PURPOSE: Dual velocity encoding PC-MRI can produce spurious artifacts when using high ratios of velocity encoding values (VENCs), limiting its ability to generate high-quality images across a wide range of encoding velocities. This study aims to propose and compare dual-VENC correction methods for such artifacts. THEORY AND METHODS: Two denoising approaches based on spatiotemporal regularization are proposed and compared with a state-of-the-art method based on sign correction. Accuracy is assessed using simulated data from an aorta and brain aneurysm, as well as 8 two-dimensional (2D) PC-MRI ascending aorta datasets. Two temporal resolutions (30,60) ms and noise levels (9,12) dB are considered, with noise added to the complex magnetization. The error is evaluated with respect to the noise-free measurement in the synthetic case and to the unwrapped image without additional noise in the volunteer datasets. RESULTS: In all studied cases, the proposed methods are more accurate than the Sign Correction technique. Using simulated 2D+T data from the aorta (60 ms, 9 dB), the Dual-VENC (DV) error 0.82±0.07$$ 0.82\pm 0.07 $$ is reduced to: 0.66±0.04$$ 0.66\pm 0.04 $$ (Sign Correction); 0.34±0.04$$ 0.34\pm 0.04 $$ and 0.32±0.04$$ 0.32\pm 0.04 $$ (proposed techniques). The methods are found to be significantly different (p-value <0.05$$ <0.05 $$ ). Importantly, brain aneurysm data revealed that the Sign Correction method is not suitable, as it increases error when the flow is not unidirectional. All three methods improve the accuracy of in vivo data. CONCLUSION: The newly proposed methods outperform the Sign Correction method in improving dual-VENC PC-MRI images. Among them, the approach based on temporal differences has shown the highest accuracy.

• MeSH
• algoritmy * MeSH
• aorta * diagnostické zobrazování   MeSH
• artefakty * MeSH
• fantomy radiodiagnostické MeSH
• interpretace obrazu počítačem metody   MeSH
• intrakraniální aneurysma diagnostické zobrazování   MeSH
• lidé MeSH
• magnetická rezonanční tomografie * metody   MeSH
• mozek diagnostické zobrazování   MeSH
• počítačová simulace MeSH
• počítačové zpracování obrazu * metody   MeSH
• poměr signál - šum * MeSH
• reprodukovatelnost výsledků MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

• MeSH
• absorpce v dýchacích cestách MeSH
• diagnostické techniky dýchacího ústrojí * klasifikace   přístrojové vybavení   MeSH
• diagnostické zobrazování * klasifikace   metody   přístrojové vybavení   MeSH
• interpretace obrazu počítačem metody   přístrojové vybavení   MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• nemoci dýchací soustavy diagnostické zobrazování   MeSH
• ultrasonografie MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• přehledy MeSH

• MeSH
• arachnoidální cysty diagnostické zobrazování   MeSH
• dospělí MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• meningokéla diagnostické zobrazování   MeSH
• mozkomíšní mok * diagnostické zobrazování   MeSH
• neurozobrazování * metody   MeSH
• pooperační komplikace diagnostické zobrazování   MeSH
• výsledek terapie MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• Publikační typ
• kazuistiky MeSH

Introduction: Measurement of an- hippocampal area or volume is useful in clinical practice as a supportive aid for diagnosis of Alzheimer's disease. Since it is time-consuming and not simple, it is not being used very often. We present a simplified protocol for hippocampal atrophy evaluation based on a single optimal slice in Alzheimer's disease. Methods: We defined a single optimal slice for hippocampal measurement on brain magnetic resonance imaging (MRI) at the plane where the amygdala disappears and only the hippocampus is present. We compared an absolute area and volume of the hippocampus on this optimal slice between 40 patients with Alzheimer disease and 40 age-, education- and gender-mateched elderly controls. Furthermore, we compared these results with those relative to the size of the brain or the skull: the area of the optimal slice normalized to the area of the brain at anterior commissure and the volume of the hippocampus normalized to the total intracranial volume. Results: Hippocampal areas on the single optimal slice and hippocampal volumes on the left and right in the control group were significantly higher than those in the AD group. Normalized hippocampal areas and volumes on the left and right in the control group were significantly higher compared to the AD group. Absolute hippocampal areas and volumes did not significantly differ from corresponding normalized hippocampal areas as well as normalized hippocampal volumes using comparisons of areas under the receiver operating characteristic curves. Conclusion: The hippocampal area on the well-defined optimal slice of brain MRI can reliably substitute a complicated measurement of the hippocampal volume. Surprisingly, brain or skull normalization of these variables does not add any incremental differentiation between Alzheimer disease patients and controls or give better results.

• MeSH
• Alzheimerova nemoc diagnostické zobrazování   MeSH
• hipokampus diagnostické zobrazování   MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• senioři MeSH
• zobrazování trojrozměrné metody   MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

• MeSH
• diagnostické zobrazování * klasifikace   MeSH
• digitální subtrakční angiografie MeSH
• dítě MeSH
• interpretace obrazu počítačem metody   MeSH
• jednofotonová emisní výpočetní tomografie MeSH
• lidé MeSH
• nemoci centrálního nervového systému * diagnostické zobrazování   MeSH
• pozitronová emisní tomografie metody   MeSH
• radiofarmaka MeSH
• Check Tag
• dítě MeSH
• lidé MeSH

Even though MRI visualization of white matter lesions is pivotal for the diagnosis and management of multiple sclerosis (MS), the issue of detecting diffuse brain tissue damage beyond the apparent T2-hyperintense lesions continues to spark considerable interest. Motivated by the notion that rotating frame MRI methods are sensitive to slow motional regimes critical for tissue characterization, here we utilized novel imaging protocols of rotating frame MRI on a clinical 3 Tesla platform, including adiabatic longitudinal, T1ρ, and transverse, T2ρ, relaxation methods, and Relaxation Along a Fictitious Field (RAFF) in the rotating frame of rank 4 (RAFF4), in 10 relapsing-remitting multiple sclerosis patients and 10 sex- and age-matched healthy controls. T1ρ, T2ρ and RAFF4 relaxograms extracted from the whole white matter exhibited a significant shift towards longer relaxation time constants in MS patients as compared to controls. T1ρ and RAFF4 detected alterations even when considering only regions of normally appearing white matter (NAWM), while other MRI metrics such as T1w/T2w ratio and diffusion tensor imaging measures failed to find group differences. In addition, RAFF4, T2ρ and, to a lesser extent, T1ρ showed differences in subcortical grey matter structures, mainly hippocampus, whereas no functional changes in this region were detected in resting-state functional MRI metrics. We conclude that rotating frame MRI techniques are exceptionally sensitive methods for the detection of subtle abnormalities not only in NAWM, but also in deep grey matter in MS, where they surpass even highly sensitive measures of functional changes, which are often suggested to precede detectable structural alterations. Such abnormalities are consistent with a wide spectrum of different, but interconnected pathological features of MS, including the loss of neuronal cells and their axons, decreased levels of myelin even in NAWM, and altered iron content.

• MeSH
• bílá hmota diagnostické zobrazování   patologie   MeSH
• dospělí MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• mozek patologie   MeSH
• neurozobrazování metody   MeSH
• průřezové studie MeSH
• relabující-remitující roztroušená skleróza diagnostické zobrazování   patologie   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH

Ultrasound imaging of the thyroid gland is considered to be the best diagnostic choice for evaluating thyroid nodules in early stages, since it has been marked as cost-effective, non-invasive and risk-free. Computer aided diagnosis (CAD) systems can offer a second opinion to radiologists, thereby increasing the overall diagnostic accuracy of ultrasound imaging. Although current CAD systems exhibit promising results, their use in clinical practice is limited. Some of the main limitations are that the majority use direction dependent features so, they are only compatible with static images in just one plane (axial or longitudinal), requiring precise segmentation of a nodule. Our intention has been to design a CAD system which will use only direction independent features i.e., not dependent upon the orientation or inclination angle of the ultrasound probe when acquiring the image. In this study, 60 thyroid nodules (20 malignant, 40 benign) were divided into small patches of 17 × 17 pixels, which were then used to extract several direction independent features by employing Two-Threshold Binary Decomposition, a method that decomposes an image into the set of binary images. The features were then used in Random Forests (RF) and Support Vector Machine (SVM) classifiers to categorize nodules into malignant and benign classes. Classification was evaluated using group 10-fold cross-validation method. Performance on individual patches was then averaged to classify whole nodules with the following results: overall accuracy, sensitivity, specificity and area under receiver operating characteristics (ROC) curve: 95%, 95%, 95%, 0.971 for RF and; 91.6%, 95%, 90%, 0.965 for SVM respectively. The patch-based CAD system we present can provide support to radiologists in their current diagnosis of thyroid nodules, whereby it can increase the overall accuracy of ultrasound imaging.

• MeSH
• diagnóza počítačová metody   MeSH
• diferenciální diagnóza MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• senzitivita a specificita MeSH
• support vector machine * MeSH
• ultrasonografie metody   MeSH
• uzle štítné žlázy diagnostické zobrazování   patologie   MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Purpose To develop a deep learning-based method for fully automated quantification of left ventricular (LV) function from short-axis cine MR images and to evaluate its performance in a multivendor and multicenter setting. Materials and Methods This retrospective study included cine MRI data sets obtained from three major MRI vendors in four medical centers from 2008 to 2016. Three convolutional neural networks (CNNs) with the U-NET architecture were trained on data sets of increasing variability: (a) a single-vendor, single-center, homogeneous cohort of 100 patients (CNN1); (b) a single-vendor, multicenter, heterogeneous cohort of 200 patients (CNN2); and (c) a multivendor, multicenter, heterogeneous cohort of 400 patients (CNN3). All CNNs were tested on an independent multivendor, multicenter data set of 196 patients. CNN performance was evaluated with respect to the manual annotations from three experienced observers in terms of (a) LV detection accuracy, (b) LV segmentation accuracy, and (c) LV functional parameter accuracy. Automatic and manual results were compared with the paired Wilcoxon test, Pearson correlation, and Bland-Altman analysis. Results CNN3 achieved the highest performance on the independent testing data set. The average perpendicular distance compared with manual analysis was 1.1 mm ± 0.3 for CNN3, compared with 1.5 mm ± 1.0 for CNN1 (P < .05) and 1.3 mm ± 0.6 for CNN2 (P < .05). The LV function parameters derived from CNN3 showed a high correlation (r2 ≥ 0.98) and agreement with those obtained by experts for data sets from different vendors and centers. Conclusion A deep learning-based method trained on a data set with high variability can achieve fully automated and accurate cine MRI analysis on multivendor, multicenter cine MRI data. © RSNA, 2018 See also the editorial by Colletti in this issue.

• MeSH
• deep learning * MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé MeSH
• magnetická rezonance kinematografická metody   MeSH
• retrospektivní studie MeSH
• srdce - funkce komor fyziologie   MeSH
• srdeční komory diagnostické zobrazování   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

• Klíčová slova
• gingivální štěp, CBCT, dehiscence, augmentace,
• MeSH
• bolesti zubů etiologie   MeSH
• extrakce zubů MeSH
• fraktury zubů komplikace   MeSH
• implantace zubů metody   MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• parodontální chobot komplikace   MeSH
• řezáky diagnostické zobrazování   patologie   MeSH
• stomatochirurgické výkony metody   ošetřování   MeSH
• stomatologická protetika metody   MeSH
• výsledek terapie MeSH
• zubní náhrada ve spojení s implantáty * metody   MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• ženské pohlaví MeSH
• Publikační typ
• kazuistiky MeSH

Brain white matter fiber bundles in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) have abnormalities not usually seen in unaffected subjects. Ideal algorithm of the localization-specific properties in white matter integrity might reveal the changes of tissue properties varying along each tract, while previous studies only detected the mean DTI parameters of each fiber. The aim of this study was to investigate whether these abnormalities of nerve fiber tracts are localized to specific regions of the tracts or spread throughout and to analyze which of the examined fiber tracts are involved in the early stages of Alzheimer's disease. In this study, we utilized VBA, TBSS as well as AFQ together to comprehensively investigate the white matter fiber impairment on 25 CE patients, 29 MCI patients and 34 normal control (NC) subjects. Two tract profiles, fractional anisotropy (FA) and mean diffusivity (MD), were extracted to evaluate the white matter integrity at 100 locations along each of 20 fiber tracts and then we validated the results with 27 CE patients, 21 MCI patients and 22 NC from the ADNI cohort. Also, we compare the AFQ with VBA and TBSS in our cohort. In comparison with NC, AD patients showed widespread FA reduction in 25% (5 /20) and MD increase in 65%(13/20) of the examined fiber tracts. The MCI patients showed a regional FA reduction in 5% (1/20) of the examined fiber tracts (right cingulum cingulate) and MD increase in 5%(1/20) of the examined fiber tracts (left arcuate fasciculus). Among these changed tracts, only the right cingulum cingulate showed widespread disruption of myelin or/and fiber axons in MCI and aggravated deterioration in AD, findings supported by FA/MD changes both by the mean and FA changes by point wise methods and TBSS. And the AFQ findings from ADNI cohort showed some similarity with our cohort, especially in the pointwise comparison of MD profiles between AD vs NC. Furthermore, the pattern of white matter abnormalities was different across neuronal fiber tracts; for example, the MCI and AD patients showed similar FA reduction in the middle part of the right cingulum cingulate, and the anterior part were not damaged. However, the left arcuate fasciculus showed MD elevation located at the temporal part of the fibers in the MCI patients and expanding to the temporal and middle part of the fibers in AD patients. So, the AFQ may be an alternative complementary method of VBA and TBSS, and may provide new insights into white matter degeneration in MCI and its association with AD.

• MeSH
• Alzheimerova nemoc diagnostické zobrazování   patologie   MeSH
• bílá hmota diagnostické zobrazování   patologie   MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• nervová vlákna patologie   MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• zobrazování difuzních tenzorů metody   MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH