Cardiac T1 and T2 Mapping Showed Myocardial Involvement in Recovered COVID-19 Patients Initially Considered Devoid of Cardiac Damage.

BACKGROUND: Myocardial injury has been found using magnetic resonance imaging in recovered coronavirus disease 2019 (COVID-19) patients unselected or with ongoing cardiac symptoms. PURPOSE: To evaluate for the presence of myocardial involvement in recovered COVID-19 patients without cardiovascular symptoms and abnormal serologic markers during hospitalization. STUDY TYPE: Prospective. POPULATION: Twenty-one recovered COVID-19 patients and 20 healthy controls (HC). FIELD STRENGTH/SEQUENCE: 3.0 T, cine, T2-weighted imaging, T1 mapping, and T2 mapping. ASSESSMENT: Cardiac ventricular function includes end-diastolic volume, end-systolic volume, stroke volume, cardiac output, left ventricle (LV) mass, and ejection fraction (EF) of LV and right ventricle (RV), and segmental myocardial T1 and T2 values were measured. STATISTICAL TESTS: Student's t-test, univariate general linear model test, and chi-square test were used for analyses between two groups. Ordinary one-way analyses of variance or Kruskal-Wallis H test were used for analyses between three groups, followed by post-hoc analyses. RESULTS: Fifteen (71.43%) COVID-19 patients had abnormal magnetic resonance findings, including raised myocardial native T1 (5, 23.81%) and T2 values (10, 47.62%), decreased LVEF (1, 4.76%), and RVEF (2, 9.52%). The segmental myocardial T2 value of COVID-19 patients (49.20 [46.1, 54.6] msec) was significantly higher than HC (48.3 [45.2, 51.7] msec) (P < 0.001), while the myocardial native T1 value showed no significant difference between COVID-19 patients and HC. The myocardial T2 value of serious COVID-19 patients (52.5 [48.1, 57.1] msec) was significantly higher than unserious COVID-19 patients (48.8 [45.9, 53.8] msec) and HC (48.3 [45.2, 51.7]) (P < 0.001). COVID-19 patients with abnormally elevated D-dimer, C-reactive protein, or lymphopenia showed higher myocardial T2 values than without (all P < 0.05). DATA CONCLUSION: Cardiac involvement was observed in recovered COVID-19 patients with no preexisting cardiovascular disease, no cardiovascular symptoms, and elevated serologic markers of myocardial injury during the whole course of COVID-19. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 5.

Quantitative radiomic model for predicting malignancy of small solid pulmonary nodules detected by low-dose CT screening.

BACKGROUND: It is a permanent challenge to differentiate small solid lung nodules. Massive data, extracted from medical image through radiomics analysis, may help early diagnosis of lung cancer. The aim of this study was to assess the usefulness of a quantitative radiomic model developed from baseline low-dose computed tomography (LDCT) screening for the purpose of predicting malignancy in small solid pulmonary nodules (SSPNs). METHODS: This retrospective study included malignant and benign SSPNs (6 to 15 mm) detected in baseline low-dose CT screening. The malignancy was confirmed pathologically, and benignity was confirmed by long term follow-up or pathological diagnosis. The non-contrast CT images were reconstructed with a lung kernel of a slice thickness of 1 mm and were processed to extract 385 quantitative radiomic features using Analysis-Kinetic software. A predictive model was established with the training set of 156 benign and 40 malignant nodules, and was tested with the validation set of 77 benign and 21 malignant nodules through the analysis of R square. The performance of the radiomic model in predicting malignancy was compared with that of the ACR Lung Imaging Reporting and Data System (ACR lung-RADS). RESULTS: In 294 cases of SSPNs, 61 lung cancers and 24 benign nodules were confirmed pathologically and the remaining 209 nodules were stable with long-term follow-up (4.1±0.9 years). Eleven non-redundant features, including 8 high-order texture features, were extracted from the training data set. The sensitivity and specificity of the prediction model in malignancy differentiation were 81.0% and 92.2% respectively. The accuracy was superior to ACR-lung RADS (89.8% vs. 76.5%). CONCLUSIONS: A radiomic model based on baseline low-dose CT screening for lung cancer can improve the accuracy in predicting malignancy of SSPNs.

Hypermethylation and Expression Silencing of PDCD4 Gene in Hepatocellular Carcinoma: A Consort Study.

Programmed cell death 4 (PDCD4) is a novel tumor suppressor, which is involved in the initiation and progression of cancers. However, the role of PDCD4 in hepatocellular carcinoma (HCC) has not been reported. The aim of this study was to investigate the molecular mechanism and clinical significance of PDCD4 inactivation in HCC.The mRNA levels of PDCD4 in HCC tissues and adjacent nontumor tissues were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). Bisulfite sequencing PCR was performed to determine the methylation status of PDCD4 promoter. Furthermore, the mRNA expression level and the methylated level of PDCD4 were analyzed with the clinical and pathological characteristics.qRT-PCR analysis showed that PDCD4 mRNA levels in tumor tissues were significantly decreased compared with that in adjacent nontumor tissues. The methylation rate of PDCD4 promoter was significantly higher in HCC tissues than that in adjacent nontumor tissues. PDCD4 mRNA levels and promoter methylation levels were both statistically correlated with metastasis and the degree of differentiation in HCC. In addition, the correlation between PDCD4 hypermethylation, mRNA levels, and overall survival (OS) was statistically significant.Our results indicated that PDCD4 may be a novel candidate of tumor suppressor gene in HCC, and that promoter hypermethylation is an important mechanism for its downregulation and is also a good predictor of OS for HCC.