Improving the diagnosis of common parotid tumors via the combination of CT image biomarkers and clinical parameters.

BACKGROUND: Our study aims to develop and validate diagnostic models of the common parotid tumors based on whole-volume CT textural image biomarkers (IBMs) in combination with clinical parameters at a single institution. METHODS: The study cohort was composed of 51 pleomorphic adenoma (PA) patients and 42 Warthin tumor (WT) patients. Clinical parameters and conventional image features were scored retrospectively and textural IBMs were extracted from CT images of arterial phase. Independent-samples t test or Chi-square test was used for evaluating the significance of the difference among clinical parameters, conventional CT image features, and textural IBMs. The diagnostic performance of univariate model and multivariate model was evaluated via receiver operating characteristic (ROC) curve and area under ROC curve (AUC). RESULTS: Significant differences were found in clinical parameters (age, gender, disease duration, smoking), conventional image features (site, maximum diameter, time-density curve, peripheral vessels sign) and textural IBMs (mean, uniformity, energy, entropy) between PA group and WT group (P<0.05). ROC analysis showed that clinical parameter (age) and quantitative textural IBMs (mean, energy, entropy) were able to categorize the patients into PA group and WT group, with the AUC of 0.784, 0.902, 0.910, 0.805, respectively. When IBMs were added in clinical model, the multivariate models including age-mean and age-energy performed significantly better than the univariate models with the improved AUC of 0.940, 0.944, respectively (P<0.001). CONCLUSIONS: Both clinical parameter and CT textural IBMs can be used for the preoperative, noninvasive diagnosis of parotid PA and WT. The diagnostic performance of textural IBM model was obviously better than that of clinical model and conventional image model in this study. While the multivariate model consisted of clinical parameter and textural IBM had the optimal diagnostic performance, which would contribute to the better selection of individualized surgery program.

[Magnetic Resonance Imaging Tracing the Biodistribution of SPIO-shRNA Molecular Probe in vivo].

OBJECTIVES: To investigate the biodistribution of superparamagnetic iron oxide (SPIO)-shRNA molecular probe by magnetic resonance imaging (MRI) in vivo. METHODS: Six New Zealand white rabbits were injected intravenously with SPIO-shRNA molecular probe (9.6 mg Fe/kg) via ear edge vein. The blood samples were collected to analyse the pharmacokinetic parameters through measuring the iron content by atomic absorption spectrometry (AAS) method at 30 min before and 1 min, 3 min, 5 min, 10 min, 15 min, 30 min and at 1, 2, 3, 6, 12, and 24 h after the injection. Six Kun Ming (KM) mice were injected intravenously with SPIO-shRNA molecular probe (4.8 mg Fe/kg). The biodistribution of SPIO-shRNA molecular probe was traced by MRI in vivo. Ninety six KM mice were randomly divided into control group and experimental group: each mouse in experimental group was injected intravenously with SPIO-shRNA molecular probe (4.8 mg Fe/kg). The liver, spleen, kidney, brain and muscle of the control group and the experimental group on 1, 3, 5, 7, 9, 11 and 14 d after the injection were collected. The organ iron content were measured by AAS method and Prussian blue staining in order to observe the distribution of the SPIO-shRNA molecular probe in the main organ. RESULTS: Our results demonstrated that the pharmacokinetics of the molecular probe complied with two-compartment model, and the blood half-life was (3.692±0.196) h. The data of MRI showed that the probe were distributed in liver and spleen, and the signs were reduced in accord with the increase of probe's doses in liver and spleen. The probe's metabolism was slow, and the probe was cleared from liver and spleen at 2 weeks after the injection. The results of AAS and Prussian blue staining further testified the results of MRI. CONCLUSIONS: Our data showed the biodistribution of SPIO-shRNA molecular probe in main organs can be traced by MRI in vivo. Meanwhile, it provides important information for the effectiveness of the probe by MRI at tumor in vivo.

[Pharmacokinetics and MR imaging of SPIO-shRNA dual functional molecular probe in vivo].

In this study, we investigated the pharmacokinetics parameters of SPIO-shRNA dual functional molecular probe and observed the main organ distribution by MRI in vivo. Eighteen New Zealand white rabbits were randomly divided into three groups and injected intravenously with different doses of SPIO-shRNA molecular probe, respectively. The blood samples were collected to analyze the pharmacokinetic parameters by measuring the iron content at 30 minutes before and after the injection. Twenty-four Kun Ming (KM) mice were randomly divided into 4 groups: the control group was injected intravenously with physiological saline 200 µL per mouse via the tail vein, the other 3 groups were injected intravenously with different doses of SPIO-shRNA molecular probe. MRI observation was performed in 24 hours, and the liver, spleen, kidney, brain and muscle were collected for iron quantification with Prussian blue staining to determine distribution of the SPIO-shRNA molecular probe in the main organ in vivo. Our results suggest that the molecular probe blood half-life is more than 3 hours. The data of MRI suggest the probe was distributed in liver and spleen, and the MRI signal was reduced with the increase in probe's doses (P < 0.05). The results of Prussian blue staining confirmed the results of MRI. Most of the probe could escape the phagocytosis of mononuclear phagocyte system. Our data provide the pharmacokinetic and distribution of SPIO-shRNA molecular probe in organs. Meanwhile, it suggests the choice of the time and dose of probe for MR imaging of tumor in vivo.

Effects of external magnetic field on the transfection rate of SPIO-shRNADual functional molecular probe into ovarian carcinoma SKOV3 cells in vitro.

OBJECTIVE: To explore the transfection rate of SPIO-shRNA dual functional molecular probe into ovarian carcinoma SKOV3 cells in external magnetic field. METHODS: Dual functional molecular probe at an iron concentration of 45 mg/L was transfected into SKOV3 cells. The cells with coexisting probe and magnetic fields were set as the intervention group,the probe-transfected cells as negative control group, and normally cultured SKOV3 without any transfection as blank control group. The transfection rate was detected by flow cytometry. Cell viability was observed by CCK-8 assay. Epidermal growth factor receptor (EGFR) expression level in SKOV3 cells was determined by real-time quantitative PCR and Western blot analysis. The signal intensity was measured by magnetic resonance imaging (MRI). RESULTS: The transfection rate of the intervention group was (79.20 ± 3.31)%, which was significantly higher than that of negative control group (P=0.001). Compared with the negative control group,the cell viability of the intervention group significantly decreased (P=0.011), protein and mRNA expression levels of EGFR in the intervention group were significantly decreased (both P<0.05). The signal intensity on T2(*)WI in the intervention group also significantly decreased (P=0.0004). CONCLUSION: The external magnetic field can improve the transfection efficiency SPIO-shRNA dual functional molecular probe into ovarian carcinoma SKOV3 cells.

Subtraction coronary CT angiography in patients with high heart rate.

All the previous subtraction coronary CT angiography (CCTA) had strict heart rate (HR) inclusion criteria. In this study, a new subtraction method was applied to patients with various HR. The post-contrast scan time was respectively 3.5 s after ascending aorta peak enhancement while HR >80 bpm, 4 s while 65≤ HR ≤80 bpm and 4.5 s while HR <65 bpm. Forty-six patients who underwent the new subtraction protocol were enrolled and patients were stratified into the high HR group (≥70 bpm) and low HR group (<70 bpm). Eighteen patients with 15 severe calcification segments and 25 stent segments further received invasive coronary angiography (ICA). In all included patients, the coronary artery enhancement was compared between the high and low HR groups. In patients with ICA performed, the image quality improvement and diagnostic effectiveness for detection of significant coronary segments stenosis (>50%) were compared between the conventional CCTA and subtraction CCTA and between the high HR group and low HR group, respectively. All enrolled patients got sufficient coronary artery enhancement. In patients with ICA performed, receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) for the diagnosis of significant stenosis was 0.93 in subtraction CCTA and 0.73 in conventional CCTA (p < 0.05). Furthermore, there were no significant differences in image quality improvement, specificity, positive predictive value and accuracy between the high HR group and low HR group. The new subtraction CCTA method broadened the clinical availability for patients with high HR.

Proton Magnetic Resonance Spectroscopy at 3.0T in Rabbit With VX2 Liver Cancer: Diagnostic Efficacy and Correlations With Tumor Size.

Purposes: The purpose of this study was to explore the diagnostic performance of Cho peak area (Cho Are), Cho peak amplitude (Cho Amp), and the combined approach (Cho Are_Amp) in detecting rabbit VX2 liver cancer at the early stage via hydrogen-1 proton magnetic resonance spectroscopy (1H-MRS), as well as the correlations between Cho Are, Cho Amp, and tumor parameters like diameter and volume. Methods: Conventional magnetic resonance imaging (MRI) and MRS were performed to scan the VX2 liver cancer in rabbit. The tumor diameter was measured on T2-weighted imaging (T2WI), and the tumor volume was accordingly calculated. Cho Are and Cho Amp were obtained from MRS. The diagnostic performance of Cho Are, Cho Amp, and Cho Are_Amp was assessed by a receiver operating characteristic (ROC) curve and area under ROC curve (AUC), whereas specificity and sensitivity were calculated by the maximum Youden's index. Spearman's correlation analysis was performed to evaluate the relevance between tumor parameters (diameter, volume) and radiological indexes (Cho Are, Cho Amp). Results: ROC curve analysis showed that Cho Amp, Cho Are, and Cho Are_Amp were effective in diagnosing VX2 liver cancer. The AUC of Cho Amp was 0.883, and the specificity and sensitivity were 0.944 and 0.722, respectively (p < 0.001). The AUC of Cho Are was 0.807, and the specificity and sensitivity were 0.778 and 0.833, respectively (p < 0.05). The AUC of Cho Are_Amp was 0.892, and the specificity and sensitivity were 0.833 and 0.833, respectively (p < 0.001). Cho Are and Cho Amp exhibited a high positive correlation with tumor diameter and tumor volume, among which Cho Amp demonstrated better correlations to tumor diameter and tumor volume (r = 0.956 and 0.946) than that of Cho Are (r = 0.787 and 0.794). A high positive correlation was detected between Cho Are and Cho Amp (r = 0.787), as well as tumor diameter and tumor volume (r = 0.965). Conclusion: Cho Are_Amp can be used as an effective tool in diagnosing early-stage VX2 liver cancer with satisfied diagnostic accuracy. Cho Are and Cho Amp were positively correlated with tumor volume and tumor diameter. The results of this study provide further evidence that Cho Amp and Cho Are_Amp of MRS could aid in the early diagnosis of liver cancer.

Differentiating solitary brain metastases from glioblastoma by radiomics features derived from MRI and 18F-FDG-PET and the combined application of multiple models.

This study aimed to explore the ability of radiomics derived from both MRI and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) images to differentiate glioblastoma (GBM) from solitary brain metastases (SBM) and to investigate the combined application of multiple models. The imaging data of 100 patients with brain tumours (50 GBMs and 50 SBMs) were retrospectively analysed. Three model sets were built on MRI, 18F-FDG-PET, and MRI combined with 18F-FDG-PET using five feature selection methods and five classification algorithms. The model set with the highest average AUC value was selected, in which some models were selected and divided into Groups A, B, and C. Individual and joint voting predictions were performed in each group for the entire data. The model set based on MRI combined with 18F-FDG-PET had the highest average AUC compared with isolated MRI or 18F-FDG-PET. Joint voting prediction showed better performance than the individual prediction when all models reached an agreement. In conclusion, radiomics derived from MRI and 18F-FDG-PET could help differentiate GBM from SBM preoperatively. The combined application of multiple models can provide greater benefits.

A Preliminary Study on the Diagnostic Efficacy of Proton Magnetic Resonance Spectroscopy at 3.0T in Rabbit With VX2 Liver Tumor.

BACKGROUND: To investigate the diagnostic efficacy of choline (Cho) value of magnetic resonance spectroscopy (MRS) in rabbit with VX2 liver tumor via comparative and quantitative analysis with the choline compounds concentration measured by enzyme linked immunosorbent assay (ELISA). METHODS: MRS was performed on normal liver and VX2 tumor. The Cho value of VX2 tumor was compared with that of normal liver. Tissues were harvested for ELISA to detect the concentrations of acetylcholine (ACh), glycophorophosphygholine (GPC) and phosphochorine (PC). The diagnostic performance of Cho value and concentrations of choline compounds were assessed by receiver operating characteristic (ROC) curve and area under ROC curve (AUC). The specificity and sensitivity were discussed by the maximum Youden's index. RESULTS: The concentration of ACh was obviously higher than that of GPC and PC both in VX2 tumor and normal liver (P < 0.01). Furthermore, the concentration differences among ACh, GPC and PG were the third power of 10. Both the ACh concentration and Cho value of MRS in VX2 tumor were significantly higher than those in normal liver (P < 0.01). The AUC of ACh in VX2 tumor was 0.883, when the cutoff value was 7259000, the sensitivity and specificity of the diagnosis of liver cancer were 94.4% and 77.8%, respectively. The AUC of Cho in VX2 tumor was 0.807, when the cutoff value was 28.35, the sensitivity and specificity of the diagnosis of liver cancer were 83.3% and 77.8%, respectively. CONCLUSION: The change of Cho value in MRS between liver cancer and normal liver was consistent with the changes of concentrations of choline compounds measured by ELISA, especially the change of ACh concentration. The diagnostic efficiency of Cho value and that of choline compounds concentration in liver cancer were extremely similar, with the AUC more than 0.8. We conclude that MRS may be applied as an important, non-invasive biomarker for the diagnosis of liver cancer.

An Integrated Radiomics Model Incorporating Diffusion-Weighted Imaging and 18F-FDG PET Imaging Improves the Performance of Differentiating Glioblastoma From Solitary Brain Metastases.

BACKGROUND: The effectiveness of conventional MRI (cMRI)-based radiomics in differentiating glioblastoma (GBM) from solitary brain metastases (SBM) is not satisfactory enough. Therefore, we aimed to develop an integrated radiomics model to improve the performance of differentiating GBM from SBM. METHODS: One hundred patients with solitary brain tumors (50 with GBM, 50 with SBM) were retrospectively enrolled and randomly assigned to the training set (n = 80) or validation set (n = 20). A total of 4,424 radiomic features were obtained from contrast-enhanced T1-weighted imaging (CE-T1WI) with the contrast-enhancing and peri-enhancing edema region, T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI)-derived apparent diffusion coefficient (ADC), and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) images. The partial least squares (PLS) regression with fivefold cross-validation is used to analyze the correlation between different radiomic features and different modalities. The cross-validity analysis was performed to judge whether a new principal component or a new feature dimension can significantly improve the final prediction effect. The principal components with effective interpretation in all radiomic features were projected to a low-dimensional space (2D in this study). The effective features of the new projection mapping were then sent to the random forest classifier to predict the results. The performance of differentiating GBM from SBM was compared between the integrated radiomics model and other radiomics models or nonradiomics methods using the area under the receiver operating characteristics curve (AUC). RESULTS: Through the cross-validity analysis of partial least squares, hundreds of radiomic features were projected into a new two-dimensional space to complete the construction of radiomics model. Compared with the combined radiomics model using DWI + 18F-FDG PET (AUC = 0.93, p = 0.014), cMRI + DWI (AUC = 0.89, p = 0.011), cMRI + 8F-FDG PET (AUC = 0.91, p = 0.015), and single radiomics model using cMRI (AUC = 0.85, p = 0.018), DWI (AUC = 0.84, p = 0.017), and 18F-FDG PET (AUC = 0.85, p = 0.421), the integrated radiomics model (AUC = 0.98) showed more efficient diagnostic performance. The integrated radiomics model (AUC = 0.98) also showed significantly better performance than any single ADC, SUV, or TBR parameter (AUC = 0.57-0.71, p < 0.05). The integrated radiomics model showed better performance in the training (AUC = 0.98) and validation (AUC = 0.93) sets than any other models and methods, demonstrating robustness. CONCLUSIONS: We developed an integrated radiomics model incorporating DWI and 18F-FDG PET, which improved the performance of differentiating GBM from SBM greatly.

Abnormal Baseline Brain Activity in Neuromyelitis Optica Patients Without Brain Lesion Detected by Resting-State Functional Magnetic Resonance Imaging.

OBJECTIVE: To investigate the baseline brain activity in neuromyelitis optica patients without brain lesion using the regional amplitude of low-frequency fluctuation (ALFF) and fractional amplitude of low-frequency fluctuation (fALFF) as indexes. MATERIALS AND METHODS: Forty-two patients of NMO with normal performance in conventional MRI and 42 healthy controls, matched in gender and age, were enrolled in this study. Resting-state functional magnetic resonance imaging (rs-fMRI) data acquired using the rs-fMRI Data Analysis Toolkit. The relationships between expanded disability states scale (EDSS) scores, abnormal baseline brain activity and disease duration were explored. RESULTS: The left inferior temporal, left cerebellum_4_5, bilateral superior temporal pole, left caudate, right superior temporal, left middle frontal and left superior occipital showed significantly increased ALFF in the NMO. Regions of abnormal fALFF were similar to those of ALFF except that increased fALFF were also indicated in the right cerebellum crus2, right hippocampus, left parahippocampal gyrus and left supplementary motor area. Furthermore, a significant correlation between EDSS scores and ALFF/fALFF was noted in the left inferior temporal gyrus. CONCLUSION: Results confirmed the disturbances in NMO-related neural networks, which probably be related to spinal cord damage.

A Preliminary Study of CT Texture Analysis for Characterizing Epithelial Tumors of the Parotid Gland.

OBJECTIVE: The aim of this study was to explore and validate the diagnostic performance of whole-volume CT texture features in differentiating the common benign and malignant epithelial tumors of the parotid gland. MATERIALS AND METHODS: Contrast-enhanced CT images of 83 patients with common benign and malignant epithelial tumors of the parotid gland confirmed by histopathology were retrospectively analyzed, including 50 patients with pleomorphic adenoma (PA) and 33 patients with malignant epithelial tumors. Quantitative texture features of tumors were extracted from CT images of arterial phase. The diagnostic performance of texture features was evaluated via receiver operating characteristic (ROC) curve and area under ROC curve (AUC). The specificity and sensitivity were respectively discussed by the maximum Youden's index. RESULTS: All the texture features were subject to normal distribution and homoscedasticity. Energy, mean, correlation, and sum entropy of epithelial malignancy group were significantly higher than those of PA group (P<0.05). There were no statistically significant differences between PA group and epithelial malignancy group in uniformity, entropy, skewness, kurtosis, contrast, and difference entropy (P>0.05). The AUC of each texture feature and joint diagnostic model was 0.887 (energy), 0.734 (mean), 0.739 (correlation), 0.623 (sum entropy), 0.888 (energy-mean), 0.883 (energy-correlation), 0.784 (mean-correlation). The diagnostic efficiency of energy-mean was the best. Based on the maximum Youden's index, the specificity of energy-correlation was the highest (97%) and the sensitivity of energy was the highest (97%). CONCLUSION: Energy, mean, correlation, and sum entropy can be the effective quantitative texture features to differentiate the benign and malignant epithelial tumors of the parotid gland. With higher AUC, energy and energy-mean are superior to other indexes or joint diagnostic models in differentiating the benign and malignant epithelial tumors of the parotid gland. CT texture analysis can be used as a noninvasive and valuable means of preoperative assessment of parotid epithelial tumors without additional cost to the patients.