Digital image processing software for diagnosing diabetic retinopathy from fundus photograph

Evaluation of multiple sclerosis severity using a new OCT tool

PURPOSE

To assess the ability of a new posterior pole protocol to detect areas with significant differences in retinal nerve fiber layer (RNFL) and ganglion cell layer (GCL) thickness in patients with multiple sclerosis versus healthy control subjects; in addition, to assess the correlation between RNFL and GCL thickness, disease duration, and the Expanded Disability Status Scale (EDSS).

METHODS

We analyzed 66 eyes of healthy control subjects and 100 eyes of remitting-relapsing multiple sclerosis (RR-MS) patients. Double analysis based on first clinical symptom onset (CSO) and conversion to clinically definite MS (CDMS) was performed. The RR-MS group was divided into subgroups by CSO and CDMS year: CSO-1 (≤ 5 years) and CSO-2 (≥ 6 years), and CDMS-1 (≤ 5 years) and CDMS-2 (≥ 6 years).

RESULTS

Significant differences in RNFL and GCL thickness were found between the RR-MS group and the healthy controls and between the CSO and CDMS subgroups and in both layers. Moderate to strong correlations were found between RNFL and GCL thickness and CSO and CDMS. Furthermore, we observed a strong correlation with EDSS 1 year after the OCT examination.

CONCLUSIONS

The posterior pole protocol is a useful tool for assessing MS and can reveal differences even in early stages of the disease. RNFL thickness shows a strong correlation with disability status, while GCL thickness correlates better with disease duration.

3D Mapping of the Lateral Malleolus Fractures for Predicting Syndesmotic Injuries in Supination External Rotation Type Ankle Fractures

Supination external rotation (SER) type ankle fracture is the most common ankle fracture in the Lauge-Hansen classification and is often accompanied with syndesmotic injury. However, the mechanism of this injury is indistinct and a suggestive role can be given by preoperative imaging. This study was to preoperatively predict whether SER type ankle fractures are accompanied with syndesmotic injuries by the means of lateral malleolus fracture mapping. One hundred and forty-eight patients diagnosed with SER type ankle fractures were retrospectively enrolled in this study. The baseline data were collected and computed tomography data were reconstructed in 3-dimensional (3D) model. Patients were divided into stable and unstable groups according to intraoperative Cotton test and whether the inferior tibiofibular screw was placed. All fracture lines were superimposed on the ankle template to create a fracture map, and the data on the fracture map were further measured. Logistic regression was conducted to identify relevant factors and the cutoff values were given using receiver operating characteristic curves. Forty-one patients were enrolled in the unstable group and 107 patients were enrolled in the stable group. The lateral malleolus fracture lines of the unstable group were higher and steeper than that in the stable group on lateral and posterior views. The fracture height of the posterior cortex and peak height were the significant contributing factors, and the cut-off values of posterior cortex, peak height and inclination angle were 40.35 mm (sensitivity: 78%, specificity: 82%), 55.34 mm (sensitivity: 85%, specificity: 70%) and 55.6° (sensitivity: 66%, specificity: 86%), respectively. In general, when the fracture lines of the lateral malleolus were high and steep, it was usually indicative of a syndesmotic injury and can be predicted by the preoperative 3D reconstruction of fracture height of posterior cortex, peak height and inclination angle. If the cut-off values of these indicators are exceeded, the syndesmotic injuries may be presented and need to be verified in the intraoperative Cotton test to decide whether to insert an inferior tibiofibular screw.

Recent developments on computer aided systems for diagnosis of diabetic retinopathy: a review

Diabetes is a long-term condition in which the pancreas quits producing insulin or the body's insulin isn't utilised properly. One of the signs of diabetes is Diabetic Retinopathy. Diabetic retinopathy is the most prevalent type of diabetes, if remains unaddressed, diabetic retinopathy can affect all diabetics and become very serious, raising the chances of blindness. It is a chronic systemic condition that affects up to 80% of patients for more than ten years. Many researchers believe that if diabetes individuals are diagnosed early enough, they can be rescued from the condition in 90% of cases. Diabetes damages the capillaries, which are microscopic blood vessels in the retina. On images, blood vessel damage is usually noticeable. Therefore, in this study, several traditional, as well as deep learning-based approaches, are reviewed for the classification and detection of this particular diabetic-based eye disease known as diabetic retinopathy, and also the advantage of one approach over the other is also described. Along with the approaches, the dataset and the evaluation metrics useful for DR detection and classification are also discussed. The main finding of this study is to aware researchers about the different challenges occurs while detecting diabetic retinopathy using computer vision, deep learning techniques. Therefore, a purpose of this review paper is to sum up all the major aspects while detecting DR like lesion identification, classification and segmentation, security attacks on the deep learning models, proper categorization of datasets and evaluation metrics. As deep learning models are quite expensive and more prone to security attacks thus, in future it is advisable to develop a refined, reliable and robust model which overcomes all these aspects which are commonly found while designing deep learning models.

Ganglion Cell and Retinal Nerve Fiver Layers Correlated with Time Disease of Bipolar Disorder Using 64 Cell Grid OCT Tool

MATERIALS AND METHODS

Twenty-five eyes of 25 patients with bipolar disorder and 74 eyes of 74 healthy controls underwent retinal measurements of retinal nerve fiber layer (RNFL) and ganglion cell layer (GCL) thickness. Measurements were obtained using the Spectralis-OCT device with the new Posterior Pole protocol which assesses the macular area by analyzing retinal thickness in a grid of 64 (8*8) cells.

RESULTS

Significant differences (p < 0.05) in RNFL and GCL thickness were found between BD patients and healthy controls, in parafoveal and perifoveal cells respectively. Significant inverse correlations were found between RNFL and GCL thinning at their thickest location and the duration of bipolar disorder. Several predictive variables were observed with a binary logistic regression for the presence/absence of BD: cell 1.3 RNFL (p = 0.028) and GCL in cells 7.8 (p = 0.012), 2.7 (p = 0.043) and 1.3 (p = 0.047).

CONCLUSION

Posterior Pole OCT protocol is a useful tool to assess changes in the inner retinal layers in bipolar disorder. These observed changes, especially those affecting the GCL, may be associated with disease evolution and may be predictive of the presence of the disease. OCT data could potentially be a useful tool for clinicians to diagnose and monitor BD patients.