The Fusion of Wide Field Optical Coherence Tomography and AI: Advancing Breast Cancer Surgical Margin Visualization.

This study explores the integration of Wide Field Optical Coherence Tomography (WF-OCT) with an AI-driven clinical decision support system, with the goal of enhancing productivity and decision making in breast cancer surgery margin assessment. A computationally efficient convolutional neural network (CNN)-based binary classifier is developed using 585 WF-OCT margin scans from 151 subjects. The CNN model swiftly identifies suspicious areas within margins with an on-device inference time of approximately 10 ms for a 420 × 2400 image. In independent testing on 155 pathology-confirmed margins, including 31 positive margins from 29 patients, the classifier achieved an AUROC of 0.976, a sensitivity of 0.93, and a specificity of 0.98. At the margin level, the deep learning model accurately identified 96.8% of pathology-positive margins. These results highlight the clinical viability of AI-enhanced margin visualization using WF-OCT in breast cancer surgery and its potential to decrease reoperation rates due to residual tumors.

A Feasibility Study on Deep Learning Reconstruction to Improve Image Quality With PROPELLER Acquisition in the Setting of T2-Weighted Gynecologic Pelvic Magnetic Resonance Imaging.

OBJECTIVES: Evaluate deep learning (DL) to improve the image quality of the PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction technique) for 3 T magnetic resonance imaging of the female pelvis. METHODS: Three radiologists prospectively and independently compared non-DL and DL PROPELLER sequences from 20 patients with a history of gynecologic malignancy. Sequences with different noise reduction factors (DL 25%, DL 50%, and DL 75%) were blindly reviewed and scored based on artifacts, noise, relative sharpness, and overall image quality. The generalized estimating equation method was used to assess the effect of methods on the Likert scales. Quantitatively, the contrast-to-noise ratio and signal-to-noise ratio (SNR) of the iliac muscle were calculated, and pairwise comparisons were performed based on a linear mixed model. P values were adjusted using the Dunnett method. Interobserver agreement was assessed using the κ statistic. P value was considered statistically significant at less than 0.05. RESULTS: Qualitatively, DL 50 and DL 75 were ranked as the best sequences in 86% of cases. Images generated by the DL method were significantly better than non-DL images ( P < 0.0001). Iliacus muscle SNR on DL 50 and DL 75 was significantly better than non-DL images ( P < 0.0001). There was no difference in contrast-to-noise ratio between the DL and non-DL techniques in the iliac muscle. There was a high percent agreement (97.1%) in terms of DL sequences' superior image quality (97.1%) and sharpness (100%) relative to non-DL images. CONCLUSION: The utilization of DL reconstruction improves the image quality of PROPELLER sequences with improved SNR quantitatively.

Automated Placement of Scan and Pre-Scan Volumes for Breast MRI Using a Convolutional Neural Network.

Graphically prescribed patient-specific imaging volumes and local pre-scan volumes are routinely placed by MRI technologists to optimize image quality. However, manual placement of these volumes by MR technologists is time-consuming, tedious, and subject to intra- and inter-operator variability. Resolving these bottlenecks is critical with the rise in abbreviated breast MRI exams for screening purposes. This work proposes an automated approach for the placement of scan and pre-scan volumes for breast MRI. Anatomic 3-plane scout image series and associated scan volumes were retrospectively collected from 333 clinical breast exams acquired on 10 individual MRI scanners. Bilateral pre-scan volumes were also generated and reviewed in consensus by three MR physicists. A deep convolutional neural network was trained to predict both the scan and pre-scan volumes from the 3-plane scout images. The agreement between the network-predicted volumes and the clinical scan volumes or physicist-placed pre-scan volumes was evaluated using the intersection over union, the absolute distance between volume centers, and the difference in volume sizes. The scan volume model achieved a median 3D intersection over union of 0.69. The median error in scan volume location was 2.7 cm and the median size error was 2%. The median 3D intersection over union for the pre-scan placement was 0.68 with no significant difference in mean value between the left and right pre-scan volumes. The median error in the pre-scan volume location was 1.3 cm and the median size error was -2%. The average estimated uncertainty in positioning or volume size for both models ranged from 0.2 to 3.4 cm. Overall, this work demonstrates the feasibility of an automated approach for the placement of scan and pre-scan volumes based on a neural network model.

GRASPNET: Fast spatiotemporal deep learning reconstruction of golden-angle radial data for free-breathing dynamic contrast-enhanced magnetic resonance imaging.

The purpose of the current study was to develop a deep learning technique called Golden-angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic contrast-enhanced 4D MRI acquired with golden-angle radial k-space trajectories. GRASPnet operates in the image-time space and does not use explicit data consistency to minimize the reconstruction time. Three different network architectures were developed: (1) GRASPnet-2D: 2D convolutional kernels (x,y) and coil and contrast dimensions collapsed into a single combined dimension; (2) GRASPnet-3D: 3D kernels (x,y,t); and (3) GRASPnet-2D + time: two 3D kernels to first exploit spatial correlations (x,y,1) followed by temporal correlations (1,1,t). The networks were trained using iterative GRASP reconstruction as the reference. Free-breathing 3D abdominal imaging with contrast injection was performed on 33 patients with liver lesions using a T1-weighted golden-angle stack-of-stars pulse sequence. Ten datasets were used for testing. The three GRASPnet architectures were compared with iterative GRASP results using quantitative and qualitative analysis, including impressions from two body radiologists. The three GRASPnet techniques reduced the reconstruction time to about 13 s with similar results with respect to iterative GRASP. Among the GRASPnet techniques, GRASPnet-2D + time compared favorably in the quantitative analysis. Spatiotemporal deep learning enables reconstruction of dynamic 4D contrast-enhanced images in a few seconds, which would facilitate translation to clinical practice of compressed sensing methods that are currently limited by long reconstruction times.

Novel deep learning-based noise reduction technique for prostate magnetic resonance imaging.

INTRODUCTION: Magnetic resonance imaging (MRI) has played an increasingly major role in the evaluation of patients with prostate cancer, although prostate MRI presents several technical challenges. Newer techniques, such as deep learning (DL), have been applied to medical imaging, leading to improvements in image quality. Our goal is to evaluate the performance of a new deep learning-based reconstruction method, "DLR" in improving image quality and mitigating artifacts, which is now commercially available as AIRTM Recon DL (GE Healthcare, Waukesha, WI). We hypothesize that applying DLR to the T2WI images of the prostate provides improved image quality and reduced artifacts. METHODS: This study included 31 patients with a history of prostate cancer that had a multiparametric MRI of the prostate with an endorectal coil (ERC) at 1.5 T or 3.0 T. Four series of T2-weighted images were generated in total: one set with the ERC signal turned on (ERC) and another set with the ERC signal turned off (Non-ERC). Each of these sets then reconstructed using two different reconstruction methods: conventional reconstruction (Conv) and DL Recon (DLR): ERCDLR, ERCConv, Non-ERCDLR, and Non-ERCConv. Three radiologists independently reviewed and scored the four sets of images for (i) image quality, (ii) artifacts, and (iii) visualization of anatomical landmarks and tumor. RESULTS: The Non-ERCDLR scored as the best series for (i) overall image quality (p < 0.001), (ii) reduced artifacts (p < 0.001), and (iii) visualization of anatomical landmarks and tumor. CONCLUSION: Prostate imaging without the use of an endorectal coil could benefit from deep learning reconstruction as demonstrated with T2-weighted imaging MRI evaluations of the prostate.

Application of compressed sensing to 3D magnetic resonance cholangiopancreatography for the evaluation of pancreatic cystic lesions.

The aim of this study was to assess changes in acquisition time, image quality and evaluation of pancreatic cysts when applying CS to a 3D MRCP sequence. Thirty subjects (17F; 13M) undergoing MRCP for evaluation of pancreatic cyst(s) were prospectively recruited and underwent 3D MRCP and CS 3D MRCP (CS factor = 2) on a 3T scanner. The acquisition time was recorded. Two experienced radiologists independently recorded quality of the images, presence of artifacts, visualization of the main pancreatic duct, bile ducts and index pancreatic cyst using a five-point scale. Presence of mural nodules and septations in the cyst, size of the cyst and caliber of the main pancreatic duct were also recorded. A paired sample t-test was used to compare the acquisition time of 3D MRCP and CS 3D MRCP. Image quality metrics and visualization of cyst features were compared with Wilcoxon signed-rank test and McNemar test. The mean acquisition time of CS-3D-MRCP (150 ±â€¯63 s) was significantly lower than that of 3D-MRCP (317 ±â€¯104 s; P < 0.001). The median score of overall quality (reader 1, 3.7 ±â€¯1.0 vs. 3.4 ±â€¯1.1, P = 0.11; reader 2, 3.8 ±â€¯1.0 vs. 3.7 ±â€¯1.1, P = 0.36), artifacts and visualization of the bile ducts were not significantly different between 3D-MRCP and CS-3D-MRCP. There was no significant difference in the visualization score of the index pancreatic cyst (reader 1, 4.2 ±â€¯0.9 vs. 4.1 ±â€¯0.9, P = 0.42; reader 2, 4.2 ±â€¯0.4 vs. 4.0 ±â€¯0.7, P = 0.27) and no difference in the assessment of cyst features. Applying CS to 3D-MRCP yields a two-fold reduction in acquisition time with comparable image quality and visualization of key pancreatic cyst features.

Optimization of a novel large field of view distortion phantom for MR-only treatment planning.

PURPOSE: MR-only treatment planning requires images of high geometric fidelity, particularly for large fields of view (FOV). However, the availability of large FOV distortion phantoms with analysis software is currently limited. This work sought to optimize a modular distortion phantom to accommodate multiple bore configurations and implement distortion characterization in a widely implementable solution. METHOD AND MATERIALS: To determine candidate materials, 1.0 T MR and CT images were acquired of twelve urethane foam samples of various densities and strengths. Samples were precision-machined to accommodate 6 mm diameter paintballs used as landmarks. Final material candidates were selected by balancing strength, machinability, weight, and cost. Bore sizes and minimum aperture width resulting from couch position were tabulated from the literature (14 systems, 5 vendors). Bore geometry and couch position were simulated using MATLAB to generate machine-specific models to optimize the phantom build. Previously developed software for distortion characterization was modified for several magnet geometries (1.0 T, 1.5 T, 3.0 T), compared against previously published 1.0 T results, and integrated into the 3D Slicer application platform. RESULTS: All foam samples provided sufficient MR image contrast with paintball landmarks. Urethane foam (compressive strength ∼1000 psi, density ~20 lb/ft3 ) was selected for its accurate machinability and weight characteristics. For smaller bores, a phantom version with the following parameters was used: 15 foam plates, 55 × 55 × 37.5 cm3 (L×W×H), 5,082 landmarks, and weight ~30 kg. To accommodate > 70 cm wide bores, an extended build used 20 plates spanning 55 × 55 × 50 cm3 with 7,497 landmarks and weight ~44 kg. Distortion characterization software was implemented as an external module into 3D Slicer's plugin framework and results agreed with the literature. CONCLUSION: The design and implementation of a modular, extendable distortion phantom was optimized for several bore configurations. The phantom and analysis software will be available for multi-institutional collaborations and cross-validation trials to support MR-only planning.

A flexible fast spin echo triple-echo Dixon technique.

PURPOSE: To develop a flexible fast spin echo (FSE) triple-echo Dixon (FTED) technique. METHODS: An FSE pulse sequence was modified by replacing each readout gradient with three fast-switching bipolar readout gradients with minimal interecho dead time. The corresponding three echoes were used to generate three raw images with relative phase shifts of -θ, 0, and θ between water and fat signals. A region growing-based two-point Dixon phase correction algorithm was used to joint process two separate pairs of the three raw images, yielding a final set of water-only and fat-only images. The flexible FTED technique was implemented on 1.5T and 3.0T scanners and evaluated in five subjects for fat-suppressed T2-weighted imaging and in one subject for post-contrast fat-suppressed T1-weighted imaging. RESULTS: The flexible FTED technique achieved a high data acquisition efficiency, comparable to that of FSE, and was flexible in scan protocols. The joint two-point Dixon phase correction algorithm helped to ensure consistency in the processing of the two separate pairs of raw images. Reliable and uniform separation of water and fat was achieved in all of the test cases. CONCLUSION: The flexible FTED technique incorporates the benefits of both FSE and Dixon imaging and provided more flexibility than the original FTED in applications such as fat-suppressed T2-weighted and T1-weighted imaging. Magn Reson Med 77:1049-1057, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Comparison of high-resolution T1W 3D GRE (LAVA) with 2-point Dixon fat/water separation (FLEX) to T1W fast spin echo (FSE) in prostate cancer (PCa).

PURPOSE: To compare T1-weighted (T1W) fast spin echo (FSE) to T1W 3-dimensional gradient recalled echo (LAVA) with fat water separation (FLEX) in prostate cancer (PCa). METHODOLOGY: With institutional review board waiver, 39 patients underwent 3-T magnetic resonance imaging including T1W LAVA FLEX (157s)/T1W FSE (316s). Two radiologists assessed (a) image quality/sharpness, (b) presence/severity of artifacts, and (c) skeletal (N=22)/nodal (N=9) metastases. Results were compared using Wilcoxon signed-rank test/receiver operator characteristic analysis. RESULTS: With T1W LAVA FLEX, image quality/sharpness improved (P<.001) with less motion (P=.002-.03) and no difference in phase-encoding artifact (P>.05). One patient had moderate fat/water swap. Detection of skeletal metastases was unchanged (P>.05) and nodal metastases either improved (P=.002) or were comparable (P=.16) using T1W LAVA FLEX. CONCLUSION: T1W LAVA FLEX improves image quality, lessens motion artifact, and is comparable or improves detection of metastases in PCa with reduction in acquisition time.

Optimization of white-matter-nulled magnetization prepared rapid gradient echo (MP-RAGE) imaging.

PURPOSE: To optimize the white-matter-nulled (WMn) Magnetization Prepared Rapid Gradient Echo (MP-RAGE) sequence at 7 Tesla (T), with comparisons to 3T. METHODS: Optimal parameters for maximizing signal-to-noise ratio (SNR) efficiency were derived. The effect of flip angle and repetition time (TR) on image blurring was modeled using simulations and validated in vivo. A novel two-dimensional (2D) -centric radial fan beam (RFB) k-space segmentation scheme was used to shorten scan times and improve parallel imaging. Healthy subjects as well as patients with multiple sclerosis and tremor were scanned using the optimized protocols. RESULTS: Inversion repetition times (TS) of 4.5 s and 6 s were found to yield the highest SNR efficiency for WMn MP-RAGE at 3T and 7T, respectively. Blurring was more sensitive to flip in WMn than in CSFn MP-RAGE and relatively insensitive to TR for both regimes. The 2D RFB scheme had 19% and 47% higher thalamic SNR and SNR efficiency than the 1D centric scheme for WMn MP-RAGE. Compared with 3T, SNR and SNR efficiency were higher for the 7T WMn regime by 56% and 41%, respectively. MS lesions in the cortex and thalamus as well as thalamic subnuclei in tremor patients were clearly delineated using WMn MP-RAGE. CONCLUSION: Optimization and new view ordering enabled MP-RAGE imaging with 0.8-1 mm(3) isotropic spatial resolution in scan times of 5 min with whole brain coverage.

Breath-held MR cholangiopancreatography (MRCP) using a 3D Dixon fat-water separated balanced steady state free precession sequence.

A novel 3D breath-held Dixon fat-water separated balanced steady state free precession (b-SSFP) sequence for MR cholangiopancreatography (MRCP) is described and its potential clinical utility assessed in a series of patients. The main motivation is to develop a robust breath-held alternative to the respiratory gated 3D Fast Spin Echo (FSE) sequence, the current clinical sequence of choice for MRCP. Respiratory gated acquisitions are susceptible to motion artifacts and blurring in patients with significant diaphragmatic drift, erratic respiratory rhythms or sleep apnea. A two point Dixon fat-water separation scheme was developed which eliminates signal loss arising from B0 inhomogeneity effects and minimizes artifacts from perturbation of the b-SSFP steady state. Preliminary results from qualitative analysis of 49 patients demonstrate robust performance of the 3D Dixon b-SSFP sequence with diagnostic image quality acquired in a 20-24s breath-hold.

A 3D balanced-SSFP Dixon technique with group-encoded k-space segmentation for breath-held non-contrast-enhanced MR angiography.

A three-dimensional balanced steady-state free precession (b-SSFP)-Dixon technique with a novel group-encoded k-space segmentation scheme called GUINNESS (Group-encoded Ungated Inversion Nulling for Non-contrast Enhancement in the Steady State) was developed. GUINNESS was evaluated for breath-held non-contrast-enhanced MR angiography of the renal arteries on 18 subjects (6 healthy volunteers, 12 patients) at 3.0 T. The method provided high signal-to-noise and contrast renal angiograms with homogeneous fat and background suppression in short breath-holds on the order of 20 s with high spatial resolution and coverage. GUINNESS has potential as a short breath-hold alternative to conventional respiratory-gated methods, which are often suboptimal in pediatric subjects and patients with significant diaphragmatic drift/sleep apnea.

High-resolution double arterial phase hepatic MRI using adaptive 2D centric view ordering: initial clinical experience.

OBJECTIVE: The objective of our study was to evaluate a new 3D fast spoiled gradient-recalled echo (FSPGR) sequence referred to as modified liver acceleration volume acquisition (LAVA) for high-resolution gadolinium-enhanced dual arterial phase liver MRI and to determine the effect of this technique on the timing of the contrast bolus and lesion detection. MATERIALS AND METHODS: Gadolinium-enhanced dual arterial phase liver MRI was performed in 109 patients using a modified LAVA sequence that supports adaptive 2D centric view ordering, efficient 2D autocalibrated acceleration, and partial-Fourier to achieve faster scan times while maintaining the same slice thickness, resolution, and coverage as single-phase imaging. After a fixed 20-second scan delay, a modified LAVA acquisition required a single 24- to 26-second breath-hold for two arterial phases with 56-60 slices per pass. Images were reviewed for timing relative to liver enhancement, lesion conspicuity, and lesion detection. Liver lesion depiction was evaluated qualitatively and quantitatively. A control group of 109 patients underwent imaging using a single arterial phase 3D FSPGR sequence, which was also performed with a fixed 20-second scan delay. RESULTS: The single arterial phase images produced optimal timing in the middle or late arterial phase in 79 (72%) of the 109 control group patients compared with 99 (91%) of the 109 study group patients who underwent imaging using a dynamic modified LAVA dual arterial phase sequence. For the modified LAVA sequence, the first-pass images were obtained during the mid arterial phase in 34 patients (31%). The second-pass images were obtained during the mid arterial phase in 51 patients (47%) and late arterial phase in 26 patients (24%). Sixty-two patients had liver lesions showing greater conspicuity--on the first phase in 17 patients (27%) and second phase in 45 patients (73%). Hypovascular lesions were more conspicuous on second-phase images in 24 (86%) of 28 patients. Hypervascular lesions were more conspicuous on first-phase images in 13 patients (38%) and on second-phase images in 21 (62%) of 34 patients. The first-phase images detected 165 and 155 liver lesions, respectively, for two observers compared with 233 and 224 lesions on the second-phase images, whereas the combined dual arterial phase images detected 256 and 248 hepatic lesions. CONCLUSION: High-resolution dual arterial phase 3D FSPGR MRI improves the timing of the arterial phase of liver enhancement and provides additional information for liver lesion detection.

Multiecho time-resolved acquisition (META): a high spatiotemporal resolution Dixon imaging sequence for dynamic contrast-enhanced MRI.

PURPOSE: To evaluate a new dynamic contrast-enhanced (DCE) imaging technique called multiecho time-resolved acquisition (META) for abdominal/pelvic imaging. META combines an elliptical centric time-resolved three-dimensional (3D) spoiled gradient-recalled echo (SPGR) imaging scheme with a Dixon-based fat-water separation algorithm to generate high spatiotemporal resolution volumes. MATERIALS AND METHODS: Twenty-three patients referred for hepatic metastases or renal masses were imaged using the new META sequence and a conventional fat-suppressed 3D SPGR sequence on a 3T scanner. In 12 patients, equilibrium-phase 3D SPGR images acquired immediately after META were used for comparing the degree and homogeneity of fat suppression, artifacts, and overall image quality. In the remaining 11 of 23 patients, DCE 3D SPGR images acquired in a previous or subsequent examination were used for comparing the efficiency of arterial phase capture in addition to the qualitative analysis for the degree and homogeneity of fat suppression, artifacts, and overall image quality. RESULTS: META images were determined to be significantly better than conventional 3D SPGR images for degree and uniformity of fat suppression and ability to visualize the arterial phase. There were no significant differences in artifact levels or overall image quality. CONCLUSION: META is a promising high spatiotemporal resolution imaging sequence for capturing the fast dynamics of hyperenhancing hepatic lesions and provides robust fat suppression even at 3T.

Linear phase-error correction for improved water and fat separation in dual-echo dixon techniques.

Large and spatially-linear phase errors along the frequency-encode direction may be induced by several common and hard-to-avoid system imperfections such as eddy currents. For data acquired in dual-echo Dixon techniques, the linear phase error can be more aggravated when compared to that acquired in a single echo and can pose challenges to a phase-correction algorithm necessary for successful Dixon processing. In this work, we propose a two-step process that first corrects the linear component of the phase errors with a modified Ahn-Cho algorithm (Ahn CB and Cho ZH, IEEE Trans. Med. Imaging 6:32, 1987) and then corrects the residual phase errors with a previously-developed region-growing algorithm (Ma J, Magn. Res. Med. 52:415, 2004). We demonstrate that successive application of the two-step process to data from a dual-echo Dixon technique provides a "1-2 punch" to the overall phase errors and can overcome local water and fat separation failures that are observed when the region-growing-based algorithm is applied alone.

Effects of refocusing flip angle modulation and view ordering in 3D fast spin echo.

Recent advances have reduced scan time in three-dimensional fast spin echo (3D-FSE) imaging, including very long echo trains through refocusing flip angle (FA) modulation and 2D-accelerated parallel imaging. This work describes a method to modulate refocusing FAs that produces sharp point spread functions (PSFs) from very long echo trains while exercising direct control over minimum, center-k-space, and maximum FAs in order to accommodate the presence of flow and motion, SNR requirements, and RF power limits. Additionally, a new method for ordering views to map signal modulation from the echo train into k(y)-k(z) space that enables nonrectangular k-space grids and autocalibrating 2D-accelerated parallel imaging is presented. With long echo trains and fewer echoes required to encode large matrices, large volumes with high in- and through-plane resolution matrices may be acquired with scan times of 3-6 min, as demonstrated for volumetric brain, knee, and kidney imaging.

Left ventricular spherical remodeling and apical myocardial relaxation: cardiovascular MR imaging measurement of myocardial segments.

PURPOSE: To prospectively evaluate left ventricular (LV) shape and regional relaxation to determine if rapid, early relaxation of the LV is lost with spherical remodeling of the LV. MATERIALS AND METHODS: This HIPAA-compliant study was approved by the institutional review board. All participants gave written informed consent. Cardiovascular magnetic resonance (MR) imaging and transthoracic echocardiography (TTE) were performed in 18 individuals. Each participant was classified into one of three groups according to LV shape and TTE-derived mitral filling parameters. Pairwise comparisons of cardiovascular MR imaging measurements of LV relaxation were made between healthy individuals and those with spherically shaped LVs. RESULTS: The LV regional relaxation rates were determined in a total of 108 basal, middle, and apical myocardial segments in 18 participants (13 women, five men; age range, 35-76 years). Participants with a spherically shaped LV (sphericity index, <1.5) and a mitral inflow velocity E wave/A wave ratio of less than 1.0 exhibited apical thinning velocities that were lower than those of healthy individuals (sphericity index, > or =1.5) (P < .01). The ratio of LV relaxation velocities in the apical versus middle LV segments correlated significantly with sphericity index (R(2) = 0.53; P = .0005). CONCLUSION: LV apical relaxation velocities in participants with LV spherical remodeling (sphericity index, <1.5) were reduced compared with those of healthy individuals (sphericity index, > or =1.5).

Leg flow-mediated arterial dilation in elderly patients with heart failure and normal left ventricular ejection fraction.

BACKGROUND: flow-mediated arterial dilation (FMAD), an indicator of endothelial function, is reduced in patients with heart failure and reduced left ventricular ejection fraction (HFREF). Many elderly patients with heart failure exhibit a normal left ventricular ejection fraction (HFNEF). It is unknown whether FMAD is severely reduced in the elderly with HFNEF. METHODS AND RESULTS: 30 participants >60 yr of age, 11 healthy, 9 with HFNEF, and 10 with HFREF, underwent a cardiovascular magnetic resonance (CMR) assessment of FMAD in the superficial femoral artery followed within 48 h by symptom-limited exercise with expired gas analysis. Elderly patients with HFREF and HFNEF had severely reduced peak oxygen consumption (Vo(2 peak); 12 +/- 2 and 13 +/- 1 ml.kg(-1).min(-1), respectively) vs. their healthy age-matched contemporaries (20 +/- 3 ml.kg(-1).min(-1)). FMAD was 3.8 +/- 1.3% (0.85 +/- 0.22 mm(2)) in patients with HFREF; it was 12.1 +/- 3.6% (3.1 +/- 1.2 mm(2)) and 13.7 +/- 5.9% (3.9 +/- 1.7 mm(2)), respectively, in patients with HFNEF and age-matched healthy older individuals. After adjustment for age and gender, the association of FMAD with Vo(2) was high in healthy and HFREF subjects (P = 0.05 and 0.02, respectively) but less so in HFNEF participants (P = 0.58). CONCLUSIONS: elderly patients with HFNEF do not exhibit marked reduction in leg FMAD. These data suggest that mechanisms other than impaired femoral arterial endothelial function contribute to the severe exercise intolerance experienced by these individuals.

Minimum reliable scale selection in 3D.

Multiscale analysis is often required in image processing applications because image features are optimally detected at different levels of resolution. With the advance of high-resolution 3D imaging, the extension of multiscale analysis to higher dimensions is necessary. This paper extends an existing 2D scale selection method, known as the minimum reliable scale, to 3D volumetric images. The method is applied to 3D boundary detection and is illustrated in examples from biomedical imaging. The experimental results show that the 3D scale selection improves the detection of edges over single scale operators using as few as three different scales.

QSAR modeling of mono- and bis-quaternary ammonium salts that act as antagonists at neuronal nicotinic acetylcholine receptors mediating dopamine release.

Back-propagation artificial neural networks (ANNs) were trained on a dataset of 42 molecules with quantitative IC50 values to model structure-activity relationships of mono- and bis-quaternary ammonium salts as antagonists at neuronal nicotinic acetylcholine receptors (nAChR) mediating nicotine-evoked dopamine release. The ANN QSAR models produced a reasonable level of correlation between experimental and calculated log(1/IC50) (r2=0.76, r(cv)2=0.64). An external test for the models was performed on a dataset of 18 molecules with IC50 values >1 microM. Fourteen of these were correctly classified. Classification ability of various models, including self-organizing maps (SOM), for all 60 molecules was also evaluated. A detailed analysis of the modeling results revealed the following relative contributions of the used descriptors to the trained ANN QSAR model: approximately 44.0% from the length of the N-alkyl chain attached to the quaternary ammonium head group, approximately 20.0% from Moriguchi octanol-water partition coefficient of the molecule, approximately 13.0% from molecular surface area, approximately 12.6% from the first component shape directional WHIM index/unweighted, approximately 7.8% from Ghose-Crippen molar refractivity, and 2.6% from the lowest unoccupied molecular orbital energy. The ANN QSAR models were also evaluated using a set of 13 newly synthesized compounds (11 biologically active antagonists and two biologically inactive compounds) whose structures had not been previously utilized in the training set. Twelve among 13 compounds were predicted to be active which further supports the robustness of the trained models. Other insights from modeling include a structural modification in the bis-quinolinium series that involved replacing the 5 and/or 8 as well as the 5' and/or 8' carbon atoms with nitrogen atoms, predicting inactive compounds. Such data can be effectively used to reduce synthetic and in vitro screening activities by eliminating compounds of predicted low activity from the pool of candidate molecules for synthesis. The application of the ANN QSAR model has led to the successful discovery of six new compounds in this study with experimental IC50 values of less than 0.1 microM at nAChR subtypes responsible for mediating nicotine-evoked dopamine release, demonstrating that the ANN QSAR model is a valuable aid to drug discovery.