Visual Outcomes With Intraocular Trifocal Lens Implant.

BACKGROUND: Cataract surgery has become one of the most common surgeries in the world with one in every four surgeries performed being a cataract extraction and the numbers are expected to increase by 16 percent in the USA alone by 2024 as compared to the current statistics. The aim of the study is to analyze the visual outcomes of intraocular lens implants for various visual ranges. METHODS: This non-comparative interventional study was conducted at the Ophthalmology department of Al Ehsan Eye Hospital from Jan to Dec 2021. It included patients who underwent uneventful phacoemulsification with an intraocular lens implant and analysis of the visual outcomes for uncorrected distance (UDVA), uncorrected intermediate distance (UIVA), and uncorrected near distance (UNVA). RESULTS: Independent sample t-test was applied to observe the mean values of recorded far vision on the 1stday, 1 week, and 1 month after the trifocal intraocular lens implantation. It showed a significant difference with a p-value of 0.00 on 1st day, 1 week, and 1 month after was 0.3±0.1, 0.17±0.09, and 0.14±0.08 respectively. Mean improvement in near vision after 1 month was N6 with S.D 1.03 and in intermediate vision was N8±1.4 respectively. CONCLUSIONS: Trifocal Intraocular lens implantation offers an improved vision for near, intermediate, and distant visual ranges without the need for correction.

AMNIOTIC MEMBRANE GRAFT FOR THE TREATMENT OF LARGE REFRACTORY MACULAR HOLE.

PURPOSE: Study off-label human amniotic membrane use outcomes for giant refractory macular hole closure. MATERIALS AND METHODS: The study was performed at Lahore General Hospital, Lahore, over 52 months on patients who had undergone standard macular hole surgical procedures for treatment, but the hole failed to close. Refractory macular hole dimensions ranged from 824 µ m to 1,568 µ m. Before surgery, patients underwent slit-lamp examination, fundus photography, and optical coherence tomography for macular scan. Amniotic membrane graft (AMG) used in surgery was harvested from a human placenta 24 hours before. Before AMG application, enough internal limiting membrane peeling was performed to ensure perfect fitting and recovery. All holes were plugged with AMG and SF6 gas tamponade. RESULTS: Twenty-nine patients, 20 men and nine women, were included in this study. Mean age of patients was 58 ± 6. Patients had refractory holes of average 1,237.48 ± 151.25 µ m. Post-op, 100% macular hole closure was achieved in all patients. Type 1 closure was found in patients (37.93%) who underwent AMG surgery within 3 months after primary surgical failure. Type 2 closure was found in patients (62.07%) who were operated on 3 months after primary surgical failure. CONCLUSION: Refractory macular holes treated by AMG with SF6 gas tamponade achieve anatomical Type 1 closure if performed within 3 months of primary surgical repair.

Automated feature detection in dental periapical radiographs by using deep learning.

OBJECTIVE: The aim of this study was to investigate automated feature detection, segmentation, and quantification of common findings in periapical radiographs (PRs) by using deep learning (DL)-based computer vision techniques. STUDY DESIGN: Caries, alveolar bone recession, and interradicular radiolucencies were labeled on 206 digital PRs by 3 specialists (2 oral pathologists and 1 endodontist). The PRs were divided into "Training and Validation" and "Test" data sets consisting of 176 and 30 PRs, respectively. Multiple transformations of image data were used as input to deep neural networks during training. Outcomes of existing and purpose-built DL architectures were compared to identify the most suitable architecture for automated analysis. RESULTS: The U-Net architecture and its variant significantly outperformed Xnet and SegNet in all metrics. The overall best performing architecture on the validation data set was "U-Net+Densenet121" (mean intersection over union [mIoU] = 0.501; Dice coefficient = 0.569). Performance of all architectures degraded on the "Test" data set; "U-Net" delivered the best performance (mIoU = 0.402; Dice coefficient = 0.453). Interradicular radiolucencies were the most difficult to segment. CONCLUSIONS: DL has potential for automated analysis of PRs but warrants further research. Among existing off-the-shelf architectures, U-Net and its variants delivered the best performance. Further performance gains can be obtained via purpose-built architectures and a larger multicentric cohort.