Pulmonary hypertension (PH) is a progressive disorder characterized by abnormally elevated blood pressure of the pulmonary circulation. PH progresses rapidly to right ventricular (RV) failure and even death without treatment. Cardiac magnetic resonance (CMR) is an accurate and reproducible tool for the assessment of RV morphology and function, which plays an important role in the prognosis of patients with PH. The aim of this study is to review the clinical application and research progress of CMR in evaluation of PH.

According to the sera aquaporin-4 antibody (AQP4), neuromyelitis optica (NMO) can be classified into two types as AQP4 antibody positive (AQP4+) and negative (AQP4-). However, the NMO patients with AQP4- are prone to delayed treatment, and may have a different pathogenesis compared to that in patients with AQP4+. Scientific researches and the clinical trials on NMO with AQP4- will deepen the understanding of NMO pathogenesis and help to make an early accurate diagnosis and rational therapy for NMO with AQP4-. This review aims to summarize the progress in clinic diagnosis for NMO patients with AQP4-.

Objective To investigate the application value of 3D arterial spin labeling (ASL) perfusion imaging for patients with unilateral carotid stenosis or occlusion.Methods Cervical MRA and cerebral 3D ASL were performed on 36 consecutive patients with unilateral carotid stenosis diagnosed by digital subtraction angiography (DSA).The consistency of degree of stenosis between cervical MRA and DSA was analyzed.36 patients were divided into mild,moderate and severe groups by degree of stenosis,which was based on the DSA result.Variance analysis of cerebral blood flow (CBF) unilateral and contralateral changes were performed on three different groups.Patients with severe stenosis,diagnosed by DSA,were divided into symptomatic group and asymptomatic group.Analysis was carried out on unilateral and contralateral change differences between symptomatic group and asymptomatic group.Results There was no statistical significance between MRA and DSA in the cervical artery stenosis degree (kappa＞ 0.75,P＜0.05).There was no statistical difference in CBF unilateral and contralateral changes between mild group and moderate group (P＞0.01).There was statistical difference in CBF unilateral and contralateral changes between severe group and other two groups (P＜0.01).There was statistical difference in CBF unilateral and contralateral changes between symptomatic group and asymptomatic group (P＜0.01).Conclusion 3D ASL as a safe,non-invasive,repeatable method,are meaningful for cerebral hemodynamics evaluation in patients with unilateral carotid stenosis.

Objective To analyze quantitatively the multiple parameters of iterative Dixon water-fat separation with echo asymmetric and least-squares estimation (IDEAL) MR imaging sequence, in order to realize safe, noninvasive and accurate observation of intervertebral disc degeneration, and to predict early degeneration in time, improve image quality, and to realize precision medical treatment by providing personalized examinations and optimized imaging protocols.Methods A total of 40 volunteers, 23 males and 17 females, with 20-84 years of age (mean (53.4±16.5) years), were participated in our study to accept lumbar spine MRI examination, including sequences of OSAG T2 FSE, OSAG T1 FSE, OAX T2 FSE, OSAG T2 FSE FS and OSAG IDEAL T2.Lumbar intervertebral disc degeneration was evaluated by Pfirrmann classification.The water signal fraction (WSF) of each disc was measured and calculated accurately with IDEAL in phase and IDEAL out phase images.The differences between Pfirrmann grade and WSF were analyzed statistically.The signal-to-noise ratio (SNR) measurements were carried out on equal size region of interest (ROI) from the same levels of vertebral body (L3) and background zone of T2 FSE FS and T2 IDEAL water image mid-sagittal planes, respectively, and the average value of vertebral body signal strength and the standard deviation of background signal were measured.SNRs of the two sequences were calculated, and the image qualities were compared statistically.Results Of all 200 lumbar discs that measured using Pfirrmann classification, 39 discs were classified as Pfirrmann grade Ⅰ, 42 as grade Ⅱ, 27 as grade Ⅲ, 53 as grade Ⅳ, and 39 as grade Ⅴ.The SNR of T2 FSE FS images was (11.42±6.17) dB, while that of the IDEAL water images was (20.63±9.44) dB, and there was a statistically significant difference between them (P＜0.05).The WSF decreased along with the increase of Pfirrmann grade.The significant differences of WSF were found in all grades (P＜0.05) except for the grade Ⅳ and Ⅴ (P＞0.05).Conclusions The SNR of the IDEAL water images is significantly higher than that of T2 FSE FS images, which bring about better image quality.The WSF calculated based on the IDEAL in phase and IDEAL out phase images will make possible the quantitative, noninvasive and accurate analysis of lumbar disc degeneration, especially on the early stage of disc degeneration.

Objective:To evaluate the value of curative effect in neuromyelitis spectrum disease (NMOSD) based on circulatory function evaluation of intracerebral glymphatic system by using diffusion tensor imaging analysis along the perivascular space.Methods:The clinical and imaging data of 23 patients diagnosed with NMOSD at Tianjin Medical University General Hospital from March 2018 to December 2019 were retrospectively analyzed in this study. The clinical data included expanded disability status scale (EDSS), average relapse rate (ARR) and retinal nerve fiber layer (RNFL) thickness at baseline and 1 year follow-up after treatment. Among the 23 NMOSD patients, there were 22 females and 1 male, aged from 21 to 71 (45±13) years old. All the patients underwent MR scans at both baseline and 1 year after treatment, and the scanning sequences included cerebral 3D-T 1WI, T 2WI, diffusion tensor imaging and cervical spinal sagittal 3D-T 2WI, and the cervical spinal cord volume and bilateral diffusion tensor imaging analysis along the perivascular space index (ALPS index) were calculated. The partial correlation test was used to analyze the correlations between ALPS index and the clinical indicators such as EDSS, ARR, and bilateral RNFL, with the control variables as gender, age, years of education and course of disease. The multiple linear regression model was used to analyze the independent predictors for ALPS index and EDSS after treatment. Receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to evaluate the diagnostic value of NMOSD treatment outcome by using ALPS index. Results:When controlling for gender, age, years of education and course of disease, there were significant negative correlations between right ALPS index and EDSS ( r=-0.50, P=0.048), bilateral average ALPS index and EDSS ( r=-0.53, P=0.034), left ALPS index and ARR ( r=-0.58, P=0.018), while there was significant positive correlations between right ALPS index and RNFL ( r=0.88, P=0.008) at 1 year follow-up after treatment. Multiple linear regression analysis showed that cervical spinal cord volume was an independent impact factor of bilateral average ALPS indexes (β=0.24, 95%CI 0.10-0.38, P=0.002), and bilateral average ALPS indexes (β=-3.22, 95%CI -5.97--0.48, P=0.024) and right RNFL (β=-0.05, 95%CI -0.08--0.02, P=0.002) at baseline were the independent impact factors of EDSS after treatment. ROC curve analysis showed that the bilateral average ALPS index at baseline had the best efficacy in predicting the curative effect of NMOSD patients with AUC=0.92. Conclusions:After treatment, NMOSD patients with severe clinical disability, high frequency of disease attack, poor visual performance, and severe cervical spinal cord atrophy have more serious impairment of intracerebral glymphatic system circulatory function. The ALPS index could help in predicting the clinical curative effect of NMOSD patients.

Objective:To investigate the efficacy of a machine learning model based on radiomics of brain lesions on T 2WI in differentiating multiple sclerosis (MS) from neuromyelitis optica spectrum disorders (NMOSD). Methods:Totally 223 MS and NMOSD patients who were treated from January 2009 to September 2018 in Beijing Tiantan Hospital Affiliated to Capital Medical University, Donghu Branch of the First Affiliated Hospital of Nanchang University, Tianjin Medical University General Hospital, and Xuanwu Hospital of Capital Medical University were analyzed retrospectively, and according to the proportion of 7∶3, 223 patients were completely randomly divided into training set (156 cases) and test set (67 cases). A total of 74 patients with MS and NMOSD who were treated in Huashan Hospital Affiliated to Fudan University and China-Japan Friendship Hospital of Jilin University from January 2009 to September 2018 and in Xianghu Branch of the First Affiliated Hospital of Nanchang University from March 2020 to September 2021 were collected as an independent external validation set. All patients underwent brain cross-sectional MR T 2WI, radiomics features were extracted from T 2WI, and features were selected by max-relevance and min-redundancy and least absolute shrinkage and selection operator algorithms. Then various machine learning classifier models (logistic regression, decision tree, AdaBoost, random forest or support vector machine) were constructed to differentiate MS from NMOSD. The area under curve (AUC) of receiver operating characteristics was used to evaluate the performance of each classifier model in the training set, test set and external validation set. Results:Based on multi-center T 2WI, a total of 11 radiomics features related to the discrimination between MS and NMOSD were extracted and classifier models were constructed. Among them, the random forest model had the best efficiency in distinguishing MS from NMOSD, and its AUC values for distinguishing MS from NMOSD in the training set, test set and external validation set were 1.000, 0.944 and 0.902, with specificity of 100%, 76.9% and 86.0%, and sensitivity of 100%, 92.1% and 79.7%, respectively. Conclusion:The random forest model based on the radiomic features of T 2WI of brain lesions can effectively distinguish MS from NMOSD.