Assessment Of Fibrosis Research Articles

Delayed 3D IR FLASH for airway imaging in children: more than myocardial fibrosis assessment

BackgroundTo investigate the ability of a delayed respiratory-navigated, electrocardiographically-gated three-dimensional inversion recovery-prepared flash low angle shot (3D IR FLASH) sequence to evaluate the lower airways in children undergoing routine cardiovascular magnetic resonance (CMR). MethodsThis retrospective study included pediatric patients (0-18 years) who underwent clinical CMR where a delayed 3D IR FLASH sequence was performed between July 2020 and April 2021. The airway image quality and extent of lower airway visibility was graded by two blinded readers using a four-point ordinal scale (0-3). Lower airway anatomical variants and abnormalities were recorded. Results180 patients were included with a median age of 11.7 (4.6-15.3) years. 51/180 (28%) were under general anesthesia (GA). Overall, the median grading of airway image quality was 3 (2-3) and extent of lower airway visibility was 3 (3-3). Interrater agreement was almost perfect (κ = 0.867 and κ = 0.956, respectively). Image quality correlated with extent of lower airway visibility (r = 0.62, p < 0.01). Delayed 3D IR FLASH was able to characterize the segmental bronchi in 137/180 (76%) and lobar bronchi in 172/180 (96%) of patients. Lower airway abnormalities were identified in 37/180 (21%) of patients and in 33/129 (26%) with congenital heart disease (CHD). Identified abnormalities included tracheobronchial branching anomalies in 6/180 (3%), abnormal tracheobronchial situs in 6/180 (3%), and extrinsic vascular compression in 25/180 (14%). ConclusionsDelayed 3D IR FLASH has excellent performance for evaluation of the lower airway anatomy and can simultaneously assess for myocardial late gadolinium enhancement. Lower airway abnormalities are not infrequently seen in children undergoing routine CMR for CHD.

Histopathological correlations of CT-based radiomics imaging biomarkers in native kidney biopsy

BackgroundKidney biopsy is the standard of care for the diagnosis of various kidney diseases. In particular, chronic histopathologic lesions, such as interstitial fibrosis and tubular atrophy, can provide prognostic information regarding chronic kidney disease progression. In this study, we aimed to evaluate historadiological correlations between CT-based radiomic features and chronic histologic changes in native kidney biopsies and to construct and validate a radiomics-based prediction model for chronicity grade.MethodsWe included patients aged ≥ 18 years who underwent kidney biopsy and abdominal CT scan within a week before kidney biopsy. Left kidneys were three-dimensionally segmented using a deep learning model based on the 3D Swin UNEt Transformers architecture. We additionally defined isovolumic cortical regions of interest near the lower pole of the left kidneys. Shape, first-order, and high-order texture features were extracted after resampling and kernel normalization. Correlations and diagnostic metrics between extracted features and chronic histologic lesions were examined. A machine learning-based radiomic prediction model for moderate chronicity was developed and compared according to the segmented regions of interest (ROI).ResultsOverall, moderate correlations with statistical significance (P < 0.05) were found between chronic histopathologic grade and top-ranked radiomic features. Total parenchymal features were more strongly correlated than cortical ROI features, and texture features were more highly ranked. However, conventional imaging markers, including kidney length, were poorly correlated. Top-ranked individual radiomic features had areas under receiver operating characteristic curves (AUCs) of 0.65 to 0.74. Developed radiomics models for moderate-to-severe chronicity achieved AUCs of 0.89 (95% confidence interval [CI] 0.75–0.99) and 0.74 (95% CI 0.52–0.93) for total parenchymal and cortical ROI features, respectively.ConclusionSignificant historadiological correlations were identified between CT-based radiomic features and chronic histologic changes in native kidney biopsies. Our findings underscore the potential of CT-based radiomic features and their prediction model for the non-invasive assessment of kidney fibrosis.

Transient elastography and diffusion-weighted magnetic resonance imaging for assessment of liver fibrosis in children with chronic hepatitis C.

Chronic hepatitis C (CHC) is a health burden with consequent morbidity and mortality. Liver biopsy is the gold standard for evaluating fibrosis and assessing disease severity and prognostic purposes post-treatment. Noninvasive alternatives for liver biopsy such as transient elastography (TE) and diffusion-weighted magnetic resonance imaging (DW-MRI) are critical needs. To evaluate TE and DW-MRI as noninvasive tools for predicting liver fibrosis in children with CHC. This prospective cross-sectional study initially recruited 100 children with CHC virus infection. Sixty-four children completed the full set of investigations including liver stiffness measurement (LSM) using TE and measurement of apparent diffusion coefficient (ADC) of the liver and spleen using DW-MRI. Liver biopsies were evaluated for fibrosis using Ishak scoring system. LSM and liver and spleen ADC were compared in different fibrosis stages and correlation analysis was performed with histopathological findings and other laboratory parameters. Most patients had moderate fibrosis (73.5%) while 26.5% had mild fibrosis. None had severe fibrosis or cirrhosis. The majority (68.8%) had mild activity, while only 7.8% had moderate activity. Ishak scores had a significant direct correlation with LSM (P = 0.008) and were negatively correlated with both liver and spleen ADC but with no statistical significance (P = 0.086 and P = 0.145, respectively). Similarly, histopathological activity correlated significantly with LSM (P = 0.002) but not with liver or spleen ADC (P = 0.84 and 0.98 respectively). LSM and liver ADC were able to significantly discriminate F3 from lower fibrosis stages (area under the curve = 0.700 and 0.747, respectively) with a better performance of liver ADC. TE and liver ADC were helpful in predicting significant fibrosis in children with chronic hepatitis C virus infection with a better performance of liver ADC.

Comparing imaging modalities in the assessment of fibrosis in metabolic dysfunction-associated steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common liver disease in children. Liver biopsy is considered the gold standard for diagnosis. Magnetic resonance elastography (MRE) and transient elastography (TE) are imaging modalities that can monitor fibrosis and steatosis noninvasively. More studies are needed to identify whether imaging modalities can provide accurate and reproducible data. We hypothesize that MRE provides reliable data similar to that of TE when compared to liver biopsy in children with MASLD/metabolic dysfunction-associated steatohepatitis. We conducted a retrospective chart review of children with liver biopsy-proven MASLD at Children's Hospital Los Angeles between September 2017 and January 2023, investigating and comparing the predictive accuracy of MRE and TE in the detection of high-grade fibrosis on liver biopsy. Seventy-seven patients were reviewed, all of whom had undergone liver biopsy, MRE and TE for evaluation of MASLD. Fibrosis was identified in 90% of liver biopsies. The area under the receiver operating characteristic curves (AUROC) of MRE and TE for detection of high-grade fibrosis were 0.817 and 0.750, respectively, and not significantly different (p = 0.4785). We demonstrate that MRE and TE did not accurately predict high-grade fibrosis on liver biopsy. Between the two noninvasive imaging modalities, the correlation of identifying high-grade fibrosis was not statistically different; however, the AUROC for MRE was slightly superior to that of TE. Studies with larger cohorts will be required to validate these findings.

Evaluating Observer Reliability and Diagnostic Accuracy of CT-LEFAT Criteria for Post-Treatment Head and Neck Lymphedema: A Prospective Blinded Comparative Analysis of Oncologist Human Inter-Rater Performance.

Radiation-associated lymphedema and fibrosis (LEF) is a significant toxicity following radiation therapy (RT) for head and neck cancer (HNC) patients. Recently, the CT Lymphedema and Fibrosis Assessment Tool (CT-LEFAT) was developed to standardize LEF diagnosis through fat stranding visualized on CT. This study aims to evaluate the inter-observer reliability and diagnostic accuracy of the CT-LEFAT criteria. This study retrospectively evaluated 26 HNC patients treated with RT that received a minimum of two contrast-enhanced CT scans. Qualitative review was conducted by five physician raters to assess the fat stranding observed on CT according to the CT-LEFAT criteria. Fleiss' kappa analysis was used to assess the inter- and intra-rater reliability, and Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) analysis was used to evaluate diagnostic accuracy. The inter-rater reliability across the six CT-LEFAT regions generally indicated a slight to fair agreement across all raters (0.04 ≤ kappa ≤ 0.36). Intra-observer agreement was generally fair to moderate (overall kappa=0.44). The ROC AUC analysis varied based on aggregation method used (0.60 ≤ average AUC ≤ 0.70). This specific use-case evaluating CT-LEFAT criteria displays limited performance. This suggests that additional materials, such as further training, refinement of imaging methods, or other processes may be required before achieving clinically-ready diagnostic performance of LEF diagnosis.

Strong Diagnostic Performance of Single Energy 256-row Multidetector Computed Tomography with Deep Learning Image Reconstruction in the Assessment of Myocardial Fibrosis.

Objective Although magnetic resonance imaging (MRI) is the gold standard for evaluating abnormal myocardial fibrosis and extracellular volume (ECV) of the left ventricular myocardium (LVM), a similar evaluation has recently become possible using computed tomography (CT). In this study, we investigated the diagnostic accuracy of a new 256-row multidetector CT with a low tube-voltage single energy scan and deep-learning-image reconstruction (DLIR) in detecting abnormal late enhancement (LE) in LVM. Methods We evaluated the diagnostic performance of CT for detecting LE in LVM and compared the results with those of MRI as a reference. We also measured the ECV of the LVM on CT and compared the results with those on MRI. Materials We analyzed 50 consecutive patients who underwent cardiac CT, including a late-phase scan and MRI, within three months of suspected cardiomyopathy. All patients underwent 256-slice CT (Revolution APEX; GE Healthcare, Waukesha, USA) with a low tube-voltage (70 kV) single energy scan and DLIR for a late-phase scan. Results In patient- and segment-based analyses, the sensitivity, specificity, and accuracy of detection of LE on CT were 94% and 85%, 100% and 95%, and 96% and 93%, respectively. The ECV of LVM per patient on CT and MRI was 33.0±6.2% and 35.9±6.1%, respectively. These findings were extremely strongly correlated, with a correlation coefficient of 0.87 (p<0.0001). The effective radiation dose on late-phase scanning was 2.4±0.9 mSv. Conclusion The diagnostic performance of 256-row multislice CT with a low tube voltage and DLIR for detecting LE and measuring ECV in LVM is credible.

Predictive Model for Post-Transplant Renal Fibrosis Using Ultrasound Shear Wave Elastography.

BACKGROUND The aim of this study was to investigate the clinical utility of ultrasound shear wave elastography (SWE) for assessment of renal fibrosis in post-renal transplant patients. MATERIAL AND METHODS We selected 183 patients who underwent renal transplantation. The complete dataset was randomly partitioned into a training cohort (128 cases) and a validation cohort (55 cases). All patients were subjected to SWE and renal allograft biopsy. The baseline data was compared using t-test, Z-test, or chi-square test. Through univariate and multivariate analyses, we identified independent risk factors influencing renal fibrosis after transplantation, a predictive model for post-transplant renal fibrosis was developed, and calibration curves, decision curve analyses, and ROC curves were generated. RESULTS Age, TST, Scr, GFR, and Emean showed significant differences (P<0.05). The C-index of the nomogram was 0.85, and the calibration curve and Hosmer-Lemeshow test demonstrated accurate diagnosis of fibrosis in both the training and validation sets (P>0.05). DCA showed that the prediction model effectively improved the diagnostic accuracy of fibrosis. The highest AUC of the nomogram for combined prediction of renal fibrosis in transplant patients was 0.902 in the training group and 0.871 in the validation group. These values were significantly higher compared to the AUCs of individual predictors (P<0.05). CONCLUSIONS Ultrasound SWE allows for early evaluation of renal fibrosis following transplantation. The prediction model, constructed by amalgamating other indicators, augments the accuracy and reliability of the prediction, providing more precise and accurate diagnostic and therapeutic recommendations for clinical practitioners.

Improving the Evaluation of MR Elastography for Liver Fibrosis Assessment in Autoimmune Liver Disease.

Improving the Evaluation of MR Elastography for Liver Fibrosis Assessment in Autoimmune Liver Disease.

Dynamic Changes in ELF Score Predict Hepatocellular Carcinoma in Chronic Hepatitis B Patients Receiving Antiviral Treatment.

Enhanced liver fibrosis (ELF) score is a noninvasive assessment for liver fibrosis. We aimed to evaluate the performance of changes in ELF score 3 years apart in combination with liver stiffness measurement (LSM)-hepatocellular carcinoma (HCC) score to predict HCC in chronic hepatitis B (CHB) patients. This is a prospective cohort study. Patients who underwent transient elastography (TE) examinations and at intermediate or high risk of HCC defined by LSM-HCC score were invited to repeat the examination about 3 years later. Their serum samples at these two time points were retrieved to assess the ELF score changes. The primary endpoint was HCC. There were 445 CHB patients (males: 73.9%; mean age: 51.6 ± 10.3 years) who received two TE examinations and ELF scores. Among them, 252 (56.6%) and 193 (43.4%) patients were at intermediate and high HCC risk at first assessment defined by LSM-HCC score, respectively. Kaplan-Meier analysis showed that the changes in ELF score could stratify the HCC risk in both intermediate- and high-risk patients defined by LSM-HCC score (p < 0.001 for intermediate-risk group; p = 0.011 for high-risk group). Patients remained having mild or moderate fibrosis at both assessments had the lowest risk of HCC (4.0%), followed by patients with fibrosis regressed (11.3%; p = 0.014) during a mean follow-up of 163 months. Patients remained having or progressed to severe fibrosis were at highest risk of HCC (>20%). Consistent findings were demonstrated in patients at both intermediate and high risk of HCC defined by LSM-HCC score. Dynamic changes in ELF score provided additional value to LSM-HCC score for stratifying HCC risk in CHB patients.

Redox Homeostasis and Non-Invasive Assessment of Significant Liver Fibrosis by Shear Wave Elastography.

Hepatic fibrosis with various origins can be estimated non-invasively by using certain biomarkers and imaging-based measurements. The aim of our study was to examine redox homeostasis biomarkers and liver stiffness measurements for the assessment of significant liver fibrosis in different etiologies of chronic liver diseases. A cohort study consisting of 88 chronic liver disease patients of both sexes (age 49.1 ± 14.7 years) was performed. Cytokine profiles as well as redox homeostasis characteristics were determined. Liver fibrosis stages were assessed with shear wave elastography. The plasma levels of four cytokines showed no significant alteration between the four fibrotic stages; however, higher values were measured in the F2-4 stages. Free sulfhydryl group concentration, the marker of redox homeostasis, was lower in significant fibrosis (F0-F1: 0.36 ± 0.06 vs. F2-4: 0.29 ± 0.08 mmol/L, p < 0.05). Higher chemiluminescence values, as free radical-antioxidant parameters, were detected in advanced fibrosis stages in erythrocytes (F0-F1: 36.00 ± 37.13 vs. F2-4: 51.47 ± 44.34 RLU%). These data suggest that oxidative stress markers can predict significant fibrosis, with the aim of reducing the number of protocol liver biopsies in patients unlikely to have significant disease; however, their role in distinguishing between the certain fibrosis groups needs further studies.

Non-invasive assessment of severe liver fibrosis in patients with Fontan-associated liver disease: The VALDIG-EASL FONLIVER cohort

Background & AimsFontan-type surgery is used as a palliation for congenital heart disease with univentricular physiology but may, in the long term, lead to advanced chronic liver disease. This study assessed the accuracy of conventional non-invasive models in assessing liver fibrosis and introduces a new risk score employing non-invasive tools. MethodsA prospective, cross-sectional, observational study was conducted across five European centers and encompassing all consecutive adult patients with Fontan circulation, liver biopsy and non-invasive tests (elastography, APRI, FIB-4, Fibrosis score, Doha, GUCI, and AAR). The primary outcome was the identification of severe liver fibrosis on biopsy. Multivariable logistic regression identified non-invasive predictors of severe fibrosis, leading to the development and internal validation of a new scoring model named the FonLiver risk score. ResultsIn total, 217 patients (mean [standard deviation] age, 27.9 [8.9] years; 50.7% males) were included. Severe liver fibrosis was present in 47.9% (95% CI 41.2%–54.5%) and correlated with a lower functional class, protein-losing enteropathy, and compromised cardiopulmonary and systemic hemodynamics. The final FonLiver risk score incorporated liver stiffness measurement using transient elastography and platelet count and demonstrated strong discrimination and calibration (area under the receiver operating curve [AUROC] of 0.81). The FonLiver risk score outperformed conventional prediction models (APRI, FIB-4, Fibrosis score, Doha, GUCI, and AAR), which all exhibited worse performance in our cohort (AUROC < 0.70 for all). ConclusionSevere liver fibrosis is prevalent in adults following Fontan-type palliation and can be effectively estimated using with the novel FonLiver risk score. This scoring system can be easily incorporated into the routine assessment of patients with Fontan circulation.

Multi-echo three-dimensional (3D) Dixon sequence combined with disodium gadolinium for risk stratification of advanced fibrosis in metabolic dysfunction-associated steatotic liver disease.

The hepatic steatosis and fibrosis related to metabolic dysfunction-associated steatotic liver disease (MASLD) are important factors in the progression. The Multi echo three-dimensional (3D) Dixon sequence can obtain a single breath hold scan for a fat fraction map and an R2* map. The R2* value is usually used to evaluate iron deposition. Whether the change in R2* value is related to liver fibrosis after injection of gadolinium disulfide (Gd) should be noted. This study evaluates the value of enhanced magnetic relaxation time in the risk stratification of liver fibrosis by analyzing the changes in R2* before and after Gd enhancement, and explores the potential application of Multi echo 3D Dixon sequence in one-stop evaluation of MASLD. This retrospective study included 138 MASLD patients who underwent Gadolinum ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) magnetic resonance imaging (MRI) examination in The First Affiliated Hospital of Chongqing Medical University from June 2020 to December 2021. Finally, 90 subjects were divided into moderate and high-risk fibrosis group and low-risk fibrosis group by two-step assessment of liver fibrosis. Multi-echo 3D chemical shift imaging sequence (Q-Dixon) sequences and gradient-echo T1WI (Vibe-Dixon) sequence were performed during the non-enhanced phase and hepatobiliary phase, respectively, and then the signal-intensity enhancement (SE) and magnetic relaxation-time enhancement (RE) values were calculated. The interobserver correlation coefficient was used to evaluate the consistency between observers. Univariate t-test was used to analyze the differences in RE and SE of liver fibrosis among different risk levels. Delong analysis was performed on receiver operating characteristic (ROC) curve to evaluate the difference in diagnostic efficacy between RE and SE in differentiating the risk level of liver fibrosis. Among the 90 patients, 55 (61.1%) belonged to the low-risk group and 35 (38.9%) belonged to the medium-to-high-risk group. The average RE and SE values were 1.23±0.15 and 1.57±0.23 in the low-risk group and 0.99±0.09 and 1.38±0.21 in both the medium-to-high-risk group (P<0.01). The ROC curve showed that the area under the curve (AUC) value of RE was 0.922, with a corresponding optimal threshold of 0.713, sensitivity of 0.852, and specificity of 0.861. The AUC value of SE was 0.724, with a corresponding optimal threshold of 0.352, sensitivity of 0.519, and specificity of 0.833. The AUC difference between RE and SE for the predictive value of different risk assessments was 0.198, and the 95% confidence interval of the difference was 0.084-0.312. The Delong test showed that the difference was significant (P<0.01). Magnetic RE had high effectiveness for distinguishing between liver-fibrosis risk levels. The combination of the Q-Dixon sequence and Gd-EOB-DTPA has the potential of one-stop evaluation of MASLD.

Noninvasive tools for the assessment of fibrosis in metabolic dysfunction-associated steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously nonalcoholic fatty liver disease (NAFLD), is the number one chronic liver disorder worldwide. Progression to advanced fibrosis marks the emergence of a significant risk of liver-related negative outcomes. However, only a minority of patients will present at this stage. Since widespread liver biopsy in unfeasible at such high disease prevalence, there was a need to develop noninvasive tests (NITs) that could easily and reliably be applied to patients with MASLD, regardless of clinical setting. The NITs include simple scores, like the fibrosis-4 (FIB-4) Index, patented serum tests, like the Enhanced Liver Fibrosis test (ELF™), and imaging-based modalities, like the vibration-controlled transient elastography (VCTE). Guidelines suggests a stepwise approach that utilizes more than one NIT, with FIB-4 <1.30 being used as a first step to rule out patients that do not need further testing. Subsequent choice of NIT will be influenced by setting, cost, and local availability. While these NITs are accurate, they are not perfect. As such, research is ongoing. A promising avenue is that of omics, a group of technologies that provide concomitant results on a large number of molecules (and other variables). With the advance of artificial intelligence, new NITs may arise from large demographic, biochemical, and radiological data sets.

A combination model of CT-based radiomics and clinical biomarkers for staging liver fibrosis in the patients with chronic liver disease

A combined model was developed using contrast-enhanced CT-based radiomics features and clinical characteristics to predict liver fibrosis stages in patients with chronic liver disease (CLD). We retrospectively analyzed multiphase CT scans and biopsy-confirmed liver fibrosis. 160 CLD patients were randomly divided into 7:3 training/validation ratio. Clinical laboratory indicators associated with liver fibrosis were identified using Spearman's correlation and multivariate logistic regression correlation. Radiomic features were extracted after segmenting the entire liver from multiphase CT images. Feature dimensionality reduction was performed using RF-RFE, LASSO, and mRMR methods. Six radiomics-based models were developed in the training cohort of 112 patients. Internal validation was conducted on 48 randomly assigned patients. Receptor Operating Characteristic (ROC) curves and confusion matrices were constructed to evaluate model performance. The radiomics model exhibited robust performance, with AUC values of 0.810 to 1.000 for significant fibrosis, advanced fibrosis, and cirrhosis. The integrated clinical-radiomics model had superior diagnostic efficacy in the validation cohort, with AUC values of 0.836 to 0.997. Moreover, these models outperformed established biomarkers such as the aspartate aminotransferase to platelet ratio index (APRI) and the fibrosis 4 score (FIB-4), as well as the gamma glutamyl transpeptidase to platelet ratio (GPR), in predicting the fibrotic stages. The clinical-radiomics model holds considerable promise as a non-invasive diagnostic tool for the assessment and staging of liver fibrosis in the patients with CLD, potentially leading to better patient management and outcomes.

Assessment of Left Atrial Fibrosis by Cardiac Magnetic Resonance Imaging in Ischemic Stroke Patients Without Atrial Fibrillation: A Systematic Review and Meta-Analysis.

Left atrial (LA) fibrosis is a marker of atrial cardiomyopathy and has been reported to be associated with both atrial fibrillation and ischemic stroke. Elucidating this relationship is clinically important as LA fibrosis could serve as a surrogate biomarker of LA cardiomyopathy. The objective of this study is to investigate the association of LA fibrosis and embolic stroke of undetermined source (ESUS) using cardiac magnetic resonance imaging. Following an International Prospective Register of Systematic Reviews-registered protocol, 3 blinded reviewers performed a systematic review for studies that quantified the degree of LA fibrosis in patients with ESUS as compared with healthy patients from inception to February 2024. A meta-analysis was conducted in the mean difference. From 7 studies (705 patients), there was a significantly higher degree of LA fibrosis in patients with ESUS compared with healthy controls (MD, 5.71% [95% CI, 3.55%-7.87%], P<0.01). The degree of LA fibrosis was significantly higher in patients with atrial fibrillation than healthy controls (MD, 8.22% [95% CI, 5.62%-10.83%], P<0.01). A similar degree of LA fibrosis was observed in patients with ESUS compared with patients with atrial fibrillation (MD, -0.92% [95% CI, -2.29% to 0.44%], P=0.35). A significantly higher degree of LA fibrosis was found in patients with ESUS as compared with healthy controls. This suggests that LA fibrosis may play a significant role in the pathogenesis of ESUS. Further research is warranted to investigate LA fibrosis as a surrogate biomarker of atrial cardiomyopathy and recurrent stroke risk in patients with ESUS.

Ultrasonic Assessment of Liver Fibrosis Using One-Dimensional Convolutional Neural Networks Based on Frequency Spectra of Radiofrequency Signals with Deep Learning Segmentation of Liver Regions in B-Mode Images: A Feasibility Study.

The early detection of liver fibrosis is of significant importance. Deep learning analysis of ultrasound backscattered radiofrequency (RF) signals is emerging for tissue characterization as the RF signals carry abundant information related to tissue microstructures. However, the existing methods only used the time-domain information of the RF signals for liver fibrosis assessment, and the liver region of interest (ROI) is outlined manually. In this study, we proposed an approach for liver fibrosis assessment using deep learning models on ultrasound RF signals. The proposed method consisted of two-dimensional (2D) convolutional neural networks (CNNs) for automatic liver ROI segmentation from reconstructed B-mode ultrasound images and one-dimensional (1D) CNNs for liver fibrosis stage classification based on the frequency spectra (amplitude, phase, and power) of the segmented ROI signals. The Fourier transform was used to obtain the three kinds of frequency spectra. Two classical 2D CNNs were employed for liver ROI segmentation: U-Net and Attention U-Net. ROI spectrum signals were normalized and augmented using a sliding window technique. Ultrasound RF signals collected (with a 3-MHz transducer) from 613 participants (Group A) were included for liver ROI segmentation and those from 237 participants (Group B) for liver fibrosis stage classification, with a liver biopsy as the reference standard (Fibrosis stage: F0 = 27, F1 = 49, F2 = 51, F3 = 49, F4 = 61). In the test set of Group A, U-Net and Attention U-Net yielded Dice similarity coefficients of 95.05% and 94.68%, respectively. In the test set of Group B, the 1D CNN performed the best when using ROI phase spectrum signals to evaluate liver fibrosis stages ≥F1 (area under the receive operating characteristic curve, AUC: 0.957; accuracy: 89.19%; sensitivity: 85.17%; specificity: 93.75%), ≥F2 (AUC: 0.808; accuracy: 83.34%; sensitivity: 87.50%; specificity: 78.57%), and ≥F4 (AUC: 0.876; accuracy: 85.71%; sensitivity: 77.78%; specificity: 94.12%), and when using the power spectrum signals to evaluate ≥F3 (AUC: 0.729; accuracy: 77.14%; sensitivity: 77.27%; specificity: 76.92%). The experimental results demonstrated the feasibility of both the 2D and 1D CNNs in liver parenchyma detection and liver fibrosis characterization. The proposed methods have provided a new strategy for liver fibrosis assessment based on ultrasound RF signals, especially for early fibrosis detection. The findings of this study shed light on deep learning analysis of ultrasound RF signals in the frequency domain with automatic ROI segmentation.

18F]AlF-CBP imaging of type I collagen for non-invasive monitoring of pulmonary fibrosis in preclinical models.

Pulmonary fibrosis is an irreversible scar-forming condition for which there is a lack of non-invasive and specific methods for monitoring its progression and therapy efficacy. However, the disease is known to be accompanied by collagen accumulation. Here, we developed a novel positron emission tomography (PET) probe targeting type I collagen to evaluate its utility for the non-invasive assessment of pulmonary fibrosis. We designed a 18F-labeled PET probe ([18F]AlF-CBP) to target type I collagen and evaluated its binding affinity, specificity and stability in vitro. PET with [18F]AlF-CBP, CT, histopathology, immunofluorescence, and biochemical indice were performed to assess and quantify type I collagen levels and pulmonary fibrosis progression and treatment in murine models. Dynamic PET/CT studies of [18F]AlF-CBP were conducted to assess lung fibrosis in non-human primate models. [18F]AlF-CBP was successfully prepared, and in vitro and in vivo tests showed high stability (> 95%) and type I collagen specificity (IC50 = 0.36 µM). The lungs of the fibrotic murine model showed more elevated probe uptake and retention compared to the control group, and there was a positive correlation between the radioactivity uptake signals and the degree of fibrosis (CT: R2 = 0.89, P < 0.0001; hydroxyproline levels: R2 = 0.89, P < 0.0001). PET signals also correlated well with mean lung density in non-human primate models of pulmonary fibrosis (R2 = 0.84, P < 0.0001). [18F]AlF-CBP PET imaging is a promising non-invasive method for specific monitoring of lung fibrosis progression and therapy efficacy.

Diagnostic accuracy of vibration-controlled transient elastography for staging liver fibrosis in autoimmune liver diseases: A systematic review and meta-analysis.

The assessment of liver fibrosis is crucial for managing autoimmune liver diseases such as primary biliary cholangitis (PBC), autoimmune hepatitis (AIH), and primary sclerosing cholangitis (PSC). However, data on the efficacy of noninvasive tests for these diseases are limited. This meta-analysis evaluated the diagnostic accuracy of vibration-controlled transient elastography (VCTE) for staging fibrosis in patients with autoimmune liver disease. Searches were conducted in PubMed, Embase, CINAHL, Web of Science, and Cochrane Library databases to assess the diagnostic accuracy of VCTE against histology as the reference standard in adult patients with autoimmune liver disease. The summary area under the curve (sAUC) and diagnostic odds ratio were calculated for significant fibrosis (SF), advanced fibrosis (AF), and cirrhosis, according to liver biopsy. Fourteen articles were included, comprising 559 PBC patients from six studies, 388 AIH patients from five studies, and 151 PSC patients from three studies. VCTE demonstrated good performance for fibrosis staging in PBC, AIH, and PSC. In PBC, sAUCs of VCTE were 0.87, 0.89, and 0.99 for staging SF, AF, and cirrhosis, respectively. In AIH, the sAUCs were 0.88, 0.88, and 0.92, respectively, while in PSC, they were 0.88, 0.95, and 0.92, respectively. The cutoff values for AF were 7.5-17.9 kPa in PBC, 8.18-12.1 kPa in AIH, and 9.6 kPa in PSC. VCTE shows high diagnostic accuracy for staging liver fibrosis in patients with autoimmune liver diseases. This non-invasive method serves as a valuable tool for the evaluation and monitoring of fibrosis in these lifelong diseases.

Plasma microRNA-15a/16-1 serves as a non-invasive indicator of liver fibrosis severity in individuals with chronic hepatitis B

BackgroundThe lack of effective non-invasive diagnostic methods for liver fibrosis hinders timely treatment for chronic hepatitis B (CHB) patients, leading to the progression of advanced liver disease. Circulating microRNAs offer a non-invasive approach to fibrosis assessment. MicroRNA-15a/16-1 (miR-15a/16) was reported to be implicated in fibrosis development, but the role of plasma miR-15a/16 in liver fibrosis assessment remains poorly understood. This study explored the importance of plasma miR-15a/16 in assessing liver fibrosis severity of CHB patients. MethodsQuantitative PCR was utilized to measure the levels of plasma miR-15a/16 in 435 patients with CHB and 74 healthy controls. We assessed the correlation between plasma miR-15a/16 levels and liver fibrosis and cirrhosis using Pearson correlation coefficients, multivariate linear and logistic regression models, and smooth curve fitting. Utilizing the receiver operating characteristic (ROC) curve, we examined the diagnostic potential of plasma miR-15a/16 in severe fibrosis and cirrhosis. ResultsPlasma levels of miR-15a/16 in patients with CHB were significantly reduced compared to those in healthy controls. In the CHB cohort, levels were notably decreased in individuals with severe fibrosis or cirrhosis compared to those without severe fibrosis or cirrhosis. Plasma miR-15a/16 levels exhibited a negative relationship with the severity of liver fibrosis, gradually decreasing as the histological fibrosis stage progressed from S0 to S4. Reduced levels of plasma miR-15a/16 were linked to an elevated risk of severe liver fibrosis (miR-15a: odds ratio [OR] = 0.243; 95 % confidence interval [CI]: 0.138, 0.427; miR-16: OR = 0.201; 95 % CI: 0.097, 0.417) and cirrhosis (miR-15a: OR = 0.153; 95 % CI: 0.079, 0.298; miR-16: OR = 0.064; 95 % CI: 0.025, 0.162). MiR-15a achieved an area under the ROC curve of 0.886 and 0.832 for detecting moderate-to-severe fibrosis (S2-S4) and cirrhosis, respectively. MiR-16 demonstrated similar diagnostic values. ConclusionPlasma miR-15a/16 levels were negatively correlated with the severity of liver fibrosis in CHB patients and could serve as a new non-invasive indicator in evaluating liver fibrosis.

Pancreatic fibrosis assessment and association with pancreatic cancer: comparison with the extracellular volume fraction

To compare the iodine washout rate (IWR) from multiphasic contrast-enhanced computed tomography (CT) with the extracellular volume fraction (fECV) for assessing pancreatic fibrosis and its association with pancreatic cancer. The study included 51 individuals (33 men; median age: 69 years; 21 with pancreatic cancer, 30 with other diseases) who underwent multiphasic contrast-enhanced CT and histological evaluation for fibrotic changes in pancreas. The histological pancreatic fibrosis fraction (HPFF) was assessed on Azan-stained sections. Pancreatic parenchymal enhancement values were measured to calculate IWR and fECV. Statistical methods, such as Spearman's rho and Mann-Whitney U-test, were used. Linear regression models using IWR and fECV were constructed to predict HPFF, with the performance expressed as root mean squared error (RMSE) and Akaike information criterion (AIC). HPFF correlated with all CT parameters at the estimated transection line, strongest for IWRPPP-EP (r=-0.69, P<0.01). HPFF and fECV values were higher in the pancreatic cancer group than in controls (30% vs. 12.5%, P<0.01; 40.3% vs. 33.0%, P<0.01), whereas IWR values were lower (IWRPPP-EP: 43.3% vs. 55.0%, P<0.01; IWRPVP-EP: 25.0% vs. 33.5%, P<0.01). Linear regression models combining IWRPPP-EP+fECV and IWRPVP-EP+fECV were superior for predicting HPFF, with lower RMSE (9.23-9.35) and AIC (379.38-380.72) values than models with IWR or fECV alone. IWRPPP-EP, IWRPVP-EP, and fECV were reliable biomarkers for noninvasively assessing pancreatic fibrosis and were associated with pancreatic cancer risk. Linear regression combining these variables showed enhanced predictive accuracy for pancreatic fibrosis.