Analysis Of Autofluorescence Images Research Articles

Identification of rare cell populations in autofluorescence lifetime image data.

Drug‐resistant cells and anti‐inflammatory immune cells within tumor masses contribute to tumor aggression, invasion, and worse patient outcomes. These cells can be a small proportion (<10%) of the total cell population of the tumor. Due to their small quantity, the identification of rare cells is challenging with traditional assays. Single cell analysis of autofluorescence images provides a live‐cell assay to quantify cellular heterogeneity. Fluorescence intensities and lifetimes of the metabolic coenzymes reduced nicotinamide adenine dinucleotide and oxidized flavin adenine dinucleotide allow quantification of cellular metabolism and provide features for classification of cells with different metabolic phenotypes. In this study, Gaussian distribution modeling and machine learning classification algorithms are used for the identification of rare cells within simulated autofluorescence lifetime image data of a large tumor comprised of tumor cells and T cells. A Random Forest machine learning algorithm achieved an overall accuracy of 95% for the identification of cell type from the simulated optical metabolic imaging data of a heterogeneous tumor of 20,000 cells consisting of 70% drug responsive breast cancer cells, 5% drug resistant breast cancer cells, 20% quiescent T cells and 5% activated T cells. High resolution imaging methods combined with single‐cell quantitative analyses allows identification and quantification of rare populations of cells within heterogeneous cultures

Multiclass classification of autofluorescence images of oral cavity lesions based on quantitative analysis.

BackgroundOral cancer is one of the most common diseases globally. Conventional oral examination and histopathological examination are the two main clinical methods for diagnosing oral cancer early. VELscope is an oral cancer-screening device that exploited autofluorescence. It yields inconsistent results when used to differentiate between normal, premalignant and malignant lesions. We develop a new method to increase the accuracy of differentiation.Materials and methodsFive samples (images) of each of 21 normal mucosae, as well as 31 premalignant and 16 malignant lesions of the tongue and buccal mucosa were collected under both white light and autofluorescence (VELscope, 400-460 nm wavelength). The images were developed using an iPod (Apple, Atlanta Georgia, USA).ResultsThe normalized intensity and standard deviation of intensity were calculated to classify image pixels from the region of interest (ROI). Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) classifiers were used. The performance of both of the classifiers was evaluated with respect to accuracy, precision, and recall. These parameters were used for multiclass classification. The accuracy rate of LDA with un-normalized data was increased by 2% and 14% and that of QDA was increased by 16% and 25% for the tongue and buccal mucosa, respectively.ConclusionThe QDA algorithm outperforms the LDA classifier in the analysis of autofluorescence images with respect to all of the standard evaluation parameters.

PREVALENCE OF DRUG-RESISTANT MICROORGANISMS IN ORAL CAVITY DURING ORTHODONTIC TREATMENT

Bacterial antibiotic resistance is a steadily growing global problem, which is nowadays compared with issues such as global warming, ozone depletion and extinction of species. Rough surfaces such as brackets in orthodontics treatment can cause biofilm accumulation and maturation, what could advance changes in the oral microbiota, favoring the resistance of these microorganisms. Objectives To investigate the prevalence of drug-resistant microorganisms in patients using fixed orthodontic appliance. Methods Sample consisted in 22 patients (11 female and 11 male) with mean (SD) of 22.3 (11.0) years with good general and oral health conditions participates in the study. Oral biofilm was evaluated by autofluorescence imaging analysis (using LED light) to indicate mature biofilm and posteriorly collected at the buccal tooth surface around fixed orthodontic appliance. Oral biofilm samples were inoculated into chromogenic medium and screening of representative microorganisms was performed. The CFUs were isolated and tested with antibiogram discs and antimicrobial agents which are common in clinical practice were used. Results Oral microorganisms collected around brackets showed a surprising high prevalence of bacterial resistance for all tested drugs: Erythromycin (54.5%), Clindamycin (50%), Amoxicillin (45.5%), Amoxicillin with Clavulanic Acid (31.8%) and Cephalexin (31.8%). Conclusion A special attention should be directed to precautions against these microorganisms, particularly in immunosuppressed patients, who are more susceptible to infections.

Evaluation of fundus autofluorescence ımaging of diabetic patients without retinopathy.

To evaluate the usefulness of fundus autofluorescence imaging of diabetic patients without retinopathy to investigate early retinal damage. Fundus autofluorescence images of patients with type 2 diabetes mellitus without retinopathy (diabetic group) and age-sex matched healthy patients (control group) were recorded with a CX-1 digital mydriatic retinal camera after detailed ophthalmologic examinations. MATLAB 2013a software was used to measure the average pixel intensity and average curve width of the macula and fovea. Fifty-six eyes of 28 patients, as the diabetic group, and 54 eyes of 27 healthy patients, as the control group, were included in this study. The mean aggregation index was 168.32 ± 37.18 grayscale units (gsu) in the diabetic group and 152.27 ± 30.39 gsu in the control group (p=0.014). The mean average pixel intensity value of the fovea was 150.87 ± 35.83 gsu the in diabetic group and as 141.51 ± 31.10 gsu in the control group (p=0.060). The average curve width value was statistically higher in the diabetic group than in the control group (71.7 ± 9.2 vs. 59.4 ± 8.6 gsu, respectively, p=0.03). Fundus autofluorescence imaging analysis revealed that diabetic patients without retinopathy have significant fluorescence alterations. Therefore, a noninvasive imaging technique, such as fundus autofluorescence, may be valuable for evaluation of the retina of diabetic patients without retinopathy.

USE OF AUTOFLUORESCENCE DERMATOSCOPY IN PATIENTS WITH PSORIASIS

Results of autofluorescence dermatoscopy using videodermatoscope «EcoSkin» in patients with different dermatologic diseases are represented. The study included 64 patients, 27 of them had different types of psoriasis, 11 – acne, 3 – rosacea, 5 – eczema, 3 – mite-induced dermatitis, 4 – superficial mycosis of the glabrous skin, 7 – atopic dermatitis, 4 – seborrheic dermatitis. The major changes of autofluorescence were detected in pathological foci in patients with psoriasis. Authors suppose that increased autofluorescence of porphyrins in psoriatic plaques in the study is associated with enhanced prolyferation in pathological tissues and with liver dysfunction. The analysis of autofluorescence images in patients with rosacea, eczema, atopic and mite-induced dermatitis did not show significant difference in autofluorescence images of affected skin comparing with intact skin in same patients. In patients with acne a pattern of spot red-orange autofluorescence of skin in seborrheic areas corresponding with location of openings of pilosebaceous apparatus was detected that was associated by authors with Propionibacterium acnes infection.

Novel quantitative analysis of autofluorescence images for oral cancer screening

ObjectivesVELscope® was developed to inspect oral mucosa autofluorescence. However, its accuracy is heavily dependent on the examining physician’s experience. This study was aimed toward the development of a novel quantitative analysis of autofluorescence images for oral cancer screening. Materials and methodsPatients with either oral cancer or precancerous lesions and a control group with normal oral mucosa were enrolled in this study. White light images and VELscope® autofluorescence images of the lesions were taken with a digital camera. The lesion in the image was chosen as the region of interest (ROI). The average intensity and heterogeneity of the ROI were calculated. A quadratic discriminant analysis (QDA) was utilized to compute boundaries based on sensitivity and specificity. Results47 oral cancer lesions, 54 precancerous lesions, and 39 normal oral mucosae controls were analyzed. A boundary of specificity of 0.923 and a sensitivity of 0.979 between the oral cancer lesions and normal oral mucosae were validated. The oral cancer and precancerous lesions could also be differentiated from normal oral mucosae with a specificity of 0.923 and a sensitivity of 0.970. ConclusionThe novel quantitative analysis of the intensity and heterogeneity of VELscope® autofluorescence images used in this study in combination with a QDA classifier can be used to differentiate oral cancer and precancerous lesions from normal oral mucosae.

Serum and macular responses to multiple xanthophyll supplements in patients with early age-related macular degeneration

ObjectiveThis randomized controlled trial examined serum and macular (in vivo measured macular pigment optical density [MPOD]) responses to supplemental lutein and zeaxanthin in Chinese subjects with early age-related macular degeneration. MethodsOne hundred and eight patients with early age-related macular degeneration older than 50 y were randomized to low lutein (LL; 10 mg/d), high lutein (HL; 20 mg/d), lutein plus zeaxanthin (LZ; each 10 mg/d), or placebo during a 48-wk intervention. Serum concentrations were quantified by C30 high-performance liquid chromatography (at baseline and 4, 12, 24, and 48 wk), and MPOD was measured by analysis of autofluorescence images (at baseline and 24 and 48 wk). ResultsSerum lutein levels in the LL, LZ, and HL groups increased significantly in the first 4 wk and then increased 4.24-, 4.66-, and 6.23-fold during the trial, respectively (all P < 0.001). The serum lutein level in the HL group was significantly higher than that in the LL or LZ group at 48 wk (P < 0.05). Similarly, the serum zeaxanthin concentration in the LZ group increased 3.11-fold at 48 wk. MPOD increased smoothly in all treated groups, and the increase from baseline was greatest in the HL group at 24 and 48 wk (both P < 0.05). MPOD and serum lutein levels increased linearly with the dosage and their increasing rates were statistically correlated (all P < 0.05). No notable changes were detected in the placebo group for MPOD and serum concentrations. ConclusionXanthophyll supplementation significantly increased serum concentrations and MPOD in patients with early age-related macular degeneration, and a higher lutein supplementation (20 mg/d) might be more effective in increasing these two biochemical markers in Chinese patients without significant side effects.

The Ringlike Structure of Macular Pigment in Age-Related Maculopathy: Results from the Muenster Aging and Retina Study (MARS)

The role of macular pigment (MP) in age-related maculopathy (ARM) is still not clearly understood. Recent studies have reported on variations in the spatial distribution of MP optical density (MPOD) including a secondary peak ("ring") in the slope of the MPOD profile. The authors investigated in a cross-sectional manner the presence of ringlike structures, their determinants, and their relationship with ARM. In all, 369 participants of the Muenster Aging and Retina Study were examined using dual-wavelength analysis of autofluorescence images. ARM was graded using digital fundus photographs according to the International Classification System. A ringlike structure was observed in 73 (19.8%) study participants. The MP maximum of the ring was located on average at 0.85° and the minimum at 0.48° from the center of the fovea. Their concordance between pairs of eyes was highly significant. MPOD measured at eccentricities of 0°, 0.25°, and 0.5° from the fovea was significantly lower in eyes with ringlike structure, whereas it was significantly higher at 1.0° and 2.0° than that in eyes without the ring. Ringlike structures were significantly more common in females and never smokers and were found significantly less often in eyes with ARM than in healthy eyes, even after adjustment for influential factors (adjusted odds ratio, 0.347; 95% confidence interval, 0.196-0.617). Ringlike structures in the MP spatial profile are fairly common, show a high degree of bilaterality, and appeared inversely related with ARM.

Determinants of Macular Pigment Optical Density and Its Relation to Age-Related Maculopathy: Results from the Muenster Aging and Retina Study (MARS)

The controversial protective effect of macular pigment (MP), consisting of lutein (L) and zeaxantin (Z), in age-related maculopathy (ARM) and its late-stage, age-related macular degeneration (AMD) is discussed. Determinants of MP optical density (MPOD) and its relation to ARM were investigated. MPOD was accessed at eccentricities of 0.5° and 2.0° from the fovea in 369 participants in the 2.6-year follow-up examination of the prospective Muenster Aging and Retina Study using dual-wavelength analysis of autofluorescence images. ARM was graded from standardized fundus photographs according to the International Classification System. MPOD at 0.5° and 2.0° between pairs and within single eyes was strongly correlated (P < 0.001). Smoking and body mass index showed moderately inverse associations with MPOD at 2.0°, and age was positively related to MPOD at both eccentricities. Serum L, measured at the baseline examination, was significantly associated with MPOD measured at follow-up. Likewise, use of L/Z-containing supplements raised MPOD. Crude mean MPOD increased with ascending stage of ARM. However, adjustment for influential factors and exclusion of L supplement users removed differences of mean MPOD between ARM stages. Considering further the accompanying eye, study eyes with ARM had significantly higher MPOD when the contralateral eye had AMD. MPOD levels showed a high degree of intraindividual concordance and interindividual variability. Long-standing serum L levels, and in particular L supplementation, were the strongest determinants of MPOD. The hypothetical inverse association between MPOD and ARM stage was not confirmed.

Feed Forward Neural Network for Autofluorescence Imaging Classification

The key elements in cancer diagnostics are the early identification and estimation of the tumor growth anditsspreadinordertodeterminetheareatobeoperatedon. Theaimofourstudywastodevelopnewmethodsof analyzing autofluorescence images which will allow us an objective and accurate assessment of the locationof a tumor and will also be helpful in determining the advancement of the disease. The proposed classificationmethods are based on neural network algorithms. An Olympus company endoscopic system was used for anautofluorescence intestine imaging study. The autofluorescence imaging analysis process can be divided intoseveral main stages. The first step is preparation of a training data set. The second one involves selection offeaturespace, namelytheselectionof thosefeatureswhichenabledistinguishing thepathologicallyalteredareasfromthehealthyones. Finalstagesoftheanalysisincludepathologicallychangedtissueclassificationanddiagnosis.PACSnumbers:87.57.

Autofluorescence imaging analysis of gastric cancer

AIMS: To investigate the characteristics of gastric cancer in autofluorescence images.METHODS: A double‐channel laser scanning confocal microscope with an argon ion laser (excitation wavelength 488 nm) and helium−neon laser (excitation wavelength 543 nm) were used to detect autofluorescence from 16 gastric cancer tissue specimens and corresponding normal gastric tissue.RESULTS: Autofluorescence from normal gastric tissue produced a green‐colored image. The intensity of red color increased obviously in all gastric cancer tissues (100%) after illumination and the tissues produced a reddish‐brown‐colored image.CONCLUSIONS: A reddish‐brown image is characteristic of autofluorescence in gastric cancer detected by an argon ion laser and helium−neon laser with a double‐channel laser scanning confocal microscope. Autofluorescence imaging analysis is useful in the diagnosis of gastric cancer.