The cerebral glymphatic system, particularly the Virchow-Robin Spaces (VRS), plays an important role in waste clearance from the brain. Idiopathic generalized epilepsy (IGE) is a common epilepsy type associated with blood-brain-barrier dysfunction, abnormal exchange of cerebrospinal fluid and interstitial fluid. These disorders may be reflected in the glymphatic system. Therefore, this study investigated the relationships between visible VRS on MRI and seizures, to detect changes in glymphatic function. Methods: We retrospectively included 32 children with newly diagnosed IGE and 30 controls aged 3-13 years. Visible VRS were identified using a custom-designed automated method. VRS counts and volume were quantified and compared between children with IGE and controls. Meanwhile, Correlations of VRS counts and volume with seizure duration and course after seizure onset were respectively explored via Spearman's coefficient (r). Results: In this study, visible VRS counts were higher in IGE than control group (VRS _epilepsy , 234.34 ± 113.88 vs. VRS _control , 111.83 ± 52.46; P < 0.001), as similar results were found in VRS volume (VRS _epilepsy , 1377.47 ± 778.79 mm 3 vs. VRS _control , 795.153 ± 452.49 mm 3 ; P = 0.001). Visible VRS counts and volume positively correlated with seizure duration (r _counts = 0.638, r _volume = 0.639; P < 0.001) and gradually decreased with time after seizure onset (r _counts = −0.559, r_ volume = −0.558; P < 0.001). Conclusion: Epileptic seizures can induce changes in VRS counts and volume, which were associated with seizure duration and post-onset course. Quantitative metrics of VRS visible on MRI might be potential biomarkers for monitoring glymphatic function.

Background: Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs.Methods: Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λ HU ), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT 40keV ), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements.Results: Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λ HU , and CT 40keV performed better in the VP (NIC VP , λ VPHU , and CT VP40keV ) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NIC VP , λ VPHU , and CT VP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NIC AP (AUC =0.89) were greater than other parameters. NIC AP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility.Conclusions: Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.

Osteosarcoma, as the most common primary bone cancer, is difficult to make a differentiation between tumor with contrast agents (CAs) accumulation and healthy bones using X‐ray computed tomography (CT) since they both display high attenuation of X‐ray. Recently, an advanced CT form, gemstone spectral CT (GSCT), has received extensive attention due to its significant ability of material decomposition and monochromatic images, which can overcome the above disadvantages of conventional CT. Herein, the lutecium (Lu)‐based upconversion nanoparticles (UCNPs, polyethylene glycol (PEG)–NaLuF4:Yb/Er), which possess great spectral CT performance over clinical used iohexol, is investigated as a novel kind of spectral CT CAs in the diagnosis of osteosarcoma. Both in vitro and in vivo experiments show that Lu‐based UCNPs provided much more diagnostic interpretation, and can successfully distinguish the osteosarcoma from the surround bones with GSCT while the iohexol fails due to the different X‐ray attenuation characteristics of UCNPs (i.e., lutecium) and iohexol (e.g., iodine) under different energy. As a proof of concept, the Lu‐based UCNPs with excellent biocompatibility hold great potential for further clinical diagnosis of skeletal system diseases.

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