as the reference for metabolite quantifications: 7.8% (3.3%-17.8%), 7.8% (3.1%-18.0%), 9.8% (3.7%-31.0%) and 17.0% (5.9%-54.0%) for tNAA, tCr, tCho and mI, respectively. Further, the larger the brain region (indicated by a greater number of voxels within that region), the better the reproducibility for both temperature and metabolite estimates. Our results demonstrate good reproducibility of whole-brain temperature and metabolite measurements using the WB-MRSI technique.

Therapeutic hypothermia: Applications in adults with acute ischemic stroke

The advent of mechanical thrombectomy and increasing alteplase use have transformed the care of patients with acute ischemic stroke. Patients with major arterial occlusions with poor outcomes now have a chance of returning to independent living in more than half of the cases. However, many patients with these severe strokes suffer major disability despite these therapies. The search is ongoing for agents that can be combined with thrombectomy to achieve better recovery through halting infarct growth and mitigating injury after ischemic stroke. Several studies in animals and humans have demonstrated that therapeutic hypothermia (TH) offers potential to interrupt the ischemic cascade, reduce infarct volume, and improve functional independence. We performed a literature search to look up recent advances in the use of TH surrounding the science, efficacy, and feasibility of inducing TH in modern stroke treatments. While protocols remain controversial, there is a real opportunity to combine TH with the existing therapies to improve outcome in adults with acute ischemic stroke.

How does blood regulate cerebral temperatures during hypothermia?

Macro-modeling of cerebral blood flow can help determine the impact of thermal intervention during instances of head trauma to mitigate tissue damage. This work presents a bioheat model using a 3D fluid-porous domain coupled with intersecting 1D arterial and venous vessel trees. This combined vascular porous (VaPor) model resolves both cerebral blood flow and energy equations, including heat generated by metabolism, using vasculature extracted from MRI data and is extended using a tree generation algorithm. Counter-current flows are expected to increase thermal transfer within the brain and are enforced using either the vascular structure or flow reversal, represented by a flow reversal constant, C_R. These methods exhibit larger average brain cooling (from 0.56 °C ± <0.01 °C to 0.58 °C ± <0.01 °C) compared with previous models (0.39 °C) when scalp temperature is reduced. An greater reduction in core brain temperature is observed (from 0.29 °C ± <0.01 °C to 0.45 °C ± <0.01 °C) compared to previous models (0.11 °C) due to the inclusion of counter-current cooling effects. The VaPor model also predicts that a hypothermic average temperature (<36 °C) can be reached in core regions of neonatal models using scalp cooling alone.

Variance components associated with long-echo-time MR spectroscopic imaging in human brain at 1.5T and 3T

OBJECT

Magnetic resonance spectroscopic imaging (MRSI) is increasingly used in medicine and clinical research. Previous reliability studies have used small samples and focussed on limited aspects of variability; information regarding 1.5T versus 3T performance is lacking. The aim of the present work was to measure the inter-session, intra-session, inter-subject, within-brain and residual variance components using both 1.5T and 3T MR scanners.

MATERIALS AND METHODS

Eleven healthy volunteers were invited for MRSI scanning on three occasions at both 1.5T and 3T, with four scans acquired at each visit. We measured variance components, correcting for grey matter and white matter content of voxels, of metabolite peak areas and peak area ratios.

RESULTS

Residual variance was in general the largest component at 1.5T (8.6-24.6%), while within-brain variation was the largest component at 3T (12.0-24.7%). Inter-subject variation was around 5%, while inter- and intra-session variance were both generally small.

CONCLUSION

Multiple variance contributions associated with MRSI measurements were quantified and the performance of 1.5T and 3T MRI scanners compared using data from the same group of subjects. Residual error is much lower at 3T, but other variance components remain important.

A model based on the Pennes bioheat transfer equation is valid in normal brain tissue but not brain tissue suffering focal ischaemia

Ischaemic stroke is a major public health issue in both developed and developing nations. Hypothermia is believed to be neuroprotective in cerebral ischaemia. Conversely, elevated brain temperature is associated with poor outcome after ischaemic stroke. Mechanisms of heat exchange in normally-perfused brain are relatively well understood, but these mechanisms have not been studied as extensively during focal cerebral ischaemia. A finite element model (FEM) of heat exchange during focal ischaemia in the human brain was developed, based on the Pennes bioheat equation. This model incorporated healthy (normally-perfused) brain tissue, tissue that was mildly hypoperfused but not at risk of cell death (referred to as oligaemia), tissue that was hypoperfused and at risk of death but not dead (referred to as penumbra) and tissue that had died as a result of ischaemia (referred to as infarct core). The results of simulations using this model were found to match previous in-vivo temperature data for normally-perfused brain. However, the results did not match what limited data are available for hypoperfused brain tissue, in particular the penumbra, which is the focus of acute neuroprotective treatments such as hypothermia. These results suggest that the assumptions of the Pennes bioheat equation, while valid in the brain under normal circumstances, are not valid during focal ischaemia. Further investigation into the heat exchange profiles that do occur during focal ischaemia may yield results for clinical trials of therapeutic hypothermia.

Multiparametric quantification of thermal heterogeneity within aqueous materials by water 1H NMR spectroscopy: Paradigms and algorithms

Processes involving heat generation and dissipation play an important role in the performance of numerous materials. The behavior of (semi-)aqueous materials such as hydrogels during production and application, but also properties of biological tissue in disease and therapy (e.g., hyperthermia) critically depend on heat regulation. However, currently available thermometry methods do not provide quantitative parameters characterizing the overall temperature distribution within a volume of soft matter. To this end, we present here a new paradigm enabling accurate, contactless quantification of thermal heterogeneity based on the line shape of a water proton nuclear magnetic resonance (¹H NMR) spectrum. First, the ¹H NMR resonance from water serving as a "temperature probe" is transformed into a temperature curve. Then, the digital points of this temperature profile are used to construct a histogram by way of specifically developed algorithms. We demonstrate that from this histogram, at least eight quantitative parameters describing the underlying statistical temperature distribution can be computed: weighted median, weighted mean, standard deviation, range, mode(s), kurtosis, skewness, and entropy. All mathematical transformations and calculations are performed using specifically programmed EXCEL spreadsheets. Our new paradigm is helpful in detailed investigations of thermal heterogeneity, including dynamic characteristics of heat exchange at sub-second temporal resolution.

Optimization of Single Voxel MR Spectroscopy Sequence Parameters and Data Analysis Methods for Thermometry in Deep Hyperthermia Treatments

OBJECTIVE

The difference in the resonance frequency of water and methylene moieties of lipids quantifies in magnetic resonance spectroscopy the absolute temperature using a predefined calibration curve. The purpose of this study was the investigation of peak evaluation methods and the magnetic resonance spectroscopy sequence (point-resolved spectroscopy) parameter optimization that enables thermometry during deep hyperthermia treatments.

MATERIALS AND METHODS

Different Lorentz peak-fitting methods and a peak finding method using singular value decomposition of a Hankel matrix were compared. Phantom measurements on organic substances (mayonnaise and pork) were performed inside the hyperthermia 1.5-T magnetic resonance imaging system for the parameter optimization study. Parameter settings such as voxel size, echo time, and flip angle were varied and investigated.

RESULTS

Usually all peak analyzing methods were applicable. Lorentz peak-fitting method in MATLAB proved to be the most stable regardless of the number of fitted peaks, yet the slowest method. The examinations yielded an optimal parameter combination of 8 cm³ voxel volume, 55 millisecond echo time, and a 90° excitation pulse flip angle.

CONCLUSION

The Lorentz peak-fitting method in MATLAB was the most reliable peak analyzing method. Measurements in homogeneous and heterogeneous phantoms resulted in optimized parameters for the magnetic resonance spectroscopy sequence for thermometry.

MRS thermometry calibration at 3 T: effects of protein, ionic concentration and magnetic field strength

MRS thermometry has been utilized to measure temperature changes in the brain, which may aid in the diagnosis of brain trauma and tumours. However, the temperature calibration of the technique has been shown to be sensitive to non-temperature-based factors, which may provide unique information on the tissue microenvironment if the mechanisms can be further understood. The focus of this study was to investigate the effects of varied protein content on the calibration of MRS thermometry at 3 T, which has not been thoroughly explored in the literature. The effects of ionic concentration and magnetic field strength were also considered. Temperature reference materials were controlled by water circulation and freezing organic fixed-point compounds (diphenyl ether and ethylene carbonate) stable to within 0.2 °C. The temperature was measured throughout the scan time with a fluoro-optic probe, with an uncertainty of 0.16 °C. The probe was calibrated at the National Physical Laboratory (NPL) with traceability to the International Temperature Scale 1990 (ITS-90). MRS thermometry measures were based on single-voxel spectroscopy chemical shift differences between water and N-acetylaspartate (NAA), Δ(H20-NAA), using a Philips Achieva 3 T scanner. Six different phantom solutions with varying protein or ionic concentration, simulating potential tissue differences, were investigated within a temperature range of 21-42 °C. Results were compared with a similar study performed at 1.5 T to observe the effect of field strengths. Temperature calibration curves were plotted to convert Δ(H20-NAA) to apparent temperature. The apparent temperature changed by -0.2 °C/% of bovine serum albumin (BSA) and a trend of 0.5 °C/50 mM ionic concentration was observed. Differences in the calibration coefficients for the 10% BSA solution were seen in this study at 3 T compared with a study at 1.5 T. MRS thermometry may be utilized to measure temperature and the tissue microenvironment, which could provide unique unexplored information for brain abnormalities and other pathologies.

Improving thermal dose accuracy in magnetic resonance-guided focused ultrasound surgery: Long-term thermometry using a prior baseline as a reference

PURPOSE

To investigate thermal dose volume (TDV) and non-perfused volume (NPV) of magnetic resonance-guided focused ultrasound (MRgFUS) treatments in patients with soft tissue tumors, and describe a method for MR thermal dosimetry using a baseline reference.

MATERIALS AND METHODS

Agreement between TDV and immediate post treatment NPV was evaluated from MRgFUS treatments of five patients with biopsy-proven desmoid tumors. Thermometry data (gradient echo, 3T) were analyzed over the entire course of the treatments to discern temperature errors in the standard approach. The technique searches previously acquired baseline images for a match using 2D normalized cross-correlation and a weighted mean of phase difference images. Thermal dose maps and TDVs were recalculated using the matched baseline and compared to NPV.

RESULTS

TDV and NPV showed between 47%-91% disagreement, using the standard immediate baseline method for calculating TDV. Long-term thermometry showed a nonlinear local temperature accrual, where peak additional temperature varied between 4-13°C (mean = 7.8°C) across patients. The prior baseline method could be implemented by finding a previously acquired matching baseline 61% ± 8% (mean ± SD) of the time. We found 7%-42% of the disagreement between TDV and NPV was due to errors in thermometry caused by heat accrual. For all patients, the prior baseline method increased the estimated treatment volume and reduced the discrepancies between TDV and NPV (P = 0.023).

CONCLUSION

This study presents a mismatch between in-treatment and post treatment efficacy measures. The prior baseline approach accounts for local heating and improves the accuracy of thermal dose-predicted volume.