Effect of Liver Segments and Hepatic Fibrosis Grade on Repeatability, Reliability, and Diagnostic Efficiency of Intravoxel Incoherent Motion.

BACKGROUND: Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) is considered a potential marker of hepatic fibrosis (HF). OBJECTIVE: To explore the influencing factors of repeatability and reliability in IVIM-DWI parameters of ROI-based liver segments in participants with HF and healthy volunteers (HV) and to assess the diagnostic efficiency of these parameters in HF. METHODS: Participants with early HF (EHF, n=59) or advanced HF (AHF, n=38) and HV (n=48) were recruited. Two examiners measured IVIM data using mono-, bi-exponential and stretched exponential models. The results and influencing factors of repeatability and reliability of IVIM-DWI, and the diagnostic efficiency were analyzed. RESULTS: The repeatability of D* (CV: 26.62-41.47%) and DDC (CV: 18.01-34.40%) was poor, the repeatability of ADC (CV: 4.95-9.76%), D (CV: 7.09-15.52%), f (CV: 9.35-17.15%), and α (CV: 7.48-13.81%) was better; ordered logistic regression showed statistically significant results of IVIM-derived parameters; the reliability showed no obvious trend, and ordered logistic regression showed statistically significant results of IVIMderived parameters, groups, and partial hepatic segments (all p<0.001). IVIM-derived parameters with relatively good repeatability (CV<20%) and reliability (ICC>0.4) were used to establish regression models for differential diagnosis. The AUC of regression models was 0.744-0.783 (EHF vs. AHF), but no statistically significant parameters were found in the HV vs EHF comparison. CONCLUSION: IVIM-derived parameters were the most important factors affecting the repeatability and reliability, while staging of HF and hepatic segments may be the influencing factors of reliability. IVIM-derived parameters showed medium diagnostic efficiency in distinguishing between EHF and AHF.

Analytical and Clinical Evaluation of a Chemiluminescent Immunoassay to Detect Serum Chitinase-3-like Protein 1 in HBV-Related Liver Diseases.

Serum chitinase-3-like protein 1 (CHI3L1) is a diagnostic marker for liver diseases, such as hepatocellular carcinoma (HCC). Herein, we aimed to evaluate the analytical performance of a chemiluminescent immunoassay (CLIA) for the quantitative detection of CHI3L1 and its application in hepatitis B virus (HBV)-related liver diseases. The CLIA for CHI3L1 detection presented good analytical performance, with a linear range of 1.50-2000.00 ng/mL and a detection limit of 0.98 ng/mL. To evaluate its clinical application, serum CHI3L1 levels were detected in 82 patients with chronic hepatitis B (CHB) and in 21 healthy controls. The patients with CHB and HCC had higher CHI3L1 levels than the healthy controls and the patients with CHB without HCC. However, CHI3L1 levels did not change significantly with the increase in liver fibrosis stages. The area under the receiver operating characteristic curve for the diagnosis of HBV-related HCC was 0.808, representing a moderate diagnostic value. Correlation analysis revealed a significant association between CHI3L1 and alpha-fetoprotein (AFP) levels, the fibrosis-4 (FIB-4) index, and the aspartate aminotransferase-to-platelet ratio index (APRI). In conclusion, compared with currently reported methods for CHI3L1 detection, the CLIA has a high sensitivity, a wide linear range, and an acceptable accuracy, precision, and reference intervals, making it valuable in the diagnosis of HBV-related HCC.

Field-of-view optimized and constrained undistorted single shot intravoxel incoherent motion diffusion-weighted imaging of the cervix during the menstrual cycle: A prospective study.

OBJECTIVE: To provide insight into the biological characteristics of the healthy cervix by defining intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters across the menstrual cycle. METHODS: Forty-three females of reproductive age (18-45 years old) were included in this prospective study. Conventional magnetic resonance imaging (MRI) and IVIM-DWI scans were performed at multiple time-points across the menstrual cycle: T1 (menses), T2 (follicular phase), T3 (luteal phase). Intra- and interobserver repeatability of the IVIM-DWI values were evaluated with intraclass correlation coefficients (ICC), and D* was excluded from the analyses due to poor repeatability. Differences in each IVIM-DWI parameter among T1, T2, and T3 were explored. Subjects were stratified by age and parity for subgroup analyses (younger [18 - < 30 years] vs. older [≥30-45 years]; parity 0 vs. parity 1 and 2). Correlations between subject age and IVIM-DWI parameters were assessed. The overlap for each IVIM-DWI parameter among T1, T2, and T3 was evaluated. RESULTS: ADC and D values of the cervix were significantly lower at T3 compared with T1 (p = 0.02 and 0.03) or T2 (p < 0.01 and < 0.01). In younger subjects (n = 26), ADC and D values were significantly lower at T3 compared with T1 (p < 0.01 and p = 0.02) or T2 (p = 0.03 and p = 0.04). In older subjects (n = 17), ADC values were significantly higher at T2 compared with T1 (p = 0.01) or T3 (p = 0.01). There were significant differences in ADC values at T1 in subgroup analyses stratified by age and parity (both p < 0.01). There was a moderate correlation between age and ADC values at T1. Overlap for IVIM-DWI parameters across the menstrual cycle was >50%. CONCLUSION: ADC and D values of the heathy cervix differed across the menstrual cycle. Age and parity may influence the ADC value.

Cystic renal mass screening: machine-learning-based radiomics on unenhanced computed tomography.

PURPOSE: The present study compares the diagnostic performance of unenhanced computed tomography (CT) radiomics-based machine learning (ML) classifiers and a radiologist in cystic renal masses (CRMs). METHODS: Patients with pathologically diagnosed CRMs from two hospitals were enrolled in the study. Unenhanced CT radiomic features were extracted for ML modeling in the training set (Guangzhou; 162 CRMs, 85 malignant). Total tumor segmentation was performed by two radiologists. Features with intraclass correlation coefficients of >0.75 were screened using univariate analysis, least absolute shrinkage and selection operator, and bidirectional elimination to construct random forest (RF), decision tree (DT), and k-nearest neighbor (KNN) models. External validation was performed in the Zhuhai set (45 CRMs, 30 malignant). All images were assessed by a radiologist. The ML models were evaluated using calibration curves, decision curves, and receiver operating characteristic (ROC) curves. RESULTS: Of the 207 patients (102 women; 59.1 ± 11.5 years), 92 (41 women; 58.0 ± 13.7 years) had benign CRMs, and 115 (61 women; 59.8 ± 11.4 years) had malignant CRMs. The accuracy, sensitivity, and specificity of the radiologist's diagnoses were 85.5%, 84.2%, and 91.1%, respectively [area under the (ROC) curve (AUC), 0.87]. The ML classifiers showed similar sensitivity (94.2%-100%), specificity (94.7%-100%), and accuracy (94.3%-100%) in the training set. In the validation set, KNN showed better sensitivity, accuracy, and AUC than DT and RF but weaker specificity. Calibration and decision curves showed excellent and good results in the training and validation set, respectively. CONCLUSION: Unenhanced CT radiomics-based ML classifiers, especially KNN, may aid in screening CRMs.

Immunological dynamic characteristics in acute myeloid leukemia predict the long-term outcomes and graft-versus host-disease occurrences post-transplantation.

To investigate the relationship between immune dynamic and graft-versus-host-disease (GVHD) risk, 111 initial diagnostic acute myeloid leukemia patients were reviewed. The flow cytometry data of 12 major lymphocyte subsets in bone marrow (BM) from 60 transplant patients at four different time points were analyzed. Additionally, 90 immune subsets in peripheral blood (PB) of 11 post-transplantation on day 100 were reviewed. Our results demonstrated that transplant patients had longer OS compared to non-transplant patients (P < 0.001). Among transplant patients, those who developed GVHD showed longer OS than those without GVHD (P < 0.05). URD donors and CMV-negative status donors were associated with improved OS in transplant patients (P < 0.05). Importantly, we observed a decreased Th/Tc ratio in BM at initial diagnostic in patients with GVHD compared to those without GVHD (P = 0.034). Receiver operating characteristic analysis indicated that a low Th/Tc ratio predicted an increased risk of GVHD with a sensitivity of 44.44% and specificity of 87.50%. Moreover, an increased T/NK ratio in BM of post-induction chemotherapy was found to be associated with GVHD, with a sensitivity of 75.76% and specificity of 65.22%. Additionally, we observed a decreased percentage of NK1 (CD56-CD16+NK) in PB on day 100 post-transplantation in the GVHD group (P < 0.05). These three indicators exhibit promising potential as specific and useful biomarkers for predicting GVHD. These findings provide valuable insights for the early identification and management of GVHD risk, thereby facilitating the possibility of improving patient outcomes.

Enhanced and unenhanced: Radiomics models for discriminating between benign and malignant cystic renal masses on CT images: A multi-center study.

BACKGROUND: Machine learning algorithms used to classify cystic renal masses (CRMs) nave not been applied to unenhanced CT images, and their diagnostic accuracy had not been compared against radiologists. METHOD: This retrospective study aimed to develop radiomics models that discriminate between benign and malignant CRMs in a triple phase computed tomography (CT) protocol and compare the diagnostic accuracy of the radiomics approach with experienced radiologists. Predictive models were established using a training set and validation set of unenhanced and enhanced (arterial phase [AP] and venous phase [VP]) CT images of benign and malignant CRMs. The diagnostic capabilities of the models and experienced radiologists were compared using Receiver Operating Characteristic (ROC) curves. RESULTS: On unenhanced, AP and VP CT images in the validation set, the AUC, specificity, sensitivity and accuracy for discriminating between benign and malignant CRMs were 90.0 (95%CI: 81-98%), 90.0%, 90.5% and 90.2%; 93.0% (95%CI: 86-99%), 86.7%, 95.2% and 88.3%; and 95.0% (95%CI: 90%-100%), 93.3%, 90.5% and 92.1%, respectively, for the radiomics models. Diagnostic accuracy of the radiomics models differed significantly on unenhanced images in the training set vs. each radiologist (p = 0.001 and 0.003) but not in the validation set (p = 0.230 and 0.590); differed significantly on AP images in the validation set vs. each radiologist (p = 0.007 and 0.007) but not in the training set (p = 0.663 and 0.663); and there were no differences on VP images in the training or validation sets vs. each radiologist (training set: p = 0.453 and 0.051, validation set: p = 0.236 and 0.786). CONCLUSIONS: Radiomics models may have clinical utility for discriminating between benign and malignant CRMs on unenhanced and enhanced CT images. The performance of the radiomics model on unenhanced CT images was similar to experienced radiologists, implying it has potential as a screening and diagnostic tool for CRMs.

Diagnostic Value of Serum Golgi Protein 73 for Liver Fibrosis: A Systematic Review and Meta-Analysis.

BACKGROUND: The assessment of liver fibrosis has been a critical component in the clinical management of liver diseases. We performed a meta-analysis to evaluate serum Golgi protein 73 (GP73) in the diagnosis of liver fibrosis. METHODS: A literature search was performed in eight databases until July 13, 2022. We strictly searched studies according to inclusion and exclusion criteria, extracted data, and then assessed quality. We pooled the sensitivity, specificity, and other diagnostic estimates of serum GP73 to assess liver fibrosis. Moreover, publication bias, threshold analysis, sensitivity analysis, meta-regression, subgroup analysis, and post-test probability were evaluated. RESULTS: Our research integrated 16 articles including 3,676 patients. Potential publication bias and threshold effect were not found. The pooled sensitivity, specificity, and area under the curve of the summary receiver operating characteristic curve were 0.63, 0.79, and 0.818 for significant fibrosis; 0.77, 0.76, and 0.852 for advanced fibrosis; and 0.80, 0.76, and 0.894 for cirrhosis, respectively. The aetiology was one of the important sources of heterogeneity. CONCLUSION: Serum GP73 was a feasible diagnostic marker for liver fibrosis, which is of great significance for the clinical management of liver diseases.

Diagnostic Value of Serum Chitinase-3-Like Protein 1 for Liver Fibrosis: A Meta-analysis.

Background: Serum chitinase-3-like protein 1 (CHI3L1) is a promising marker for diagnosing liver fibrosis. This meta-analysis was carried out to assess the diagnostic performance of serum CHI3L1 for the estimation of liver fibrosis. Methods: Systematic searches were performed on PubMed, Embase, Web of Science, Scopus, the Cochrane Library, Google Scholar, Sinomed, the China National Knowledge Infrastructure (CNKI), the Chinese Medical Journal Database, and the Wanfang databases for available studies. The primary studies were screened strictly according to inclusion and exclusion criteria, and sensitivity, specificity, and other measures of accuracy of serum CHI3L1 for evaluating liver fibrosis were pooled with 95% confidence intervals. I 2 was calculated to assess heterogeneity, and sources of heterogeneity were explored by subgroup analysis. Deeks' test was used to assess for publication bias, and likelihood ratio was used to determine posttest probability. Results: Our research integrated 11 articles, accounting for 1897 patients older than 18 years old. The pooled sensitivity and specificity for significant fibrosis, advanced fibrosis, and cirrhosis were 0.79 and 0.82 with an area under the receiver operating characteristic curve (AUC) of 0.85, 0.81 and 0.83 with an AUC of 0.91, and 0.72 and 0.74 with an AUC of 0.85, respectively. Random-effects models were used to assess for significant heterogeneity, and subgroup analysis showed that age and aetiology of included patients were likely sources of heterogeneity. No potential publication bias was found for serum CHI3L1 in the diagnosis of significant fibrosis, advanced fibrosis, or cirrhosis, and posttest probability was moderate. Conclusion: Measurement of serum CHI3L1 is a feasible diagnostic tool for liver fibrosis.