Autoimmune encephalitis with posterior reversible encephalopathy syndrome: A case report.

BACKGROUND: Posterior reversible encephalopathy syndrome (PRES) is a neuroimaging-based syndrome and is associated with multifocal vasogenic cerebral edema. Patients with PRES frequently demonstrate headache, seizure, encephalopathy, altered mental function, visual loss and so on. We here report a patient who showed persistent neurologic deficits after PRES and was ultimately diagnosed with autoimmune encephalitis (AE). CASE SUMMARY: This case exhibits a rare imaging manifestation of anti-casper 2 encephalitis which was initially well-matched with PRES and associated vasogenic edema. CONCLUSION: AE should be further considered when the etiology, clinical manifestations, and course of PRES are atypical.

Prediction of Early Alzheimer Disease by Hippocampal Volume Changes under Machine Learning Algorithm.

This research was aimed at discussing the application value of different machine learning algorithms in the prediction of early Alzheimer's disease (AD), which was based on hippocampal volume changes in magnetic resonance imaging (MRI). In the research, the 84 cases in American Alzheimer's disease neuroimaging initiative (ADNI) database were selected as the research data. Based on the scoring results of cognitive function, all cases were divided into three groups, including cognitive function normal (normal group), early mild cognitive impairment (e-MCI group), and later mild cognitive impairment (l-MCI group) groups. Each group included 28 cases. The features of hippocampal volume changes in MRI images of the patients in different groups were extracted. The samples of training set and test set were established. Besides, the established support vector machine (SVM), decision tree (DT), and random forest (RF) prediction models were used to predict e-MCI. Metalinear regression was utilized to analyze MRI feature data, and the predictive accuracy, sensitivity, and specificity of different models were calculated. The result showed that the volumes of hippocampal left CA1, left CA2-3, left CA4-DG, left presubiculum, left tail, right CA2-3, right CA4-DG, right presubiculum, and right tail in e-MCI group were all smaller than those in normal group (P < 0.01). The corresponding volume of hippocampal subregions in l-MCI group was remarkably reduced compared with that in normal group (P < 0.001). The volumes of regions left CA1, left CA2-3, left CA4-DG, right CA2-3, right CA4-DG, and right presubiculum were all positively correlated with logical memory test-delay recall (LMT-DR) score (R 2 = 0.1702, 0.3779, 0.1607, 0.1620, 0.0426, and 0.1309; P < 0.001). The predictive accuracy of training set sample by DT, SVM, and RF was 86.67%, 93.33%, and 98.33%, respectively. Based on the changes in the volumes of left CA4-DG, right CA2-3, and right CA4-DG, the predictive accuracy of e-MCI and l-MCI by RF model was both higher than those by DT model (P < 0.01). Besides, the predictive accuracy, sensitivity, and specificity of e-MCI by RF model was all notably higher than those by DT model (P < 0.01). The above results demonstrated that the effective early AD prediction models were established by the volume changes in hippocampal subregions, which was based on RF in the research. The establishment of early AD prediction models offered certain reference basis to the diagnosis and treatment of AD patients.

Artificial Intelligence-based MRI Images for Brain in Prediction of Alzheimer's Disease.

The study aimed to explore the accuracy and stability of Deep metric learning (DML) algorithm in Magnetic Resonance Imaging (MRI) examination of Alzheimer's Disease (AD) patients. In this study, MRI data of patients obtained were from Alzheimer's Disease Neuroimaging Initiative (ADNI) database (A total of 180 AD cases, 88 women, 92 men; 188 samples in healthy conditions (HC), including 90 females and 98 males. 210 samples of mild cognitive impairment (MCI), 104 females and 106 males). On the basis of deep learning, an early AD diagnosis system was constructed using CNN (Convolutional Neural Network) and DML algorithms. Then, the system was used to classify AD, HC, and MCI, and the two algorithms were compared for the accuracy and stability of in classification of MRI images. It was found that in the classification of AD and HC, the classification accuracy and sensitivity of the deep measurement learning model are both 0.83, superior to the CNN model; in terms of specificity, the classification specificity of the DML model was 0.82, slightly lower than that of the CNN model; and that in the classification of MCI and HC, the classification accuracy and sensitivity of the DML model was 0.65, superior to the CNN model; and in terms of specificity, the classification specificity of the DML model was 0.66, slightly lower than that of the CNN model. It suggested that the DML model demonstrated better classification effects on early AD patients. The loss curve analysis results showed that, for classification of AD and HC or MCI and HC, the DML algorithm can improve the convergence speed of the AD early prediction model. Therefore, the DML algorithm can significantly improve the clarity and quality of MRI images, elevate the classification accuracy and stability of early AD patients, and accelerate the convergence of the model, providing a new way for early prediction of AD.

Comparison of diffusion-weighted imaging mono-exponential mode with diffusion kurtosis imaging for predicting pathological grades of clear cell renal cell carcinoma.

PURPOSE: To evaluate the role of diffusion kurtosis imaging (DKI1) in the characterization of clear cell renal cell carcinoma (ccRCC2) compared with standard diffusion-weighted imaging (DWI3). METHODS: 89 patients with histologically proven ccRCC were evaluated by DKI and DWI on a 3-T scanner. All ccRCCs were classified as grade 1-4 according to the Fuhrman classification system. The apparent diffusion coefficient (ADC4), fractional anisotropy (FA5), mean diffusivity (MD6), mean kurtosis (MK7), axial kurtosis (Ka8) and radial kurtosis (Kr9) values were recorded. The differences in DWI and DKI parameters were evaluated by independent-sample t test and a receiver operating characteristic (ROC10) analysis was performed. The DeLong test was performed to compare the ROCs. RESULTS: Compared to normal renal parenchyma, ADC and MD values of ccRCC decreased and MK, Ka, and Kr values increased (p < 0.05). ADC and MD values of ccRCC decreased with the increase in pathological grade, while MK, Ka, and Kr values were increased (p < 0.05). ADC could discriminate G1 vs G3, G1 vs G4, G2 vs G3, G2 vs G4, and G3 vs G4 (p < 0.05) except for G1 vs G2 (p > 0.05). Ka and Kr could discriminate G1 vs G2, G1 vs G3, G1 vs G4, G2 vs G4, and G3 vs G4 (p < 0.05) except for G2 vs G3 (p > 0.05). MD and MK could discriminate G1 vs G2, G1 vs G3, G1 vs G4, G2 vs G3, G2 vs G4, and G3 vs G4 (p < 0.05). The AUC of MK was the highest. The DeLong test showed that there were significant differences regarding ROCs between ADC/MK, ADC/Ka, ADC/Kr in grading G1/G2, and ADC/MK, MK/Ka in grading G3/G4 (p < 0.05). CONCLUSION: DKI was superior compared to the mono-exponential mode of DWI in grading ccRCC.

Role of Diffusional Kurtosis Imaging in Evaluating the Efficacy of Transcatheter Arterial Chemoembolization in Patients with Liver Cancer.

Objective: To explore the role of diffusional kurtosis imaging (DKI) in evaluating the efficacy of transcatheter arterial chemoembolization (TACE) in patients with liver cancer. Materials and Methods: A total of 54 patients with primary liver cancer underwent TACE were selected as the study subjects. Magnetic resonance imaging and DKI scans were carried out before and after TACE, and the relevant parameters were analyzed. Results: Compared with those before TACE, the values of radial diffusivity (Dr), axial diffusivity (Da), and mean diffusivity (MD) of tumor tissues in the patients after TACE were significantly increased, whereas the values of axial kurtosis (Ka), fractional anisotropy of kurtosis (FAk), hepatic blood volume (HBV), hepatic blood flow (HBF), and hepatic artery perfusion (HAP) were notably decreased (p < 0.05). There were no significant changes regarding FA, radial kurtosis (Kr), mean kurtosis (MK), hepatic arterial fracture (HAF), permeability-surface area product (PS), mean transit time (MTT), and portal vein perfusion (PVP) (p > 0.05). The differences in apparent diffusion coefficients (ADCs) of different liver cancer tissues in patients under different b values after operation were statistically significant, and the ADC values of liver cancer tissues were evidently higher than those of other tumor tissues (p < 0.05). Conclusion: DKI is characterized with advantages such as fastness, simpleness, high resolution, and impregnability of the density of lipiodol. It can not only directly reflect the changes in blood perfusion at the lesion but also accurately and efficiently evaluate the remnants, necrosis, and recurrence of tumor tissues based on changes in ADC under different b values. It provides certain clinical assistance for the evaluation of the efficacy before and after TACE.

Methylation Status of Transcriptional Modulatory Genes Associated with Colorectal Cancer in Northeast China.

BACKGROUND/AIMS: Methylation status plays a causal role in carcinogenesis in targeted tissues. However, the relationship between the DNA methylation status of multiple genes in blood leukocytes and colorectal cancer (CRC) susceptibility as well as interactions between dietary factors and CRC risks are unclear. METHODS: We performed a case-control study with 466 CRC patients and 507 cancer-free controls to investigate the association among the methylation status of individual genes, multiple CpG site methylation (MCSM), multiple CpG site heterogeneous methylation and CRC susceptibility. Peripheral blood DNA methylation levels were detected by performing methylation-sensitive high-resolution melting. RESULTS: Total heterogeneous methylation of CA10 and WT1 conferred a significantly higher risk of CRC (adjusted odds ratio [ORadjusted], 5.445; 95% confidence interval [CI], 3.075 to 9.643; ORadjusted, 1.831; 95% CI, 1.100 to 3.047; respectively). Subjects with high-level MCSM (MCSM-H) status demonstrated a higher risk of CRC (ORadjusted, 4.318; 95% CI, 1.529 to 12.197). Additionally, interactions between the high-level intake of fruit and CRH, WT1, and MCSM on CRC were statistically significant. CONCLUSIONS: The gene methylation status of blood leukocytes may be associated with CRC risk. MCSM-H of blood leukocytes was associated with CRC, especially in younger people. Some dietary factors may affect hypermethylation status and influence susceptibility to CRC.

Methylation Status of Transcriptional Modulatory Genes Associated with Colorectal Cancer in Northeast China

BACKGROUND/AIMS: Methylation status plays a causal role in carcinogenesis in targeted tissues. However, the relationship between the DNA methylation status of multiple genes in blood leukocytes and colorectal cancer (CRC) susceptibility as well as interactions between dietary factors and CRC risks are unclear. METHODS: We performed a case-control study with 466 CRC patients and 507 cancer-free controls to investigate the association among the methylation status of individual genes, multiple CpG site methylation (MCSM), multiple CpG site heterogeneous methylation and CRC susceptibility. Peripheral blood DNA methylation levels were detected by performing methylation-sensitive high-resolution melting. RESULTS: Total heterogeneous methylation of CA10 and WT1 conferred a significantly higher risk of CRC (adjusted odds ratio [OR(adjusted)], 5.445; 95% confidence interval [CI], 3.075 to 9.643; OR(adjusted), 1.831; 95% CI, 1.100 to 3.047; respectively). Subjects with high-level MCSM (MCSM-H) status demonstrated a higher risk of CRC (OR(adjusted), 4.318; 95% CI, 1.529 to 12.197). Additionally, interactions between the high-level intake of fruit and CRH, WT1, and MCSM on CRC were statistically significant. CONCLUSIONS: The gene methylation status of blood leukocytes may be associated with CRC risk. MCSM-H of blood leukocytes was associated with CRC, especially in younger people. Some dietary factors may affect hypermethylation status and influence susceptibility to CRC.

[An allelotype study of primary and corresponding recurrent glioblastoma multiforme].

OBJECTIVE: To investigate molecular genetic alterations associated with primary and corresponding recurrent glioblastoma multiforme(GBM) and to identify which chromosomal regions of the whole genome may be involved in the recurrence of primary GBM. METHODS: A high-resolution allelotyping study of one patient's primary GBM and corresponding recurrent GBM was performed by PCR-based loss of heterozygosity(LOH) analysis with the use of 382 fluorescent dye-labeled polymorphic microsatellite markers covering all 22 autosomes. The mean genetic distance between two flanking markers is 10 cM. RESULTS: LOH at locus D9S157 on 9p21 and at loci D10S537, D10S185, D10S192, D10S597, D10S587, D10S217 on 10q21.3-26.3 was observed in the primary GBM. As for corresponding recurrent tumor, LOH was observed not only in expanded regions on 9p21 and 10q21.3-26.3 but also on multiple other chromosomal arms, including 1q, 7p,7q, 21q, 20p, 20q, 10p, 19p, 19q. CONCLUSION: Chromosome 9p and 10q may be involved in the development of this GBM. Although histopathological diagnoses of the primary and corresponding recurrent tumor are identical, the recurrence of GBM is characterized by an increased involvement of molecular genetic abnormalities and may be accompanied by inactivation of more tumor suppressor genes.

An allelotype study of primary and corresponding recurrent glioblastoma multiforme / 中华医学遗传学杂志

<p><b>OBJECTIVE</b>To investigate molecular genetic alterations associated with primary and corresponding recurrent glioblastoma multiforme(GBM) and to identify which chromosomal regions of the whole genome may be involved in the recurrence of primary GBM.</p><p><b>METHODS</b>A high-resolution allelotyping study of one patient's primary GBM and corresponding recurrent GBM was performed by PCR-based loss of heterozygosity(LOH) analysis with the use of 382 fluorescent dye-labeled polymorphic microsatellite markers covering all 22 autosomes. The mean genetic distance between two flanking markers is 10 cM.</p><p><b>RESULTS</b>LOH at locus D9S157 on 9p21 and at loci D10S537, D10S185, D10S192, D10S597, D10S587, D10S217 on 10q21.3-26.3 was observed in the primary GBM. As for corresponding recurrent tumor, LOH was observed not only in expanded regions on 9p21 and 10q21.3-26.3 but also on multiple other chromosomal arms, including 1q, 7p,7q, 21q, 20p, 20q, 10p, 19p, 19q.</p><p><b>CONCLUSION</b>Chromosome 9p and 10q may be involved in the development of this GBM. Although histopathological diagnoses of the primary and corresponding recurrent tumor are identical, the recurrence of GBM is characterized by an increased involvement of molecular genetic abnormalities and may be accompanied by inactivation of more tumor suppressor genes.</p>