Purpose To evaluate the potential role of diffusion kurtosis imaging and conventional magnetic resonance (MR) imaging findings including standard monoexponential model of diffusion-weighted imaging and morphologic features for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Materials and Methods Institutional review board approval and written informed consent were obtained. Between September 2015 and November 2016, 84 patients (median age, 54 years; range, 29-79 years) with 92 histopathologically confirmed HCCs (40 MVI-positive lesions and 52 MVI-negative lesions) were analyzed. Preoperative MR imaging examinations including diffusion kurtosis imaging (b values: 0, 200, 500, 1000, 1500, and 2000 sec/mm) were performed and kurtosis, diffusivity, and apparent diffusion coefficient maps were calculated. Morphologic features of conventional MR images were also evaluated. Univariate and multivariate logistic regression analyses were used to evaluate the relative value of these parameters as potential predictors of MVI. Results Features significantly related to MVI of HCC at univariate analysis were increased mean kurtosis value (P < .001), decreased mean diffusivity value (P = .033) and apparent diffusion coefficient value (P = .011), and presence of infiltrative border with irregular shape (P = .005) and irregular circumferential enhancement (P = .026). At multivariate analysis, mean kurtosis value (odds ratio, 6.25; P = .001), as well as irregular circumferential enhancement (odds ratio, 6.92; P = .046), were independent risk factors for MVI of HCC. The mean kurtosis value for MVI of HCC showed an area under the receiver operating characteristic curve of 0.784 (optimal cutoff value was 0.917). Conclusion Higher mean kurtosis values in combination with irregular circumferential enhancement are potential predictive biomarkers for MVI of HCC. RSNA, 2017.
• ADC histogram analyses can potentially predict chemotherapy response in colorectal liver metastases. • Lower histogram-derived parameters (mean, percentiles) for ADC tend to have good response. • MR enhancement histogram analyses are not reliable to predict response.
3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:383-392.
Background: Accumulating evidence has revealed that coronavirus disease 2019 (COVID-19) patients may be complicated with myocardial injury during hospitalization. However, data regarding persistent cardiac involvement in patients who recovered from COVID-19 are limited. Our goal is to further explore the sustained impact of COVID-19 during follow-up, focusing on the cardiac involvement in the recovered patients.Methods: In this prospective observational follow-up study, we enrolled a total of 40 COVID-19 patients (20 with and 20 without cardiac injury during hospitalization) who were discharged from Zhongnan Hospital of Wuhan University for more than 6 months, and 27 patients (13 with and 14 without cardiac injury during hospitalization) were finally included in the analysis. Clinical information including self-reported symptoms, medications, laboratory findings, Short Form 36-item scores, 6-min walk test, clinical events, electrocardiogram assessment, echocardiography measurement, and cardiac magnetic resonance imaging was collected and analyzed.Results: Among 27 patients finally included, none of patients reported any obvious cardiopulmonary symptoms at the 6-month follow-up. There were no statistically significant differences in terms of the quality of life and exercise capacity between the patients with and without cardiac injury. No significant abnormalities were detected in electrocardiogram manifestations in both groups, except for nonspecific ST-T changes, premature beats, sinus tachycardia/bradycardia, PR interval prolongation, and bundle-branch block. All patients showed normal cardiac structure and function, without any statistical differences between patients with and without cardiac injury by echocardiography. Compared with patients without cardiac injury, patients with cardiac injury exhibited a significantly higher positive proportion in late gadolinium enhancement sequences [7/13 (53.8%) vs. 1/14 (7.1%), p = 0.013], accompanied by the elevation of circulating ST2 level [median (interquartile range) = 16.6 (12.1, 22.5) vs. 12.5 (9.5, 16.7); p = 0.044]. Patients with cardiac injury presented higher levels of aspartate aminotransferase, creatinine, high-sensitivity troponin I, lactate dehydrogenase, and N-terminal pro–B-type natriuretic peptide than those without cardiac injury, although these indexes were within the normal range for all recovered patients at the 6-month follow-up. Among patients with cardiac injury, patients with positive late gadolinium enhancement presented higher cardiac biomarker (high-sensitivity troponin I) and inflammatory factor (high-sensitivity C-reactive protein) on admission than the late gadolinium enhancement–negative subgroup.Conclusions: Our preliminary 6-month follow-up study with a limited number of patients revealed persistent cardiac involvement in 29.6% (8/27) of recovered patients from COVID-19 after discharge. Patients with cardiac injury during hospitalization were more prone to develop cardiac fibrosis during their recovery. Among patients with cardiac injury, those with relatively higher cardiac biomarkers and inflammatory factors on admission appeared more likely to have cardiac involvement in the convalescence phase.
To explore and visualize the relationships among multiple symptoms in people living with HIV (PLWH) and compare centrality indices and the density of symptom networks among groups of individuals with different HIV-positive durations. Methods: We conducted a secondary analysis of data from the HIV-related Symptoms Monitoring Survey conducted in China. Networks were constructed among 27 symptoms. Centrality properties, including strength and closeness, and network density were used to describe relationships among symptoms in 5 different HIV-positive duration groups. Results: The findings showed that PLWH with longer HIV-positive durations did not have more severe symptoms; instead, their symptom networks were denser than those of their newly HIV-diagnosed counterparts (F = 27.073, P < 0.001). Fatigue was the most severe and central symptom in PLWH with an HIV-positive duration <10 years (r S = 7.79-10.09, r B = 18-44, r C = 0.01). Confusion was the most central symptom across the 3 centrality indices (r S = 11.81, r B = 14.00, r C = 0.02) in PLWH who had HIV-positive durations >10 years. Conclusion:This study demonstrates a need to include an assessment of PLWH symptom networks as an essential component of HIV care. We recommended evaluating cognitive function and cognitive training as essential components of HIV care for long-term survivors, even in younger populations (aged 50 years).
The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement.The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001).MR histogram analyses—in particular for 1th percentile for PVP images—held promise for prediction of MVI of HCC.
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