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Background: Fruit has since long been advocated as a healthy source of many nutrients, however, the high content of sugars in fruit might be a concern., Objectives: To study effects of an increased fruit intake compared with similar amount of extra calories from nuts in humans., Methods: Thirty healthy non-obese participants were randomized to either supplement the diet with fruits or nuts, each at +7 kcal/kg bodyweight/day for two months. Major endpoints were change of hepatic fat content (HFC, by magnetic resonance imaging, MRI), basal metabolic rate (BMR, with indirect calorimetry) and cardiovascular risk markers., Results: Weight gain was numerically similar in both groups although only statistically significant in the group randomized to nuts (fruit: from 22.15 ± 1.61 kg/m(2) to 22.30 ± 1.7 kg/m(2), p = 0.24 nuts: from 22.54 ± 2.26 kg/m(2) to 22.73 ± 2.28 kg/m(2), p = 0.045). On the other hand BMR increased in the nut group only (p = 0.028). Only the nut group reported a net increase of calories (from 2519 ± 721 kcal/day to 2763 ± 595 kcal/day, p = 0.035) according to 3-day food registrations. Despite an almost three-fold reported increased fructose-intake in the fruit group (from 9.1 ± 6.0 gram/day to 25.6 ± 9.6 gram/day, p<0.0001, nuts: from 12.4 ± 5.7 gram/day to 6.5 ± 5.3 gram/day, p = 0.007) there was no change of HFC. The numerical increase in fasting insulin was statistically significant only in the fruit group (from 7.73±3.1 mIE/L to 8.81±2.9 mIE/L, p = 0.018, nuts: from 7.29±2.9 mIE/L to 8.62±3.0 mIE/L, p = 0.14). Levels of vitamin C increased in both groups while α-tocopherol/cholesterol-ratio increased only in the fruit group., Conclusions: Although BMR increased in the nut-group only this was not linked with differences in weight gain between groups which potentially could be explained by the lack of reported net caloric increase in the fruit group. In healthy non-obese individuals an increased fruit intake seems safe from cardiovascular risk perspective, including measurement of HFC by MRI., Trial Registration: ClinicalTrials.gov NCT02227511.

Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such as MRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat-muscle quantitation system (AMRA(TM) Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRA(TM) Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRA(TM) Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRA(TM) Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variation was 1.4% for IAAT and 1.2% for ASAT, the intra-observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRA(TM) Profiler, opening up the possibility of large-scale human phenotypic studies., (Copyright © 2015 John Wiley & Sons, Ltd.)

Background: To evaluate the possibility of quantifying brown adipose tissue (BAT) volume and fat concentration with a high resolution, long echo time, dual-echo Dixon imaging protocol., Methods: A 0.42 mm isotropic resolution water-fat separated MRI protocol was implemented by using the second opposite-phase echo and third in-phase echo. Fat images were calibrated with regard to the intensity of nearby white adipose tissue (WAT) to form relative fat content (RFC) images. To evaluate the ability to measure BAT volume and RFC contrast dynamics, rats were divided into two groups that were kept at 4° or 22°C for 5 days. The rats were then scanned in a 70 cm bore 3.0 Tesla MRI scanner and a human dual energy CT. Interscapular, paraaortal, and perirenal BAT (i/pa/pr-BAT) depots as well as WAT and muscle were segmented in the MRI and CT images. Biopsies were collected from the identified BAT depots., Results: The biopsies confirmed that the three depots identified with the RFC images consisted of BAT. There was a significant linear correlation (P < 0.001) between the measured RFC and the Hounsfield units from DECT. Significantly lower iBAT RFC (P = 0.0064) and significantly larger iBAT and prBAT volumes (P = 0.0017) were observed in the cold stimulated rats., Conclusion: The calibrated Dixon images with RFC scaling can depict BAT and be used to measure differences in volume, and fat concentration, induced by cold stimulation. The high correlation between RFC and HU suggests that the fat concentration is the main RFC image contrast mechanism., (© 2015 Wiley Periodicals, Inc.)

Purpose: To quantitatively and qualitatively evaluate the water-signal performance of the consistent intensity inhomogeneity correction (CIIC) method to correct for intensity inhomogeneities, Methods: Water-fat volumes were acquired using 1.5 Tesla (T) and 3.0T symmetrically sampled 2-point Dixon three-dimensional MRI. Two datasets: (i) 10 muscle tissue regions of interest (ROIs) from 10 subjects acquired with both 1.5T and 3.0T whole-body MRI. (ii) Seven liver tissue ROIs from 36 patients imaged using 1.5T MRI at six time points after Gd-EOB-DTPA injection. The performance of CIIC was evaluated quantitatively by analyzing its impact on the dispersion and bias of the water image ROI intensities, and qualitatively using side-by-side image comparisons., Results: CIIC significantly ( P1.5T≤2.3×10-4,P3.0T≤1.0×10-6) decreased the nonphysiological intensity variance while preserving the average intensity levels. The side-by-side comparisons showed improved intensity consistency ( Pint⁡≤10-6) while not introducing artifacts ( Part=0.024) nor changed appearances ( Papp≤10-6)., Conclusion: CIIC improves the spatiotemporal intensity consistency in regions of a homogenous tissue type., (© 2014 Wiley Periodicals, Inc.)

This paper presents a novel method for discrimination between innocent and pathological murmurs using the growing time support vector machine (GTSVM). The proposed method is tailored for characterizing innocent murmurs (IM) by putting more emphasis on the early parts of the signal as IMs are often heard in early systolic phase. Individuals with mild to severe aortic stenosis (AS) and IM are the two groups subjected to analysis, taking the normal individuals with no murmur (NM) as the control group. The AS is selected due to the similarity of its murmur to IM, particularly in mild cases. To investigate the effect of the growing time windows, the performance of the GTSVM is compared to that of a conventional support vector machine (SVM), using repeated random sub-sampling method. The mean value of the classification rate/sensitivity is found to be 88%/86% for the GTSVM and 84%/83% for the SVM. The statistical evaluations show that the GTSVM significantly improves performance of the classification as compared to the SVM., (Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.)

Purpose: To develop and demonstrate a rapid whole-body magnetic resonance imaging (MRI) method for automatic quantification of total and regional skeletal muscle volume., Materials and Methods: The method was based on a multi-atlas segmentation of intensity corrected water-fat separated image volumes. Automatic lean muscle tissue segmentations were achieved by nonrigid registration of atlas datasets with 10 different manually segmented muscle groups. Ten subjects scanned at 1.5 T and 3.0 T were used as atlases, initial validation and optimization. Further validation used 11 subjects scanned at 3.0 T. The automated and manual segmentations were compared using intraclass correlation, true positive volume fractions, and delta volumes., Results: For the 1.5 T datasets, the intraclass correlation, true positive volume fractions (mean ± standard deviation, SD), and delta volumes (mean ± SD) were 0.99, 0.91 ± 0.02, -0.10 ± 0.70L (whole body), 0.99, 0.93 ± 0.02, 0.01 ± 0.07L (left anterior thigh), and 0.98, 0.80 ± 0.07, -0.08 ± 0.15L (left abdomen). The corresponding values at 3.0 T were 0.97, 0.92 ± 0.03, -0.17 ± 1.37L (whole body), 0.99, 0.93 ± 0.03, 0.03 ± 0.08L (left anterior thigh), and 0.89, 0.90 ± 0.04, -0.03 ± 0.42L (left abdomen). The validation datasets showed similar results., Conclusion: The method accurately quantified the whole-body skeletal muscle volume and the volume of separate muscle groups independent of field strength and image resolution., (© 2014 Wiley Periodicals, Inc.)

Purpose: To measure the test-retest reproducibility of an automated system for quantifying whole body and compartmental muscle volumes using wide bore 3 T MRI., Materials and Methods: Thirty volunteers stratified by body mass index underwent whole body 3 T MRI, two-point Dixon sequences, on two separate occasions. Water-fat separation was performed, with automated segmentation of whole body, torso, upper and lower leg volumes, and manually segmented lower leg muscle volumes., Results: Mean automated total body muscle volume was 19·32 L (SD9·1) and 19·28 L (SD9·12) for first and second acquisitions (Intraclass correlation coefficient (ICC) = 1·0, 95% level of agreement -0·32-0·2 L). ICC for all automated test-retest muscle volumes were almost perfect (0·99-1·0) with 95% levels of agreement 1.8-6.6% of mean volume. Automated muscle volume measurements correlate closely with manual quantification (right lower leg: manual 1·68 L (2SD0·6) compared to automated 1·64 L (2SD 0·6), left lower leg: manual 1·69 L (2SD 0·64) compared to automated 1·63 L (SD0·61), correlation coefficients for automated and manual segmentation were 0·94-0·96)., Conclusion: Fully automated whole body and compartmental muscle volume quantification can be achieved rapidly on a 3 T wide bore system with very low margins of error, excellent test-retest reliability and excellent correlation to manual segmentation in the lower leg., Key Points: Sarcopaenia is an important reversible complication of a number of diseases. Manual quantification of muscle volume is time-consuming and expensive. Muscles can be imaged using in and out of phase MRI. Automated atlas-based segmentation can identify muscle groups. Automated muscle volume segmentation is reproducible and can replace manual measurements.

The development of MRI-visual order-disorder structures for cancer nanomedicine explores a pH-triggered mechanism for theragnosis of tumor hallmark functions. Superparamagnetic iron oxide nanoparticles (SPIONs) stabilized with amphiphilic poly(styrene)-b-poly(acrylic acid)-doxorubicin with folic acid (FA) surfacing are employed as a multi-functional approach to specifically target, diagnose, and deliver drugs via a single nanoscopic platform for cancer therapy. The functional aspects of the micellar nanocomposite is investigated in vitro using human breast SkBr3 and colon cancer HCT116 cell lines for the delivery, release, localization, and anticancer activity of the drug. For the first time, concentration-dependent T2 -weighted MRI contrast for a monolayer of clustered cancer cells is shown. The pH tunable order-disorder transition of the core-shell structure induces the relative changes in MRI contrast. The outcomes elucidate the potential of this material for smart cancer theranostics by delivering non-invasive real-time diagnosis, targeted therapy, and monitoring the course and response of the action before, during, and after the treatment regimen., (© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

If the beneficial effects of brown adipose tissue (BAT) on whole body metabolism, as observed in nonhuman experimental models, are to be translated to humans, tools that accurately measure how BAT influences human metabolism will be required. This chapter discusses such techniques, how they can be used, what they can measure and also some of their limitations. The focus is on detection and functional analysis of human BAT and how this can be facilitated by applying advanced imaging technology such as positron emission tomography, magnetic resonance imaging, and dual energy computed tomography., (© 2014 Elsevier Inc. All rights reserved.)

The mastoid air cell system has traditionally been considered to have a passive role in gas exchange and pressure regulation of the middle ear possibly with some acoustic function. However, more evidence has focused on the mucosa of the mastoid, which may play a more active role in regulation of middle ear pressure. In this study we have applied micro-CT scanning on a series of three human temporal bones. This approach greatly enhances the resolution (40-60 μm), so that we have discovered anatomical details, which has not been reported earlier. Thus, qualitative analysis using volume rendering has demonstrated notable micro-channels connecting the surface of the compact bone directly to the mastoid air cells as well as forming a network of connections between the air cells. Quantitative analysis on 2D slices was employed to determine the average diameter of these micro-channels (158 μm; range = 40-440 μm) as well as their density at a localized area (average = 75 cm(-2); range = 64-97 cm(-2)). These channels are hypothesized to contain a separate vascular supply for the mastoid mucosa. However, future studies of the histological structure of the micro-channels are warranted to confirm the hypothesis. Studies on the mastoid mucosa and its blood supply may improve our knowledge of its physiological properties, which may have important implications for our understanding of the pressure regulation of the middle ear. This article is part of a special issue entitled "MEMRO 2012"., (Copyright © 2013 Elsevier B.V. All rights reserved.)

The previously observed supraclavicular depot of brown adipose tissue (BAT) in adult humans was commonly believed to be the equivalent of the interscapular thermogenic organ of small mammals. This view was recently disputed on the basis of the demonstration that this depot consists of beige (also called brite) brown adipocytes, a newly identified type of brown adipocyte that is distinct from the classical brown adipocytes that make up the interscapular thermogenic organs of other mammals. A combination of high-resolution imaging techniques and histological and biochemical analyses showed evidence for an anatomically distinguishable interscapular BAT (iBAT) depot in human infants that consists of classical brown adipocytes, a cell type that has so far not been shown to exist in humans. On the basis of these findings, we conclude that infants, similarly to rodents, have the bona fide iBAT thermogenic organ consisting of classical brown adipocytes that is essential for the survival of small mammals in a cold environment.

Computed Tomography Angiography (CTA) is commonly used in clinical routine for diagnosing vascular diseases. The procedure involves the injection of a contrast agent into the blood stream to increase the contrast between the blood vessels and the surrounding tissue in the image data. CTA is often visualized with Direct Volume Rendering (DVR) where the enhanced image contrast is important for the construction of Transfer Functions (TFs). For increased efficiency, clinical routine heavily relies on preset TFs to simplify the creation of such visualizations for a physician. In practice, however, TF presets often do not yield optimal images due to variations in mixture concentration of contrast agent in the blood stream. In this paper we propose an automatic, optimization-based method that shifts TF presets to account for general deviations and local variations of the intensity of contrast enhanced blood vessels. Some of the advantages of this method are the following. It computationally automates large parts of a process that is currently performed manually. It performs the TF shift locally and can thus optimize larger portions of the image than is possible with manual interaction. The method is based on a well known vesselness descriptor in the definition of the optimization criterion. The performance of the method is illustrated by clinically relevant CT angiography datasets displaying both improved structural overviews of vessel trees and improved adaption to local variations of contrast concentration.

Background: An earlier study from our group of long time survivors of head and neck cancer who had received a low radiation dose to the hypothalamic-pituitary region, with no signs of recurrence or pituitary dysfunction, had their quality of life (QoL) compromised as compared with matched healthy controls. Hippocampal changes have been shown to accompany several psychiatric conditions and the aim of the present study was to test whether the patients' lowered QoL was coupled to a reduction in hippocampal volume., Methods: Patients (11 men and 4 women, age 31-65) treated for head and neck cancer 4-10 years earlier and with no sign of recurrence or pituitary dysfunction, and 15 matched controls were included. The estimated radiation doses to the basal brain including the hippocampus (1.5 - 9.3 Gy) had been calculated in the earlier study. The hippocampal volumetry was done on coronal sections from a 1.5 T MRI scanner. Measurements were done by two independent raters, blinded to patients and controls, using a custom method for computer assisted manual segmentation. The volumes were normalized for intracranial volume which was also measured manually. The paired t test and Wilcoxon's signed rank test were used for the main statistical analysis., Results: There was no significant difference with respect to left, right or total hippocampal volume between patients and controls. All mean differences were close to zero, and the two-tailed 95% confidence interval for the difference in total, normalized volume does not include a larger than 8% deficit in the patients., Conclusion: The study gives solid evidence against the hypothesis that the patients' lowered quality of life was due to a major reduction of hippocampal volume.

Purpose: The mean intercept length tensor is the most used technique to estimate microstructure orientation and anisotropy of trabecular bone. This paper proposes an efficient extension of this technique to gray-scale images based on a closed formulation of the mean intercept length tensor and a generalization using different angular convolution kernels., Methods: First, the extended Gaussian image is computed for the binary or gray-scale image. Second, the intercepts are computed for all possible orientations through an angular convolution with the half-cosine function. Finally, the tensor is computed by means of the covariance matrix. The complexity of the method is O(n + m) in contrast with O(nm) of traditional implementations, where n is the number of voxels in the image and m is the number of orientations used in the computations. The method is generalized by applying other angular convolution kernels instead of the half-cosine function. As a result, the anisotropy of the tensor can be controlled while keeping the eigenvectors intact., Results: The proposed extension to gray-scale yields accurate results for reliable computations of the extended Gaussian image and, unlike the traditional methodology, is not affected by artifacts generated by discretizations during the sampling of different orientations., Conclusions: Experiments show that the computations on both binary and gray-scale images are correlated, and that computations in gray-scale are more robust, enabling the use of the mean intercept length tensor to clinical examinations of trabecular bone. The use of kernels based on the von Mises-Fisher distribution is promising as the anisotropy can be adjusted with a parameter in order to improve its power to predict mechanical properties of trabecular bone.

Objective: Increase of resistin and/or reduction of adiponectin have been implicated in the development of insulin resistance following weight gain. We aimed to study this prospectively in humans., Design: Prospective and interventional with parallel control group., Methods: Twelve healthy men and six healthy women (age 26 ± 6.6 years) and an age-matched control group were recruited. Subjects in the intervention group aimed for a bodyweight increase of 5-15% by doubling the baseline caloric intake by eating at least two fast food-based meals a day in combination with adoption of a sedentary lifestyle for 4 weeks., Results: Bodyweight increased from 67.6 ± 9.1 to 74.0 ± 11 kg, P<0.001, by the intervention. Insulin levels increased (before: 27.4 ± 12 pmol/l, after: 53.0 ± 22 pmol/l, P=0.004), while plasma levels of adiponectin (before: 5038 ± 3736 ng/ml, after: 6739 ± 7949 ng/ml, P=0.18) and resistin (before: 21.8 ± 19 ng/ml, after: 14.4 ± 6.8 ng/ml, P=0.074) remained unchanged by the weight gain and were similar as in controls. On the other hand, leptin levels increased about threefold following the intervention (before: 5.7 ± 7.4, after: 16 ± 20 ng/ml, P=0.008), and also the inflammatory marker C-reactive protein (CRP) increased from 0.34 ± 0.44 to 0.71 ± 0.87 mg/l, P=0.03, when two outliers >10 mg/l were disregarded., Conclusions: Hyperalimentation reduces insulin sensitivity when weight gain of 9% was combined with reduction of exercise. However, the levels of resistin and adiponectin were unaffected by the intervention, while CRP levels increased within this short time period suggesting that low-grade inflammation can occur early in the process of developing a metabolic syndrome.

We prospectively studied the effects of fast food-based hyperalimentation on insulin sensitivity and components of the metabolic syndrome and analyzed this with respect to sex. Twelve nonobese men and 6 nonobese women (26 +/- 6.6 years old), and an age-matched control group were recruited. Subjects in the intervention group aimed for 5% to 15% weight increase by doubling their regular caloric intake based on at least 2 fast food meals a day while also adopting a sedentary lifestyle for 4 weeks (<5000 steps a day). Weight of subjects in the intervention group increased from 67.6 +/- 9.1 to 74.0 +/- 11 kg (P < .001), with no sex difference with regard to this or with respect to changes of total abdominal fat volumes or waist circumferences. Fasting insulin (men: before, 3.8 +/- 1.7 microU/mL; after, 7.4 +/- 3.1 microU/mL; P = .004; women: before, 4.9 +/- 2.3 microU/mL; after, 5.9 +/- 2.8 microU/mL; P = .17), systolic blood pressure (men: before, 117 +/- 13 mm Hg; after, 127 +/- 9.1 mm Hg; P = .002; women: before, 102 +/- 5.1 mm Hg; after, 98 +/- 5.4 mm Hg; P = .39), serum low-density lipoprotein cholesterol, and apolipoprotein B increased only in the men of the intervention group. The sex differences in the metabolic responses to the intervention were linked to a considerable difference in the fat accumulation pattern; 41.4% +/- 9.2% of the increase of the fat volume in the abdominal region was accumulated intraabdominally in men and 22.7 +/- 6.5% in women (P < .0001). This study thus showed that women are protected, compared with men, against developing intraabdominal obesity when adopting a standardized obesity-provoking lifestyle. Our findings suggest that it is not different lifestyles and/or behaviors that underlie the fact that men have a higher cardiovascular risk at the same level of percentage of body fat than women.

This paper presents a novel method for phase unwrapping for phase sensitive reconstruction in MR imaging. The unwrapped phase is obtained by integrating the phase gradient by solving a Poisson equation. An efficient solver, which has been made publicly available, is used to solve the equation. The proposed method is demonstrated on a fat quantification MRI task that is a part of a prospective study of fat accumulation. The method is compared to a phase unwrapping method based on region growing. Results indicate that the proposed method provides more robust unwrapping. Unlike region growing methods, the proposed method is also straight-forward to implement in 3D.

Canonical correlation analysis (CCA) has previously been shown to work well for detecting neural activity in fMRI data. The reason is that CCA enables simultaneous temporal modeling and adaptive spatial filtering of the data. This article introduces a novel method for adaptive anisotropic filtering using the CCA framework and compares it to a previously proposed method. Isotropic adaptive filtering, which is only able to form isotropic filters of different sizes, is also presented and evaluated. It is shown that a new feature of the proposed method is invariance to the orientation of activated regions, and that the detection performance is superior to both that of the previous method and to isotropic filtering.

The use of surgical simulator systems for education and preoperative planning is likely to increase in the future. A natural course of development of these systems is to incorporate patient specific anatomical models. This step requires some kind of segmentation process in which the different anatomical parts are extracted. Anatomical datasets are, however, usually very large and manual processing would be too demanding. Hence, automatic, or semi-automatic, methods to handle this step are required. The framework presented in this paper uses nonrigid registration, based on the morphon method, to automatically segment the hip anatomy and generate models for a hip surgery simulator system.

Assessment of the association between risk factors and outcomes in cardiac surgery is a complex problem. The aim of this study was to explore the relationship between possible risk factors and several clinical outcomes in cardiac surgery by using canonical correlation analysis (CCA). This retrospective study of 2605 consecutive adult patients who underwent cardiac surgery, evaluated 74 potential risk factors and up to 12 outcomes by canonical correlation analysis. For three serious outcomes, sternal wound complications/mediastinitis, cerebral complications, and perioperative myocardial infarctions, CCA was preceded by univariate analyses and backward stepwise multivariate logistic regression analyses. The CCA suggests that the major risk factors for complications in these models are intraoperative and postoperative risk factors. The power of risk prediction models developed with multivariate regression analysis can be enhanced by application of canonical correlation analysis, thereby offering new ways of analyzing and interpreting sets of potential risk factors in relation to sets of clinical outcomes.

This article addresses the impact that colored noise, temporal filtering, and temporal detrending have on the fMRI analysis situation. Specifically, it is shown why the detection of event-related designs benefit more from pre-whitening than blocked designs in a colored noise structure. Both theoretical and empirical results are provided. Furthermore, a novel exploratory method for producing drift models that efficiently capture trends and drifts in the fMRI data is introduced. A comparison to currently employed detrending approaches is presented. It is shown that the novel exploratory model is able to remove a major part of the slowly varying drifts that are abundant in fMRI data. The value of such a model lies in its ability to remove drift components that otherwise would have contributed to a colored noise structure in the voxel time series.

This article introduces novel and fundamental improvements of fMRI data analysis. Central is a technique termed constrained canonical correlation analysis, which can be viewed as a natural extension and generalization of the popular general linear model method. The concept of spatial basis filters is presented and shown to be a very successful way of adaptively filtering the fMRI data. A general method for designing suitable hemodynamic response models is also proposed and incorporated into the constrained canonical correlation approach. Results that demonstrate how each of these parts significantly improves the detection of brain activity, with a computation time well within limits for practical use, are provided.

A novel and computationally efficient method for exploratory analysis of functional MRI data is presented. The basic idea is to reveal underlying components in the fMRI data that have maximum autocorrelation. The tool for accomplishing this task is Canonical Correlation Analysis. The relation to Principal Component Analysis and Independent Component Analysis is discussed and the performance of the methods is compared using both simulated and real data., (2002 Elsevier Science (USA))

A technique for detecting neural activity in functional MRI data is introduced. It is based on a novel framework termed maximum correlation modeling. The method employs a spatial filtering approach that adapts to the local activity patterns, which results in an improved detection sensitivity combined with good specificity. A spatially varying hemodynamic response is simultaneously modelled by a sum of two gamma functions. Comparisons to traditional analysis methods are made using both synthetic and real data. The results indicate that the maximum correlation modeling approach is a strong alternative for analyzing fMRI data.

A novel method for detecting neural activity in functional magnetic resonance imaging (fMRI) data is introduced. It is based on canonical correlation analysis (CCA), which is a multivariate extension of the univariate correlation analysis widely used in fMRI. To detect homogeneous regions of activity, the method combines a subspace modeling of the hemodynamic response and the use of spatial relationships. The spatial correlation that undoubtedly exists in fMR images is completely ignored when univariate methods such as as t-tests, F-tests, and ordinary correlation analysis are used. Such methods are for this reason very sensitive to noise, leading to difficulties in detecting activation and significant contributions of false activations. In addition, the proposed CCA method also makes it possible to detect activated brain regions based not only on thresholding a correlation coefficient, but also on physiological parameters such as temporal shape and delay of the hemodynamic response. Excellent performance on real fMRI data is demonstrated. Magn Reson Med 45:323-330, 2001., (Copyright 2001 Wiley-Liss, Inc.)

Phosphoinositides are localized in various intracellular compartments and can regulate a number of intracellular functions, such as cytoskeletal dynamics and membrane trafficking. Phospholipase Ds (PLDs) are regulated enzymes that hydrolyse phosphatidylcholine (PtdCho) to generate the putative second messenger phosphatidic acid (PtdOH). In vitro, PLDs have an absolute requirement for higher phosphorylated inositides, such as phosphatidylinositol 4,5-bisphosphate [PtdIns(4,5)P(2)]. Whether this lipid is able to regulate the activity of PLD in vivo is contentious. To examine this hypothesis we studied the relationship between PLD and an enzyme critical for the intracellular synthesis of PtdIns(4,5)P(2): phosphatidylinositol 4-phosphate 5-kinase alpha (Type Ialpha PIPkinase). We find that both PLD1 and PLD2 interact with the Type Ialpha PIPkinase and that PLD2 activity in vivo can be regulated solely by the expression of this lipid kinase. Moreover, PLD2 is able to recruit the Type Ialpha PIPkinase to its intracellular location. We show that the physiological requirement of PLD enzymes for PtdIns(4,5)P(2) is critical and that PLD2 activity can be regulated solely by the levels of this key intracellular lipid.