Set Of Acquisition Parameters Research Articles

Optimizing MR Scan Design for Model-Based ${T}_{1}$ , ${T}_{2}$ Estimation From Steady-State Sequences.

Rapid, reliable quantification of MR relaxation parameters T1 and T2 is desirable for many clinical applications. Steady-state sequences such as Spoiled Gradient-Recalled Echo (SPGR) and Dual-Echo Steady-State (DESS) are fast and well-suited for relaxometry because the signals they produce are quite sensitive to T1 and T2 variation. However, T1, T2 estimation with these sequences typically requires multiple scans with varied sets of acquisition parameters. This paper describes a systematic framework for selecting scan types (e.g., combinations of SPGR and DESS scans) and optimizing their respective parameters (e.g., flip angles and repetition times). The method is based on a Cramér-Rao Bound (CRB)-inspired min-max optimization that finds scan parameter combinations that robustly enable precise object parameter estimation. We apply this technique to optimize combinations of SPGR and DESS scans for T1, T2 relaxometry in white matter (WM) and grey matter (GM) regions of the human brain at 3T field strength. Phantom accuracy experiments show that SPGR/DESS scan combinations are in excellent agreement with reference measurements. Phantom precision experiments show that trends in T1,T2 pooled sample standard deviations reflect CRB-based predictions. In vivo experiments show that in WM and GM, T1 and T2 estimates from a pair of optimized DESS scans exhibit precision (but not necessarily accuracy) comparable to that of optimized combinations of SPGR and DESS scans. To our knowledge, T1 maps from DESS acquisitions alone are new. This example application illustrates that scan optimization may help reveal new parameter mapping techniques from combinations of established pulse sequences.

Optimal experiment design for magnetic resonance fingerprinting.

Magnetic resonance (MR) fingerprinting is an emerging quantitative MR imaging technique that simultaneously acquires multiple tissue parameters in an efficient experiment. In this work, we present an estimation-theoretic framework to evaluate and design MR fingerprinting experiments. More specifically, we derive the Cramér-Rao bound (CRB), a lower bound on the covariance of any unbiased estimator, to characterize parameter estimation for MR fingerprinting. We then formulate an optimal experiment design problem based on the CRB to choose a set of acquisition parameters (e.g., flip angles and/or repetition times) that maximizes the signal-to-noise ratio efficiency of the resulting experiment. The utility of the proposed approach is validated by numerical studies. Representative results demonstrate that the optimized experiments allow for substantial reduction in the length of an MR fingerprinting acquisition, and substantial improvement in parameter estimation performance.

Performance Assessment in Fingerprinting and Multi Component Quantitative NMR Analyses.

An interlaboratory comparison (ILC) was organized with the aim to set up quality control indicators suitable for multicomponent quantitative analysis by nuclear magnetic resonance (NMR) spectroscopy. A total of 36 NMR data sets (corresponding to 1260 NMR spectra) were produced by 30 participants using 34 NMR spectrometers. The calibration line method was chosen for the quantification of a five-component model mixture. Results show that quantitative NMR is a robust quantification tool and that 26 out of 36 data sets resulted in statistically equivalent calibration lines for all considered NMR signals. The performance of each laboratory was assessed by means of a new performance index (named Qp-score) which is related to the difference between the experimental and the consensus values of the slope of the calibration lines. Laboratories endowed with a Qp-score falling within the suitable acceptability range are qualified to produce NMR spectra that can be considered statistically equivalent in terms of relative intensities of the signals. In addition, the specific response of nuclei to the experimental excitation/relaxation conditions was addressed by means of the parameter named NR. NR is related to the difference between the theoretical and the consensus slopes of the calibration lines and is specific for each signal produced by a well-defined set of acquisition parameters.

Optimization of contrast-enhanced spectral mammography depending on clinical indication.

The objective is to optimize low-energy (LE) and high-energy (HE) exposure parameters of contrast-enhanced spectral mammography (CESM) examinations in four different clinical applications for which different levels of average glandular dose (AGD) and ratios between LE and total doses are required. The optimization was performed on a Senographe DS with a SenoBright® upgrade. Simulations were performed to find the optima by maximizing the contrast-to-noise ratio (CNR) on the recombined CESM image using different targeted doses and LE image quality. The linearity between iodine concentration and CNR as well as the minimal detectable iodine concentration was assessed. The image quality of the LE image was assessed on the CDMAM contrast-detail phantom. Experiments confirmed the optima found on simulation. The CNR was higher for each clinical indication than for SenoBright®, including the screening indication for which the total AGD was 22% lower. Minimal iodine concentrations detectable in the case of a 3-mm-diameter round tumor were 12.5% lower than those obtained for the same dose in the clinical routine. LE image quality satisfied EUREF acceptable limits for threshold contrast. This newly optimized set of acquisition parameters allows increased contrast detectability compared to parameters currently used without a significant loss in LE image quality.

Reducing CT radiation dose with iterative reconstruction algorithms: The influence of scan and reconstruction parameters on image quality and CTDIvol

ObjectivesIn this phantom CT study, we investigated whether images reconstructed using filtered back projection (FBP) and iterative reconstruction (IR) with reduced tube voltage and current have equivalent quality. We evaluated the effects of different acquisition and reconstruction parameter settings on image quality and radiation doses. Additionally, patient CT studies were evaluated to confirm our phantom results. MethodsHelical and axial 256 multi-slice computed tomography scans of the phantom (Catphan®) were performed with varying tube voltages (80–140kV) and currents (30–200mAs). 198 phantom data sets were reconstructed applying FBP and IR with increasing iterations, and soft and sharp kernels. Further, 25 chest and abdomen CT scans, performed with high and low exposure per patient, were reconstructed with IR and FBP. Two independent observers evaluated image quality and radiation doses of both phantom and patient scans. ResultsIn phantom scans, noise reduction was significantly improved using IR with increasing iterations, independent from tissue, scan-mode, tube-voltage, current, and kernel. IR did not affect high-contrast resolution. Low-contrast resolution was also not negatively affected, but improved in scans with doses <5mGy, although object detectability generally decreased with the lowering of exposure. At comparable image quality levels, CTDIvol was reduced by 26–50% using IR. In patients, applying IR vs. FBP resulted in good to excellent image quality, while tube voltage and current settings could be significantly decreased. ConclusionsOur phantom experiments demonstrate that image quality levels of FBP reconstructions can also be achieved at lower tube voltages and tube currents when applying IR. Our findings could be confirmed in patients revealing the potential of IR to significantly reduce CT radiation doses.

Probabilities of triggering and validation in a digital silicon photomultiplier

A digital silicon photomultiplier (dSiPM) consists of an array of single photon avalanche diodes (SPADs) operating in Geiger-mode. Each SPAD is connected to a dedicated CMOS quenching and digitization circuit. One type of dSiPM is the Digital Photon Counter (DPC) manufactured by Philips Digital Photon Counting (PDPC). Due to the digital architecture of the device, a DPC can be adapted and optimized for different applications through a set of adjustable acquisition parameters. The influence of these parameters must be well understood for the correct use of the sensor. In particular, for applications involving low light intensity, such as in scintillation detectors, it is essential to carefully set all the parameters related to triggering and validation in order to discriminate between noise and true events. The triggering and validation processes in a DPC intrinsically are of a probabilistic nature since their fully digital implementations are based on configurable logic interconnections between groups of SPADs. In this study we develop an analytical model that relates the probability of triggering and validation to the number of fired SPADs in a given event, for some of the available trigger and validation schemes. The model is shown to accurately predict experimental data acquired on a PDPC DPC3200-22-44.

Segmentations of Liver and Hepatic Tumors from 3D Computed Tomography Abdominal Images

The segmentation of liver using computed tomography (CT) data has gained a lot of importance in the medical image processing field. In this paper, we present a survey on liver segmentation methods and techniques using CT images for liver segmentation. An adaptive initialization method was developed to produce fully automatic processing frameworks based on graph-cut and gradient flow active contour algorithms. This method was applied to abdominal Computed Tomography (CT) images for segmentation of liver tissue and hepatic tumors. Twenty-five anonymized datasets were randomly collected from several radiology centres without specific request on acquisition parameter settings nor patient clinical situation as inclusion criteria. Resulting automatic segmentations of liver tissue and tumors were compared to their reference standard delineations manually performed by a specialist. Segmentation accuracy has been assessed through the following evaluation framework: dice similarity coefficient, false negative ratio, false positive ratio and processing time. The implemented initialization method allows fully automatic segmentation leading to superior overall performances of graph-cut algorithm in terms of accuracy and processing time. The initialization method here presented resulted suitable and reliable for two different segmentation techniques and could be further extended.

Optimizing isotropic three-dimensional fast spin-echo methods for imaging the knee.

To optimize acquisition parameters for three dimensional fast spin-echo (3D FSE) imaging of the knee. The knees of eight healthy volunteers were imaged in a 3 Tesla MRI scanner using an eight-channel knee coil. A total of 146 intermediate weighted isotropic resolution 3D FSE (3D-FSE-Cube)images with varied acquisition parameter settings were acquired with an additional reference scan performed for subjective image quality assessment. Images were graded for overall quality, parallel imaging artifact severity and blurring. Cartilage, muscle, and fluid signal-to-noise ratios and fluid-cartilage contrast-to-noise ratios were quantified by acquiring scans without radio frequency excitation and custom-reconstructing the k-space data.Mixed effects regression modeling was used to determine statistically significant effects of different parameters on image quality. Changes in receiver bandwidth, repetition time and echo train length significantly affected all measurements of image quality (P < 0.05). Reducing band width improved all metrics of image quality with the exception of blurring. Reader agreement was slight to fair for subjective metrics, but overall trends in quality ratings were apparent. We used a systematic approach to optimize 3D-FSE-Cube parameters for knee imaging. Image quality was overall improved using a receiver bandwidth of 631.25 kHz, and blurring increased with lower band width and longer echo trains.

SU‐E‐J‐16: Evaluation of Image Quality From KV Cone‐Beam CT with Couch Offset for Two Image Protocols

Purpose: To evaluate kV cone‐beam CT image quality for two clinical reconstruction algorithms when the volume of interest deviates from isocenter Methods: The CatPhan phantom (The Phantom Lab.) was scanned using CBCT on a TrueBeam LINAC (Varian Medical Systems). The phantom contains various sections designed to assess certain image quality parameters. Images were acquired with the phantom centered about the imaging isocenter (as typically done for routine CBCT QA), and then also acquired with phantom offset 5 cm laterally and longitudinally. At each position, scans were taken using two techniques typically used in the clinic: Head &amp; Pelvis. The centered‐phantom CBCT was used as a baseline, and image quality for this scan was compared against that for each offset scan. The end points of the image quality comparison were four parameters: MTF, low contrast detectability, uniformity and noise. Analysis of all CT sets were performed by the PIPSpro QA software (Standard Imaging, Inc.). Results: For the pelvis protocol, the critical frequency (f50, lp/cm) in lateral and longitudinal offset scans was worse than that of the reference position, meaning lowered small object detectability with high contrast in offset scans. There is no significant difference found in low contrast detectability and noise level for offset scans in both Pelvis and Head protocols. The uniformity index for the lateral shift cases better than the reference image sets. Conclusions: The results show that even though off‐centered CBCT is a useful tool to handle when the volume deviates from isocenter, a precaution is needed because of a decrease in high contrast detectability. A further study of image quality comparison for cou ch offset will co nsider different acquisition parameter settings.

Evaluation of B0-inhomogeneity correction for triple-quantum-filtered sodium MRI of the human brain at 4.7 T

Off-resonance can result in signal loss on triple-quantum-filtered (TQF) sodium images. Three correction methods have been proposed to mitigate this problem, but their effectiveness and necessity has not yet been evaluated for human brain. This evaluation is warranted given the doubling or quadrupling of scan length without the expected signal-to-noise ratio (SNR) benefit. First, simulations and agar gel experiments showed that the off-resonance effects on signal loss were asymmetric about on-resonance. Second, the two scan length doubling correction methods were tested for two sets of TQF acquisition parameters in 10 healthy volunteers at 4.7Tesla. Using only manual shimming on the sodium signal and a 3-pulse TQF sequence with an optimal preparation time value of 6ms, the majority of brain tissue voxels (87–94% depending on sequence parameters) experienced B0 inhomogeneity amounting to less than 10% signal losses. Relative signal intensities of 0.96±0.04 and 0.98±0.02 were measured in these voxels relative to on-resonant voxels for SNR-optimized and standard TQF parameters. The remaining brain voxels in regions with known susceptibility problems suffered more substantial signal losses, which were partially recovered with the correction methods. At field strengths below 4.7T, at similar ranges of offset frequencies at higher fields and in typical volunteers, B0 correction appears unnecessary for TQF analysis in most of the brain. In many cases where regions with known susceptibility issues are not of concern, a doubling of scan time may be better spent to either improve SNR or spatial resolution in the TQF sodium images.

Critical considerations for fast and accurate regiospecific analysis of triacylglycerols using quantitative 13C NMR

Quantitative 13C NMR (qCNMR) has been used as an appealing methodology for regiospecific analysis of triacylglycerols in edible oils and fats. It has advantages of shorter analysis time, precision and accuracy over laborious conventional Grignard or enzymatic hydrolysis method. Previous reported studies have recommended diversified NMR acquisition and processing parameters for the same quantification work. Different quantitative data were obtained by using a distinct sets of NMR parameters. To overcome this problem, we conducted a systematic investigation to examine the role of each acquisition and processing parameters to obtain high accuracy and repeatability data. Principal acquisition parameters, for instance pulse flip angle, repetition delay and temperature were investigated to correlate the targeted accuracies and practical experimental conditions. New data on spin-lattice relaxation times (T1) for carbonyl carbons in a variety of oils and fats had been obtained and analyzed comprehensively. With this set of acquisition parameters and free induction decay (FID) data processing method, error of less than 2.0 mol% were obtained with high repeatability and versatility for the analysis of oils and fats from diverse sources, including the reaction intermediates by chemical interesterification, lipids content extracted from biological samples and those natural occurring oils without their regiospecific data reported up-to-date. Instead of the semi-quantitative approach in previous reports on fish oil, we used narrower spectral width targeting sn-position in triacylglycerols to obtain full quantitative data in a shorter analysis time. The present selection of data acquisition and processing parameters led to a blueprint for a generic approach to performing a routinely practiced qCNMR regiospecific analysis.

Modelling Temporal Stability of EPI Time Series Using Magnitude Images Acquired with Multi-Channel Receiver Coils

In 2001, Krueger and Glover introduced a model describing the temporal SNR (tSNR) of an EPI time series as a function of image SNR (SNR0). This model has been used to study physiological noise in fMRI, to optimize fMRI acquisition parameters, and to estimate maximum attainable tSNR for a given set of MR image acquisition and processing parameters. In its current form, this noise model requires the accurate estimation of image SNR. For multi-channel receiver coils, this is not straightforward because it requires export and reconstruction of large amounts of k-space raw data and detailed, custom-made image reconstruction methods. Here we present a simple extension to the model that allows characterization of the temporal noise properties of EPI time series acquired with multi-channel receiver coils, and reconstructed with standard root-sum-of-squares combination, without the need for raw data or custom-made image reconstruction. The proposed extended model includes an additional parameter κ which reflects the impact of noise correlations between receiver channels on the data and scales an apparent image SNR (SNR′0) measured directly from root-sum-of-squares reconstructed magnitude images so that κ = SNR′0/SNR0 (under the condition of SNR0>50 and number of channels ≤32). Using Monte Carlo simulations we show that the extended model parameters can be estimated with high accuracy. The estimation of the parameter κ was validated using an independent measure of the actual SNR0 for non-accelerated phantom data acquired at 3T with a 32-channel receiver coil. We also demonstrate that compared to the original model the extended model results in an improved fit to human task-free non-accelerated fMRI data acquired at 7T with a 24-channel receiver coil. In particular, the extended model improves the prediction of low to medium tSNR values and so can play an important role in the optimization of high-resolution fMRI experiments at lower SNR levels.

Effect of acquisition parameters on digital breast tomosynthesis: Total angular range and number of projection views

The purpose of this study was to investigate the effect of different acquisition parameters and to determine the optimal set of acquisition parameters of projection views (PVs) for the new developed digital breast tomosynthesis (DBT) system. The DBT imaging parameters were optimized using 32 different acquisition sets with six angular ranges (±5°, ±10°, ±13°, ±17°, ±21°, and ±25°) and eight projection views (5, 11, 15, 21, 25, 31, 41, and 51 prjections). In addition to the contrastto-noise ratio (CNR), the artifact spread function (ASF) was used to quantify the in-focus plane artifacts along the z-direction in order to explore the relationship between the acquisition parameters and the image quality. A commercially, available breast-mimicking phantom was imaged to qualitatively verify our results. Our results show that a wide angular range improved the reconstructed image quality in the z-direction. If a large number of projections are acquired, then the electronic noise may dominate the CNR due to reduce the radiation dose per projection. Although increasing angular range was found to improve the vertical resolution, due to greater effective breast thickness, the image quality of microcalcifications in the in-focus plane was also found not to be improved by increasing the noise. Therefore, potential trade-offs of these physical imaging properties must be considered to optimize the acquisition configuration of a DBT system. Our results suggest possible directions for further improvements in DBT systems for high quality imaging.

Analysis of CT acquisition parameters suitable for use in SPECT/CT: A free-response receiver operating characteristic study

PurposeThis dose optimisation free-response receiver operating characteristic (FROC) study compares the diagnostic performance of 8 CT acquisition parameter settings suitable for use with diagnostic quality SPECT/CT systems. Observers were required to localise simulated pulmonary lesions within an anthropomorphic chest phantom. MethodNine observers of varying CT experience (0–10+ years) reviewed 64 cases from each acquisition protocol. FROC methods were used to provide the area under the ROC curve (AUC) figures of merit for each CT acquisition parameter setting. The American College of Radiologists (ACR) CT accreditation phantom was used to acquire quality control (QC) images at each acquisition parameter setting. Measures of contrast to noise ratio (CNR), spatial (contrast) resolution and uniformity could then be compared to the AUC data. Effective dose (E) was estimated using the ImpaCT tool. ResultsAUC analysis revealed no significant difference (p = 0.866) between CT acquisitions for the detection of simulated pulmonary lesions within a chest phantom. The best observer averaged AUC performance was 0.853 (95% CI 0.803–0.903) at an estimated E of 0.82 mSv. The worst observer averaged AUC was recorded at the lowest estimated E (0.28 mSv) was 0.825 (95% CI 0.766–0.885). No correlation was evident between AUC and measures of CNR, spatial resolution or uniformity. ConclusionOur findings suggest that the lowest dose CT acquisition protocol can be used to accurately localise simulated pulmonary lesions within a chest phantom; suggesting that similar protocols could be used on diagnostic quality SPECT/CT systems to allow low-dose evaluations of lung lesions.

Hemispheric Asymmetry in White Matter Connectivity of the Temporoparietal Junction with the Insula and Prefrontal Cortex

The temporoparietal junction (TPJ) is a key node in the brain's ventral attention network (VAN) that is involved in spatial awareness and detection of salient sensory stimuli, including pain. The anatomical basis of this network's right-lateralized organization is poorly understood. Here we used diffusion-weighted MRI and probabilistic tractography to compare the strength of white matter connections emanating from the right versus left TPJ to target regions in both hemispheres. Symmetry of structural connectivity was evaluated for connections between TPJ and target regions that are key cortical nodes in the right VAN (insula and inferior frontal gyrus) as well as target regions that are involved in salience and/or pain (putamen, cingulate cortex, thalamus). We found a rightward asymmetry in connectivity strength between the TPJ and insula in healthy human subjects who were scanned with two different sets of diffusion-weighted MRI acquisition parameters. This rightward asymmetry in TPJ-insula connectivity was stronger in females than in males. There was also a leftward asymmetry in connectivity strength between the TPJ and inferior frontal gyrus, consistent with previously described lateralization of language pathways. The rightward lateralization of the pathway between the TPJ and insula supports previous findings on the roles of these regions in stimulus-driven attention, sensory awareness, interoception and pain. The findings also have implications for our understanding of acute and chronic pains and stroke-induced spatial hemineglect.

Fully Automatic Segmentations of Liver and Hepatic Tumors From 3-D Computed Tomography Abdominal Images: Comparative Evaluation of Two Automatic Methods

An adaptive initialization method was developed to produce fully automatic processing frameworks based on graph-cut and gradient flow active contour algorithms. This method was applied to abdominal Computed Tomography (CT) images for segmentation of liver tissue and hepatic tumors. Twenty-five anonymized datasets were randomly collected from several radiology centres without specific request on acquisition parameter settings nor patient clinical situation as inclusion criteria. Resulting automatic segmentations of liver tissue and tumors were compared to their reference standard delineations manually performed by a specialist. Segmentation accuracy has been assessed through the following evaluation framework: dice similarity coefficient (DSC), false negative ratio (FNR), false positive ratio (FPR) and processing time. Regarding liver surfaces, graph-cuts achieved a DSC of 95.49% ( FPR=2.35% and FNR=5.10%), while active contours reached a DSC of 96.17% (FPR=3.35% and FNR=3.87%). The analyzed datasets presented 52 tumors: graph-cut algorithm detected 48 tumors with a DSC of 88.65%, while active contour algorithm detected only 44 tumors with a DSC of 87.10%. In addition, in terms of time performances, less time was requested for graph-cut algorithm with respect to active contour one. The implemented initialization method allows fully automatic segmentation leading to superior overall performances of graph-cut algorithm in terms of accuracy and processing time. The initialization method here presented resulted suitable and reliable for two different segmentation techniques and could be further extended.

Multislice fractional ventilation imaging in large animals with hyperpolarized gas MRI

The noninvasive assessment of regional lung ventilation is of critical importance in the quantification of the severity of disease and evaluation of response to therapy in many pulmonary diseases. This work presents, for the first time, the implementation of a hyperpolarized (HP) gas MRI technique to measure whole-lung regional fractional ventilation (r) in Yorkshire pigs (n = 5) through the use of a gas mixing and delivery device in the supine position. The proposed technique utilizes a series of back-to-back HP gas breaths with images acquired during short end-inspiratory breath-holds. In order to decouple the radiofrequency pulse decay effect from the ventilatory signal build-up in the airways, the regional distribution of the flip angle (α) was estimated in the imaged slices by acquiring a series of back-to-back images with no interscan time delay during a breath-hold at the tail end of the ventilation sequence. Analysis was performed to assess the sensitivity of the multislice ventilation model to noise, oxygen and the number of flip angle images. The optimal α value was determined on the basis of the minimization of the error in r estimation: α(opt) = 5-6º for the set of acquisition parameters in pigs. The mean r values for the group of pigs were 0.27 ± 0.09, 0.35 ± 0.06 and 0.40 ± 0.04 for the ventral, middle and dorsal slices, respectively (excluding conductive airways r 0.9). A positive gravitational (ventral-dorsal) ventilation gradient effect was present in all animals. The trachea and major conductive airways showed a uniform near-unity r value, with progressively smaller values corresponding to smaller diameter airways, and ultimately leading to lung parenchyma. The results demonstrate the feasibility of the measurement of the fractional ventilation in large species, and provide a platform to address the technical challenges associated with long breathing time scales through the optimization of acquisition parameters in species with a pulmonary physiology very similar to that of humans.

Acquisition strategy to obtain quantitative diffusion NMR data

Pulsed Gradient Spin Echo (PGSE) diffusion NMR experiments constitute a powerful tool for analyzing complex mixtures because they can in principle separate the NMR spectra of each mixture component. However, because these experiments intrinsically rely on spin echoes, they are traditionally regarded as non-quantitative, due to the signal attenuation caused by longitudinal (T1) and transverse (T2) nuclear magnetic relaxation during the rather long delays of the pulse sequence. Alternatively to the quantitative Direct Exponential Curve Resolution Algorithm (qDECRA) approach proposed by Antalek (J. Am. Chem. Soc. 128 (2006) 8402–8403), this work presents an acquisition strategy that renormalizes this relaxation attenuation using estimates of the T1 and T2 relaxation times for all the nuclei in the mixture, as obtained directly with the pulse sequence used to record the PGSE experiment. More specifically, it is shown that only three distinct PGSE experiments need to be recorded, each with a specific set of acquisition parameters. For small- and medium-sized molecules, only T1 is required for obtaining accurate quantification. For larger molecular weight species, which typically exhibit short T2 values, estimates of T2 must also be included but only a rough estimation is required. This appears fortunate because these data are especially hard to obtain with good accuracy when analyzing homonuclear scalar-coupled systems. Overall, the proposed methodology is shown to yield a quantification accuracy of ±5%, both in the absence and in the presence of spectral overlap, giving rise – at least, in our hands – to results that superseded those achieved by qDECRA, while requiring substantially less experimental time.

Rapid and direct quantitative analysis of positional fatty acids in triacylglycerols using 13C NMR

AbstractThere is increasing evidence that the positional fatty acid composition (FAC) of TAG is more important than total FAC with regard to nutrition values of edible oils and fats. A rapid and direct regiospecific analysis of positional fatty acids in TAG using 13C NMR was developed to overcome the tedious conventional methods which involve enzymatic hydrolysis, Grignard chemical degradation, and chromatography analysis. A set of NMR data acquisition parameters and processing methods had proven their excellent versatility and applicability on various types of oils and fats, with systematic error of 1.0 mol%. It was found that there are discrepancies between the regiospecific analysis results obtained by the current method and by conventional methods. Probable acyl migration occurring in the hydrolysis process in conventional methods is a noted problem. As the current 13C NMR method is a direct measurement and no hydrolysis of the sample is needed, acyl migration during the analysis is eliminated. As a result, the saturation level is always higher at sn‐1, 3 positions and lower at sn‐2 position in TAG structure of oils in the regiospecific data obtained from the current 13C NMR than that from conventional methods. In the absence of laborious chemical derivatization, this method is simple, accurate, and user‐friendly for researchers, especially for nutritionists to support their nutritional studies from the perspective of positional FAC of edible oils and fats.

Calcium scoring in unenhanced and enhanced CT data of the aorta-iliacal arteries: impact of image acquisition, reconstruction, and analysis parameter settings

Several studies have been published on the matter of abdominal aortic and iliac calcifications and the association to clinical entities such as diabetes mellitus and renal failure. However, comparing of these studies is questionable since quantification methods for atherosclerosis differ. To evaluate the effect of image acquisition settings, reconstruction parameters, and analysis methods on calcium quantification in the abdominal aorta. Calcium scores were retrospectively determined on standardized abdominal CT scans of 15 patients. Two researchers obtained calcium scores with 10 different lower thresholds (LT) (130, 145, 160, 175, 200, 300, 400, 500, 600, 1000) in CT scans with and without contrast enhancement, with slice thicknesses (ST) varying between 2.0-5.0 mm for the non-contrast-enhanced series and between 1.0-5.0 mm for the contrast-enhanced series. In addition calcium scores obtained with two convolution kernels (B10f, B20f) were compared. Inter-observer variability was calculated. Calcium scoring at higher STs is overestimated compared to smaller STs and this effect was more pronounced with increasing calcium loads. Concerning the convolution kernel, scores obtained with kernel B10f were overestimated compared to kernel B20f. Increase of LT resulted in a decrease of the calcium score and scoring in contrast-enhanced series resulted in higher scores compared to non-contrast-enhanced series. These effects are more apparent in patients with higher calcium loads. Calcium scoring reproducibility with the reference standard is limited for the aorta-iliac trajectory, whereas scoring with the remaining settings is reproducible. Scores obtained with different settings cannot be compared. The inter-observer reproducibility was limited using the reference standard and practical difficulties were substantial. Scoring with higher LT, ST, and contrast enhancement is faster and has less practical difficulties.