Delineation of recurrent glioblastoma by whole brain spectroscopic magnetic resonance imaging.

BACKGROUND: Glioblastoma (GBM) cellularity correlates with whole brain spectroscopic MRI (sMRI) generated relative choline to N-Acetyl-Aspartate ratio (rChoNAA) mapping. In recurrent GBM (rGBM), tumor volume (TV) delineation is challenging and rChoNAA maps may assist with re-RT targeting. METHODS: Fourteen rGBM patients underwent sMRI in a prospective study. Whole brain sMRI was performed to generate rChoNAA maps. TVs were delineated by the union of rChoNAA ratio over 2 (rChoNAA > 2) on sMRI and T1PC. rChoNAA > 2 volumes were compared with multiparametric MRI sequences including T1PC, T2/FLAIR, diffusion-restriction on apparent diffusion coefficient (ADC) maps, and perfusion relative cerebral blood volume (rCBV). RESULTS: rChoNAA > 2 (mean 27.6 cc, range 6.6-79.1 cc) was different from other imaging modalities (P ≤ 0.05). Mean T1PC volumes were 10.7 cc (range 1.2-31.4 cc). The mean non-overlapping volume of rChoNAA > 2 and T1PC was 29.2 cm3. rChoNAA > 2 was 287% larger (range 23% smaller-873% larger) than T1PC. T2/FLAIR volumes (mean 111.7 cc, range 19.0-232.7 cc) were much larger than other modalities. rCBV volumes (mean 6.2 cc, range 0.2-19.1 cc) and ADC volumes were tiny (mean 0.8 cc, range 0-3.7 cc). Eight in-field failures were observed. Three patients failed outside T1PC but within rChoNAA > 2. No grade 3 toxicities attributable to re-RT were observed. Median progression-free and overall survival for re-RT patients were 6.5 and 7.1 months, respectively. CONCLUSIONS: Treatment of rGBM may be optimized by sMRI, and failure patterns suggest benefit for dose-escalation within sMRI-delineated volumes. Dose-escalation and radiologic-pathologic studies are underway to confirm the utility of sMRI in rGBM.

A Novel Approach to Determining Tumor Progression Using a Three-Site Pilot Clinical Trial of Spectroscopic MRI-Guided Radiation Dose Escalation in Glioblastoma.

Glioblastoma (GBM) is a fatal disease, with poor prognosis exacerbated by difficulty in assessing tumor extent with imaging. Spectroscopic MRI (sMRI) is a non-contrast imaging technique measuring endogenous metabolite levels of the brain that can serve as biomarkers for tumor extension. We completed a three-site study to assess survival benefits of GBM patients when treated with escalated radiation dose guided by metabolic abnormalities in sMRI. Escalated radiation led to complex post-treatment imaging, requiring unique approaches to discern tumor progression from radiation-related treatment effect through our quantitative imaging platform. The purpose of this study is to determine true tumor recurrence timepoints for patients in our dose-escalation multisite study using novel methodology and to report on median progression-free survival (PFS). Follow-up imaging for all 30 trial patients were collected, lesion volumes segmented and graphed, and imaging uploaded to our platform for visual interpretation. Eighteen months post-enrollment, the median PFS was 16.6 months with a median time to follow-up of 20.3 months. With this new treatment paradigm, incidence rate of tumor recurrence one year from treatment is 30% compared to 60-70% failure under standard care. Based on the delayed tumor progression and improved survival, a randomized phase II trial is under development (EAF211).

Mapping early tumor response to radiotherapy using diffusion kurtosis imaging*.

PURPOSE: In this pilot study, DKI measures of diffusivity and kurtosis were compared in active tumor regions and correlated to radiologic response to radiotherapy after completion of 2 weeks of treatment to derive potential early measures of tumor response. METHODS: MRI and Magnetic Resonance Spectroscopic Imaging (MRSI) data were acquired before the beginning of RT (pre-RT) and 2 weeks after the initiation of treatment (during-RT) in 14 glioblastoma patients. The active tumor region was outlined as the union of the residual contrast-enhancing region and metabolically active tumor region. Average and standard deviation of mean, axial, and radial diffusivity (MD, AD, RD) and mean, axial, and radial kurtosis (MK, AK, RK) values were calculated for the active tumor VOI from images acquired pre-RT and during-RT and paired t-tests were executed to estimate pairwise differences. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the predictive capabilities of changes in diffusion metrics for progression-free survival (PFS). RESULTS: Analysis showed significant pairwise differences for AD (p = 0.035; Cohen's d of 0.659) and AK (p = 0.019; Cohen's d of 0.753) in diffusion measures after 2 weeks of RT. ROC curve analysis showed that percentage change differences in AD and AK between pre-RT and during-RT scans provided an Area Under the Curve (AUC) of 0.524 and 0.762, respectively, in discriminating responders (PFS>180 days) and non-responders (PFS<180 days). CONCLUSION: This pilot study, although preliminary in nature, showed significant changes in AD and AK maps, with kurtosis derived AK maps showing an increased sensitivity in mapping early changes in the active tumor regions.

A Novel Computerized Cognitive Test for the Detection of Mild Cognitive Impairment and Its Association with Neurodegeneration in Alzheimer's Disease Prone Brain Regions.

During the prodromal stage of Alzheimer's disease (AD), neurodegenerative changes can be identified by measuring volumetric loss in AD-prone brain regions on MRI. Cognitive assessments that are sensitive enough to measure the early brain-behavior manifestations of AD and that correlate with biomarkers of neurodegeneration are needed to identify and monitor individuals at risk for dementia. Weak sensitivity to early cognitive change has been a major limitation of traditional cognitive assessments. In this study, we focused on expanding our previous work by determining whether a digitized cognitive stress test, the Loewenstein-Acevedo Scales for Semantic Interference and Learning, Brief Computerized Version (LASSI-BC) could differentiate between Cognitively Unimpaired (CU) and amnestic Mild Cognitive Impairment (aMCI) groups. A second focus was to correlate LASSI-BC performance to volumetric reductions in AD-prone brain regions. Data was gathered from 111 older adults who were comprehensively evaluated and administered the LASSI-BC. Eighty-seven of these participants (51 CU; 36 aMCI) underwent MR imaging. The volumes of 12 AD-prone brain regions were related to LASSI-BC and other memory tests correcting for False Discovery Rate (FDR). Results indicated that, even after adjusting for initial learning ability, the failure to recover from proactive semantic interference (frPSI) on the LASSI-BC differentiated between CU and aMCI groups. An optimal combination of frPSI and initial learning strength on the LASSI-BC yielded an area under the ROC curve of 0.876 (76.1% sensitivity, 82.7% specificity). Further, frPSI on the LASSI-BC was associated with volumetric reductions in the hippocampus, amygdala, inferior temporal lobes, precuneus, and posterior cingulate.

Associations Between Vascular Risk Factors and Perivascular Spaces in Adults with Intact Cognition, Mild Cognitive Impairment, and Dementia.

BACKGROUND: Perivascular spaces (PVS) are fluid-filled compartments surrounding small intracerebral vessels that transport fluid and clear waste. OBJECTIVE: We examined associations between PVS count, vascular and neurodegenerative risk factors, and cognitive status among the predominantly Hispanic participants of the FL-VIP Study of Alzheimer's Disease Risk. METHODS: Using brain MRI (n = 228), we counted PVS in single axial image through the basal ganglia (BG) and centrum semiovale (CSO). PVS per region were scored as 0 (none), 1 (<10), 2 (11-20), 3 (21-40), and 4 (>40). Generalized linear models examined PVS associations with vascular risk factors and a composite vascular comorbidity risk (VASCom) score. RESULTS: Our sample (mean age 72±8 years, 61% women, 60% Hispanic, mean education 15±4 years, 33% APOE4 carriers) was 59% hypertensive, 21% diabetic, 66% hypercholesteremic, and 30% obese. Mean VASCom score was 2.3±1.6. PVS scores ranged from 0-4 in the BG (mean 1.3±0.7) and CSO (mean 1.2±0.9), and 0-7 combined (mean 2.5±1.4). In multivariable regression models, BG PVS was associated with age (ß= 0.03/year, p < 0.0001), Hispanic ethnicity (ß= 0.29, p = 0.01), education (ß= 0.04/year, p = 0.04), and coronary bypass surgery (ß= 0.93, p = 0.02). CSO PVS only associated with age (ß= 0.03/year, p < 0.01). APOE4 and amyloid-ß were not associated with PVS. CONCLUSION: BG PVS may be a marker of subclinical cerebrovascular disease. Further research is needed to validate associations and identify mechanisms linking BG PVS and cerebrovascular disease markers. PVS may be a marker of neurodegeneration despite our negative preliminary findings and more research is warranted. The association between BG PVS and Hispanic ethnicity also requires further investigation.

A multi-institutional pilot clinical trial of spectroscopic MRI-guided radiation dose escalation for newly diagnosed glioblastoma.

Background: Glioblastomas (GBMs) are aggressive brain tumors despite radiation therapy (RT) to 60 Gy and temozolomide (TMZ). Spectroscopic magnetic resonance imaging (sMRI), which measures levels of specific brain metabolites, can delineate regions at high risk for GBM recurrence not visualized on contrast-enhanced (CE) MRI. We conducted a clinical trial to assess the feasibility, safety, and efficacy of sMRI-guided RT dose escalation to 75 Gy for newly diagnosed GBMs. Methods: Our pilot trial (NCT03137888) enrolled patients at 3 institutions (Emory University, University of Miami, Johns Hopkins University) from September 2017 to June 2019. For RT, standard tumor volumes based on T2-FLAIR and T1w-CE MRIs with margins were treated in 30 fractions to 50.1 and 60 Gy, respectively. An additional high-risk volume based on residual CE tumor and Cho/NAA (on sMRI) ≥2× normal was treated to 75 Gy. Survival curves were generated by the Kaplan-Meier method. Toxicities were assessed according to CTCAE v4.0. Results: Thirty patients were treated in the study. The median age was 59 years. 30% were MGMT promoter hypermethylated; 7% harbored IDH1 mutation. With a median follow-up of 21.4 months for censored patients, median overall survival (OS) and progression-free survival were 23.0 and 16.6 months, respectively. This regimen appeared well-tolerated with 70% of grade 3 or greater toxicity ascribed to TMZ and 23% occurring at least 1 year after RT. Conclusion: Dose-escalated RT to 75 Gy guided by sMRI appears feasible and safe for patients with newly diagnosed GBMs. OS outcome is promising and warrants additional testing. Based on these results, a randomized phase II trial is in development.

Prevalence and Clinical Correlates of Intracranial Dolichoectasia in Individuals With Ischemic Stroke.

Background and Purpose: Acute ischemic stroke is a known complication of intracranial dolichoectasia (IDE). However, the frequency of IDE causing brain infarction is unknown. We aim to determine the prevalence and clinical correlates of IDE in acute ischemic stroke by employing an objective IDE definition for major intracranial arteries of the anterior and posterior circulation. Methods: Consecutive patients with acute ischemic stroke admitted to a tertiary-care hospital during a 4-month period were analyzed. Intracranial arterial diameter, length, and tortuosity were determined by semiautomatic vessel segmentation and considered abnormal if ≥2 SDs from the study population mean. Either ectasia (increased diameter) or dolichosis (increased length or tortuosity) of at least one proximal intracranial artery defined IDE. Symptomatic IDE was considered when the infarct was located in the territory supplied by an affected artery in the absence of any alternative pathogenic explanation. Multivariate models were fitted to determine IDE clinical correlates. Results: Among 211 cases screened, 200 patients (mean age 67±14 years, 47.5% men) with available intracranial vessel imaging were included. IDE was identified in 24% cases (5% with isolated ectasia, 9.5% with isolated dolichosis, and 9.5% with both ectasia and dolichosis). IDE was considered the most likely pathogenic mechanism in 12 cases (6% of the entire cohort), which represented 23.5% of strokes initially categorized as undetermined cause. In addition, 21% of small-artery occlusion strokes had the infarct territory supplied by a dolichoectatic vessel (3% of the entire cohort). IDE was independently associated with male sex (odds ratio, 4.2 [95% CI, 1.7­10.6]) and its component of ectasia was associated with advanced age (odds ratio, 3.5 [95% CI, 1.3­9.5]). Vascular risk profile was similar across patients with stroke with and without IDE. Conclusions: Our findings suggest that IDE is an arteriopathy frequently found in patients with acute ischemic stroke and is likely responsible for a sizable fraction of strokes initially categorized as of undetermined cause and perhaps also in those with small-artery occlusion.

T1-weighted and T2-weighted Subtraction MR Images for Glioma Visualization and Grading.

BACKGROUND AND PURPOSE: To evaluate the performance of multiparametric MR images in differentiation of different regions of the gross tumor area and for assessment of glioma grade. METHODS: Forty-six glioma subjects (18 grade II, 11 grade III, and 17 grade IV) underwent a comprehensive MR and spectroscopic imaging procedure. Maps were generated by subtraction of T1-weighted images from contrast-enhanced T1-weighted images (ΔT1 map) and T1-weighted images from T2-weighted images (ΔT2 map). Regions of interest (ROIs) were positioned in normal-appearing white matter (NAWM), enhancing tumor, hyperintense T2, necrotic region, and immediate and distal peritumoral regions (IPR and DPR). Relative signal contrast was estimated as difference between mean intensities in ROIs and NAWM. Classification using support vector machines was applied to all image series to determine the efficacy of regional contrast measures for differentiation of low- and high-grade lesions and grade III and IV lesions. RESULTS: ΔT1 and ΔT2 maps offered higher contrast as compared to other parametric maps in differentiating enhancing tumor and edematous regions, respectively, and provided the highest classification accuracy for differentiating low- and high-grade tumors, of 91% and 90.4%. Choline/N-acetylaspartate maps provided significant contrast for delineating IPR and DPR. For differentiating high-grade gliomas, ΔT2 and ΔT1 maps provided a mean accuracy of 90.9% and 88.2%, which was lower than that obtained using cerebral blood volume (93.7%) and choline/creatine (93.3%) maps. CONCLUSION: This study showed that subtraction maps provided significant contrast in differentiating several regions of the gross tumor area and are of benefit for accurate tumor grading.

The Longitudinal Imaging Tracker (BrICS-LIT):A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients.

Glioblastoma is a common and aggressive form of brain cancer affecting up to 20,000 new patients in the US annually. Despite rigorous therapies, current median survival is only 15-20 months. Patients who complete initial treatment undergo follow-up imaging at routine intervals to assess for tumor recurrence. Imaging is a central part of brain tumor management, but MRI findings in patients with brain tumor can be challenging to interpret and are further confounded by interpretation variability. Disease-specific structured reporting attempts to reduce variability in imaging results by implementing well-defined imaging criteria and standardized language. The Brain Tumor Reporting and Data System (BT-RADS) is one such framework streamlined for clinical workflows and includes quantitative criteria for more objective evaluation of follow-up imaging. To facilitate accurate and objective monitoring of patients during the follow-up period, we developed a cloud platform, the Brain Imaging Collaborative Suite's Longitudinal Imaging Tracker (BrICS-LIT). BrICS-LIT uses semiautomated tumor segmentation algorithms of both T2-weighted FLAIR and contrast-enhanced T1-weighted MRI to assist clinicians in quantitative assessment of brain tumors. The LIT platform can ultimately guide clinical decision-making for patients with glioblastoma by providing quantitative metrics for BT-RADS scoring. Further, this platform has the potential to increase objectivity when measuring efficacy of novel therapies for patients with brain tumor during their follow-up. Therefore, LIT will be used to track patients in a dose-escalated clinical trial, where spectroscopic MRI has been used to guide radiation therapy (Clinicaltrials.gov NCT03137888), and compare patients to a control group that received standard of care.

Effects of apodization smoothing and denoising on spectral fitting.

PURPOSE: Visual review of individual spectra in magnetic resonance spectroscopic imaging (MRSI) data benefits from the application of spectral smoothing; however, if this processing step is applied prior to spectral analysis this can impact the accuracy of the quantitation. This study aims to analyze the effect of spectral denoising and apodization smoothing on the quantitation of whole-brain MRSI data obtained at short TE. METHODS: Short-TE MRSI data obtained at 3 T were analyzed with no spectral smoothing, following (i) Gaussian apodization with values of 1, 2, 4, 6, and 8 Hz, and (ii) denoising using principal component analysis (dnPCA) with 3 different values for the number of retained principal components. The mean lobar white matter estimates for four metabolites, signal-to-noise ratio (SNR), spectral linewidth, and confidence intervals were compared to data reconstructed using no smoothing. Additionally, a voxel-wise comparison for N-acetylaspartate quantitation with different smoothing schemes was performed. RESULTS: Significant pairwise differences were seen for all Gaussian smoothing methods as compared to no smoothing (p<0.001) in linewidth and metabolite estimates, whereas dnPCA methods showing no statistically significant differences in these measures. Confidence intervals decreased, and SNR increased with increasing levels of apodization smoothing or dnPCA denoising. CONCLUSION: Mild Gaussian apodization (≤2 Hz at 3 T) can be applied with minimal (1%) errors in quantitation; however, smoothing values greater than that can significantly affect metabolite quantification. In contrast, mild to moderate dnPCA based denoising provides quantitative results that are consistent with the analysis of unsmoothed data and this method is recommended for spectral denoising.

The Association between Whole-Brain MR Spectroscopy and IDH Mutation Status in Gliomas.

BACKGROUND AND PURPOSE: Mutations in isocitrate dehydrogenase (IDH) have a direct effect on gliomagenesis. The purpose of this study is to quantify differences in brain metabolites due to IDH mutations. METHODS: Magnetic Resonance Spectroscopic Imaging (MRSI) was performed in 35 patients with gliomas of different grade and varied IDH mutation status. Volumes of interest (VOIs) for active tumor (tVOI), peritumoral area (pVOI), and contralateral normal-appearing white matter (cVOI) were created. Metabolite ratios of Choline (Cho) to both N-acetylaspartate (NAA) and Creatine (Cr) were estimated. Ratios of Glutamate/Glutamine complex (Glx) and myoinositol (mIno) to Cr were also quantified. General linear models (GLMs) were used to estimate the effects of IDH mutation on metabolite measures, with age, gender, and tumor grade used as covariates. RESULTS: GLM analysis showed that maximum Cho/NAA and Cho/Cr in the tVOI were significantly (P < .05) higher in IDH mutant lesions as compared to wild-type. In the pVOI, mean Cho/Cr was found to be significantly different among IDH mutant and wild-type gliomas. Mean Cho/NAA (P = .306) and Cho/Cr (P = .292) within the tVOI were not significantly different. Ratios of Glx/Cr and mIno/Cr in any region showed no significant differences between IDH mutant and wild-type gliomas. No significant differences in metabolite ratios were seen in the cVOI between IDH mutants and wild-types. CONCLUSION: IDH mutation's effect in gliomas show an increase in Cho in the tumor and perilesional regions as compared to wild-type lesions but do not show widespread changes across the brain.

The Brain Imaging Collaboration Suite (BrICS): A Cloud Platform for Integrating Whole-Brain Spectroscopic MRI into the Radiation Therapy Planning Workflow.

Glioblastoma has poor prognosis with inevitable local recurrence despite aggressive treatment with surgery and chemoradiation. Radiation therapy (RT) is typically guided by contrast-enhanced T1-weighted magnetic resonance imaging (MRI) for defining the high-dose target and T2-weighted fluid-attenuation inversion recovery MRI for defining the moderate-dose target. There is an urgent need for improved imaging methods to better delineate tumors for focal RT. Spectroscopic MRI (sMRI) is a quantitative imaging technique that enables whole-brain analysis of endogenous metabolite levels, such as the ratio of choline-to-N-acetylaspartate. Previous work has shown that choline-to-N-acetylaspartate ratio accurately identifies tissue with high tumor burden beyond what is seen on standard imaging and can predict regions of metabolic abnormality that are at high risk for recurrence. To facilitate efficient clinical implementation of sMRI for RT planning, we developed the Brain Imaging Collaboration Suite (BrICS; https://brainimaging.emory.edu/brics-demo), a cloud platform that integrates sMRI with standard imaging and enables team members from multiple departments and institutions to work together in delineating RT targets. BrICS is being used in a multisite pilot study to assess feasibility and safety of dose-escalated RT based on metabolic abnormalities in patients with glioblastoma (Clinicaltrials.gov NCT03137888). The workflow of analyzing sMRI volumes and preparing RT plans is described. The pipeline achieved rapid turnaround time by enabling team members to perform their delegated tasks independently in BrICS when their clinical schedules allowed. To date, 18 patients have been treated using targets created in BrICS and no severe toxicities have been observed.

Value of diffusion kurtosis imaging in assessing low-grade gliomas.

BACKGROUND: Diffusion kurtosis imaging (DKI) measures have been shown to provide increased sensitivity relative to diffusion tensor imaging (DTI) in detecting pathologies. PURPOSE: To compare the sensitivity of DKI-derived kurtosis and diffusion maps for assessment of low-grade gliomas (LGG). STUDY TYPE: Prospective study. POPULATION: In all, 19 LGG patients and 26 healthy control subjects were recruited. FIELD STRENGTH/SEQUENCE: Echo-planar-imaging diffusion-weighted MR images (b-values = 0, 1000, and 2000 with 30 diffusion gradient directions) were acquired on a 3T scanner. ASSESSMENT: Maps for mean, axial, and radial diffusivity (MD, AD, and RD) and kurtosis (MK, AK, and RK), and fractional anisotropy (FA) were evaluated in the tumor, perilesional white matter, and contralateral normal-appearing white matter regions. STATISTICAL TESTING: General linear models (GLM), Cohen's d for effect size estimates, false discovery rate (FDR) for multiple corrections, Cochran Q-test. RESULTS: Pairwise differences were observed for all diffusion and kurtosis measures between the studied regions (FDR P < 0.001), except an FA map that failed to show significant differences between the lesion and perilesional white matter (FDR P = 0.373). Effect size analysis showed that kurtosis metrics were found to be 18.8% (RK, P = 0.144) to 29.1% (AK, P < 0.05) more sensitive in discriminating perilesional regions from the lesion than corresponding diffusion metrics, whereas AK provided a 25.0% (P < 0.05) increase in sensitivity in discriminating perilesional and contralateral white matter. RK was found to be the most sensitive to contralateral white matter differences between low-grade gliomas and controls, with MK and RK providing a significantly greater sensitivity of 587.2% (P < 0.001) and 320.7% (P < 0.001) than MD and RD, respectively. DATA CONCLUSION: Kurtosis maps showed increased sensitivity, as compared to counterpart diffusion maps, for evaluation of microstructural changes in gliomas with a 3-6-fold increment in assessing changes in contralateral white matter. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;48:1551-1558.

Spectral decomposition for resolving partial volume effects in MRSI.

PURPOSE: Estimation of brain metabolite concentrations by MR spectroscopic imaging (MRSI) is complicated by partial volume contributions from different tissues. This study evaluates a method for increasing tissue specificity that incorporates prior knowledge of tissue distributions. METHODS: A spectral decomposition (sDec) technique was evaluated for separation of spectra from white matter (WM) and gray matter (GM), and for measurements in small brain regions using whole-brain MRSI. Simulation and in vivo studies compare results of metabolite quantifications obtained with the sDec technique to those obtained by spectral fitting of individual voxels using mean values and linear regression against tissue fractions and spectral fitting of regionally integrated spectra. RESULTS: Simulation studies showed that, for GM and the putamen, the sDec method offers < 2% and 3.5% error, respectively, in metabolite estimates. These errors are considerably reduced in comparison to methods that do not account for partial volume effects or use regressions against tissue fractions. In an analysis of data from 197 studies, significant differences in mean metabolite values and changes with age were found. Spectral decomposition resulted in significantly better linewidth, signal-to-noise ratio, and spectral fitting quality as compared to individual spectral analysis. Moreover, significant partial volume effects were seen on correlations of neurometabolite estimates with age. CONCLUSION: The sDec analysis approach is of considerable value in studies of pathologies that may preferentially affect WM or GM, as well as smaller brain regions significantly affected by partial volume effects. Magn Reson Med 79:2886-2895, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Effects of tissue susceptibility on brain temperature mapping.

A method for mapping of temperature over a large volume of the brain using volumetric proton MR spectroscopic imaging has been implemented and applied to 150 normal subjects. Magnetic susceptibility-induced frequency shifts in gray- and white-matter regions were measured and included as a correction in the temperature mapping calculation. Additional sources of magnetic susceptibility variations of the individual metabolite resonance frequencies were also observed that reflect the cellular-level organization of the brain metabolites, with the most notable differences being attributed to changes of the N-Acetylaspartate resonance frequency that reflect the intra-axonal distribution and orientation of the white-matter tracts with respect to the applied magnetic field. These metabolite-specific susceptibility effects are also shown to change with age. Results indicate no change of apparent brain temperature with age from 18 to 84 years old, with a trend for increased brain temperature throughout the cerebrum in females relative for males on the order of 0.1°C; slightly increased temperatures in the left hemisphere relative to the right; and a lower temperature of 0.3°C in the cerebellum relative to that of cerebral white-matter. This study presents a novel acquisition method for noninvasive measurement of brain temperature that is of potential value for diagnostic purposes and treatment monitoring, while also demonstrating limitations of the measurement due to the confounding effects of tissue susceptibility variations.

Regional distributions of brain glutamate and glutamine in normal subjects.

Glutamate (Glu) and glutamine (Gln) play an important role in neuronal regulation and are of value as MRS-observable diagnostic biomarkers. In this study the relative concentrations of these metabolites have been measured in multiple regions in the normal brain using a short-TE whole-brain MRSI measurement at 3 T combined with a modified data analysis approach that used spatial averaging to obtain high-SNR spectra from atlas-registered anatomic regions or interest. By spectral fitting of high-SNR spectra this approach yielded reliable measurements across a wide volume of the brain. Spectral averaging also demonstrated increased SNR and improved fitting accuracy for the sum of Glu and Gln (Glx) compared with individual voxel fitting. Results in 26 healthy controls showed relatively constant Glu/Cr and Gln/Cr throughout the cerebrum, although with increased values in the anterior cingulum and paracentral lobule, and increased Gln/Cr in the superior motor area. The deep gray-matter regions of thalamus, putamen, and pallidum show lower Glu/Cr compared with cortical white-matter regions. Lobar measurements demonstrated reduced Glu/Cr and Gln/Cr in the cerebellum as compared with the cerebrum, where white-matter regions show significantly lower Glu/Cr and Gln/Cr as compared with gray-matter regions across multiple brain lobes. Regression analysis showed no significant effect of gender on Glu/Cr or Gln/Cr measurement; however, Glx/Cr ratio was found to be significantly negatively correlated with age in some lobar brain regions. In summary, this methodology provides the spectral quality necessary for reliable separation of Glu and Gln at 3 T from a single MRSI acquisition enabling generation of regional distributions of metabolites over a large volume of the brain, including cortical regions. Copyright © 2016 John Wiley & Sons, Ltd.

18F-FLT Positron Emission Tomography/Computed Tomography Imaging in Pancreatic Cancer: Determination of Tumor Proliferative Activity and Comparison with Glycolytic Activity as Measured by 18F-FDG Positron Emission Tomography/Computed Tomography Imaging.

OBJECTIVE: This phase-I imaging study examined the imaging characteristic of 3'-deoxy-3'-(18F)-fluorothymidine (18F-FLT) positron emission tomography (PET) in patients with pancreatic cancer and comparisons were made with (18F)-fluorodeoxyglucose (18F-FDG). The ultimate aim was to develop a molecular imaging tool that could better define the biologic characteristics of pancreas cancer, and to identify the patients who could potentially benefit from surgical resection who were deemed inoperable by conventional means of staging. METHODS: Six patients with newly diagnosed pancreatic cancer underwent a combined FLT and FDG computed tomography (CT) PET/CT imaging protocol. The FLT PET/CT scan was performed within 1 week of FDG PET/CT imaging. Tumor uptake of a tracer was determined and compared using various techniques; statistical thresholding (z score=2.5), and fixed standardized uptake value (SUV) thresholds of 1.4 and 2.5, and applying a threshold of 40% of maximum SUV (SUVmax) and mean SUV (SUVmean). The correlation of functional tumor volumes (FTV) between 18F-FDG and 18F-FLT was assessed using linear regression analysis. RESULTS: It was found that there is a correlation in FTV due to metabolic and proliferation activity when using a threshold of SUV 2.5 for FDG and 1.4 for FLT (r=0.698, p=ns), but a better correlation was obtained when using SUV of 2.5 for both tracers (r=0.698, p=ns). The z score thresholding (z=2.5) method showed lower correlation between the FTVs (r=0.698, p=ns) of FDG and FLT PET. CONCLUSION: Different tumor segmentation techniques yielded varying degrees of correlation in FTV between FLT and FDG-PET images. FLT imaging may have a different meaning in determining tumor biology and prognosis.

(124)I PET/CT in Patients with Differentiated Thyroid Cancer: Clinical and Quantitative Image Analysis.

BACKGROUND: Although radioactive iodine (RAI) imaging/therapy is one of the earliest applications of theranostics, there remain a number of unresolved clinical questions as to the optimization of diagnostic techniques/protocols and improvements in patient-specific treatment planning strategies. The objectives of this study were to determine the imaging characteristics and clinical feasibility of (124)I positron emission tomography/computed tomography (PET/CT) for the determination of extent of disease and evaluation of RAI kinetics in its physiologic and neoplastic distribution in patients with differentiated thyroid cancer (DTC). METHODS: The study was designed as a prospective phase II diagnostic trial of patients with confirmed DTC. Following adequate preparation, patients received 2 mCi (124)I in liquid form and sequential whole-body PET/CT imaging was performed at five time points (2-4 h, 24 ± 6 h, 48 ± 6 h, 72 ± 6 h, and 96 ± 6 h post-administration). All patients who had (124)I imaging subsequently underwent RAI treatment with (131)I, with administered activities ranging from 100 to 300 mCi. Post-treatment scans were obtained 5-7 days after RAI treatment. A by-patient and by-lesion analysis of the (124)I images was performed and compared with the post-treatment (131)I scans as well as F-18 FDG PET/CT images. Quantitative image analysis was also performed to determine the total functional volume (mL), activity per functional volume (µCi/mL), and cumulated activity (µCi/h) for remnants, salivary glands, and nodal metastases. RESULTS: Fifteen patients (6 women; Mage = 57 years; range 29-91 years) were enrolled into the study. Forty-six distinct lesions were identified in these 15 patients on (124)I PET/CT images, with a sensitivity of 92.5%. In addition, (124)I identified 22.5% more foci of RAI-avid lesions compared with the planar (131)I post-treatment scans. This study demonstrates different kinetic profiles for normal thyroid remnants (peaked at 24 h with mono-exponential clearance), salivary glands (peaked at 4 h with bi-exponential clearance), and metastatic lesions (protracted retention), as well as individual variations in functional volumes and thus cumulated activities. CONCLUSIONS: (124)I PET/CT is a valuable clinical imaging tool/agent, both in determining the extent of disease in the setting of metastatic DTC and in the functional volumetric and kinetic evaluation of target lesions.

Proliferative and Glycolytic Assessment of the Whole-Body Bone Marrow Compartment.

OBJECTIVE: Quantitative assessment of active bone marrow (BM) in vivo is yet to be well-defined. This study aims to compare total body BM volume estimations obtained from use of both18F-FLT PET/CT and 18F-FDG PET/CT in order to consolidate higher cellular proliferation rates with imaging the highly active red BM in pancreatic cancer. METHODS: This phase I pilot study includes seven patients with pancreatic cancers who underwent both 18F-FLT and 18F-FDG imaging each acquired within a week's duration. A CT-based classifier is used for segmenting bone into cortical and trabecular regions. The total BM volume is determined through statistical thresholding on PET activity found within the trabecular bone. RESULTS: Results showed that 18F-FLT measures of red BM volume (RBV) were higher than those obtained from 18F-FDG (∆=89.21 ml). RBV obtained using 18F-FLT in males were found to have high correlation with measured weight (R2=0.61) and BMI (R2=0.70). The red BM fraction obtained from 18F-FLT was significantly different between males and females, with females showing much higher red bone matter within the trabecular bone (p<0.05). In contrast to 18F-FLT, 18F-FDG BM measurements showed that RBV was significantly different between males and females (p<0.05). Results also show that spinal activity SUV threshold for red BM segmentation is significantly different between 18F-FLT PET and 18F-FDG PET (p<0.05). CONCLUSION: By combining 18F-FLT-PET and 18F-FDG-PET, this study provides useful insights for in vivo BM estimation through its proliferative and glycolytic activities.

Inclusion of Neuropsychological Scores in Atrophy Models Improves Diagnostic Classification of Alzheimer's Disease and Mild Cognitive Impairment.

Brain atrophy in mild cognitive impairment (MCI) and Alzheimer's disease (AD) are difficult to demarcate to assess the progression of AD. This study presents a statistical framework on the basis of MRI volumes and neuropsychological scores. A feature selection technique using backward stepwise linear regression together with linear discriminant analysis is designed to classify cognitive normal (CN) subjects, early MCI (EMCI), late MCI (LMCI), and AD subjects in an exhaustive two-group classification process. Results show a dominance of the neuropsychological parameters like MMSE and RAVLT. Cortical volumetric measures of the temporal, parietal, and cingulate regions are found to be significant classification factors. Moreover, an asymmetrical distribution of the volumetric measures across hemispheres is seen for CN versus EMCI and EMCI versus AD, showing dominance of the right hemisphere; whereas CN versus LMCI and EMCI versus LMCI show dominance of the left hemisphere. A 2-fold cross-validation showed an average accuracy of 93.9%, 90.8%, and 94.5%, for the CN versus AD, CN versus LMCI, and EMCI versus AD, respectively. The accuracy for groups that are difficult to differentiate like EMCI versus LMCI was 73.6%. With the inclusion of the neuropsychological scores, a significant improvement (24.59%) was obtained over using MRI measures alone.