Weak to no correlation between quantitative high-resolution computed tomography metrics and lung function change in fibrotic diseases.

Background: Identifying systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) patients at risk of more rapid forced vital capacity (FVC) decline could improve trial design. The purpose of the present study was to explore the prognostic value of quantitative high-resolution computed tomography (HRCT) metrics derived by Imbio lung texture analysis (LTA) tool in predicting FVC slope. Methods: This retrospective study used data from patients who were not treated with investigational drugs with and without background antifibrotic therapies in tocilizumab phase 3 SSc, lebrikizumab phase 2 IPF, and zinpentraxin alfa phase 2 IPF studies conducted from 2015 to 2021. Controlled HRCT axial volumetric multidetector computed tomography scans were evaluated using the Imbio LTA tool. Associations between HRCT metrics and FVC slope were assessed through the Spearman correlation coefficient and adjusted R2 in a linear regression model adjusted by demographics and baseline clinical characteristics. Results: A total of 271 SSc and IPF patients were analysed. Correlation coefficients of highest magnitude were observed in the SSc study between the extent of ground glass, normal volume, quantification of interstitial lung disease, reticular pattern, and FVC slope (-0.25, 0.28, -0.28, and -0.33, respectively), while the correlation coefficients observed in IPF studies were in general <0.2. The incremental prognostic value of the baseline HRCT metrics was marginal after adjusting baseline characteristics and was inconsistent across study arms. Conclusion: Data from the SSc and IPF studies suggested weak to no and inconsistent correlation between quantitative HRCT metrics derived by the Imbio LTA tool and FVC slope in the studied SSc and IPF population.

Magnetic Resonance Enterography and Histology in Patients With Fibrostenotic Crohn's Disease: A Multicenter Study.

INTRODUCTION: Magnetic resonance enterography (MRE) is useful for detecting bowel strictures, whereas a number of imaging biomarkers may reflect severity of fibrosis burden in Crohn's disease (CD). This study aimed to verify the association of MRE metrics with histologic fibrosis independent of inflammation. METHODS: This prospective European multicenter study performed MRE imaging on 60 patients with CD with bowel strictures before surgical resection. Locations of 61 histological samples were annotated on MRE examinations, followed by central readings using the Chiorean score and measurement of delayed gain of enhancement (DGE), magnetization transfer ratio, T2-weighted MRI sequences (T2R), apparent diffusion coefficient (ADC), and the magnetic resonance index of activity (MaRIA). Correlations of histology and MRE metrics were assessed. Least Absolute Shrinkage and Selection Operator and receiver operator characteristic (ROC) curve analyses were used to select composite MRE scores predictive of histology and to estimate their predictive value. RESULTS: ADC and MaRIA correlated with fibrosis (R = -0.71, P < 0.0001, and 0.59, P < 0.001) and more moderately with inflammation (R = -0.35, P < 0.01, and R = 0.53, P < 0.001). Lower or no correlations of fibrosis or inflammation were found with DGE, magnetization transfer ratio, or T2R. Least Absolute Shrinkage and Selection Operator and ROC identified a composite score of MaRIA, ADC, and DGE as a very good predictor of histologic fibrosis (ROC area under the curve = 0.910). MaRIA alone was the best predictor of histologic inflammation with excellent performance in identifying active histologic inflammation (ROC area under the curve = 0.966). DISCUSSION: MRE-based scores for histologic fibrosis and inflammation may assist in the characterization of CD stenosis and enable development of fibrosis-targeted therapies and clinical treatment of stenotic patients.

Heart and bladder detection and segmentation on FDG PET/CT by deep learning.

PURPOSE: Positron emission tomography (PET)/ computed tomography (CT) has been extensively used to quantify metabolically active tumors in various oncology indications. However, FDG-PET/CT often encounters false positives in tumor detection due to 18fluorodeoxyglucose (FDG) accumulation from the heart and bladder that often exhibit similar FDG uptake as tumors. Thus, it is necessary to eliminate this source of physiological noise. Major challenges for this task include: (1) large inter-patient variability in the appearance for the heart and bladder. (2) The size and shape of bladder or heart may appear different on PET and CT. (3) Tumors can be very close or connected to the heart or bladder. APPROACH: A deep learning based approach is proposed to segment the heart and bladder on whole body PET/CT automatically. Two 3D U-Nets were developed separately to segment the heart and bladder, where each network receives the PET and CT as a multi-modal input. Data sets were obtained from retrospective clinical trials and include 575 PET/CT for heart segmentation and 538 for bladder segmentation. RESULTS: The models were evaluated on a test set from an independent trial and achieved a Dice Similarity Coefficient (DSC) of 0.96 for heart segmentation and 0.95 for bladder segmentation, Average Surface Distance (ASD) of 0.44 mm on heart and 0.90 mm on bladder. CONCLUSIONS: This methodology could be a valuable component to the FDG-PET/CT data processing chain by removing FDG physiological noise associated with heart and/or bladder accumulation prior to image analysis by manual, semi- or automated tumor analysis methods.

First-in-Human Phase I Study to Evaluate the Brain-Penetrant PI3K/mTOR Inhibitor GDC-0084 in Patients with Progressive or Recurrent High-Grade Glioma.

PURPOSE: GDC-0084 is an oral, brain-penetrant small-molecule inhibitor of PI3K and mTOR. A first-in-human, phase I study was conducted in patients with recurrent high-grade glioma. PATIENTS AND METHODS: GDC-0084 was administered orally, once daily, to evaluate safety, pharmacokinetics (PK), and activity. Fluorodeoxyglucose-PET (FDG-PET) was performed to measure metabolic responses. RESULTS: Forty-seven heavily pretreated patients enrolled in eight cohorts (2-65 mg). Dose-limiting toxicities included 1 case of grade 2 bradycardia and grade 3 myocardial ischemia (15 mg), grade 3 stomatitis (45 mg), and 2 cases of grade 3 mucosal inflammation (65 mg); the MTD was 45 mg/day. GDC-0084 demonstrated linear and dose-proportional PK, with a half-life (∼19 hours) supportive of once-daily dosing. At 45 mg/day, steady-state concentrations exceeded preclinical target concentrations producing antitumor activity in xenograft models. FDG-PET in 7 of 27 patients (26%) showed metabolic partial response. At doses ≥45 mg/day, a trend toward decreased median standardized uptake value in normal brain was observed, suggesting central nervous system penetration of drug. In two resection specimens, GDC-0084 was detected at similar levels in tumor and brain tissue, with a brain tissue/tumor-to-plasma ratio of >1 and >0.5 for total and free drug, respectively. Best overall response was stable disease in 19 patients (40%) and progressive disease in 26 patients (55%); 2 patients (4%) were nonevaluable. CONCLUSIONS: GDC-0084 demonstrated classic PI3K/mTOR-inhibitor related toxicities. FDG-PET and concentration data from brain tumor tissue suggest that GDC-0084 crossed the blood-brain barrier.

The role of fMRI in drug development.

Functional magnetic resonance imaging (fMRI) has been known for over a decade to have the potential to greatly enhance the process of developing novel therapeutic drugs for prevalent health conditions. However, the use of fMRI in drug development continues to be relatively limited because of a variety of technical, biological, and strategic barriers that continue to limit progress. Here, we briefly review the roles that fMRI can have in the drug development process and the requirements it must meet to be useful in this setting. We then provide an update on our current understanding of the strengths and limitations of fMRI as a tool for drug developers and recommend activities to enhance its utility.

Evaluation of an fMRI USPIO-based assay in healthy human volunteers.

PURPOSE: To present the testretest and contrast dose effect results of cerebral blood volume (CBV) functional MRI (fMRI) in healthy human volunteers using ferumoxytol (Feraheme), an ultrasmall-superparamagnetic iron oxide (USPIO) nanoparticle. MATERIALS AND METHODS: This was an open-label, two-period, fixed-sequence study in healthy young volunteers. In eight subjects, using a 3 Tesla field strength system, blood oxygen level dependent (BOLD) and CBV fMRI were acquired in response to a visual black-and-white checkboard stimulation paradigm using an escalating ferumoxytol dose design (250, 350, and 510 mg iron). Multiple outcome measures were analyzed including absolute percent signal change (|PSC|, primary endpoint), its contrast-to-noise ratio (CNR) and corresponding z-score, percent CBV change (ΔCBV) and respective CNR, concentration of Fe, and baseline CBV. RESULTS: The |PSC| in the visual cortex increased with ferumoxytol dose and was up to 3 × higher than BOLD fMRI. Test-retest reliability was comparable for BOLD and CBV fMRI. Intraclass correlation coefficients (ICCs) for |PSC| were 0.3 (one-sided 95% lower confidence limit = 0.00), 0.81 (0.47), 0.48 (0.00), and 0.3 (0.00) for BOLD and the 250-, 350-, and 510-mg doses of ferumoxytol, respectively. For ΔCBV, ICCs were 0.77 (0.37), 0.48 (0.00), and 0.49 (0.00) for 250 mg, 350 mg, and 510 mg, respectively. CONCLUSION: This work demonstrates that CBV fMRI techniques and endpoints are dose dependent, robust and have good test-retest repeatability. It also confirms previous findings that USPIO enhances sensitivity of fMRI stimulus-response endpoints. LEVEL OF EVIDENCE: 1 J. MAGN. RESON. IMAGING 2017;46:124-133.

A comparison of confidence interval methods for the concordance correlation coefficient and intraclass correlation coefficient with small number of raters.

The intraclass correlation coefficient (ICC) with fixed raters or, equivalently, the concordance correlation coefficient (CCC) for continuous outcomes is a widely accepted aggregate index of agreement in settings with small number of raters. Quantifying the precision of the CCC by constructing its confidence interval (CI) is important in early drug development applications, in particular in qualification of biomarker platforms. In recent years, there have been several new methods proposed for construction of CIs for the CCC, but their comprehensive comparison has not been attempted. The methods consisted of the delta method and jackknifing with and without Fisher's Z-transformation, respectively, and Bayesian methods with vague priors. In this study, we carried out a simulation study, with data simulated from multivariate normal as well as heavier tailed distribution (t-distribution with 5 degrees of freedom), to compare the state-of-the-art methods for assigning CI to the CCC. When the data are normally distributed, the jackknifing with Fisher's Z-transformation (JZ) tended to provide superior coverage and the difference between it and the closest competitor, the Bayesian method with the Jeffreys prior was in general minimal. For the nonnormal data, the jackknife methods, especially the JZ method, provided the coverage probabilities closest to the nominal in contrast to the others which yielded overly liberal coverage. Approaches based upon the delta method and Bayesian method with conjugate prior generally provided slightly narrower intervals and larger lower bounds than others, though this was offset by their poor coverage. Finally, we illustrated the utility of the CIs for the CCC in an example of a wake after sleep onset (WASO) biomarker, which is frequently used in clinical sleep studies of drugs for treatment of insomnia.

Ferumoxytol enhanced resting state fMRI and relative cerebral blood volume mapping in normal human brain.

The brain demonstrates spontaneous low-frequency (<0.1 Hz) cerebral blood flow (CBF) fluctuations, measurable by resting state functional MRI (rs-fMRI). Ultra small superparamagnetic iron oxide particles have been shown to enhance task-based fMRI signals (cerebral blood volume fMRI or CBV-fMRI), compared to the BOLD effect, by a factor of ≈2.5 at 3 T in primates and humans. We evaluated the use of ferumoxytol for steady state, resting state FMRI (CBV-rs-fMRI) and relative cerebral blood volume (rCBV) mapping, at 3T, in healthy volunteers. All standard resting state networks (RSNs) were identified in all subjects. On average the RSN Z statistics (MELODIC independent components) and volumes of the visual and default mode (DMN) networks were comparable. rCBV values were averaged for the visual (Vis) and DMN networks and correlated with the corresponding DMN and visual network Z statistics. There was a negative correlation between the rCBV and the Z statistics for the DMN, for both BOLD and CBV-rs-fMRI contrast (R2=0.63, 0.76). A similar correlation was not found for the visual network. Short repetition time rs-fMRI data were Fourier transformed to evaluate the effect of ferumoxytol on cardiac and respiratory fluctuations in the brain rs-BOLD, CBV signals. Cardiac and respiratory fluctuations decreased to baseline within large vessels post ferumoxytol. Robust rs-fMRI and CBV mapping is possible in normal human brain.

Parallel buprenorphine phMRI responses in conscious rodents and healthy human subjects.

Pharmacological magnetic resonance imaging (phMRI) is one method by which a drug's pharmacodynamic effects in the brain can be assessed. Although phMRI has been frequently used in preclinical and clinical settings, the extent to which a phMRI signature for a compound translates between rodents and humans has not been systematically examined. In the current investigation, we aimed to build on recent clinical work in which the functional response to 0.1 and 0.2 mg/70 kg i.v. buprenorphine (partial µ-opioid receptor agonist) was measured in healthy humans. Here, we measured the phMRI response to 0.04 and 0.1 mg/kg i.v. buprenorphine in conscious, naive rats to establish the parallelism of the phMRI signature of buprenorphine across species. PhMRI of 0.04 and 0.1 mg/kg i.v. buprenorphine yielded dose-dependent activation in a brain network composed of the somatosensory cortex, cingulate, insula, striatum, thalamus, periaqueductal gray, and cerebellum. Similar dose-dependent phMRI activation was observed in the human phMRI studies. These observations indicate an overall preservation of pharmacodynamic responses to buprenorphine between conscious, naive rodents and healthy human subjects, particularly in brain regions implicated in pain and analgesia. This investigation further demonstrates the usefulness of phMRI as a translational tool in neuroscience research that can provide mechanistic insight and guide dose selection in drug development.

Quantifying temporal correlations: a test-retest evaluation of functional connectivity in resting-state fMRI.

There have been many interpretations of functional connectivity and proposed measures of temporal correlations between BOLD signals across different brain areas. These interpretations yield from many studies on functional connectivity using resting-state fMRI data that have emerged in recent years. However, not all of these studies used the same metrics for quantifying the temporal correlations between brain regions. In this paper, we use a public-domain test-retest resting-state fMRI data set to perform a systematic investigation of the stability of the metrics that are often used in resting-state functional connectivity (FC) studies. The fMRI data set was collected across three different sessions. The second session took place approximately eleven months after the first session, and the third session was an hour after the second session. The FC metrics composed of cross-correlation, partial cross-correlation, cross-coherence, and parameters based on an autoregressive model. We discussed the strengths and weaknesses of each metric. We performed ROI-level and full-brain seed-based voxelwise test-retest analyses using each FC metric to assess its stability. For both ROI-level and voxel-level analyses, we found that cross-correlation yielded more stable measurements than the other metrics. We discussed the consequences of this result on the utility of the FC metrics. We observed that for negatively correlated ROIs, their partial cross-correlation is shrunk towards zero, thus affecting the stability of their FC. For the present data set, we found greater stability in FC between the second and third sessions (one hour between sessions) compared to the first and second sessions (approximately 11months between sessions). Finally, we report that some of the metrics showed a positive association between strength and stability. In summary, the results presented in this paper suggest important implications when choosing metrics for quantifying and assessing various types of functional connectivity for resting-state fMRI studies.

Decision-making using fMRI in clinical drug development: revisiting NK-1 receptor antagonists for pain.

Substance P (SP) and neurokinin-1 receptors (NK-1R) are localized within central and peripheral sensory pain pathways. The roles of SP and NK-1R in pain processing, the anatomical distribution of NK-1R and efficacy observed in preclinical pain studies involving pain and sensory sensitization models, suggested that NK-1R antagonists (NK-1RAs) would relieve pain in patient populations. Despite positive data available in preclinical tests for a role of NK-1RAs in pain, clinical studies across several pain conditions have been negative. In this review, we discuss how functional imaging-derived information on activity in pain-processing brain regions could have predicted that NK-1RAs would have a low probability of success in this therapeutic domain.

Modulation of CNS pain circuitry by intravenous and sublingual doses of buprenorphine.

Buprenorphine (BUP) is a partial agonist at µ-, δ- and ORL1 (opioid receptor-like)/nociceptin receptors and antagonist at the κ-opioid receptor site. BUP is known to have both analgesic as well as antihyperalgesic effects via its central activity, and is used in the treatment of moderate to severe chronic pain conditions. Recently, it was shown that intravenous (IV) administration of 0.2mg/70 kg BUP modulates the blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) response to acute noxious stimuli in healthy human subjects. The present study extends these observations by investigating the effects of BUP dose and route of administration on central nervous system (CNS) pain circuitry. Specifically, the modulation of evoked pain BOLD responses and resting state functional connectivity was measured following IV (0.1 and 0.2mg/70 kg) and sublingual (SL) (2mg) BUP administration in healthy human subjects. While 0.1mg/70 kg IV BUP is sub-analgesic, both 0.2mg/70 kg IV BUP and 2.0mg SL BUP are analgesic doses of the drug. Evoked BOLD responses were clearly modulated in a dose-dependent manner. The analgesic doses of BUP by both routes of administration yielded a potentiation in limbic/mesolimbic circuitry and attenuation in sensorimotor/sensory-discriminative circuitry. In addition, robust decreases in functional connectivity between the putamen and the sensorimotor/sensory-discriminative structures were observed at the two analgesic doses subsequent to measuring the maximum plasma BUP concentrations (C(max)). The decreases in functional connectivity within the sensorimotor/sensory-discriminative circuitry were also observed to be dose-dependent in the IV administration cohorts. These reproducible and consistent functional CNS measures at clinically effective doses of BUP demonstrate the potential of evoked pain fMRI and resting-state functional connectivity as objective tools that can inform the process of dose selection. Such methods may be useful during early clinical phase evaluation of potential analgesics in drug development.

fMRI of pain processing in the brain: a within-animal comparative study of BOLD vs. CBV and noxious electrical vs. noxious mechanical stimulation in rat.

This study aims to identify fMRI signatures of nociceptive processing in whole brain of anesthetized rats during noxious electrical stimulation (NES) and noxious mechanical stimulation (NMS) of paw. Activation patterns for NES were mapped with blood oxygen level dependent (BOLD) and cerebral blood volume (CBV) fMRI, respectively, to investigate the spatially-dependent hemodynamic responses during nociception processing. A systematic evaluation of fMRI responses to varying frequencies of electrical stimulus was carried out to optimize the NES protocol. Both BOLD and CBV fMRI showed widespread activations, but with different spatial characteristics. While BOLD and CBV showed well-localized activations in ipsilateral dorsal column nucleus, contralateral primary somatosensory cortex (S1), and bilateral caudate putamen (CPu), CBV fMRI showed additional bilateral activations in the regions of pons, midbrain and thalamus compared to BOLD fMRI. CBV fMRI that offers higher sensitivity compared to BOLD was then used to compare the nociception processing during NES and NMS in the same animal. The activations in most regions were similar. In the medulla, however, NES induced a robust activation in the ipsilateral dorsal column nucleus while NMS showed no activation. This study demonstrates that (1) the hemodynamic response to nociception is spatial-dependent; (2) the widespread activations during nociception in CBV fMRI are similar to what have been observed in (14)C-2-deoxyglucose (2DG) autoradiography and PET; (3) the bilateral activations in the brain originate from the divergence of neural responses at supraspinal level; and (4) the similarity of activation patterns suggests that nociceptive processing in rats is similar during NES and NMS.

Imaging drugs with and without clinical analgesic efficacy.

The behavioral response to pain is driven by sensory and affective components, each of which is mediated by the CNS. Subjective pain ratings are used as readouts when appraising potential analgesics; however, pain ratings alone cannot enable a characterization of CNS pain circuitry during pain processing or how this circuitry is modulated pharmacologically. Having a more objective readout of potential analgesic effects may allow improved understanding and detection of pharmacological efficacy for pain. The pharmacological/functional magnetic resonance imaging (phMRI/fMRI) methodology can be used to objectively evaluate drug action on the CNS. In this context, we aimed to evaluate two drugs that had been developed as analgesics: one that is efficacious for pain (buprenorphine (BUP)) and one that failed as an analgesic in clinical trials aprepitant (APREP). Using phMRI, we observed that activation induced solely by BUP was present in regions with µ-opioid receptors, whereas APREP-induced activation was seen in regions expressing NK(1) receptors. However, significant pharmacological modulation of functional connectivity in pain-processing pathways was only observed following BUP administration. By implementing an evoked pain fMRI paradigm, these drugs could also be differentiated by comparing the respective fMRI signals in CNS circuits mediating sensory and affective components of pain. We report a correlation of functional connectivity and evoked pain fMRI measures with pain ratings as well as peak drug concentration. This investigation demonstrates how CNS-acting drugs can be compared, and how the phMRI/fMRI methodology may be used with conventional measures to better evaluate candidate analgesics in small subject cohorts.

A procedural framework for good imaging practice in pharmacological fMRI studies applied to drug development #1: processes and requirements.

There is increasing interest in the application of quantitative magnetic resonance imaging (MRI) methods to drug development, but as yet little standardization or best practice guidelines for its use in this context. Pharmaceutical trials are subject to regulatory constraints and sponsor company processes, including site qualification and expectations around study oversight, blinding, quality assurance and quality control (QA/QC), analysis and reporting of results. In this article, we review the processes on the sponsor side and also the procedures involved in data acquisition at the imaging site. We then propose summary recommendations to help guide appropriate imaging site qualification, as part of a framework of 'good imaging practice' for functional (f)MRI studies applied to drug development.

Robust, unbiased general linear model estimation of phMRI signal amplitude in the presence of variation in the temporal response profile.

PURPOSE: To determine a simple yet robust method to generate parsimonious design matrices that accurately estimate the "pharmacological MRI" (phMRI) response amplitude in the presence of both confounding signals and variability in temporal profile. Variability in the temporal response profile of phMRI time series data is often observed. If not properly accounted for, this variation can result in inaccurate and unevenly biased signal amplitude estimates when modeled within a general linear model (GLM) framework. MATERIALS AND METHODS: The approach uses a low-rank singular value decomposition (SVD) approximation to a set of vectors capturing anticipated variations of no interest around the signal model to generate additional regressors for the design matrix. The method is demonstrated for both plateau and bolus type phMRI response profiles in the presence of variation in signal onset and/or shape, and applied to an in vivo blood oxygenation level-dependent (BOLD) phMRI study of buprenorphine in healthy human subjects. RESULTS: In general, 2-3 additional regressors, capturing >75% of the anticipated variance, resulted in robust and unbiased signal amplitude estimates in the presence of substantial variability. CONCLUSION: This method provides a simple and flexible means to provide robust phMRI amplitude estimates within a GLM framework.

A statistical framework for optimal design matrix generation with application to fMRI.

The general linear model (GLM) is a well established tool for analyzing functional magnetic resonance imaging (fMRI) data. Most fMRI analyses via GLM proceed in a massively univariate fashion where the same design matrix is used for analyzing data from each voxel. A major limitation of this approach is the locally varying nature of signals of interest as well as associated confounds. This local variability results in a potentially large bias and uncontrolled increase in variance for the contrast of interest. The main contributions of this paper are two fold: 1) we develop a statistical framework that enables estimation of an optimal design matrix while explicitly controlling the bias variance decomposition over a set of potential design matrices and 2) we develop and validate a numerical algorithm for computing optimal design matrices for general fMRI data sets. The implications of this framework include the ability to match optimally the magnitude of underlying signals to their true magnitudes while also matching the "null" signals to zero size thereby optimizing both the sensitivity and specificity of signal detection. By enabling the capture of multiple profiles of interest using a single contrast (as opposed to an F-test) in a way that optimizes for both bias and variance enables the passing of first level parameter estimates and their variances to the higher level for group analysis which is not possible using F-tests. We demonstrate the application of this approach to in vivo pharmacological fMRI data capturing the acute response to a drug infusion, to task-evoked, block design fMRI and to the estimation of a haemodynamic response function (HRF) in event-related fMRI. Although developed with motivation from fMRI, our framework is quite general and has potentially wide applicability to a variety of disciplines.

Improved characterization of BOLD responses for evoked sensory stimuli.

Pain and somatosensory processing involves an interaction of multiple neuronal networks. One result of these complex interactions is the presence of differential responses across brain regions that may be incompletely modeled by a straightforward application of standard general linear model (GLM) approaches based solely on the applied stimulus. We examined temporal blood oxygenation-level dependent (BOLD) signatures elicited by two stimulation paradigms (brush and heat) providing innocuous and noxious stimuli. Data were acquired from 32 healthy male subjects (2 independent cohorts). Regional time courses and model-free analyses of the first cohort revealed distinct temporal features of the BOLD responses elicited during noxious versus innocuous stimulation. Specifically, a biphasic (dual peak) BOLD signal was observed in response to heat but much less so in response to brush stimuli. This signal was characterized by a stimulus-locked response along with a second peak delayed by approximately 12.5 s. A cross-validation error analysis determined a modified design matrix comprising two explanatory variables (EVs) as a parsimonious means to model the biphasic responses within a GLM framework. One EV was directly derived from the stimulation paradigm (EV1), while the second EV (EV2) was EV1 shifted by 12.5 s. The 2EV GLM analysis enabled a more detailed characterization of the elicited BOLD responses, particularly during pain processing. This was confirmed by application of the model to a second, independent cohort[AU1]. Furthermore, the delayed component of the biphasic response was strongly associated with the noxious heat stimuli, suggesting that this may represent a sensitive fMRI link of pain processing.

BOLD and blood volume-weighted fMRI of rat lumbar spinal cord during non-noxious and noxious electrical hindpaw stimulation.

Spinal cord fMRI is a useful tool for studying spinal mechanisms of pain, hence for analgesic drug development. Its technical feasibility in both humans and rats has been demonstrated. This study investigates the reproducibility, robustness, and spatial accuracy of fMRI of lumbar spinal cord activation due to transcutaneous noxious and non-noxious electrical stimulation of the hindpaw in alpha-chloralose-anesthetized rats. Blood oxygenation level-dependent (BOLD) and blood volume-weighted fMRI data were acquired without and with intravenous injection of ultra small superparamagnetic iron oxide particles (USPIO), respectively, using a gradient echo (GE) echo planar imaging (EPI) technique at 4.7 T. Neuronal activation in the spinal cord induced by noxious stimulation to the hindpaw (2 ms wide, 5 mA amplitude, known to activate C-fibers) can be robustly detected by both fMRI techniques with excellent reproducibility and peaked at the stimulus frequency of 40 Hz. However, both fMRI techniques were not sensitive to neuronal activation in spinal cord induced by non-noxious stimulation (0.3 ms, 1.5 mA, known only to activate A-fibers). Spatially, the fMRI signal extended approximately 5 mm in the longitudinal direction, covering L(3)-L(5) segments. In the cross-sectional direction, the highest signal change of blood volume-weighted fMRI was in the middle of the ipsilateral dorsal horn, which roughly corresponds to laminae V and VI, while the highest signal change of BOLD fMRI was in the ipsilateral dorsal surface. This study demonstrates that spinal cord fMRI can be performed in anesthetized rats reliably and reproducibly offering it as a potential tool for analgesic drug discovery.

The role of MRI and PET/SPECT in Alzheimer's disease.

Alzheimer's disease (AD) is difficult to diagnose in its early stages, and even if detected early, there is no preventative treatment. Imaging modalities such as MRI, PET, and SPECT have the potential to contribute to both the diagnosis of Alzheimer's disease, as well as assist in the search for more effective treatments. A number of AD-related biomarkers have been proposed and evaluated. The use of PET imaging to detect alterations in regional brain metabolism using [(18)F]FDG has enabled more sensitive and accurate early diagnosis of AD, especially in conjunction with traditional medical evaluation. Additionally, magnetic resonance imaging and spectroscopy provide a wide range of biomarkers that have been shown to correlate with the progression of AD. Some of these markers have been pursued in clinical trials. Progress has been made toward the evaluation of other more AD-specific biomarkers. However, many questions remain concerning the validity and sensitivity of these imaging biomarkers to aid in the assessment of potential new treatments, especially those related to increased levels of amyloid peptides in the brain.