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Background: Prostate cancer invades the capsule is a key factor in selecting appropriate treatment methods. Accurate preoperative prediction of extraprostatic extension (EPE) can help achieve precise selection of treatment plans. Purpose: The aim of this study is to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), and Amide proton transfer (APT) value in predicting EPE. Additionally, the study aims to investigate the potential additional value of APT for predicting EPE. Method: This study include 47 tumor organ confined patients (age, 64.16 ± 9.18) and 50 EPE patients (age, 61.51 ± 8.82). The difference of tumor size, LCC, ADC and APT value between groups were compared. Binary logistic regression was used to screen the EPE predictors. The receiver operator characteristic curve analysis was performed to assess the diagnostic performance of variables for predicting EPE. The diagnostic efficacy of combined models (model I: ADC+LCC+tumor size; model II: APT+LCC +tumor size; and model III: APT +ADC+LCC+tumor size) were also analyzed. Results: APT, ADC, tumor size and the LCC were independent predictors of EPE. The area under the curve (AUC) of APT, ADC, tumor size and the LCC were 0.752, 0.665, 0.700 and 0.756, respectively. The AUC of model I, model II, and model III were 0.803, 0.845 and 0.869, respectively. The cutoff value of APT, ADC, tumor size and the LCC were 3.65%, 0.97×10−3mm2/s, 17.30mm and 10.78mm, respectively. The sensitivity/specificity of APT, ADC, tumor size and the LCC were 76%/89.4.0%, 80%/59.6%, 54%/78.9%, 72%/66%, respectively. The sensitivity/specificity of model I, Model II and Model III were 74%/72.3%, 82%/72.5% and 84%/80.9%, respectively. Data conclusion: Amide proton transfer imaging has added value for predicting EPE. The combination model of APT balanced the sensitivity and specificity. [ABSTRACT FROM AUTHOR]

Background: Delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) is a severe complication that can arise from acute carbon monoxide poisoning (ACOP). This study aims to identify the independent risk factors associated with DEACMP and to develop a nomogram to predict the probability of developing DEACMP. Methods: The data of patients diagnosed with ACOP between September 2015 and June 2021 were analyzed retrospectively. The patients were divided into the two groups: the DEACMP group and the non-DEACMP group. Univariate analysis and multivariate logistic regression analysis were conducted to identify the independent risk factors for DEACMP. Subsequently, a nomogram was constructed to predict the probability of DEACMP. Results: The study included 122 patients, out of whom 30 (24.6%) developed DEACMP. The multivariate logistic regression analysis revealed that acute high-signal lesions on diffusion-weighted imaging (DWI), duration of carbon monoxide (CO) exposure, and Glasgow Coma Scale (GCS) score were independent risk factors for DEACMP (Odds Ratio = 6.230, 1.323, 0.714, p < 0.05). Based on these indicators, a predictive nomogram was constructed. Conclusions: This study constructed a nomogram for predicting DEACMP using high-signal lesions on DWI and clinical indicators. The nomogram may serve as a dependable tool to differentiate high-risk patients and enable the provision of personalized treatment to lower the incidence of DEACMP. [ABSTRACT FROM AUTHOR]

Objective: To investigate the correlations between quantitative diffusion parameters and prognostic factors and molecular subtypes of breast cancer, based on a single fast high-resolution diffusion-weighted imaging (DWI) sequence with mono-exponential (Mono), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) models. Materials and Methods: A total of 143 patients with histopathologically verified breast cancer were included in this retrospective study. The multi-model DWIderived parameters were quantitatively measured, including Mono-ADC, IVIM-D, IVIM-D*, IVIM-f, DKI-Dapp, and DKI-Kapp. In addition, the morphologic characteristics of the lesions (shape, margin, and internal signal characteristics) were visually assessed on DWI images. Next, Kolmogorov-Smirnov test, Mann-Whitney U test, Spearman's rank correlation, logistic regression, receiver operating characteristic (ROC) curve, and Chi-squared test were utilized for statistical evaluations. Results: The histogram metrics of Mono-ADC, IVIM-D, DKI-Dapp, and DKI-Kapp were significantly different between estrogen receptor (ER)-positive vs. ERnegative groups, progesterone receptor (PR)-positive vs. PR-negative groups, Luminal vs. non-Luminal subtypes, and human epidermal receptor factor-2 (HER2)-positive vs. non-HER2-positive subtypes. The histogram metrics of Mono-ADC, DKI-Dapp, and DKI-Kapp were also significantly different between triple-negative (TN) vs. non-TN subtypes. The ROC analysis revealed that the area under the curve considerably improved when the three diffusion models were combined compared with every single model, except for distinguishing lymph node metastasis (LNM) status. For the morphologic characteristics of the tumor, the margin showed substantial differences between ER-positive and ERnegative groups. Conclusions: Quantitative multi-model analysis of DWI showed improved diagnostic performance for determining the prognostic factors and molecular subtypes of breast lesions. The morphologic characteristics obtained from highresolution DWI can be identifying ER statuses of breast cancer. [ABSTRACT FROM AUTHOR]

We previously reported a phenotype of Creutzfeldt-Jakob disease (CJD), CJD-MMiK, that could help identify iatrogenic CJD. To find cases mimicking CJD-MMiK, we investigated clinical features and pathology of 1,155 patients with diagnosed sporadic CJD or unclassified CJD with and without history of neurosurgery. Patients with history of neurosurgery more frequently had an absence of periodic sharp-wave complexes on electroencephalogram than patients without a history of neurosurgery. Among 27 patients with history of neurosurgery, 5 had no periodic sharp-wave complexes on electroencephalogram. We confirmed 1 case of CJD-MMiK and suspected another. Both had methionine homozygosity at codon 129 of the prion protein gene and hyperintensity lesions in the thalamus on magnetic resonance images of the brain, which might be a clinical marker of CJD-MMiK. A subgroup with a history of neurosurgery and clinical features mimicking dura mater graft-associated CJD might have been infected during neurosurgery and had symptoms develop after many years.

Introduction: Magnetic resonance imaging (MRI) currently accompanies clinical findings in disease diagnosis, patients' follow-up, assessment of drugs complications, and evaluation of treatment response. Although contrast-enhanced MRI (CE-MRI) is considered as the imaging modality of choice for multiple sclerosis (MS), due to disease chronicity, applying multiple doses of gadolinium-based contrast agents (GBCAs) increases the risk of nephrogenic syndrome in patients with acute (ARF) and chronic renal syndromes (CRF). Moreover, the effect of gadolinium on the fetus is not well-known in pregnant patients. Therefore, this study evaluates the possibility of replacing postcontrast images with physiologically based MRI sequences such as diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC). Method: We prospectively evaluated 26 patients with known multiple sclerosis. The patients with MS attacks and the asymptomatic patients who were referred for follow-up were enrolled. Conventional MRI including postcontrast T1W, DWI, and ADC were performed for all patients. The signal intensity (SI) of all enhancing and nonenhancing plaques of more than 10 × 10 mm size were investigated in all sequences and analyzed. Results: A total of 83 plaques were detected in T2-FLAIR sequences of which 51 plaques were enhanced (68%) after gadolinium administration. While 42 MS plaques had hypersignal intensity in DWI (56%), 32 plaques had iso- or hyposignal intensities in DWI (44%). No statistically significant values were obtained. Conclusion: Although DWI could not replace CE-MRI, using these two modalities together could increase detection of active MS plaques and alter patients' therapy and prognosis.

Osteosarcoma is a primary malignant bone tumor in children and adolescents with significant morbidity and poor prognosis. Diffusion weighted imaging (DWI) plays a crucial role in diagnosis and prognosis of this malignant disease by capturing cellular changes in tumor tissue early in the course of treatment without any contrast injection. Segmentation of tumor in DWI is challenging due to low signal-to-noise ratio, partial-volume effects, intensity inhomogeneities and irregular shape of osteosarcoma. The purpose of this study was to segment osteosarcoma solely utilizing DWI and identify effective and robust technique(s) for tumor segmentation. DWI dataset of fifty-five (N = 55; male:female = 41:14; Age = 17.8 ± 7.4 years) patients with osteosarcoma was acquired before treatment. Total nine automated and semi-automated segmentation algorithms based on (1) Otsu thresholding (OT), (2) Otsu threshold-based region growing (OT-RG), (3) Active contour (AC), (4) Simple linear iterative clustering Superpixels (SLIC-S), (5) Fuzzy c-means clustering (FCM), (6) Graph cut (GC), (7) Logistic regression (LR) (8) Linear support vector machines (L-SVM) and (9) Deep feed-forward neural network (DNN) were implemented. Segmentation accuracy was estimated by Dice coefficient (DC), Jaccard Index (JI), precision (P) and recall (R) using manually demarcated ground-truth tumor mask by a radiologist. Evaluated apparent diffusion coefficient (ADC) in segmented tumor mask and ground-truth tumor mask was compared using paired t test for statistical significance (p < 0.05) and Pearson correlation coefficient (PCC). Automated SLIC-S and FCM showed quantitatively and qualitatively superior segmentation with DC: ~ 79–82%; JI: ~ 67–71%; P: ~ 81–83%; R: ~ 80–86% and PCC = 0.89, 0.88 among all methods. Among semi-automated methods, AC was quantitatively more accurate (DC: ~ 77%; JI: ~ 65%; P: ~ 72%; R: ~ 88%; PCC = 0.85) than OT-RG and GC (DC: ~ 74–75%; JI: ~ 60–61%; P: ~ 67–72%; R: ~ 84–89%; PCC = 0.78, 0.73). Among machine learning algorithms, DNN showed the highest accuracy (DC: ~ 73%; JI: ~ 62%; P: ~ 77%; R: ~ 86%; PCC = 0.79) than LR and L-SVM (DC: ~ 70–71%; JI: ~ 58–63%; P: ~ 73%; R: ~ 74–85%; PCC = 0.69, 0.71). Execution times were instantaneous for SLIC-S, FCM and machine learning methods, while OT-RG, AC and GC took comparable ~ 1–6 s/slice image. Automated SLIC-S, FCM and semi-automated AC methods produced promising tumor segmentation results using DWI of the osteosarcoma dataset. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer invades the capsule is a key factor in selecting appropriate treatment methods. Accurate preoperative prediction of extraprostatic extension (EPE) can help achieve precise selection of treatment plans., Purpose: The aim of this study is to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), and Amide proton transfer (APT) value in predicting EPE. Additionally, the study aims to investigate the potential additional value of APT for predicting EPE., Method: This study include 47 tumor organ confined patients (age, 64.16 ± 9.18) and 50 EPE patients (age, 61.51 ± 8.82). The difference of tumor size, LCC, ADC and APT value between groups were compared. Binary logistic regression was used to screen the EPE predictors. The receiver operator characteristic curve analysis was performed to assess the diagnostic performance of variables for predicting EPE. The diagnostic efficacy of combined models (model I: ADC+LCC+tumor size; model II: APT+LCC+tumor size; and model III: APT +ADC+LCC+tumor size) were also analyzed., Results: APT, ADC, tumor size and the LCC were independent predictors of EPE. The area under the curve (AUC) of APT, ADC, tumor size and the LCC were 0.752, 0.665, 0.700 and 0.756, respectively. The AUC of model I, model II, and model III were 0.803, 0.845 and 0.869, respectively. The cutoff value of APT, ADC, tumor size and the LCC were 3.65%, 0.97×10-3mm2/s, 17.30mm and 10.78mm, respectively. The sensitivity/specificity of APT, ADC, tumor size and the LCC were 76%/89.4.0%, 80%/59.6%, 54%/78.9%, 72%/66%, respectively. The sensitivity/specificity of model I, Model II and Model III were 74%/72.3%, 82%/72.5% and 84%/80.9%, respectively., Data Conclusion: Amide proton transfer imaging has added value for predicting EPE. The combination model of APT balanced the sensitivity and specificity., Competing Interests: KD is employed by Philips China Investment Co., Ltd., Guangzhou Branch. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Qin, Lv, Zhang, Mu, Zheng, Liu, Huang, Li, Yang, Deng and Zhu.)

Introduction: Magnetic resonance imaging (MRI) currently accompanies clinical findings in disease diagnosis, patients' follow-up, assessment of drugs complications, and evaluation of treatment response. Although contrast-enhanced MRI (CE-MRI) is considered as the imaging modality of choice for multiple sclerosis (MS), due to disease chronicity, applying multiple doses of gadolinium-based contrast agents (GBCAs) increases the risk of nephrogenic syndrome in patients with acute (ARF) and chronic renal syndromes (CRF). Moreover, the effect of gadolinium on the fetus is not well-known in pregnant patients. Therefore, this study evaluates the possibility of replacing postcontrast images with physiologically based MRI sequences such as diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC). Method: We prospectively evaluated 26 patients with known multiple sclerosis. The patients with MS attacks and the asymptomatic patients who were referred for follow-up were enrolled. Conventional MRI including postcontrast T1W, DWI, and ADC were performed for all patients. The signal intensity (SI) of all enhancing and nonenhancing plaques of more than 10 × 10 mm size were investigated in all sequences and analyzed. Results: A total of 83 plaques were detected in T2-FLAIR sequences of which 51 plaques were enhanced (68%) after gadolinium administration. While 42 MS plaques had hypersignal intensity in DWI (56%), 32 plaques had iso- or hyposignal intensities in DWI (44%). No statistically significant values were obtained. Conclusion: Although DWI could not replace CE-MRI, using these two modalities together could increase detection of active MS plaques and alter patients' therapy and prognosis. [ABSTRACT FROM AUTHOR]

Background: Delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) is a severe complication that can arise from acute carbon monoxide poisoning (ACOP). This study aims to identify the independent risk factors associated with DEACMP and to develop a nomogram to predict the probability of developing DEACMP., Methods: The data of patients diagnosed with ACOP between September 2015 and June 2021 were analyzed retrospectively. The patients were divided into the two groups: the DEACMP group and the non-DEACMP group. Univariate analysis and multivariate logistic regression analysis were conducted to identify the independent risk factors for DEACMP. Subsequently, a nomogram was constructed to predict the probability of DEACMP., Results: The study included 122 patients, out of whom 30 (24.6%) developed DEACMP. The multivariate logistic regression analysis revealed that acute high-signal lesions on diffusion-weighted imaging (DWI), duration of carbon monoxide (CO) exposure, and Glasgow Coma Scale (GCS) score were independent risk factors for DEACMP (Odds Ratio = 6.230, 1.323, 0.714, p < 0.05). Based on these indicators, a predictive nomogram was constructed., Conclusions: This study constructed a nomogram for predicting DEACMP using high-signal lesions on DWI and clinical indicators. The nomogram may serve as a dependable tool to differentiate high-risk patients and enable the provision of personalized treatment to lower the incidence of DEACMP., Competing Interests: The authors declare no conflict of interest., (© 2023 The Author(s). Published by IMR Press.)

Background: Spinal angiolipomas (SAL) are rare benign tumors, commonly presenting with slow progressive spinal cord compression. There are only about 170 cases identified so far. Magnetic resonance imaging (MRI) has become the modality of choice for SAL. The purpose of this article is to report three cases of SAL and their characteristic MRI features. Case presentation: Three cases of epidual spinal angiolipoma from ethnic Han Chinese patients are presented here, including one lumbar and two thoracic tumors. MRI imaging findings were reviewed. Conclusions: Multiple MRI technology for characterization of SAL provides useful information for differential diagnosis and therapeutic management. [ABSTRACT FROM AUTHOR]

Background: The underlying causes of minor stroke are difficult to assess. Here, we evaluate the reliability of the Chinese Ischemic Stroke Subclassification (CISS) system in patients with minor stroke, and compare it to the Trial of Org 10172 in Acute Stroke Treatment (TOAST) system.Methods: A total of 320 patients with minor stroke were retrospectively registered and categorized into different subgroups of the CISS and TOAST by two neurologists. Inter- and intra-rater agreement with the two systems were assessed with kappa statistics.Results: The percentage of undetermined etiology (UE) cases in the CISS system was 77.3 % less than that in the TOAST system, which was statistically significant (P < 0.001). The percentage of large artery atherosclerosis (LAA) in the CISS system was 79.7 % more than that in the TOAST system, which was also statistically significant (P < 0.001). The kappa values for inter-examiner agreement were 0.898 (P = 0.031) and 0.732 (P = 0.022) for the CISS and TOAST systems, respectively. The intra-observer reliability indexes were moderate (0.569 for neurologist A, and 0.487 for neurologist B).Conclusions: The CISS and TOAST systems are both reliable in classifying patients with minor stroke. CISS classified more patients into known etiologic categories without sacrificing reliability. [ABSTRACT FROM AUTHOR]

Objective: To investigate the correlations between quantitative diffusion parameters and prognostic factors and molecular subtypes of breast cancer, based on a single fast high-resolution diffusion-weighted imaging (DWI) sequence with mono-exponential (Mono), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) models., Materials and Methods: A total of 143 patients with histopathologically verified breast cancer were included in this retrospective study. The multi-model DWI-derived parameters were quantitatively measured, including Mono-ADC, IVIM- D , IVIM- D* , IVIM- f , DKI-Dapp, and DKI-Kapp. In addition, the morphologic characteristics of the lesions (shape, margin, and internal signal characteristics) were visually assessed on DWI images. Next, Kolmogorov-Smirnov test, Mann-Whitney U test, Spearman's rank correlation, logistic regression, receiver operating characteristic (ROC) curve, and Chi-squared test were utilized for statistical evaluations., Results: The histogram metrics of Mono-ADC, IVIM- D , DKI-Dapp, and DKI-Kapp were significantly different between estrogen receptor (ER)-positive vs . ER-negative groups, progesterone receptor (PR)-positive vs . PR-negative groups, Luminal vs . non-Luminal subtypes, and human epidermal receptor factor-2 (HER2)-positive vs . non-HER2-positive subtypes. The histogram metrics of Mono-ADC, DKI-Dapp, and DKI-Kapp were also significantly different between triple-negative (TN) vs . non-TN subtypes. The ROC analysis revealed that the area under the curve considerably improved when the three diffusion models were combined compared with every single model, except for distinguishing lymph node metastasis (LNM) status. For the morphologic characteristics of the tumor, the margin showed substantial differences between ER-positive and ER-negative groups., Conclusions: Quantitative multi-model analysis of DWI showed improved diagnostic performance for determining the prognostic factors and molecular subtypes of breast lesions. The morphologic characteristics obtained from high-resolution DWI can be identifying ER statuses of breast cancer., Competing Interests: Authors HZ and TY were employed by the company Siemens Healthineers Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Qin, Wu, Hu, He, Huo, Tang, Yi, Zhang, Yin and Ai.)

Very preterm children are at a high risk for neurodevelopmental impairments, but there is variability in the pattern and severity of outcome. Neonatal magnetic resonance imaging (MRI) enhances the capacity to detect brain injury and altered brain development and assists in the prediction of high-risk children who warrant surveillance and early intervention. This review describes the application of conventional and advanced MRI with very preterm neonates, specifically focusing on the relationship between neonatal MRI findings and later neurodevelopmental outcome. Research demonstrates that conventional MRI is strongly associated with neurodevelopmental outcome in childhood. Further studies are needed to examine the role of advanced MRI techniques in predicting outcome in very preterm children, but early research findings are promising. In conclusion, neonatal MRI is predictive of later neurodevelopment but is dependent on appropriately trained specialists and should be interpreted in conjunction with other clinical and social information. [ABSTRACT FROM AUTHOR]

Abstract: We describe a girl with sepsis-associated encephalopathy complicating biliary atresia. At 4 months of age, decreased consciousness and repetitive seizures of the left upper and lower extremities occurred in association with fever. Pseudomonas aeruginosa was cultured from blood, while bacterial culture was negative and cell counts were normal in cerebrospinal fluid. The interleukin-6 level in the cerebrospinal fluid was markedly elevated. MRI revealed unilateral subcortical white matter lesions in the right hemisphere. She was diagnosed as having sepsis-associated encephalopathy and was treated with dexamethasone and midazolam. She achieved normal psychomotor development until the last follow-up at 19 months of age, whereas mild atrophic changes were observed in the right hemisphere. [Copyright &y& Elsevier]

• Ablation volumes were comparable between patients with good and poor outcome. • ADC of preoperative mesial temporal regions was comparable between two cohorts. • ADC within ablated regions were higher for patients with good seizure control. Magnetic resonance-guided laser interstitial thermal therapy (MRgLiTT) is becoming a first-line surgical therapy for mesial temporal lobe epilepsy (mTLE) due to good seizure control and low complication risk. However, seizure outcomes after MRgLiTT remain highly variable and there is a need to improve patient selection and post-operative prognostication. In this retrospective study, we investigated whether the pre-operative MRI-derived apparent diffusion coefficient (ADC), used as a marker of tissue pathology in the mesial temporal structures could help predict seizure outcome. Thirty-five patients who underwent MRgLiTT at our institution between 2014 and 2019 were included in the study. Demographic and clinical data were retrospectively collected. Seizure outcome was defined as good (ILAE Class I-II) and poor (ILAE Class III-VI). Volumetrics were performed on pre-ablation hippocampus and amygdala. Ablation volumes, and the proportion of ablated hippocampus and amygdala calculated via their respective mean voxel-wise ADC intensities were quantified from pre-operative and intra-operative post-ablation MRIs and statistically compared between the two outcome cohorts. Univarate and multivariate regression analysis was performed to identify demographic, clinical, and radiographic predictors of seizure outcome. Mean age at LiTT was 36 years and 14 (40 %) were female. Mean follow-up duration was 1.90 ± 0.17 years. Twenty-seven (77 %) patients had mesial temporal sclerosis. There was no significant difference in the ablation volumes and proportion of ablated volume of hippocampus and amygdala between the two outcome groups. Patients with good seizure outcome had significantly higher normalized ADC intensities in the ablated mesial temporal structures compared to those with poor outcome (0.01 ± 0.08 vs.−0.29 ± 0.06; p = 0.015). mTLE patients with higher ADC intensities in the ablated regions of the hippocampus and the amygdala are more likely to have good seizure outcome following MRgLiTT. Our results suggest that pre-operative ADC analysis may improve both patient selection and epileptogenic zone targeting during MRgLiTT. Further investigation with large, prospective cohorts is needed to validate the clinical utility of ADC in improving seizure outcome following MRgLiTT. [ABSTRACT FROM AUTHOR]

Background: Liver fibrosis (LF) is a common pathological feature of all chronic liver diseases. With the accumulation of extracellular matrix in the fibrotic liver, true molecular water diffusion and perfusion-related diffusion are restricted. Intravoxel incoherent motion (IVIM) can capture the information on tissue diffusivity and microcapillary perfusion separately and reflect the fibrotic severity with diffusion coefficients., Aim: To investigate the diagnostic performance of IVIM in detecting and staging LF with histology as a reference standard., Methods: A comprehensive literature search was conducted to identify studies on the diagnostic accuracy of IVIM for assessment of histologically proven LF. The stages of LF were classified as F0 (no fibrosis), F1 (portal fibrosis without septa), F2 (periportal fibrosis with few septa), F3 (septal fibrosis), and F4 (cirrhosis) according to histopathological findings. Data were extracted to calculate the pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio, as well as the area under the summary receiver operating characteristic curve (AUC) in each group., Results: A total of 12 studies with 923 subjects were included in this meta-analysis with 5 studies ( n = 465) for LF ≥ F1, 9 studies ( n = 757) for LF ≥ F2, 4 studies ( n = 413) for LF ≥ F3, and 6 studies ( n = 562) for LF = F4. The pooled sensitivity and specificity were estimated to be 0.78 (95% confidence interval: 0.73-0.82) and 0.81 (0.74-0.86) for LF ≥ F1 detection with IVIM; 0.82 (0.79-0.86) and 0.80 (0.75-0.84) for staging F2 fibrosis; 0.85 (0.79-0.90) and 0.83 (0.77-0.87) for staging F3 fibrosis, and 0.90 (0.84-0.94) and 0.75 (0.70-0.79) for detecting F4 cirrhosis, respectively. The AUCs for LF ≥ F1, F2, F3, F4 detection were 0.862 (0.811-0.914), 0.883 (0.856-0.909), 0.886 (0.865-0.907), and 0.899 (0.866-0.932), respectively. Moderate to substantial heterogeneity was observed with inconsistency index ( I 2 ) ranging from 0% to 77.9%. No publication bias was detected., Conclusion: IVIM is a noninvasive tool with good diagnostic performance in detecting and staging LF. Optimized and standardized IVIM protocols are needed to further improve its diagnostic accuracy in clinical practice., Competing Interests: Conflict-of-interest statement: The authors have no conflicts of interest to declare., (©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background: Spinal angiolipomas (SAL) are rare benign tumors, commonly presenting with slow progressive spinal cord compression. There are only about 170 cases identified so far. Magnetic resonance imaging (MRI) has become the modality of choice for SAL. The purpose of this article is to report three cases of SAL and their characteristic MRI features., Case Presentation: Three cases of epidual spinal angiolipoma from ethnic Han Chinese patients are presented here, including one lumbar and two thoracic tumors. MRI imaging findings were reviewed., Conclusions: Multiple MRI technology for characterization of SAL provides useful information for differential diagnosis and therapeutic management.

Background: The underlying causes of minor stroke are difficult to assess. Here, we evaluate the reliability of the Chinese Ischemic Stroke Subclassification (CISS) system in patients with minor stroke, and compare it to the Trial of Org 10172 in Acute Stroke Treatment (TOAST) system., Methods: A total of 320 patients with minor stroke were retrospectively registered and categorized into different subgroups of the CISS and TOAST by two neurologists. Inter- and intra-rater agreement with the two systems were assessed with kappa statistics., Results: The percentage of undetermined etiology (UE) cases in the CISS system was 77.3 % less than that in the TOAST system, which was statistically significant (P < 0.001). The percentage of large artery atherosclerosis (LAA) in the CISS system was 79.7 % more than that in the TOAST system, which was also statistically significant (P < 0.001). The kappa values for inter-examiner agreement were 0.898 (P = 0.031) and 0.732 (P = 0.022) for the CISS and TOAST systems, respectively. The intra-observer reliability indexes were moderate (0.569 for neurologist A, and 0.487 for neurologist B)., Conclusions: The CISS and TOAST systems are both reliable in classifying patients with minor stroke. CISS classified more patients into known etiologic categories without sacrificing reliability.