Antifibrotic therapy has changed the treatment paradigm for idiopathic pulmonary fibrosis (IPF); however, a subset of patients still experienced rapid disease progression despite treatment. This study aimed to determine whether CT-based radiomic features can predict therapeutic response to antifibrotic agents. In this retrospective study, 35 patients with IPF on antifibrotic treatment enrolled from two centers were divided into training (n = 26) and external validation (n = 9) sets. Clinical and pulmonary function data were collected. The patients were categorized into stable disease (SD) and progressive disease (PD) groups based on functional or radiologic criteria. From pretreatment non-enhanced high-resolution CT (HRCT) images, twenty-six radiomic features were extracted through whole-lung texture analysis, and six parenchymal patterns were quantified using dedicated imaging platforms. The predictive factors for PD were determined via univariate and multivariate logistic regression analyses. In the training set (SD/PD: 12/14), univariate analysis identified eight radiomic features and ground-glass opacity percentage (GGO%) as potential predicators of PD. However, multivariate analysis found that the single independent predictor was the sum entropy (accuracy, 80.77%; AUC, 0.75). The combined sum entropy-GGO% model improved the predictive performance in the training set (accuracy, 88.46%; AUC, 0.77). The overall accuracy of the combined model in the validation set (SD/PD: 7/2) was 66.67%. Our preliminary results demonstrated that radiomic features based on pretreatment HRCT could predict the response of patients with IPF to antifibrotic treatment.

Objective: Electrical impedance tomography (EIT) is a noninvasive imaging technology used to reconstruct the conductivity distribution in objects and the human body. Methods: In recent years, numerous EIT systems and image reconstruction algorithms have been developed. However, most of these EIT systems require conventional electrodes with conductive gels (wet electrodes) and cannot be adapted to different body types, resulting in limited applicability. Results: In this study, a wearable wireless EIT belt with dry electrodes was designed to enable EIT imaging of the human body without using wet electrodes. The specific design of the belt mechanism and dry electrodes provide the advantages of easy wear and adaptation to different body sizes. Additionally, the Gauss–Newton method was used to optimize the EIT image. Conclusion: Finally, experiments were performed on the phantom and human body to validate the performance of the proposed EIT belt. Significance: The results demonstrate that the proposed system can provide accurate location information of the objects in the EIT image and the system can be successfully applied for noninvasive measurement of the human body.

Hepatocellular carcinoma (HCC) remains a difficult-to-treat cancer due to late diagnosis and limited curative treatment options. Developing more effective therapeutic strategies is essential for the management of HCC. Oncolytic virotherapy is a novel treatment modality for cancers, and its combination with small molecules merits further exploration. In this study, we combined oncolytic measles virus (MV) with the natural triterpenoid compound ursolic acid (UA) and evaluated their combination effect against HCC cells, including those harboring hepatitis B virus (HBV) or hepatitis C virus (HCV) replication. We found that the combination of MV and UA synergistically induced more cell death in Huh-7 HCC cells through enhanced apoptosis. In addition, increased oxidative stress and loss of mitochondrial potential were observed in the treated cells, indicating dysregulation of the mitochondria-dependent pathway. Similar synergistic cytotoxic effects were also found in HCC cells harboring HBV or HCV genomes. These findings underscore the potential of oncolytic MV and UA combination for further development as a treatment strategy for HCC.

Although important for determining long-term outcome, pathologic stage of hepatocellular carcinoma (HCC) is difficult to predict before surgery. Current state-of-the-art magnetic resonance imaging (MRI) using gadoxetic acid provides many imaging features that could potentially be used to classify single HCC as pT1 or pT2. To determine which gadoxetic acid-enhanced MRI (EOB-MRI) findings predict pathologic stage T2 in patients with solitary HCC (cT1). Pre-operative EOB-MRI findings were reviewed in a retrospective cohort of patients with solitary HCC. The following imaging features were examined: Hyperintensity in unenhanced T2-weighted images, hypointensity in unenhanced T1-weighted images, arterial enhancement, corona enhancement, washout appearance, capsular appearance, hypointensity in the tumor tissue during the hepatobiliary (HB) phase, peritumoral hypointensity in the HB phase, hypointense rim in the HB phase, intratumoral fat, hyperintensity on diffusion-weighted imaging, hypointensity on apparent diffusion coefficient map, mosaic appearance, nodule-in-nodule appearance, and the margin (smooth or irregular). Surgical pathology was used as the reference method for tumor staging. Univariate and multivariate analyses were performed to identify predictors of microvascular invasion or satellite nodules. There were 39 (34.2%; 39 of 114) and 75 (65.8%; 75 of 114) pathological stage T2 and T1 HCCs, respectively. Large tumor size (≥ 2.3 cm) and two MRI findings, i.e., corona enhancement [odds ratio = 2.67; 95% confidence interval: 1.101-6.480] and peritumoral hypointensity in HB phase images (odds ratio = 2.203; 95% confidence interval: 0.961-5.049) were associated with high risk of pT2 HCC. The positive likelihood ratio was 6.25 (95% confidence interval: 1.788-21.845), and sensitivity of EOB-MRI for detecting pT2 HCC was 86.2% when two or three of these MRI features were present. Small tumor size and hypointense rim in the HB phase were regarded as benign features. Small HCCs with hypointense rim but not associated with aggressive features were mostly pT1 lesions (specificity, 100%). Imaging features on EOB-MRI could potentially be used to predict the pathologic stage of solitary HCC (cT1) as pT1 or pT2.