Classification of brain lesions using a machine learning approach with cross-sectional ADC value dynamics.

Diffusion-weighted imaging (DWI) and its numerical expression via apparent diffusion coefficient (ADC) values are commonly utilized in non-invasive assessment of various brain pathologies. Although numerous studies have confirmed that ADC values could be pathognomic for various ring-enhancing lesions (RELs), their true potential is yet to be exploited in full. The article was designed to introduce an image analysis method allowing REL recognition independently of either absolute ADC values or specifically defined regions of interest within the evaluated image. For this purpose, the line of interest (LOI) was marked on each ADC map to cross all of the RELs' compartments. Using a machine learning approach, we analyzed the LOI between two representatives of the RELs, namely, brain abscess and glioblastoma (GBM). The diagnostic ability of the selected parameters as predictors for the machine learning algorithms was assessed using two models, the k-NN model and the SVM model with a Gaussian kernel. With the k-NN machine learning method, 80% of the abscesses and 100% of the GBM were classified correctly at high accuracy. Similar results were obtained via the SVM method. The proposed assessment of the LOI offers a new approach for evaluating ADC maps obtained from different RELs and contributing to the standardization of the ADC map assessment.

Measurement-Based Domain Parameter Optimization in Electrical Impedance Tomography Imaging.

This paper discusses the optimization of domain parameters in electrical impedance tomography-based imaging. Precise image reconstruction requires accurate, well-correlated physical and numerical finite element method (FEM) models; thus, we employed the Nelder-Mead algorithm and a complete electrode model to evaluate the individual parameters, including the initial conductivity, electrode misplacement, and shape deformation. The optimization process was designed to calculate the parameters of the numerical model before the image reconstruction. The models were verified via simulation and experimental measurement with single source current patterns. The impact of the optimization on the above parameters was reflected in the applied image reconstruction process, where the conductivity error dropped by 6.16% and 11.58% in adjacent and opposite driving, respectively. In the shape deformation, the inhomogeneity area ratio increased by 11.0% and 48.9%; the imprecise placement of the 6th electrode was successfully optimized with adjacent driving; the conductivity error dropped by 12.69%; and the inhomogeneity localization exhibited a rise of 66.7%. The opposite driving option produces undesired duality resulting from the measurement pattern. The designed optimization process proved to be suitable for correlating the numerical and the physical models, and it also enabled us to eliminate imaging uncertainties and artifacts.

In vitro motor patterns and electrophysiological changes in patients with colonic diverticular disease.

PURPOSE: The underlying mechanism responsible for motility changes in colonic diverticular disease (DD) is still unknown. In the present study, our aim was to investigate the structural and in vitro motor changes in the sigmoid colon of patients with DD. METHODS: Muscle bath, microelectrodes and immunohistochemical techniques were performed with samples obtained from the left and sigmoid colon of patients with DD and compared with those of patients without DD. RESULTS: The amplitude and area under the curve of the spontaneous rhythmic phasic contractions were greatly reduced in patients with DD whereas their frequency and tone remained unaltered. Electrical field stimulation induced a neurally mediated, enhanced ON-contraction (amplitude) in patients with DD and increased the duration of latency of OFF-contractions. The resting membrane potential of smooth muscle cells was hyperpolarized and the amplitude of the inhibitory junction potential was increased in patients with DD. In contrast, no significant histological differences were observed in patients with DD as smooth muscle (circular and longitudinal layers), interstitial cells of Cajal, glial cells and myenteric neurons densities remained unaltered. CONCLUSIONS: Sigmoid strips from patients with asymptomatic DD showed an altered motor pattern with reduced spontaneous motility and enhanced neurally mediated colonic responses involving both excitatory and inhibitory motor pathways. No major neural and muscular structural elements were detected at this stage of the disease. These findings could be valuable in understanding the pathophysiology of this prevalent digestive disease.