PURPOSE: To compare the prediction error in the calculation of toric intraocular lenses (IOLs) associated with methods that estimate the power of the posterior corneal surface (ie, Barrett toric calculator and Abulafia–Koch formula) with that of methods that consider real measures obtained using Scheimpflug imaging: a software that uses vectorial calculation (Panacea toric calculator: http://www.panaceaiolandtoriccalculator.com ) and a ray tracing software (PhacoOptics, Aarhus Nord, Denmark). METHODS: In 107 eyes of 107 patients undergoing cataract surgery with toric IOL implantation (Acrysof IQ Toric; Alcon Laboratories, Inc., Fort Worth, TX), predicted residual astigmatism by each calculation method was compared with manifest refractive astigmatism. Prediction error in residual astigmatism was calculated using vector analysis. RESULTS: All calculation methods resulted in overcorrection of with-the-rule astigmatism and undercorrection of against-the-rule astigmatism. Both estimation methods resulted in lower mean and centroid astigmatic prediction errors, and a larger number of eyes within 0.50 diopters (D) of absolute prediction error than methods considering real measures ( P < .001). Centroid prediction error (CPE) was 0.07 D at 172° for the Barrett toric calculator and 0.13 D at 174° for the Abulafia–Koch formula (combined with Holladay calculator). For methods using real posterior corneal surface measurements, CPE was 0.25 D at 173° for the Panacea calculator and 0.29 D at 171° for the ray tracing software. CONCLUSIONS: The Barrett toric calculator and Abulafia–Koch formula yielded the lowest astigmatic prediction errors. Directly evaluating total corneal power for toric IOL calculation was not superior to estimating it. [ J Refract Surg . 2017;33(12):794–800.]

Photodynamic therapy (PDT) and photothermal therapy (PTT) are photo-mediated treatments with different mechanisms of action that can be addressed for cancer treatment. Both phototherapies are highly successful and barely or non-invasive types of treatment that have gained attention in the past few years. The death of cancer cells because of the application of these therapies is caused by the formation of reactive oxygen species, that leads to oxidative stress for the case of photodynamic therapy and the generation of heat for the case of photothermal therapies. The advancement of nanotechnology allowed significant benefit to these therapies using nanoparticles, allowing both tuning of the process and an increase of effectiveness. The encapsulation of drugs, development of the most different organic and inorganic nanoparticles as well as the possibility of surfaces’ functionalization are some strategies used to combine phototherapy and nanotechnology, with the aim of an effective treatment with minimal side effects. This article presents an overview on the use of nanostructures in association with phototherapy, in the view of cancer treatment.

Describe the ocular biometric parameters and their associations in a population of cataract surgery candidates. A cross-sectional study of 13,012 eyes of 6,506 patients was performed. Biometric parameters of the eyes were measured by optical low-coherence reflectometry. The axial length (AL), mean keratometry (K) and astigmatism, anterior chamber depth (ACD) (epithelium to lens), lens thickness (LT), and Corneal Diameter (CD) were evaluated. The mean age was 69 ± 10 years (44–99 years). Mean AL, Km, and ACD were 23.87 ± 1.55 mm (19.8–31.92 mm), 43.91 ± 1.71 D (40.61–51.14 D), and 3.25 ± 0.44 mm (2.04–5.28 mm), respectively. The mean LT was 4.32 ± 0.49 mm (2.73–5.77 mm) and the mean CD was 12.02 ± 0.46 mm (10.50–14.15 mm). The mean corneal astigmatism was 1.08 ± 0.84 D (0.00–7.58 D) and 43.5% of eyes had astigmatism ≥ 1.00 D. Male patients had longer AL and ACDs (p < .001) and flatter corneas (p < .001). In regression models considering age, gender, Km, ACD, LT, and CD, a longer AL was associated with being male and having higher ACD, LT and CD. These data represent normative biometric values for the Portuguese population. The greatest predictor of ocular biometrics was gender. There was no significant correlation between age and AL, ACD, or Km. These results may be relevant in the evaluation of refractive error and in the calculation of intraocular lens power.