Development and Application of Prototype System Based on Light-Emitting Diode Arrays (660 nm) with a Top Hat Beam Profile in Order to Optimize Photobiomodulation Protocols for Treatment of Radiation-Induced Oral Mucositis in Rats.

Background: Oral mucositis (OM) is a common adverse effect of radiation to the head and neck. Recent research has shown that extra oral photobiomodulation (EO-PBM) reduces the severity of OM. However, appropriate EO-PBM therapy parameters for OM severity reduction have not been documented. Objective: This work aims to optimize EO-PBM radiation parameters for lowering the severity of radiation-induced OM in rats by establishing a photobiomodulation (PBM) treatment system based on light-emitting diode arrays with top-hat beam profile. Methods: The 36 rats are separated into 2 control groups and 4 groups receiving PBM treatment. The PBM groups are exposed to irradiance between 4 and 24 J/cm2 at 660 nm. The cheek pouch mucosa is removed after scarification for biochemical and histological examination. Student's t-test, and one-way analysis of variance (ANOVA) followed by Tukey's Multiple were applied to compare the statistical significance of differences between control groups and PBM treatment groups. Results: Statistical analysis reveals that PBM irradiation at 12 J/cm2 (200 sec) with a flatness of 0.8 and a diameter of 3 cm substantially decreased the level of inflammatory cytokines compared with the positive control group. Conclusions: Our results indicate that the designed treatment PBM system is capable of delivering the optical parameters necessary for therapeutic treatment.

Treatment Parameters of Photobiomodulation in the Prevention of Non-surgical Cancer Treatment-Induced Oral Mucositis: A Review of Preclinical Studies.

Introduction: The most important side effect after non-surgery cancer treatment (NSCT) is oral mucositis (OM) which degrades the quality of life. Using photobiomodulation (PBM), formerly known as low-level laser therapy (LLLT), in the prevention of NSCT-induced OM was widely studied. Hence, this review evaluates the efficacy of optical treatment parameters behind the working process of PBM in preventing NSCT-induced OM in preclinical studies. Methods: Using the PubMed, Scopus and Embase databases, the present study systematically reviewed existing preclinical studies for optical treatment parameters of PBM in preventing NSCT-induced OM in experimental models without restriction on the year of publication. Results: In total, 51 articles were recognized during the search of the literature, and only 16 research papers were included in this review, taking into consideration the inclusion as well as exclusion benchmarks. The reviewed studies showed that a consensus has yet to be reached on the optimal PBM treatment parameters in preventing NSCT-induced OM. However, a wavelength of 660 nm, a power density of 40 mW as well as fluence which ranged between 2 and 6 J/cm2 were mostly utilized in the included studies. Furthermore, the severity of NSCT-induced OM was reduced following PBM application with no reported severe side effects. Conclusion: The efficacy of PBM with the associated optical parameters is a promising strategy in preventing NSCT-induced OM. However, the optimal parameters of PBM need to be investigated.

Erratum: Retinal image mosaicking using scale-invariant feature transformation feature descriptors and Voronoi diagram (Erratum).

[This corrects the article DOI: 10.1117/1.JMI.7.4.044001.].

Retinal image mosaicking using scale-invariant feature transformation feature descriptors and Voronoi diagram.

Purpose: Peripheral retinal lesions substantially increase the risk of diabetic retinopathy and retinopathy of prematurity. The peripheral changes can be visualized in wide field imaging, which is obtained by combining multiple images with an overlapping field of view using mosaicking methods. However, a robust and accurate registration of mosaicking techniques for normal angle fundus cameras is still a challenge due to the random selection of matching points and execution time. We propose a method of retinal image mosaicking based on scale-invariant feature transformation (SIFT) feature descriptor and Voronoi diagram. Approach: In our method, the SIFT algorithm is used to describe local features in the input images. Then the input images are subdivided into regions based on the Voronoi method. Each pair of Voronoi regions is matched by the method zero mean normalized cross correlation. After matching, the retinal images are mapped into the same coordinate system to form a mosaic image. The success rate and the mean registration error (RE) of our method were compared with those of other state-of-the-art methods for the P category of the fundus image registration database. Results: Experimental results show that the proposed method accurately registered 42% of retinal image pairs with a mean RE of 3.040 pixels, while a lower success rate was observed in the other four state-of-the-art retinal image registration methods GDB-ICP (33%), Harris-PIIFD (0%), HM-2016 (0%), and HM-2017 (2%). Conclusions: The proposed method outperforms state-of-the-art methods in terms of quality and running time and reduces the computational complexity.