Collagen and elastic fibers assessment of the human heart valves for age estimation in Thais using image analysis.

The study investigated the relationship between the histological compositions of the tricuspid, pulmonary, mitral, and aortic valves, and age. All 85 fresh human hearts were obtained with an age range between 20 and 90 years. The central area of the valves was conducted to analyze the density of collagen and elastic fibers by using an image analysis program. Neural network function in MATLAB was used for classification data and accuracy test of the age predictive model. Overall, a gradual increase in the density of collagen and elastic fibers was demonstrated with age in all valve types. The pulmonary valve cusps had the least density of collagen and elastic contents, whereas the most dense of collagen was found in the mitral leaflets. A similarity was noted for the elastic fibers in the tricuspid, mitral, and aortic valves. The highest correlation between the collagen (r = 0.629) and elastic fibers (r = 0.713) and age was found in the noncoronary cusp of the aortic valve. The established predictive equations using collagen and elastic fibers in the noncoronary cusp provided the standard error of ± 14.0 and 12.5 years, respectively. A 60.9% of accuracy was found in all age groups using collagen, while accuracy in elastic fibers showed 70.0% in the classification process using the neural networks. The current study provided additional data regarding age-associated changes of collagen and elastic fibers in the human heart valves in Thais and the benefits and application in age forensic identification.

Sex determination using the clavicle by deep learning in a Thai population.

Determining sex is a critical process in estimating biological profiles from skeletal remains. The clavicle is interesting in studying sex determination because it is durable to the environment, slow to decay, challenging to destroy, making the clavicle useful in autopsies and identification which can then lead to verification. The goal of this study was to use deep learning in determining sex from clavicles within the Thai population and obtain the accuracies for the validation set using a convolutional neural network (GoogLeNet). A total of 200 pairs of clavicles were obtained from 200 Thai persons (100 males and 100 females) as part of a training group. For the deep learning approach, the clavicle was photographed, and each clavicle image was submitted to the training model for sex determination. Training groups of 200 samples were made. Images of the same size were input into the training model. The percentage of the validation set accuracy was calculated from the MATLAB program. GoogLeNet was the best training model and get the result of validation set accuracy. The results of this study found accuracies for a validation set with the highest overall right lateral view of the clavicle with an accuracy of 95%. Accuracy from the validation set of each view of the clavicle can demonstrate the forensic value of sex determination. A deep learning approach with clavicles can determine the sex and is simple to utilize for forensic anthropology professionals.

The Success of Serious Games and Gamified Systems in HIV Prevention and Care: Scoping Review.

BACKGROUND: AIDS, which is caused by HIV, has long been one of the most significant global public health issues. Since the beginning of the HIV epidemic, various types of nonelectronic communication tools have been commonly used in HIV/AIDS prevention and care, but studies that apply the potential of electronic games are still limited. OBJECTIVE: We aimed to identify, compare, and describe serious games and gamified systems currently used in HIV/AIDS prevention and care that were studied over a specific period of time. METHODS: A scoping review was conducted into serious games and gamified systems used in HIV prevention and care in various well-known digital libraries from January 2010 to July 2021. RESULTS: After identifying research papers and completing the article selection process, 49 of the 496 publications met the inclusion criteria and were examined. A total of 32 articles described 22 different serious games, while 17 articles described 13 gamified systems for HIV prevention and care. CONCLUSIONS: Most of the studies described in the publications were conducted in the United States, while only a few studies were performed in sub-Saharan African countries, which have the highest global HIV/AIDS infection rates. Regarding the development platform, the vast majority of HIV/AIDS gaming systems were typically deployed on mobile devices. This study demonstrates the effectiveness of using serious games and gamified systems. Both can improve the efficacy of HIV/AIDS prevention strategies, particularly those that encourage behavior change.

A web application for sex and stature estimation from radiographic proximal femur for a Thai population.

In both forensic and archaeological domains, the discovery of incomplete human remains is a frequent occurrence. Nevertheless, the estimation of biological profiles from such remains presents a challenge due to the absence of crucial skeletal elements, such as the skull and pelvis. This study aimed to assess the utility of the proximal femur in the forensic identification process by creating a web application for osteometric analysis of the proximal femur. The aim was to determine the sex and stature of an individual from radiographs of the left anteroposterior femur. To accomplish this, an automated method was developed for acquiring linear measurements from radiographic images of the proximal femur using Python tools. The application of Hough techniques and Canny edge detection was utilized to generate linear femoral dimensions from radiographs. A total of 354 left femora were radiographed and measured by the algorithm. The sex classification model employed in this study was the Naïve Bayes algorithm (accuracy = 91.2 %). Results indicated that Gaussian process regression (GPR) was the most effective method for estimating stature (mean error = 4.68 cm, SD = 3.93 cm). The proposed web application holds the potential to serve as a valuable asset in the realm of forensic investigations in Thailand, particularly in the estimation of biological profiles from fragmentary skeletal remains.

Convolutional neural network of age-related trends digital radiographs of medial clavicle in a Thai population: a preliminary study.

Age at death estimation has always been a crucial yet challenging part of identification process in forensic field. The use of human skeletons have long been explored using the principle of macro and micro-architecture change in correlation with increasing age. The clavicle is recommended as the best candidate for accurate age estimation because of its accessibility, time to maturation and minimal effect from weight. Our study applies pre-trained convolutional neural network in order to achieve the most accurate and cost effective age estimation model using clavicular bone. The total of 988 clavicles of Thai population with known age and sex were radiographed using Kodak 9000 Extra-oral Imaging System. The radiographs then went through preprocessing protocol which include region of interest selection and quality assessment. Additional samples were generated using generative adversarial network. The total clavicular images used in this study were 3,999 which were then separated into training and test set, and the test set were subsequently categorized into 7 age groups. GoogLeNet was modified at two layers and fine tuned the parameters. The highest validation accuracy was 89.02% but the test set achieved only 30% accuracy. Our results show that the use of medial clavicular radiographs has a potential in the field of age at death estimation, thus, further study is recommended.

Deep learning and morphometric approach for Sex determination of the lumbar vertebrae in a Thai population.

Sex determination is a fundamental step in biological profile estimation from skeletal remains in forensic anthropology. This study proposes deep learning and morphometric technique to perform sex determination from lumbar vertebrae in a Thai population. A total of 1100 lumbar vertebrae (L1-L5) from 220 Thai individuals (110 males and 110 females) were obtained from the Forensic Osteology Research Center, Faculty of Medicine, Chiang Mai University, Thailand. In addition, two linear measurements of superior and inferior endplates from the digital caliper and image analysis were carried out for morphometric technique. Deep learning applied image classification to the superior and inferior endplates of the lumbar vertebral body. All lumbar vertebrae images are included in the dataset to increase the number of images per class. The accuracy determined the performance of each technique. The results showed the accuracies of 82.7%, 90.0%, and 92.5% for digital caliper, image analysis, and deep learning techniques, respectively. The lumbar vertebrae L1-L5 exhibit sexual dimorphism and can be used in sex estimation. Deep learning is more accurate in determining sex than the morphometric method. In addition, the subjectivity and errors in the measurement are decreased. Finally, this study presented an alternative approach to determining sex from lumbar vertebrae when the more traditionally used skeletal elements are incomplete or absent.

Comparison of sex determination using three methods applied to the greater sciatic notch of os coxae in a Thai population: Dry bone morphology, 2-dimensional photograph morphometry, and deep learning artificial neural network.

The os coxa is commonly used for sex and age estimation with a high degree of accuracy. Our study aimed to compare the accuracy among three methods, which include a deep learning approach to increase the accuracy of sex prediction. A total sample of 250 left os coxae from a Thai population was divided into a 'training' set of 200 samples and a 'test' set of 50 samples. The age of the samples ranged from 26 to 94 years. Three methods of sex determination were assessed in this experiment: a dry bone method, an image-based method and deep learning method. The intra- and inter-observer reliabilities were also assessed in the dry bone and photo methods. Our results showed that the accuracies were 80.65%, 90.3%, and 91.95% for the dry bone, image-based, and deep learning methods, respectively. The greater sciatic notch shape was wide and symmetrical in females while narrow and asymmetrical in males. The intra- and inter-observer agreements were moderate to almost perfect level (Kappa = 0.67-0.93, ICC = 0.74-0.94). Conclusion: The image-based and deep learning methods were efficient in sex determination. However, the deep learning technique performed the best among the three methods due to its high accuracy and rapid analysis. In this study, deep learning technology was found to be a viable option for remote consultations regarding sex determination in the Thai population.

Estimating age from digital radiographic images of lumbar vertebrae in a Thai population using an image analysis technique.

Using the lumbar vertebra for age estimation is helpful in cases when skeletal remains are incomplete and typical skeletal age indicators are absent. This study aimed to apply an image analysis method in extracting black pixel variables for age estimation by using the radiographic images of lumbar vertebra in a Thai population. All lumbar vertebrae L1-L5 of 220 (110 males and 110 females) from Thai individuals of known sex and ages were studied. The variables of Total Percentage of black pixels (TP), Mean Percentage of black pixels (MP), and Ratio of black to white pixels (BW), were calculated to assess the relationship between black pixel variables and aging. Equations were formulated using linear regression analysis. The results of this study indicated three variables of the lumbar vertebrae had significantly positive correlations with age. The correlation between parameters with age in males ranged 0.211-0.419, while the range in females was 0.219-0.458. The appropriate linear regression equation with the total and mean percentages of black pixel variables shows Age = -1.348+0.871 (TP) +0.514 (MP) of L4 for males (SEE; 15.4 years), and Age = 5.338 +0.316 (TP) +0.952 (MP) of L1 for females (SEE; 13.8 years). Age estimation using an image analysis method is an alternative to investigating the trabecular structure. The black pixel variable is not the actual value of bone density. However, it is useful to study its relationship with aging.

The development and testing of Thai facial soft tissue thickness data in three-dimensional computerized forensic facial reconstruction.

Forensic facial reconstruction is a useful tool to assist the public in recognizing human remains, leading to positive forensic investigation outcomes. To reproduce a virtual face, facial soft tissue thickness is one of the major guidelines to reach the accuracy and reliability for three-dimensional computerized facial reconstruction, a method that is making a significant contribution to improving forensic investigation and identification. This study aimed to develop a facial soft tissue thickness dataset for a Thai population, and test its reliability in the context of facial reconstruction. Three-dimensional facial reconstruction was conducted on four skulls (2 males and 2 females, with ages ranging between 51 to 60 years). Two main tools of three-dimensional computer animation and modeling software-Blender and Autodesk Maya-were used to rebuild the three-dimensional virtual face. The three-dimensional coordinate (x, y, z) cutaneous landmarks on the mesh templates were aligned homologous to the facial soft tissue thickness markers on the three-dimensional skull model. The final three-dimensional virtual face was compared to the target frontal photograph using face pool comparison. Four three-dimensional virtual faces were matched at low to moderate levels, ranging from 30% to 70% accuracy. These results demonstrate that the facial soft tissue thickness database of a Thai population applied in this study could be useful for three-dimensional computerized facial reconstruction purposes.

Sex and stature estimation from adult lumbar vertebrae in a Thai population based on image analysis / Estimación de sexo y estatura de vértebras lumbares adultas en una población Tailandesa basada en análisis de imagen

SUMMARY: Although molecular techniques evolved considerably in last years, anthropological methods of assessing skeletal remains, continues to be an important tool in the identification process in medico legal investigations. The objective of this study was to develop a discriminant function equation for estimating sex and stature using several measurements of lumbar vertebrae in a Thai population. We studied 150 lumbar columns (75 male and 75 female) age range of 22 to 89 years from the Forensic Osteology Research Center, Chiang Mai University, Thailand. The quantitative variables with sex were analyzed by the discriminant function analysis and that with stature were calculated using linear regression. The pixel density of the major axis of the trabecular surface of superior endplate of the first lumbar vertebra had the most accuracy in sex determination. The regression equation with quantitative variables in stature estimation described 32.3 % of the total variance with standard error of estimate of 7.736 cm. Lumbar vertebrae can be used as part of the stature and sex quantitatively and qualitatively estimating in Thais incomplete skeletal remains.

RESUMEN: Los métodos antropológicos de evaluación del esqueleto siguen siendo una herramienta importante en el proceso de identificación en las investigaciones médico-legales. El objetivo de este estudio fue desarrollar una ecuación de función discriminante para estimar el sexo y la estatura utilizando varias medidas de las vértebras lumbares en una población tailandesa. Se estudiaron 150 columnas lumbares (75 hombres y 75 mujeres) con un rango etario de 22 a 89 años del Centro de Investigación de Osteología Forense, Universidad de Chiang Mai, Tailandia. Las variables cuantitativas de sexo se analizaron mediante el análisis de función discriminante y la estatura fue calculada mediante regresión lineal. En cuanto a la determinación de sexo, la densidad de píxeles del eje mayor de superficie trabecular de la placa terminal superior de la primera vértebra lumbar fue de mayor precisión. La ecuación de regresión con variables cuantitativas en la estimación de la estatura describió el 32,3 % de la varianza total con el error estándar de estimación de 7,736 cm. Las vértebras lumbares se pueden utilizar como parte de la estatura y el sexo, estimando cuantitativa y cualitativamente los restos esqueléticos incompletos en sujetos tailandeses.

The estimation of age from elastic fibers in the tunica media of the aortic wall in a thai population: a preliminary study using aorta image analysis.

Image analysis has an increasing role in the identification of individuals in forensic application. Beside the bones, microstructural of arteries can be used in age estimation study. Aorta is the largest elastic artery which consists of many elastic fibers. Elastin in arterial wall highly resist to chemical and physical influence. The purposes of the study were to quantify elastic fibers in tunica media in each location of the aorta and examine the correlation between elastic fibers and age by using image analysis program. A total of 36 human aortas were dissected in 4 locations. The aortas were obtained from cadavers with an age range of 20 to 90 years. Specimens were stained with Elastic Van Gieson staining. Histological images were investigated about elastic fibers using light microscope with cellSens program and aorta image analysis was used for the evaluation of data. The results showed that the mean percentage density of elastic fibers in the ascending aorta and the aortic arch increased. However, the mean percentage density of elastic fibers decreased in the 31 to 40 years age group in the thoracic aorta and the abdominal aorta and decreased in each location of aorta continuously until 81 to 90 years. The abdominal aorta showed the highest correlation with age (r=0.732) followed by the thoracic aorta, the aortic arch and the ascending aorta, respectively. Changes in the percentage density of elastic fibers in the tunica media of the aortic wall can be used to add information to age estimation for identification purposes.

Serious Game for Teaching Undergraduate Medical Students in Cleft lip and Palate Treatment Protocol.

OBJECTIVES: To develop and evaluate a serious game to deliver knowledge about the cleft lip with or without cleft palate (CL/P) protocol used in Craniofacial Center, Chiang Mai University. METHODS: The game "Cleft Island" was developed then extensively evaluated using different criteria, including the measured knowledge gained by participants, and gameplay experience. A group of 53 fourth and fifth-year medical students (male: 24, female: 29) were recruited to take part in an experiment. They were from the Faculty of Medicine, Chiang Mai University, and had just rotated to the Department of Surgery. Three evaluations were conducted: 1) to test whether the players had competently gained CL/P knowledge; 2) to evaluate the usability of the game according to the System Usability Scale (SUS); and 3) to evaluate the game experience in terms of a Game Experience Questionnaire (GEQ) test. RESULTS: The results indicate a statistically significant improvement of medical students' knowledge after performing the Wilcoxon Signed-Ranks test (p < 0.5) between pre-test and post-test scores of the same medical student group; the acceptable average SUS score (M = 55.28) of the serious game; a moderate degree of experience of the GEQ components including positive affect (M = 2.64), competence (M = 2.49), and immersion (M = 2.21). CONCLUSIONS: Cleft Island can be used as an effective supplementary instructional material, which has the potential to provide significant knowledge of CL/P treatment protocol for the players. As far as the authors are aware, this is the first study to implement and assess a serious game for training in CL/P protocol.

Image analysis of morphometric evaluation from the heart valves for age estimation in Thai population / Análisis de la evaluación morfométrica de las valvas cardíacas para la estimación de la edad en la población tailandesa

Determination of age represents one of the most important aspects in forensic identification. Through aging, changes can occur in morphological structures of the heart valves. The objective is to examine the relationship between the dimensions of the rigth atrioventricular (tricuspid), pulmonary, left atrioventricular (mitral), and aortic valves and age at death. Sixty fresh human hearts were obtained from Department of Anatomy and Department of Forensic Medicine, Faculty of medicine, Chiang Mai University, Thailand. The age of individuals was between 20-90 years. We investigated the morphometric parameters of the valves were taken including: valve circumference, length, the height and area of each leaflet. All parameters were measured by using specific image analysis software. The correlation test and predictive equation were established. The positive correlation between the circumference, area of posterior leaflet, height of anterior leaflet, and area of anterior leaflet of the rigth atrioventricular valve were found. The left atrioventricular valve showed correlation with age in circumference, length and area of posterior leaflet. For the pulmonary and aortic valves, there were correlated between circumference at sinotubular junction and leaflet sizes in almost leaflets. The circumference at sinotubular junction of the pulmonary valve was highest significantly correlation with age (r=0.693). The predictive equation was age = -3.659+0.652(Circumference at sinotubular junction of the pulmonary valve) with standard error of ± 14.7 years. Additional knowledge of morphometric features in human heart valves and its relationship with age could be used as age indicator in forensic field.

La determinación de la edad representa uno de los aspectos más importantes en la identificación forense. Pueden ocurrir cambios a través del envejecimiento, en las estructuras morfológicas de las válvulas cardíacas. El objetivo de este estudio fue examinar la relación entre las dimensiones de las valvas atrioventricular derecha (tricúspide), pulmonar, atrioventricular izquierda (mitral) y aórtica, y la edad en relación a la muerte. Se obtuvieron sesenta corazones humanos frescos del Departamento de Anatomía y el Departamento de Medicina Forense de la Facultad de Medicina de la Universidad de Chiang Mai, Tailandia. La edad de las personas fluctuaba entre los 20 y 90 años. Investigamos los parámetros morfométricos de las valvas analizadas, incluyendo: circunferencia de la valva, longitud, altura y área de cada valva. Todos los parámetros se midieron utilizando un software de análisis de imagen específico. Se estableció la prueba de correlación y la ecuación predictiva. Se encontró la correlación positiva entre la circunferencia, el área de la valvula posterior, la altura de la valvula anterior y el área de la valvula anterior de la valva atrioventricular derecha. La valva atrioventricular izquierda mostró correlación con la edad en la circunferencia, longitud y área de la valvula posterior. Para las valvas pulmonar y aórtica, se correlacionó entre la circunferencia en la unión sinotubular y el tamaño de las válvulas. La circunferencia en la unión sinotubular de la valva pulmonar fue la mayor correlación significativa con la edad (r = 0,693). La ecuación predictiva fue edad = -3,659 + 0,652 (circunferencia en la unión sinotubular de la valva pulmonar) con error estándar de ± 14,7 años. El conocimiento adicional de las características morfométricas en las valvas cardíacas humanas y su relación con la edad podría usarse como indicador de edad en el campo forense.

Heuristic neural network approach in histological sections detection of hydatidiform mole.

A heuristic-based, multineural network (MNN) image analysis as a solution to the problematical diagnosis of hydatidiform mole (HM) is presented. HM presents as tumors in placental cell structures, many of which exhibit premalignant phenotypes (choriocarcinoma and other conditions). HM is commonly found in women under age 17 or over 35 and can be partial HM or complete HM. Appropriate treatment is determined by correct categorization into PHM or CHM, a difficult task even for expert pathologists. Image analysis combined with pattern recognition techniques has been applied to the problem, based on 15 or 17 image features. The use of limited data for training and validation set was optimized using a k -fold validation technique allowing performance measurement of different MNN configurations. The MNN technique performed better than human experts at the categorization for both the 15- and 17-feature data, promising greater diagnostic consistency, and further improvements with the availability of larger datasets.

Age Estimation of Lumbar Vertebrae by Visual Assessment in a Thai Population.

BACKGROUND: The age estimation of bone is essential for identification of the unknown-identity persons in both forensic and anthropological sciences. The lumbar vertebrae carry the most weight; hence, they have more biomechanical stress than any other vertebrae. As a result, the degenerative changes commonly occur in them. However, the estimation from visual assessment in lumbar vertebrae has not been reported in a Thai population. OBJECTIVE: To evaluate the age estimation from the degree of osteophyte formation, the macroporosity, and the cortical surface to develop equations of lumbar vertebrae. MATERIALS AND METHODS: A total of 250 lumbar columns (125 males and 125 females) in age range of 22 to 89 years were collected from the Forensic Osteology Research Center (FORC), Faculty of Medicine, Chiang Mai University. RESULT: The most appropriate linear regression equation was used to estimate age by the inferior surface of L1 vertebra (R2= 0.408) with the standard error of 11.686 years. CONCLUSION: It was clear to recognize that three morphological aspects will be useful methods for forensic situations.