ProJect: a powerful mixed-model missing value imputation method.

Missing values (MVs) can adversely impact data analysis and machine-learning model development. We propose a novel mixed-model method for missing value imputation (MVI). This method, ProJect (short for Protein inJection), is a powerful and meaningful improvement over existing MVI methods such as Bayesian principal component analysis (PCA), probabilistic PCA, local least squares and quantile regression imputation of left-censored data. We rigorously tested ProJect on various high-throughput data types, including genomics and mass spectrometry (MS)-based proteomics. Specifically, we utilized renal cancer (RC) data acquired using DIA-SWATH, ovarian cancer (OC) data acquired using DIA-MS, bladder (BladderBatch) and glioblastoma (GBM) microarray gene expression dataset. Our results demonstrate that ProJect consistently performs better than other referenced MVI methods. It achieves the lowest normalized root mean square error (on average, scoring 45.92% less error in RC_C, 27.37% in RC_full, 29.22% in OC, 23.65% in BladderBatch and 20.20% in GBM relative to the closest competing method) and the Procrustes sum of squared error (Procrustes SS) (exhibits 79.71% less error in RC_C, 38.36% in RC full, 18.13% in OC, 74.74% in BladderBatch and 30.79% in GBM compared to the next best method). ProJect also leads with the highest correlation coefficient among all types of MV combinations (0.64% higher in RC_C, 0.24% in RC full, 0.55% in OC, 0.39% in BladderBatch and 0.27% in GBM versus the second-best performing method). ProJect's key strength is its ability to handle different types of MVs commonly found in real-world data. Unlike most MVI methods that are designed to handle only one type of MV, ProJect employs a decision-making algorithm that first determines if an MV is missing at random or missing not at random. It then employs targeted imputation strategies for each MV type, resulting in more accurate and reliable imputation outcomes. An R implementation of ProJect is available at https://github.com/miaomiao6606/ProJect.

Identification of prognostic biomarkers for cholangiocarcinoma by combined analysis of molecular characteristics of clinical MVI subtypes and molecular subtypes.

Cholangiocarcinoma (CCA) is widely noted for its high degree of malignancy, rapid progression, and limited therapeutic options. This study was carried out on transcriptome data of 417 CCA samples from different anatomical locations. The effects of lipid metabolism related genes and immune related genes as CCA classifiers were compared. Key genes were derived from MVI subtypes and better molecular subtypes. Pathways such as epithelial mesenchymal transition (EMT) and cell cycle were significantly activated in MVI-positive group. CCA patients were classified into three (four) subtypes based on lipid metabolism (immune) related genes, with better prognosis observed in lipid metabolism-C1, immune-C2, and immune-C4. IPTW analysis found that the prognosis of lipid metabolism-C1 was significantly better than that of lipid metabolism-C2 + C3 before and after correction. KRT16 was finally selected as the key gene. And knockdown of KRT16 inhibited proliferation, migration and invasion of CCA cells.

Comparison of preoperative ultrasound and MRI in the diagnosis of microvascular invasion in hepatocellular carcinoma.

Ultrasound has few reports on its application in prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). The purpose of this study was to explore the diagnostic efficacies of preoperative ultrasound and magnetic resonance imaging (MRI) for HCC MVI and compare these two imaging methods for the diagnosis of this condition. The clinical and preoperative ultrasound and MR imaging data of 26 patients with newly diagnosed HCC were collected between October 2020 and October 2021. According to the gold standard (postoperative pathology), the patients were divided into MVI-positive and MVI-negative groups, and the efficacies of ultrasound and MRI in diagnosing HCC MVI and the consistency between the two imaging modalities were analyzed. For the preoperative diagnosis of MVI using ultrasound, the sensitivity was 93.33%, the specificity was 81.82%, and the accuracy was 88.46%. For preoperative MRI, the sensitivity was 66.67%, the specificity was 100%, and the accuracy was 80.77%. In diagnosing MVI, the two methods had significantly different efficacy (P = 0.031). Ultrasound and MRI have high diagnostic efficiency for MVI, but the accuracy of preoperative MRI was lower than that of preoperative ultrasound. These results indicate that ultrasound has a certain guiding significance in the diagnosis of HCC MVI.

Noninvasive urinary protein signatures combined clinical information associated with microvascular invasion risk in HCC patients.

BACKGROUND: Microvascular invasion (MVI) is the main factor affecting the prognosis of patients with hepatocellular carcinoma (HCC). The aim of this study was to identify accurate diagnostic biomarkers from urinary protein signatures for preoperative prediction. METHODS: We conducted label-free quantitative proteomic studies on urine samples of 91 HCC patients and 22 healthy controls. We identified candidate biomarkers capable of predicting MVI status and combined them with patient clinical information to perform a preoperative nomogram for predicting MVI status in the training cohort. Then, the nomogram was validated in the testing cohort (n = 23). Expression levels of biomarkers were further confirmed by enzyme-linked immunosorbent assay (ELISA) in an independent validation HCC cohort (n = 57). RESULTS: Urinary proteomic features of healthy controls are mainly characterized by active metabolic processes. Cell adhesion and cell proliferation-related pathways were highly defined in the HCC group, such as extracellular matrix organization, cell-cell adhesion, and cell-cell junction organization, which confirms the malignant phenotype of HCC patients. Based on the expression levels of four proteins: CETP, HGFL, L1CAM, and LAIR2, combined with tumor diameter, serum AFP, and GGT concentrations to establish a preoperative MVI status prediction model for HCC patients. The nomogram achieved good concordance indexes of 0.809 and 0.783 in predicting MVI in the training and testing cohorts. CONCLUSIONS: The four-protein-related nomogram in urine samples is a promising preoperative prediction model for the MVI status of HCC patients. Using the model, the risk for an individual patient to harbor MVI can be determined.

Cerebrospinal Fluid Flow Detection in Post-hemorrhagic Hydrocephalus With Novel Microvascular Imaging Modality.

Cerebrospinal fluid flow dynamics serve as an important biomarker to guide medical and/or surgical intervention of hydrocephalus in infants. Imaging of cerebrospinal fluid flow can be assessed with magnetic resonance imaging, but routine evaluation is limited by practical challenges. We show for the first time that cerebrospinal fluid flow can be depicted using brain ultrasound by implementing highly sensitive ultrasound-based microvascular imaging technology (B-flow). This novel application could potentially expand the use of this technology beyond its current application in depiction of vascular flow pathologies in newborns.

Radiomics analysis of [18F]FDG PET/CT for microvascular invasion and prognosis prediction in very-early- and early-stage hepatocellular carcinoma.

As a reliable preoperative predictor for microvascular invasion (MVI) and disease-free survival (DFS) is lacking, we developed a radiomics nomogram of [18F]FDG PET/CT to predict MVI status and DFS in patients with very-early- and early-stage (BCLC 0, BCLC A) hepatocellular carcinoma (HCC). METHODS: Patients (N = 80) with BCLC0-A HCC who underwent [18F]FDG PET/CT before surgery were enrolled in this retrospective study and were randomized to a training cohort and a validation cohort. Texture features from patients obtained using Lifex software in the training cohort were subjected to LASSO regression to select the most useful predictive features of MVI and DFS. Then, the radiomics nomogram was constructed using the radiomics signature and clinical features and further validated. RESULTS: To predict MVI, the [18F]FDG PET/CT radiomics signature consisted of five texture features from the PET and six texture features from CT. The signature was significantly associated with MVI status in the training cohort (P = 0.001). None of the clinical features was independent predictors for MVI status (P > 0.05). The area under the curve value of the M-PET/CT model was 0.891 (95% CI: 0.799-0.984) in the training cohort and showed good discrimination and calibration. To predict DFS, the [18F]FDG PET/CT radiomics nomogram (D-PET/CT model) and a clinicopathologic nomogram were built in the training cohort. The D-PET/CT model, which integrated the D-PET/CT radiomics signature with INR and TB, provided better predictive performance (C-index: 0.831, 95% CI: 0.761-0.900) and larger net benefits than the simple clinical model, as determined by decision curve analyses. CONCLUSION: The newly developed [18F]FDG PET/CT radiomics signature was an independent biomarker for the estimation of MVI and DFS in patients with very-early- and early-stage HCC. Moreover, PET/CT nomogram, which incorporated the radiomics signature of [18F]FDG PET/CT and clinical risk factors in patients with very-early- and early-stage HCC, performed better for individualized DFS estimation, which might enable a step forward in precise medicine.

Prognostic role of tumor mutation burden in hepatocellular carcinoma after radical hepatectomy.

BACKGROUND AND AIM: This study aimed to assess the potential relationship between tumor mutation burden (TMB) and the recurrence risk of hepatocellular cancer (HCC) after curative resection and tried to develop a reliable TMB based nomogram. METHODS: This retrospective study was conducted in 128 patients (40 patients suffered from a recurrence of HCC) who had received radical hepatectomy by the same surgical team. A nomogram model was constructed using the R and EmpowerStats software. RESULTS: TMB was not associated with maximum tumor size and the presence of microvascular invasion (MVI). In the whole population or subgroups, the recurrence-free survival (RFS) rate was significantly lower in the TMB high group. In multivariate analysis, TMB (hazard ratio [HR], 10.12; 95% confidence interval [CI], 5.03-20.31; P < .001), large tumor diameter (HR, 2.91; 95% CI, 1.51-5.63; P = .001), presence of MVI (HR, 1.93; 95% CI, 1.03-3.65; P = .042) were independent predictors of RFS. The predictive power of the nomogram integrating TMB, tumor size and MVI was higher than model only incorporating tumor size and MVI. CONCLUSION: This study demonstrated for the first time that higher TMB was associated with poor prognosis in patients with HCC who had received curative resection, and a TMB based nomogram model had a well predictive performance for RFS in this population.

Ocular manifestations in patients with Stevens-Johnson syndrome in Malawi-review of the literature illustrated by clinical cases.

PURPOSE: In Sub-Saharan Africa, manifestations of Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are commonly seen in human immunodeficiency virus-infected patients receiving nevirapine-based antiretroviral therapy and/or cotrimoxazole. These patients often face severe ocular complications that lead to moderate to severe visual impairment or blindness. METHODS: Review of the current literature, illustrated by retrospective hospital-based case series: Eight patients at Lions Sight First Eye Hospital, Blantyre, Malawi with severe ocular complications like severe cicatrizing conjunctivitis with symblephara, corneal punctate erosions, corneal vascularization, and corneal ulceration are illustrated after the diagnosis of SJS/TEN. RESULTS: Light perception was reported in six (12 eyes) of them; two patients (4 eyes) had moderate visual impairment (6/36 and 6/18). In one patient, eye problems started after therapy with cotrimoxazole; in seven after therapy, with antiretroviral therapy. CONCLUSION: SJS/TEN in Sub Saharan Africa correlates significantly with moderate visual impairment up to blindness. Early recognition of eye complications and involvement of ophthalmologists in the acute stage, early treatment with local steroids, and close monitoring for up to 6 months after the acute phase are crucial. Severe ocular complications seem to be more severe in dark skin phototype.

Can microvascular invasion in hepatocellular carcinoma be predicted by diagnostic imaging? A critical review.

Imaging still has a limited capacity to detect microvascular invasion (mVI). The objective of this critical review is the evaluation of the most significant predictors of mVI in hepatocellular carcinoma (HCC) detectable by computed tomography, PET/computed tomography and MRI using a mathematical model. We systematically reviewed 15 observational studies from 2008 to 2018 to analyze factors with most impact on mVI detection. The most significant predictors of mVI correlating with imaging techniques were considered. From 1902 patients considered, we individuated 30 total predictors of mVI in a multivariate analysis. The most frequent predictors related to the highest presence with mVI in HCC were: α-fetoprotein (p < 0.0001), tumor size (p < 0.0001) and number of HCC nodules (p = 0.0020).

Identification of intestinal ion transport defects in microvillus inclusion disease.

Loss of function mutations in the actin motor myosin Vb (Myo5b) lead to microvillus inclusion disease (MVID) and death in newborns and children. MVID results in secretory diarrhea, brush border (BB) defects, villus atrophy, and microvillus inclusions (MVIs) in enterocytes. How loss of Myo5b results in increased stool loss of chloride (Cl(-)) and sodium (Na(+)) is unknown. The present study used Myo5b loss-of-function human MVID intestine, polarized intestinal cell models of secretory crypt (T84) and villus resembling (CaCo2BBe, C2BBe) enterocytes lacking Myo5b in conjunction with immunofluorescence confocal stimulated emission depletion (gSTED) imaging, immunohistochemical staining, transmission electron microscopy, shRNA silencing, immunoblots, and electrophysiological approaches to examine the distribution, expression, and function of the major BB ion transporters NHE3 (Na(+)), CFTR (Cl(-)), and SLC26A3 (DRA) (Cl(-)/HCO3 (-)) that control intestinal fluid transport. We hypothesized that enterocyte maturation defects lead villus atrophy with immature secretory cryptlike enterocytes in the MVID epithelium. We investigated the role of Myo5b in enterocyte maturation. NHE3 and DRA localization and function were markedly reduced on the BB membrane of human MVID enterocytes and Myo5bKD C2BBe cells, while CFTR localization was preserved. Forskolin-stimulated CFTR ion transport in Myo5bKD T84 cells resembled that of control. Loss of Myo5b led to YAP1 nuclear retention, retarded enterocyte maturation, and a cryptlike phenotype. We conclude that preservation of functional CFTR in immature enterocytes, reduced functional expression of NHE3, and DRA contribute to Cl(-) and Na(+) stool loss in MVID diarrhea.

Preliminary evaluation of the SimPORTAL major vessel injury (MVI) repair model.

BACKGROUND: Major vessel injury (MVI) is a dangerous complication associated with laparoscopic surgery that leads, if not properly handled, to blood loss, conversion to open surgery, and eventually death. In this paper, we describe the preliminary evaluation of the SimPORTAL MVI model, created with the goal of simulating an intra-corporeal injury to a large vessel. METHODS: For this study, we created MVI models for 17 residents (PGY 1-4). Each resident was asked to perform an intracorporeal knot on a penrose drain within a maximum time limit of 6 min (in accordance with European basic laparoscopic urological skills rules) and then to subsequently repair a vessel injury on the MVI model, which was perfused with synthetic blood, within a maximum blood loss of 3 L. During the vessel repair, low lights and pulse sounds were used to simulate the operating room environment. All participants filled out a survey pre- and post-task to score various aspects of the model. RESULTS: We successfully created a model that simulates a critical surgical event. None of the participants reported having previous experience repairing a MVI. Six participants were able to perform the intracorporeal knot, and 12 residents (70.5%) were able to repair the MVI model under the given time and blood loss limits. Eleven participants agreed that the MVI model behaves like a real vessel, and six felt to be capable of performing the task prior to attempting it. Sixteen participants thought that the MVI model should be part of laparoscopic curriculums during residency. CONCLUSIONS: The SimPORTAL MVI model is a feasible low-cost model that would be well appreciated as a part of laparoscopic curriculum for residents. Minor improvements, including pressure measurement in the vessel for task assessment, will be made in the future, and further studies are necessary to definitively validate this model.

Can living donor liver transplantation offer similar outcomes to deceased donor liver transplantation using expanded selection criteria for hepatocellular carcinoma?

OBJECTIVE: To compare the outcomes of living donor liver transplantation (LDLT) versus deceased donor liver transplantation (DDLT) for patients with hepatocellular carcinoma (HCC) in different selection criteria. METHODS: Data of patients with HCC who underwent liver transplantation between 2005 and 2013 at our center were reviewed. Clinical data of LDLT recipients and DDLT recipients were compared. The postoperative recurrence-free survival (RFS) rate and overall survival (OS) rate after LDLT versus DDLT were compared in the Milan recipients, the University of California, San Francisco (UCSF) recipients, the up-to-seven recipients, the Hangzhou recipients and the Chengdu recipients. RESULTS: Data of 255 patients were retrospectively reviewed in this study. Seventeen DDLT recipient and 9 LDLT recipients died during the perioperative period. Among the remaining 229 recipients (NLDLT=66, NDDLT=163), 96 patients met the Milan criteria, 123 recipients met the UCSF criteria, 135 patients met the up-to-seven criteria, 216 patients met the Hangzhou criteria, and 229 recipients met the Chengdu criteria. The overall RFS and OS rates of the Milan recipients, the UCSF recipients, the up-to-seven recipients, the Hangzhou recipients and the Chengdu recipients after LDLT and DDLT were all similar. CONCLUSION: Using well-studied selection criteria, LDLT offers similar outcomes to DDLT for patient with HCC, even using expanded selection criteria.

Corrigendum: Fat fraction quantification with MRI estimates tumor proliferation of hepatocellular carcinoma.

[This corrects the article DOI: 10.3389/fonc.2024.1367907.].

Fat fraction quantification with MRI estimates tumor proliferation of hepatocellular carcinoma.

Purpose: To assess the utility of fat fraction quantification using quantitative multi-echo Dixon for evaluating tumor proliferation and microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: A total of 66 patients with resection and histopathologic confirmed HCC were enrolled. Preoperative MRI with proton density fat fraction and R2* mapping was analyzed. Intratumoral and peritumoral regions were delineated with manually placed regions of interest at the maximum level of intratumoral fat. Correlation analysis explored the relationship between fat fraction and Ki67. The fat fraction and R2* were compared between high Ki67(>30%) and low Ki67 nodules, and between MVI negative and positive groups. Receiver operating characteristic (ROC) analysis was used for further analysis if statistically different. Results: The median fat fraction of tumor (tFF) was higher than peritumor liver (5.24% vs 3.51%, P=0.012). The tFF was negatively correlated with Ki67 (r=-0.306, P=0.012), and tFF of high Ki67 nodules was lower than that of low Ki67 nodules (2.10% vs 4.90%, P=0.001). The tFF was a good estimator for low proliferation nodules (AUC 0.747, cut-off 3.39%, sensitivity 0.778, specificity 0.692). There was no significant difference in tFF and R2* between MVI positive and negative nodules (3.00% vs 2.90%, P=0.784; 55.80s-1 vs 49.15s-1, P=0.227). Conclusion: We infer that intratumor fat can be identified in HCC and fat fraction quantification using quantitative multi-echo Dixon can distinguish low proliferative HCCs.

Prediction of preoperative microvascular invasion by dynamic radiomic analysis based on contrast-enhanced computed tomography.

PURPOSE: Microvascular invasion (MVI) is a common complication of hepatocellular carcinoma (HCC) surgery, which is an important predictor of reduced surgical prognosis. This study aimed to develop a fully automated diagnostic model to predict pre-surgical MVI based on four-phase dynamic CT images. METHODS: A total of 140 patients with HCC from two centers were retrospectively included (training set, n = 98; testing set, n = 42). All CT phases were aligned to the portal venous phase, and were then used to train a deep-learning model for liver tumor segmentation. Radiomics features were extracted from the tumor areas of original CT phases and pairwise subtraction images, as well as peritumoral features. Lastly, linear discriminant analysis (LDA) models were trained based on clinical features, radiomics features, and hybrid features, respectively. Models were evaluated by area under curve (AUC), accuracy, sensitivity, specificity, positive and negative predictive values (PPV and NPV). RESULTS: Overall, 86 and 54 patients with MVI- (age, 55.92 ± 9.62 years; 68 men) and MVI+ (age, 53.59 ± 11.47 years; 43 men) were included. Average dice coefficients of liver tumor segmentation were 0.89 and 0.82 in training and testing sets, respectively. The model based on radiomics (AUC = 0.865, 95% CI: 0.725-0.951) showed slightly better performance than that based on clinical features (AUC = 0.841, 95% CI: 0.696-0.936). The classification model based on hybrid features achieved better performance in both training (AUC = 0.955, 95% CI: 0.893-0.987) and testing sets (AUC = 0.913, 95% CI: 0.785-0.978), compared with models based on clinical and radiomics features (p-value < 0.05). Moreover, the hybrid model also provided the best accuracy (0.857), sensitivity (0.875), and NPV (0.917). CONCLUSION: The classification model based on multimodal intra- and peri-tumoral radiomics features can well predict HCC patients with MVI.

The value of contrast-enhanced ultrasound combined with microflow imaging in predicting microvascular invasion of hepatocellular carcinoma before operation.

OBJECTIVE: To evaluate the preoperative predictive value of contrast-enhanced ultrasound (CEUS) combined with microflow imaging (MFI) in microvascular invasion (MVI) of hepatocellular carcinoma (HCC). METHODS: In our study, 80 patients with HCC were analyzed retrospectively. According to the gold standard of postoperative pathology, the patients were divided into MVI positive group (n = 39) and MVI negative group (n = 41). we were to analyze the correlation between CEUS and MVI in combination with MFI, to identify independent risk factors for the occurrence of MVI positive, and to analyze the predictive efficacy of every independent risk factor and their combination in preoperative prediction of MVI. RESULTS: In our study, 80 patients were enrolled, including 39 patients in the MVI-positive group and 41 patients in the MVI-negative group, with a MVI-positive rate of 48.8%. By univariate analysis and multivariate analysis, it was found that there were statistically significant differences in enhancement range extension, start time of wash out and CEUS-MFI between the two groups, which were independent risk factors for MVI-positive. The combination of three independent risk factors is more effective than single one in predicting MVI of HCC. CONCLUSIONS: CEUS combined with MFI is feasible for the preoperative prediction of MVI in HCC, and can provides meaningful help for individualized clinical treatment.

Role of microvascular invasion in early recurrence of hepatocellular carcinoma after liver resection: A literature review.

Hepatectomy is widely considered a potential treatment for hepatocellular carcinoma (HCC). Unfortunately, one-third of HCC patients have tumor recurrence within 2 years after surgery (early recurrence), accounting for more than 60% of all recurrence patients. Early recurrence is associated with a worse prognosis. Previous studies have shown that microvascular invasion (MVI) is one of the key factors for early recurrence and poor prognosis in patients with HCC after surgery. This paper reviews the latest literature and summarizes the predictors of MVI, the correlation between MVI and early recurrence, the identification of suspicious nodules or subclinical lesions, and the treatment strategies for MVI-positive HCC. The aim is to explore the management of patients with MVI-positive HCC.

Radiogenomics nomogram based on MRI and microRNAs to predict microvascular invasion of hepatocellular carcinoma.

Purpose: This study aimed to develop and validate a radiogenomics nomogram for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) on the basis of MRI and microRNAs (miRNAs). Materials and methods: This cohort study included 168 patients (training cohort: n = 116; validation cohort: n = 52) with pathologically confirmed HCC, who underwent preoperative MRI and plasma miRNA examination. Univariate and multivariate logistic regressions were used to identify independent risk factors associated with MVI. These risk factors were used to produce a nomogram. The performance of the nomogram was evaluated by receiver operating characteristic curve (ROC) analysis, sensitivity, specificity, accuracy, and F1-score. Decision curve analysis was performed to determine whether the nomogram was clinically useful. Results: The independent risk factors for MVI were maximum tumor length, rad-score, and miRNA-21 (all P < 0.001). The sensitivity, specificity, accuracy, and F1-score of the nomogram in the validation cohort were 0.970, 0.722, 0.884, and 0.916, respectively. The AUC of the nomogram was 0.900 (95% CI: 0.808-0.992) in the validation cohort, higher than that of any other single factor model (maximum tumor length, rad-score, and miRNA-21). Conclusion: The radiogenomics nomogram shows satisfactory predictive performance in predicting MVI in HCC and provides a feasible and practical reference for tumor treatment decisions.

The influencing factors for tumor thrombus in patients with hepatocellular carcinoma.

Background: Microvascular invasion (MVI) is considered to be an important factor in the early invasion and metastasis of liver cancer, and the survival rate of patients with MVI is much lower than that of patients without MVI. Therefore, it is crucial to accurately predict the independent predictors of tumor thrombus formation. This study aimed to assess the risk factors for tumor thrombus grades in patients with hepatocellular carcinoma (HCC). Methods: Between August 2011 and December 2022, the data of 231 patients diagnosed with HCC were collected and divided into the following three groups: an MVI-negative group, an MVI-positive group, and a portal vein tumor thrombus (PVTT) group. Univariate analysis was used to compare the differences between the three groups in terms of clinical features, pathology, and imaging features. Multiple logistic regression analysis was used to analyze the risk factors associated with tumor thrombus grades, and the cutoff value was finally calculated by using the receiver operating characteristic (ROC) curve. Results: The incidence of MVI and PVTT in the patients with HCC were 10.0% and 6.1%, respectively; univariate analysis revealed statistically significant differences in tumor diameter, alpha fetoprotein level, Ki-67 expression level, gender, tumor quantity, arteriovenous fistula, peritumoral enhancement, and satellite nodules among the three groups (P<0.05). Multiple logistic regression analysis showed that Ki-67 expression level, tumor diameter, and peritumoral enhancement were independent risk factors for tumor thrombus grades (P<0.05). The area under the curve (AUC) of Ki-67 expression level and tumor diameter was 0.713 [95% confidence interval (CI): 0.626-0.800] and 0.753 (95% CI: 0.669-0.837), respectively, and the AUC of the combination analysis was 0.805 (95% CI: 0.723-0.888), with a cutoff value of 17.5% and 4.1 cm, respectively (P<0.05). Conclusions: Tumor diameter, Ki-67 expression level, and peritumoral enhancement can be used as independent predictors of tumor thrombus in patients with HCC. The combination of tumor diameter and Ki-67 expression level can further improve diagnostic efficacy.

Preoperative prediction of microvascular invasion: new insights into personalized therapy for early-stage hepatocellular carcinoma.

Owing to advances in diagnosis and treatment methods over past decades, a growing number of early-stage hepatocellular carcinoma (HCC) diagnoses has enabled a greater of proportion of patients to receive curative treatment. However, a high risk of early recurrence and poor prognosis remain major challenges in HCC therapy. Microvascular invasion (MVI) has been demonstrated to be an essential independent predictor of early recurrence after curative therapy. Currently, biopsy is not generally recommended before treatment to evaluate MVI in HCC according clinical guidelines due to sampling error and the high risk of tumor cell seeding following biopsy. Therefore, the postoperative histopathological examination is recognized as the gold standard of MVI diagnosis, but this lagging indicator greatly impedes clinicians in selecting the optimal effective treatment for prognosis. As imaging can now noninvasively and completely assess the whole tumor and host situation, it is playing an increasingly important role in the preoperative assessment of MVI. Therefore, imaging criteria for MVI diagnosis would be highly desirable for optimizing individualized therapeutic decision-making and achieving a better prognosis. In this review, we summarize the emerging image characteristics of different imaging modalities for predicting MVI. We also discuss whether advances in imaging technique have generated evidence that could be practice-changing and whether advanced imaging techniques will revolutionize therapeutic decision-making of early-stage HCC.