Ve Values Research Articles

Association of dynamic susceptibility contrast- and dynamic contrast-enhanced magnetic resonance imaging parameters with molecular marker status in lower-grade gliomas: A retrospective study.

Molecular marker status is clinically relevant for treatment planning and predicting the prognosis of gliomas. This study aimed to assess whether quantitative imaging parameters from dynamic susceptibility contrast- (DSC-) and dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) can predict the molecular marker status of lower-grade gliomas (LGGs). Overall, 132 patients with LGGs who underwent DSC- and DCE-MRI were retrospectively enrolled. Statuses of relevant molecular markers including isocitrate dehydrogenase isoenzyme (IDH), 1p19q codeletion, epidermal growth factor receptor (EGFR), O6-methylguanine-DNA methyltransferase (MGMT), and telomerase reverse transcriptase (TERT) were collected. For each molecular marker, age, tumor diameter and location, and DSC- and DCE-MRI parameters, including the normalized cerebral blood volume (nCBV), volume transfer constant (Ktrans), rate transfer coefficient (Kep), extravascular extracellular volume fraction (Ve), and plasma volume fraction (Vp), were compared. Multivariable logistic regression analyses were performed. The nCBV was significantly lower in LGGs with IDH mutation (p = .001) and TERT mutation (p = .027) than those without these mutations. Ktrans (p = .034), Ve (p = .023), and Vp (p = .044) values were significantly lower in MGMT methylated LGGs than in MGMT unmethylated LGGs. Perfusion parameters were not significantly associated with EGFR amplification and 1p19q codeletion. Young age (p < .001) and small diameter (p = .001) were significantly associated with IDH mutation. The nCBV was independently associated with IDH status (AUC, 0.817; 95% CI: 0.739-0.894). DSC- and DCE-MRI parameters demonstrated correlations with molecular markers of LGGs. Especially, the nCBV can be helpful in predicting the IDH mutation status.

New Cluster Analysis Method for Quantitative Dynamic Contrast-Enhanced MRI Assessing Tumor Heterogeneity Induced by a Tumor-Microenvironmental Ameliorator (E7130) Treatment to a Breast Cancer Mouse Model.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can provide insight into tumor perfusion. However, a method that can quantitatively measure the intra-tumor distribution of tumor voxel clusters with a distinct range of Ktrans and ve values remains insufficiently explored. Two-dimensional cluster analysis may quantify the distribution of a tumor voxel subregion with a distinct range of Ktrans and ve values in human breast cancer xenografts. Prospective longitudinal study. Twenty-two female athymic nude mice with MCF-7 xenograft, treated with E7130, a tumor-microenvironmental ameliorator, or saline. 9.4 Tesla, turbo rapid acquisition with relaxation enhancement, and spoiled gradient-echo sequences. We performed two-dimensional k-means clustering to identify tumor voxel clusters with a distinct range of Ktrans and ve values on Days 0, 2, and 5 after treatment, calculated the ratio of the number of tumor voxels in each cluster to the total number of tumor voxels, and measured the normalized distances defined as the ratio of the distance between each tumor voxel and the nearest tumor margin to a tumor radius. Unpaired t-tests, Dunnett's multiple comparison tests, and Chi-squared test were used. The largest and second largest clusters constituted 44.4% and 27.5% of all tumor voxels with cluster centroid values of Ktrans at 0.040 min-1 and 0.116 min-1 , and ve at 0.131 and 0.201, respectively. At baseline (Day 0), the average normalized distances for the largest and second largest clusters were 0.33 and 0.24, respectively. E7130-treated group showed the normalized distance of the initial largest cluster decreasing to 0.25, while that of the second largest cluster increasing to 0.31. Saline-treated group showed no change. A two-dimensional cluster analysis might quantify the spatial distribution of a tumor subregion with a distinct range of Ktrans and ve values. 1 TECHNICAL EFFICACY: Stage 1.

Evaluation of the Effects of Anti-PD-1 Therapy on Triple-Negative Breast Cancer in Mice by Diffusion Kurtosis Imaging and Dynamic Contrast-Enhanced Imaging.

The monitoring of immunotherapies is still based on changes in the tumor size in imaging, with a long evaluation period and low sensitivity. To investigate the effectiveness of diffusion kurtosis imaging (DKI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing the therapeutic efficacy of anti-programmed death-1 (PD-1) therapy in a mouse triple negative breast cancer (TNBC) model. Prospective. A total of 54 BALB/c mouse subcutaneous 4T1 transplantation models of TNBC. A 3.0-T; turbo spin echo (TSE) T2-weighted imaging, DKI with seven b values (0, 500, 1000, 1500, 2000, 2500, and 3000 sec/mm2 ) and T1-twist DCE acquisition series. DKI and DCE-MRI parameters were evaluated by two radiologists independently. Regions of interest (ROIs) were drawn manually on the maximum cross-sectional area of the lesion; care was taken to avoid necrotic areas. The tumor cell density, the CD45 and CD31 levels were analyzed by two pathologists. The two-tailed unpaired t-test, Mann-Whitney U test, Fisher's exact test and Pearson correlation coefficient were performed. A P< 0.05 was considered statistically significant. The apparent diffusion coefficient (ADC), mean diffusivity (MD), Ktrans and Kep values were significantly different between the two groups at each time point after treatment. There were significant differences in the mean kurtosis (MK) and Ve values between the two groups at 5 and 10 days after treatment but no significant differences at 15 days (P=0.317 and 0.183, respectively). The ADC and MD values were significantly correlated with tumor cell density (ADC, r=-0.833; MD, r=0.890) and the CD45 level (ADC, r=0.720; MD, r=0.718). The Ktrans and Kep values were significantly correlated with the CD31 level (Ktrans , r=0.820; Kep , r=0.683). DKI and DCE-MRI could reflect the changes in tumor microstructure and tumor tissue vasculature after anti-PD-1 therapy, respectively. 1 TECHNICAL EFFICACY: Stage 4.

Diagnostic Value of DCE-MRI and Tofts Model in Children with Unilateral Hydronephrosis.

Hydronephrosis is a common condition, and the correct diagnosis of hydronephrosis is necessary to improve the early diagnosis rates of pediatric hydronephrosis. The objective of this study is to explore and analyze the diagnostic value of dynamic contrast- enhanced magnetic resonance imaging (DCE-MRI) analyzed using the Tofts model in children with unilateral hydronephrosis. We retrospectively selected data from 88 children with unilateral hydronephrosis treated in our hospital from September 2018 to October 2020. Routine and DCE-MR renal image indexes were collected and their pharmacokinetic variables were calculated based on the Tofts model to compare kinetic parameters of affected and normal kidney. We compared the renal parenchymal thickness and other renal function indexes in children with different degrees of hydronephrosis, and drew receiver operating characteristic (ROC) curves to evaluate the diagnostic value of this approach in children with hydronephrosis. The Ktrans, Kep, and Ve values in the diseased kidneys were lower than those in the normal ones (P<0.05). The thickness of the healthy renal parenchyma in children with severe hydronephrosis was higher than in children with moderate and mild hydronephrosis, but the renal parenchyma thickness and the thickness ratio of renal parenchyma on the affected side were lower than those in children with moderate and mild hydronephrosis (P<0.05). Sensitivity, specificity and accuracy of DCE-MRI and Tofts model in the diagnosis of hydronephrosis in children were higher than those of a single DCE-MRI (P<0.05). The area under the ROC curve for the DCE-MRI and Tofts model approach for the diagnosis of hydronephrosis in children was 0.789 (95% CI, 0.72-0.859), and the sensitivity and specificity were 86.36% and 71.59%, respectively. DCE-MRI and Tofts model can provide a clear picture of renal morphology, and renal function evaluation parameters. They have high sensitivity and specificity in the diagnosis of hydronephrosis in children.

Arterial input function for quantitative dynamic contrast-enhanced MRI to diagnose prostate cancer.

PURPOSE This study aims to analyze the ability of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to distinguish between prostate cancer (PCa) and benign lesions in transition zone (TZ) and peripheral zone (PZ) using different methods for arterial input function (AIF) determination. Study endpoints are identification of a standard AIF method and optimal quantitative perfusion parameters for PCa detection. METHODS DCE image data of 50 consecutive patients with PCa who underwent multiparametric MRI were analyzed retrospectively with three different methods of AIF acquisition. First, a region of interest was manually defined in an artery (AIFm); second, an automated algorithm was used (AIFa); and third, a population-based AIF (AIFp) was applied. Values of quantitative parameters after Tofts (Ktrans, ve, and kep) in PCa, PZ, and TZ in the three different AIFs were analyzed. RESULTS Ktrans and kep were significantly higher in PCa than in benign tissue independent from the AIF method. Whereas in PZ, Ktrans and kep could differentiate PCa (P < .001), in TZ only kep using AIFpdemonstrated a significant difference (P = .039). The correlations of the perfusion parameters that resulted from AIFm and AIFa were higher than those that resulted from AIFp, and the absolute values of Ktrans, kep, and ve were significantly lower when using AIFp. The values of quantitative perfusion parameters for PCa were similar regardless of whether PCa was located in PZ or TZ. CONCLUSION Ktrans and kep were able to differentiate PCa from benign PZ independent of the AIF method. AIFaseems to be the most feasible method of AIF determination in clinical routine. For TZ, none of the quantitative perfusion parameters provided satisfying results.

Quantitative Dynamic-Enhanced MRI and Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Prediction of the Pathological Response to Neoadjuvant Chemotherapy and the Prognosis in Locally Advanced Gastric Cancer.

BackgroundThis study aimed to explore the predictive value of quantitative dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) quantitative parameters for the response to neoadjuvant chemotherapy (NCT) in locally advanced gastric cancer (LAGC) patients, and the relationship between the prediction results and patients’ prognosis, so as to provide a basis for clinical individualized precision treatment.MethodsOne hundred twenty-nine newly diagnosed LAGC patients who underwent IVIM-DWI and DCE-MRI pretreatment were enrolled in this study. Pathological tumor regression grade (TRG) served as the reference standard of NCT response evaluation. The differences in DCE-MRI and IVIM-DWI parameters between pathological responders (pR) and pathological non-responders (pNR) groups were analyzed. Univariate and multivariate logistic regressions were used to identify independent predictive parameters for NCT response. Prediction models were built with statistically significant quantitative parameters and their combinations. The performance of these quantitative parameters and models was evaluated using receiver operating characteristic (ROC) analysis. Clinicopathological variables, DCE-MRI and IVIM-DWI derived parameters, as well as the prediction model were analyzed in relation to 2-year recurrence-free survival (RFS) by using Cox proportional hazards model. RFS was compared using the Kaplan–Meier method and the log-rank test.ResultsSixty-nine patients were classified as pR and 60 were pNR. Ktrans, kep, and ve values in the pR group were significantly higher, while ADCstandard and D values were significantly lower than those in the pNR group. Multivariate logistic regression analysis demonstrated that Ktrans, kep, ve, and D values were independent predictors for NCT response. The combined predictive model, which consisted of DCE-MRI and IVIM-DWI, showed the best prediction performance with an area under the curve (AUC) of 0.922. Multivariate Cox regression analysis showed that ypStage III and NCT response predicted by the IVIM-DWI model were independent predictors of poor RFS. The IVIM-DWI model could significantly stratify median RFS (52 vs. 15 months) and 2-year RFS rate (72.3% vs. 21.8%) of LAGC.ConclusionPretreatment DCE-MRI quantitative parameters Ktrans, kep, ve, and IVIM-DWI parameter D value were independent predictors of NCT response for LAGC patients. The regression model based on baseline DCE-MRI, IVIM-DWI, and their combination could help RFS stratification of LAGC patients.

Feasibility of Intravoxel Incoherent Motion (IVIM) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in Differentiation of Benign Parotid Gland Tumors.

Simple SummaryMultiparametric magnetic resonance imaging gains recognition in the diagnostic algorithm of salivary gland tumors, providing data from different diffusion-weighted imaging (DWI) models and dynamic contrast enhanced sequences (DCE-MRI). The aim of this prospective study is to identify quantitative intravoxel incoherent motion and DCE-MRI parameters of the most frequent benign parotid tumors, pleomorphic adenomas and Warthin tumors, to compare their utility and diagnostic accuracy. With a precise pre-treatment diagnostic tool, patients can potentially avoid unnecessary diagnostic procedures and be offered optimal treatment. Aim: The aim of this prospective study is to identify quantitative intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging parameters of the most frequent benign parotid tumors, compare their utility and diagnostic accuracy. Methods: The study group consisted of 52 patients with 64 histopathologically confirmed parotid focal lesions. Parametric maps representing apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (FP) and transfer constant (Ktrans), reflux constant (Kep), extra-vascular extra-cellular volume fraction (Ve), and initial area under curve in 60 s (iAUC) have been obtained from multiparametric MRI. Results: Statistically significant (p < 0.001) inter-group differences were found between pleomorphic adenomas (PA) and Warthin tumors (WT) in all tested parameters but iAUC. Receiver operating characteristic curves were constructed to determine the optimal cut-off levels of the most significant parameters allowing differentiation between WT and PA. The Area Under the Curve (AUC) values and thresholds were for ADC: 0.931 and 1.05, D: 0.896 and 0.9, Kep: 0.964 and 1.1 and Ve: 0.939 and 0.299, respectively. Lesions presenting with a combination of ADC, D, and Ve values superior to the cut-off and Kep values inferior to the cut-off are classified as pleomorphic adenomas. Lesions presenting with combination of ADC, D, and Ve values inferior to the cut-off and Kep values superior to the cut-off are classified as Warthin tumors. Conclusions: DWI, IVIM and quantitative analysis of DCE-MRI derived parameters demonstrated distinctive features of PAs and WT and as such they seem feasible in differentiation of benign parotid gland tumors.

Dynamic contrast-enhanced MRI in malignant pleural mesothelioma: prediction of outcome based on DCE-MRI measurements in patients undergoing cytotoxic chemotherapy

BackgroundThe malignant pleural mesothelioma (MPM) response rate to chemotherapy is low. The identification of imaging biomarkers that could help guide the most effective therapy approach for individual patients is highly desirable. Our aim was to investigate the dynamic contrast-enhanced (DCE) MR parameters as predictors for progression-free (PFS) and overall survival (OS) in patients with MPM treated with cisplatin-based chemotherapy.MethodsThirty-two consecutive patients with MPM were enrolled in this prospective study. Pretreatment and intratreatment DCE-MRI were scheduled in each patient. The DCE parameters were analyzed using the extended Tofts (ET) and the adiabatic approximation tissue homogeneity (AATH) model. Comparison analysis, logistic regression and ROC analysis were used to identify the predictors for the patient’s outcome.ResultsPatients with higher pretreatment ET and AATH-calculated Ktrans and ve values had longer OS (P≤.006). Patients with a more prominent reduction in ET-calculated Ktrans and kep values during the early phase of chemotherapy had longer PFS (P =.008). No parameter was identified to predict PFS. Pre-treatment ET-calculated Ktrans was found to be an independent predictive marker for longer OS (P=.02) demonstrating the most favourable discrimination performance compared to other DCE parameters with an estimated sensitivity of 89% and specificity of 78% (AUC 0.9, 95% CI 0.74-0.98, cut off > 0.08 min-1).ConclusionsIn the present study, higher pre-treatment ET-calculated Ktrans values were associated with longer OS. The results suggest that DCE-MRI might provide additional information for identifying MPM patients that may respond to chemotherapy.

ADAPTOR MESIN PENCACAH SAMPAH PLASTIK

Plastic waste is a material that is difficult to decompose when buried in the ground. The large amount of plastic waste from human activities can cause environmental pollution. The reason for designing this plastic trash chopper is because the price of machines that have been marketed has an expensive price. Prices on the market range from around Rp. 18.000.000 to Rp. 30.000.000 depending on the engine specifications. In addition to the price of the machine i tu own, reasons that become the background count tool design plastic waste is due to concerns about trash, especially plastic waste in the city of Palembang, which until now still cannot be solved by optimal. To overcome these problems, a redesign of a plastic trash chopper was carried out using the Value Engineering method. From the results of research and analysis is known that p e designof the machine counter trash plastic the profit that as many as 8 benefit with b iaya value of VE were issued at 5.44. The total costs incurred after the redesign was carried out, amounting to Rp.1.470 .000.

The correlations between dynamic contrast enhanced magnetic resonance imaging and immunohistochemical data in head and neck squamous cell carcinomas.

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) can in vivo characterize tumor microvascular environment. The aim of the present study was to reveal the DCE-MRI findings and to determine the correlation between these findings and immunohistochemical data in head and neck squamous cell carcinoma (HNSCC). Thirty-three patients diagnosed with primary HNSCC were evaluated retrospectively. DCE-MRI was conducted in all cases. CD34, CD105, and ki-67 expressions were analyzed with immunohistochemistry in tissue sections to determine micro-vessel density and proliferative activity. The DCE-MRI is a successful technique in distinguishing tumor tissue from normal tissue. It was determined that Ve, Ktrans, and ki-67 values were significantly higher in high-stage tumors and there were positive correlations between the Ktrans value (by standard ROI) and CD34 MVDmax and CD34 MVDmean values. No statistically significant correlation was determined between other parameters in DCE-MRI and immunohistochemical data, and T stage. DCE-MRI could successfully differentiate tumor tissue in HNSCC. Furthermore, it was observed that DCE-MRI had the potential to reveal certain immunohistochemical information in vivo.

The Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in the Differentiation of Pseudoprogression and Recurrence of Intracranial Gliomas.

Objective The objective of this study was to determine the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing postoperative changes in intracranial gliomas. Method A total of fifty-one patients who had new enhanced lesions after surgical resection followed by standard radiotherapy and chemotherapy were collected retrospectively from October 2014 to June 2021. The patients were divided into a pseudoprogression group (15 cases) and a recurrence group (36 cases) according to the pathological results of the second operation or a follow-up of more than six months. The follow-up data of all patients were complete, and DCE-MRI was performed. The images were processed to obtain the quantitative parameters Ktrans, Ve, and Kep and the semiquantitative parameter iAUC, which were analysed with relevant statistical software. Results First, the difference in Ktrans and iAUC values between the two groups was statistically significant (P < 0.05), and the difference in Ve and Kep values was not statistically significant (P > 0.05). Second, by comparing the area under the curve, threshold, sensitivity and specificity of Ktrans, and iAUC, it was found that the iAUC threshold value was slightly higher than that of Ktrans, and the specificity of Ktrans was equal to that of iAUC, while the area under the curve and sensitivity of Ktrans were higher than those of iAUC. Third, Ktrans and iAUC had high accuracy in diagnosing recurrence and pseudoprogression, and Ktrans had higher accuracy than iAUC. Conclusion In this study, DCE-MRI has a certain diagnostic value in the early differentiation of recurrence and pseudoprogression, offering a new method for the diagnosis and assessment of gliomas after surgery.

Quantitative Evaluation of Extramural Vascular Invasion of Rectal Cancer by Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

This study was carried out to explore the preoperative predictive value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in extramural vascular invasion (EMVI) in patients with rectal cancer. 124 patients with rectal cancer were randomly divided into two groups, with 62 groups in each group. One group used conventional magnetic resonance imaging (MRI) and was recorded as the control group. The other group used DCE-MRI and was recorded as the experimental group. The diagnostic value was evaluated by comparing the MRI quantitative parameters of EMVI positive and EMVI negative patients, as well as the area under the curve (AUC) of the receiver operating characteristic curve (ROC), diagnostic sensitivity, and specificity of the two groups. The results showed that the Ktrans and Ve values of EMVI positive patients in the experimental group and the control group were 1.08 ± 0.97 and 1.03 ± 0.93, and 0.68 ± 0.29 and 0.65 ± 0.31, respectively, which were significantly higher than those in EMVI negative patients (P < 0.05). The AUC of EMVI diagnosis in the experimental group and the control group were 0.732 and 0.534 (P < 0.05), the sensitivity was 0.913 and 0.765 (P < 0.05), and the specificity was 0.798 and 0.756 (P > 0.05), respectively. In conclusion, DCE-MRI has a higher diagnostic value than conventional MRI in predicting EMVI in patients with rectal cancer, which was worthy of further clinical promotion.

Added-value of dynamic contrast-enhanced MRI on prediction of tumor recurrence in locally advanced cervical cancer treated with chemoradiotherapy.

To evaluate whether the DCE-MRI derived parameters integrated into clinical and conventional imaging variables may improve the prediction of tumor recurrence for locally advanced cervical cancer (LACC) patients following concurrent chemoradiotherapy (CCRT). Between March 2014 and November 2019, 79 consecutive LACC patients who underwent pelvic MRI examinations with DCE-MRI sequence before treatment were prospectively enrolled. The primary outcome was disease-free survival (DFS). DCE-MRI derived parameters, conventional imaging, and clinical factors were collected. Univariate and multivariate Cox hazard regression analyses were performed to evaluate these parameters in the prediction of DFS. The independent and prognostic interested variables were combined to build a prediction model compared with the clinical International Federation of Gynecological (FIGO) staging system. Lymph node metastasis (LNM) and the mean value of ve (ve_mean) were independently associated with tumor recurrence (all p < 0.05). The prediction model based on T stage, LNM, and ve_mean demonstrated a moderate predictive capability in identifying LACC patients with a high risk of tumor recurrence; the model was more accurate than the FIGO staging system alone (c-index: 0.735 vs. 0.661) and the combination of ve_mean and the FIGO staging system (c-index: 0.735 vs. 0.688). Moreover, patients were grouped into low-, medial-, and high-risk levels based on the advanced T stage, positive LNM, and ve_mean < 0.361, with which the 2-year DFS was significantly stratified (p < 0.001). The ve_mean from DCE-MRI could be used as a useful biomarker to predict DFS in LACC patients treated with CCRT as an assistant of LNM and T stage. Lower ve_mean is an independent predictor of poor prognosis for disease-free survival in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy (hazard ratio [HR]: 0.016, p<0.023). A combined prediction model based on advanced T stage, LNM, and ve_mean performed better than the FIGO staging system alone.

Evaluation of Angiogenesis and Pathological Classification of Extrahepatic Cholangiocarcinoma by Dynamic MR Imaging for E-Healthcare.

For staging cholangiocarcinoma and determining respectability, MR is an accurate noninvasive method which provides size of tumor and vascular patency information. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive inspection method for evaluating the vascular structure and functional characteristics of tumor tissue. However, some limitations should be noted about the technology. At present, the technology cannot be used alone, which is just an assisted method during the conventional MRI examination. 50 ECC patients, admitted to Indira Gandhi Medical College and Hospital between 2016 and 2019, were selected as research subjects. They were classified pathologically according to the Steiner classification system. After image processing, regions of interest (ROIs) were selected from the image to measure the rate constant (Kep), extravascular space volume fraction (Ve), and tissue volume transfer constant (Ktrans). There were 15 cases with highly differentiated carcinoma, 23 cases with moderately differentiated carcinoma, and 12 cases with lowly differentiated carcinoma. Non-VEGF expression was noted in 21 cases, with low expression noted in 15 cases, moderate expression noted in 14 cases, and no high expression case noted. The relevant parameters in the dynamic MRI image can quantitatively reflect the angiogenesis and pathological classification of ECC, which is suggested in the clinical treatment of ECC. The Ktrans, Kep, and Ve values of the ECC patients were all not associated with the pathological classification, with no significant difference (P < 0.05). Besides, due to the fact that the patient cannot completely hold his breath, the air leak reduces the image quality.

Predicting T and N Staging of Resectable Gastric Cancer According to Whole Tumor Histogram Analysis About a Non-Cartesian k-Space Acquisition DCE-MRI: A Feasibility Study.

ObjectiveTo explore the feasibility of the whole tumor histogram analysis parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) based on stack-of stars (StarVIBE) to predict T and N staging of resectable gastric cancer (GC).MethodsEighty-seven patients confirmed as GC by histopathology were enrolled in this prospective study. DCE-MRI were performed before surgery, and quantitative DCE parameters (Ktrans, Kep, Ve) and histogram metrics (Skewness, Kurtosis and Entropy) were measured by Omni-Kinetics software. Intraclass correlation coefficient (ICC) testing was used to determine the consistency of Ktrans, Kep and Ve values and histogram metrics values between two radiologists using Bland–Altman analysis. The quantitative DCE parameters or histogram metrics values between T stage or N stage were compared using ANOVA or Kruskal–Wallis testing. Receiver operating characteristic (ROC) analyses was performed to find out the best parameters for identifying T and N staging.ResultsThere was statistical difference in Ktrans, Kep, Ve and entropy to identify T staging (P=0.015, 0.033, <0.001, and 0.007, respectively), and in pairwise comparisons of Ve values showed statistically difference between T1+2 and T3 group (P<0.001), T1+2 and T4 group (P<0.001). There were statistical differences in Ve to identify N staging (P=0.041). In ROC analysis, Ve was the best parameter for identifying T staging (AUC: 0.788, the sensitivity and specificity was 0.929 and 0.578, respectively) and N staging (AUC: 0.590, the sensitivity and specificity was 0.714 and 0.899, respectively).ConclusionThe whole tumor histogram analysis parameters derived from StarVIBE DCE-MRI may be able to quantitatively evaluate T and N staging of GC, so as to help clinical treatment decision optimization.

Artificial Intelligence-Based Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Quantitative Evaluation of the Efficacy of Targeted Therapy for Liver Metastasis from Colon Cancer and Nursing

The purpose of this study was to quantitatively evaluate the targeted treatment and nursing effect of patients with liver metastasis of colon cancer by enhanced magnetic resonance imaging. First, Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) images were restored. 35 patients with liver metastases from colon cancer were selected as research subjects and treated by bevacizumab, and high-quality nursing methods were used to improve the psychophysiology of the patients. Enhanced CT examination and DCE-MRI scan were performed before and after the treatment. After the image was processed by the artificial intelligence algorithm, apparent diffusion coefficient (ADC), measurement transmission constant (Ktrans), reflux constant (Kep), extravascular extracellular volume fraction (Ve), and other data on the image were recorded. Two months after the treatment, 35 patients were divided into effective and ineffective groups. It was found that, after treatment, the Kep value and Ktrans value of the effective group were significantly reduced, showing statistically significant differences, and the P value was less than 0.05, and the Kep value and Ktrans value of the ineffective group showed no significant changes. The Ve value of the two groups gradually decreased with the progress of the treatment. In the effective group, the Ve values before the treatment, on the third day after the treatment, and on the seventh day after treatment were (0.235 ± 0.134), (0.338 ± 0.116), and (0.457 ± 0.097), respectively. Compared with the Ve values of the ineffective group, there was a statistical difference, F = 3.592, P = 0.0245 ; the ADC value was negatively correlated with the Ktrans and Kep values, and the results were statistically significant. It was concluded that the above indicators are effective in evaluating the efficacy of the targeted therapy of liver metastasis from colon cancer, and DCE-MRI is of great significance in predicting the efficacy of targeted therapy of liver metastasis from colon cancer.

Quantitative dynamic contrast-enhanced MRI and readout segmentation of long variable echo-trains diffusion-weighted imaging in differentiating parotid gland tumors.

To evaluate the ability of quantitative dynamic contrast-enhanced (DCE)-MRI and readout segmentation of long variable echo-trains diffusion-weighted imaging (RESOLVE-DWI) in differentiating parotid tumors (PTs) with different histological types. In this retrospective study, 123 patients with 145 histologically proven PTs who underwent both RESOLVE-DWI and DCE-MRI were enrolled including 51 pleomorphic adenomas (PAs), 52 Warthin's tumors (WTs), 27 other benign neoplasms (OBNs), and 15 malignant tumors (MTs). Quantitative parameters of DCE-MRI (Ktrans, Kep, and Ve) and the apparent diffusion coefficient (ADC) of lesions were calculated and analyzed. Kruskal-Wallis tests with Dunn-Bonferroni correction, logistic regression analyses, and receiver operating characteristic curve were used for statistical analyses. PAs exhibited a lowest Ktrans among these four PTs. WTs demonstrated the highest Kep and lowest Ve values. WTs and MTs showed lower ADCmin values than PAs and OBNs. The combination of Kep and Ve provided 98.1% sensitivity, 85% specificity, and 98.7% accuracy for differentiating WTs from the other three PTs. The ADCmin cutoff value of ≤ 0.826 yielded 80.0% sensitivity, 92.3% specificity, and 90.3% accuracy for the differentiation of MTs from PAs and OBNs. Ktrans with a cutoff value of ≤ 0.185 achieved a sensitivity, specificity, and accuracy of 84.3, 70.4, and 79.5%, respectively, for discriminating PAs from OBNs. The combination of quantitative DCE-MRI and RESOLVE-DWI is beneficial for characterizing four histological types of PTs.

Use of heart rate variability to predict hospital length of stay for COVID-19 patients: A prospective observational study.

Background:As the COVID-19 pandemic continues, determining hospital demands has become a vital priority. Heart rate variability (HRV) has been linked to both the presence of viral infection and its severity. We investigate the possibility of using HRV parameters in comparison to other clinical parameters for predicting the hospital length of stay (LOS) for COVID-19 patients.Methods:This was a population-based cohort study. Measurements were performed in a specialized hospital for respiratory disease, dedicated to COVID-19. Patients were polymerase chain reaction positive for COVID-19 and on their 1st day of admission. Heart period, respiratory sinus arrhythmia (RSA), low frequency (LF) HRV, and vagal efficiency were calculated from electrocardiogram signals. This study investigated the correlation of HRV, demographic, and laboratory parameters with hospital LOS.Results:Forty-one participants were recruited, with a significant relationship, observed between hospital LOS and some demographic and clinical parameters such as lymphocyte count, age, and oxygen saturation of arterial blood. There was a negative relationship between LF and hospital LOS (r = −0.53, 95% confidence interval: −0.73, −0.24). Higher vagal efficiency predicted shorter hospital LOS in patients younger than 40 years of age (19.27% shorter hospital LOS was associated with a one SD higher value of VE, P = 0.007).Conclusion:HRV measurement is a non-invasive, inexpensive, and scalable procedure that produces several metrics, some of which are useful for predicting hospital LOS and managing treatment resources during COVID-19 pandemic.

Comparison between high-frequency irreversible electroporation and irreversible electroporation ablation of small swine liver: follow-up of DCE-MRI and pathological observations.

Background:High-frequency irreversible electroporation (H-FIRE) is a novel, next-generation nanoknife technology with the advantage of relieving irreversible electroporation (IRE)-induced muscle contractions. However, the difference between IRE and H-FIRE with distinct ablation parameters was not clearly defined. This study aimed to compare the efficacy of the two treatments in vivo.Methods:Ten Bama miniature swine were divided into two group: five in the 1-day group and five in the 7-day group. The efficacy of IRE and H-FIRE ablation was compared by volume transfer constant (Krans), rate constant (Kep) and extravascular extracellular volume fraction (Ve) value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), size of the ablation zone, and histologic analysis. Each animal underwent the IRE and H-FIRE. Temperatures of the electrodes were measured during ablation. DCE-MRI images were obtained 1, 4, and 7 days after ablation in the 7-day group. All animals in the two groups were euthanized 1 day or 7 days after ablation, and subsequently, IRE and H-FIRE treated liver tissues were collected for histological examination. Student's t test or Mann-Whitney U test was applied for comparing any two groups. One-way analysis of variance (ANOVA) test and Welch's ANOVA test followed by Holm-Sidak's multiple comparisons test, one-way ANOVA with repeated measures followed by Bonferroni test, or Kruskal-Wallis H test followed by Dunn's multiple comparison test was used for multiple group comparisons and post hoc analyses. Pearson correlation coefficient test was conducted to analyze the relationship between two variables.Results:Higher Ve was seen in IRE zone than in H-FIRE zone (0.14 ± 0.02 vs. 0.08 ± 0.05, t = 2.408, P = 0.043) on day 4, but no significant difference was seen in Ktrans or Kep between IRE and H-FIRE zones at all time points (all P > 0.05). For IRE zone, the greatest Ktrans was seen on day 7, which was significantly higher than that on day 1 (P = 0.033). The ablation zone size of H-FIRE was significantly larger than IRE 1 day (4.74 ± 0.88 cm2vs. 3.20 ± 0.77 cm2, t = 3.241, P = 0.009) and 4 days (2.22 ± 0.83 cm2vs. 1.30 ± 0.50 cm2, t = 2.343, P = 0.041) after treatment. Apoptotic index (0.05 ± 0.02 vs. 0.73 ± 0.06 vs. 0.68 ± 0.07, F = 241.300, P < 0.001) and heat shock protein 70 (HSP70) (0.03 ± 0.01 vs. 0.46 ± 0.09 vs. and 0.42 ± 0.07, F = 64.490, P < 0.001) were significantly different between the untreated, IRE and H-FIRE zones, but no significant difference was seen in apoptotic index or HSP70 between IRE and H-FIRE zone (both P > 0.05). Electrode temperature variations were not significantly different between the two zones (18.00 ± 3.77°C vs. 16.20 ± 7.45°C, t = 0.682, P = 0.504). The Ktrans value (r = 0.940, P = 0.017) and the Kep value (r = 0.895, P = 0.040) of the H-FIRE zone were positively correlated with the number of hepatocytes in the ablation zone.Conclusions:H-FIRE showed a comparable ablation effect to IRE. DCE-MRI has the potential to monitor the changes of H-FIRE ablation zone.

Can quantitative analysis of multi-parametric MRI independently predict failure of focal salvage HIFU therapy in men with radio-recurrent prostate cancer?

ObjectivesFocal salvage HIFU is a feasible therapeutic option in some men who have recurrence after primary radiotherapy for prostate cancer. We aimed to determine if multi-parametric quantitative parameters, in addition to clinical factors, might have a role in independently predicting focal salvage HIFU outcomes. MethodsA retrospective registry analysis included 150 consecutive men who underwent focal salvage HIFU (Sonablate500) (2006-2015); 89 had mpMRI available. Metastatic disease was excluded by nodal assessment on pelvic MRI, a radioisotope bone-scan and/or choline or FDG PET/CT scan. All men had mpMRI and either transperineal template prostate mapping biopsy or targeted and systematic TRUS-biopsy. mpMRI included T2‐weighted, diffusion‐weighted and dynamic contrast‐enhancement. Pre-HIFU quantitative mpMRI data was obtained using Horos DICOM Viewer v3.3.5 for general MRI parameters and IB DCE v2.0 plug-in. Progression-free survival (PFS) was defined by biochemical failure and/or positive localized or distant imaging results and/or positive biopsy and/or systemic therapy and/or metastases/prostate cancer‐specific death. Potential predictors of PFS were analyzed by univariable and multivariable Cox-regression. ResultsMedian age at focal salvage HIFU was 71 years (interquartile range [IQR] 65–74.5) and median PSA pre-focal salvage treatment was 5.8ng/ml (3.8-8). Median follow-up was 35 months (23-47) and median time to failure was 15 months (7.8–24.3). D-Amico low, intermediate and high-risk disease was present in 1% (1/89), 40% (36/89) and 43% (38/89) prior to focal salvage HIFU (16% missing data). 56% (50/89) failed by the composite outcome. A total of 22 factors were evaluated on univariable and 8 factors on multivariable analysis. The following quantitative parameters were included: Ktrans, Kep, Ve, Vp, IS, rTTP and TTP. On univariable analysis, PSA, prostate volume at time of radiotherapy failure and Ve (median) value were predictors for failure. Ve represents extracellular fraction of the whole tissue volume. On multivariable analysis, only Ve (median) value remained as an independent predictor. ConclusionsOne pharmacokinetic quantitative parameter based on DCE sequences seems to independently predict failure following focal salvage HIFU for radio-recurrent prostate cancer. This likely relates to the tumor microenvironment producing heat-sinks which counter the heating effect of HIFU. Further validation in larger datasets and evaluating mechanisms to reduce heat-sinks are required.