Impact of L-PRF on pain and healing outcomes in lower third molar surgery: a randomized split-mouth trial.

This study explored the effects of L-PRF on pain, soft tissue healing, periodontal condition, and post-extraction bone repair of mandibular third molars (3Ms). A randomized, prospective, triple-blind, split-mouth clinical trial was conducted with 34 volunteers. Eligible patients were randomly allocated into two treatments: G1 (without L-PRF), G2 (alveoli filled with L-PRF), in which the removal of bilateral 3Ms was performed at the same surgical time. Outcomes were assessed according to a visual analogue scale (pain), soft tissue scoring system (wound healing), periodontal probing of mandibular second molar. Bone repair was determined by volumetric analysis (ITK-SNAP software) and fractal analysis (ImageJ software). An intention-to-treat approach to Statistical analysis was used. L-PRF reduced pain in the 7-day postoperative follow-up (p = 0.019) and not only improved soft tissue healing after 1 month of follow-up (p = 0.021), but also probing depth (distal face) in 3 months postoperatively (p = 0.011). Significant alveolar reduction occurred in 3 months after surgery in both treatments (p < 0.05), however, this was more significant in G1 (p = 0.016). The fractal dimension showed no statistical differences. L-PRF improved postoperative clinical parameters of pain, soft tissue healing, and periodontal condition, suggesting that it has a beneficial effect on preserving the alveolar ridge and accelerating the initial repair process.

Multifractality approach of a generalized Shannon index in financial time series.

Multifractality is a concept that extends locally the usual ideas of fractality in a system. Nevertheless, the multifractal approaches used lack a multifractal dimension tied to an entropy index like the Shannon index. This paper introduces a generalized Shannon index (GSI) and demonstrates its application in understanding system fluctuations. To this end, traditional multifractality approaches are explained. Then, using the temporal Theil scaling and the diffusive trajectory algorithm, the GSI and its partition function are defined. Next, the multifractal exponent of the GSI is derived from the partition function, establishing a connection between the temporal Theil scaling exponent and the generalized Hurst exponent. Finally, this relationship is verified in a fractional Brownian motion and applied to financial time series. In fact, this leads us to proposing an approximation called local fractional Brownian motion approximation, where multifractal systems are viewed as a local superposition of distinct fractional Brownian motions with varying monofractal exponents. Also, we furnish an algorithm for identifying the optimal q-th moment of the probability distribution associated with an empirical time series to enhance the accuracy of generalized Hurst exponent estimation.

Multifractal analysis of maize and soybean DNA.

This paper investigates the complexity of DNA sequences in maize and soybean using the multifractal detrended fluctuation analysis (MF-DFA) method, chaos game representation (CGR), and the complexity-entropy plane approach. The study aims to understand the patterns and structures of these DNA sequences, which can provide insights into their genetic makeup and improve crop yield and quality. The results show that maize and soybean DNA sequences exhibit fractal properties, indicating a complex and self-organizing structure. We observe the persistence trend between sequences of base pairs, which indicates long-range correlations between base pairs. We also identified the stochastic nature of the DNA sequences of both species.

Multifractal fluctuations in zebrafish (Danio rerio) polarization time series.

In this work, we study the polarization time series obtained from experimental observation of a group of zebrafish (Danio rerio) confined in a circular tank. The complex dynamics of the individual trajectory evolution lead to the appearance of multiple characteristic scales. Employing the Multifractal Detrended Fluctuation Analysis (MF-DFA), we found distinct behaviors according to the parameters used. The polarization time series are multifractal at low fish densities and their average scales with ρ - 1 / 4 . On the other hand, they tend to be monofractal, and their average scales with ρ - 1 / 2 for high fish densities. These two regimes overlap at critical density ρ c , suggesting the existence of a phase transition separating them. We also observed that for low densities, the polarization velocity shows a non-Gaussian behavior with heavy tails associated with long-range correlation and becomes Gaussian for high densities, presenting an uncorrelated regime.

Multifractal Analysis of Brain Tumor Interface in Glioblastoma.

The dynamics of tumor growth is a very complex process, generally accompanied by numerous chromosomal aberrations that determine its genetic and dynamical heterogeneity. Consequently, the tumor interface exhibits a non-regular and heterogeneous behavior often described by a single fractal dimension. A more suitable approach is to consider the tumor interface as a multifractal object that can be described by a set of generalized fractal dimensions. In the present work, detrended fluctuation and multifractal analysis are used to characterize the complexity of glioblastoma.

Adaptive exponential integrate-and-fire model with fractal extension.

The description of neuronal activity has been of great importance in neuroscience. In this field, mathematical models are useful to describe the electrophysical behavior of neurons. One successful model used for this purpose is the Adaptive Exponential Integrate-and-Fire (Adex), which is composed of two ordinary differential equations. Usually, this model is considered in the standard formulation, i.e., with integer order derivatives. In this work, we propose and study the fractal extension of Adex model, which in simple terms corresponds to replacing the integer derivative by non-integer. As non-integer operators, we choose the fractal derivatives. We explore the effects of equal and different orders of fractal derivatives in the firing patterns and mean frequency of the neuron described by the Adex model. Previous results suggest that fractal derivatives can provide a more realistic representation due to the fact that the standard operators are generalized. Our findings show that the fractal order influences the inter-spike intervals and changes the mean firing frequency. In addition, the firing patterns depend not only on the neuronal parameters but also on the order of respective fractal operators. As our main conclusion, the fractal order below the unit value increases the influence of the adaptation mechanism in the spike firing patterns.

Fractal analysis of the mandible cortical bone: correlation among fractal dimension values obtained by two processing methods from periapical radiograph and micro-computed tomography with cone-beam computed tomography.

The objectives of the present study were to assess Fractal Dimension (FD) values in the mandible cortical bone obtained from digital periapical radiographs (DPR), high-resolution microtomography (µCT), and cone-beam computed tomography (CBCT), by two processing methods: binarization (FD.b) and grayscale-based method (FD.f) and, finally, to identify the correlation among these values with other micro-architectural parameters. For this, a prospective study was conducted on 18 healthy individuals (mean age 23 ± 2.4 years old) who underwent third molar extraction. Pre-operative CBCT scans were conducted, bone fragments were removed from the retro-molar region, and DPR and µCT were performed on those bone samples. FD.b and FD.f values were calculated using three parasagittal sections for CBCT, one image for DPR, and three sections for µCT. The 3D bone microarchitecture was analyzed in µCT (voxel size: 19 µm). As a result, FD.b mean values of 1.55 ± 0.02 and 1.80 ± 0.01 were obtained for CBCT and µCT, respectively. Furthermore, FD.f mean values of 1.22 ± 0.12 for DPR, 0.99 ± 0.04 for CBCT, and 1.30 ± 0.07 for µCT were obtained. Both FD.b and FD.f values showed a good agreement. FD.f was negatively correlated with the standard deviation of the mean gray value (p = 0.003) for DPR and intra-cortical bone surface (p = 0.02) for µCT. In conclusion, image processing with or without binarization revealed different values for FD, although showing agreement. The grayscale-based method retrieved FD values correlated with the gray levels and the cortical porous network, which means that FD can be a valuable index for mandibular cortical bone evaluation. FD is associated with mineralization and microarchitecture. Nevertheless, there was no correlation between FD values obtained from low- (DPR) and high-resolution (µCT) X-ray modalities with FD obtained from the in vivo CBCT.

Fractal and fractional SIS model for syphilis data.

This work studies the SIS model extended by fractional and fractal derivatives. We obtain explicit solutions for the standard and fractal formulations; for the fractional case, we study numerical solutions. As a real data example, we consider the Brazilian syphilis data from 2011 to 2021. We fit the data by considering the three variations of the model. Our fit suggests a recovery period of 11.6 days and a reproduction ratio (R0) equal to 6.5. By calculating the correlation coefficient (r) between the real data and the theoretical points, our results suggest that the fractal model presents a higher r compared to the standard or fractional case. The fractal formulation is improved when two different fractal orders with distinguishing weights are considered. This modification in the model provides a better description of the data and improves the correlation coefficient.

Breast cancer: A fractal approach, scaling analysis and quantum cluster algorithm.

Tumor growth in the breast is a complex process, understanding this type of phenomenon is important in order to establish adequate strategies at diagnostic and therapeutic levels, beginning with the evaluation morphology, through adequate descriptors. Scaling analysis is used to extract parameters such as exponents of local roughness and fractal dimension, which characterize tumor growth. The results show that invasive lobular and ductal tumors in situ behave as proposed by Family-Vicsek (Family and Vicsek, 1991), while benign tumors behave differently.

The mandibular bone structure in children by fractal dimension and its correlation with pixel intensity values: a pilot study.

OBJECTIVES: To identify a normal pattern of mandibular trabecular bone in children based on the fractal dimension (FD), and its possible correlation with pixel intensity (PI) values, to facilitate the early diagnosis of possible diseases and/or future bone alterations. MATERIALS AND METHODS: The 50 panoramic images were selected and divided into two groups, according to the children's age: 8-9 (Group 1; n = 25) and 6-7 (Group 2; n = 25). For FD and PI analyses, three regions of interest (ROIs) were selected, and their mean values were evaluated for each ROI, according to each group, using the t test for independent samples and the model of generalized estimation equations (GEE). Subsequently, these mean values were correlated by the Pearson test. RESULTS: Comparing the groups, FD and PI did not differ from each other for any of the measured regions (p > 0.00). It was observed that in the mandible branch (ROI1), FD and PI means were 1.26 ± 0.01 and 81.0 ± 2.50, respectively. In the mandible angle (ROI2), the means were 1.21 ± 0.02 (FD) and 72.8 ± 2.13 (PI); and in the mandible, cortical (ROI3) values of FD = 1.03 ± 0.01 and PI = 91.3 ± 1.75 were obtained. There was no correlation between FD and PI in any of the analyzed ROI (r < 0.285). The FD means of ROI1 and ROI2 did not differ from each other (p = 0.053), but both were different from ROI3 (p < 0.00). All PI values differed from each other (p < 0.00). CONCLUSION: The bone trabeculate pattern in 6-9-year-old children presented FD between 1.01 and 1.29. Besides that, there was no significant correlation between FD and PI.

On the fractal patterns of language structures.

Natural Language Processing (NLP) makes use of Artificial Intelligence algorithms to extract meaningful information from unstructured texts, i.e., content that lacks metadata and cannot easily be indexed or mapped onto standard database fields. It has several applications, from sentiment analysis and text summary to automatic language translation. In this work, we use NLP to figure out similar structural linguistic patterns among several different languages. We apply the word2vec algorithm that creates a vector representation for the words in a multidimensional space that maintains the meaning relationship between the words. From a large corpus we built this vectorial representation in a 100-dimensional space for English, Portuguese, German, Spanish, Russian, French, Chinese, Japanese, Korean, Italian, Arabic, Hebrew, Basque, Dutch, Swedish, Finnish, and Estonian. Then, we calculated the fractal dimensions of the structure that represents each language. The structures are multi-fractals with two different dimensions that we use, in addition to the token-dictionary size rate of the languages, to represent the languages in a three-dimensional space. Finally, analyzing the distance among languages in this space, we conclude that the closeness there is tendentially related to the distance in the Phylogenetic tree that depicts the lines of evolutionary descent of the languages from a common ancestor.

Evaluation of entropy and fractal dimension as biomarkers for tumor growth and treatment response using cellular automata.

Cell-based models provide a helpful approach for simulating complex systems that exhibit adaptive, resilient qualities, such as cancer. Their focus on individual cell interactions makes them a particularly appropriate strategy to study cancer therapies' effects, which are often designed to disrupt single-cell dynamics. In this work, we propose them as viable methods for studying the time evolution of cancer imaging biomarkers (IBM). We propose a cellular automata model for tumor growth and three different therapies: chemotherapy, radiotherapy, and immunotherapy, following well-established modeling procedures documented in the literature. The model generates a sequence of tumor images, from which a time series of two biomarkers: entropy and fractal dimension, is obtained. Our model shows that the fractal dimension increased faster at the onset of cancer cell dissemination. At the same time, entropy was more responsive to changes induced in the tumor by the different therapy modalities. These observations suggest that the prognostic value of the proposed biomarkers could vary considerably with time. Thus, it is essential to assess their use at different stages of cancer and for different imaging modalities. Another observation derived from the results was that both biomarkers varied slowly when the applied therapy attacked cancer cells scattered along the automatons' area, leaving multiple independent clusters of cells at the end of the treatment. Thus, patterns of change of simulated biomarkers time series could reflect on essential qualities of the spatial action of a given cancer intervention.

Teoría de la complejidad y los sistemas de salud / Complexity theory and health systems

En la investigación en salud es todavía poco frecuente el uso de la Teoría de la Complejidad y de la Fractalidad (más aún en tópicos no relacionados directamente con la biología molecular o con la clínica). La complejidad nos propone complementar con propuestas desde nuevas perspectivas el pensamiento lineal y cuantitativo predominante todavía en la metodología de producción del conocimiento científico. El estudio de los sistemas de salud necesita un enfoque que se aparte de la linealidad, lo rígido y lo direccional, dado que los mismos son sistemas complejos en los que el todo es más que la simple suma de sus partes. La crisis global generada ante la pandemia por COVID-19 nos puso frente a la oportunidad (y a la obligación) de repensar tanto nuestra praxis cotidiana como nuestra forma de producir conocimiento (AU)

In health research, the use of the Complexity and Fractality Theory is still infrequent (even more so in topics not directly related to molecular or clinical biology). The complexity proposes us to complement with proposals from new perspectives the linear and quantitative thinking still predominant in the methodology of production of scientific knowledge. The study of health systems needs an approach that moves away from linearity, rigidity and direction, since they are complex systems in which the whole is more than the simple sum of its parts. The global crisis generated by the COVID-19 pandemic presented us with the opportunity (and the obligation) to rethink both our daily praxis and our way of producing knowledge (AU)

Fractal analysis of dental periapical radiographs: A revised image processing method.

OBJECTIVE: To assess trabecular bone structure as calculated with fractal analysis by 2 binarization processes: White and Rudolph's original method (WR.o) and a revised version (WR.r). Fractal dimension (FD) values calculated with WR.r (FD.r) and a gray-scale-based method (FD.f) were also compared. FD, histogram parameters, and lacunarity were compared by dentate status, jaw location, and sex. STUDY DESIGN: Regions of interest from digital periapical radiographs were defined below the teeth roots and in the edentulous sites of 37 patients. Histograms were assessed for pixel values. Binarization was performed with WR.o and then with WR.r, in which the outliers were removed. FD was assessed using WR.r (FD.r) and (FD.f). Histograms were assessed to obtain pixel values. Lacunarity was calculated. RESULTS: WR.r revealed fewer trabeculae, branches, and junctions than WR.o (P < .0001). The majority of the mean differences between FD.r and FD.f were within the 95% CI. Dentate areas had greater mean gray levels than partially edentulous areas (P = .0027). FD.f was higher in the mandible (P = .01), but gray-level SD (P < .0001) and lacunarity (P = .02) were greater in the maxilla. FD.f and lacunarity were higher (P = .0005) and lower (P = .0014) in males, respectively. CONCLUSION: WR.r was effective in revealing skeletonized bone trabeculae by removing non-trabecular noise. FD.r and FD.f revealed good agreement. FD.f, histogram parameters, and lacunarity differed based on dentate status, jaw location, and sex.

Growth models of fractal interfaces in the description of microorganism colony growth: effect of photodynamic inactivation.

Candida albicans is responsible for most of the nosocomial infections that affect immunocompromised individuals. We investigated the application of eosin in photodynamic inactivation as a strategy in the inhibition of the growth of C. albicans and the morphological variation and growth dynamics in light of fractal theory. The damage caused to fungal structures alters the roughness of the colony, and these changes were described by parameters that were defined by mathematical models. Proliferation of the fungi should be inhibited in the center of the colonies and the analysis of the edges gives an indication about the dynamics of growth and cell reproduction.

Análise fractal do osso mandibular e a ocorrência de osteorradionecrose: um estudo transversal com grupo controle / Fractal analysis of mandibular bone and occurrence of osteoradionecrosis: a cross-sectional study with control group

A radioterapia (RT) é amplamente utilizada para o tratamento do câncer em região de cabeça e pescoço. A osteorradionecrose (ORN) é uma das mais severas complicações desta modalidade terapêutica. Todos os pacientes tratados com radioterapia são considerados de alta risco para o desenvolvimento da ORN, devido à falta de fatores preditivos dessa comorbidade, a morbidade e a imprevisibilidade da resposta ao tratamento. A análise fractal é utilizada para descrever a complexidade de uma estrutura e avaliar anormalidades e gravidade de distúrbios da arquitetura óssea. Entretanto, poucos estudos utilizaram a análise fractal para avaliar a estrutura óssea de pacientes submetidos à RT em região de cabeça e pescoço. Portanto, o objetivo deste trabalho foi avaliar a dimensão fractal (DF) e lacunaridade do osso mandibular em indivíduos submetidos à RT para tratamento de câncer de cabeça e pescoço, comparando aqueles desenvolveram ORN (grupo caso) com aqueles que não desenvolveram ORN (grupo controle). O estudo foi aprovado pelo Comitê de Ética em Pesquisa da UFMG (CAAE 30560820.9.0000.5149). É um estudo transversal com grupo controle, no qual 34 pacientes foram incluídos e divididos em grupo caso (com ORN, n=17) e grupo controle (sem ORN, n=17). Uma radiografia panorâmica digital, adquirida após o término da RT, foi avaliada para cada paciente. A DF e lacunaridade do osso mandibular foram determinados usando o software ImageJ. Foi realizada análise estatística bivariada, bem como análise da curva ROC. A significância foi estabelecida em p< 0,05. Os valores médios de DF e lacunaridade não foram significativamente diferentes entre os grupos. A área sob a curva para DF foi de 0,576 e para lacunaridade foi de 0,626. O ponto de corte encontrado para DF foi ≤1,1736 e >0,4155 para lacunaridade, os quais classificaram corretamente casos e controles. A maioria dos pacientes com ORN (92.9%) tiveram DF> 1.1736 e todos os controles tiveram DF≤ 1.1736 (p< 0.001). Para a lacunaridade, a maioria dos pacientes com ORN (71.4%) apresentaram valor > 0.4155 e todos os controles tiveram valor ≤ 0.4155 (p< 0.001). Em conclusão, os pontos de corte da DF e lacunaridade do osso mandibular, estabelecidos pela análise de radiografias panorâmicas, puderam classificar corretamente pacientes com ORN e sem ORN.

Radiotherapy (RT) is widely used in the treatment of head and neck cancer. Osteoradionecrosis (ORN) is one of the most severe complication of this therapeutic modality. All patients treated with RT are considered at high risk for the development of ORN, due to the lack of predictive factors for ORN, the morbidity, and the unpredictable response to treatment. Fractal analysis is used to describe the complexity of a structure and to assess abnormalities and the severity of bone architecture disorders. However, few studies have used fractal analysis to assess the bone structure of patients undergoing RT in head and neck region. Therefore, the aim of this study was to evaluate the FD and lacunarity of the mandibular bone in individuals who received radiation therapy for HNC, comparing those who had developed ORN to those who had not developed ORN (control group). The study was approved by the Research Ethics Committee of the Universidade Federal de Minas Gerais (certificate number: 30560820.9.0000.5149). This is a cross-sectional study with a control group and thirty-four patients were included and divided into case group (with ORN, n=17) and control group (without ORN, n=17). One digital panoramic radiograph acquired after the end of RT was evaluated for each patient. FD and lacunarity of the mandibular bone were determined using ImageJ software. Bivariate statistics was done, as well as ROC curve analysis. Significance was stablished at p< 0.05. The mean FD and lacunarity values were not significantly different between the groups. The area under the curve for FD and lacunarity were 0.576 and 0.626, respectively. The cut-off point found for FD was ≤1.1736 and >0.4155 for lacunarity, allowing us to correctly classify cases and controls. Most participants in the case group (92.9%) had a FD >1.1736 and all participants in the control group had a FD ≤ 1.1736 (p < 0.001). For lacunarity, most individuals in the case group (71.4%) had a value >0.4155 and all participants in the control group had a value ≤0.4155 (p <0.001). Conclusion: The cut-off values of FD and lacunarity of mandibular bone, assessed on panoramic radiographs, differ between patients with and without ORN.

Multi-fractal detrended cross-correlation heatmaps for time series analysis.

Complex systems in biology, climatology, medicine, and economy hold emergent properties such as non-linearity, adaptation, and self-organization. These emergent attributes can derive from large-scale relationships, connections, and interactive behavior despite not being apparent from their isolated components. It is possible to better comprehend complex systems by analyzing cross-correlations between time series. However, the accumulation of non-linear processes induces multiscale structures, therefore, a spectrum of power-law exponents (the fractal dimension) and distinct cyclical patterns. We propose the Multifractal detrended cross-correlation heatmaps (MF-DCCHM) based on the DCCA cross-correlation coefficients with sliding boxes, a systematic approach capable of mapping the relationships between fluctuations of signals on different scales and regimes. The MF-DCCHM uses the integrated series of magnitudes, sliding boxes with sizes of up to 5% of the entire series, and an average of DCCA coefficients on top of the heatmaps for the local analysis. The heatmaps have shown the same cyclical frequencies from the spectral analysis across different multifractal regimes. Our dataset is composed of sales and inventory from the Brazilian automotive sector and macroeconomic descriptors, namely the Gross Domestic Product (GDP) per capita, Nominal Exchange Rate (NER), and the Nominal Interest Rate (NIR) from the Central Bank of Brazil. Our results indicate cross-correlated patterns that can be directly compared with the power-law spectra for multiple regimes. We have also identified cyclical patterns of high intensities that coincide with the Brazilian presidential elections. The MF-DCCHM uncovers non-explicit cyclic patterns, quantifies the relations of two non-stationary signals (noise effect removed), and has outstanding potential for mapping cross-regime patterns in multiple domains.

Number theory, borderline dimension and extensive entropy in distributions of ranked data.

The consideration of an existing stochastic approach for the reproduction of ranked data pointed at a formal equivalence between its key mathematical expression and that for trajectories at the tangent bifurcation. This fact led to a nonlinear dynamical approach for rank distributions that shows similarities with universality classes in critical phenomena. The renormalization group (RG) fixed-point map f*(x) for a tangent bifurcation of arbitrary nonlinearity z > 1 has proved to be a powerful tool into which the formalism can be couched. The source distribution P(N) of the stochastic approach can be linked to f*(x) while the size-rank N(k) and frequency-rank F(k') distributions are obtained, respectively, from the map trajectories xt and the sums of its positions. We provide now an extension to Number Theory as we obtain from the trajectories xt of f*(x) the numbers, or asymptotic approximations of them, for the Factorial, Natural, Prime and Fibonacci sets. A measure of the advance of these numbers towards infinity is given by sums of positions that represent their reciprocals. We specify rank distribution universality classes, already associated with real data, to these number sets. We find that the convergence of the series of number reciprocals occurs first at nonlinearity z = 2, that which corresponds to the classical Zipf law, and link this transition edge to the action of the attractor when it first reduces the fractal dimension of trajectory positions to zero. Furthermore, the search of logarithmic corrections common to borderline dimensions provides a link to the Prime numbers set. Finally, we find corroborating evidence of these logarithmic corrections from the analysis of large data sets for ranked earthquake magnitudes. The formalism links all types of ranked distributions to a generalized extensive entropy.

Nanoscale surface dynamics of spatial patterns of polymeric bilayered particles loaded with essential oil.

Gelatin/PCL bilayered particles loaded with Piper nigrum essential oil was synthesized aiming to access their morphological and surface dynamic patterns. Atomic force microscopy (AFM) was applied to investigate the 3D morphology and multifractal aspects of the particles surface. The AFM maps revealed spherical surfaces and well dispersed particles, besides a rougher surface on the loaded system. Minkowski functionals showed that shape of the rough peaks was similar in the unloaded and loaded systems; however, the presence of deep valleys on the loaded particles revealed their rougher pattern. Multifractal analysis revealed that unloaded and loaded particles presented multifractal behavior with different surface dynamics. The loaded surface presented a greater width of the multifractal spectrum and smaller difference of fractal dimensions, confirming their more vertically growing. These results can be useful in the development of novel polymeric-based particles loaded with essential oil. Their unique surface dynamics can provide enhanced physical properties and performance in emerging biotechnological applications.

Fractal methods applied to the seminiferous lumen images can quantify testicular changes induced by heat stress.

Male infertility affects many couples around the world and can be related to environmental factors such as exposure to high temperatures. Even so, automated methods evaluating the seminiferous tubules to detect testicular damage are still scarce. In search of new approaches to automation in the microscopic analysis of the testis; the present study used the fractal dimension, lacunarity, multifractality and quantitative morphometry to quantify changes in microphotographs of the seminiferous lumen in testicles reversibly damaged by heat stress (43 °C, 12 min). The parameters fractal dimension, lacunarity, multifractality (Dq and α), perimeter, feret and circularity were able to detect changes in the seminiferous lumen at 7, 15 and 30 days after the testicular damage. These methods also detected the recovery of spermatogenesis at 60 days after heat stress. Area, f(α), centroid X and Y, roundness, rectangle height and width were unable to detect changes caused by heat stress. In conclusion, computer assisted methods applied to the seminiferous lumen images can be a useful new viewpoint to analyze microscopic changes in the testicles, a fast low-cost tool to assist in the automated quantification of testicular damage.