Spinal Cord Diffusion-Tensor Imaging and Motor-evoked Potentials in Multiple Sclerosis Patients: Microstructural and Functional Asymmetry

Purpose: To assess possible association between intrinsic structural damage and clinical disability by correlating spinal cord diffusion-tensor (DT) imaging data with electrophysiological parameters in patients with a diagnosis of multiple sclerosis (MS). Materials and Methods: This study was approved by the local ethical committee according to the declaration of Helsinki and written informed consent was obtained. DT images and T1- and T2-weighted images of the spinal cord were acquired in 28 healthy volunteers and 41 MS patients. Fractional anisotropy (FA) and apparent diffusion coefficients were evaluated in normal-appearing white matter (NAWM) at the cervical level and were correlated with motor-evoked potentials (n = 34). Asymmetry index was calculated for FA values with corresponding left and right regions of interest as percentage of the absolute difference between these values relative to the sum of the respective FA values. Statistical analysis included Spearman rank correlations, Mann-Whitney test, and reliability analysis. Results: Healthy volunteers had low asymmetry index (1.5%-2.2%). In MS patients, structural abnormalities were reflected by asymmetric decrease of FA (asymmetry index: 3.6%; P = .15). Frequently asymmetrically affected among MS patients was left and right central motor conduction time (CMCT) to abductor digiti minimi muscle (ADMM) (asymmetry index, 15%-16%) and tibialis anterior muscle (TAM) (asymmetry index, 9.5%-14.1%). Statistically significant correlations of functional (ie, electrophysiological) and structural (ie, DT imaging) asymmetries were found (P = .005 for CMCT to ADMM; P = .007 for CMCT to TAM) for the cervical lateral funiculi, which comprise the crossed pyramidal tract. Interobserver reliability for DT imaging measurements was excellent (78%-87%). Conclusion: DT imaging revealed asymmetric anatomic changes in spinal cord NAWM, which corresponded to asymmetric electrophysiological deficits for both arms and legs, and reflected a specific structure-function relationship in the human spinal cord. © RSNA, 2013.

Examining the gateway to the limbic system with diffusion tensor imaging: the perforant pathway in dementia

Current treatments for Alzheimer's disease (AD) are only able to slow the progression of mental deterioration, making early and reliable diagnosis an essential part of any promising therapeutic strategy. In the initial stages of AD, the first neuropathological alterations occur in the perforant pathway (PP), a large neuronal fiber tract located at the entrance to the limbic system. However, to date, there is no sensitive diagnostic tool for performing in vivo assessments of this structure. In the present bimodal magnetic resonance imaging (MRI) study, we examined 10 elderly controls, 10 subjects suffering from mild cognitive impairment (MCI), and 10 AD patients in order to evaluate the sensitivity of diffusion tensor imaging (DTI), a new MRI technique, for detecting changes in the PP. Furthermore, the diagnostic explanatory power of DTI data of the PP should be compared to high-resolution MRI volumetry and intervoxel coherences (COH) of the hippocampus and the entorhinal cortex, two limbic regions also involved in the pathophysiology of early AD. DTI revealed a marked decrease in COH values in the PP region of MCI (right side: 26%, left side: 29%, as compared to controls) and AD patients (right side: 37%, left side: 43%, as compared to controls). Reductions in COH values of the PP region were significantly correlated with cognitive impairment. DTI data of the PP zone were the only parameter differing significantly between control subjects and MCI patients, while the volumetric measures and the COH values of the hippocampus and the entorhinal cortex did not. DTI of medial temporal brain regions is a promising non-invasive tool for the in vivo diagnosis of the early/preclinical stages of AD.

Apparent diffusion coefficient in the aging mouse brain: a magnetic resonance imaging study

Novel magnetic resonance imaging sequences have and still continue to play an increasing role in neuroimaging and neuroscience. Among these techniques, diffusion-weighted imaging (DWI) has revolutionized the diagnosis and management of diseases such as stroke, neoplastic disease and inflammation. However, the effects of aging on diffusion are yet to be determined. To establish reference values for future experimental mouse studies we tested the hypothesis that absolute apparent diffusion coefficients (ADC) of the normal brain change with age. A total of 41 healthy mice were examined by T2-weighted imaging and DWI. For each animal ADC frequency histograms (i) of the whole brain were calculated on a voxel-by-voxel basis and region-of-interest (ROI) measurements (ii) performed and related to the animals' age. The mean entire brain ADC of mice <3 months was 0.715(+/-0.016) x 10(-3) mm2/s, no significant difference to mice aged 4 to 5 months (0.736(+/-0.040) x 10(-3) mm2/s) or animals older than 9 months 0.736(+/-0.020) x 10(-3) mm2/s. Mean whole brain ADCs showed a trend towards lower values with aging but both methods (i + ii) did not reveal a significant correlation with age. ROI measurements in predefined areas: 0.723(+/-0.057) x 10(-3) mm2/s in the parietal lobe, 0.659(+/-0.037) x 10(-3) mm2/s in the striatum and 0.679(+/-0.056) x 10(-3) mm2/s in the temporal lobe. With advancing age, we observed minimal diffusion changes in the whole mouse brain as well as in three ROIs by determination of ADCs. According to our data ADCs remain nearly constant during the aging process of the brain with a small but statistically non-significant trend towards a decreased diffusion in older animals.

Noninvasive estimation of organ weights by postmortem magnetic resonance imaging and multislice computed tomography

OBJECTIVE: Computed tomography (CT) and magnetic resonance imaging (MRI) are introduced as an alternative to traditional autopsy. The purpose of this study was to investigate their accuracy in mass estimation of liver and spleen. METHODS: In 44 cases, the weights of spleen and liver were estimated based on MRI and CT data using a volume-analysis software and a postmortem tissue-specific density factor. In a blinded approach, the results were compared with the weights noted at autopsy. RESULTS: Excellent correlation between estimated and real weights (r = 0.997 for MRI, r = 0.997 for CT) was found. Putrefaction gas and venous air embolism led to an overestimation. Venous congestion and drowning caused higher estimated weights. CONCLUSION: Postmortem weights of liver and spleen can accurately be assessed by nondestructive imaging. Multislice CT overcomes the limitation of putrefaction and venous air embolism by the possibility to exclude gas. Congestion seems to be even better assessed.

Dental CT imaging as a screening tool for dental profiling: advantages and limitations

The use of dental processing software for computed tomography (CT) data (Dentascan) is described on postmortem (pm) CT data for the purpose of pm identification. The software allows reconstructing reformatted images comparable to conventional panoramic dental radiographs by defining a curved reconstruction line along the teeth on oblique images. Three corpses that have been scanned within the virtopsy project were used to test the software for the purpose of dental identification. In every case, dental panoramic images could be reconstructed and compared to antemortem radiographs. The images showed the basic component of teeth (enamel, dentin, and pulp), the anatomic structure of the alveolar bone, missing or unerupted teeth as well as restorations of the teeth that could be used for identification. When streak artifacts due to metal-containing dental work reduced image quality, it was still necessary to perform pm conventional radiographs for comparison of the detailed shape of the restoration. Dental identification or a dental profiling seems to become possible in a noninvasive manner using the Dentascan software.

Accuracy of magnetic resonance imaging for the diagnosis of multiple sclerosis: systematic review

OBJECTIVE: To determine the accuracy of magnetic resonance imaging criteria for the early diagnosis of multiple sclerosis in patients with suspected disease. DESIGN: Systematic review. DATA SOURCES: 12 electronic databases, citation searches, and reference lists of included studies. Review methods Studies on accuracy of diagnosis that compared magnetic resonance imaging, or diagnostic criteria incorporating such imaging, to a reference standard for the diagnosis of multiple sclerosis. RESULTS: 29 studies (18 cohort studies, 11 other designs) were included. On average, studies of other designs (mainly diagnostic case-control studies) produced higher estimated diagnostic odds ratios than did cohort studies. Among 15 studies of higher methodological quality (cohort design, clinical follow-up as reference standard), those with longer follow-up produced higher estimates of specificity and lower estimates of sensitivity. Only two such studies followed patients for more than 10 years. Even in the presence of many lesions (> 10 or > 8), magnetic resonance imaging could not accurately rule multiple sclerosis in (likelihood ratio of a positive test result 3.0 and 2.0, respectively). Similarly, the absence of lesions was of limited utility in ruling out a diagnosis of multiple sclerosis (likelihood ratio of a negative test result 0.1 and 0.5). CONCLUSIONS: Many evaluations of the accuracy of magnetic resonance imaging for the early detection of multiple sclerosis have produced inflated estimates of test performance owing to methodological weaknesses. Use of magnetic resonance imaging to confirm multiple sclerosis on the basis of a single attack of neurological dysfunction may lead to over-diagnosis and over-treatment.

A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

A multivariate approach for processing magnetization effects in triggered event-related functional magnetic resonance imaging time series

Triggered event-related functional magnetic resonance imaging requires sparse intervals of temporally resolved functional data acquisitions, whose initiation corresponds to the occurrence of an event, typically an epileptic spike in the electroencephalographic trace. However, conventional fMRI time series are greatly affected by non-steady-state magnetization effects, which obscure initial blood oxygen level-dependent (BOLD) signals. Here, conventional echo-planar imaging and a post-processing solution based on principal component analysis were employed to remove the dominant eigenimages of the time series, to filter out the global signal changes induced by magnetization decay and to recover BOLD signals starting with the first functional volume. This approach was compared with a physical solution using radiofrequency preparation, which nullifies magnetization effects. As an application of the method, the detectability of the initial transient BOLD response in the auditory cortex, which is elicited by the onset of acoustic scanner noise, was used to demonstrate that post-processing-based removal of magnetization effects allows to detect brain activity patterns identical with those obtained using the radiofrequency preparation. Using the auditory responses as an ideal experimental model of triggered brain activity, our results suggest that reducing the initial magnetization effects by removing a few principal components from fMRI data may be potentially useful in the analysis of triggered event-related echo-planar time series. The implications of this study are discussed with special caution to remaining technical limitations and the additional neurophysiological issues of the triggered acquisition.

Grey-matter abnormalities in boys with Tourette syndrome: magnetic resonance imaging study using optimised voxel-based morphometry

The genesis of Tourette syndrome is still unknown, but a core role for the pathways of cortico-striatal-thalamic-cortical circuitry (CSTC) is supposed. Volume-rendering magnetic resonance imaging data-sets were analysed in 14 boys with Tourette syndrome and 15 age-matched controls using optimised voxel-based morphometry. Locally increased grey-matter volumes (corrected P < 0.001) were found bilaterally in the ventral putamen. Regional decreases in grey matter were observed in the left hippocampal gyrus. This unbiased analysis confirmed an association between striatal abnormalities and Tourette syndrome, and the hippocampal volume alterations indicate an involvement of temporolimbic pathways of the CSTC in the syndrome.

[The importance of clinical information in diagnostic imaging in the febrile patient]

From conventional radiography to cross-sectional imaging methods, modern radiology offers a wide range of diagnostic tools for investigating patients with fever. To achieve the best results and to yield a correct diagnosis, the radiologist must tailor the diagnostic protocol individually for every patient. The decision on the most suitable imaging method, and the type and timing of contrast media strongly depends on the suspected diagnosis. Based on patient history and laboratory data, some modalities may be contraindicated or the patient may need a premedication. The authors give a short overview of diagnostic strategies in evaluating the most important causes of fever and point to the need of discussion and co-operation between clinicians and radiologists.

Quantitative magnetic resonance imaging of enzymatically induced degradation of the nucleus pulposus of intervertebral discs

STUDY DESIGN: The structural integrity of the nucleus pulposus (NP) of intervertebral discs was targeted by enzyme-specific degradations to correlate their effects to the magnetic resonance (MR) signal. OBJECTIVE: To develop quantitative MR imaging as an accurate and noninvasive diagnostic tool to better understand and treat disc degeneration. SUMMARY OF BACKGROUND DATA: Quantitative MR analysis has been previously shown to reflect not only the disc matrix composition, but also the structural integrity of the disc matrix. Further work is required to identify the contribution of the structural integrity versus the matrix composition to the MR signal. METHODS: The bovine coccygeal NPs were injected with either enzyme or buffer, incubated at 37 degrees C as static, unloaded and closed 3-disc segments, and analyzed by a 1.5-Tesla MR scanner to measure MR parameters. RESULTS: Collagenase degradation of the NP significantly decreased the relaxation times, slightly decreased the magnetization transfer ratio, and slightly increased the apparent diffusion coefficient. Targeting the proteoglycan and/or hyaluronan integrity by trypsin and hyaluronidase did not significantly affect the MR parameters, except for an increase in the apparent diffusion coefficient of the disc after trypsin treatment. CONCLUSIONS: Our results demonstrate that changes in the structural integrity of matrix proteins can be assessed by quantitative MR.

Application of 3D documentation and geometric reconstruction methods in traffic accident analysis: with high resolution surface scanning, radiological MSCT/MRI scanning and real data based animation

The examination of traffic accidents is daily routine in forensic medicine. An important question in the analysis of the victims of traffic accidents, for example in collisions between motor vehicles and pedestrians or cyclists, is the situation of the impact. Apart from forensic medical examinations (external examination and autopsy), three-dimensional technologies and methods are gaining importance in forensic investigations. Besides the post-mortem multi-slice computed tomography (MSCT) and magnetic resonance imaging (MRI) for the documentation and analysis of internal findings, highly precise 3D surface scanning is employed for the documentation of the external body findings and of injury-inflicting instruments. The correlation of injuries of the body to the injury-inflicting object and the accident mechanism are of great importance. The applied methods include documentation of the external and internal body and the involved vehicles and inflicting tools as well as the analysis of the acquired data. The body surface and the accident vehicles with their damages were digitized by 3D surface scanning. For the internal findings of the body, post-mortem MSCT and MRI were used. The analysis included the processing of the obtained data to 3D models, determination of the driving direction of the vehicle, correlation of injuries to the vehicle damages, geometric determination of the impact situation and evaluation of further findings of the accident. In the following article, the benefits of the 3D documentation and computer-assisted, drawn-to-scale 3D comparisons of the relevant injuries with the damages to the vehicle in the analysis of the course of accidents, especially with regard to the impact situation, are shown on two examined cases.

FUNCTIONAL PRINCIPAL COMPONENTS MODEL FOR HIGH-DIMENSIONAL BRAIN IMAGING

We establish a fundamental equivalence between singular value decomposition (SVD) and functional principal components analysis (FPCA) models. The constructive relationship allows to deploy the numerical efficiency of SVD to fully estimate the components of FPCA, even for extremely high-dimensional functional objects, such as brain images. As an example, a functional mixed effect model is fitted to high-resolution morphometric (RAVENS) images. The main directions of morphometric variation in brain volumes are identified and discussed.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

A CASE STUDY IN PHARMACOLOGIC IMAGING USING PRINCIPAL CURVES IN SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY

In this manuscript we are concerned with functional imaging of the colon to assess the kinetics of a microbicide lubricant. The overarching goal is to understand the distribution of the lubricant in the colon. Such information is crucial for understanding the potential impact of the microbicide on HIV viral transmission. The experiment was conducted by imaging a radiolabeled lubricant distributed in the subject’s colon. The tracer imaging was conducted via single photon emission computed tomography (SPECT), a non-invasive, in-vivo functional imaging technique. We develop a novel principal curve algorithm to construct a three dimensional curve through the colon images. The developed algorithm is tested and debugged on several difficult two dimensional images of familiar curves where the original principal curve algorithm does not apply. The final curve fit to the colon data is compared with experimental sigmoidoscope collection.