Tumors of the clivus and metastases to the clivus are very rare. Metastasis involving the clivus has previously been described in only two case reports. In skull metastasis, the breast and prostate are the most common primary foci, while metastasis from gastric carcinoma is extremely rare. A review of the English literature revealed only one published case of clivus metastases from gastric adenocarcinoma. There is no literature thoroughly explaining the differential diagnosis between chordoma and metastasis. Here we report a rare case of metastasis to the clivus from a gastric adenocarcinoma in a 42-year-old female patient with sudden blurry vision, presenting as bilateral cranial nerve VI palsy.
The angiographic spot sign (AS) on CT angiography (CTA) is known to be useful for predicting expansion in intracranial hemorrhage, but its use is limited due to its relatively low sensitivity. Recently, dual-energy computed tomography (DECT) has been shown to be superior in distinguishing between hemorrhage and iodine. This study aimed to evaluate the diagnostic performance of hematoma expansion (HE) using DECT AS in traumatic intracranial hemorrhage.We recruited participants with intracranial hemorrhage confirmed via CTA for suspected traumatic cerebrovascular injuries. We evaluated AS on both conventional-like and fusion images of DECT. AS is grouped into three categories: intralesional enhancement without change, delayed enhancement (DE), and growing contrast leakage (GL). HE was evaluated by measuring hematoma size on DECT and follow-up CT. Logistic regression analysis was used to evaluate whether AS on fusion images was a significant risk factor for HE. Diagnostic accuracy was calculated, and the results from conventional-like and fusion images were compared.Thirty-nine hematomas in 24 patients were included in this study. Of these, 18 hematomas in 13 patients showed expansion on follow-up CT. Among the expanders, AS and GL on fusion images were noted in 13 and 5 hematomas, respectively. In non-expanders, 10 and 1 hematoma showed AS and GL, respectively. In the logistic regression model, GL on the fusion image was a significant independent risk factor for predicting HE. However, when AS was used on conventional-like images, no factors significantly predicted HE. In the receiver operating characteristic curve analysis, the area under the curve of AS on the fusion images was 0.71, with a sensitivity and specificity of 66.7% and 76.2%, respectively.GL on fusion images of DECT in traumatic intracranial hemorrhage is a significant independent radiologic risk factor for predicting HE. The AS of DECT fusion images has improved sensitivity compared to that of conventional-like images.
Adsorption of per- and poly-fluoroalkyl substances (PFAS) on activated carbon (AC) is considerably hindered by the surface water constituents, degrading the ability of the AC adsorption process to remove PFAS in drinking water treatment. Herein, we developed ionic-liquid-impregnated AC (IL/AC) as an alternative to AC for PFAS sorption and demonstrated its performance with real surface water for the first time. Ionic liquids (ILs) of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (IL(C2)) and 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (IL(C6)) were selected from among 272 different ILs using COSMO-RS simulation. Impregnation of the ILs in AC was verified using various analytical techniques. Although the synthesized IL/ACs were less effective than pristine AC in treating PFAS in deionized water, their performances were less impacted by the surface water constituents, resulting in comparable or sometimes better performances than pristine AC for treating PFAS in surface water. The removal efficiencies of 10 wt% IL(C6)/AC for six PFAS were 1.40 to 1.96 times higher than those of pristine AC in a surface water sample containing 2.6 mg/L dissolved organic carbon and millimolar-level divalent cation concentration. PFAS partitioning from the surface water to ILs was not hindered by dissolved organic matter and was enhanced by the divalent cations, indicating the advantages of IL/ACs for treating significant amounts of PFAS in water. The synthesized IL/ACs were effective at treating coexisting pharmaceutical and personal-care products in surface water, showcasing their versatility for treating a broad range of water micropollutants.
Despite advances in deep learning for estimating brain age from structural MRI data, incorporating functional MRI data is challenging due to its complex structure and the noisy nature of functional connectivity measurements. To address this, we present the Multitask Adversarial Variational Autoencoder, a custom deep learning framework designed to improve brain age predictions through multimodal MRI data integration. This model separates latent variables into generic and unique codes, isolating shared and modality-specific features. By integrating multitask learning with sex classification as an additional task, the model captures sex-specific aging patterns. Evaluated on the OpenBHB dataset, a large multisite brain MRI collection, the model achieves a mean absolute error of 2.77 years, outperforming traditional methods. This success positions M-AVAE as a powerful tool for metaverse-based healthcare applications in brain age estimation.
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