Filamin A and DRD2 expression in corticotrophinomas.

PURPOSE: Filamin A (FLNA) expression is related to dopamine receptor type 2 (DRD2) expression in prolactinomas. Nevertheless, in corticotrophinomas, there are few studies about DRD2 expression and no data on FLNA. Therefore, we evaluated FLNA and DRD2 expression in corticotrophinomas and their association with tumor characteristics. METHODS: DRD2 and FLNA expression by immunohistochemistry, using H-score, based on the percentage of positive cells in a continuous scale of 0-300, were evaluated in 23 corticotrophinomas samples from patients submitted to neurosurgery. In six patients, treatment with cabergoline was indicated after non curative surgery. RESULTS: Twenty-two patients were female and one male. Regarding tumor size, 10 were micro and 12 were macroadenomas. DRD2 expression was found in 89% of cases and did not correlate with FLNA expression. Moreover, the response to cabergoline, observed in 33% of the cases, did not correlate with DRD2 nor FLNA expression. FLNA expression was not associated with clinical and tumor characteristics, except for sphenoid sinus invasion. CONCLUSIONS: In our cohort of corticotrophinomas, DRD2 expression was not associated with FLNA expression nor to the response to CAB. Nonetheless, FLNA expression could be related to tumor invasiveness.

Substantia nigra fractional anisotropy is not a diagnostic biomarker of Parkinson's disease: A diagnostic performance study and meta-analysis.

OBJECTIVES: Our goal was to estimate the diagnostic accuracy of substantia nigra fractional anisotropy (SN-FA) for Parkinson's disease (PD) diagnosis in a sample similar to the clinical setting, including patients with essential tremor (ET) and healthy controls (HC). We also performed a systematic review and meta-analysis to estimate mean change in SN-FA induced by PD and its diagnostic accuracy. METHODS: Our sample consisted of 135 subjects: 72 PD, 21 ET and 42 HC. To address inter-scanner variability, two 3.0-T MRI scans were performed. MRI results of this sample were pooled into a meta-analysis that included 1,432 subjects (806 PD and 626 HC). A bivariate model was used to evaluate diagnostic accuracy measures. RESULTS: In our sample, we did not observe a significant effect of disease on SN-FA and it was uninformative for diagnosis. The results of the meta-analysis estimated a 0.03 decrease in mean SN-FA in PD relative to HC (CI: 0.01-0.05). However, the discriminatory capability of SN-FA to diagnose PD was low: pooled sensitivity and specificity were 72 % (CI: 68-75) and 63 % (CI: 58-70), respectively. There was high heterogeneity between studies (I2 = 91.9 %). CONCLUSIONS: SN-FA cannot be used as an isolated measure to diagnose PD. KEY POINTS: • SN-FA appears insufficiently sensitive and specific to diagnose PD. • Radiologists must be careful when translating mean group results to clinical practice. • Imaging protocol and analysis standardization is necessary for developing reproducible quantitative biomarkers.

Natural language processing in the classification of radiology reports in benign gallbladder diseases.

Objective: To develop a natural language processing application capable of automatically identifying benign gallbladder diseases that require surgery, from radiology reports. Materials and Methods: We developed a text classifier to classify reports as describing benign diseases of the gallbladder that do or do not require surgery. We randomly selected 1,200 reports describing the gallbladder from our database, including different modalities. Four radiologists classified the reports as describing benign disease that should or should not be treated surgically. Two deep learning architectures were trained for classification: a convolutional neural network (CNN) and a bidirectional long short-term memory (BiLSTM) network. In order to represent words in vector form, the models included a Word2Vec representation, with dimensions of 300 or 1,000. The models were trained and evaluated by dividing the dataset into training, validation, and subsets (80/10/10). Results: The CNN and BiLSTM performed well in both dimensional spaces. For the 300- and 1,000-dimensional spaces, respectively, the F1-scores were 0.95945 and 0.95302 for the CNN model, compared with 0.96732 and 0.96732 for the BiLSTM model. Conclusion: Our models achieved high performance, regardless of the architecture and dimensional space employed.

Objetivo: Desenvolver uma aplicação de processamento de linguagem natural capaz de identificar automaticamente doenças cirúrgicas benignas da vesícula biliar a partir de laudos radiológicos. Materiais e Métodos: Desenvolvemos um classificador de texto para classificar laudos como contendo ou não doenças cirúrgicas benignas da vesícula biliar. Selecionamos aleatoriamente 1.200 laudos com descrição da vesícula biliar de nosso banco de dados, incluindo diferentes modalidades. Quatro radiologistas classificaram os laudos como doença benigna cirúrgica ou não. Duas arquiteturas de aprendizagem profunda foram treinadas para a classificação: a rede neural convolucional (convolutional neural network - CNN) e a memória longa de curto prazo bidirecional (bidirectional long short-term memory - BiLSTM). Para representar palavras de forma vetorial, os modelos incluíram uma representação Word2Vec, com dimensões variando de 300 a 1000. Os modelos foram treinados e avaliados por meio da divisão do conjunto de dados entre treinamento, validação e teste (80/10/10). Resultados: CNN e BiLSTM tiveram bom desempenho em ambos os espaços dimensionais. Relatamos para 300 e 1000 dimensões, respectivamente, as pontuações F1 de 0,95945 e 0,95302 para o modelo CNN e de 0,96732 e 0,96732 para a BiLSTM. Conclusão: Nossos modelos alcançaram alto desempenho, independentemente de diferentes arquiteturas e espaços dimensionais.

Clinical and neuroimaging correlates in a pilot randomized trial of aerobic exercise for major depression.

BACKGROUND: Aerobic exercise (AE) combined with pharmacotherapy is known to reduce depressive symptoms; however, studies have not focused on long-term AE for volumetric changes of brain regions (amygdala, thalamus, and nucleus accumbens [NAcc]) linked to the control of affective responses and hopelessness in individuals with major depression (MD). In addition, AE with motor complexity (AEMC) would be more effective than AE in causing brain plasticity. We compared the effects of 24 weeks of AE and AEMC combined with pharmacotherapy on clinical and volumetric outcomes in individuals with MD. METHODS: Forty medicated individuals with MD were randomly assigned to nonexercising control (C), AE, and AEMC groups. The training groups exercised for 60 min, twice a week for 24 weeks. Clinical and volumetric outcomes were assessed before and after the 24 weeks. Effect size (ES) and confidence interval (CI) were calculated for within-group and between-groups changes. RESULTS: AE and AEMC reduced hopelessness (ES = -0.73 and ES = -0.62, respectively) and increased affective responses (ES = 1.24 and ES = 1.56, respectively). Only AE increased amygdala (ES = 0.27 left and ES = 0.34 right), thalamus (ES = 0.33 left and ES = 0.26 right) and left NAcc (ES = 0.54) volumes. AE was more effective than the C group in reducing hopelessness and causing brain plasticity. The changes in the right amygdala volume showed a strong trend in explaining 72 % of the changes in affective responses following AE (p = 0.06). LIMITATION: Lack of posttraining follow-up and small sample size. CONCLUSION: These preliminary data indicate that AE combined with pharmacotherapy can cause clinical improvement and brain plasticity in individuals with MD.

Postmortem chest computed tomography in COVID-19: A minimally invasive autopsy method.

Objectives: Performing autopsies in a pandemic scenario is challenging, as the need to understand pathophysiology must be balanced with the contamination risk. A minimally invasive autopsy might be a solution. We present a model that combines radiology and pathology to evaluate postmortem CT lung findings and their correlation with histopathology. Methods: Twenty-nine patients with fatal COVID-19 underwent postmortem chest CT, and multiple lung tissue samples were collected. The chest CT scans were analyzed and quantified according to lung involvement in five categories: normal, ground-glass opacities, crazy-paving, small consolidations, and large or lobar consolidations. The lung tissue samples were examined and quantified in three categories: normal lung, exudative diffuse alveolar damage (DAD), and fibroproliferative DAD. A linear index was used to estimate the global severity of involvement by CT and histopathological analysis. Results: There was a positive correlation between patient mean CT and histopathological severity score indexes - Pearson correlation coefficient (R) = 0.66 (p = 0.0078). When analyzing the mean lung involvement percentage of each finding, positive correlations were found between the normal lung percentage between postmortem CT and histopathology (R=0.65, p = 0.0082), as well as between ground-glass opacities in postmortem CT and normal lungs in histopathology (R=0.65, p = 0.0086), but negative correlations were observed between ground-glass opacities extension and exudative diffuse alveolar damage in histological slides (R=-0.68, p = 0.005). Additionally, it was found is a trend toward a decrease in the percentage of normal lung tissue on the histological slides as the percentage of consolidations in postmortem CT scans increased (R =-0.51, p = 0.055). The analysis of the other correlations between the percentage of each finding did not show any significant correlation or correlation trends (p ≥ 0.10). Conclusions: A minimally invasive autopsy is valid. As the severity of involvement is increased in CT, more advanced disease is seen on histopathology. However, we cannot state that one specific radiological category represents a specific pathological correspondent. Ground-glass opacities, in the postmortem stage, must be interpreted with caution, as expiratory lungs may overestimate disease.

Nonlinear estimation of neural processing time from BOLD signal with application to decision-making.

The extraction of information about neural activity timing from BOLD signal is a challenging task as the shape of the BOLD curve does not directly reflect the temporal characteristics of electrical activity of neurons. In this work, we introduce the concept of neural processing time (NPT) as a parameter of the biophysical model of the hemodynamic response function (HRF). Through this new concept we aim to infer more accurately the duration of neuronal response from the highly nonlinear BOLD effect. The face validity and applicability of the concept of NPT are evaluated through simulations and analysis of experimental time series. The results of both simulation and application were compared with summary measures of HRF shape. The experiment that was analyzed consisted of a decision-making paradigm with simultaneous emotional distracters. We hypothesize that the NPT in primary sensory areas, like the fusiform gyrus, is approximately the stimulus presentation duration. On the other hand, in areas related to processing of an emotional distracter, the NPT should depend on the experimental condition. As predicted, the NPT in fusiform gyrus is close to the stimulus duration and the NPT in dorsal anterior cingulate gyrus depends on the presence of an emotional distracter. Interestingly, the NPT in right but not left dorsal lateral prefrontal cortex depends on the stimulus emotional content. The summary measures of HRF obtained by a standard approach did not detect the variations observed in the NPT.

Postmortem brain 7T MRI with minimally invasive pathological correlation in deceased COVID-19 subjects.

BACKGROUND: Brain abnormalities are a concern in COVID-19, so we used minimally invasive autopsy (MIA) to investigate it, consisting of brain 7T MR and CT images and tissue sampling via transethmoidal route with at least three fragments: the first one for reverse transcription polymerase chain reaction (RT-PCR) analysis and the remaining fixed and stained with hematoxylin and eosin. Two mouse monoclonal anti-coronavirus (SARS-CoV-2) antibodies were employed in immunohistochemical (IHC) reactions. RESULTS: Seven deceased COVID-19 patients underwent MIA with brain MR and CT images, six of them with tissue sampling. Imaging findings included infarcts, punctate brain hemorrhagic foci, subarachnoid hemorrhage and signal abnormalities in the splenium, basal ganglia, white matter, hippocampi and posterior cortico-subcortical. Punctate brain hemorrhage was the most common finding (three out of seven cases). Brain histological analysis revealed reactive gliosis, congestion, cortical neuron eosinophilic degeneration and axonal disruption in all six cases. Other findings included edema (5 cases), discrete perivascular hemorrhages (5), cerebral small vessel disease (3), perivascular hemosiderin deposits (3), Alzheimer type II glia (3), abundant corpora amylacea (3), ischemic foci (1), periventricular encephalitis foci (1), periventricular vascular ectasia (1) and fibrin thrombi (1). SARS-CoV-2 RNA was detected with RT-PCR in 5 out of 5 and IHC in 6 out 6 patients (100%). CONCLUSIONS: Despite limited sampling, MIA was an effective tool to evaluate underlying pathological brain changes in deceased COVID-19 patients. Imaging findings were varied, and pathological features corroborated signs of hypoxia, alterations related to systemic critically ill and SARS-CoV-2 brain invasion.

Global efficiency of the motor network is decreased in Parkinson's disease in comparison with essential tremor and healthy controls.

BACKGROUND: Graph theory (GT) is a mathematical field that analyses complex networks that can be applied to neuroimaging to quantify brain's functional systems in Parkinson's disease (PD) and essential tremor (ET). OBJECTIVES: To evaluate the functional connectivity (FC) measured by the global efficiency (GE) of the motor network in PD and compare it to ET and healthy controls (HC), and correlate it to clinical parameters. METHODS: 103 subjects (54PD, 18ET, 31HC) were submitted to structural and functional MRI. A network was designed with regions of interest (ROIs) involved in motor function, and GT was applied to determine its GE. Clinical parameters were analyzed as covariates to estimate the impact of disease severity and medication on GE. RESULTS: GE of the motor circuit was reduced in PD in comparison with HC (p .042). Areas that most contributed to it were left supplementary motor area (SMA) and bilateral postcentral gyrus. Tremor scores correlated positively with GE of the motor network in PD subgroups. For ET, there was an increase in the connectivity of the anterior cerebellar network to the other ROIs of the motor circuit in comparison with PD. CONCLUSIONS: FC measured by the GE of the motor network is diminished in PD in comparison with HC, especially due to decreased connectivity of left SMA and bilateral postcentral gyrus. This finding supports the theory that there is a global impairment of the motor network in PD, and it does not affect just the basal ganglia, but also areas associated with movement modulation. The ET group presented an increased connectivity of the anterior cerebellar network to the other ROIs of the motor circuit when compared to PD, which reinforces what it is known about its role in this pathology.

Abnormal visual activation in Parkinson's disease patients.

Among nonmotor symptoms observed in Parkinson's disease (PD) dysfunction in the visual system, including hallucinations, has a significant impact in their quality of life. To further explore the visual system in PD patients we designed two fMRI experiments comparing 18 healthy volunteers with 16 PD patients without visual complaints in two visual fMRI paradigms: the flickering checkerboard task and a facial perception paradigm. PD patients displayed a decreased activity in the primary visual cortex (Broadmann area 17) bilaterally as compared to healthy volunteers during flickering checkerboard task and increased activity in fusiform gyrus (Broadmann area 37) during facial perception paradigm. Our findings confirm the notion that PD patients show significant changes in the visual cortex system even before the visual symptoms are clinically evident. Further studies are necessary to evaluate the contribution of these abnormalities to the development visual symptoms in PD.

Depression in Parkinson's disease: convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus.

Depression is the most frequent psychiatric disorder in Parkinson's disease (PD). Although evidence suggests that depression in PD is related to the degenerative process that underlies the disease, further studies are necessary to better understand the neural basis of depression in this population of patients. In order to investigate neuronal alterations underlying the depression in PD, we studied thirty-six patients with idiopathic PD. Twenty of these patients had the diagnosis of major depression disorder and sixteen did not. The two groups were matched for PD motor severity according to Unified Parkinson Disease Rating Scale (UPDRS). First we conducted a functional magnetic resonance imaging (fMRI) using an event-related parametric emotional perception paradigm with test retest design. Our results showed decreased activation in the left mediodorsal (MD) thalamus and in medial prefrontal cortex in PD patients with depression compared to those without depression. Based upon these results and the increased neuron count in MD thalamus found in previous studies, we conducted a region of interest (ROI) guided voxel-based morphometry (VBM) study comparing the thalamic volume. Our results showed an increased volume in mediodorsal thalamic nuclei bilaterally. Converging morphological changes and functional emotional processing in mediodorsal thalamus highlight the importance of limbic thalamus in PD depression. In addition this data supports the link between neurodegenerative alterations and mood regulation.

Natural language processing in the classification of radiology reports in benign gallbladder diseases / O processamento de língua natural permite a classificação correta de laudos radiológicos em doenças benignas da vesícula biliar

Abstract Objective: To develop a natural language processing application capable of automatically identifying benign gallbladder diseases that require surgery, from radiology reports. Materials and Methods: We developed a text classifier to classify reports as describing benign diseases of the gallbladder that do or do not require surgery. We randomly selected 1,200 reports describing the gallbladder from our database, including different modalities. Four radiologists classified the reports as describing benign disease that should or should not be treated surgically. Two deep learning architectures were trained for classification: a convolutional neural network (CNN) and a bidirectional long short-term memory (BiLSTM) network. In order to represent words in vector form, the models included a Word2Vec representation, with dimensions of 300 or 1,000. The models were trained and evaluated by dividing the dataset into training, validation, and subsets (80/10/10). Results: The CNN and BiLSTM performed well in both dimensional spaces. For the 300- and 1,000-dimensional spaces, respectively, the F1-scores were 0.95945 and 0.95302 for the CNN model, compared with 0.96732 and 0.96732 for the BiLSTM model. Conclusion: Our models achieved high performance, regardless of the architecture and dimensional space employed.

Resumo Objetivo: Desenvolver uma aplicação de processamento de linguagem natural capaz de identificar automaticamente doenças cirúrgicas benignas da vesícula biliar a partir de laudos radiológicos. Materiais e Métodos: Desenvolvemos um classificador de texto para classificar laudos como contendo ou não doenças cirúrgicas benignas da vesícula biliar. Selecionamos aleatoriamente 1.200 laudos com descrição da vesícula biliar de nosso banco de dados, incluindo diferentes modalidades. Quatro radiologistas classificaram os laudos como doença benigna cirúrgica ou não. Duas arquiteturas de aprendizagem profunda foram treinadas para a classificação: a rede neural convolucional (convolutional neural network - CNN) e a memória longa de curto prazo bidirecional (bidirectional long short-term memory - BiLSTM). Para representar palavras de forma vetorial, os modelos incluíram uma representação Word2Vec, com dimensões variando de 300 a 1000. Os modelos foram treinados e avaliados por meio da divisão do conjunto de dados entre treinamento, validação e teste (80/10/10). Resultados: CNN e BiLSTM tiveram bom desempenho em ambos os espaços dimensionais. Relatamos para 300 e 1000 dimensões, respectivamente, as pontuações F1 de 0,95945 e 0,95302 para o modelo CNN e de 0,96732 e 0,96732 para a BiLSTM. Conclusão: Nossos modelos alcançaram alto desempenho, independentemente de diferentes arquiteturas e espaços dimensionais.

Morphologic criteria of vermiform appendix on computed tomography and a possible risk of developing acute appendicitis.

OBJECTIVE: To evaluate the correlation of morphological criteria of the cecal appendix using computed tomography (CT) and the possible risk of developing acute appendicitis. MATERIALS AND METHODS: Cases were defined as patients with surgically confirmed acute appendicitis who had undergone CT at least twice: at diagnosis and at least one month prior. Controls were defined as emergency patients with abdominal pain who had undergone abdominal CT that excluded acute appendicitis and had also undergone CT at least one month before. RESULTS: 100 cases and 100 controls were selected for inclusion in the final analysis. Comparisons between the cases and controls revealed the following: mean transverse diameter of 0.6 cm (range, 0.4-1.0 cm) versus 0.6 cm (range, 0.6-0.8 cm; p = 0.37); mean length of 6.6 cm (range, 3.5-9.7 cm) versus 6.6 cm (range, 4.5-8.3 cm; p = 0.87); mean angle of 100° (range, 23-178°) versus 86° (range, 43-160°; p = 0.01); vertical descending orientation in 56% versus 45% (p = 0.2); absence of gas in 69% versus 77% (p = 0.34); and presence of an appendicolith in 17% versus 8% (p = 0.08). CONCLUSION: Hypothetical risk factors for obstruction of the vermiform appendix detected on CT were not associated with acute appendicitis. That suggests that factors other than those related to mechanical obstruction are implicated in the pathogenesis of acute appendicitis.

OBJETIVO: Avaliar a correlação de critérios morfológicos do apêndice cecal por tomografia computadorizada (TC) e o risco de apendicite aguda. MATERIAIS E MÉTODOS: Casos foram definidos como apendicite aguda confirmada cirurgicamente que tiveram pelo menos dois exames de TC: um no diagnóstico de apendicite aguda e outro no mínimo um mês antes. O grupo controle foi definido como pacientes emergenciais com dor abdominal com TC de abdome excluindo apendicite aguda e com TC prévia pelo menos um mês antes. RESULTADOS: 100 casos e 100 controles foram selecionados. A comparação das variáveis dos casos e controles revelou: diâmetro transverso médio de 0,6 cm (faixa: 0,4-1,0 cm) versus 0,6 (faixa: 0,6-0,8 cm) (p = 0,37); comprimento médio de 6,6 cm (faixa: 3,5-9,7 cm) versus 6,6 cm (faixa: 4,5-8,3 cm) (p = 0,87); ângulo médio de 100° (faixa: 23-178°) versus 86° (faixa: 43-160°) (p = 0,01); orientação descendente em 56% versus 45% (p = 0,2); ausência de gás em 69% versus 77% (p = 0,34) e presença de apendicólito em 17% versus 8% (p = 0,08). CONCLUSÃO: Fatores obstrutivos hipotéticos do apêndice cecal na TC não foram associados a apendicite aguda. Isso sugere que outros fatores diferentes de obstrução mecânica podem estar implicados na gênese da apendicite aguda.

Hyperplane navigation: a method to set individual scores in fMRI group datasets.

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups' patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects.

Altered Functional Connectivity Between Precuneus and Motor Systems in Parkinson's Disease Patients.

Parkinson's disease (PD) is a neurodegenerative disorder that affects motor skills and cognition. As brain structure and function are compromised, functional magnetic resonance imaging (fMRI) can be a helpful tool to further investigate how intrinsic connectivity is impaired on the disease. The precuneus and medial prefrontal cortex (mPFC) are hub regions involved on the default mode network (DMN), a system that is active during rest and related to cognitive processes. We hypothesized that PD patients would present a decrease in functional connectivity among these two regions and the rest of the brain. Our goal was to identify regions in which functional connectivity to precuneus and mPFC was altered in PD. This study was based on resting-state fMRI data from 37 healthy subjects and 55 PD patients. Precuneus and mPFC were selected as seed regions in a whole brain functional connectivity mapping. As expected, we found abnormal connectivity from precuneus to motor system regions in PD patients, pointing toward a decreased connectivity in the disease. No significant group effects were found for the mPFC. Our findings suggest that internetwork connectivity from DMN to motor system is impaired in PD.

An fMRI-compatible force measurement system for the evaluation of the neural correlates of step initiation.

Knowledge of brain correlates of postural control is limited by the technical difficulties in performing controlled experiments with currently available neuroimaging methods. Here we present a system that allows the measurement of anticipatory postural adjustment of human legs to be synchronized with the acquisition of functional magnetic resonance imaging data. The device is composed of Magnetic Resonance Imaging (MRI) compatible force sensors able to measure the level of force applied by both feet. We tested the device in a group of healthy young subjects and a group of elderly subjects with Parkinson's disease using an event-related functional MRI (fMRI) experiment design. In both groups the postural behavior inside the magnetic resonance was correlated to the behavior during gait initiation outside the scanner. The system did not produce noticeable imaging artifacts in the data. Healthy young people showed brain activation patterns coherent with movement planning. Parkinson's disease patients demonstrated an altered pattern of activation within the motor circuitry. We concluded that this force measurement system is able to index both normal and abnormal preparation for gait initiation within an fMRI experiment.

Morphologic criteria of vermiform appendix on computed tomography and a possible risk of developing acute appendicitis / Critérios morfológicos do apêndice cecal na tomografia computadorizada e possível risco de desenvolver apendicite aguda

Abstract Objective: To evaluate the correlation of morphological criteria of the cecal appendix using computed tomography (CT) and the possible risk of developing acute appendicitis. Materials and Methods: Cases were defined as patients with surgically confirmed acute appendicitis who had undergone CT at least twice: at diagnosis and at least one month prior. Controls were defined as emergency patients with abdominal pain who had undergone abdominal CT that excluded acute appendicitis and had also undergone CT at least one month before. Results: 100 cases and 100 controls were selected for inclusion in the final analysis. Comparisons between the cases and controls revealed the following: mean transverse diameter of 0.6 cm (range, 0.4-1.0 cm) versus 0.6 cm (range, 0.6-0.8 cm; p = 0.37); mean length of 6.6 cm (range, 3.5-9.7 cm) versus 6.6 cm (range, 4.5-8.3 cm; p = 0.87); mean angle of 100° (range, 23-178°) versus 86° (range, 43-160°; p = 0.01); vertical descending orientation in 56% versus 45% (p = 0.2); absence of gas in 69% versus 77% (p = 0.34); and presence of an appendicolith in 17% versus 8% (p = 0.08). Conclusion: Hypothetical risk factors for obstruction of the vermiform appendix detected on CT were not associated with acute appendicitis. That suggests that factors other than those related to mechanical obstruction are implicated in the pathogenesis of acute appendicitis.

Resumo Objetivo: Avaliar a correlação de critérios morfológicos do apêndice cecal por tomografia computadorizada (TC) e o risco de apendicite aguda. Materiais e Métodos: Casos foram definidos como apendicite aguda confirmada cirurgicamente que tiveram pelo menos dois exames de TC: um no diagnóstico de apendicite aguda e outro no mínimo um mês antes. O grupo controle foi definido como pacientes emergenciais com dor abdominal com TC de abdome excluindo apendicite aguda e com TC prévia pelo menos um mês antes. Resultados: 100 casos e 100 controles foram selecionados. A comparação das variáveis dos casos e controles revelou: diâmetro transverso médio de 0,6 cm (faixa: 0,4-1,0 cm) versus 0,6 (faixa: 0,6-0,8 cm) (p = 0,37); comprimento médio de 6,6 cm (faixa: 3,5-9,7 cm) versus 6,6 cm (faixa: 4,5-8,3 cm) (p = 0,87); ângulo médio de 100° (faixa: 23-178°) versus 86° (faixa: 43-160°) (p = 0,01); orientação descendente em 56% versus 45% (p = 0,2); ausência de gás em 69% versus 77% (p = 0,34) e presença de apendicólito em 17% versus 8% (p = 0,08). Conclusão: Fatores obstrutivos hipotéticos do apêndice cecal na TC não foram associados a apendicite aguda. Isso sugere que outros fatores diferentes de obstrução mecânica podem estar implicados na gênese da apendicite aguda.

In vivo magnetic resonance imaging tracking of C6 glioma cells labeled with superparamagnetic iron oxide nanoparticles.

OBJECTIVE: The aim of the current study was to monitor the migration of superparamagnetic iron oxide nanoparticle (SPION)-labeled C6 cells, which were used to induce glioblastoma tumor growth in an animal model, over time using magnetic resonance imaging (MRI), with the goal of aiding in tumor prognosis and therapy. METHODS: Two groups of male Wistar rats were used for the tumor induction model. In the first group (n=3), the tumors were induced via the injection of SPION-labeled C6 cells. In the second group (n=3), the tumors were induced via the injection of unlabeled C6 cells. Prussian Blue staining was performed to analyze the SPION distribution within the C6 cells in vitro. Tumor-inducing C6 cells were injected into the right frontal cortex, and subsequent tumor monitoring and SPION detection were performed using T2- and T2*-weighted MRI at a 2T field strength. In addition, cancerous tissue was histologically analyzed after performing the MRI studies. RESULTS: The in vitro qualitative evaluation demonstrated adequate distribution and satisfactory cell labeling of the SPIONs. At 14 or 21 days after C6 injection, a SPION-induced T2- and T2*-weighted MRI signal reduction was observed within the lesion located in the left frontal lobe on parasagittal topography. Moreover, histological staining of the tumor tissue with Prussian Blue revealed a broad distribution of SPIONs within the C6 cells. CONCLUSION: MRI analyses exhibit potential for monitoring the tumor growth of C6 cells efficiently labeled with SPIONs.

rTMS treatment for depression in Parkinson's disease increases BOLD responses in the left prefrontal cortex.

The mechanisms underlying the effects of antidepressant treatment in patients with Parkinson's disease (PD) are unclear. The neural changes after successful therapy investigated by neuroimaging methods can give insights into the mechanisms of action related to a specific treatment choice. To study the mechanisms of neural modulation of repetitive transcranial magnetic stimulation (rTMS) and fluoxetine, 21 PD depressed patients were randomized into only two active treatment groups for 4 wk: active rTMS over left dorsolateral prefrontal cortex (DLPFC) (5 Hz rTMS; 120% motor threshold) with placebo pill and sham rTMS with fluoxetine 20 mg/d. Event-related functional magnetic resonance imaging (fMRI) with emotional stimuli was performed before and after treatment - in two sessions (test and re-test) at each time-point. The two groups of treatment had a significant, similar mood improvement. After rTMS treatment, there were brain activity decreases in left fusiform gyrus, cerebellum and right DLPFC and brain activity increases in left DLPFC and anterior cingulate gyrus compared to baseline. In contrast, after fluoxetine treatment, there were brain activity increases in right premotor and right medial prefrontal cortex. There was a significant interaction effect between groups vs. time in the left medial prefrontal cortex, suggesting that the activity in this area changed differently in the two treatment groups. Our findings show that antidepressant effects of rTMS and fluoxetine in PD are associated with changes in different areas of the depression-related neural network.