Preclinical evaluation of severely defective manganese-based nanocrystal as a liver-specific contrast media for MR imaging: comparison with Gd-EOB-DTPA and MnDPDP.

Manganese-based (chemically formulated of KMnF3) nanocrystal was evaluated as a liver-specific contrast agent for MR imaging and its imaging performance was also compared with those of two commercial hepatobiliary contrast media (Gd-EOB-DTPA and MnDPDP). KMnF3 nanocrystal was post-treated using a plasma technique to cause severe defects, leading to appropriate water dispersibility and high relaxivity. Severely defective KMnF3 nanocrystal (SD-KMnF3) has characteristic high tolerance, as evidenced by cytotoxicity on the macrophage cell, and acute and subchronic toxicity on the healthy mouse. SD-KMnF3 showed better hepatic MR imaging as the T 1 relaxation time of the liver decreased to only 17% of the control group, compared to 22% of the control group for Gd-EOB-DTPA (P < 0.01) and 42% of the control group for MnDPDP (P < 0.001). As applied to MR imaging of the allograft orthotopic model of liver cancer, statistical studies demonstrated that SD-KMnF3 significantly improved the tumor's contrast-to-noise ratio, compared with Gd-EOB-DTPA (P < 0.01) and MnDPDP (P < 0.01) by spin-echo pulse sequence, and even better performance (P < 0.001) by gradient-echo sequence. Our findings indicate that SD-KMnF3 could serve as a hepatic contrast agent for imaging liver cancer such as hepatocarcinoma or metastatic lesions.

A Radiomics Model for Predicting Early Recurrence in Grade II Gliomas Based on Preoperative Multiparametric Magnetic Resonance Imaging.

OBJECTIVE: This study aimed to develop a radiomics model to predict early recurrence (<1 year) in grade II glioma after the first resection. METHODS: The pathological, clinical, and magnetic resonance imaging (MRI) data of patients diagnosed with grade II glioma who underwent surgery and had a recurrence between 2017 and 2020 in our hospital were retrospectively analyzed. After a rigorous selection, 64 patients were eligible and enrolled in the study. Twenty-two cases had a pathologically confirmed recurrent glioma. The cases were randomly assigned using a ratio of 7:3 to either the training set or validation set. T1-weighted image (T1WI), T2-weighted image (T2WI), and contrast-enhanced T1-weighted image (T1CE) were acquired. The minimum-redundancy-maximum-relevancy (mRMR) method alone or in combination with univariate logistic analysis were used to identify the most optimal predictive feature from the three image sequences. Multivariate logistic regression analysis was then used to develop a predictive model using the screened features. The performance of each model in both training and validation datasets was assessed using a receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: A total of 396 radiomics features were initially extracted from each image sequence. After running the mRMR and univariate logistic analysis, nine predictive features were identified and used to build the multiparametric radiomics model. The model had a higher AUC when compared with the univariate models in both training and validation data sets with an AUC of 0.966 (95% confidence interval: 0.949-0.99) and 0.930 (95% confidence interval: 0.905-0.973), respectively. The calibration curves indicated a good agreement between the predictable and the actual probability of developing recurrence. The DCA demonstrated that the predictive value of the model improved when combining the three MRI sequences. CONCLUSION: Our multiparametric radiomics model could be used as an efficient and accurate tool for predicting the recurrence of grade II glioma.

A Clinical-Radiomic Nomogram Based on Unenhanced Computed Tomography for Predicting the Risk of Aldosterone-Producing Adenoma.

PURPOSE: To develop and validate a clinical-radiomic nomogram for the preoperative prediction of the aldosterone-producing adenoma (APA) risk in patients with unilateral adrenal adenoma. PATIENTS AND METHODS: Ninety consecutive primary aldosteronism (PA) patients with unilateral adrenal adenoma who underwent adrenal venous sampling (AVS) were randomly separated into training (n = 62) and validation cohorts (n = 28) (7:3 ratio) by a computer algorithm. Data were collected from October 2017 to June 2020. The prediction model was developed in the training cohort. Radiomic features were extracted from unenhanced computed tomography (CT) images of unilateral adrenal adenoma. The least absolute shrinkage and selection operator (LASSO) regression model was used to reduce data dimensions, select features, and establish a radiomic signature. Multivariable logistic regression analysis was used for the predictive model development, the radiomic signature and clinical risk factors integration, and the model was displayed as a clinical-radiomic nomogram. The nomogram performance was evaluated by its calibration, discrimination, and clinical practicability. Internal validation was performed. RESULTS: Six potential predictors were selected from 358 texture features by using the LASSO regression model. These features were included in the Radscore. The predictors included in the individualized prediction nomogram were the Radscore, age, sex, serum potassium level, and aldosterone-to-renin ratio (ARR). The model showed good discrimination, with an area under the receiver operating characteristic curve (AUC) of 0.900 [95% confidence interval (CI), 0.807 to 0.993], and good calibration. The nomogram still showed good discrimination [AUC, 0.912 (95% CI, 0.761 to 1.000)] and good calibration in the validation cohort. Decision curve analysis presented that the nomogram was useful in clinical practice. CONCLUSIONS: A clinical-radiomic nomogram was constructed by integrating a radiomic signature and clinical factors. The nomogram facilitated accurate prediction of the probability of APA in patients with unilateral adrenal nodules and could be helpful for clinical decision making.

Diagnostic value of whole body diffusion weighted imaging for screening primary tumors of patients with metastases.

OBJECTIVE: To evaluate the values of whole body diffusion weighted imaging (DWI) in screening primary unknown tumor in patients with metastases. METHODS: Totally, 34 patients with metastases of primary unknown tumors were scanned with whole body DWI, and conventional magnetic resonance (MR) imaging was performed if suspected lesions were detected. All the metastases including 27 cases of osseous metastases, 2 brain metastases, 2 liver metastases, 1 pulmonary multiple metastasis, 1 neck metastasis and 1 malignant ascites, were diagnosed by computed tomography, single photon emission computed tomography, or MR imaging. For the proven primary tumors diagnosed by biopsy or pathology of surgical specimens, apparent diffusion coefficient (ADC) values of the primary and metastatic lesions were measured respectively. The sensitivity and specificity of this technique for screening primary tumors were evaluated. RESULTS: We found 24 cases with suspected primary lesions, in which 23 lesions were proved to be primary tumors, and 1 was proved to be benign lesion. And no definite primary lesion was found in 10 cases on whole body DWI, but in which 1 case was diagnosed with primary tumor by biopsy later, and the other 9 cases remained unknown within follow-up of over half a year. The difference was not significant in ADC values between primary and metastatic lesions (P>0.05). The sensitivity and specificity of whole body DWI for searching primary tumors was 95.8% and 90.0%, respectively. CONCLUSION: Combined with conventional MR scanning, whole body DWI can help to search primary lesions of patients with metastases.

Non-coding RNA 886 promotes renal cell carcinoma growth and metastasis through the Janus kinase 2/signal transducer and activator of transcription 3 signaling pathway.

Non-coding RNA 886 (nc886) has been suggested to serve tumor-suppressing roles in several cancer cells. However, the expression pattern of nc886 and its function in renal cell carcinoma (RCC) has not been reported until now. The present study aimed to examine the expression of nc886 in human RCC tissues and to investigate the role of nc886 in RCC cell proliferation, apoptosis and invasion in vitro. Furthermore, whether nc886 exerts its function on RCC via Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) signaling was investigated. It was demonstrated that nc886 is overexpressed in human RCC tissues compared with normal tissues, as determined by reverse transcription-quantitative polymerase chain reaction analysis. The nc886 mimic and inhibitor were transfected into the A­498 cells to overexpress or knock down nc886 expression. Cell proliferation, cell apoptosis rate and cell invasion ability were determined by MTT, flow cytometry and Transwell­Matrigel invasion assays. The results demonstrated that nc886 overexpression promotes A­498 cell proliferation and invasion, and inhibits cell apoptosis, while nc886 knockdown resulted in the opposite effects. Furthermore, nc886 could activate the JAK2/STAT3 signaling pathway in A­498 cells. AG490, an inhibitor of JAK2, could attenuate the effects of nc886 on cell proliferation, apoptosis and invasion. In conclusion, to the best of our knowledge, the present study for the first time revealed the expression profile and the tumor­promoting role of nc886 in RCC. nc886 affects RCC cell proliferation, apoptosis and invasion at least partially via the activation of JAK2/STAT3 signaling. This study may provide a useful therapeutic target for RCC.

High-resolution MR imaging of the arterial wall in moyamoya disease.

High resolution magnetic resonance imaging (HRMRI) has been developed as an emerging tool for evaluating intracranial arterial disease. We aimed to analyze the progression of diseased arterial walls in moyamoya disease (MMD) and further elucidate differences compared to intracranial atherosclerotic stenosis using HRMRI. The population of this HRMRI study consisted of 21 patients with MMD and 44 patients with atherosclerotic middle cerebral artery (MCA) stenosis. The cross-sectional images of the MCA wall on HRMRI were compared between the two groups based on outer diameter, wall thickness, luminal stenotic morphology, signal intensity, collateral vascular structures adjacent to stenotic position. In addition, stage classification based on MRA finding was used to depict the course of moyamoya disease. We compared outer diameter and wall thickness of the MCAs in different MRA stages. As a result, the outer diameter and wall thickness of MCAs were significantly smaller in the MMD group than in the atherosclerosis group (outer diameter: MMD 2.01 ± 0.31 mm vs. atherosclerosis 3.31 ± 0.37 mm, p<0.001 and wall thickness: MMD 0.39 ± 0.19 mm vs. atherosclerosis 1.64 ± 0.38 mm, p < 0.001). The concentric stenosis (91.4% in MMD vs. 36.9% in atherosclerosis group, p < 0.001), homogeneous signal intensity (85.7% in MMD vs. 32.6% in atherosclerosis group, p < 0.001) and collateral vascular structures (54.3% in MMD vs. 8.7% in atherosclerosis group, p < 0.001) were more common in MMD patients. In addition, the outer diameter of MCAs in MMD was significantly different between MRA stage 1 and MRA stage 3 or 4 (MRA stage 1 vs. MRA stage 3, Nemenyi test p = 0.005 and MRA stage 1 vs. MRA stage 4, Nemenyi test p = 0.009). But the wall thickness of MCAs was no significantly different in different MRA stages (Kruskal-wallis H test, p = 0.074). We conclude that HRMRI may be used to identify different types of middle cerebral artery stenosis. MMD was characterized by concentric stenosis, homogeneous signal intensity, and collateral vascular structures in the affected MCA segments by HRMRI. Pathological shrinkage of MCA was an important phenomenon in MMD progression.

[Optic radiation in normal adults: a study using magnetic resonance diffusion tensor imaging and diffusion tensor tractography].

OBJECTIVE: To study the fractional anisotropy (FA) and the architecture of the optic radiation fiber tracts of normal adults with magnetic resonance (MR) diffusion tensor imaging (DTI). METHODS: Diffusion tensor images were obtained from 30 healthy volunteers without any cerebral abnormalities on conventional MRI. FA and the mean diffusivity (MD) of the optic radiation were measured in the directional encoded color (DEC) maps. The architecture of the optic radiation fiber tracts were displayed with the software of diffusion tensor fiber tracking. RESULTS: In all subjects, the optic radiation could be readily identified in the DEC maps. The FA value was 0.509-/+0.029 in the left and 0.502-/+0.026 in the right, with the MD value of (0.763-/+0.050) x10(-3) and 0.748-/+0.052)x10(-3) mm2/s, respectively. No significant differences were found in the FA or MD value of the bilateral optic radiation (P>0.05). Diffusion tensor tractography (DTT) demonstrated that the 3 bundles of the optic radiation fibers were located in the lateral sagittal stratum, passing from the lateral geniculate body of the thalamus to the primary visual cortex. The dorsal and lateral bundles passed posteriorly to the superior bank of the calcarine cortex, while the ventral bundle passed anteriorly before making a sharp turn, known as the Meyer loop, and subsequently coursed posteriorly to terminate in the inferior margin of the calcarine cortex, which was consistent with the results of classic anatomical studies. CONCLUSION: As a novel method to study the relationship between visual function and optic pathway, DTI and DTT can show the FA and architecture of the optic radiation.