Radiomic analysis based on multi-phase magnetic resonance imaging to predict preoperatively microvascular invasion in hepatocellular carcinoma.

BACKGROUND: The prognosis of hepatocellular carcinoma (HCC) remains poor and relapse occurs in more than half of patients within 2 years after hepatectomy. In terms of recent studies, microvascular invasion (MVI) is one of the potential predictors of recurrence. Accurate preoperative prediction of MVI is potentially beneficial to the optimization of treatment planning. AIM: To develop a radiomic analysis model based on pre-operative magnetic resonance imaging (MRI) data to predict MVI in HCC. METHODS: A total of 113 patients recruited to this study have been diagnosed as having HCC with histological confirmation, among whom 73 were found to have MVI and 40 were not. All the patients received preoperative examination by Gd-enhanced MRI and then curative hepatectomy. We manually delineated the tumor lesion on the largest cross-sectional area of the tumor and the adjacent two images on MRI, namely, the regions of interest. Quantitative analyses included most discriminant factors (MDFs) developed using linear discriminant analysis algorithm and histogram analysis with MaZda software. Independent significant variables of clinical and radiological features and MDFs for the prediction of MVI were estimated and a discriminant model was established by univariate and multivariate logistic regression analysis. Prediction ability of the above-mentioned parameters or model was then evaluated by receiver operating characteristic (ROC) curve analysis. Five-fold cross-validation was also applied via R software. RESULTS: The area under the ROC curve (AUC) of the MDF (0.77-0.85) outperformed that of histogram parameters (0.51-0.74). After multivariate analysis, MDF values of the arterial and portal venous phase, and peritumoral hypointensity in the hepatobiliary phase were identified to be independent predictors of MVI (P < 0.05). The AUC value of the model was 0.939 [95% confidence interval (CI): 0.893-0.984, standard error: 0.023]. The result of internal five-fold cross-validation (AUC: 0.912, 95%CI: 0.841-0.959, standard error: 0.0298) also showed favorable predictive efficacy. CONCLUSION: Noninvasive MRI radiomic model based on MDF values and imaging biomarkers may be useful to make preoperative prediction of MVI in patients with primary HCC.

Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging in the activity staging of terminal ileum Crohn's disease.

BACKGROUND: The activity staging of Crohn's disease (CD) in the terminal ileum is critical in developing an accurate clinical treatment plan. The activity of terminal ileum CD is associated with the microcirculation of involved bowel walls. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) can reflect perfusion and permeability of bowel walls by providing microcirculation information. As such, we hypothesize that DCE-MRI and DWI parameters can assess terminal ileum CD, thereby providing an opportunity to stage CD activity. AIM: To evaluate the value of DCE-MRI and DWI in assessing activity of terminal ileum CD. METHODS: Forty-eight patients with CD who underwent DCE-MRI and DWI were enrolled. The patients' activity was graded as remission, mild and moderate-severe. The transfer constant (Ktrans), wash-out constant (Kep), and extravascular extracellular volume fraction (Ve) were calculated from DCE-MRI and the apparent diffusion coefficient (ADC) was obtained from DWI. Magnetic Resonance Index of Activity (MaRIA) was calculated from magnetic resonance enterography. Differences in these quantitative parameters were compared between normal ileal loop (NIL) and inflamed terminal ileum (ITI) and among different activity grades. The correlations between these parameters, MaRIA, the Crohn's Disease Activity Index (CDAI), and Crohn's Disease Endoscopic Index of Severity (CDEIS) were examined. Receiver operating characteristic curve analyses were used to determine the diagnostic performance of these parameters in differentiating between CD activity levels. RESULTS: Higher Ktrans (0.07 ± 0.04 vs 0.01 ± 0.01), Kep (0.24 ± 0.11 vs 0.15 ± 0.05) and Ve (0.27 ± 0.07 vs 0.08 ± 0.03), but lower ADC (1.41 ± 0.26 vs 2.41 ± 0.30) values were found in ITI than in NIL (all P < 0.001). The Ktrans, Kep, Ve and MaRIA increased with disease activity, whereas the ADC decreased (all P < 0.001). The Ktrans, Kep, Ve and MaRIA showed positive correlations with the CDAI (r = 0.866 for Ktrans, 0.870 for Kep, 0.858 for Ve, 0.890 for MaRIA, all P < 0.001) and CDEIS (r = 0.563 for Ktrans, 0.567 for Kep, 0.571 for Ve, 0.842 for MaRIA, all P < 0.001), while the ADC showed negative correlations with the CDAI (r = -0.857, P < 0.001) and CDEIS (r = -0.536, P < 0.001). The areas under the curve (AUC) for the Ktrans, Kep, Ve, ADC and MaRIA values ranged from 0.68 to 0.91 for differentiating inactive CD (CD remission) from active CD (mild to severe CD). The AUC when combining the Ktrans, Kep and Ve was 0.80, while combining DCE-MRI parameters and ADC values yielded the highest AUC of 0.95. CONCLUSION: DCE-MRI and DWI parameters all serve as measures to stage CD activity. When they are combined, the assessment performance is improved and better than MaRIA.

Six Visual Rating Scales as A Biomarker for Monitoring Atrophied Brain Volume in Parkinson's Disease.

The focus of our investigation was to determine the feasibility of using six visual rating scales as whole-brain imaging markers for monitoring atrophied brain volume in Parkinson's disease (PD). This was a prospective cross-sectional single-center observational study. A total of 98 PD patients were enrolled and underwent an MRI scan and a battery of neuropsychological evaluations. The brain volume was calculated using the online resource MRICloud. Brain atrophy was rated based on six visual rating scales. Correlation analysis was performed between visual rating scores and brain volume and clinical features. We found a significant negative correlation between the total scores of visual rating scores and quantitative brain volume, indicating that six visual rating scales reliably reflect whole brain atrophy in PD. Multiple linear regression-based analyses indicated severer non-motor symptoms were significantly associated with higher scores on the visual rating scales. Furthermore, we performed sample size calculations to evaluate the superiority of visual rating scales; the result show that using total scores of visual rating scales as an outcome measure, sample sizes for differentiating cognition injury require significantly fewer subjects (n = 177) compared with using total brain volume (n = 2524). Our data support the use of the total visual rating scores rather than quantitative brain volume as a biomarker for monitoring cerebral atrophy.

Topological insulator bismuth selenide as a theranostic platform for simultaneous cancer imaging and therapy.

Employing theranostic nanoparticles, which combine both therapeutic and diagnostic capabilities in one dose, has promise to propel the biomedical field toward personalized medicine. Here we investigate the theranostic properties of topological insulator bismuth selenide (Bi2Se3) in in vivo and in vitro system for the first time. We show that Bi2Se3 nanoplates can absorb near-infrared (NIR) laser light and effectively convert laser energy into heat. Such photothermal conversion property may be due to the unique physical properties of topological insulators. Furthermore, localized and irreversible photothermal ablation of tumors in the mouse model is successfully achieved by using Bi2Se3 nanoplates and NIR laser irradiation. In addition, we also demonstrate that Bi2Se3 nanoplates exhibit strong X-ray attenuation and can be utilized for enhanced X-ray computed tomography imaging of tumor tissue in vivo. This study highlights Bi2Se3 nanoplates could serve as a promising platform for cancer diagnosis and therapy.