Longitudinal analysis of subfoveal choroidal thickness after panretinal laser photocoagulation in diabetic retinopathy using swept-source optical coherence tomography.

Purpose: To describe the central three-dimensional (3D) thickness profile of the macula (CMT) and the subfoveal choroidal region (SFCT) in diabetic retinopathy (DR) following panretinal laser photocoagulation (PRP) using swept-source optical coherence tomography (SS-OCT). Methods: A prospective observational study including 17 eyes with proliferative DR (PDR) and 27 eyes with severe nonproliferative DR (sNPDR)] for whom PRP was done. All subjects received SS-OCT imaging before and 3 months after PRP (POM#3). SFCT and CMT changes were analysed at both visits. Intraclass Correlation Coefficients (ICC) and Coefficients of Variation (COV) were used to test the accuracy of thickness data. Results: SFCT has thinned from 233 ± 54 µm before PRP treatment to 216 ± 51 µm 3 months later (p < 0.001). Likewise, CMT declined at POM#3 as compared to pre-PRP status (p<0.001). SFCT was thinner in PDR before and at POM#3 (p<0.05) than sNPDR; whereas, no significant difference was observed in CMT between both groups in the two visits. No significant changes were found between groups in SFCT and CMT at POM#3. Regarding reliability, ICCSFCT=0.98 and ICCCMT=0.99. The COVs for CMT and SFCT were 5.03% and 5.91%, respectively. Conclusion: The mean SFCT and CMT decreased 3 months after PRP. We also reported reliability of SFCT measurements in DR using SS-OCT. Abbreviations: SS = Swept-Source, TD = time domain, SD = spectral domain, FD = Fourier-domain, 3D = three-dimensional, 2D = two-dimensional.

Formulation and optimization of duloxetine hydrochloride buccal films: in vitro and in vivo evaluation.

Duloxetine hydrochloride (DH) is a serotonin-norepinephrine reuptake inhibitor (SSNRI) indicated for the treatment of depression. Duloxetine suffers from reduced oral bioavailability (≈50%) due to hepatic metabolism. This study aims to develop DH buccoadhesive films to improve its bioavailability. DH buccoadhesive films were prepared adopting the solvent casting method using hydroxypropyl methylcellulose (HPMC) and polyvinyl alcohol (PVA). The prepared films were evaluated for weight uniformity, drug content, surface pH, swelling index, mucoadhesion strength and drug release percentages. Accelerated stability and bioavailability studies in healthy human volunteers were also performed for the selected films. Results of the evaluation tests showed that the optimum physicochemical characters were obtained by the films prepared with 2% HPMC using 10% propylene glycol (F2 films). Accelerated stability studies revealed that DH showed proved stability throughout the experiment time. DH bioavailability from F2 films was determined and compared with that of the marketed oral capsules (Cymbalta® 30 mg). The pharmacokinetic results showed that Cmax for F2 was higher than the market product. In addition, ANOVA analysis showed that a Tmax of F2 film was significantly lower, while, the AUC0-72 of F2 was significantly higher than that of Cymbalta capsules. The percentage relative bioavailability of DH from F2 was found to be 296.39%. Therefore, the prepared buccal films offer an alternative route for the administration of DH with the possibility of improving its bioavailability.

Computer aided detection system for micro calcifications in digital mammograms.

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. Mammogram breast X-ray is considered the most reliable method in early detection of breast cancer. However, it is difficult for radiologists to provide both accurate and uniform evaluation for the enormous mammograms generated in widespread screening. Micro calcification clusters (MCCs) and masses are the two most important signs for the breast cancer, and their automated detection is very valuable for early breast cancer diagnosis. The main objective is to discuss the computer-aided detection system that has been proposed to assist the radiologists in detecting the specific abnormalities and improving the diagnostic accuracy in making the diagnostic decisions by applying techniques splits into three-steps procedure beginning with enhancement by using Histogram equalization (HE) and Morphological Enhancement, followed by segmentation based on Otsu's threshold the region of interest for the identification of micro calcifications and mass lesions, and at last classification stage, which classify between normal and micro calcifications 'patterns and then classify between benign and malignant micro calcifications. In classification stage; three methods were used, the voting K-Nearest Neighbor classifier (K-NN) with prediction accuracy of 73%, Support Vector Machine classifier (SVM) with prediction accuracy of 83%, and Artificial Neural Network classifier (ANN) with prediction accuracy of 77%.