Digital fundus image quality assessment

Diabetic retinopathy (DR) is a disease caused by complications of diabetes. It starts asymptomatically and can end in blindness. To detect it, doctors use special fundus cameras that allow them to register images of the retina in the visible range of the spectrum. On these images one can see features, which determine the presence of DR and its grade. Researchers around the world are developing systems for the automated analysis of fundus images. At present, the level of accuracy of classification of diseases caused by DR by systems based on machine learning is comparable to the level of qualified medical doctors.The article shows variants for representation of the retina in digital images by different cameras. We define the task to develop a universal approach for the image quality assessment of a retinal image obtained by an arbitrary fundus camera. It is solved in the first block of any automated retinal image analysis system. The quality assessment procedure is carried out in several stages. At the first stage, it is necessary to perform binarization of the original image and build a retinal mask. Such a mask is individual for each image, even among the images recorded by one camera. For this, a new universal retinal image binarization algorithm is proposed. By analyzing result of the binarization, it is possible to identify and remove imagesoutliers, which show not the retina, but other objects. Further, the problem of no-reference image quality assessment is solved and images are classified into two classes: satisfactory and unsatisfactory for analysis. Contrast, sharpness and possibility of segmentation of the vascular system on the retinal image are evaluated step by step. It is shown that the problem of no-reference image quality assessment of an arbitrary fundus image can be solved.Experiments were performed on a variety of images from the available retinal image databases.

Frequent Quantitation of Circulating Tumor Cells Predictive of Real-Time Therapy Response

Precision medicine is playing an increasingly important role in cancer management and treatment. Specifically in the field of oncology, circulating tumor cells (CTCs) hold significant promise in enabling non-invasive prognostication and near real-time monitoring to individualize treatments. In this study, we present strong associations between CTC subtype counts with treatment response and tumor staging in lung, nasopharyngeal and breast cancers. Longitudinal analysis of CTC count changes over short-time windows further reveals the ability to predict treatment response close to real-time. Our findings demonstrate the suitability of CTCs as a definitive blood-based metric for continuous treatment monitoring. Robust processing of high-throughput image data, explainable classification of CTC subtypes and accurate quantification were achieved using an in-house image analysis system CTC-Quant, which showed excellent agreement with expert opinion upon extensive validation.

Early-Age Mechanical Properties of 3D-Printed Mortar with Spent Garnet

This study determines the effect of spent garnet as a replacement for natural sand in 3D-printed mortar at early ages. Five mixes with different spent garnet amounts were prepared (0%, 25%, 50%, 75% and 100% by volume). The ratio of binder to aggregate remained unchanged. In all mixes the water/binder ratio was assumed as a constant value of 0.375. Tests were performed to confirm the printability of the mix (a path quality test using a gantry robot with an extruder). Determinations of key buildability properties of the mix (green strength and Young’s Modulus) during uniaxial compressive strength at 15 min, 30 min and 45 min after adding water were conducted. A hydraulic press and the GOM ARAMIS precision image analysis system were used to conduct the study. The results showed that an increase in spent garnet content caused a decrease in green strength and Young’s Modulus (up to 69.91% and 80.37%, respectively). It was found that to maintain proper buildability, the recommended maximum replacement rate of natural sand with garnet is 50%. This research contributes new knowledge in terms of using recycled waste in the 3D printing technology of cementitious materials.

Reproducibility of effects of the homeopathic dilutions 14x - 30x of gibberellic acid on growth of Lemna gibba L.

Background: Reproducibility of investigations in homeopathy is still challenging. Duckweed (Lemna gibba L.), a monocotyledonous waterplant which mostly reproduces vegetatively and therefore builds genetically identical clones, may be a suitable test system for standardised trials. Aims: This study investigated if formerly observed effects of gibberellic acid 14x – 30x on growth of Lemna gibba were reproducible. Methododology: Duckweed was grown in dilutions of gibberellic acid (14x–30x) as well as once succussed (c1) and unsuccussed (c0) water control. Area-related growth rate for day 0–7 was determined by a computerised image analysis system. Three series including five independent blinded and randomised experiments each were carried out in the same way as in the original study. Only time and conductor of experiments were modified. System stability was controled by three series of systematic negative control (SNC) experiments with the same set-up, but distilled and autoclaved water was used as the only test substance. According to the series with gibberellic acid, each serie of SNC experiments included five experiments. Full two-way ANOVA (α = 5%) was used for statistical analysis. Independent variables were treatment and experiment number, dependent variable was r(area) for day 0–7. Data of each experiment was normalised to its mean value to allow a better comparison between experiments. Only if the global ANOVA F-test was significant (p < 0.05) we compared the investigated groups with Fisher`s LSD test (protected Fisher`s LSD). Results: No specific effects of agitated dilutions of gibberellic acid were found in the first two replication series (p=0.263 and p=0.062). In the third serie with gibbous Lemna gibba L. we observed a significant effect (p=0.009) of the homeopathic treatment, however growth was increased in contrast to decreasing in the former study. Variability in experiments with gibberellic acid 14x – 30x was lower than in SNC experiments. The stability of the experimental system was verified by the SNC experiments. Conclusions: When designing new studies to investigate reproducibility, different physiological states of the test organism must be considered. Variability might be an interesting parameter to investigate effects of homeopathic remedies in basic research.

Spironolactone Inhibits Cardiomyocyte Hypertrophy by Regulating the Ca2+/Calcineurin/p-NFATc3 Pathway

This study aimed to investigate the protective effect and molecular mechanism of spironolactone in isoproterenol-induced cardiomyocyte hypertrophy. In this study, primary cardiomyocytes were extracted from the heart of neonatal rats. After stable culture, they were processed with isoproterenol alone or isoproterenol (10 μM) combined with different doses (low dose of 10 μM and high dose of 50 μM), and the cellular activity was determined by MTT experiment. The volume of cells was measured with an inverted microscope and CIAS-1000 cell image analysis system. The mRNA expression levels of ANP and BNP in cells were explored by RT-qPCR. The levels of ANP and BNP proteins and NFATc3 phosphorylation in the nucleus were detected by western blot. The extracellular Ca2+ concentration and CaN activity were measured by colorimetry with the kit. Isoproterenol significantly enlarged the volume of cardiomyocytes ( p < 0.001 ), upregulated mRNA and expression levels of ANP and BNP proteins ( p < 0.001 ), increased extracellular Ca2+ concentration and CaN activity ( p < 0.001 ), and upregulated NFATc3 phosphorylation in the nucleus ( p < 0.001 ). The volume of cells treated with isoproterenol combined with different doses of spironolactone significantly decreased compared with those treated with isoproterenol alone ( p < 0.001 ). mRNA and expression levels of ANP and BNP proteins downregulated significantly ( p < 0.001 ). The extracellular Ca2+ ( p < 0.01 ) concentration and CaN activity ( p < 0.001 ) decreased significantly, and NFATc3 phosphorylation in the nucleus downregulated significantly ( p < 0.001 ). There was no significant difference in cell volume ( p = 0.999 ), ANP and BNP mRNA ( p = 0.695 ), expression levels of proteins, CaN activity (0.154), and NFATc3 phosphorylation in the nucleus between the cells treated with isoproterenol combined with high-dose spironolactone and those in the control group. In conclusion, spironolactone can reverse isoproterenol-induced cardiomyocyte hypertrophy by inhibiting the Ca2+/CaN/NFATc3 pathway.

COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts

(1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for COVID lung severity diagnosis. Earlier proposed approaches during 2020–2021 were semiautomated or automated but not accurate, user-friendly, and industry-standard benchmarked. The proposed study compared the COVID Lung Image Analysis System, COVLIAS 1.0 (GBTI, Inc., and AtheroPointTM, Roseville, CA, USA, referred to as COVLIAS), against MedSeg, a web-based Artificial Intelligence (AI) segmentation tool, where COVLIAS uses hybrid deep learning (HDL) models for CT lung segmentation. (2) Materials and Methods: The proposed study used 5000 ITALIAN COVID-19 positive CT lung images collected from 72 patients (experimental data) that confirmed the reverse transcription-polymerase chain reaction (RT-PCR) test. Two hybrid AI models from the COVLIAS system, namely, VGG-SegNet (HDL 1) and ResNet-SegNet (HDL 2), were used to segment the CT lungs. As part of the results, we compared both COVLIAS and MedSeg against two manual delineations (MD 1 and MD 2) using (i) Bland–Altman plots, (ii) Correlation coefficient (CC) plots, (iii) Receiver operating characteristic curve, and (iv) Figure of Merit and (v) visual overlays. A cohort of 500 CROATIA COVID-19 positive CT lung images (validation data) was used. A previously trained COVLIAS model was directly applied to the validation data (as part of Unseen-AI) to segment the CT lungs and compare them against MedSeg. (3) Result: For the experimental data, the four CCs between COVLIAS (HDL 1) vs. MD 1, COVLIAS (HDL 1) vs. MD 2, COVLIAS (HDL 2) vs. MD 1, and COVLIAS (HDL 2) vs. MD 2 were 0.96, 0.96, 0.96, and 0.96, respectively. The mean value of the COVLIAS system for the above four readings was 0.96. CC between MedSeg vs. MD 1 and MedSeg vs. MD 2 was 0.98 and 0.98, respectively. Both had a mean value of 0.98. On the validation data, the CC between COVLIAS (HDL 1) vs. MedSeg and COVLIAS (HDL 2) vs. MedSeg was 0.98 and 0.99, respectively. For the experimental data, the difference between the mean values for COVLIAS and MedSeg showed a difference of <2.5%, meeting the standard of equivalence. The average running times for COVLIAS and MedSeg on a single lung CT slice were ~4 s and ~10 s, respectively. (4) Conclusions: The performances of COVLIAS and MedSeg were similar. However, COVLIAS showed improved computing time over MedSeg.

Effect of Finish Line Design on the Fit Accuracy of CAD/CAM Monolithic Polymer-Infiltrated Ceramic-Network Fixed Dental Prostheses: An In Vitro Study

A polymer-infiltrated ceramic network (PICN) material has recently been introduced for dental use and evidence is developing regarding the fit accuracy of such crowns with different preparation designs. The aim of this in vitro study was to evaluate the precision of fit of machined monolithic PICN single crowns in comparison to lithium disilicate crowns in terms of marginal gap, internal gap, and absolute marginal discrepancies. A secondary aim was to assess the effect of finish line configuration on the fit accuracy of crowns made from the two materials. Two master metal dies were used to create forty stone dies, with twenty each for the two finish lines, shoulder and chamfer. The stone dies were scanned to produce virtual models, on which ceramic crowns were designed and milled, with ten each for the four material–finish line combinations (n = 10). Marginal gaps and absolute marginal discrepancies were evaluated at six pre-determined margin locations, and the internal gap was measured at 60 designated points using a stereomicroscope-based digital image analysis system. The influence of the material and finish line on the marginal and internal adaptation of crowns was assessed by analyzing the data using two-way analysis of variance (ANOVA), non-parametric, and Bonferroni multiple comparison post-hoc tests (α = 0.05). ANOVA revealed that the differences in the marginal gaps and the absolute marginal discrepancies between the two materials were significant (p < 0.05), but that those the finish line effect and the interaction were not significant (p > 0.05). Using the Mann–Whitney U test, the differences in IG for ‘material’ and ‘finish line’ were not found to be significant (p > 0.05). In conclusion, the finish line configuration did not seem to affect the marginal and internal adaptation of PICN and lithium disilicate crowns. The marginal gap of PICN crowns was below the clinically acceptable threshold of 120 µm.