Intra- and inter-examiner reliability of digital images of skin donor areas in burns.

OBJECTIVE: The main objective of this study was to evaluate intra- and inter-rater reliability in the analysis of digital images of donor areas for skin in burn patients using the CaPAS plugin in the ImageJ®. METHODS: Donor sites were reviewed by two independent reviewers in duplicate. The capture of images was standardized on the same device and distance (with a millimeter ruler), without a flash. The evaluators were trained to capture the images and use the plugin. RESULTS: We selected 70 images from donor areas, from men and women between 18 and 60 years old. In the analysis of intra-examiner reliability, eight of the nine variables exhibited excellent reliability (0.985-0.998) and one (entropy) exhibited good reliability (0.525). The same was true for the inter-examiner analysis: excellent reliability for eight variables (0.824-0.993) and good reliability for entropy (0.501). CONCLUSIONS: The CaPAS plugin has proven to be a reliable tool for use in research in skin donor areas in burns, as demonstrated by its excellent intra- and inter-examiner reliability values. This is a pioneering study in the quantitative assessment of skin donor areas in burn patients using the CaPAS plugin.

Intra- and inter-examiner reliability of digital images of skin donor areas in burns

SUMMARY OBJECTIVE: The main objective of this study was to evaluate intra- and inter-rater reliability in the analysis of digital images of donor areas for skin in burn patients using the CaPAS plugin in the ImageJ®. METHODS: Donor sites were reviewed by two independent reviewers in duplicate. The capture of images was standardized on the same device and distance (with a millimeter ruler), without a flash. The evaluators were trained to capture the images and use the plugin. RESULTS: We selected 70 images from donor areas, from men and women between 18 and 60 years old. In the analysis of intra-examiner reliability, eight of the nine variables exhibited excellent reliability (0.985-0.998) and one (entropy) exhibited good reliability (0.525). The same was true for the inter-examiner analysis: excellent reliability for eight variables (0.824-0.993) and good reliability for entropy (0.501). CONCLUSIONS: The CaPAS plugin has proven to be a reliable tool for use in research in skin donor areas in burns, as demonstrated by its excellent intra- and inter-examiner reliability values. This is a pioneering study in the quantitative assessment of skin donor areas in burn patients using the CaPAS plugin.

Prediction of Radiation-Related Dental Caries Through PyRadiomics Features and Artificial Neural Network on Panoramic Radiography.

The prediction and detection of radiation-related caries (RRC) are crucial to manage the side effects of the head and the neck cancer (HNC) radiotherapy (RT). Despite the demands for the prediction of RRC, no study proposes and evaluates a prediction method. This study introduces a method based on artificial intelligence neural network to predict and detect either regular caries or RRC in HNC patients under RT using features extracted from panoramic radiograph. We selected fifteen HNC patients (13 men and 2 women) to analyze, retrospectively, their panoramic dental images, including 420 teeth. Two dentists manually labeled the teeth to separate healthy and teeth with either type caries. They also labeled the teeth by resistant and vulnerable, as predictive labels telling about RT aftermath caries. We extracted 105 statistical/morphological image features of the teeth using PyRadiomics. Then, we used an artificial neural network classifier (ANN), firstly, to select the best features (using maximum weights) and then label the teeth: in caries and non-caries while detecting RRC, and resistant and vulnerable while predicting RRC. To evaluate the method, we calculated the confusion matrix, receiver operating characteristic (ROC), and area under curve (AUC), as well as a comparison with recent methods. The proposed method showed a sensibility to detect RRC of 98.8% (AUC = 0.9869) and to predict RRC achieved 99.2% (AUC = 0.9886). The proposed method to predict and detect RRC using neural network and PyRadiomics features showed a reliable accuracy able to perform before starting RT to decrease the side effects on susceptible teeth.

Relationship between microvascular changes, autonomic denervation, and myocardial fibrosis in Chagas cardiomyopathy: Evaluation by MRI and SPECT imaging.

BACKGROUND: The relationship between microvasculopathy, autonomic denervation, and myocardial fibrosis, in Chagas cardiomyopathy is incompletely understood. The aim of this study was to explore the relative extent and anatomic distribution of myocardial hypoperfusion, autonomic denervation, and myocardial scarring using Single-Photon Emission Computerized Tomography (SPECT) imaging and Magnetic Resonance Imaging (MRI). METHODS: Thirteen patients with Chagas disease all had Iodine-123-metaiodobenzylguanidine (MIBG) SPECT, 99mTc-Sestamibi (MIBI) rest-stress SPECT, and gadolinium late enhancement MRI imaging within a 2-month interval. The anatomic location and extent of denervation, of stress-induced hypoperfusion and fibrosis, were assessed through image co-registration and quantification of abnormal tissue areas as a percent of total myocardium. RESULTS: The results showed a strong general anatomic concordance between areas of hypoperfusion, denervation, and fibrosis, suggesting that the three abnormal features may be correlated. Myocardial denervation was anatomically and quantitatively closely associated areas of stress hypoperfusion. CONCLUSION: Combined myocardial analysis of the extent and location of autonomic denervation, hypoperfusion, and scarring may allow for better understanding of the pathophysiology of Chagas cardiomyopathy. Autonomic myocardial denervation may be a more sensitive marker of cardiac involvement in Chagas Disease than finding by other imaging modalities.

Changes in the Complexity of Heart Rate Variability with Exercise Training Measured by Multiscale Entropy-Based Measurements.

Quantifying complexity from heart rate variability (HRV) series is a challenging task, and multiscale entropy (MSE), along with its variants, has been demonstrated to be one of the most robust approaches to achieve this goal. Although physical training is known to be beneficial, there is little information about the long-term complexity changes induced by the physical conditioning. The present study aimed to quantify the changes in physiological complexity elicited by physical training through multiscale entropy-based complexity measurements. Rats were subject to a protocol of medium intensity training ( n = 13 ) or a sedentary protocol ( n = 12 ). One-hour HRV series were obtained from all conscious rats five days after the experimental protocol. We estimated MSE, multiscale dispersion entropy (MDE) and multiscale SDiff q from HRV series. Multiscale SDiff q is a recent approach that accounts for entropy differences between a given time series and its shuffled dynamics. From SDiff q , three attributes (q-attributes) were derived, namely SDiff q m a x , q m a x and q z e r o . MSE, MDE and multiscale q-attributes presented similar profiles, except for SDiff q m a x . q m a x showed significant differences between trained and sedentary groups on Time Scales 6 to 20. Results suggest that physical training increases the system complexity and that multiscale q-attributes provide valuable information about the physiological complexity.

Enhancing quality in Diffusion Tensor Imaging with anisotropic anomalous diffusion filter

Abstract Introduction: Diffusion tensor imaging (DTI) is an important medical imaging modality that has been useful to the study of microstructural changes in neurological diseases. However, the image noise level is a major practical limitation, in which one simple solution could be the average signal from a sequential acquisition. Nevertheless, this approach is time-consuming and is not often applied in the clinical routine. In this study, we aim to evaluate the anisotropic anomalous diffusion (AAD) filter in order to improve the general image quality of DTI. Methods A group of 20 healthy subjects with DTI data acquired (3T MR scanner) with different numbers of averages (N=1,2,4,6,8, and 16), where they were submitted to 2-D AAD and conventional anisotropic diffusion filters. The Relative Mean Error (RME), Structural Similarity Index (SSIM), Coefficient of Variation (CV) and tractography reconstruction were evaluated on Fractional Anisotropy (FA) and Apparent Diffusion Coefficient (ADC) maps. Results The results point to an improvement of up to 30% of CV, RME, and SSIM for the AAD filter, while up to 14% was found for the conventional AD filter (p<0.05). The tractography revealed a better estimative in fiber counting, where the AAD filter resulted in less FA variability. Furthermore, the AAD filter showed a quality improvement similar to a higher average approach, i.e. achieving an image quality equivalent to what was seen in two additional acquisitions. Conclusions In general, the AAD filter showed robustness in noise attenuation and global image quality improvement even in DTI images with high noise level.

Populational brain models of diffusion tensor imaging for statistical analysis: a complementary information in common space

Abstract Introduction: The search for human brain templates has been progressing in the past decades and in order to understand disease patterns a need for a standard diffusion tensor imaging (DTI) dataset was raised. For this purposes, some DTI templates were developed which assist group analysis studies. In this study, complementary information to the most commonly used DTI template is proposed in order to offer a patient-specific statistical analysis on diffusion-weighted data. Methods 131 normal subjects were used to reconstruct a population-averaged template. After image pre processing, reconstruction and diagonalization, the eigenvalues and eigenvectors were used to reconstruct the quantitative DTI maps, namely fractional anisotropy (FA), mean diffusivity (MD), relative anisotropy (RA), and radial diffusivity (RD). The mean absolute error (MAE) was calculated using a voxel-wise procedure, which informs the global error regarding the mean intensity value for each quantitative map. Results the MAE values presented a low MAE estimate (max(MAE) = 0.112), showing a reasonable error measure between our DTI-USP-131 template and the classical DTI-JHU-81 approach, which also shows a statistical equivalence (p<0.05) with the classical DTI template. Hence, the complementary standard deviation (SD) maps for each quantitative DTI map can be added to the classical DTI-JHU-81 template. Conclusion In this study, variability DTI maps (SD maps) were reconstructed providing the possibility of a voxel-wise statistical analysis in patient-specific approach. Finally, the brain template (DTI-USP-131) described here was made available for research purposes on the web site (http://dx.doi.org/10.17632/br7bhs4h7m.1), being valuable to research and clinical applications.

Isotropic anomalous filtering in Diffusion-Weighted Magnetic Resonance Imaging.

Noise is inherent to Diffusion-Weighted Magnetic Resonance Imaging (DWI) and noise reduction methods are necessary. Although process based on classical diffusion is one of the most used approaches for digital image, anomalous diffusion has the potential for image enhancement and it has not been tested for DWI noise reduction. This study evaluates Anomalous Diffusion (AD) filter as DWI enhancement method. The proposed method was applied to magnetic resonance diffusion weighted images (DW-MRI) with different noise levels. Results show better performance for anomalous diffusion when compared to classical diffusion approach. The proposed method has shown potential in DWI enhancement and can be an important process to improve quality in DWI for neuroimage-based diagnosis.

Fractal dimension in quantifying the degree of myocardial cellular rejection after cardiac transplantation.

INTRODUCTION: The term "Fractal" is derived from the Latin fractus meaning "irregular" or "broken" considering the observed structure with a non-integer dimension. There are many studies which employed the Fractal Dimension (FD) as a diagnostic tool. One of the most common methods for its study is the "Box Counting Method". OBJECTIVE: The aim of the present study was to try to establish the contribution of FD in the quantification of myocardial cellular rejection after cardiac transplantation. METHODS: Microscopic digital images were captured at 800x600 resolution (magnification 100x). FD was calculated with the aid of "ImageJ software" with adaptations. The classification of the degrees of rejection was in agreement with the "International Society for Heart and Lung Transplantation" (ISHLT 2004). The final report of the degree of rejection was confirmed and redefined after an exhaustive review of the slides by an external experienced pathologist. 658 slides were evaluated with the following distribution among the degrees of rejection (R): 335 (0R); 214 (1R); 70 (2R); 39 (3R). The data were statistically analyzed with Kruskal-Wallis tests and ROC curves being considered significant values of P < 0.05. RESULTS: There was significant statistical difference between the various degrees of rejection with the exception of R3 versus R2. The same trend was observed in applying the ROC curve. CONCLUSION: FD may contribute to the assessment of myocardial cellular rejection. Higher values are directly associated with progressively higher degrees of rejection. This may help in decision making of doubtful cases and those which contemplate the intensification of immunosuppressive medication.

Dimensão fractal na quantificação do grau de rejeição celular miocárdica pós-transplante cardíaco / Fractal dimension in quantifying the degree of myocardial cellular rejection after cardiac transplantation

INTRODUÇÃO: O termo "fractal" é derivado do latim fractus, que significa "irregular" ou "quebrado", considerando a estrutura observada como tendo uma dimensão não-inteira. Há muitos estudos que empregaram a Dimensão Fractal (DF) como uma ferramenta de diagnóstico. Um dos métodos mais comuns para o seu estudo é a "Box-plot counting" (Método de contagem de caixas). OBJETIVO: O objetivo do estudo foi tentar estabelecer a contribuição da DF na quantificação da rejeição celular miocárdica após o transplante cardíaco. MÉTODOS: Imagens microscópicas digitalizadas foram capturadas na resolução 800x600 (aumento de 100x). A DF foi calculada com auxílio do "software ImageJ", com adaptações. A classificação dos graus de rejeição foi de acordo com a "Sociedade Internacional de Transplante Cardíaco e Pulmonar" (ISHLT 2004). O relatório final do grau de rejeição foi confirmado e redefinido após exaustiva revisão das lâminas por um patologista experiente externo. No total, 658 lâminas foram avaliadas, com a seguinte distribuição entre os graus de rejeição (R): 335 (0R), 214 (1R), 70 (2R), 39 (3R). Os dados foram analisados estatisticamente com os testes Kruskal-Wallis e curvas ROC sendo considerados significantes valores de P < 0,05. RESULTADOS: Houve diferença estatística significativa entre os diferentes graus de rejeição com exceção da 3R versus 2R. A mesma tendência foi observada na aplicação da curva ROC. CONCLUSÃO: ADF pode contribuir para a avaliação da rejeição celular do miocárdio. Os valores mais elevados estiveram diretamente associados com graus progressivamente maiores de rejeição. Isso pode ajudar na tomada de decisão em casos duvidosos e naqueles que possam necessitar de intensificação da medicação imunossupressora.

INTRODUCTION: The term "Fractal" is derived from the Latin fractus meaning "irregular" or "broken" considering the observed structure with a non-integer dimension. There are many studies which employed the Fractal Dimension (FD) as a diagnostic tool. One of the most common methods for its study is the "Box Counting Method". OBJECTIVE: The aim of the present study was to try to establish the contribution of FD in the quantification of myocardial cellular rejection after cardiac transplantation. METHODS: Microscopic digital images were captured at 800x600 resolution (magnification 100x). FD was calculated with the aid of "ImageJ software" with adaptations. The classification of the degrees of rejection was in agreement with the "International Society for Heart and Lung Transplantation" (ISHLT 2004). The final report of the degree of rejection was confirmed and redefined after an exhaustive review of the slides by an external experienced pathologist. 658 slides were evaluated with the following distribution among the degrees of rejection (R): 335 (0R); 214 (1R); 70 (2R); 39 (3R). The data were statistically analyzed with Kruskal-Wallis tests and ROC curves being considered significant values of P < 0.05. RESULTS: There was significant statistical difference between the various degrees of rejection with the exception of R3 versus R2. The same trend was observed in applying the ROC curve. CONCLUSION: FD may contribute to the assessment of myocardial cellular rejection. Higher values are directly associated with progressively higher degrees of rejection. This may help in decision making of doubtful cases and those which contemplate the intensification of immunosuppressive medication.

Quantitative estimation of the nonstationary behavior of neural spontaneous activity.

The "stationarity time" (ST) of neuronal spontaneous activity signals of rat embryonic cortical cells, measured by means of a planar Multielectrode Array (MEA), was estimated based on the "Detrended Fluctuation Analysis" (DFA). The ST is defined as the mean time interval during which the signal under analysis keeps its statistical characteristics constant. An upgrade on the DFA method is proposed, leading to a more accurate procedure. Strong statistical correlation between the ST, estimated from the Absolute Amplitude of Neural Spontaneous Activity (AANSA) signals and the Mean Interburst Interval (MIB), calculated by classical spike sorting methods applied to the interspike interval time series, was obtained. In consequence, the MIB may be estimated by means of the ST, which further includes relevant biological information arising from basal activity. The results point out that the average ST of MEA signals lies between 2-3 seconds. Furthermore, it was shown that a neural culture presents signals that lead to different statistical behaviors, depending on the relative geometric position of each electrode and the cells. Such behaviors may disclose physiological phenomena, which are possibly associated with different adaptation/facilitation mechanisms.

Análise videodensitométrica da placa carotídea vulnerável: correlação histopatológica / Videodensitometric analysis of vulnerable carotid plaque: correlation with histological examination

Objetivos: Estabelecer a correlação entre a avaliação quantitativa, através da caracterização tecidual videodensitométrica, de imagens ultra-sonográficas bidimensionais digitalizadas e a análise histopatológica de placas carotídeas vulneráveis removidas cirurgicamente da artéria carótida, com estenose acima de 70 por cento, foram submetidos à caracterização tecidual ultra-sônica da placa antes do procedimento cirúrgico. Um software de computador (CaPAS - Carotid Plaque Analysis Software) foi especificamente desenvolvido para a análise videodensitométrica das imagens bidimensionais digitalizadas das placas carotídeas através de índice estatísticos de primeira (NMC - nível médio de cinza e DP - desvio padrão) e segunda (Entopia, Energia e Homogeneidade) ordens. Os pacientes foram divididos em 3 grupos de acordo com a sintomatologia: GRUPO I(n igual 6), pacientes com sintomas até 3 meses antecedendo o procedimento cirúrgico, GRUPO II(n igual 9), pacientes com sintomas acima de 3 meses antecedendo o procedimento cirúrgico e GRUPO III(n igual 10), pacientes assintomáticos. Os espécimes cirúrgicos foram analisados histopatologicamente para determinar as percentagens de gordura/necrose, fibrose e cálcio. Resultados: O NMC (primeira ordem) e os parâmetros de segunda ordem (entropia, energia e homogeneidade) diferenciaram os grupos clínicos, mas não se correlacionaram com os achados histopatológicos, mostrando apenas um tendência no NMC (primeira ordem) em refletir tais achados. Conclusão: A análise videodensitométrica de imagens bidimensionais digitalizadas pode ser usada para identificar placas vulneráveis e potencialmente instáveis, porém não se correlaciona com a proporção de componentes estruturais básicos avaliados histologicamente.

Quantitative analysis of segmental left ventricular wall motion using a polar representation of color kinesis images / Avaliação quantitativa da mobilidade segmentar do ventrículo esquerdo utilizando uma representação polar das imagens de "color kinesis"

A "color kinesis (CK) é uma técnica que representa o tempo e a magnitude da mobilidade global e segmentar do ventrículo esquerdo (MSVE) em tempo real. Neste estudo descreve-se um novo método para representar estas imagens na forma "bulls-eye" em mapas polares que provêem uma avaliação integrada e objetiva da MSVE. Foram avaliados indivíduos normais e em pacientes apresentando anormalidades na MSVE no estudo ecocardiográfico bidimensional com o objetivo de verificar a capacidade desta técnica para identificar e quantificar automaticamente a disfunção ventricular. Os dados obtidos demonstram que, embora a representação polar de imagens de CK seja factível em uma elevada proporção de indivíduos e possa proporcionar uma avaliação quantitativa da MSVE mais objetiva e menos dependente do operador, essa ferramenta de processamento de imagens mostrou limitada capacidade para identificação automática de disfunção ventricular quando comparada com a análise de observadores experientes.