Assessment of late gadolinium enhancement-negative chronic total occlusion by longitudinal strain analysis using cardiac magnetic resonance imaging.

BACKGROUND: Strain analysis has become commonly used in clinical practice in various heart diseases. PURPOSE: To explore whether late gadolinium enhancement (LGE)-negative areas with coronary artery chronic total occlusion (CTO) appear normal when analyzed for longitudinal strain using cardiac magnetic resonance (CMR) imaging. MATERIAL AND METHODS: A total of 16 patients and 31 healthy controls who underwent 1.5-T MR at our hospital between January 2015 and July 2017 were included in the study. The LGE-CMR of patients with CTO was negative. Left ventricular functional parameters, segmental longitudinal strain/strain rate, and perfusion parameters were measured using CVI42 software. RESULTS: For myocardial segments supplied by CTO vessels, systolic longitudinal strain rate (SLSR)was significantly lower than that of healthy controls, and diastolic longitudinal strain rate (DLSR) was significantly higher (1.19 1/s vs. 1.02 1/s; P = 0.018). Moreover, longitudinal strain (LS), SLSR, and DLSR did not differ between good and poor collateral circulation. Perfusion index of CTO territory segments was lower than non-CTO territory segments (0.20 vs. 0.22; P = 0.027). No correlation was found between longitudinal strain parameters and perfusion parameters. CONCLUSION: Although LGE-CMR was negative in patients with CTO, the myocardial SLSR of CTO territory segments was significantly lower than that of healthy controls.

Myocardium microcirculation study in a healthy Chinese population using 3.0-T cardiac magnetic resonance intravoxel incoherent motion imaging.

BACKGROUND: Intravoxel incoherent motion imaging (IVIM) can non-invasively evaluate diffusion and microvascular perfusion. PURPOSE: To explore the myocardium microcirculation of a healthy Chinese population by using cardiac magnetic resonance (CMR) IVIM. MATERIAL AND METHODS: A total of 80 healthy volunteers (44 men, 36 women) who underwent 3.0-T CMR examination were enrolled. All participants had cardiac cine imaging and short-axis CMR-IVIM of the left ventricle (LV) using multiple b-values. The consistency of the IVIM parameters was assessed by intraclass correlation coefficient (ICC) and the Bland-Altman test. Spearman correlation analysis was performed between IVIM parameters and age, and body mass index (BMI). The differences of IVIM parameters were analyzed between gender and different ages. RESULTS: LV end-diastolic volume (EDV), end-systolic volume (ESV), LVmass, cardiac output (CO), and BMI in the male group were higher than those in the female group (P<0.05). IVIM parameters had good intra-observer and inter-observer consistency (≥0.75). Bland-Altman analysis also showed good intra-observer and inter-observer consistency. ADCfast decreased with increasing female age (rs = -0.37; P = 0.01), while IVIM parameters had no correlation with BMI regardless of sex. ADCfast in the female group had a statistical difference between different age groups. The ADCslow and f in the male group were lower than those in the female group (P<0.05); however, there was no statistical difference in ADCfast between genders. CONCLUSION: IVIM parameters in healthy Chinese volunteers provided good consistency. There was a negative correlation between ADCfast and age in the female group.

Tumor size measured by multidetector CT in resectable colon cancer: correlation with regional lymph node metastasis and N stage.

BACKGROUND: Lymph node metastasis (LNM) is a risk factor for poor long-term outcomes and a prognostic factor for disease-free survival in colon cancer. Preoperative lymph node status evaluation remains a challenge. The purpose of this study is to determine whether tumor size measured by multidetector computed tomography (MDCT) could be used to predict LNM and N stage in colon cancer. MATERIAL AND METHODS: One hundred six patients with colon cancer who underwent radical surgery within 1 week of MDCT scan were enrolled. Tumor size including tumor length (Tlen), tumor maximum diameter (Tdia), tumor maximum cross-sectional area (Tare), and tumor volume (Tvol) were measured to be correlated with pathologic LNM and N stage using univariate logistic regression analysis, multivariate logistic analysis, and receiver operating characteristic (ROC) curve analysis. RESULTS: The inter- and intraobserver reproducibility of Tlen (intraclass correlation coefficient [ICC] = 0.94, 0.95, respectively), Tdia (ICC = 0.81, 0.93, respectively), Tare (ICC = 0.97, 0.91, respectively), and Tvol (ICC = 0.99, 0.99, respectively) parameters measurement are excellent. Univariate logistic regression analysis showed that there were significant differences in Tlen, Tdia, Tare, and Tvol between positive and negative LNM (p < 0.001, 0.001, < 0.001, < 0.001, respectively). Multivariate logistic regression analysis revealed that Tvol was independent risk factor for predicting LNM (odds ratio, 1.082; 95% confidence interval for odds ratio, 1.039, 1.127, p<0.001). Tlen, Tdia, Tare, and Tvol could distinguish N0 from N1 stage (p < 0.001, 0.041, < 0.001, < 0.001, respectively), N0 from N2 (all p < 0.001), N0 from N1-2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively), and N0-1 from N2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively). The area under the ROC curve (AUC) was higher for Tvol than that of Tlen, Tdia, and Tare in identifying LNM (AUC = 0.83, 0.82, 0.69, 0.79), and distinguishing N0 from N1 stage (AUC = 0.79, 0.78, 0.63, 0.74), N0 from N2 stage (AUC = 0.92, 0.89, 0.80, 0.89, respectively), and N0-1 from N2 stage (AUC = 0.84, 0.79, 0.76, 0.83, respectively). CONCLUSION: Tumor size was correlated with regional LNM in resectable colon cancer. In particularly, Tvol showed the most potential for noninvasive preoperative prediction of regional LNM and N stage.

Evaluation of myocardial microcirculation using intravoxel incoherent motion imaging.

PURPOSE: To explore whether cardiac magnetic resonance-intravoxel incoherent motion imaging (MR-IVIM) is feasible for the clinical evaluation of myocardial microcirculation. MATERIALS AND METHODS: The study included 30 patients (with hypertrophic cardiomyopathy, diabetes mellitus, hypertension, or combined diabetes and hypertension) and 34 healthy volunteers. MR-IVIM with a maximum gradient strength of 50 mT/m was performed on the left ventricular short axis (apex, middle, and base), using multiple b values (0-500 s/mm2 ) on a 3.0T MR scanner. MR-IVIM parameters of the left ventricle included apparent diffusion coefficient (ADC)slow , ADCfast , and f (fraction of ADCfast ). With a double-blind design, the image quality and IVIM parameters were assessed by two cardiovascular radiologists at 1-month intervals. Participants were stratified into two groups (failure or success), based on criteria for success of MR-IVIM acquisition. The heart rate of each participant was recorded. RESULTS: The success rates for image acquisition were 68.23% (131/192) overall, with the healthy group (74.51% [76/102]) significantly higher than the patient group (61.11% [55/90]). The mean heart rate was significantly higher in the failure group than the success group. The two radiologists were comparable in quality evaluations of the images (kappa = 0.82). Both the interobserver and intraobserver reliability for IVIM parameters were excellent for patients and healthy volunteers (intraclass correlation coefficient >0.8). However, the left ventricle myocardial ADCfast of each patient group was significantly lower than that of the healthy volunteers. CONCLUSION: MR-IVIM could noninvasively assess human myocardial microcirculation, but challenges remain before this method can be applied in the clinic. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1818-1828.

Noninvasive radiomics approach predicts dopamine agonists treatment response in patients with prolactinoma: a multicenter study.

RATIONALE AND OBJECTIVES: The first-line treatment for prolactinoma is drug therapy with dopamine agonists (DAs). However, some patients with resistance to DA treatment should prioritize surgical treatment. Therefore, it is crucial to accurately identify the drug treatment response of prolactinoma before treatment. The present study was performed to determine the DA treatment response of prolactinoma using a clinical radiomic model that incorporated radiomic and clinical features before treatment. MATERIALS AND METHODS: In total, 255 patients diagnosed with prolactinoma were retrospectively divided to training and validation sets. An elastic net algorithm was used to screen the radiomic features, and a fusion radiomic model was established. A clinical radiomic model was then constructed to integrate the fusion radiomic model and the most important clinical features through multivariate logistic regression analysis for individual prediction. The calibration, discrimination, and clinical applicability of the established models were evaluated. 60 patients with prolactinoma from other centers were used to validate the performance of the constructed model. RESULTS: The fusion radiomic model was constructed from three significant radiomic features, and the area under the curve in the training set and validation set was 0.930 and 0.910, respectively. The clinical radiomic model was constructed using the radiomic model and three clinical features. The model exhibited good recognition and calibration abilities as evidenced by its area under the curve of 0.96, 0.92, and 0.92 in the training, validation, and external multicenter validation set, respectively. Analysis of the decision curve showed that the fusion radiomic model and clinical radiomic model had good clinical application value for DA treatment response prediction in patients with prolactinoma. CONCLUSION: Our clinical radiomic model demonstrated high sensitivity and excellent performance in predicting DA treatment response in prolactinoma. This model holds promise for the noninvasive development of individualized diagnosis and treatment strategies for patients with prolactinoma.

Clinicopathological and Prognostic Value of Gastric Carcinoma Highly Expressed Transcript 1 in Cancer: A Meta-Analysis.

BACKGROUND: Long noncoding RNA gastric cancer highly expressed transcript 1 (lncRNA GHET1) is often reported to be abnormally expressed in multiple cancers, but the situation is different in different cancers. Therefore, a meta-analysis is necessary to clarify the value of lncRNA GHET1 as a prognostic indicator in cancer. METHODS: Relevant research studies on lncRNA GHET1 and cancer were retrieved from three electronic literature databases of Web of Science, PubMed, and OVID. Meanwhile, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to explore the relationship between lncRNA GHET1 expression and survival of cancer patients. The odds ratios (ORs) and 95% CIs were calculated to assess the association of lncRNA GHET1 expression with pathological parameters of cancer patients. RESULTS: The meta-analysis included a total of 11 studies involving 714 cancer patients. The pooled HR suggests that high lncRNA GHET1 expression is associated with poor overall survival. In addition, high expression of lncRNA GHET1 was found to be associated with larger tumor size, poor histological grade, high tumor stage, lymph node metastasis, and distant metastasis. CONCLUSIONS: High lncRNA GHET1 expression can predict poor survival and pathological parameters. And lncRNA GHET1 could serve as a new indicator in multiple cancers.

Significance of lncRNA MIR31HG in predicting the prognosis for Chinese patients with cancer: a meta-analysis.

It is important to clarify the significance of long noncoding RNA MIR31 host gene (lncRNA MIR31HG) in predicting the prognosis for malignant tumors through meta-analysis. Electronic databases were systemically searched, from inception until 2 January 2019, to identify related articles. Meanwhile, the hazard ratios (odds ratios) and 95% CIs were computed for exploring the association between the expression of lncRNA MIR31HG and the survival (pathological variables). Eleven studies with 1041 cases were enrolled into the current meta-analysis. Low expression of lncRNA MIR31HG showed correlation with the dismal overall survival, disease-free survival, high tumor stage and lymph node metastasis among patients with digestive system cancers. Low expression of lncRNA MIR31HG may serve as a potential novel factor to indicate the dismal prognosis and metastasis in patients with digestive system cancers.

Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation.

Background: Prediction of tumor consistency before surgery is of vital importance to determine individualized therapeutic schemes for patients with acromegaly. The present study was performed to noninvasively predict tumor consistency based on magnetic resonance imaging and radiomics analysis. Methods: In total, 158 patients with acromegaly were randomized into the primary cohort (n = 100) and validation cohort (n = 58). The consistency of the tumor was classified as soft or firm according to the neurosurgeon's evaluation. The critical radiomics features were determined using the elastic net feature selection algorithm, and the radiomics signature was constructed. The most valuable clinical characteristics were then selected based on the multivariable logistic regression analysis. Next, a radiomics model was developed using the radiomics signature and clinical characteristics, and 30 patients with acromegaly were recruited for multicenter validation of the radiomics model. The model's performance was evaluated based on the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, and other associated classification measures. Its calibration, discriminating capacity, and clinical usefulness were also evaluated. Results: The radiomics signature established according to four radiomics features screened in the primary cohort exhibited excellent discriminatory capacity in the validation cohort. The radiomics model, which incorporated both the radiomics signature and Knosp grade, displayed favorable discriminatory capacity and calibration, and the AUC was 0.83 (95% confidence interval, 0.81-0.85) and 0.81 (95% confidence interval, 0.78-0.83) in the primary and validation cohorts, respectively. Furthermore, compared with the clinical characteristics, the as-constructed radiomics model is more effective in prediction of the tumor consistency in patients with acromegaly. Moreover, the multicenter validation and decision curve analysis suggested that the radiomics model was clinically useful. Conclusions: This radiomics model can assist neurosurgeons in predicting tumor consistency in patients with acromegaly before surgery and facilitates the determination of individualized therapeutic schemes.