Jonathan Goodwin

Oxygen extraction fraction measurement using quantitative susceptibility mapping: Comparison with positron emission tomography:

The purposes of this study are to establish oxygen extraction fraction (OEF) measurements using quantitative susceptibility mapping (QSM) of magnetic resonance imaging (MRI), and to compare QSM–OEF data with the gold standard 15O positron emission tomography (PET). Twenty-six patients with chronic unilateral internal carotid artery or middle cerebral artery stenosis or occlusion, and 15 normal subjects were included. MRI scans were conducted using a 3.0 Tesla scanner with a three-dimensional spoiled gradient recalled sequence. QSM images were created using the morphology-enabled dipole inversion method, and OEF maps were generated from QSM images using extraction of venous susceptibility induced by deoxygenated hemoglobin. Significant correlation of relative OEF ratio to contra-lateral hemisphere between QSM–OEF and PET–OEF was observed (r = 0.62, p < 0.001). The local (intra-section) correlation was also significant (r = 0.52, p < 0.001) in patients with increased PET–OEF. The sensitivity and specificity of OEF increase in QSM was 0.63 (5/8) and 0.89 (16/18), respectively, in comparison with PET. In conclusion, good correlation was achieved between QSM–OEF and PET–OEF in the identification of elevated OEF in affected hemispheres of patients with unilateral chronic steno-occlusive disease.

Assessment of the accuracy of a Bayesian estimation algorithm for perfusion CT by using a digital phantom

IntroductionA new deconvolution algorithm, the Bayesian estimation algorithm, was reported to improve the precision of parametric maps created using perfusion computed tomography. However, it remains unclear whether quantitative values generated by this method are more accurate than those generated using optimized deconvolution algorithms of other software packages. Hence, we compared the accuracy of the Bayesian and deconvolution algorithms by using a digital phantom.MethodsThe digital phantom data, in which concentration–time curves reflecting various known values for cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and tracer delays were embedded, were analyzed using the Bayesian estimation algorithm as well as delay-insensitive singular value decomposition (SVD) algorithms of two software packages that were the best benchmarks in a previous cross-validation study. Correlation and agreement of quantitative values of these algorithms with true values were examined.ResultsCBF, CBV, and MTT values estimated by all the algorithms showed strong correlations with the true values (r = 0.91–0.92, 0.97–0.99, and 0.91–0.96, respectively). In addition, the values generated by the Bayesian estimation algorithm for all of these parameters showed good agreement with the true values [intraclass correlation coefficient (ICC) = 0.90, 0.99, and 0.96, respectively], while MTT values from the SVD algorithms were suboptimal (ICC = 0.81–0.82).ConclusionsQuantitative analysis using a digital phantom revealed that the Bayesian estimation algorithm yielded CBF, CBV, and MTT maps strongly correlated with the true values and MTT maps with better agreement than those produced by delay-insensitive SVD algorithms.

Detection of early changes in the parahippocampal and posterior cingulum bundles during mild cognitive impairment by using high-resolution multi-parametric diffusion tensor imaging.

We aimed to determine alterations occurring in the parahippocampal cingulum bundle (PhC) and posterior cingulum bundle (PoC) in patients with mild cognitive impairment (MCI) through analysis of high-resolution multi-parametric diffusion tensor imaging (DTI). Participants comprised 41 patients with MCI (21 AD converters [MCI-C] and 20 non-converters [MCI-NC]), 20 patients with Alzheimer׳s disease (AD), and 26 healthy elderly subjects who underwent prospective examination with high-resolution DTI. An atlas-based regions-of-interest (ROIs) method calculated fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR) in the PhC and PoC. For the PhC, FA values showed significant decreases, and MD and DR values showed significantly increases, in the MCI-C and AD groups compared with the healthy controls, although the MCI-C and MCI-NC groups did not differ significantly in these metrics. Conversely, none of the diffusion metrics for the PoC showed a significant difference among the MCI groups and the control groups, although there were significant differences between the AD group and control groups. High-resolution multi-parametric DTI analysis was able to detect substantial changes in diffusion anisotropy and diffusivity in the PhC of patients with MCI who were destined to convert to AD.

Optimization of Scan Parameters to Reduce Acquisition Time for Diffusion Kurtosis Imaging at 1.5T

PURPOSE To shorten acquisition of diffusion kurtosis imaging (DKI) in 1.5-tesla magnetic resonance (MR) imaging, we investigated the effects of the number of b-values, diffusion direction, and number of signal averages (NSA) on the accuracy of DKI metrics. METHODS We obtained 2 image datasets with 30 gradient directions, 6 b-values up to 2500 s/mm(2), and 2 signal averages from 5 healthy volunteers and generated DKI metrics, i.e., mean, axial, and radial kurtosis (MK, K∥, and K⊥) maps, from various combinations of the datasets. These maps were estimated by using the intraclass correlation coefficient (ICC) with those from the full datasets. RESULTS The MK and K⊥ maps generated from the datasets including only the b-value of 2500 s/mm(2) showed excellent agreement (ICC, 0.96 to 0.99). Under the same acquisition time and diffusion directions, agreement was better of MK, K∥, and K⊥ maps obtained with 3 b-values (0, 1000, and 2500 s/mm(2)) and 4 signal averages than maps obtained with any other combination of numbers of b-value and varied NSA. Good agreement (ICC > 0.6) required at least 20 diffusion directions in all the metrics. CONCLUSION MK and K⊥ maps with ICC greater than 0.95 can be obtained at 1.5T within 10 min (b-value = 0, 1000, and 2500 s/mm(2); 20 diffusion directions; 4 signal averages; slice thickness, 6 mm with no interslice gap; number of slices, 12).

Electron paramagnetic resonance-based pH mapping using spectral-spatial imaging of sequentially scanned spectra

The development of electron paramagnetic resonance (EPR)-based mapping of pH is an important advancement for the field of diagnostic imaging. The ability to accurately quantify pH change in vivo and monitor spatial distribution is desirable for the assessment of a number of pathological conditions in the human body as well as the monitoring of treatment response. In this work we introduce a method for EPR-based pH mapping utilizing a method of spectral-spatial imaging of sequentially scanned spectra to decrease the missing gradient rotation angle, without increasing the spatial field of view. Repeated in vitro measurements of pH phantom tubes demonstrated higher precision measurements of the hyperfine coupling constant (HFC) compared to previous EPR-based methods, resulting in mean pH values accurate to less than 0.1 pH across a range of physiologically observed values.

Susceptibility‐Weighted Phase Imaging and Oxygen Extraction Fraction Measurement during Sedation and Sedation Recovery using 7T MRI

In this work, we demonstrate oxygen extraction fraction (OEF) measurement using 7T MRI with susceptibility‐weighted imaging (SWI), in sedated and nonsedated adults.

In vivo tumour extracellular pH monitoring using electron paramagnetic resonance: the effect of X-ray irradiation

The in vivo quantification of extracellular pH (pHe) in tumours may provide a useful biomarker for tumour cell metabolism. In this study, we assessed the viability of continuous‐wave electron paramagnetic resonance (CW‐EPR) spectroscopy with a pH‐sensitive nitroxide for the measurement of extracellular tumour pH in a mouse model. CW‐EPR spectroscopy (750 MHz) of C3H HeJ mice hind leg squamous cell tumour was performed after intravenous tail vein injection of pH‐sensitive nitroxide (R‐SG, 2‐(4‐((2‐(4‐amino‐4‐carboxybutanamido)‐3‐(carboxymethylamino)‐3‐oxoproylthio)methyl)phenyl)‐4‐pyrrolidino‐2,5,5‐triethyl‐2,5‐dihydro‐1Н‐imidazol‐1‐oxyl) during stages of normal tumour growth and in response to a single 10‐Gy dose of X‐ray irradiation. An inverse relationship was observed between tumour volume and pHe value, whereby, during normal tumour growth, a constant reduction in pHe was observed. This relationship was disrupted by X‐ray irradiation and, from 2–3 days post‐exposure, a transitory increase in pHe was observed. In this study, we demonstrated the viability of CW‐EPR spectroscopy using R‐SG nitroxide to obtain high‐sensitivity pH measurements in a mouse tumour model with an accuracy of <0.1 pH units. In addition, the measured changes in pHe in response to X‐ray irradiation suggest that this may offer a useful method for the assessment of the physiological change in response to existing and novel cancer therapies. Copyright

Penumbral Imaging by Using Perfusion Computed Tomography and Perfusion-Weighted Magnetic Resonance Imaging: Current Concepts

Perfusion computed tomography and perfusion-weighted magnetic resonance imaging are used to evaluate the extent of the area with ischemic penumbra; however, different parameters, algorithms, and software packages show significant discrepancies in the size of perfusion abnormalities, which should be minimized. Recently, cross-validation studies were performed using digital phantoms and have elucidated the precision and reliability of various penumbral imaging techniques. These research initiatives can promote further multicenter trials on recanalization therapies by providing accurate inclusion/exclusion criteria for appropriate patient selection.

Assessment of sensations experienced by subjects during MR imaging examination at 7T.

PURPOSE We investigated sensations experienced by a large number of subjects during magnetic resonance (MR) imaging examinations using a 7-tesla scanner and slow table-feed speed. METHODS After examinations at 7T, 504 of 508 consecutive subjects completed questionnaires using an 11-point scale to rate 14 potential sensations and symptoms during table movement and stationary positioning of the table. We compared scores among the sensations and between table conditions and the mean values of the scores with those reported in previous studies and examined correlations between the scores and subject characteristics. RESULTS Vertigo and feelings of curving or leaning in the right or left direction during table movement were experienced frequently and markedly compared to other sensations and sensations experienced when the table was stationary (P < 0.01) and were correlated with subject age and examination time (P < 0.05). However, moderate to severe (scores of 5 to 10) vertigo and a curving/leaning feeling during table movement were noted in only 10.5% (vertigo) and 10.9% (curving/leaning) of subjects, and the mean vertigo score, 1.26, appeared to be substantially lower than that reported in a previous study. Reports of a metallic taste, nausea, and light flashes were significantly rarer and weaker than other sensations (P < 0.05). CONCLUSION Vertigo and feelings of curving during table movement were the most frequent sensations reported during MR imaging examination at 7T. However, the occurrence and severity were low and mild, presumably because of the slow table-feed speed, which suggests that most patients and volunteers found discomfort at 7T acceptable.

Comparison of Different Post-Processing Algorithms for Dynamic Susceptibility Contrast Perfusion Imaging of Cerebral Gliomas

Purpose: The purpose of the present study was to compare different software algorithms for processing DSC perfusion images of cerebral tumors with respect to i) the relative CBV (rCBV) calculated, ii) the cutoff value for discriminating low- and high-grade gliomas, and iii) the diagnostic performance for differentiating these tumors. Methods: Following approval of institutional review board, informed consent was obtained from all patients. Thirty-five patients with primary glioma (grade II, 9; grade III, 8; and grade IV, 18 patients) were included. DSC perfusion imaging was performed with 3-Tesla MRI scanner. CBV maps were generated by using 11 different algorithms of four commercially available software and one academic program. rCBV of each tumor compared to normal white matter was calculated by ROI measurements. Differences in rCBV value were compared between algorithms for each tumor grade. Receiver operator characteristics analysis was conducted for the evaluation of diagnostic performance of different algorithms for differentiating between different grades. Results: Several algorithms showed significant differences in rCBV, especially for grade IV tumors. When differentiating between low- (II) and high-grade (III/IV) tumors, the area under the ROC curve (Az) was similar (range 0.85–0.87), and there were no significant differences in Az between any pair of algorithms. In contrast, the optimal cutoff values varied between algorithms (range 4.18–6.53). Conclusions: rCBV values of tumor and cutoff values for discriminating low- and high-grade gliomas differed between software packages, suggesting that optimal software-specific cutoff values should be used for diagnosis of high-grade gliomas.