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Accurate processing and analysis of non-human primate (NHP) brain magnetic resonance imaging (MRI) serves an indispensable role in understanding brain evolution, development, aging, and diseases. Despite the accumulation of diverse NHP brain MRI datasets at various developmental stages and from various imaging sites/scanners, existing computational tools designed for human MRI typically perform poor on NHP data, due to huge differences in brain sizes, morphologies, and imaging appearances across species, sites, and ages, highlighting the imperative for NHP-specialized MRI processing tools. To address this issue, in this paper, we present a robust, generic, and fully automated computational pipeline, called non-human primates Brain Extraction and Segmentation Toolbox (nBEST), whose main functionality includes brain extraction, non-cerebrum removal, and tissue segmentation. Building on cutting-edge deep learning techniques by employing lifelong learning to flexibly integrate data from diverse NHP populations and innovatively constructing 3D U-NeXt architecture, nBEST can well handle structural NHP brain MR images from multi-species, multi-site, and multi-developmental-stage (from neonates to the elderly). We extensively validated nBEST based on, to our knowledge, the largest assemblage dataset in NHP brain studies, encompassing 1,469 scans with 11 species (e.g., rhesus macaques, cynomolgus macaques, chimpanzees, marmosets, squirrel monkeys, etc.) from 23 independent datasets. Compared to alternative tools, nBEST outperforms in precision, applicability, robustness, comprehensiveness, and generalizability, greatly benefiting downstream longitudinal, cross-sectional, and cross-species quantitative analyses. We have made nBEST an open-source toolbox (https://github.com/TaoZhong11/nBEST) and we are committed to its continual refinement through lifelong learning with incoming data to greatly contribute to the research field., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: Visibility of deep medullary veins (DMVs) seen at SWI is predictive of poor prognosis in ischemic stroke. Few attentions have been paid to DMVs in atherosclerotic cerebral small vessel disease (aCSVD) which is attributed to long-term imbalanced microhemodynamics. We conducted this retrospective study to explore the association between DMVs profiles and aCSVD risk factors, neuroimaging markers., Methods: Two hundred and two patients identified as aCSVD from January 2017 to March 2019 were included in the study. Their demographic, clinical, laboratory, and neuroimaging data were reviewed. The quantity and morphology of DMVs were assessed with a 5-grade (range 0~4) visual rating scale. Total CSVD burden was calculated with an ordinal "SVD score" (range 0~4). Spearman rank correlation and multivariable logistic regression analysis were performed to determine the association between DMV scale and CSVD markers., Results: DMV scale showed strong positive correlation with CSVD burden (r s  = 0.629, P < 0.001). Age (OR 1.078, 95% CI 1.015-1.145, P = 0.015) and hypertension (OR 2.629, 95% CI 1.024-6.749, P = 0.045) were two demographic risk factors for high DMV scale. Among CSVD neuroimaging markers, periventricular WMH (OR 2.925, 95% CI 1.464-5.845, P = 0.002), deep WMH (OR 2.872, 95% CI 1.174-7.022, P = 0.021), lacunae (OR 1.961, 95% CI 1.181-3.254, P = 0.009), and cerebral atrophy (OR 2.046, 95% CI 1.079-3.880, P = 0.028) were associated with high DMV scale after adjusting for clinical and metabolic confounders., Conclusion: Multifactorial association between DMV scale and epidemiological, radiological contributors of aCSVD suggests DMV's involved pathomechanism may participate in aCSVD development. Attach importance to DMV radiological profile in aCSVD will provide more neuroimaging information for diagnosis and prognosis.

Purpose: The features of intracranial arterial injury in tuberculous meningitis (TBM) are of important diagnostic and prognostic value. The study aimed to elucidate the high-resolution vessel wall imaging (HR-VWI) manifestations of intracranial arterial insults in TBM., Methods: The clinical data, routine cranial magnetic resonance imaging, magnetic resonance angiography (MRA) and HR-VWI before and after contrast enhancement of intracranial arteries in clinically diagnosed TBM patients were retrospectively analyzed., Results: In this study 27 TBM patients were included. Abnormalities in the intracranial arteries were detected in all patients using HR-VWI. Typical vessel insults included nodular or granular lesions, related thickness and prominent enhancement in the wall, and lumen narrowing or occlusion. The most frequently involved arteries were the C4 segment of the internal carotid artery and the P1 segment of the posterior cerebral artery. The lesions were consistent with disease stage and disease duration and correlated with infarction., Conclusion: The use of HR-VWI revealed that cerebral artery involvement in patients with TBM is much more common and extensive than in previous radiological reports. The use of HR-VWI improves recognition of arterial pathologies and has diagnostic value in patients with TBM.

Interstitial brachytherapy (IBT) is often utilized to treat women with bulky endometrial or cervical cancers not amendable to intracavitary treatments. A modern trend in IBT is the utilization of magnetic resonance imaging (MRI) with a high dose rate (HDR) afterloader for conformal 3D image-based treatments. The challenging part of this procedure is to properly complete many sequenced and co-related physics preparations. We presented the physics preparations and clinical workflow required for implementing MRI-based HDR IBT (MRI-HDR-IBT) of gynecologic cancer patients in a high-volume brachytherapy center. The present document is designed to focus on the clinical steps required from a physicist's standpoint. Those steps include: (a) testing IBT equipment with MRI scanner, (b) preparation of templates and catheters, (c) preparation of MRI line markers, (d) acquisition, importation and registration of MRI images, (e) development of treatment plans and (f) treatment evaluation and documentation. The checklists of imaging acquisition, registration and plan development are also presented. Based on the TG-100 recommendations, a workflow chart, a fault tree analysis and an error-solution table listing the speculated errors and solutions of each step are provided. Our workflow and practice indicated the MRI-HDR-IBT is achievable in most radiation oncology clinics if the following equipment is available: MRI scanner, CT (computed tomography) scanner, MRI/CT compatible templates and applicators, MRI line markers, HDR afterloader and a brachytherapy treatment planning system capable of utilizing MRI images. The OR/procedure room availability and anesthesiology support are also important. The techniques and approaches adopted from the GEC-ESTRO (Groupe Européen de Curiethérapie - European Society for Therapeutic Radiology and Oncology) recommendations and other publications are proven to be feasible. The MRI-HDR-IBT program can be developed over time and progressively validated through clinical experience, this document is expected to serve as a reference workflow guideline for implementing and performing the procedure., (© 2019 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Background Aims: Assessing mesenchymal stromal cells (MSCs) after grafting is essential for understanding their migration and differentiation processes. The present study sought to evaluate via cellular magnetic resonance imaging (MRI) if transplantation route may have an effect on MSCs engrafting to fibrotic liver of rats., Methods: Rat MSCs were prepared, labeled with superparamagnetic iron oxide and scanned with MRI. Labeled MSCs were transplanted via the portal vein or vena caudalis to rats with hepatic fibrosis. MRI was performed in vitro before and after transplantation. Histologic examination was performed. MRI scan and imaging parameter optimization in vitro and migration under in vivo conditions were demonstrated., Results: Strong MRI susceptibility effects could be found on gradient echo-weighted, or T2∗-weighted, imaging sequences from 24 h after labeling to passage 4 of labeled MSCs in vitro. In vivo, MRI findings of the portal vein group indicated lower signal in liver on single shot fast spin echo-weighted, or T2-weighted, imaging and T2∗-weighted imaging sequences. The low liver MRI signal increased gradually from 0-3 h and decreased gradually from 3 h to 14 days post-transplantation. The distribution pattern of labeled MSCs in liver histologic sections was identical to that of MRI signal. It was difficult to find MSCs in tissues near the portal area on day 14 after transplantation; labeled MSCs appeared in fibrous tuberculum at the edge of the liver. No MRI signal change and a positive histologic examination were observed in the vena caudalis group., Conclusions: The portal vein route seemed to be more beneficial than the vena caudalis on MSC migration to fibrotic liver of rats via MRI., (Copyright © 2013 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.)

Background: Brain stem lesions are common in patients with acute disseminated encephalomyelitis (ADEM), neuromyelitis optica (NMO), and multiple sclerosis (MS)., Objectives: To investigate comparative brain stem lesions on magnetic resonance imaging (MRI) among adult patients with ADEM, NMO, and MS., Methods: Sixty-five adult patients with ADEM (n = 17), NMO (n = 23), and MS (n = 25) who had brain stem lesions on MRI were enrolled. Morphological features of brain stem lesions among these diseases were assessed., Results: Patients with ADEM had a higher frequency of midbrain lesions than did patients with NMO (94.1% vs. 17.4%, P<0.001) and MS (94.1% vs. 40.0%, P<0.001); patients with NMO had a lower frequency of pons lesions than did patients with MS (34.8% vs. 84.0%, P<0.001) and ADEM (34.8% vs. 70.6%, P = 0.025); and patients with NMO had a higher frequency of medulla oblongata lesions than did patients with ADEM (91.3% vs. 35.3%, P<0.001) and MS (91.3% vs. 36.0%, P<0.001). On the axial section of the brain stem, the majority (82.4%) of patients with ADEM showed lesions on the ventral part; the brain stem lesions in patients with NMO were typically located in the dorsal part (91.3%); and lesions in patients with MS were found in both the ventral (44.0%) and dorsal (56.0%) parts. The lesions in patients with ADEM (100%) and NMO (91.3%) had poorly defined margins, while lesions of patients with MS (76.0%) had well defined margins. Brain stem lesions in patients with ADEM were usually bilateral and symmetrical (82.4%), while lesions in patients with NMO (87.0%) and MS (92.0%) were asymmetrical or unilateral., Conclusions: Brain stem lesions showed various morphological features among adult patients with ADEM, NMO, and MS. The different lesion locations may be helpful in distinguishing these diseases.

Objective: To investigate the value of 3D FIESTA sequence in magnetic resonance sialography (MRS) in the diagnosis of obstructive salivary diseases., Methods: Eleven patients with obstructive salivary diseases underwent MRS, and three-dimensional (3D) reconstruction and virtual endoscopic images of the salivary gland ducts were obtained after MRS data post-processing for comparison with those of sialoendoscopy., Results: The diagnostic accuracy of MRS was 72.7% for obstructive salivary diseases. The virtual endoscopy provided a visual field highly consistent with that by sialoendoscopy., Conclusion: MRS is capable of visualizing the tracts of salivary glands. MR virtual endoscopy can provide sufficient morphological and pathological data for preoperative assessment of salivary operations with sialoendoscopy.

Objective: To explore the method of displaying the bone and joint structures transfixed with stainless steel lag screws using magnetic resonance imaging (MRI), 2 patients whose knee joints (and ankle joint in one case) were transfixed with stainless steel underwent MRI with FSE-XL pulse sequence. The images clearly displayed the bones, ligaments and articular cartilage around the stainless steel materials, demonstrating the efficacy of FSE-XL pulse sequence in evaluation of the anatomical features of the bones and joints transfixed with stainless steel materials.

Objectives: The objectives of this study were to investigate the feasibility of clinical application of magnetic resonance (MR) virtual endoscopy as a presurgical procedure before sialoendoscopy and to evaluate its value in the diagnosis of obstructive salivary gland diseases and preoperative visualization of endoluminal views., Study Design: This study presents our initial experience to use MR virtual endoscopy for the presurgical visualization of salivary duct lumen and ductal pathologies in comparison to the sialoendoscopy findings in a feasibility study., Methods: Six consecutive patients with suspected obstructive salivary gland diseases underwent MR sialography with a three-dimensional fast imaging using steady-state acquisition. The three-dimensional MR data were transferred to an independent workstation and were postprocessed with navigator software to generate three-dimensional reconstruction and virtual endoscopic images. The fly-through mode was used to imitate the sialoendoscopic exploratory procedure. Then the patients underwent sialoendoscopy and the endoscopic findings were compared with the preoperative virtual endoscopic images., Results: The MR data acquisition and postprocessing protocol were feasible. The virtual endoscopy created clear endoluminal views of salivary duct and the ductal pathologies. The diagnoses were all confirmed by surgical sialoendoscopy. The virtual endoscopic images showed close resemblance to the sialoendoscopic findings., Conclusions: MR virtual endoscopy is an effective and noninvasive diagnostic method for evaluating the endoluminal anatomy and pathologies of the salivary duct. The clinical application of MR virtual endoscopy as a presurgical procedure before sialoendoscopy is a valuable and promising approach, which can provide surgeons useful morphologic and pathologic information.

Background: Systemic cardiac hypoperfusion is a well-acknowledged contributor to ischemic leukoencephalopathy. However, it has remained elusive how atherosclerosis-mediated cardiac remodelling modifies cerebral perfusion homeostasis as well as neuroimaging burden in cerebral small vessel disease (CSVD) development.Methods: This retrospective study identified 103 arteriosclerotic CSVD (aCSVD) patients (CSVD burdenlow 0 ~ 1, n = 61 and CSVD burdenhigh 2 ~ 4, n = 42) from Sep. 2017 to Dec. 2019 who underwent transthoracic echocardiography(n = 81), structural magnetic resonance imaging and arterial spin labelling (ASL). Total CSVD burden was graded according to the ordinal "small vessel disease" rating score (0-4). We investigated the univariate and multivariate linear regression of mean deep regional cerebral blood flow (CBF) as well as logistic regression analysis of CSVD burdenhigh.Results: Right atrial diameter (B coefficient, - 0.289; 95% CI, - 0.578 to - 0.001; P = 0.049) and left ventricular ejection fraction (B coefficient, 32.555; 95% CI, 7.399 to 57.711; P = 0.012) were independently associated with deep regional CBF in aCSVD patients. Binary logistic regression analysis demonstrated decreased deep regional CBF (OR 0.894; 95% CI 0.811-0.985; P = 0.024) was independently associated with higher CSVD burden after adjusted for clinical confounders. Multivariate receiver operating characteristics curve integrating clinical risk factors, mean deep CBF and echocardiographic parameters showed predictive significance for CSVD burdenhigh diagnosis (area under curve = 84.25, 95% CI 74.86-93.65%, P < 0.0001).Conclusion: The interrelationship of "cardiac -deep regional CBF-neuroimaging burden" reinforces the importance and prognostic significance of echocardiographic and cerebral hemodynamic assessment in CSVD early-warning. [ABSTRACT FROM AUTHOR]

This study aimed to identify neural biomarkers for schizophrenia (SZ) and bipolar disorder (BP) by analyzing multimodal neuroimaging. Utilizing data from structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (rs-fMRI), multiclass classification models were created for SZ, BP, and healthy controls (HC). A total of 113 participants (BP: 31, SZ: 39, and HC: 43) were recruited under strict enrollment control, from which 272, 200, and 1875 features were extracted from sMRI, DTI, and rs-fMRI data, respectively. A support vector machine (SVM) with recursive feature elimination (RFE) was employed to build the models using a one-against-one approach and leave-one-out cross-validation, achieving a classification accuracy of 70.8%. The most discriminative features were primarily from rs-fMRI, along with significant findings in sMRI and DTI. Key biomarkers identified included the increased thickness of the left cuneus cortex and decreased regional functional connectivity strength (rFCS) in the left supramarginal gyrus as shared indicators for BP and SZ. Additionally, decreased fractional anisotropy in the left superior fronto-occipital fasciculus was suggested as specific to BP, while decreased rFCS in the left inferior parietal area might serve as a specific biomarker for SZ. These findings underscore the potential of multimodal neuroimaging in distinguishing between BP and SZ and contribute to the understanding of their neural underpinnings. [ABSTRACT FROM AUTHOR]

Purpose: Perforating Artery Infarcts (PAIs) can be divided into two subtypes based on their etiologies: branch Atheromatous Disease (BAD) and Lacunar Infarct (LI). Recent studies have shown that while both subtypes can be caused by large artery lesions, the different mechanisms that underlie their development are not clear. This study was designed to use High-Resolution Magnetic Resonance Imaging (HRMRI) to explore the differences that contribute to the occurrence of these two subtypes in large artery lesions in the anterior circulation. Methods: Fifty patients with an acute PAI in the anterior circulation were enrolled (32 BAD and 18 LI patients). The ipsilateral middle cerebral artery (MCA) was scanned with HRMRI to analyze the atherosclerosis plaques. Artery remodeling and plaque characteristics of MCA lesions were compared between the two subtypes. Results: The rate of MCA lesions was significantly higher in BAD and substantially lower in LI (P = 0.033). LAs for the lumen areas in Bad, they were smaller than LI (P < 0.001), Additionally, the plaque area (P = 0.001) and plaque burden (P < 0.001) were superior in the BAD group. Most BAD patients displayed non-positive remodeling, while the great majority of LI patients showed positive remodeling (P < 0.001). Conclusion: In the anterior circulation, a considerable amount of BAD and LI share similarities with atherosclerotic plaques in large arteries. BAD patients mainly showed relatively large and stable atherosclerotic plaques in large arteries, while LI patients mainly exhibited relatively small and unstable atherosclerotic plaques. Clinical Trial Registration: This clinical trial is a retrospective study and therefore does not require registration. [ABSTRACT FROM AUTHOR]

Background There are few studies about the Liver Imaging Reporting and Data System (LI-RADS), which was developed with the purpose of standardizing the interpretation and reporting of liver imaging examinations in patients at risk for hepatocellular carcinoma (HCC). Purpose To evaluate the diagnostic accuracy of HCC diagnosis using LI-RADS. Material and Methods The computed tomography (CT), magnetic resonance imaging (MRI), and clinical data of 297 lesions in 249 patients between June 2012 and August 2013 were retrospectively analyzed. Using LI-RADS 2014, two radiologists evaluated the lesions and a LI-RADS category was retrospectively assigned to each nodule. Results The final diagnoses of 297 nodules in 249 patients consisted of 191 malignant and 106 benign lesions. Out of 44 LI-RADS category 1 lesions, none were HCCs. However, 2/25 category 2 lesions, 3/35 category 3 lesions, 16/25 category 4 lesions, 151/156 category 5 lesions, and 3/12 category LRM/OM (probable malignancy, not specific for HCC/other malignancy) lesions were HCCs. The Kappa value was 0.44 (95% confidence interval [CI] = 0.39-0.49) between two observers during LI-RADS grading. Conclusion The negative predictive value of LI-RADS category 1 was 100%. In addition, a relevant proportion of lesions categorized as category 2 or 3, or even as other malignancies, were HCCs. LI-RADS category 5 had a high specificity for HCC. LI-RADS was not able to give a differential diagnosis for the false-positive lesions of LI-RADS category 5. [ABSTRACT FROM AUTHOR]

Abstract: Background: ZNF804A gene polymorphism rs1344706, the first genetic risk variant to achieve genome wide significance for schizophrenia, has been linked to neural functional connectivity. Dysconnectivity of WM may be the primary pathological mechanism of schizophrenia. Association of this variant with regional WM density has not been investigated in schizophrenic patients. Methods: 69 healthy controls and 80 patients with schizophrenia underwent genotyping of rs1344706 SNPs, and were examined for WM density (T1-weighted MRI). The association of rs1344706 with WM changes in schizophrenia patients and healthy controls was analyzed using a full-factorial 2×2 analysis of variance. Results: 1. There was an interaction on WM density in the left prefrontal lobe between the rs1344706 genotype and schizophrenic diagnosis, where the risk T allele carriers presented higher WM density in the schizophrenia patients and lower WM density in healthy controls in comparison with the non-risk allele carriers. 2. The risk allele was associated with an increased WM density of the bilateral hippocampus in both the patients and the healthy group. Limitation: The influence of antipsychotics to the white matter in schizophrenic patients was not fully eliminated. Conclusions: The ZNF804A variant may confer risk for schizophrenia by exerting its effects on the WM in the left prefrontal lobe together with other risk factors for schizophrenia. [Copyright &y& Elsevier]

Abstract: Schizophrenia is thought to arise in part from abnormal gray matter (GM), which are partly shared by the relatives of the probands. DISC1 is one of the most promising susceptibility genes of schizophrenia and a SNP rs821597 (A) in the gene was associated with schizophrenia in Han Chinese population. In this study, 61 healthy controls and 72 with schizophrenic patients were genotyped at rs821597, and underwent T1-weighted MRI for the density of GM. The results showed that the risk allele (A) carriers had higher GM density in regional left parahippocampal gyrus and right orbitofrontal cortex in schizophrenic patients, but had reduced GM density of these brain regions in healthy controls. The DISC1 variant rs821597 may confer risk for schizophrenia by its effects on the regional GM in left parahippocampal gyrus and right orbitofrontal cortex with other risk factors for schizophrenia. [Copyright &y& Elsevier]

Abstract: Purpose: Our aim was to study the quantitative fiber tractography variations and patterns in patients with relapsing–remitting multiple sclerosis (RRMS) and to assess the correlation between quantitative fiber tractography and Expanded Disability Status Scale (EDSS). Material and methods: Twenty-eight patients with RRMS and 28 age-matched healthy volunteers underwent a diffusion tensor MR imaging study. Quantitative deterministic and probabilistic fiber tractography were generated in all subjects. And mean numbers of tracked lines and fiber density were counted. Paired-samples t tests were used to compare tracked lines and fiber density in RRMS patients with those in controls. Bivariate linear regression model was used to determine the relationship between quantitative fiber tractography and EDSS in RRMS. Results: Both deterministic and probabilistic tractography''s tracked lines and fiber density in RRMS patients were less than those in controls (P <.001). Both deterministic and probabilistic tractography''s tracked lines and fiber density were found negative correlations with EDSS in RRMS (P <.001). The fiber tract disruptions and reductions in RRMS were directly visualized on fiber tractography. Conclusion: Changes of white matter tracts can be detected by quantitative diffusion tensor fiber tractography, and correlate with clinical impairment in RRMS. [Copyright &y& Elsevier]

• We present a novel method of reusing ground-truth information to improve the performance of detecting cerebral microbleeds by using the SSD algorithm. • The ground-truth information is using to stabilize the feature in forwarding propagation of the convolution network. • Compared with baseline results, using the feature enhancement achieve more effective results. • This method is flexible to be integrated into other object detecting methods. Cerebral microbleeds (CMBs) are cerebral small vascular diseases and are often used to diagnose symptoms such as stroke and dementia. Manual detection of cerebral microbleeds is a time-consuming and error-prone task, so the application of microbleed detection algorithms based on deep learning is of great significance. This study presents the feature enhancement technology applying to improve the performances of detecting CMBs. The primary purpose of the feature enhancement is emphasizing the meaningful features, leading deep learning network easier and correctly to optimize. In this study, we applied feature enhancement in detecting CMBs from brain MRI images. Feature enhancement enhanced specific intervals and suppressed the useless intervals of the feature map. This method was applied in SSD-512 and SSD-300 algorithm, using VGG architecture pre-trained in the ImageNet dataset. The proposed method was applied in SSD-512. Moreover, the model was trained and tested on the sequence of SWAN images of brain MRI images. The results of the experiment demonstrate that our method effectively improves the detection performance of the SSD network in detecting CMBs. We train SSD-512 120000 iterations and test results on the test datasets, by applying the feature enhancement layer, improving the precision with 3.3% and the mAP of 2.3%. In the same way, we trained SSD-300, improving the mAP of 2.0%. 2.8% and 7.4% precision are improved by applying feature enhancement layer In ResNet-34 and MobileNet. The proposed method achieved more effective performance, demonstrated that feature enhancement can be a helpful algorithm to enhance the deep learning model. [ABSTRACT FROM AUTHOR]