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1.
Sichuan Da Xue Xue Bao Yi Xue Ban ; 52(2): 300-305, 2021 Mar.
Artigo em Chinês | MEDLINE | ID: mdl-33829706

RESUMO

Objective: A predictive model of Alzheimer's disease (AD) was established based on brain surface meshes and geometric deep learning, and its performance was evaluated. Methods: Seventy-six clinically diagnosed AD patients and 83 healthy older adults were enrolled and randomly assigned to the training set and the test set according to a 4-to-1 ratio. Brain surface mesh was constructed from 3-D T1-weighted high-resolution structural MR volumes of each participant. After applying a series of simplification to the surface meshes, the training set was fed into the geometric deep neural network for training. The performance of the prediction model was evaluated with the test set, and the evaluation metrics included accuracy, sensitivity and specificity. Results: The prediction model trained on the right brain surface meshes with 6 000 faces achieved the best performance, with accuracy reaching 93.8%, sensitivity, 91.7%, and specificity, 94.1%. The evolution of the brain surface meshes during convolution and pooling revealed that AD patients had diffuse brain tissue loss compared with healthy older adults. Conclusion: Morphological brain analysis based on mesh data and geometric deep learning has great potential in the differential diagnosis of AD.


Assuntos
Doença de Alzheimer , Aprendizado Profundo , Idoso , Doença de Alzheimer/diagnóstico , Encéfalo/diagnóstico por imagem , Humanos , Imagem por Ressonância Magnética , Redes Neurais de Computação
2.
Neuroradiology ; 2021 Mar 23.
Artigo em Inglês | MEDLINE | ID: mdl-33758963

RESUMO

PURPOSE: To figure out the spectra features of malformations of cortical development (MCDs) and the differences between MCDs subcategories. METHODS: Twenty patients and 18 controls were studied. The patients included two subcategories: disorders of migration (DOM) and postmigration (DOPM). Spectra of patients were acquired from both the lesion and the normal-appearing contralateral side (NACS), and they were compared to those of the controls obtained from the frontal lobe. RESULTS: Compared to the controls, a decreased NAA (P = 0.002) was identified in MCDs. After dividing the MCDs into the DOM and DOPM, we found that NAA reduction was only notable in the DOM (P = 0.007). Moreover, Ins and Cr of the DOPM were higher than those of the controls (P = 0.017 and 0.013) and the DOM (P = 0.027 and 0.001). Compared to the NACS, a decreased NAA (P = 0.042) and an increased Ins (P = 0.039) were identified in the lesion of MCDs. After dividing the MCDs into the DOM and DOPM, we found no significant differences in the DOM, but Ins, Cr, and Glx of the lesion were higher than those of the NACS (P = 0.007, 0.005 and 0.047) in the DOPM. In addition, we found that Cr and Glx correlated positively to the seizure frequency (P = 0.003 and 0.016). CONCLUSION: Decreased NAA was the prominent abnormality confirmed in MCDs. Spectra of different MCDs subcategories were different: the DOM was characterized by decreased NAA, while the DOPM was characterized by increased Ins.

3.
J Magn Reson Imaging ; 2021 Jan 03.
Artigo em Inglês | MEDLINE | ID: mdl-33393131

RESUMO

Combining isocitrate dehydrogenase mutation (IDHmut) with O6 -methylguanine-DNA methyltransferase promoter methylation (MGMTmet) has been identified as a critical prognostic molecular marker for gliomas. The aim of this study was to determine the ability of glioma radiomics features from magnetic resonance imaging (MRI) to predict the co-occurrence of IDHmut and MGMTmet by applying the tree-based pipeline optimization tool (TPOT), an automated machine learning (autoML) approach. This was a retrospective study, in which 162 patients with gliomas were evaluated, including 58 patients with co-occurrence of IDHmut and MGMTmet and 104 patients with other status comprising: IDH wildtype and MGMT unmethylated (n = 67), IDH wildtype and MGMTmet (n = 36), and IDHmut and MGMT unmethylated (n = 1). Three-dimensional (3D) T1-weighted images, gadolinium-enhanced 3D T1-weighted images (Gd-3DT1WI), T2-weighted images, and fluid-attenuated inversion recovery (FLAIR) images acquired at 3.0 T were used. Radiomics features were extracted from FLAIR and Gd-3DT1WI images. The TPOT was employed to generate the best machine learning pipeline, which contains both feature selector and classifier, based on input feature sets. A 4-fold cross-validation was used to evaluate the performance of automatically generated models. For each iteration, the training set included 121 subjects, while the test set included 41 subjects. Student's t-test or a chi-square test was applied on different clinical characteristics between two groups. Sensitivity, specificity, accuracy, kappa score, and AUC were used to evaluate the performance of TPOT-generated models. Finally, we compared the above metrics of TPOT-generated models to identify the best-performing model. Patients' ages and grades between two groups were significantly different (p = 0.002 and p = 0.000, respectively). The 4-fold cross-validation showed that gradient boosting classifier trained on shape and textual features from the Laplacian-of-Gaussian-filtered Gd-3DT1 achieved the best performance (average sensitivity = 81.1%, average specificity = 94%, average accuracy = 89.4%, average kappa score = 0.76, average AUC = 0.951). Using autoML based on radiomics features from MRI, a high discriminatory accuracy was achieved for predicting co-occurrence of IDHmut and MGMTmet in gliomas. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 3.

4.
Eur Neuropsychopharmacol ; 35: 39-48, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32402652

RESUMO

Hippocampal volume deficits have been reported in chronically-treated schizophrenia patients, however, the longer-term effects of antipsychotic medications on hippocampal anatomy are unclear. This case-control study investigated volume differences in hippocampal subfields of never-treated and antipsychotic-treated patients with long-term schizophrenia. High spatial-resolution T1-weighted magnetic resonance images were collected from 29 never-treated and 40 antipsychotic-treated patients with long-term schizophrenia matched for illness duration (all ≥ 5 years), and 40 demographically-matched healthy controls. Hippocampal subfield volumes were measured using FreeSurfer v6.0, compared across groups and between hemispheres, and correlated with clinical features. Volume reductions were found in both patient groups compared to healthy controls in 8 of 26 hippocampal subfields (Cohen's d = 0.46 - 1.17, P = < .001 - .03), and more diffusely and obviously in never-treated than treated patients (Cohen's d = 0.50 - 0.90, P = < .001 - .04). Greater right-than-left volumes were seen in treated patients and healthy controls in 11 of 13 subfields (T = 2.30 - 7.29, P = < .001 - .03), but not in never-treated patients, in whom the volumes were reduced more on the right than on the left. Subfield volumes were negatively correlated with symptom severity and illness duration, and declined with age in never-treated patients. Findings indicate clinically-relevant and age-related volume reductions in hippocampal subfields of never-treated patients with long-term schizophrenia. Broader and greater subfield deficits in never-treated than treated patients, especially in the right hippocampus, suggest that long-term antipsychotic treatment may benefit hippocampal structures over the longer-term course of illness.

6.
Front Neurosci ; 14: 159, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32194371

RESUMO

Background: Anorexia nervosa (AN) is a debilitating illness whose neural basis remains unclear. Studies using tract-based spatial statistics (TBSS) with diffusion tensor imaging (DTI) have demonstrated differences in white matter (WM) microarchitecture in AN, but the findings are inconclusive and controversial. Objectives: To identify the most consistent WM abnormalities among previous TBSS studies of differences in WM microarchitecture in AN. Methods: By systematically searching online databases, a total of 11 datasets were identified, including 245 patients with AN and 246 healthy controls (HC). We used Seed-based d Mapping to analyze fractional anisotropy (FA) differences between AN patients and HC, and performed meta-regression analysis to explore the effects of clinical characteristics on WM abnormalities in AN. Results: The pooled results of all AN patients showed robustly lower FA in the corpus callosum (CC) and the cingulum compared to HC. These two regions preserved significance in the sensitivity analysis as well as in all subgroup analyses. Fiber tracking showed that the WM tracts primarily involved were the body of the CC and the cingulum bundle. Meta-regression analysis revealed that the body mass index and mean age were not linearly correlated with the lower FA. Conclusions: The most consistent WM microstructural differences in AN were in the interhemispheric connections and limbic association fibers. These common "targets" advance our understanding of the complex neural mechanisms underlying the puzzling symptoms of AN, and may help in developing early treatment approaches.

7.
Neuro Oncol ; 22(3): 393-401, 2020 03 05.
Artigo em Inglês | MEDLINE | ID: mdl-31563963

RESUMO

BACKGROUND: Conventional MRI cannot be used to identify H3 K27M mutation status. This study aimed to investigate the feasibility of predicting H3 K27M mutation status by applying an automated machine learning (autoML) approach to the MR radiomics features of patients with midline gliomas. METHODS: This single-institution retrospective study included 100 patients with midline gliomas, including 40 patients with H3 K27M mutations and 60 wild-type patients. Radiomics features were extracted from fluid-attenuated inversion recovery images. Prior to autoML analysis, the dataset was randomly stratified into separate 75% training and 25% testing cohorts. The Tree-based Pipeline Optimization Tool (TPOT) was applied to optimize the machine learning pipeline and select important radiomics features. We compared the performance of 10 independent TPOT-generated models based on training and testing cohorts using the area under the curve (AUC) and average precision to obtain the final model. An independent cohort of 22 patients was used to validate the best model. RESULTS: Ten prediction models were generated by TPOT, and the accuracy obtained with the best pipeline ranged from 0.788 to 0.867 for the training cohort and from 0.60 to 0.84 for the testing cohort. After comparison, the AUC value and average precision of the final model were 0.903 and 0.911 in the testing cohort, respectively. In the validation set, the AUC was 0.85, and the average precision was 0.855 for the best model. CONCLUSIONS: The autoML classifier using radiomics features of conventional MR images provides high discriminatory accuracy in predicting the H3 K27M mutation status of midline glioma.

8.
J Hypertens ; 38(2): 347-353, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31584510

RESUMO

OBJECTIVES: The current study aimed to investigate the value of the computed tomography-based left-versus-right adrenal gland volume ratio (L/Rv) in screening patients with unilateral primary aldosteronism. METHODS: The current study recruited 114 patients who underwent successful adrenal venous sampling (AVS) and adrenal computed tomography at West China Hospital of Sichuan University. The patients were divided into three groups according to the AVS results: AVS-left, AVS-bilateral, and AVS-right primary aldosteronism. The volumes of the left and right adrenal glands were semiautomatically calculated. The L/Rv of each patient was computed, and its value in identifying unilateral primary aldosteronism was analyzed. RESULTS: The mean value of the L/Rv was larger in AVS-left patients and smaller in AVS-right patients than that in AVS-bilateral patients. In AVS-left primary aldosteronism patients, the cutoff value of the L/Rv with the highest Youden index was 1.344 [area under the curve (AUC) 0.851, sensitivity 80.0%, specificity 78.1%]. The optimal cutoff value was 1.908, of which 46.0% (23/50) of AVS-left primary aldosteronism patients could be identified (specificity 100.0%). In AVS-right primary aldosteronism patients, the cutoff value of the L/Rv with the highest Youden index was 1.267 (AUC 0.868, specificity 72.8%, sensitivity 87.9%). The optimal cutoff value was 0.765, of which 27.3% (9/33) of AVS-right primary aldosteronism patients could be identified (specificity 100.0%). Patients with L/Rv more than 1.908 or less than 0.765 had higher complete success rate postsurgery. CONCLUSION: Although not perfect, the L/Rv is an applicable index to screen unilateral primary aldosteronism patients for surgery. Primary aldosteronism patients, even those aged more than 35 years, with an L/Rv more than 1.908 or less than 0.765 can be spared AVS before surgery.

9.
Pol J Pathol ; 70(3): 162-173, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31820859

RESUMO

Quantitative analysis of immunohistochemically stained breast cancer specimens by cell counting is important for prognosis and treatment planning. This paper presents a robust, accurate, and novel method to label immunopositive and immunonegative cells automatically. During preprocessing, we developed an adaptive method to correct the colour aberration caused by imaging conditions. Next, a pixel-level segmentation was performed on preprocessed images using a support vector machine with a radial basis function kernel in HSV colour space. The segmentation result was processed by mathematical morphology operations to correct error-segmented regions and extract the marker for each cell. Validation studies showed that the automated cell-counting method had divergences varying from -5.05% to 3.99% compared with manual counting by a pathologist, indicating considerable agreement of the present automated cell counting method with manual counting. Thus, this method can free pathologists from laborious work and can potentially improve the accuracy and the reproducibility of diagnosis.


Assuntos
Neoplasias da Mama/diagnóstico , Processamento de Imagem Assistida por Computador , Imuno-Histoquímica , Algoritmos , Humanos , Reprodutibilidade dos Testes
10.
Sichuan Da Xue Xue Bao Yi Xue Ban ; 50(4): 494-499, 2019 Jul.
Artigo em Chinês | MEDLINE | ID: mdl-31642225

RESUMO

OBJECTIVE: To determine the myocardial texture features of cardiac magnetic resonance (CMR) in healthy adult Han populations. METHODS: 59 healthy Han volunteers were recruited for this study from May 2016 to November 2017. CMR examinations were performed on the participants with a 3.0T scanner (Tim Trio, Siemens Medical Solution) to estimate the functional parameters, Native T1 value and ECV. Texture analysis (TA) was performed on the region of interest (ROI) in the left ventricle myocardium on T1 mapping images, with 40 myocardial texture features being extracted. Differences in the myocardial texture features across gender and age groups were analyzed through Student's t-tests or Wilcoxon signed-rank tests. Spearman correlations were analyzed between the myocardial texture features and age, native T1 value and extracellular volume (ECV). RESULTS: Of the 59 participants, 28 were women and 29 were in the younger age group (< 45 years old). The male participants had higher left ventricular mass index (Lvmassi) and lower native T1 than their female counterparts (P < 0.01). No gender differences in blood pressure, heart rate, left ventricular ejection fraction (LVEF) and ECV values were found. Ten of the forty myocardial texture features showed gender differences, including two first order features and eight Grey-level co-occurrence matrix (GLCM) features. Gender differences appeared in five first order features and eight GLCM features in the younger group (< 45 years old), but not in the older group (≥45 years old). Eight myocardial texture features were correlated with age, including five first order features and three GLCM features (all P < 0.01). Six first-order texture features were correlated with Native T1 values of the left ventricle middle myocardium. Three first-order texture features were correlated with ECV. CONCLUSION: Myocardial texture features in T1 mapping images vary by gender and age in healthy Han populations.


Assuntos
Coração/diagnóstico por imagem , Miocárdio , Função Ventricular Esquerda , Adulto , Fatores Etários , Meios de Contraste , Feminino , Voluntários Saudáveis , Humanos , Espectroscopia de Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Fatores Sexuais
11.
Eur Radiol ; 29(11): 6152-6162, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31444599

RESUMO

OBJECTIVE: The aim of this study was to investigate whether intraplacental texture features from routine placental MRI can objectively and accurately predict invasive placentation. MATERIAL AND METHODS: This retrospective study includes 99 pregnant women with pathologically confirmed placental invasion and 56 pregnant women with simple placenta previa. All participants underwent magnetic resonance imaging after 24 gestational weeks. The placenta was segmented in sagittal images from both turbo spin echo (TSE) and balanced turbo field echo (bTFE) sequences. Textural features were extracted from the both original and Laplacian of Gaussian (LoG)-filtered MRI images. An automated machine learning algorithm was applied to the extracted feature sets to obtain the optimal preprocessing steps, classification algorithm, and corresponding hyper-parameters. RESULTS: A gradient boosting classifier using all textual features from original and LoG-filtered TSE images and bTFE images identified by the automated machine learning algorithm achieved the optimal performance with sensitivity, specificity, accuracy, and area under ROC curve (AUC) of 100%, 88.5%, 95.2%, and 0.98 in the prediction of placental invasion. In addition, textural features that contributed to the prediction of placental invasion differ from the features significantly affected by normal placenta maturation. CONCLUSIONS: Quantifying intraplacental heterogeneity using LoG filtration and texture analysis highlights the different heterogeneous appearance caused by abnormal placentation relative to normal maturation. The predictive model derived from automated machine learning yielded good performance, indicating the proposed radiomic analysis pipeline can accurately predict placental invasion and facilitate clinical decision-making for pregnant women with suspicious placental invasion. KEY POINTS: • The intraplacental texture features have high efficiency in prediction of invasive placentation after 24 gestational weeks. • The features with dominated predictive power did not overlap with the features significantly affected by gestational age.


Assuntos
Algoritmos , Aprendizado de Máquina , Imagem por Ressonância Magnética/métodos , Placenta Prévia/diagnóstico , Placenta/patologia , Placentação/fisiologia , Diagnóstico Pré-Natal/métodos , Adulto , Feminino , Humanos , Gravidez , Estudos Retrospectivos , Adulto Jovem
12.
Med Image Anal ; 55: 165-180, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31085444

RESUMO

Structure-preserved denoising of 3D magnetic resonance imaging (MRI) images is a critical step in medical image analysis. Over the past few years, many algorithms with impressive performances have been proposed. In this paper, inspired by the idea of deep learning, we introduce an MRI denoising method based on the residual encoder-decoder Wasserstein generative adversarial network (RED-WGAN). Specifically, to explore the structure similarity between neighboring slices, a 3D configuration is utilized as the basic processing unit. Residual autoencoders combined with deconvolution operations are introduced into the generator network. Furthermore, to alleviate the oversmoothing shortcoming of the traditional mean squared error (MSE) loss function, the perceptual similarity, which is implemented by calculating the distances in the feature space extracted by a pretrained VGG-19 network, is incorporated with the MSE and adversarial losses to form the new loss function. Extensive experiments are implemented to assess the performance of the proposed method. The experimental results show that the proposed RED-WGAN achieves performance superior to several state-of-the-art methods in both simulated and real clinical data. In particular, our method demonstrates powerful abilities in both noise suppression and structure preservation.


Assuntos
Algoritmos , Encéfalo/diagnóstico por imagem , Aprendizado Profundo , Processamento de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Imagem por Ressonância Magnética/métodos , Humanos , Razão Sinal-Ruído
13.
Endocr Pract ; 25(8): 830-835, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31013150

RESUMO

Objective: This study investigated the characteristics of the adrenal limbs of primary aldosteronism (PA) patients and evaluated the value of the adrenal limb width measurement for the differentiation of unilateral PA from bilateral PA. Methods: A total of 122 PA patients (93 unilateral PA, ages ranged from 23 to 72 years; 29 bilateral PA, ages ranged from 30 to 68 years) who had undergone successful adrenal venous sampling (AVS) and adrenal gland computed tomography (CT) scan were retrospectively included. The maximum width of each adrenal gland limb (normal area on CT images) was measured, the left adrenal limb width to right adrenal limb width ratio (L/Rw) was calculated, and its potential value in the differentiation of unilateral PA and bilateral PA was analyzed. Results: The mean widths of the left adrenal limbs and the right adrenal limbs were 0.52 ± 0.10 cm and 0.43 ± 0.09 cm in unilateral PA patients, versus 0.52 ± 0.10 cm and 0.49 ± 0.12 cm in bilateral PA patients. The L/Rw ratio was 1.22 ± 0.24 in unilateral PA patients and 1.11 ± 0.23 in bilateral PA patients (P<.05). In the subgroup of PA patients over 55 years of age, compared with AVS, the sensitivity and specificity of the L/Rw ratio at 1.06 for subtype classification were 75% and 82%, respectively. Conclusion: A lower L/Rw ratio, referring to the ratio of the left adrenal limb width to the right adrenal limb width, may be a predictor of bilateral PA, especially in PA patients over 55 years of age. Abbreviations: APA = aldosterone-producing adenoma; AVS = adrenal venous sampling; BAH = bilateral adrenal hyperplasia; BMI = body mass index; CT = computed tomography; L/Rw = ratio of left adrenal limb width to right adrenal limb width; PA = primary aldosteronism.


Assuntos
Adenoma Adrenocortical , Hiperaldosteronismo , Glândulas Suprarrenais , Adulto , Idoso , Aldosterona , Humanos , Pessoa de Meia-Idade , Estudos Retrospectivos , Adulto Jovem
14.
IEEE Trans Med Imaging ; 38(11): 2607-2619, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-30908204

RESUMO

Over the past few years, dictionary learning (DL)-based methods have been successfully used in various image reconstruction problems. However, the traditional DL-based computed tomography (CT) reconstruction methods are patch-based and ignore the consistency of pixels in overlapped patches. In addition, the features learned by these methods always contain shifted versions of the same features. In recent years, convolutional sparse coding (CSC) has been developed to address these problems. In this paper, inspired by several successful applications of CSC in the field of signal processing, we explore the potential of CSC in sparse-view CT reconstruction. By directly working on the whole image, without the necessity of dividing the image into overlapped patches in DL-based methods, the proposed methods can maintain more details and avoid artifacts caused by patch aggregation. With predetermined filters, an alternating scheme is developed to optimize the objective function. Extensive experiments with simulated and real CT data were performed to validate the effectiveness of the proposed methods. The qualitative and quantitative results demonstrate that the proposed methods achieve better performance than the several existing state-of-the-art methods.


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodos , Abdome/diagnóstico por imagem , Algoritmos , Aprendizado Profundo , Humanos , Radiografia Abdominal
15.
Schizophr Res ; 214: 11-17, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-29208422

RESUMO

Although regional brain deficits have been demonstrated in schizophrenia patients by structural MRI studies, one important question that remains largely unanswered is whether the complex and subtle deficits revealed by MRI could be used as objective biomarkers to discriminate patients from healthy controls individually. To address this question, a total of 326 right-handed participants were recruited, including 163 drug-naïve first-episode schizophrenia (FES) patients and 163 demographically matched healthy controls. High-resolution anatomic data were acquired from all subjects and processed via Freesurfer software to obtain cortical thickness and surface area measurements. Subsequently, the Support Vector Machine (SVM) was used to explore the potential utility for cortical thickness and surface area measurements in the differentiation of individual patients and healthy controls. The accuracy of correct classification of patients and controls was 85.0% (specificity 87.0%, sensitivity 83.0%) for surface area and 81.8% (specificity 85.0%, sensitivity 76.9%) for cortical thickness (p<0.001 after permutation testing). Regions contributing to classification accuracy mainly included the gray matter in default mode, central executive, salience, and visual networks. Current findings, in a sample of never-treated FES patients, suggest that the patterns of illness-related gray matter changes has potential as a biomarker for identifying structural brain alterations in individuals with schizophrenia. Future prospective studies are needed to evaluate the utility of imaging biomarkers for research and potentially for clinical purpose.


Assuntos
Encéfalo/diagnóstico por imagem , Imagem por Ressonância Magnética/métodos , Esquizofrenia/classificação , Esquizofrenia/diagnóstico por imagem , Máquina de Vetores de Suporte , Encéfalo/patologia , Feminino , Humanos , Interpretação de Imagem Assistida por Computador/métodos , Masculino , Tamanho do Órgão , Esquizofrenia/patologia , Sensibilidade e Especificidade , Adulto Jovem
16.
World Neurosurg ; 122: 229-239, 2019 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-30404049

RESUMO

BACKGROUND: Meningeal melanoma is a rare tumor of the central nervous system, whose amelanotic variant is called "amelanotic meningeal melanoma" (AMM). AMM does not produce melanin and therefore does not exhibit typical short T1 and short T2 signal on magnetic resonance imaging and thus can be easily misdiagnosed and be inappropriately managed. To date, only 4 AMM cases have been reported in the English literature. Here, we report the fifth case. CASE DESCRIPTION: A 26-year-old female patient presented with a 4-month history of progressive headache and nausea, the conventional magnetic resonance imaging demonstrated a posterior fossa mass accompanied by diffuse leptomeningeal dissemination. Repeated cerebrospinal fluid cytology screening showed negative results. The functional magnetic resonance examinations, including diffusion-weighted imaging, proton magnetic resonance spectroscopy, and dynamic susceptibility contrast perfusion-weighted imaging, provided complementary information. The final diagnosis of AMM was made by immunohistochemistry. Despite gross total excision of the tumor, the disease progressed, and the patient died 10 months after diagnosis. CONCLUSIONS: Our experience with this case demonstrated that meningeal melanoma should be included in the differential diagnosis when an intracranial mass is accompanied by leptomeningeal dissemination, and especially when proton magnetic resonance spectroscopy and dynamic susceptibility contrast perfusion-weighted imaging indicate a malignant tumor whereas diffusion-weighted imaging does not. And the loss of a typical melanin signal should not server as an excluding criterion for meningeal melanoma.


Assuntos
Melanoma Amelanótico/diagnóstico , Neoplasias Meníngeas/diagnóstico , Meninges/diagnóstico por imagem , Adulto , Diagnóstico Diferencial , Evolução Fatal , Feminino , Humanos , Melanoma Amelanótico/patologia , Melanoma Amelanótico/cirurgia , Neoplasias Meníngeas/patologia , Neoplasias Meníngeas/cirurgia , Meninges/patologia , Meninges/cirurgia , Metástase Neoplásica/diagnóstico por imagem
17.
Eur Child Adolesc Psychiatry ; 28(6): 807-817, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30392119

RESUMO

Previous studies have shown that posttraumatic stress disorder (PTSD) is associated with dysfunction of the limbic system, in which the amygdala plays an important role. The purpose of this study was to evaluate whether the neurochemical concentrations assessed by proton magnetic resonance spectroscopy (1H-MRS) in the amygdala are abnormal in children and adolescents with PTSD. Twenty-eight pediatric PTSD patients (11 boys, 17 girls) and 24 matched trauma-exposed control subjects (9 boys, 15 girls) underwent magnetic resonance brain imaging and 1H-MRS of the bilateral amygdalae. The concentrations of N-acetylaspartate (NAA), myo-inositol (mI), total creatine (tCr) and total choline (tCho) in the right amygdala were significantly increased in PTSD patients compared with trauma-exposed control subjects. There were significant group-by-age interactions in the left amygdala NAA and right amygdala mI concentrations: older pediatric patients with PTSD had higher left amygdala NAA concentration and younger patients had higher right amygdala mI concentration than trauma-exposed control subjects. There was also a significant correlation between right mI concentration and time since trauma in PTSD patients. Finally, there was significant group-by-age interaction in the left amygdala volume; intragroup analysis revealed that the right amygdala volume was significantly lower than the left in the PTSD group, but not in the control group. These neurochemical abnormalities of the amygdala may indicate that dysfunctions of both neurons and glial cells are involved in the pathology of pediatric PTSD.


Assuntos
Tonsila do Cerebelo/diagnóstico por imagem , Tonsila do Cerebelo/metabolismo , Transtornos de Estresse Pós-Traumáticos/diagnóstico por imagem , Transtornos de Estresse Pós-Traumáticos/metabolismo , Adolescente , Ácido Aspártico/análogos & derivados , Ácido Aspártico/metabolismo , Atrofia/diagnóstico por imagem , Atrofia/metabolismo , Biomarcadores/metabolismo , Criança , Colina/metabolismo , Creatina/metabolismo , Estudos Transversais , Feminino , Humanos , Inositol/metabolismo , Imagem por Ressonância Magnética/métodos , Espectroscopia de Ressonância Magnética/métodos , Masculino , Espectroscopia de Prótons por Ressonância Magnética/métodos
18.
Transl Psychiatry ; 8(1): 277, 2018 12 13.
Artigo em Inglês | MEDLINE | ID: mdl-30546047

RESUMO

Anorexia nervosa (AN) is a severe psychiatric disorder with high mortality. The underlying neurobiological mechanisms are not well understood, and high-resolution structural magnetic resonance brain imaging studies have given inconsistent results. Here we aimed to psychoradiologically define the most prominent and replicable abnormalities of gray matter volume (GMV) in AN patients, and to examine their relationship to demographics and clinical characteristics, by means of a new coordinate-based meta-analytic technique called seed-based d mapping (SDM). In a pooled analysis of all AN patients we identified decreased GMV in the bilateral median cingulate cortices and posterior cingulate cortices extending to the bilateral precuneus, and the supplementary motor area. In subgroup analysis we found an additional decreased GMV in the right fusiform in adult AN, and a decreased GMV in the left amygdala and left anterior cingulate cortex in AN patients without comorbidity (pure AN). Thus, the most consistent GMV alterations in AN patients are in the default mode network and the sensorimotor network. These psychoradiological findings of the brain abnormalities might underpin the neuropathophysiology in AN.


Assuntos
Anorexia Nervosa/patologia , Encéfalo/patologia , Substância Cinzenta/patologia , Adolescente , Adulto , Anorexia Nervosa/diagnóstico por imagem , Encéfalo/diagnóstico por imagem , Feminino , Substância Cinzenta/diagnóstico por imagem , Humanos , Processamento de Imagem Assistida por Computador , Imagem por Ressonância Magnética , Masculino , Adulto Jovem
19.
Front Neurosci ; 12: 744, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30405333

RESUMO

Presbycusis (PC) is characterized by bilateral sensorineural hearing loss at high frequencies and speech-perception difficulties in noisy environments and has a strikingly detrimental impact on cognitive function. As the neural consequences of PC may involve the whole brain, we hypothesized that patients with PC would show structural alterations not only in the auditory cortex but also in the cortexes involved in cognitive function. The purpose of this study was to use surface-based morphometry (SBM) analysis to elucidate whole-brain structural differences between patients with PC and age-matched normal hearing controls. Three-dimensional T1-weighted MR images of 26 patients with mild PC and 26 age-, sex- and education-matched healthy controls (HCs) were acquired. All participants underwent a battery of neuropsychological tests. Our results revealed gray matter atrophy in several auditory cortical areas, nodes of the default mode network (DMN), including the bilateral precuneus and inferior parietal lobule, the right posterior cingulate cortex (PCC), and the right insula of patients with PC compared to that in the HCs. Our findings also revealed that hearing loss was associated with reduced gray matter volume in the right primary auditory cortex of patients with PC. Moreover, structural alterations in the nodes of the DMN were associated with cognitive impairments in PC patients. Additionally, this study provides evidence that a thicker right insula is associated with better speech perception in patients with PC. Based on these findings, we argue that the onset of PC seems to trigger its own cascade of conditions, including a need for increased cognitive resources during speech comprehension, which might lead to auditory and cognition-related cortical reorganization.

20.
J Affect Disord ; 241: 539-545, 2018 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-30153637

RESUMO

BACKGROUND: Previous psychoradiological studies of posttraumatic stress disorder (PTSD) were mainly of patients at a chronic stage, focusing on brain regions outside the amygdala. The goals of this study were to investigate the early biochemical and structural changes of anterior cingulate cortex (ACC) and amygdala in patients with PTSD and to explore their relationships. METHODS: Seventy-eight drug-naïve PTSD subjects and 71 non-PTSD age- and sex-matched control subjects were enrolled, all of whom had suffered the same earthquake about one year before. Single-voxel proton magnetic resonance spectroscopy (1H-MRS) was performed and absolute metabolite concentrations in ACC and bilateral amygdalae were estimated with LCModel. Bilateral amygdalae were manually outlined and their volumes were calculated and corrected for the total intracranial volume. RESULTS: The PTSD group showed significantly increased N-acetylaspartate (NAA) concentration in the ACC, increased creatine (Cr) concentration in the left amygdala, and increased myo-inositol (mI) concentration in the right amygdala, compared to non-PTSD controls. The NAA concentration in ACC was negatively correlated with the time since trauma. The PTSD group showed significantly decreased volumes of bilateral amygdalae compared to non-PTSD controls, but amygdala volumes were not correlated with metabolite concentrations. LIMITATIONS: Longitudinal studies are needed to explore the metabolic and structural changes of PTSD at different stages. The volume of ACC was not measured. CONCLUSIONS: This concurrent increase in some metabolite concentrations and decrease of amygdala volumes may represent a pattern of biochemical and morphological changes in recent-onset PTSD which is different from that reported in chronic PTSD.


Assuntos
Tonsila do Cerebelo/metabolismo , Tonsila do Cerebelo/patologia , Ácido Aspártico/análogos & derivados , Creatina/metabolismo , Inositol/metabolismo , Transtornos de Estresse Pós-Traumáticos/metabolismo , Transtornos de Estresse Pós-Traumáticos/patologia , Adulto , Ácido Aspártico/metabolismo , Encéfalo/patologia , Feminino , Giro do Cíngulo/metabolismo , Giro do Cíngulo/patologia , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Espectroscopia de Prótons por Ressonância Magnética/métodos , Estresse Psicológico
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