Role of orthoptics and scoring system for orbital floor blowout fracture: surgical or conservative treatment

AIM: To assess the role of orthoptics in referring patients with orbital floor blowout fracture (OFBF) for conservative or surgical treatment and based on the results, to propose a scoring system for such decision making. METHODS: A retrospective analysis of 69 patients with OFBF was performed (35 treated conservatively, 34 surgically). The role of orthoptics in referring to surgery or conservative treatment was retrospectively evaluated, the factors with the highest significance for decision making were identified, and a scoring system proposed using Logistic regression. RESULTS: According to defined criteria, the treatment was unsuccessful in 2 (6%) surgically treated and only in one (3%) conservatively treated patient. The proposed scoring system includes the defect size and several values resulting from the orthoptic examination, the elevation of the eyebulb measured on Lancaster screen being the most significant. CONCLUSION: The study demonstrates the benefits of orthoptic examination when making decisions on conservative or surgical treatment and for diagnosing ocular motility disorder (with or without binocular diplopia) in OFBF patients. The proposed scoring system could, following verification in a prospective study, become a valuable adjunctive tool.Web of Science14121934192

Detection and Segmentation of Retinal Lesions in Retcam 3 Images Based on Active Contours Driven by Statistical Local Features

Clinical retinal image analysis is an import aspect of clinical diagnosis in ophthalmology. Retinopathy of Prematurity (ROP) represents one of the most severe retinal disorders in prematurely born infants. One of the ROP clinical signs is the presence of retinal lesions endangering the vision system. Unfortunately, the stage and progress of these findings is often only subjectively estimated. A procedure such as this is undoubtedly linked to subjective inaccuracies depending on the experience of the ophthalmologist. In our study, a fully autonomous segmentation algorithm to model retinal lesions found using RetCam 3 is proposed. The proposed method used a combination of retinal image preprocessing and active contours for retinal lesion segmentation. Based on this procedure, a binary model of retinal lesions that allowed retinal lesions to be classified from a retinal image background was obtained. Another important aspect of the model was feature extraction. These features reliably and automatically described the development stage of an individual lesion. A complex procedure such as this has significant implications for ophthalmic clinical practice in substituting manual clinical procedures and improving the accuracy of routine clinical decisions

Evaluation of the WinROP system for identifying retinopathy of prematurity in Czech preterm infants

Aims. Retinopathy of Prematurity (ROP) is a potentially serious condition that can afflict preterm infants. Timely and correct identification of individuals at risk of developing a serious form of ROP is therefore of paramount importance. WinROP is an online system for predicting ROP based on birth weight and weight increments. However, the results vary significantly for various populations. It has not been evaluated in the Czech population. This study evaluates the test characteristics (specificity, sensitivity, positive and negative predictive values) of the WinROP system in Czech preterm infants. Methods. Data on 445 prematurely born infants included in the ROP screening program at the University Hospital Ostrava, Czech Republic, were retrospectively entered into the WinROP system and the outcomes of the WinROP and regular screening were compared. Results. All 24 infants who developed high-risk (Type 1 or Type 2) ROP were correctly identified by the system. The sensitivity and negative predictive values for this group were 100%. However, the specificity and positive predictive values were substantially lower, resulting in a large number of false positives. Extending the analysis to low risk ROP, the system did not provide such reliable results. Conclusions. The system is a valuable tool for identifying infants who are not likely to develop high-risk ROP and this could help to substantially reduce the number of preterm infants in need of regular ROP screening. It is not suitable for predicting the development of less serious forms of ROP which is however in accordance with the declared aims of the WinROP system.Web of Science161111611

Medical image processing tools for blender with HPC support

We present a medical image processing plug-in in this paper. Our plug-in uses Blender’s environment and adds tools for the medical image processing and 3D model reconstructions and measurements. There are several software solutions to provide these tasks, two of which are used for comparison with our tool in this paper. However, there is not a single application that can perform medical image processing and subsequent 3D model reconstruction and post-processing with possible utilization of High Performance Computing (HPC) resources. In our plug-in we aim to use HPC resources to speed up the most computationally extensive tasks. The plug-in is written in Python and C++. The basic functionality and additional tools are implemented in Phyton. Blender has built-in Python interface, thus the development of the tools is quite fast. The C++ language is used for all time critical functions as it has unrestricted potential in parallel programming that can utilize available HPC resources. In the paper we present two examples, where we demonstrate possibilities of our Blender plug-in. We provide 3D reconstruction of human airway and human orbital floor and compare the results with those provided by 3D Slicer and Osirix