Radiomics is an emerging technique that allows the quantitative extraction of high-throughput features from single or multiple medical images, which cannot be observed directly with the naked eye, and then applies to machine learning approaches to construct classification or prediction models. This method makes it possible to evaluate tumor status and to differentiate malignant from benign tumors or nodules in a more objective manner. To date, the classification and prediction value of radiomics in DTC patients have been inconsistent. Herein, we summarize the available literature on the classification and prediction performance of radiomics-based DTC in various imaging techniques. More specifically, we reviewed the recent literature to discuss the capacity of radiomics to predict lymph node (LN) metastasis, distant metastasis, tumor extrathyroidal extension, disease-free survival, and B-Raf proto-oncogene serine/threonine kinase (BRAF) mutation and differentiate malignant from benign nodules. This review discusses the application and limitations of the radiomics process, and explores its ability to improve clinical decision-making with the hope of emphasizing its utility for DTC patients.

Lipoic acid (LA) is an endogenous antioxidant that exists widely in nature. Supplementation with LA is a promising approach to improve the outcomes of patients with multiple sclerosis (MS). This systematic review aimed to provide a comprehensive overview of both in vitro and in vivo studies describing the pharmacokinetics, efficacy, safety, and mechanism of LA in MS‐related experiments and clinical trials. A total of 516 records were identified by searching five databases, including PubMed, Web of Science, Embase, Scopus, and Cochrane Library. Overall, we included 20 studies reporting LA effects in cell and mouse models of MS and 12 studies reporting LA effects in patients with MS. Briefly, cell experiments revealed that LA protected neurons by inhibiting the expression of inflammatory mediators and activities of immune cells. Experimental autoimmune encephalomyelitis mouse experiments demonstrated that LA consistently reduced the number of infiltrating immune cells in the central nervous system and decreased the clinical disability scores. Patients with MS showed relatively stable Expanded Disability Status Scale scores and better walking performance with few adverse events after the oral administration of LA. Notably, heterogeneity of this evidence existed among modeling methods, LA usage, MS stage, and trial duration. In conclusion, this review provides evidence for the anti‐inflammatory and antioxidative effects of LA in both in vitro and in vivo experiments; therefore, patients with MS may benefit from LA administration. Whether LA can be a routine supplementary therapy warrants further study.

Background: 18-fluorodeoxyglucose positron emission tomography/computed tomography (F-18-PET/CT) has been widely applied for the imaging of head and neck squamous cell carcinoma (HNSCC). This study examined whether pre- and post-treatment F-18-PET/CT features can help predict the survival of HNSCC patients. Results: Three radiomics features were identified as prognostic factors. Radiomics score calculated from these features significantly predicted overall survival (OS) and disease-free disease (DFS). The clinicopathological characteristics combined with pre- or post-treatment nomograms showed better ROC curves and decision curves than the nomogram based only on clinicopathological characteristics. Conclusions: Combining clinicopathological characteristics with radiomics features of pre-treatment PET/CT or post-treatment PET/CT assessment of primary tumor sites as positive or negative may substantially improve prediction of OS and DFS of HNSCC patients. Methods: 171 patients who received pre-treatment F-18-PET/CT scans and 154 patients who received post-treatment F-18-PET/CT scans with HNSCC in the Cancer Imaging Achieve (TCIA) were included. Nomograms that combined clinicopathological features with either pre-treatment PET/CT radiomics features or post-treatment assessment of primary tumor sites were constructed using data from 154 HNSCC patients. Receiver operating characteristic (ROC) curves and decision curves were used to compare the predictions of these models with those of a model incorporating only clinicopathological features.

Central nervous sequelae are often reported in recovered patients with COVID-19. It is not clear whether recovered COVID-19 patients have glymphatic impairment and clinical correlation. In this study, we demonstrated that mild COVID-19 patients experienced asymmetric bilateral glymphatic function decline after four months of recovery, and the decrease in glymphatic function was more obvious in older recovered patients. Our results further showed that recovered patients with right-sided glymphatic dysfunction experienced a greater proportion of cognitive decline (MoCA score <26) than patients with left-sided glymphatic dysfunction. With COVID-19 infection over 90% of the general population currently, future studies of cognitive disorders in the older population should consider the impact of COVID-19 infection.