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Background Use of χ-separation imaging can provide surrogates for iron and myelin that relate closely to abnormal changes in multiple sclerosis (MS) lesions. Purpose To evaluate the appearances of MS and neuromyelitis optica spectrum disorder (NMOSD) brain lesions on χ-separation maps and explore their diagnostic value in differentiating the two diseases in comparison with previously reported diagnostic criteria. Materials and Methods This prospective study included individuals with MS or NMOSD who underwent χ-separation imaging from October 2017 to October 2020. Positive (χ) and negative (χ) susceptibility were estimated separately by using local frequency shifts and calculating R2' (R2' = R2* - R2). R2 mapping was performed with a machine learning approach. For each lesion, presence of the central vein sign (CVS) and paramagnetic rim sign (PRS) and signal characteristics on χ and χ maps were assessed and compared. For each participant, the proportion of lesions with CVS, PRS, and hypodiamagnetism was calculated. Diagnostic performances were assessed using receiver operating characteristic (ROC) curve analysis. Results A total of 32 participants with MS (mean age, 34 years ± 10 [SD]; 25 women, seven men) and 15 with NMOSD (mean age, 52 years ± 17; 14 women, one man) were evaluated, with a total of 611 MS and 225 NMOSD brain lesions. On the χ maps, 80.2% (490 of 611) of MS lesions were categorized as hypodiamagnetic versus 13.8% (31 of 225) of NMOSD lesions ( < .001). Lesion appearances on the χ maps showed no evidence of a difference between the two diseases. In per-participant analysis, participants with MS showed a higher proportion of hypodiamagnetic lesions (83%; IQR, 72-93) than those with NMOSD (6%; IQR, 0-14; < .001). The proportion of hypodiamagnetic lesions achieved excellent diagnostic performance (area under the ROC curve, 0.96; 95% CI: 0.91, 1.00). Conclusion On χ-separation maps, multiple sclerosis (MS) lesions tend to be hypodiamagnetic, which can serve as an important hallmark to differentiate MS from neuromyelitis optica spectrum disorder. © RSNA, 2022
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http://dx.doi.org/10.1148/radiol.220941 | DOI Listing |
Mol Pharm
September 2025
Department of Nuclear Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Tissue factor (TF) has emerged as a promising target for the diagnosis and treatment of hepatocellular carcinoma (HCC). However, there is limited data available on TF-related PET imaging for longitudinal monitoring of the pathophysiological changes during HCC formation. Herein, we aimed to explore the TF-expression feature and compare a novel TF-targeted PET probe with F-FDG through longitudinal imaging in diethylnitrosamine (DEN)-induced rat HCC.
View Article and Find Full Text PDFNeurol Neuroimmunol Neuroinflamm
November 2025
Departments of Neurology and Ophthalmology, NYU Grossman School of Medicine, NY; and.
Background And Objectives: While reductions in optical coherence tomography (OCT) pRNFL and ganglion cell-inner plexiform layer thicknesses have been shown to be associated with brain atrophy in adult-onset MS (AOMS) cohorts, the relationship between OCT and brain MRI measures is less established in pediatric-onset MS (POMS). Our aim was to examine the associations of OCT measures with volumetric MRI in a cohort of patients with POMS to determine whether OCT measures reflect CNS neurodegeneration in this patient population, as is seen in AOMS cohorts.
Methods: This was a cross-sectional study with retrospective ascertainment of patients with POMS evaluated at a single center with expertise in POMS and neuro-ophthalmology.
Emerg Top Life Sci
September 2025
Hurdle.bio / Chronomics Ltd., London, UK.
Artificial intelligence (AI) is transforming many fields, including healthcare and medicine. In biomarker discovery, AI algorithms have had a profound impact, thanks to their ability to derive insights from complex high-dimensional datasets and integrate multi-modal datatypes (such as omics, electronic health records, imaging or sensor and wearable data). However, despite the proliferation of AI-powered biomarkers, significant hurdles still remain in translating them to the clinic and driving adoption, including lack of population diversity, difficulties accessing harmonised data, costly and time-consuming clinical studies, evolving AI regulatory frameworks and absence of scalable diagnostic infrastructure.
View Article and Find Full Text PDFBlood Adv
September 2025
BC Cancer, Vancouver, British Columbia, Canada.
Classical Hodgkin Lymphoma (CHL) is characterized by a complex tumor microenvironment (TME) that supports disease progression. While immune cell recruitment by Hodgkin and Reed-Sternberg (HRS) cells is well-documented, the role of non-malignant B cells in relapse remains unclear. Using single-cell RNA sequencing (scRNA-seq) on paired diagnostic and relapsed CHL samples, we identified distinct shifts in B-cell populations, particularly an enrichment of naïve B cells and a reduction of memory B cells in early-relapse compared to late-relapse and newly diagnosed CHL.
View Article and Find Full Text PDFRetina
September 2025
Department of Ophthalmology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 15, CH-3010.
Purpose: To evaluate inter-grader variability in posterior vitreous detachment (PVD) classification in patients with epiretinal membrane (ERM) and macular hole (MH) on spectral-domain optical coherence tomography (SD-OCT) and identify challenges in defining a reliable ground truth for artificial intelligence (AI)-based tools.
Methods: A total of 437 horizontal SD-OCT B-scans were retrospectively selected and independently annotated by six experienced ophthalmologists adopting four categories: 'full PVD', 'partial PVD', 'no PVD', and 'ungradable'. Inter-grader agreement was assessed using pairwise Cohen's kappa scores.