Reliability of variability and complexity measures for task and task-free BOLD fMRI.

Brain activity continuously fluctuates over time, even if the brain is in controlled (e.g., experimentally induced) states. Recent years have seen an increasing interest in understanding the complexity of these temporal variations, for example with respect to developmental changes in brain function or between-person differences in healthy and clinical populations. However, the psychometric reliability of brain signal variability and complexity measures-which is an important precondition for robust individual differences as well as longitudinal research-is not yet sufficiently studied. We examined reliability (split-half correlations) and test-retest correlations for task-free (resting-state) BOLD fMRI as well as split-half correlations for seven functional task data sets from the Human Connectome Project to evaluate their reliability. We observed good to excellent split-half reliability for temporal variability measures derived from rest and task fMRI activation time series (standard deviation, mean absolute successive difference, mean squared successive difference), and moderate test-retest correlations for the same variability measures under rest conditions. Brain signal complexity estimates (several entropy and dimensionality measures) showed moderate to good reliabilities under both, rest and task activation conditions. We calculated the same measures also for time-resolved (dynamic) functional connectivity time series and observed moderate to good reliabilities for variability measures, but poor reliabilities for complexity measures derived from functional connectivity time series. Global (i.e., mean across cortical regions) measures tended to show higher reliability than region-specific variability or complexity estimates. Larger subcortical regions showed similar reliability as cortical regions, but small regions showed lower reliability, especially for complexity measures. Lastly, we also show that reliability scores are only minorly dependent on differences in scan length and replicate our results across different parcellation and denoising strategies. These results suggest that the variability and complexity of BOLD activation time series are robust measures well-suited for individual differences research. Temporal variability of global functional connectivity over time provides an important novel approach to robustly quantifying the dynamics of brain function. PRACTITIONER POINTS: Variability and complexity measures of BOLD activation show good split-half reliability and moderate test-retest reliability. Measures of variability of global functional connectivity over time can robustly quantify neural dynamics. Length of fMRI data has only a minor effect on reliability.

DeepComBat: A statistically motivated, hyperparameter-robust, deep learning approach to harmonization of neuroimaging data.

Neuroimaging data acquired using multiple scanners or protocols are increasingly available. However, such data exhibit technical artifacts across batches which introduce confounding and decrease reproducibility. This is especially true when multi-batch data are analyzed using complex downstream models which are more likely to pick up on and implicitly incorporate batch-related information. Previously proposed image harmonization methods have sought to remove these batch effects; however, batch effects remain detectable in the data after applying these methods. We present DeepComBat, a deep learning harmonization method based on a conditional variational autoencoder and the ComBat method. DeepComBat combines the strengths of statistical and deep learning methods in order to account for the multivariate relationships between features while simultaneously relaxing strong assumptions made by previous deep learning harmonization methods. As a result, DeepComBat can perform multivariate harmonization while preserving data structure and avoiding the introduction of synthetic artifacts. We apply this method to cortical thickness measurements from a cognitive-aging cohort and show DeepComBat qualitatively and quantitatively outperforms existing methods in removing batch effects while preserving biological heterogeneity. Additionally, DeepComBat provides a new perspective for statistically motivated deep learning harmonization methods.

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency.

With the rise of open data, identifiability of individuals based on 3D renderings obtained from routine structural magnetic resonance imaging (MRI) scans of the head has become a growing privacy concern. To protect subject privacy, several algorithms have been developed to de-identify imaging data using blurring, defacing or refacing. Completely removing facial structures provides the best re-identification protection but can significantly impact post-processing steps, like brain morphometry. As an alternative, refacing methods that replace individual facial structures with generic templates have a lower effect on the geometry and intensity distribution of original scans, and are able to provide more consistent post-processing results by the price of higher re-identification risk and computational complexity. In the current study, we propose a novel method for anonymized face generation for defaced 3D T1-weighted scans based on a 3D conditional generative adversarial network. To evaluate the performance of the proposed de-identification tool, a comparative study was conducted between several existing defacing and refacing tools, with two different segmentation algorithms (FAST and Morphobox). The aim was to evaluate (i) impact on brain morphometry reproducibility, (ii) re-identification risk, (iii) balance between (i) and (ii), and (iv) the processing time. The proposed method takes 9 s for face generation and is suitable for recovering consistent post-processing results after defacing.

SIPAS: A comprehensive susceptibility imaging process and analysis studio.

Quantitative susceptibility mapping (QSM) is a rising MRI-based technology and quite a few QSM-related algorithms have been proposed to reconstruct maps of tissue susceptibility distribution from phase images. In this paper, we develop a comprehensive susceptibility imaging process and analysis studio (SIPAS) that can accomplish reliable QSM processing and offer a standardized evaluation system. Specifically, SIPAS integrates multiple methods for each step, enabling users to select algorithm combinations according to data conditions, and QSM maps could be evaluated by two aspects, including image quality indicators within all voxels and region-of-interest (ROI) analysis. Through a sophisticated design of user-friendly interfaces, the results of each procedure are able to be exhibited in axial, coronal, and sagittal views in real-time, meanwhile ROIs can be displayed in 3D rendering visualization. The accuracy and compatibility of SIPAS are demonstrated by experiments on multiple in vivo human brain datasets acquired from 3T, 5T, and 7T MRI scanners of different manufacturers. We also validate the QSM maps obtained by various algorithm combinations in SIPAS, among which the combination of iRSHARP and SFCR achieves the best results on its evaluation system. SIPAS is a comprehensive, sophisticated, and reliable toolkit that may prompt the QSM application in scientific research and clinical practice.

Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source tool mrQA.

Pooling data across diverse sources acquired by multisite consortia requires compliance with a predefined reference protocol i.e., ensuring different sites and scanners for a given project have used identical or compatible MR physics parameter values. Traditionally, this has been an arduous and manual process due to difficulties in working with the complicated DICOM standard and lack of resources allocated towards protocol compliance. Moreover, issues of protocol compliance is often overlooked for lack of realization that parameter values are routinely improvised/modified locally at various sites. The inconsistencies in acquisition protocols can reduce SNR, statistical power, and in the worst case, may invalidate the results altogether. An open-source tool, mrQA was developed to automatically assess protocol compliance on standard dataset formats such as DICOM and BIDS, and to study the patterns of non-compliance in over 20 open neuroimaging datasets, including the large ABCD study. The results demonstrate that the lack of compliance is rather pervasive. The frequent sources of non-compliance include but are not limited to deviations in Repetition Time, Echo Time, Flip Angle, and Phase Encoding Direction. It was also observed that GE and Philips scanners exhibited higher rates of non-compliance relative to the Siemens scanners in the ABCD dataset. Continuous monitoring for protocol compliance is strongly recommended before any pre/post-processing, ideally right after the acquisition, to avoid the silent propagation of severe/subtle issues. Although, this study focuses on neuroimaging datasets, the proposed tool mrQA can work with any DICOM-based datasets.

Enhancing Meibography Image Analysis Through Artificial Intelligence-Driven Quantification and Standardization for Dry Eye Research.

Purpose: This study enhances Meibomian gland (MG) infrared image analysis in dry eye (DE) research through artificial intelligence (AI). It is comprised of two main stages: automated eyelid detection and tarsal plate segmentation to standardize meibography image analysis. The goal is to address limitations of existing assessment methods, bridge the curated and real-world dataset gap, and standardize MG image analysis. Methods: The approach involves a two-stage process: automated eyelid detection and tarsal plate segmentation. In the first stage, an AI model trained on curated data identifies relevant eyelid areas in non-curated datasets. The second stage refines the eyelid area in meibography images, enabling precise comparisons between normal and DE subjects. This approach also includes specular reflection removal and tarsal plate mask refinement. Results: The methodology achieved a promising instance-wise accuracy of 80.8% for distinguishing meibography images from 399 DE and 235 non-DE subjects. By integrating diverse datasets and refining the area of interest, this approach enhances meibography feature extraction accuracy. Dimension reduction through Uniform Manifold Approximation and Projection (UMAP) allows feature visualization, revealing distinct clusters for DE and non-DE phenotypes. Conclusions: The AI-driven methodology presented here quantifies and classifies meibography image features and standardizes the analysis process. By bootstrapping the model from curated datasets, this methodology addresses real-world dataset challenges to enhance the accuracy of meibography image feature extraction. Translational Relevance: The study presents a standardized method for meibography image analysis. This method could serve as a valuable tool in facilitating more targeted investigations into MG characteristics.

SAN: Mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites.

In neuroimaging studies, combining data collected from multiple study sites or scanners is becoming common to increase the reproducibility of scientific discoveries. At the same time, unwanted variations arise by using different scanners (inter-scanner biases), which need to be corrected before downstream analyses to facilitate replicable research and prevent spurious findings. While statistical harmonization methods such as ComBat have become popular in mitigating inter-scanner biases in neuroimaging, recent methodological advances have shown that harmonizing heterogeneous covariances results in higher data quality. In vertex-level cortical thickness data, heterogeneity in spatial autocorrelation is a critical factor that affects covariance heterogeneity. Our work proposes a new statistical harmonization method called spatial autocorrelation normalization (SAN) that preserves homogeneous covariance vertex-level cortical thickness data across different scanners. We use an explicit Gaussian process to characterize scanner-invariant and scanner-specific variations to reconstruct spatially homogeneous data across scanners. SAN is computationally feasible, and it easily allows the integration of existing harmonization methods. We demonstrate the utility of the proposed method using cortical thickness data from the Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) study. SAN is publicly available as an R package.

MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in managing and analyzing MRI data, due in large part to the heterogeneity of data acquisition. To address this, we have developed MRIO, the Magnetic Resonance Imaging Acquisition and Analysis Ontology. MRIO provides well-reasoned classes and logical axioms for the acquisition of several MRI acquisition types and well-known, peer-reviewed analysis software, facilitating the use of MRI data. These classes provide a common language for the neuroimaging research process and help standardize the organization and analysis of MRI data for reproducible datasets. We also provide queries for automated assignment of analyses for given MRI types. MRIO aids researchers in managing neuroimaging studies by helping organize and annotate MRI data and integrating with existing standards such as Digital Imaging and Communications in Medicine and the Brain Imaging Data Structure, enhancing reproducibility and interoperability. MRIO was constructed according to Open Biomedical Ontologies Foundry principles and has contributed several classes to the Ontology for Biomedical Investigations to help bridge neuroimaging data to other domains. MRIO addresses the need for a "common language" for MRI that can help manage the neuroimaging research, by enabling researchers to identify appropriate analyses for sets of scans and facilitating data organization and reporting.

Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities.

A primary challenge to the data-driven analysis is the balance between poor generalizability of population-based research and characterizing more subject-, study- and population-specific variability. We previously introduced a fully automated spatially constrained independent component analysis (ICA) framework called NeuroMark and its functional MRI (fMRI) template. NeuroMark has been successfully applied in numerous studies, identifying brain markers reproducible across datasets and disorders. The first NeuroMark template was constructed based on young adult cohorts. We recently expanded on this initiative by creating a standardized normative multi-spatial-scale functional template using over 100,000 subjects, aiming to improve generalizability and comparability across studies involving diverse cohorts. While a unified template across the lifespan is desirable, a comprehensive investigation of the similarities and differences between components from different age populations might help systematically transform our understanding of the human brain by revealing the most well-replicated and variable network features throughout the lifespan. In this work, we introduced two significant expansions of NeuroMark templates first by generating replicable fMRI templates for infants, adolescents, and aging cohorts, and second by incorporating structural MRI (sMRI) and diffusion MRI (dMRI) modalities. Specifically, we built spatiotemporal fMRI templates based on 6,000 resting-state scans from four datasets. This is the first attempt to create robust ICA templates covering dynamic brain development across the lifespan. For the sMRI and dMRI data, we used two large publicly available datasets including more than 30,000 scans to build reliable templates. We employed a spatial similarity analysis to identify replicable templates and investigate the degree to which unique and similar patterns are reflective in different age populations. Our results suggest remarkably high similarity of the resulting adapted components, even across extreme age differences. With the new templates, the NeuroMark framework allows us to perform age-specific adaptations and to capture features adaptable to each modality, therefore facilitating biomarker identification across brain disorders. In sum, the present work demonstrates the generalizability of NeuroMark templates and suggests the potential of new templates to boost accuracy in mental health research and advance our understanding of lifespan and cross-modal alterations.

Automated protocols for delineating human hippocampal subfields from 3 Tesla and 7 Tesla magnetic resonance imaging data.

Researchers who study the human hippocampus are naturally interested in how its subfields function. However, many researchers are precluded from examining subfields because their manual delineation from magnetic resonance imaging (MRI) scans (still the gold standard approach) is time consuming and requires significant expertise. To help ameliorate this issue, we present here two protocols, one for 3T MRI and the other for 7T MRI, that permit automated hippocampus segmentation into six subregions, namely dentate gyrus/cornu ammonis (CA)4, CA2/3, CA1, subiculum, pre/parasubiculum, and uncus along the entire length of the hippocampus. These protocols are particularly notable relative to existing resources in that they were trained and tested using large numbers of healthy young adults (n = 140 at 3T, n = 40 at 7T) whose hippocampi were manually segmented by experts from MRI scans. Using inter-rater reliability analyses, we showed that the quality of automated segmentations produced by these protocols was high and comparable to expert manual segmenters. We provide full open access to the automated protocols, and anticipate they will save hippocampus researchers a significant amount of time. They could also help to catalyze subfield research, which is essential for gaining a full understanding of how the hippocampus functions.

Improving 3D edge detection for visual inspection of MRI coregistration and alignment.

BACKGROUND: Visualizing edges is critical for neuroimaging. For example, edge maps enable quality assurance for the automatic alignment of an image from one modality (or individual) to another. NEW METHOD: We suggest that using the second derivative (difference of Gaussian, or DoG) provides robust edge detection. This method is tuned by size (which is typically known in neuroimaging) rather than intensity (which is relative). RESULTS: We demonstrate that this method performs well across a broad range of imaging modalities. The edge contours produced consistently form closed surfaces, whereas alternative methods may generate disconnected lines, introducing potential ambiguity in contiguity. COMPARISON WITH EXISTING METHODS: Current methods for computing edges are based on either the first derivative of the image (FSL), or a variation of the Canny Edge detection method (AFNI). These methods suffer from two primary limitations. First, the crucial tuning parameter for each of these methods relates to the image intensity. Unfortunately, image intensity is relative for most neuroimaging modalities making the performance of these methods unreliable. Second, these existing approaches do not necessarily generate a closed edge/surface, which can reduce the ability to determine the correspondence between a represented edge and another image. CONCLUSION: The second derivative is well suited for neuroimaging edge detection. We include this method as part of both the AFNI and FSL software packages, standalone code and online.

ENIGMA's simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury.

Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.

Measuring stomatal and guard cell metrics for plant physiology and growth using StoManager1.

Automated guard cell detection and measurement are vital for understanding plant physiological performance and ecological functioning in global water and carbon cycles. Most current methods for measuring guard cells and stomata are laborious, time-consuming, prone to bias, and limited in scale. We developed StoManager1, a high-throughput tool utilizing geometrical, mathematical algorithms, and convolutional neural networks to automatically detect, count, and measure over 30 guard cell and stomatal metrics, including guard cell and stomatal area, length, width, stomatal aperture area/guard cell area, orientation, stomatal evenness, divergence, and aggregation index. Combined with leaf functional traits, some of these StoManager1-measured guard cell and stomatal metrics explained 90% and 82% of tree biomass and intrinsic water use efficiency (iWUE) variances in hardwoods, making them substantial factors in leaf physiology and tree growth. StoManager1 demonstrated exceptional precision and recall (mAP@0.5 over 0.96), effectively capturing diverse stomatal properties across over 100 species. StoManager1 facilitates the automation of measuring leaf stomatal and guard cells, enabling broader exploration of stomatal control in plant growth and adaptation to environmental stress and climate change. This has implications for global gross primary productivity (GPP) modeling and estimation, as integrating stomatal metrics can enhance predictions of plant growth and resource usage worldwide. Easily accessible open-source code and standalone Windows executable applications are available on a GitHub repository (https://github.com/JiaxinWang123/StoManager1) and Zenodo (https://doi.org/10.5281/zenodo.7686022).

Intra- and interobserver reliability of a modified distraction test based on digital images to assess lower eyelid horizontal tension / Confiabilidade intra e interobservador do teste de tração modificado para avaliar a tensão da pálpebra inferior baseado em imagens digitais

ABSTRACT Purpose: Inferior eyelid laxity is classically evaluated using "snap-back" and "distraction" tests. This study aimed to assess the reproducibility of the technique used to indirectly quantify the horizontal tension in the lower eyelids using digital image processing. Methods: This longitudinal study was conducted to assess the reproducibility of a new technique that quantifies the horizontal tension in the lower eyelid. The study was conducted at the Hospital das Clínicas of Porto Alegre. The protocol was established by two trained ophthalmologist examiners, allowing intra- and interobserver agreement analyses. Image acquisition was done in two stages: the first image was captured with the eyelid in primary gaze position and the second with the eyelid in traction position. All images and measurements were processed using Image J 1.33m software from the National Institute of Health. The Bland-Altman method, intraclass correlation coefficients, concordance correlation coefficients, and technical measurement error were used to evaluate reproducibility. Results: The study participants comprised healthy individuals with no ophthalmologic pathologies. The measurements obtained in the neutral position showed a slightly higher agreement than those obtained in the traction position. The mean difference between the measurements performed in the traction position was 0.028 ± 0.7 mm and 0.014 ± 0.9 mm in the intra- and interobserver analyses, respectively. The Bland-Altman method demonstrated adequate confidence limits for both measurements. Correlation coefficients for measurements varied between 0.87 [95% confidence interval (CI) 0.68-0.95] and 0.91 (95% CI 0.77-0.97) in the neutral position and between 0.72 (95% CI 0.37-0.89) and 0.76 (95% CI 0.4-0.91) in the traction position. Conclusion: A high intra- and interobserver concordance was observed in the studied method to quantify lower eyelid tension. The proposed method is simple and easily reproducible, and to the best our knowledge, this is the first method that quantifies lower eyelid horizontal tension on the basis of digital image processing. This modified distraction test might be useful in studies quantifying lower eyelid horizontal tension.

RESUMO Objetivo: A frouxidão palpebral inferior é avaliada classicamente por meio de testes de "snap-back" e "distraction test". O objetivo deste estudo foi avaliar a reprodutibilidade da técnica utilizada para quantificar indiretamente a tensão horizontal nas pálpebras inferiores através do processamento digital de imagens. Métodos: Este estudo longitudinal foi realizado para avaliar a reprodutibilidade de uma nova técnica que quantifica a tensão horizontal na pálpebra inferior. O estudo foi realizado no Hospital das Clínicas de Porto Alegre. O protocolo foi estabelecido por dois examinadores oftalmologistas treinados, permitindo análises de concordância intra e interavaliador. A aquisição de imagens foi feita em duas etapas: a primeira imagem foi capturada com a pálpebra na posição primária do olhar e a segunda com pálpebra tracionada. Todas as imagens e medições foram processadas usando o software Image J 1.33m do National Institute of Health. O método de Bland-Altman, os coeficientes de correlação intraclasses, os coeficientes de correlação de concordância e o erro técnico da medida foram utilizados para avaliar a reprodutibilidade. Resultados: Os participantes do estudo foram indivíduos saudáveis e sem patologias oftalmológicas. As medidas obtidas na posição neutra mostraram concordância levemente maior do que as obtidas na posição tracionada. A diferença média entre as medidas realizadas na posição tracionada foi de 0,028 ± 0,7mm e 0,014 ± 0,9mm nas análises intra e interobservadores, respectivamente. O método de Bland-Altman demonstrou limites de confiança adequados para ambas as medidas. Os coeficientes de correlação para as medidas variaram entre 0,87 [intervalo de confiança de 95% (IC) 0,68-0,95) e 0,91 (IC 95% 0,77-0,97) na posição neutra e entre 0,72 (IC 95% 0,37-0,89) e 0,76 (IC 95% 0,46-0,91) na posição tracionada. Conclusão: Observou-se elevada concordância intra e interobservador no método estudado para quantificar a tensão palpebral inferior. O método proposto é simples e facilmente reproduzível, e, do melhor modo possível, este é o primeiro método que quantifica a tensão horizontal da pálpebra inferior com base no processamento digital de imagens. Este teste de distração modificado pode ser útil em estudos que quantifiquem a tensão horizontal da pálpebra inferior.

Software livre e de código aberto para avaliação de imagens de angiotomografia de coronárias / Free and open-source software application for the evaluation of coronary computed tomography angiography images

FUNDAMENTO: A estandardização do padrão de imagens utilizada dentro da medicina foi realizada em 1993 por meio do padrão DICOM (Digital Imaging and Communications in Medicine). Diversos exames utilizam esse padrão e cada vez mais são necessários softwares capazes de manipular esse tipo de imagem, porém esses softwares geralmente não têm o formato livre e de código aberto, e isso dificulta o seu ajuste para os mais diferentes interesses. OBJETIVO: Desenvolver e validar um software livre e de código aberto capaz de manipular imagens DICOM de exames de angiotomografia de coronárias. MÉTODOS: Desenvolvemos e testamos o software intitulado ImageLab na avaliação de 100 exames selecionados de forma randômica por meio de um banco de dados. Foram realizadas 600 análises divididas por dois observadores utilizando o ImageLab e um outro software comercializado junto a aparelhos de tomografia computadorizada Philips Brilliance, na avaliação da presença de lesões e placas coronarianas nos territórios do Tronco da Coronária Esquerda (TCE) e na Artéria Descendente Anterior (ADA). Para avaliar as concordâncias intraobservador, interobservadores e intersoftware, utilizamos concordância simples e estatística Kappa. RESULTADOS: As concordâncias observadas entre os softwares foram em geral classificadas como substancial ou quase perfeitas na maioria das comparações. CONCLUSÃO: O software ImageLab concordou com o software Philips na avaliação de exames de angiotomografia de coronárias especialmente em pacientes sem lesões, com lesões inferiores a 50% no TCE e inferiores a 70% na ADA. A concordância para lesão >70% na ADA foi menor, porém isso também é observado quando se utiliza o padrão de referência anatômico.

BACKGROUND: The standardization of images used in Medicine in 1993 was performed using the DICOM (Digital Imaging and Communications in Medicine) standard. Several tests use this standard and it is increasingly necessary to design software applications capable of handling this type of image; however, these software applications are not usually free and open-source, and this fact hinders their adjustment to most diverse interests. OBJECTIVE: To develop and validate a free and open-source software application capable of handling DICOM coronary computed tomography angiography images. METHODS: We developed and tested the ImageLab software in the evaluation of 100 tests randomly selected from a database. We carried out 600 tests divided between two observers using ImageLab and another software sold with Philips Brilliance computed tomography appliances in the evaluation of coronary lesions and plaques around the left main coronary artery (LMCA) and the anterior descending artery (ADA). To evaluate intraobserver, interobserver and intersoftware agreements, we used simple and kappa statistics agreements. RESULTS: The agreements observed between software applications were generally classified as substantial or almost perfect in most comparisons. CONCLUSION: The ImageLab software agreed with the Philips software in the evaluation of coronary computed tomography angiography tests, especially in patients without lesions, with lesions < 50% in the LMCA and < 70% in the ADA. The agreement for lesions > 70% in the ADA was lower, but this is also observed when the anatomical reference standard is used.

Accuracy of linear measurements before and after digitizing periapical and panoramic radiography images

The aim of this study was to evaluate the accuracy of linear measurements made on conventional and digitized periapical and panoramic radiographic images of dry human hemi-mandibles. Images from the posterior region of 22 dry human hemi-mandibles were obtained by conventional panoramic and periapical radiography technique. Using a digital caliper, 3 vertical measurements were marked directly on the dry hemi-mandibles (reference measurements) as well as on the tracing from the conventional radiographic images of the specimens made onto acetate paper sheet: Distance 1: between the upper limit of the alveolar ridge and the lower limit at the mandible base; Distance 2: between the upper limit of the alveolar ridge and the upper limit of the mandibular canal; Distance 3: between the lower limit of the mandibular canal and the lower limit of the mandible base. Next, the radiographs were digitized and the three measurements were made on the digital images using UTHSCSA Image Tool software. Data were analyzed statistically by one-way ANOVA (α=0.05). There was no statistically significant differences (p>0.05) between periapical and panoramic radiographs or between the measurements recorded using the digital caliper and UTHSCSA software compared with dry mandible specimens for Distances 1 (p=0.783), 2 (p=0.986) and 3 (p=0.129). In conclusion, the radiographic techniques evaluated in this study are reliable for vertical bone measurements on selected areas and the UTHSCA Image Tool software is an appropriate measurement method.

O objetivo deste estudo foi avaliar a acurácia de medidas lineares realizadas em radiografias panorâmicas e periapicais convencionais e digitalizadas de hemimandíbulas humanas secas. Imagens da região posterior de 22 hemimandíbulas humanas secas foram obtidas pelas técnicas panorâmica e periapical convencionais. Com o paquímetro eletrônico digital, foram realizadas três medições verticais diretamente sobre as hemimandíbulas (medidas referenciais), bem como sobre o decalque das imagens convencionais, em papel de acetato: Distância 1: Distância entre o limite superior do rebordo alveolar e o limite inferior da base da mandíbula; Distância 2: Distância entre o limite superior do rebordo alveolar e o limite superior do canal mandibular e Distância 3: Distância entre o limite inferior do canal mandibular e o limite inferior da base da mandíbula. Posteriormente, as radiografias foram digitalizadas e as três medidas foram realizadas nas imagens digitais utilizando o programa UTHSCSA Image Tool. Os dados foram analisados estatisticamente pelo teste ANOVA a um critério (α=0,05). Não houve diferenças estatisticamente significantes (p>0,05) entre as radiografias panorâmicas e periapicais, assim como para as medidas obtidas com o paquímetro e pelo programa UTHSCSA Image Tool, quando comparados aos espécimes mandibulares, avaliando as distâncias 1 (p=0,783), 2 (p=0,986) e 3 (p=0,129). Em conclusão, as técnicas radiográficas avaliadas neste estudo mostraram-se confiáveis para mensurações ósseas verticais na área selecionada e o programa de digitalização de imagens UTHSCSA Image Tool é um método adequado de aferição.

Estudo comparativo das medidas manual e digital da fenda palpebral / A comparative study of the manual and digital measurements of the palpebral fissure

OBJETIVO: Comparar a medida manual do comprimento vertical da fenda palpebral e sua medida obtida por meio de processamento computadorizado de imagens de indivíduos sem alterações palpebrais. MÉTODOS: Foram analisadas 102 fendas palpebrais de 51 indivíduos normais. A faixa etária variou entre 17 e 84 anos, sendo 25 (49 por cento) do sexo masculino e 26 (51 por cento) do sexo feminino. RESULTADOS: Não houve diferença estatisticamente significativa entre as medidas manuais da fenda palpebral e as obtidas por meio de processamento computadorizado de imagens. Também não se observou diferença entre ambos os sexos e a faixa etária. CONCLUSÕES: Os resultados obtidos com estes dois métodos podem ser comparados entre si devida à equivalência estatística das medidas.

Evaluation of the Image-Pro Plus 4.5 software for automatic counting of labeled nuclei by PCNA immunohistochemistry

O objetivo deste trabalho foi desenvolver e avaliar uma macro (rotina informatizada) usando o programa Image-Pro Plus 4.5 (Media Cybernetics, Silver Spring, EUA) para a contagem automática de núcleos imunopositivos para o antígeno nuclear em célula proliferante (PCNA). Utilizamos 154 imagens microscópicas digitalizadas coloridas obtidas de onze cortes histológicos de líquen plano oral reticular processados por imuno-histoquímica para PCNA. Os parâmetros densidade média (nível de cinza), densidades de vermelho, de verde e de azul, área, eixo menor, taxa de perímetro e redondeza foram usados para a discriminação dos núcleos imunopositivos pela macro, que, no final do processo, apresentava estes núcleos delineados e contados na imagem estudada. A definição dos limites de corte para densidade média e área foi realizada automaticamente em função, respectivamente, da média da densidade e da média da área dos núcleos imunopositivos presentes em cada imagem. Para controle, foi realizado o delineamento manual dos núcleos imunopositivos sobre as imagens digitalizadas e sua contagem visual. A comparação entre os resultados das contagens da macro versus contagens do controle mostrou uma correlação estatística significativa (rs = 0,964, p < 0,001) e uma alta proporção (89,8 ± 3,8%) de núcleos imunopositivos contados coerentemente pela macro. Concluímos que os principais parâmetros associados com a alta correlação entre os resultados da macro e do controle foram os limites de corte para densidade média (nível de cinza) e área baseados no padrão das imagens. Além disso, a análise de imagem usando o Image-Pro Plus 4.5 com definição automática dos limites de corte para densidade média e área pode ser considerada uma alternativa válida para o método visual de contagem de núcleos imunopositivos para PCNA.

Avaliaçäo da influência do posicionamento da placa óptica do Digora em relaçäo ao eixo dentário, na determinaçäo da curvatura radicular / The influence of digora imaging plate position in determining the radicular curvature

O objetivo deste trabalho foi avaliar as angulagens das curvaturas de raízes mésio-vestibular de molares superiores e mesial de molares inferiores obtidas pelo sistema de imagem digital Digora, com a placa óptica posicionada com seu comprimento paralelo ao longo eixo do dente e com sua largura paralela ao respectivo eixo. Foram utilizados 10 molares superiores e 10 molares inferiores. Os resultados mostraram que quando a placa óptica do Digora foi posicionada com sua largura paralela ao longo eixo dentário, a média do ângulo de curvatura das raízes mésio-vestibular dos molares superiores e mesial dos molares inferiores sofreu reduçäo de 2,5 por cento e 5,9 por cento respectivamente, em relaçäo a média obtida com a placa óptica posicionada com seu comprimento paralelo ao longo eixo dentário, näo sendo esta diferença estatisticamente significante (p<0,01)