CT-Based Radiomics Models for Differentiation of Benign and Malignant Thyroid Nodules: A Multicenter Development and Validation Study.

BACKGROUND. CT is increasingly detecting thyroid nodules. Prior studies indicated a potential role of CT-based radiomics models in characterizing thyroid nodules, although these studies lacked external validation. OBJECTIVE. The purpose of this study was to develop and validate a CT-based radiomics model for the differentiation of benign and malignant thyroid nodules. METHODS. This retrospective study included 378 patients (mean age, 46.3 ± 13.9 [SD] years; 86 men, 292 women) with 408 resected thyroid nodules (145 benign, 263 malignant) from two centers (center 1: 293 nodules, January 2018 to December 2022; center 2: 115 nodules, January 2020 to December 2022) who underwent preoperative multiphase neck CT (noncontrast, arterial, and venous phases). Nodules from center 1 were divided into training (n = 206) and internal validation (n = 87) sets; all nodules from center 2 formed an external validation set. Radiologists assessed nodules for morphologic CT features. Nodules were manually segmented on all phases, and radiomic features were extracted. Conventional (clinical and morphologic CT), noncontrast CT radiomics, arterial phase CT radiomics, venous phase CT radiomics, multiphase CT radiomics, and combined (clinical, morphologic CT, and multiphase CT radiomics) models were established using feature selection methods and evaluated by ROC curve analysis, calibration-curve analysis, and decision-curve analysis. RESULTS. The combined model included patient age, three morphologic features (cystic change, "edge interruption" sign, abnormal cervical lymph nodes), and 28 radiomic features (from all three phases). In the external validation set, the combined model had an AUC of 0.923, and, at an optimal threshold derived in the training set, sensitivity of 84.0%, specificity of 94.1%, and accuracy of 87.0%. In the external validation set, the AUC was significantly higher for the combined model than for the conventional model (0.827), noncontrast CT radiomics model (0.847), arterial phase CT radiomics model (0.826), venous phase CT radiomics model (0.773), and multiphase CT radiomics model (0.824) (all p < .05). In the external validation set, the calibration curves indicated the lowest (i.e., best) Brier score for the combined model; in the decision-curve analysis, the combined model had the highest net benefit for most of the range of threshold probabilities. CONCLUSION. A combined model incorporating clinical, morphologic CT, and multiphase CT radiomics features exhibited robust performance in differentiating benign and malignant thyroid nodules. CLINICAL IMPACT. The combined radiomics model may help guide further management for thyroid nodules detected on CT.

[Injectable hydrogel microspheres experimental research for the treatment of osteoarthritis].

Objective: To prepare a novel hyaluronic acid methacrylate (HAMA) hydrogel microspheres loaded polyhedral oligomeric silsesquioxane-diclofenac sodium (POSS-DS) patricles, then investigate its physicochemical characteristics and in vitro and in vivo biological properties. Methods: Using sulfhydryl POSS (POSS-SH) as a nano-construction platform, polyethylene glycol and DS were chemically linked through the "click chemistry" method to construct functional nanoparticle POSS-DS. The composition was analyzed by nuclear magnetic resonance spectroscopy and the morphology was characterized by transmission electron microscopy. In order to achieve drug sustained release, POSS-DS was encapsulated in HAMA, and hybrid hydrogel microspheres were prepared by microfluidic technology, namely HAMA@POSS-DS. The morphology of the hybrid hydrogel microspheres was characterized by optical microscope and scanning electron microscope. The in vitro degradation and drug release efficiency were observed. Cell counting kit 8 (CCK-8) and live/dead staining were used to detect the effect on chondrocyte proliferation. Moreover, a chondrocyte inflammation model was constructed and cultured with HAMA@POSS-DS. The relevant inflammatory indicators, including collagen type Ⅱ, aggrecan (AGG), matrix metalloproteinase 13 (MMP-13), recombinant A disintegrin and metalloproteinase with thrombospondin 5 (Adamts5), and recombinant tachykinin precursor 1 (TAC1) were detected by immunofluorescence staining and real-time fluorescence quantitative PCR, with normal cultured chondrocytes and the chondrocyte inflammation model without treatment as control group and blank group respectively to further evaluate their anti-inflammatory activity. Finally, by constructing a rat model of knee osteoarthritis, the effectiveness of HAMA@POSS-DS on osteoarthritis was evaluated by X-ray film and Micro-CT examination. Results: The overall particle size of POSS-DS nanoparticles was uniform with a diameter of about 100 nm. HAMA@POSS-DS hydrogel microspheres were opaque spheres with a diameter of about 100 µm and a spherical porous structure. The degradation period was 9 weeks, during which the loaded POSS-DS nanoparticles were slowly released. CCK-8 and live/dead staining showed no obvious cytotoxicity at HAMA@POSS-DS, and POSS-DS released by HAMA@POSS-DS significantly promoted cell proliferation (P<0.05). In the chondrocyte anti-inflammatory experiment, the relative expression of collagen type Ⅱ mRNA in HAMA@POSS-DS group was significantly higher than that in control group and blank group (P<0.05). The relative expression level of AGG mRNA was significantly higher than that of blank group (P<0.05). The relative expressions of MMP-13, Adamts5, and TAC1 mRNA in HAMA@POSS-DS group were significantly lower than those in blank group (P<0.05). In vivo experiments showed that the joint space width decreased after operation in rats with osteoarthritis, but HAMA@POSS-DS delayed the process of joint space narrowing and significantly improved the periarticular osteophytosis (P<0.05). Conclusion: HAMA@POSS-DS can effectively regulate the local inflammatory microenvironment and significantly promote chondrocyte proliferation, which is conducive to promoting cartilage regeneration and repair in osteoarthritis.

Visualizable and Lubricating Hydrogel Microspheres Via NanoPOSS for Cartilage Regeneration.

The monitoring of tissue regeneration is particularly important. However, most materials do not allow direct observation of the regeneration process in the cartilage layer. Here, using sulfhydryl polyhedral oligomeric silsesquioxane (POSS-SH) as a nano-construction platform, poly(ethylene glycol) (PEG), Kartogenin (KGN), hydrogenated soya phosphatidylcholine (HSPC), and fluorescein are linked through the "click chemistry" method to construct nanomaterial with fluorescence visualization for cartilage repair: POSS linked with PEG, KGN, HSPC, and fluorescein (PPKHF). PPKHF nanoparticles are encapsulated with hyaluronic acid methacryloyl to prepare PPKHF-loaded microfluidic hyaluronic acid methacrylate spheres (MHS@PPKHF) for in situ injection into the joint cavity using microfluidic technology. MHS@PPKHF forms a buffer lubricant layer in the joint space to reduce friction between articular cartilages, while releasing encapsulated positively charged PPKHF to the deep cartilage through electromagnetic force, facilitating visualization of the location of the drug via fluorescence. Moreover, PPKHF facilitates differentiation of bone marrow mesenchymal stem cells into chondrocytes, which are located in the subchondral bone. In animal experiment, the material accelerates cartilage regeneration while allowing monitoring of cartilage layer repair progression via fluorescence signals. Thus, these POSS-based micro-nano hydrogel microspheres can be used for cartilage regeneration and monitoring and potentially for clinical osteoarthritis therapy.

Prediction of histopathologic grades of myxofibrosarcoma with radiomics based on magnetic resonance imaging.

PURPOSE: To develop a radiomics-based model from preoperative magnetic resonance imaging (MRI) for predicting the histopathological grades of myxofibrosarcoma. METHODS: This retrospective study included 54 patients. The tumors were classified into high-grade and low-grade myxofibrosarcoma. The tumor size, signal intensity heterogeneity, margin, and surrounding tissue were evaluated on MRI. Using the least absolute shrinkage and selection operator (LASSO) algorithms, 1037 radiomics features were obtained from fat-suppressed T2-weighted images (T2WI), and a radiomics signature was established. Using multivariable logistic regression analysis, three models were built to predict the histopathologic grade of myxofibrosarcoma. A radiomics nomogram represents the integrative model. The three models' performance was evaluated using the receiver operating characteristics (ROC) and calibration curves. RESULTS: The high-grade myxofibrosarcoma had greater depth (P = 0.027), more frequent heterogeneous signal intensity at T2WI (P = 0.015), and tail sign (P = 0.014) than the low-grade tumor. The area under curve (AUC) of these conventional MRI features models was 0.648, 0.656, and 0.668, respectively. Seven radiomic features were selected by LASSO to construct the radiomics signature model, with an AUC of 0.791. The AUC of the integrative model based on radiomics signature and conventional MRI features was 0.875. The integrative model's calibration curve and insignificant Hosmer-Lemeshow test statistic (P = 0.606) revealed good calibration. CONCLUSION: An integrative model using radiomics signature and three conventional MRI features can preoperatively predict low- or high-grade myxofibrosarcoma.

Incidence, prognosis and nomograms of breast cancer with bone metastases at initial diagnosis: a large population-based study.

BACKGROUND: Bone is the most common metastatic site for breast cancer, and patients' condition will deteriorate when it occurs. METHODS: We performed a retrospective analysis on 6482 breast cancer patients with bone metastases (BCBM), who were selected from the Surveillance, Epidemiology, and End Result (SEER) 18 registry database. The optimal age cut-points were generated by using the X-tile software. By using Cox regression, we selected independent prognostic factors from 21 variables, and plotted a visual nomogram to predict the probability of surviving to the median survival time. We also diagrammed a competing risk nomogram on the basis of competitive risk model. RESULTS: Compared with other three common metastatic sites, the incidence of bone metastasis was the highest for patients with breast cancer. The incidence of BCBM peaked around the age of 60, and a large majority of patients were between the ages of 50 and 70. The survival rate decreased with age, and the median survival time was about 19 months. Factors of age, race, marital status, grade, human epidermal growth factor receptor-2 (HER2) receptor, hormone receptor, concurrent brain metastasis, concurrent liver metastasis, concurrent lung metastasis, surgery and chemotherapy are strongly related to the prognosis of patients with BCBM. It was revealed that the C-index of the nomogram was 0.72 and the calibration curves showed good agreement between the nomogram prediction and actual observation. CONCLUSION: Our practical nomograms provide a visual and user-friendly tool in the risk evaluation and prognostic prediction for breast cancer patients with bone metastases.

TCF7L2 and EGR1 synergistic activation of transcription of LCN2 via an ERK1/2-dependent pathway in esophageal squamous cell carcinoma cells.

High level expression of lipocalin 2 (LCN2) usually indicates poor prognosis in esophageal squamous cell carcinoma (ESCC) and many other cancers. Our previous study showed LCN2 promotes migration and invasion of ESCC cells through a novel positive feedback loop. However, the key transcription activation protein (KTAP) in the loop had not yet been identified. In this study, we first predicted the most probable KTAPs by bioinformatic analysis. We then assessed the transcription regulatory regions in the human LCN2 gene by fusing deletions of its 5'-flanking region to a dual-luciferase reporter. We found that the region -720/-200 containing transcription factor 7-like 2 (TCF7L2) (-273/-209) and early growth response 1 (EGR1) (-710/-616) binding sites is crucial for LCN2 promoter activity. Chromatin immunoprecipitation (ChIP) experiments demonstrated that TCF7L2 and EGR1 bound directly to their binding sites within the LCN2 promoter as KTAPs. Mechanistically, overexpression of TCF7L2 and EGR1 increased endogenous LCN2 expression via the ERK signaling pathway. Treatment with recombinant human LCN2 protein enhanced activation of the ERK pathway to facilitate endogenous LCN2 expression, as well as increase the expression level of TCF7L2 and EGR1. Treatment with the MEK inhibitor U0126 inhibited the activation by TCF7L2 or EGR1 overexpression. Moreover, overexpression of TCF7L2 or EGR1 accelerated the migration and invasion of ESCC cells. A synergistic effect was observed between TCF7L2 and EGR1 in amplifying the induction of LCN2 and enhancing migration and invasion. Taken together, our study indicates that TCF7L2 and EGR1 are the KTAPs of LCN2, within a positive "LCN2 → MEK/ERK → LCN2" path, to promote the migration and invasion of ESCC cells. Based on their clinicopathological significance, LCN2 and its two expression regulators TCF7L2 and ERG1 might be therapeutic targets for ESCC.

GRHL2 suppresses tumor metastasis via regulation of transcriptional activity of RhoG in non-small cell lung cancer.

The transcription factor, Grainyhead-like 2 (GRHL2), is involved in wound healing, epidermal integrity, and epithelial-to-mesenchymal transition (EMT) in various biological processes; however, the biological function of GRHL2 in non-small cell lung cancer (NSCLC) is unknown. In the current study, we investigated the effect of GRHL2 on cell growth and migration in NSCLC cell lines and clinical tissues. Immunohistochemical analysis of clinical NSCLC specimens revealed that patients with high GRHL2 expression were associated with poor prognosis compared to patients with low GRHL2 expression. GRHL2 overexpression promoted cell growth and colony formation, and simultaneously suppressed cell migration in NSCLC cells. Furthermore, GRHL2 decreased the transcriptional activity of RhoG by directly binding to the RhoG promoter region. These findings confirm that GRHL2 plays an important role in regulating cell proliferation and migration in NSCLC.