Odd-Leg Birdcages for Geometric Decoupling in Multinuclear Imaging and SpectroscopyRead the full article
Concepts in Magnetic Resonance Part B publishes research concerning the design and development of hardware and software employed in magnetic resonance techniques, including magnetic resonance imaging (MRI) and nuclear magnetic resonance (NMR).
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A General Framework for Automated Accurate Calculation of b-Matrix (Auto-b) in Diffusion MRI Pulse Sequences
To derive accurate diffusion metrics, both imaging and diffusion-sensitizing gradient pulses should be accounted for when calculating the diffusion-weighted b-matrix. However, it is complex to derive analytical solutions due to complicated interactions between gradient pulses, including orthogonal directions. This study proposes a general framework to calculate the b-matrix automatically (dubbed as Auto-b). Based on the divide-and-conquer approach, the b-matrix calculation is appropriately segmented, and the symbolic mathematical library is applied to handle integration operations for each interval. If the specifications of all gradient pulses are provided to Auto-b, an accurate b-matrix can be obtained. Three examples are explored to validate the accuracy of Auto-b and to detect b-value errors when using approximate calculations. (1) In the conventional spin-echo example, Auto-b exhibits high accuracy, as indicated by the maximum relative deviation of 1.68‰ between its calculated b-matrices and those obtained from analytical expressions. (2) Auto-b is applied to investigate the contribution of imaging gradients to the b-matrix in an optimized spin-echo echo planar imaging sequence at submillimeter resolution. Specifically, ignoring the contribution of imaging gradients results in a b-value error of 12.16 s/mm2 at the 0.8 × 0.8 × 0.8 mm3 resolution and 22.47 s/mm2 at the 0.6 × 0.6 × 0.8 mm3 resolution, respectively, when nominal b = 0. (3) Auto-b is also utilized to analyze the influence of approximate calculations in the spatiotemporally encoded sequence. The results showed that neglecting the contribution of phase-encoding blips causes large b-value errors up to 11.02 s/mm2. In addition, the rectangularization of trapezoidal waveforms led to a high relative b-value error of 39.91%. This study validates the high accuracy of Auto-b and underscores the importance of accurate b-value calculations in both submillimeter imaging and spatiotemporally encoded sequences. Attributed to its automation, accuracy, and broad applicability, Auto-b is helpful for developers of diffusion sequences.
Development of Electron Paramagnetic Resonance Magnet System for In Vivo Tooth Dosimetry
As part of a homebuilt continuous wave electron paramagnetic resonance (EPR) spectrometer operating at 1.2 GHz, a magnet system for in vivo tooth dosimetry was developed. The magnet was designed by adopting NdFeB permanent magnet (PM) for the main magnetic field generation. For each pole of the magnet, 32 cylindrical PMs were arranged in 2 axially aligned ring arrays. The pole gap was 18 cm, which was wide enough for a human head breadth. The measured magnetic field was compared with the magnetic field distribution calculated in a finite element method (FEM) simulation. EPR spectra of intact human teeth irradiated 5 and 30 Gy were measured for the performance test with the developed magnet system and spectrometer. The measured mean magnetic flux density was estimated to be 44.45 mT with homogeneity of 1,600 ppm in a 2 cm diameter of the spherical volume of the XY plane, which was comparable to the FEM simulation results. The sweep coefficient of the magnetic field sweep coil was 0.35 mT per Ampere in both the measurement and FEM simulation. With ±9 A current, the sweep range was 5.7 mT, which was sufficiently wide to measure the tooth radiation-induced signal (RIS) and reference material. The peak-to-peak amplitude of the measured modulation field was 0.38 mT at the center of the magnet. With the developed magnet fully integrated into an EPR system, the EPR spectra of 5 and 30 Gy irradiated teeth were successfully acquired. The developed magnet system showed sufficiently acceptable performance in terms of magnetic flux density and homogeneity. The EPR spectrum of tooth RIS could be measured ex vivo. The RIS of 5 and 30 Gy irradiated teeth was clearly distinguishable from intact human teeth.
Diagnosis of Alzheimer’s Disease with Extreme Learning Machine on Whole-Brain Functional Connectivity
The analysis of human brain fMRI subjects can research neuro-related diseases and explore the related rules of human brain activity. In this paper, we proposed an algorithm framework to analyze the functional connectivity network of the whole brain and to distinguish Alzheimer’s disease (AD), mild cognitive impairment (MCI), and cognitively normal (CN). In other studies, they use algorithms to select features or extract abstract features, or even manually select features based on prior information. Then, a classifier is constructed to classify the selected features. We designed a concise algorithm framework that uses whole-brain functional connectivity for classification without feature selection. The algorithm framework is a two-hidden-layer neural network based on extreme learning machine (ELM), which overcomes the instability of classical ELM in high-dimensional data scenarios. We use this method to conduct experiments for AD, MCI, and CN data and perform 10-fold cross-validation. We found that it has several advantages: (1) the proposed method has excellent classification accuracy with high speed. The classification accuracy of AD vs. CN is 96.85%, and the accuracy of MCI vs. CN is 95.05%. Their AUC (area under curve) of ROC (receiver operating characteristic curve) reached 0.9891 and 0.9888, respectively. Their sensitivities are 97.1% and 94.7%, and specificities are 96.3% and 95.3%, respectively. (2) Compared with other studies, the proposed method is concise. Construction of a two-hidden-layer neural network is to learn features of the whole brain for the diagnosis of AD and MCI, without the feature screening. It avoids the negative effects of feature screening by algorithm or prior information. (3) The proposed method is suitable for small sample and high-dimensional data. It meets the requirements of medical image analysis. In other studies, its classifiers usually deal with several to dozens of feature dimensions. The proposed method deals with 4005 feature dimensions.
Study of Correlation between MRI Morphology of Primary Tumor and Extramural Vascular Invasion in Rectal Cancer
Introduction. In clinical settings, nodular projection (NP) and cord sign (CS) at the tumor edge and irregular nodules (IN) in the mesorectum often appeared together with extramural vascular invasion (EMVI). We aim to evaluate the diagnostic efficiency of the MRI morphology of primary tumor in predicting EMVI in patients with rectal cancer (RC). Methods. This retrospective study included 156 patients with RC. Clinical and imaging factors including NP at the primary tumor’s edge, CS at the primary tumor’s edge, maximal extramural depth (EMD), IN in the mesorectum, growth pattern, tumor length, range of rectal wall invaded (RRWI) by tumor, peritoneal reflex invasion by surgery, and pathology-proven local node involvement (PLN) were evaluated. Then, ROC curve was drawn to depict the meaningful indicators in multivariate analyses. Results. There were 53 (34%) patients with pathological extramural venous invasion (pEMVI). Among the clinical and imaging factors evaluated, NP, CS, IN, EMD, PLN, differentiation, and peritoneal reflex invasion were significantly associated with pEMVI. NP and PLN were independent predictors of EMVI. Areas under the ROC curve (AUC) of NP for prediction of EMVI was 0.82 (95% CI, 0.74–0.90), with a sensitivity of 73.58%, a specificity of 90.29%, a positive predictive value (PPV) of 75.59%, a negative predictive value (NPV) of 86.92%, and an accuracy of 84.62%, respectively. Conclusions. Patients with primary tumor with EMVI usually showed NP and CS. NP was an independent predictor of EMVI and helpful for the diagnosis of EMVI in RC patients.
Study of Endogenous Paramagnetic Centers in Biological Systems from Different Areas
Plant leaves (Eldar pine (Pinus eldarica M.), fig (Ficus carica L.), and olive (Olea europaea L.)), collected in territories with different ecological conditions, of the Absheron Peninsula (Azerbaijan Republic) were studied by electron paramagnetic resonance spectroscopy (EPR). The generation of nanophase iron oxide magnetic particles in biological systems under the influence of stress factors was revealed. It was found that the process of biomineralization plays a role in the formation of biogenic iron oxide magnetic nanoparticles in plants and the generation of magnetite crystals in biological tissues, and stress factors have a stimulating effect on this phenomenon.
Electromagnetic Simulation of Signal Distribution of Various RF Endoluminal Loop Geometries with Coil Orientation: Towards a Reconfigurable Design
With the objective of improving MR endoluminal imaging of the colonic wall, electromagnetic simulations of different configurations of single-layer and double-layer, and double-turn endoluminal coil geometries were run. Indeed, during colon navigation, variations in coil orientation with respect to B0 are bound to occur, leading to impaired image acquisition due to a loss of signal uniformity. In this work, three typical coil orientations encountered during navigation were chosen and the resulting signal uniformity of the different geometries was investigated through the simulated values. Sampling this quantity over a circle of radius r enabled us to calculate the coefficient of variation (= standard deviation/mean) for this given distance. This procedure was repeated for mm, which represents the region of interest in the colon. Our results show that single-loop and double-layer geometries could provide complementary solutions for improved signal uniformity. Finally, using four microelectromechanical system switches, we proposed the design of a reconfigurable endoluminal coil able to switch between those two geometries while also ensuring the active decoupling of the endoluminal coil during the RF transmission of an MR experiment.