Notes

Intensifying macular ischemia throughout retinal vasculopathy with cerebral leukodystrophy.
In per-recording classification, the proposed technique using the linear discriminant analysis model outperformed the existing apnea detection approaches by achieving the accuracy of 100%. The algorithm also provided the best agreement between the estimated and reference apnea-hypopnea index (AHI) values. These results show that the algorithm has the potential to be used for home-based apnea screening systems.We develop a fully automated QA process to compare the image quality of all kV CBCT protocols on a Halcyon linac with ring gantry design, and evaluate image quality stability over a 10-month period. A total of 19 imaging scan and reconstruction protocols were characterized with measurement on a newly released QUART phantom. A set of image analysis algorithms were developed and integrated into an automated analysis suite to derive key image quality metrics, including HU value accuracy on density inserts, HU uniformity using the background plate, high contrast resolution with the modulation transfer function (MTF) from the edge profiles, low contrast resolution using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), slice thickness with the air gap modules, and geometric accuracy with the diameter of the phantom. Image quality data over 10 months was tracked and analyzed to evaluate the stability of the Halcyon kV imaging system. Futibatinib The HU accuracy over all 19 protocols is within tolerance (±50HU). The maximum uniformity deviation is 12.2 HU. The SNR and CNR, depending on the protocol selected, range from 18.5-911.9 and 1.9-102.8, respectively. A much-improved SNR and CNR were observed for iterative reconstruction (iCBCT) modes and protocols designed for large subjects over low dose and fast scanning modes. The Head and Image Gently protocols have the greatest high contrast resolution with MTF10% over 1 lp/mm and MTF50% over 0.6 lp/mm. The iCBCT mode slightly improved the MTF10% and MTF50% compared to the Feldkamp-Davis-Kress approach. The slice thickness (maximum error of 0.31 mm) and geometry metrics (maximum error of 0.7 mm) are all within tolerance (±0.5 mm for slice thickness and ±1 mm for geometry metrics). The long-term study over 10-month showed no significant drift for all key image quality metrics, which indicated the kV CBCT image quality is stable over time.Nowadays, with the increasing number of people who suffer from cardiovascular diseases such as irregular heartbeats (arrhythmia), there is a vital need to pay more attention to healthcare conditions. Therefore, the production of smart biomedical garments becomes of great necessity. The first step of manufacturing such smart garments is to build an electrocardiogram (ECG) analysis system. In this paper, the premature ventricular contraction (PVC), which is a serious life-threatening cardiovascular condition, is recognised. In addition, an improved template matching technique is developed, implemented, and evaluated to identify the irregularity of PVC beats in the QRS complex and T wave. The improvement in this technique is that a PVC recogniser is established by analysing the maximum and minimum correlation coefficient values instead of the maximum values only. Moreover, a sufficient number of features are relied upon for the accurate detection of PVC beats. The template matching algorithm is evaluated on the MIT-BIH arrhythmia, St. Petersburg Institute of Cardiological Technics (INCART), QT, MIT-BIH Supraventricular Arrhythmia, and Fantasia databases. The results show a valuable accuracy enhancement when compared with those of other recent approaches.
Quantification in positron emission tomography (PET) is subject to bias due to physical and technical limitations. The goal of quantitative harmonization is to achieve comparable measurements between different scanners, thus enabling multicenter clinical trials. Clinical guidelines, such as those from the European Association of Nuclear Medicine (EANM), recommend harmonizing PET reconstructions to bring contrast recovery coefficients (CRCs) within specifications. However, these harmonized reconstructions can show quantitative biases. In this work we improve harmonization by using a novel adaptive filtering scheme. Our goal was to obtain low quantification bias and high peak signal to noise ratio (PSNR) values at the same time.

a novel three-stage adaptive denoising filter was implemented. Filter parameters were optimized to achieve both high PSNR in a digital brain phantom and low quantitative bias of maximum CRC values (CRCmax) obtained from a National Electrical Manufacturers Association (NEMA) PET imagd the quantification variability was reduced when compared with standard reconstructions.
Our three-stage adaptive filter achieved state-of-the-art quantitative performance for PET imaging. Harmonization tolerances with lower bias and variance than EANM guidelines were achieved for a variety of scanner models. CRCmax values were close to unity and the quantification variability was reduced when compared with standard reconstructions.Cellular growth of enclosed cells in core-shell microcapsules is a key element for the practical use of the device in tissue engineering and biopharmaceutical fields. We developed alginate derivative microcapsules with a liquid core template by horseradish peroxidase crosslinking using an integrated coaxial microfluidic device by electrospray system. The cells and gelatin solution were extruded from the inner channel of coaxial microfluidic device and alginate possessing phenolic moieties (Alg-Ph) and horseradish peroxidase (HRP) flowed from the outer channel. link2 In open electric filed, concentric drops of the two coaxial fluids broken up into microdrops and sprayed into the gelling bath containing hydrogen peroxide to instantly gel alginate in the shell fluid before the two fluids got mixed or gelatin dispersed in a gelling bath. link3 The core-shell structure of about 350 μm in diameter and gel membrane of 42 μm was developed by optimization of operational parameters including electrical voltage, flow rate and concentration of polymers. The physical properties of microcapsules including swelling and mechanical resistance proved the applicability of fabricated vehicles for cell culture systems in vitro and in vivo. The viability of enclosed fibroblast cells in generated core-shell microcapsule was more than 90% which is sufficiently high compared with it before encapsulation. The growth profile and behavior of cells in microcapsules showed appropriate cell growth and the possibility of fabrication of spherical tissue was confirmed through degradation of hydrogel membrane. These results validate the significant potential of coaxial electrospray system and HRP-mediated hydrogelation in the fabrication of cell-laden core-shell microcapsule for tissue engineering and regenerative medicine.
The purpose of this study was to examine RBE variation as a function of distance from the radioactive source, and the potential impact of this variation on a realistic prostate brachytherapy treatment plan.

Three brachytherapy sources (
I,
Ir, and
Yb) were modelled in Geant4 Monte Carlo code, and the resulting electron energy spectrum in water in 3D space around these sources was scored (voxel size of 2 mm
). With this energy spectrum, microdosimetric techniques were used to calculate the maximum RBE, RBE
, as a function of distance from the source. RBE
of
I relative to
Ir was calculated in order to validate simulations against literature; all other RBE
calculations were done by normalizing electron fluence at various distances to the source position. In order to examine the impact of RBE
variation in treatment planning, a realistic
Ir prostate plan was re-evaluated in terms of RBE instead of absorbed dose.

The RBE
of
I,
Ir, and
Yb at 8 cm away from the source was 0.994 (+/-0.002), 1.030 (+/-0.003), and 1.066 (+/-0.008), respectively. RBE
in the HDR prostate treatment plan exhibited several hot (+3.6% in RBE
) spots.

The large increase RBE
observed in
Yb has not yet been described in the literature. Despite the presence of radiobiological hotspots in the HDR treatment, these variations are likely nominal and clinically insignificant.
The large increase RBEM observed in 169Yb has not yet been described in the literature. Despite the presence of radiobiological hotspots in the HDR treatment, these variations are likely nominal and clinically insignificant.Tracer kinetic modelling, based on dynamic 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is used to quantify glucose metabolism in humans and animals. Knowledge of the arterial input-function (AIF) is required for such measurements. Our aim was to explore two non-invasive machine learning-based models, for AIF prediction in a small-animal dynamic FDG PET study. 7 tissue regions were delineated in images from 68 FDG PET/computed tomography mouse scans. Two machine learning-based models were trained for AIF prediction, based on Gaussian processes (GP) and a long short-term memory (LSTM) recurrent neural network, respectively. Because blood data were unavailable, a reference AIF was formed by fitting an established AIF model to vena cava and left ventricle image data. The predicted and reference AIFs were compared by the area under curve (AUC) and root mean square error (RMSE). Net-influx rate constants, K i , were calculated with a two-tissue compartment model, using both predicted and reference AIFs for three tissue regions in each mouse scan, and compared by means of error, ratio, correlation coefficient, P value and Bland-Altman analysis. The impact of different tissue regions on AIF prediction was evaluated by training a GP and an LSTM model on subsets of tissue regions, and calculating the RMSE between the reference and the predicted AIF curve. Both models generated AIFs with AUCs similar to reference. The LSTM models resulted in lower AIF RMSE, compared to GP. K i from both models agreed well with reference values, with no significant differences. Myocardium was highlighted as important for AIF prediction, but AIFs with similar RMSE were obtained also without myocardium in the input data. Machine learning can be used for accurate and non-invasive prediction of an image-derived reference AIF in FDG studies of mice. We recommend the LSTM approach, as this model predicts AIFs with lower errors, compared to GP.Nuclear Medicine imaging is an important modality to follow up abnormalities of thyroid function tests and to uncover and characterize thyroid nodules either de novo or as previously seen on other imaging modalities, namely ultrasound. In general, the hypofunctioning 'cold' nodules pose a higher malignancy potential than hyperfunctioning 'hot' nodules, for which the risk is less then 1%. Hot nodules are detected by the radiologist as a region of focal increased radiotracer uptake, which appears as a density of pixels that is higher than surrounding normal thyroid parenchyma. Similarly, cold nodules show decreased density of pixels, corresponding to their decreased uptake of radiotracer, and are photopenic. Partly because Nuclear Medicine images have poor resolution, these density variations can sometimes be subtle, and a second reader computer-aided detection (CAD) scheme that can highlight hot/cold nodules has the potential to reduce false negatives by bringing the radiologists' attention to the occasional overlooked nodules.
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