MRS measured fatty acid composition of periprostatic adipose tissue correlates with pathological measures of prostate cancer aggressiveness.

PURPOSE: To investigate the association between magnetic resonance (MR) spectroscopically measured fatty acid composition of periprostatic adipose tissue and pathological markers of prostate cancer aggressiveness. MATERIALS AND METHODS: Periprostatic adipose (PPA) and subcutaneous adipose (SQA) tissue from prostate cancer patients undergoing radical prostatectomy were examined ex vivo by proton MR spectroscopy at 14.1T (n = 31). Fractions of monounsaturated, polyunsaturated, total unsaturated, and saturated fatty acids, as well as T2 relaxation times were measured from the spectra. Univariate and multivariate analyses based on receiver operating characteristic (ROC) and support vector machines (SVM) were used to evaluate the association between differential measures of fatty acid levels in the PPA and SQA tissues and Gleason score and extracapsular extension (ECE), which are pathological measures of prostate cancer aggressiveness. RESULTS: Both pathological markers for aggressive prostate cancer have separable patterns in the MRS features space. The association between ECE and PPA tissue fatty acid composition is linear (area under receiver operating characteristic curve (AROC) and 95% confidence intervals [CIs]: 1.00, [1.00, 1.00]), along the Δ(fM /fS ) measure, and is marked by elevated monounsaturated and reduced saturated fatty acids in the PPA tissue relative to SQA. In contrast, the association between Gleason score and PPA tissue fatty acid composition is nonlinear (classifier AROC and 95% CIs: 0.86, [0.71, 1.00]). CONCLUSION: Fatty acid composition is altered in the PPA tissue of patients with aggressive prostate cancer. Ex vivo MR spectroscopy may be a useful tool in studying the altered fatty acid metabolism in prostate cancer.

Volume effect of localized injection in functional MRI and electrophysiology.

PURPOSE: The local injection of neurotransmitter agonists and antagonists to modulate recorded neurons in awake animals has long been an important and widely used technique in neuroscience. Combined with functional magnetic resonance imaging (fMRI) and simultaneous electrophysiology, local injection enables the study of specific brain regions under precise modulations of their neuronal activity. However, localized injections are often accompanied by mechanical displacement of the tissue, known as volume effect (VE), which can induce changes in electrophysiological recordings as well as artifacts that are particular to fMRI studies. METHODS: We characterize the changes produced by VE in an agarose phantom as well as during stimulus-evoked and resting-state fMRI and simultaneously acquired electrophysiology in awake rabbits. RESULTS: Our results demonstrate that localized injection can produce significant intensity changes in fMRI data, even while effects on electrophysiological recordings are minimized. These changes are localized to the vicinity of the injection needle and diminish over time due to diffusion of the injected volume. CONCLUSION: Sufficient time should be allowed for drug diffusion to ensure stable results, particularly for resting-state fMRI experiments.

Automatic segmentation of amyloid plaques in MR images using unsupervised support vector machines.

Deposition of the ß-amyloid peptide (Aß) is an important pathological hallmark of Alzheimer's disease (AD). However, reliable quantification of amyloid plaques in both human and animal brains remains a challenge. We present here a novel automatic plaque segmentation algorithm based on the intrinsic MR signal characteristics of plaques. This algorithm identifies plaque candidates in MR data by using watershed transform, which extracts regions with low intensities completely surrounded by higher intensity neighbors. These candidates are classified as plaque or nonplaque by an unsupervised learning method using features derived from the MR data intensity. The algorithm performance is validated by comparison with histology. We also demonstrate the algorithm's ability to detect age-related changes in plaque load ex vivo in amyloid precursor protein (APP) transgenic mice that coexpress five familial AD mutations (5xFAD mice). To our knowledge, this study represents the first quantitative method for characterizing amyloid plaques in MRI data. The proposed method can be used to describe the spatiotemporal progression of amyloid deposition, which is necessary for understanding the evolution of plaque pathology in mouse models of Alzheimer's disease and to evaluate the efficacy of emergent amyloid-targeting therapies in preclinical trials.

Visualization of mouse pancreas architecture using MR microscopy.

Pancreatic diseases, which include diabetes, pancreatitis, and pancreatic cancer, are often difficult to detect and/or stage, contributing to a reduced quality of life and lifespan for patients. Thus, there is need for a technology that can visualize tissue changes in the pancreas, improve understanding of disease progression, and facilitate earlier detection in the human population. Because of low spatial resolution, current clinical magnetic resonance imaging (MRI) at low field strength has yet to fully visualize the exocrine, endocrine, vascular, and stromal components of the pancreas. We used high field strength magnetic resonance microscopy (µMRI) to image mouse pancreas ex vivo without contrast agents at high spatial resolution. We analyzed the resulting high-resolution images using volume rendering to resolve components in the pancreas, including acini, islets, blood vessels, and extracellular matrix. Locations and dimensions of pancreatic components as seen in three-dimensional µMRI were compared with histological images, and good correspondence was found. Future longitudinal studies could expand on the use of in vivo µMRI in mouse models of pancreatic diseases. Capturing three-dimensional structural changes through µMRI could help to identify early cellular and tissue changes associated with pancreatic disease, serving as a mode of improved detection in the clinic for endocrine and exocrine pathologies.

Functional magnetic resonance imaging of delay and trace eyeblink conditioning in the primary visual cortex of the rabbit.

The primary sensory cortices have been shown in recent years to undergo experience- and learning-related plasticity under a variety of experimental circumstances. In this study, we used functional magnetic resonance imaging (fMRI) in parallel with both delay and trace eyeblink conditioning to image the learning-related functional activation within the primary visual cortex (V1) of awake, behaving rabbits. We expected that the differing level of forebrain dependence between these two conditioning paradigms should produce a differential blood oxygenation level-dependent (BOLD) functional response in V1. Our results showed a significant expansion of activated volume within V1, particularly early in learning, after training with the more cognitively demanding trace paradigm. In contrast, the simpler delay paradigm produced an increase in the magnitude of the BOLD response in activated voxels, but no significant change in activated volume. No accompanying learning-related changes were observed in the primary somatosensory cortex, which mediates the unconditioned stimulus. These results suggest that the recruitment of additional neurons within V1 is necessary to support the more demanding memory imposed by the trace interval. To our knowledge, this work is the first functional imaging study to compare directly trace and delay eyeblink conditioning in an animal model.

Automated seed placement for colon segmentation in computed tomography colonography.

RATIONALE AND OBJECTIVE: To present an algorithm to automatically locate seeds for colon segmentation in computed tomography colonography (CTC). MATERIALS AND METHODS: The algorithm automatically locates two points (seeds) inside the colon lumen. Because of their high distention and fixed anatomic position, we focus on the cecum and rectum for automatic seed placement. We use two-dimensional morphological operators that find pockets of colonic air of sufficient size. For the rectum, we search within an inferiorly and centrally located CT slice. For the cecum, we search in a group of CT slices in the middle of the scanned volume on the patient's right side. We applied our automated algorithm to segment the colon in 292 consecutive cases of CTC (146 prone, 146 supine). RESULTS: After automated seed placement, 83.2% (243 of 292) of the colons were segmented completely and 9.6% (28 of 292) were segmented partially. The unsegmented colon parts were present in datasets where the colon was collapsed in more than one place or because seeds could not be placed in regions filled with fluid. In the remaining 7.2% (21 of 292) of cases, the automatic segmentation leaked outside the colon because of a limitation of the contrast-enhanced fluid detection algorithm. CONCLUSION: Fully automatic seed placement for colonic segmentation is feasible in the majority of cases without seeding of undesired extracolonic air.

Effects of anesthesia on BOLD signal and neuronal activity in the somatosensory cortex.

Most functional magnetic resonance imaging (fMRI) animal studies rely on anesthesia, which can induce a variety of drug-dependent physiological changes, including depression of neuronal activity and cerebral metabolism as well as direct effects on the vasculature. The goal of this study was to characterize the effects of anesthesia on the BOLD signal and neuronal activity. Simultaneous fMRI and electrophysiology were used to measure changes in single units (SU), multi-unit activity (MUA), local field potentials (LFP), and the blood oxygenation level-dependent (BOLD) response in the somatosensory cortex during whisker stimulation of rabbits before, during and after anesthesia with fentanyl or isoflurane. Our results indicate that anesthesia modulates the BOLD signal as well as both baseline and stimulus-evoked neuronal activity, and, most significantly, that the relationship between the BOLD and electrophysiological signals depends on the type of anesthetic. Specifically, the behavior of LFP observed under isoflurane did not parallel the behavior of BOLD, SU, or MUA. These findings suggest that the relationship between these signals may not be straightforward. BOLD may scale more closely with the best measure of the excitatory subcomponents of the underlying neuronal activity, which may vary according to experimental conditions that alter the excitatory/inhibitory balance in the cortex.

Automated centerline for computed tomography colonography.

RATIONALE AND OBJECTIVES: A novel method to compute the centerline of the human colon obtained from computed tomography colonography is proposed. Two applications of this method are demonstrated: to compute local colonic distension (caliber), and to match polyps on supine and prone images. MATERIALS AND METHODS: The centerline algorithm involves multiple steps including simplification of the colonic surface by decimation; thinning of the decimated colon to create a preliminary centerline; selection of equally spaced points on the preliminary centerline; grouping neighboring points; and mapping them back to rings in the original colon. This method was tested on 20 human computed tomography colonography datasets (supine and prone examinations of 10 patients) and on a computer-generated colon phantom. RESULTS: Visual inspection of the colons and their centerlines showed the centerline to be accurate. For the colon phantom, the average error was only 1 mm. For 11 polyps visualized in both the supine and prone positions and found by computer-aided detection, the normalized distance along the centerline to each polyp was not significantly different on the supine and prone views (r = 0.999; P < .001). CONCLUSION: This method produces an accurate colon centerline that may be useful for flight path planning, matching detections on the supine and prone views, and computing local colonic distension.