ObjectivesTo evaluate the predictive value of radiomics features based on multiparameter magnetic resonance imaging (MP-MRI) for peritoneal carcinomatosis (PC) in patients with ovarian cancer (OC).MethodsA total of 86 patients with epithelial OC were included in this retrospective study. All patients underwent FS-T2WI, DWI, and DCE-MRI scans, followed by total hysterectomy plus omentectomy. Quantitative imaging features were extracted from preoperative FS-T2WI, DWI, and DCE-MRI images, and feature screening was performed using a minimum redundancy maximum correlation (mRMR) and least absolute shrinkage selection operator (LASSO) methods. Four radiomics models were constructed based on three MRI sequences. Then, combined with radiomics characteristics and clinicopathological risk factors, a multi-factor Logistic regression method was used to construct a radiomics nomogram, and the performance of the radiomics nomogram was evaluated by receiver operating characteristic curve (ROC) curve, calibration curve, and decision curve analysis.ResultsThe radiomics model from the MP-MRI combined sequence showed a higher area under the curve (AUC) than the model from FS-T2WI, DWI, and DCE-MRI alone (0.846 vs. 0.762, 0.830, 0.807, respectively). The radiomics nomogram (AUC=0.902) constructed by combining radiomics characteristics and clinicopathological risk factors showed a better diagnostic effect than the clinical model (AUC=0.858) and the radiomics model (AUC=0.846). The decision curve analysis shows that the radiomics nomogram has good clinical application value, and the calibration curve also proves that it has good stability.ConclusionRadiomics nomogram based on MP-MRI combined sequence showed good predictive accuracy for PC in patients with OC. This tool can be used to identify peritoneal carcinomatosis in OC patients before surgery.
Background: Pancreatic cancer is a highly malignant tumor with poor prognosis. Chronic inflammation contributes to the progression of pancreatic cancer. However, few studies have examined the prognostic role of inflammatory markers in this cancer. Our study sought to analyze the prognostic risk factors of and construct a prognostic index (PI) model using inflammatory markers for pancreatic cancer.Methods: Forty-eight patients diagnosed with pancreatic cancer at our hospital were selected for this retrospective analysis. Data on the general clinical characteristics, tumor-related features, blood index factors, and treatment methods were collected. The Cox proportional-hazards model was used to analyze the factors affecting the prognosis, and the Kaplan-Meier analysis was used to draw the survival curve. Results:The median overall survival time was 14.5 months, and the 1-, 2-, and 3-year survival rates were 20.83% (10/48), 6.25% (3/48), and 4.17% (2/48), respectively. The univariate analysis showed that tumor grade, vascular invasion, adjacent tissue invasion, lymph node metastasis, tumor-node-metastasis (TNM) stage, the neutrophil-lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the lymphocytemonocyte ratio (LMR) were significantly correlated with the median survival of pancreatic cancer patients (P<0.05). The Cox regression equation showed that tumor grade III-IV (X1), vascular invasion (X2), TNM stage III-IV (X3), a NLR >3.8 (X4), and a PLR >182.1 (X5) were independent risk factors affecting the prognosis of patients with pancreatic cancer (all P<0.05). The prognostic model for pancreatic cancer can be expressed as: PI =3.521X1+4.157X2+1.282X3+2.441X4+6.015X5. Patients with tumor grade I-II, nonvascular invasion, TNM stage I-II, a NLR ≤3.8, and a PLR ≤182.1 exhibited a higher 1-year survival rate.The areas under the receiver operating characteristic (ROC) curves for the NLR >3.8 and the PLR >182.1 were 0.778 and 0.713, respectively.Conclusions: Tumor grade, vascular invasion, TNM staging, the NLR, and the PLR are independent risk factors affecting the prognosis of pancreatic cancer patients. The NLR and PLR have good clinical value in predicting the survival outcomes of pancreatic cancer patients.
BackgroundIdentifying elevated intracranial pressure (ICP) and decreased intracranial compliance (ICC) is imperative for optimizing patient management in neurocritical care settings. Intra-abdominal hypertension (IAH) and intrathoracic hypertension (ITH) is common in trauma patients, which affects homeostasis of ICP/ICC. Knowledge of this effects is little and monitoring this effect is difficult. In the current study, we examined whether the indices generated from 2D cine phase contrast MRI (2D cine PC-MRI) could reflect ICC/ICP alterations induced by elevated IAH/ITH during VM.MethodsA total of 50 healthy young volunteers participated in this study (male: female = 24:26), and took a 2D cine PC-MRI during normal breath and VM respectively. Cross-section area (CSA) of dominant IJV and ipsilateral ICA, the maximum blood flow (Fmax), minimum blood flow (Fmin), mean blood flow (MBF), pulsatility index (PI), arteriovenous delay (AVD) and time to peak of arterial pulse (TTP) were gauged from images or calculated from the blood flow curves generated from 2D cine PC-MRI. ResultsDuring VM state, in comparison to NB, CSAIJV increased significantly (p<0.0001), indicating an elevation of cerebral venous outflow resistance; Fmax_ICA, Fmax_IJV, Fmean_ICA and Fmean_IJV decreased significantly (p<0.0001, p<0.0001, p<0.001, p<0.0001, respectively); PI_ICA and PI_IJV decreased significantly (p<0.0001, p<0.0001); both absolute and normalized AVD decreased significantly (p<0.0001, p<0.0001), while absolute and normalized TTP increased significantly (p=0.0329, p=0.0376).Conclusions Indices generated from 2D cine PC-MRI, especially AVD and TTP, can reveal the ICC/ICP dynamics induced by elevated IAP/ITP. These indices have potential clinical application in ICC/ICP monitoring in patients who was speculated with an IAH or ITH.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.