No Arabic abstract
Purpose: This study aimed to investigate the actual changes of central corneal thickness (CCT) in keratoconus and normal corneas during air puff indentation, by using corneal visualization Scheimpflug technology (Corvis ST). Methods: A total of 32 keratoconic eyes and 46 normal eyes were included in this study. Three parameters of CCTinitial, CCTfinal and CCTpeak were selected to represent the CCT at initial time, final time and highest corneal concavity, respectively, during air puff indentation. Wilcoxon signed rank test (paired sample test) was used to assess the differences between these 3 parameters in both keratoconus and normal groups. Univariate linear regression analysis was performed to determine the effect of CCTinitial on CCTpeak and CCTfinal, as well as the impact of air puff force on CCT in each group. Receiver operating characteristic (ROC) curves were constructed to evaluate the discriminative ability of the 3 parameters. Results: The results demonstrated that CCTpeak and CCTfinal were significantly decreased (p<0.01) compared to CCTinitial in both keratoconus and normal groups. Regression analysis indicated a significant positive correlation between CCTpeak and CCTinitial in normal cornea group (R2=0.337, p<0.01), but not in keratoconus group (R2=0.029, p=0.187). Likewise, regression models of air puff force and CCT revealed the different patterns of CCT changes between keratoconus and normal cornea groups. Furthermore, ROC curves showed that CCTpeak exhibited the greatest AUC (area under ROC curve) of 0.940, with accuracy, sensitivity and specificity of 94.9%, 87.5% and 100%, respectively. Conclusions: CCT may change during air puff indentation, and is significantly different between keratoconus and normal cornea groups. The changing pattern is useful for the diagnosis of keratoconus, and lays the foundation for corneal biomechanics.
PURPOSE: Among the current practices for keratoconus recognition using biomechanical parameters from Corvis ST, matching intra-ocular pressure (IOP) is often required to eliminate the biasing influence; as a result, the combined biomechanical parameters determined from IOP-unmatched scenario possibly bring in confounding influence. This paper was therefore designed to introduce a novel compatible parameter set (CPS) determined from IOP-matched scenario, hopefully could show its compatibility and superiority for recognizing keratoconus in both IOP-matched and not scenarios. METHODS: A total of 335 eyes were included. Among them, 70 eyes were used to determined CPS by forward logistics regression, 62 eyes were used to validate CPS in IOP-matched scenario, and resting 203 eyes were used to validate CPS in IOP-unmatched scenario. To analyze its superiority, CPS was also compared with other two reported Biomechanical Indexes (aCBI and DCR) in both scenarios. Receiver operating characteristic curves (ROC), accuracy, FI, sensitivity and specificity were used to access and compare the performance of these three parameter sets in both scenarios. RESULTS: The resulting CPS was comprised of only 3 biomechanical parameters: DA Ratio Max 1mm (DRM1), the first applanation time (AT1) and an energy loading parameter (Eload). In the IOP-matched validation, the area under ROC (AUC) reached 95.73%, with an accuracy of 95.2%, sensitivity of 93.5% and specificity of 96.8% (leave one out cross-validation). All these indicators reached 96.54%, 95.1%, 95.6% and 94.6% respectively, in the IOP-unmatched validation (leave one out cross-validation). Surprisingly, CPS performed better than other two parameter sets on a whole. CONCLUSIONS: The parameter set determined from IOP-matched scenario indeed exhibit its superiority for differentiation of keratoconus and normal corneas, regardless of IOP-matched or not.
Corneal thickness (pachymetry) maps can be used to monitor restoration of corneal endothelial function, for example after Descemets membrane endothelial keratoplasty (DMEK). Automated delineation of the corneal interfaces in anterior segment optical coherence tomography (AS-OCT) can be challenging for corneas that are irregularly shaped due to pathology, or as a consequence of surgery, leading to incorrect thickness measurements. In this research, deep learning is used to automatically delineate the corneal interfaces and measure corneal thickness with high accuracy in post-DMEK AS-OCT B-scans. Three different deep learning strategies were developed based on 960 B-scans from 50 patients. On an independent test set of 320 B-scans, corneal thickness could be measured with an error of 13.98 to 15.50 micrometer for the central 9 mm range, which is less than 3% of the average corneal thickness. The accurate thickness measurements were used to construct detailed pachymetry maps. Moreover, follow-up scans could be registered based on anatomical landmarks to obtain differential pachymetry maps. These maps may enable a more comprehensive understanding of the restoration of the endothelial function after DMEK, where thickness often varies throughout different regions of the cornea, and subsequently contribute to a standardized postoperative regime.
The classical models of Hertz, Sneddon and Boussinesq provide solutions for problems of indentation of a semi-infinite elastic massif by a sphere, a sphere or a cone and a flat punch. Although these models have been widely tested, it appears that at small scales and for flexible materials, surface tension can contribute to considerably to the mechanical response to indentation. The scales are typically those of the less than one micron for an elastomer and less than one millimetre for a gel. The exploitation of certain experimental results of microscopy or nanoindentation remain approximate due to the absence of models incorporating the effect of surface tension.
Dementia disorders are increasingly becoming sources of a broad range of problems, strongly interfering with normal daily tasks of a growing number of individuals. Such neurodegenerative diseases are often accompanied with progressive brain atrophy that, at late stages, leads to drastically reduced brain dimensions. At the moment, this structural involution can be followed with XCT or MRI measurements that share numerous disadvantages in terms of usability, invasiveness and costs. In this work, we aim to retrieve information concerning the brain atrophy stage and its evolution, proposing a novel approach based on non-invasive time-resolved Near Infra-Red (tr-NIR) measurements. For this purpose, we created a set of human-head atlases, in which we eroded the brain as it would happen in a clinical brain-atrophy progression. With these realistic meshes, we reproduced a longitudinal tr-NIR study exploiting a Monte-Carlo photon propagation algorithm to model the varying cerebral spinal fluid (CSF). The study of the time-resolved reflectance curve at late photon arrival times exhibited peculiar slope-changes upon CSF layer increase that were confirmed under several measurement conditions. The performance of the technique suggests good sensitivity to CSF variation, useful for a fast and non-invasive observation of the dementia progression.
In the COVID-19 period, the number of deaths has increased every day around the world. The pandemic has impacted the life and economy. Especially, there is a shortage in medical including a lack of technology, facility and equipment. One of those, ventilators are the essential equipment that does not provide enough requirements for the hospital. A ventilator is an essential unit in hospitals because it seems to be the first step to protect the life of the patient getting sick. Some low-income countries aim to make a simple ventilator using locally available and low-cost materials for primary care and palliative care. One of the simple principles of ventilators is to adopt an artificial manual breath unit (AMBU) bag with paddles. Unfortunately, the squeezing angle of paddles is not proportional to the exhaust air volume from the AMBU bag. This paper analyzes the character of the squeezing angle of the paddles and the exhaust air volume of the adult AMBU bag through experiments. The result can be used to control the squeezing angle through a DC motor mounted with paddles to obtain the desired air volume.