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[en] The authors compared measurements of hindfoot alignment on MR imaging with weight-bearing CT (WB-CT) to establish the degree of correlation. Forty-seven feet in 44 patients had weight-bearing CT and MRI studies performed on the same day. Hindfoot alignment on MRI was assessed by two radiologists who calculated tibiocalcaneal angle (TCA) and calcaneofibular ligament angle (CFLA). On WB-CT, foot ankle offset (FAO), calcaneal offset (CO) and hindfoot angle (HA) were assessed by a senior Foot and Ankle Surgeon using dedicated software. Pearson correlation coefficient was used to evaluate the correlation between these measurements. The study group comprised 27 males and 17 females with a mean age of 45 years (range 13–79 years). A statistically significant positive correlation was identified between TCA on MRI and all measurements of hindfoot alignment on WB-CT (p = 0.001–0.005). The CFLA on MRI only had significant correlation with CO on WB-CT (p = 0.03). A significant negative correlation was observed between both MRI parameters (p < 0.001). A highly significant correlation between tibiocalcaneal angle on non-weight-bearing ankle MR imaging and hindfoot alignment measurements on weight-bearing CT was identified.
[en] Dynamic PET (dPET) studies have been used until now primarily within research purposes. Although it is generally accepted that the information provided by dPET is superior to that of conventional static PET acquisitions acquired usually 60 min post injection of the radiotracer, the duration of dynamic protocols, the limited axial field of view (FOV) of current generation clinical PET systems covering a relatively small axial extent of the human body for a dynamic measurement, and the complexity of data evaluation have hampered its implementation into clinical routine. However, the development of new-generation PET/CT scanners with an extended FOV as well as of more sophisticated evaluation software packages that offer better segmentation algorithms, automatic retrieval of the arterial input function, and automatic calculation of parametric imaging, in combination with dedicated shorter dynamic protocols, will facilitate the wider use of dPET. This is expected to aid in oncological diagnostics and therapy assessment. The aim of this review is to present some general considerations about dPET analysis in oncology by means of kinetic modeling, based on compartmental and noncompartmental approaches, and parametric imaging. Moreover, the current clinical applications and future perspectives of the modality are outlined.
[en] To implement and to evaluate a compressed sensing (CS) reconstruction algorithm based on the sensitivity encoding (SENSE) combination scheme (CS-SENSE), used to reconstruct sodium magnetic resonance imaging (Na MRI) multi-channel breast data sets. In a simulation study, the CS-SENSE algorithm was tested and optimized by evaluating the structural similarity (SSIM) and the normalized root-mean-square error (NRMSE) for different regularizations and different undersampling factors (USF = 1.8/3.6/7.2/14.4). Subsequently, the algorithm was applied to data from in vivo measurements of the healthy female breast (n = 3) acquired at 7 T. Moreover, the proposed CS-SENSE algorithm was compared to a previously published CS algorithm (CS-IND). The CS-SENSE reconstruction leads to an increased image quality for all undersampling factors and employed regularizations. Especially if a simple 2 order total variation is chosen as sparsity transformation, the CS-SENSE reconstruction increases the image quality of highly undersampled data sets (CS-SENSE: SSIM = 0.234, NRMSE = 0.491 vs. CS-IND: SSIM = 0.201, NRMSE = 0.506). The CS-SENSE reconstruction supersedes the need of CS weighting factors for each channel as well as a method to combine single channel data. The CS-SENSE algorithm can be used to reconstruct undersampled data sets with increased image quality. This can be exploited to reduce total acquisition times in Na MRI.
[en] To evaluate the added value of DWI, qualitative proton MR spectroscopy (H-MRS) and dynamic contrast-enhanced perfusion (DCE-P) to conventional MRI in differentiating benign and malignant non-fatty soft tissue tumors (NFSTT). From November 2009 to August 2017, 288 patients with NFSTT that underwent conventional and advanced MRI were prospectively evaluated. The study was approved by the local ethics committee. All patients signed an informed consent. A musculoskeletal (R1) and a general (R2) radiologist classified all tumors as benign, malignant, or indeterminate according to morphologic MRI features. Then, DWI, H-MRS, and DCE-P data of indeterminate tumors were analyzed by two additional radiologists (R3 and R4). Advanced techniques were considered individually and in combination for tumor benign-malignant differentiation using histology as the gold standard. There were 104 (36.1%) malignant and 184 (63.9%) benign tumors. Conventional MRI analysis classified 99 tumors for R1 and 135 for R2 as benign or malignant, an accuracy for the identification of malignancy of 87.9% for R1 and 83.7% for R2, respectively. There were 189 indeterminate tumors for R1. For these tumors, the combination of DWI and H-MRS yielded the best accuracy for malignancy identification (77.4%). DWI alone provided the best sensitivity (91.8%) while the combination of DCE-P, DWI, and H-MRS yielded the best specificity (100%). The reproducibility of the advanced imaging parameters was considered good to excellent (Kappa and ICC > 0.86). An advanced MRI evidence-based evaluation algorithm was proposed allowing to characterize 28.1 to 30.1% of indeterminate non-myxoid tumors. The prioritized use of advanced MRI techniques allowed to decrease by about 30% the number of non-myxoid NFSTT deemed indeterminate after conventional MRI analysis alone.
[en] To compare liver stiffness measurement (LSM) provided by Canon 2D-shear wave elastography (2D-SWE) and transient elastography (TE), the latter being the reference method. Prospective study conducted in four European centres from 2015 to 2016 including patients with various chronic liver diseases who had LSMs with both 2D-SWE and TE on the same day. Median of 10 valid measurements (in kPa) was used for comparison using paired t test, Pearson correlation, intraclass correlation coefficient (ICC) and Bland-Altman plot. The ability of 2D-SWE to stratify patient according to recognised LSM-TE thresholds was assessed by ROC curve analysis. Six hundred forty patients were scanned, where 593 (92.7%), 572 (89.4%) and 537 (83.9%) had reliable LSMs by TE, 2D-SWE and both combined, respectively. In the latter (n = 537, 310 [57.7%] male, mean 55.3 ± 14.8 years), median LSM-TE and LSM-2D-SWE had a mean of 10.1 ± 9.4 kPa (range 2.4–75) and 9.1 ± 6.1 kPa (range 3.6–55.7) (paired t test: p < 0.001), respectively. These were significantly correlated (Pearson r = 0.932, p < 0.001, ICC 0.850 (0.825–0.872), bias 0.99 ± 4.33 kPa [95% limits of agreement − 9.48 to + 7.49] with proportional error towards higher LSM values). LSM-2D-SWE values significantly increased with TE categories (ANOVA: p < 0.001). AUROCs ranged from 0.935 ± 0.010 (95% CI 0.910–0.954) to 0.973 ± 0.009 (95% CI 0.955–0.985), resulting in correct classification of 390/537 (73%) patients. Three 2D-SWE measurements were sufficient for reliable LSMs. LSM using 2D-SWE correlates well with TE. It tends to underestimate higher stages of liver fibrosis but correctly classifies the majority of patients. It may be used in TE-derived algorithms to manage patients.
[en] To assess the coronary atherosclerosis profile by coronary computed tomography angiography (CTA) in patients with end-stage liver disease (ESLD) due to alcohol-related liver disease (ARLD) evaluated for liver transplantation (LT), in a retrospective matched case-controlled cohort study. One hundred forty patients (age 60.6 years ± 9.8, 20.7% females) who underwent coronary CTA were included. Seventy patients with ESLD due to ARLD (ESLD-alc) were propensity score (1:1) matched for age, gender, and the major 5 cardiovascular risk factors with healthy controls. CTA analysis included the following: stenosis severity according to CAD-RADS as (0) = no, (1) minimal < 25%, (2) mild 25–50%, (3) moderate 50–70%, and (4) severe > 70% stenosis, total mixed plaque burden weighted for non-calcified component (G-score) and high-risk plaque criteria (Napkin-Ring, low attenuation plaque, spotty calcification, positive remodeling). Prevalence of coronary artery disease (CAD) was high (84.4%) in the ESLD-alc group but similar to controls. Stenosis severity was similar (CAD-RADS, 1.9 vs. 2.2, p = 0.289). High-grade stenosis (> 70%) was observed in 12.5% of ESLD-alc patients. High-risk plaques were less frequent in the ESLD-alc cohort as compared to controls (4.5% vs. 37.5%, p < 0.001), and total mixed plaque burden was lower (G-score, 4.9 versus 7.4, p = 0.001). Plaque density was lower in controls (56.6HU ± 3.2 vs. 91.3HU ± 4.5, p = 0.007) indicating more lipid-rich in controls, but higher mixed fibro-calcific plaque component in those with alcohol-related ESLD. Patients with alcohol-related ESLD exhibit more mixed fibro-calcified plaques but less plaque with high-risk features and less fibro-fatty plaque burden, while total CAD prevalence is high.
[en] We have generated a system concept for a non-destructive assay (NDA) system to certify identifed isotopes and their activity concentrations for radioactive waste in a large container. Various optimization studies have evaluated the system performance in terms of the MDA (minimum detectable activity) results using the Monte Carlo simulation in conjunction with experimental studies. The proposed system consists of a total of eight HPGe (high-pressure germanium) detectors: four detectors on the top and the other four detectors on the bottom. The top and the bottom detector arrays are aligned and face each other. This detector arrangement has advantages in employing the attenuation correction as proposed by T. Chang [IEEE Trans.Nucl. Sci. NS-25, 638 (1978)]. We also found that the UFOV (useful feld of view) of the detector highly infuences the system efciency, which leads to an improvement in the MDA performance. However, while the wider FOV of the detector improves the detection efciency by allowing incoming radiation from other segmented volumes, it may sufer from nonuniform performance or increased errors in estimating an activity concentration for each segmented volume. To prevent such potential errors in employing the wider FOV, we have proposed an activity estimation algorithm, a so-called 'fine volume reconstruction', based on a back-projection method that estimates the activity concentration of each segmented volume. We demonstrate the feasibility of the conceptual system for use as a free release assay system for ISO containers up to a size of 2.4 x 6.0 x 1.3 m3 (W x L x H). The detector efciency was about four times higher than those of typical commercial systems. Future studies include fne-tuning of the activity reconstruction algorithm and a validation study on various materials and non-uniform activity concentrations.
[en] When evolution algorithms are used to unfold the neutron energy spectrum, fitness function design is an important fundamental work for evaluating the quality of the solution, but it has not attracted much attention. In this work, we investigated the performance of eight fitness functions attached to the genetic algorithm (GA) and the differential evolution algorithm (DEA) used for unfolding four neutron spectra selected from the IAEA 403 report. Experiments show that the fitness functions with a maximum in the GA can limit the ability of the population to percept the fitness change, but the ability can be made up in the DEA. The fitness function with a feature penalty term helps to improve the performance of solutions, and the fitness function using the standard deviation and the Chi-squared result shows the balance between the algorithm and the spectra. The results also show that the DEA has good potential for neutron energy spectrum unfolding. The purposes of this work are to provide evidence for structuring and modifying the fitness functions and to suggest some genetic operations that should receive attention when using the fitness function to unfold neutron spectra.
[en] Energy is a critical issue in vehicle routing. UAV's or Drones have been the fundamental way in activities where a human has their limited skills to do. Drones save too much time in accomplishing such tasks. The growing usage of drones by commercial firms has contributed to developing a new Vehicle Routing Problem with Drones (VRPD). Self-driving cars and aircraft can be used to transfer packages from one place to another to customers. Vehicles and drones could have dependent or independent deliveries. A drone takes off from a vehicle for package delivery and then returns to the same vehicle after the delivery as long as the drone's energy restrictions are met. This paper tries to model the UAV's routing process to understand the problem clearly. Besides, the paper proposes a modified version of the Brainstorming algorithm to find the best routing for drones. Experiments are carried out in numerous environments and with various scenarios. The findings indicate the suggested algorithm to solve the drone routing problem is much effective with 70% enhancement than the random routing. (author)