A computed tomography radiogenomic biomarker predicts microvascular invasion and clinical outcomes in hepatocellular carcinoma.
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Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is an independent predictor of poor outcomes subsequent to surgical resection or liver transplantation (LT); however, MVI currently cannot be adequately determined preoperatively. Radiogenomic venous invasion (RVI) is a contrast-enhanced computed tomography (CECT) biomarker of MVI derived from a 91-gene HCC "venous invasion" gene expression signature. Preoperative CECTs of 157 HCC patients who underwent surgical resection (N?=?72) or LT (N?=?85) between 2000 and 2009 at three institutions were evaluated for the presence or absence of RVI. RVI was assessed for its ability to predict MVI and outcomes. Interobserver agreement for scoring RVI was substantial among five radiologists (??=?0.705; P?147 months), American Joint Committee on Cancer tumor-node-metastasis stage II (P?147 months), and in LT patients within Milan criteria (P?147 months). Positive RVI score also portended lower recurrence-free survival at 3 years versus negative RVI score (P?=?0.001; 27% vs. 62%).Conclusion
RVI is a noninvasive radiogenomic biomarker that accurately predicts histological MVI in HCC surgical candidates. Its presence on preoperative CECT is associated with early disease recurrence and poor OS and may be useful for identifying patients less likely to derive a durable benefit from surgical treatment.
SUBMITTER: Banerjee S
PROVIDER: S-EPMC4654334 | biostudies-literature | 2015 Sep
REPOSITORIES: biostudies-literature
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Project description:Background and aimsThe recurrence and metastasis of hepatocellular carcinoma (HCC) are mainly caused by microvascular invasion (MVI). Our study aimed to uncover the cellular atlas of MVI+ HCC and investigate the underlying immune infiltration patterns with radiomics features.MethodsThree MVI positive HCC and three MVI negative HCC samples were collected for single-cell RNA-seq analysis. 26 MVI positive HCC and 30 MVI negative HCC tissues were underwent bulk RNA-seq analysis. For radiomics analysis, radiomics features score (Radscore) were built using preoperative contrast MRI for MVI prediction and overall survival prediction. We deciphered the metabolism profiles of MVI+ HCC using scMetabolism and scFEA. The correlation of Radscore with the level of APOE+ macrophages and iCAFs was identified. Whole Exome Sequencing (WES) was applied to distinguish intrahepatic metastasis (IM) and multicentric occurrence (MO). Transcriptome profiles were compared between IM and MO.ResultsElevated levels of APOE+ macrophages and iCAFs were detected in MVI+ HCC. There was a strong correlation between the infiltration of APOE+ macrophages and iCAFs, as confirmed by immunofluorescent staining. MVI positive tumors exhibited increased lipid metabolism, which was attributed to the increased presence of APOE+ macrophages. APOE+ macrophages and iCAFs were also found in high levels in IM, as opposed to MO. The difference of infiltration level and Radscore between two nodules in IM was relatively small. Furthermore, we developed Radscore for predicting MVI and HCC prognostication that were also able to predict the level of infiltration of APOE+ macrophages and iCAFs.ConclusionThis study demonstrated the interactions of cell subpopulations and distinct metabolism profiles in MVI+ HCC. Besides, MVI prediction Radscore and MVI prognostic Radscore were highly correlated with the infiltration of APOE+ macrophages and iCAFs, which helped to understand the biological significance of radiomics and optimize treatment strategy for MVI+ HCC.
| S-EPMC10583459 | biostudies-literature
Project description:BACKGROUND:To investigate the potential value of volumetric iodine quantification using preoperative dual-energy computed tomography (DECT) for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). METHODS:This retrospective study included patients with single HCC treated through surgical resection who underwent preoperative DECT. Quantitative DECT features, including normalized iodine concentration (NIC) to the aorta and mixed-energy CT attenuation value in the arterial phase, were three-dimensionally measured for peritumoral and intratumoral regions: (i) layer-by-layer analysis for peritumoral layers (outer layers 1 and 2; numbered in close order from the tumor boundary) and intratumoral layers (inner layers 1 and 2) with 2-mm layer thickness and (ii) volume of interest (VOI)-based analysis with different volume coverage (tumor itself; VOIO1, tumor plus outer layer 1; VOIO2, tumor plus outer layers 1 and 2; VOII1, tumor minus inner layer 1; VOII2, tumor minus inner layers 1 and 2). In addition, qualitative CT features, including peritumoral enhancement and tumor margin, were assessed. Qualitative and quantitative CT features were compared between HCC patients with and without MVI. Diagnostic performance of DECT parameters of layers and VOIs was assessed using receiver operating characteristic curve analysis. RESULTS:A total of 36 patients (24 men, mean age 59.9 ± 8.5 years) with MVI (n = 14) and without MVI (n = 22) were included. HCCs with MVI showed significantly higher NICs of outer layer 1, outer layer 2, VOIO1, and VOIO2 than those without MVI (P = 0.01, 0.04, 0.02, 0.02, respectively). Among the NICs of layers and VOIs, the highest area under the curve was obtained in outer layer 1 (0.747). Qualitative features, including peritumoral enhancement and tumor margin, and the mean CT attenuation of each layer and each VOI were not significantly different between HCCs with and without MVI (both P > 0.05). CONCLUSIONS:Volumetric iodine quantification of peritumoral and intratumoral regions in arterial phase using DECT may help predict the MVI of HCC.
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Project description:Background: Previous studies reported that stress-induced phosphoprotein 1 (STIP1) can be secreted by hepatocellular carcinoma (HCC) cells and is increased in the serum of HCC patients. However, the therapy-monitoring and prognostic value of serum STIP1 in HCC remains unclear. Here, we aimed to systemically explore the prognostic significance of serum STIP1 in HCC. Methods: A total of 340 HCC patients were recruited to this study; 161 underwent curative resection and 179 underwent transcatheter arterial chemoembolization (TACE). Serum STIP1 was detected by enzyme-linked immunosorbent assay (ELISA). Optimal cutoff values for serum STIP1 in resection and TACE groups were determined by receiver operating characteristic (ROC) analysis. Prognostic value was assessed by Kaplan-Meier, log-rank, and Cox regression analyses. Predictive values of STIP1 for objective response (OR) to TACE and MVI were evaluated by ROC curves and logistic regression. Results: Serum STIP1 was significantly increased in HCC patients when compared with chronic hepatitis B patients or health donors (both P < 0.05). Optimal cutoff values for STIP1 in resection and TACE groups were 83.43 and 112.06 ng/ml, respectively. High pretreatment STIP1 was identified as an independent prognosticator. Dynamic changes in high STIP1 status were significantly associated with long-term prognosis, regardless of treatment approaches. Moreover, post-TACE STIP1 was identified as an independent predictor for OR, with a higher area under ROC curve (AUC-ROC) than other clinicopathological features. Specifically, pretreatment STIP1 was significantly increased in patients with microvascular invasion (MVI), and was confirmed as a novel, powerful predictor for MVI. Conclusions: Serum STIP1 is a promising biomarker for outcome evaluation, therapeutic response assessment, and MVI prediction in HCC. Integration serum STIP1 detection into HCC management might facilitate early clinical decision making to improve the prognosis of HCC.
| S-EPMC7212360 | biostudies-literature
Project description:Background Microvascular invasion (MVI) can only be assessed on a full surgical specimen. We aimed at evaluating, whether the histology of the primary tumor is predictive of MVI in a hepatocellular carcinoma (HCC) recurrence. Methods Patients, who underwent liver resection or orthotopic liver transplantation (OLT) for recurrent HCC from January 2001 until June 2018 were eligible for this retrospective analysis. Resected specimens were evaluated for HCC subtype/morphology, vessels encapsulating tumor clusters (VETC)-pattern and MVI. Dichotomous parameters were analyzed using χ2-test and ϕ-values, with P values <0.05 being considered significant. Results Of 230 HCC recurrences, 37 (16.1%) underwent repeated liver resection (n=22) or OLT (n=15). Of these, 67.6% initially exceeded the Milan criteria. MVI correlated Milan criteria (P=0.005), tumor size (P=0.015) and VETC-pattern (P=0.034) in the primary specimen. The recurrences shared many features of the primary HCC such as tumor grade (P=0.002), VETC-pattern (P=0.035), and MVI (P=0.046). In recurrences, however, only the concordance with the Milan criteria correlated with MVI (P=0.018). No patient without MVI in the primary HCC revealed MVI on early recurrence (<2 years) (P=0.035). Conclusions HCC recurrences share many biological features of the primary tumor. Moreover, early recurrences of MVI-negative HCC never revealed MVI. This finding offers novel concepts, e.g., patient selection for salvage OLT.
| S-EPMC10129893 | biostudies-literature
Project description:ObjectiveTo investigate microvascular invasion (MVI) of HCC through a noninvasive multi-disciplinary team (MDT)-like radiomics fusion model on dynamic contrast enhanced (DCE) computed tomography (CT).MethodsThis retrospective study included 111 patients with pathologically proven hepatocellular carcinoma, which comprised 57 MVI-positive and 54 MVI-negative patients. Target volume of interest (VOI) was delineated on four DCE CT phases. The volume of tumor core (V tc ) and seven peripheral tumor regions (V pt , with varying distances of 2, 4, 6, 8, 10, 12, and 14 mm to tumor margin) were obtained. Radiomics features extracted from different combinations of phase(s) and VOI(s) were cross-validated by 150 classification models. The best phase and VOI (or combinations) were determined. The top predictive models were ranked and screened by cross-validation on the training/validation set. The model fusion, a procedure analogous to multidisciplinary consultation, was performed on the top-3 models to generate a final model, which was validated on an independent testing set.ResultsImage features extracted from V tc +V pt(12mm) in the portal venous phase (PVP) showed dominant predictive performances. The top ranked features from V tc +V pt(12mm) in PVP included one gray level size zone matrix (GLSZM)-based feature and four first-order based features. Model fusion outperformed a single model in MVI prediction. The weighted fusion method achieved the best predictive performance with an AUC of 0.81, accuracy of 78.3%, sensitivity of 81.8%, and specificity of 75% on the independent testing set.ConclusionImage features extracted from the PVP with V tc +V pt(12mm) are the most reliable features indicative of MVI. The MDT-like radiomics fusion model is a promising tool to generate accurate and reproducible results in MVI status prediction in HCC.
| S-EPMC8008108 | biostudies-literature
Project description:BackgroundPreoperative prediction of microvascular invasion (MVI) is critical for treatment strategy making in patients with hepatocellular carcinoma (HCC). We aimed to develop a deep learning (DL) model based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict the MVI status and clinical outcomes in patients with HCC.MethodsWe retrospectively included a total of 321 HCC patients with pathologically confirmed MVI status. Preoperative DCE-MRI of these patients were collected, annotated, and further analyzed by DL in this study. A predictive model for MVI integrating DL-predicted MVI status (DL-MVI) and clinical parameters was constructed with multivariate logistic regression.ResultsOf 321 HCC patients, 136 patients were pathologically MVI absent and 185 patients were MVI present. Recurrence-free survival (RFS) and overall survival (OS) were significantly different between the DL-predicted MVI-absent and MVI-present. Among all clinical variables, only DL-predicted MVI status and a-fetoprotein (AFP) were independently associated with MVI: DL-MVI (odds ratio [OR] = 35.738; 95% confidence interval [CI] 14.027-91.056; p < 0.001), AFP (OR = 4.634, 95% CI 2.576-8.336; p < 0.001). To predict the presence of MVI, DL-MVI combined with AFP achieved an area under the curve (AUC) of 0.824.ConclusionsOur predictive model combining DL-MVI and AFP achieved good performance for predicting MVI and clinical outcomes in patients with HCC.
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Project description:Age-related loss of muscle mass and function (sarcopenia) is linked to poor outcomes after operation and trauma. Here we evaluate computed tomography measured psoas muscle density and area using quick and simple tools available to the bedside clinician. We hypothesize these measures will predict poor outcomes after blunt traumatic injury.We conducted a retrospective cohort study of patients ages ?45 years in the Ohio State University Trauma Registry in 2008 that received a computed tomographic scan of the abdomen and/or pelvis with intravenous contrast. Psoas Index and Hounsfield unit average calculation were measured at the L3 level. In the study, 90-day mortality, complication, duration of stay ?7 days, and dependent discharge were compared with Psoas Index and Hounsfield unit average calculation.In the study, 151 patients met the inclusion criteria. Patients were stratified into interquartile ranges based either on Psoas Index or Hounsfield unit average calculation values. After adjustment with sex-specific cutoffs, the lowest interquartile range of Psoas Index was associated with 90-day mortality (relative risk [RR] 5.95, P < .008), but did not reach significance in other outcomes. The lowest interquartile range of Hounsfield unit average calculation was associated with 90-day mortality (RR 5.95, P < .008), duration of stay ? 7 days (RR 1.63, P = .048), complication risk (RR 2.30, P = .002), and dependent discharge 2.14, P = .015).Psoas muscle density is a significant predictor of poor outcomes after traumatic injury. This objective, quick, and readily available measure of sarcopenia can identify patients requiring aggressive nutritional and physical therapy to improve prognosis, prevent recurrent traumatic injury, and aid in discharge planning.
| S-EPMC5893151 | biostudies-literature
Project description:ObjectivesTo compare the efficacy and safety of ultrasound (US) and computed tomography (CT) in the guidance of radiofrequency ablation (RFA) for hepatocellular carcinoma (HCC).Materials and methodsWe retrospectively analyzed consecutive treatment-naïve patients who received curative RFA for HCC from January 2008 to July 2013. Patients were divided into the US group or the CT group according to their RFA guidance instruments. Patients who were only suitable for US- or CT-guided RFA were excluded. Cumulative incidences of and hazard ratios for HCC recurrence were analyzed after adjusting for competing mortality risk.ResultsWe recruited a total of 101 patients in the US group and 51 patients in the CT group. The baseline demographic characteristics were not significantly different in both groups. Initial response rates were similar between the two groups (US vs. CT: 89.1% vs. 92.2%, p = 0.54), and complete tumor ablation was finally achieved for all patients. However, more ablations per session were performed in US group (median 2.0 [1.0-3.0] vs. 1.0 [1.0-2.0]; p<0.01). The 1-, 2- and 3-year local tumor recurrence rates (US vs. CT: 13.0%, 20.9%, and 29.2% vs. 11.2%, 29.8% and 29.8%, respectively) and overall mortality rates (US vs. CT: 5.2%, 9.6% and 16.5% vs. 0%, 3.1% and 23.8%, respectively) were not significantly different. In multivariate analysis, tumor characteristics and underlying liver function, but not US or CT guidance, were independent prognostic factors. The complication rates were similar between the two groups (US vs. CT: 10.9% vs. 9.8%; p = 0.71), and there was no procedure-related mortality.ConclusionsWith comparable major outcomes, either US or CT can be used in the guidance of RFA in experience hands.
| S-EPMC5221821 | biostudies-literature
Project description:Microvascular invasion (MVI) of hepatocellular carcinoma (HCC) is a major risk factor for early recurrence and poor survival after curative surgical therapies. However, MVI can only be diagnosed by pathological examination following resection. The aim of this study is to identify serologic biomarkers for predicting MVI preoperatively to help facilitate treatment decisions. We used the sero-proteomic approach to identify antigens that induce corresponding antibody responses either specifically in the serum from MVI (+) patients or from MVI (-) patients. Six antigens were subsequently identified as HSP 70, HSP 90, alpha-enolase (Eno-1), Annexin A2, glutathione synthetase and beta-actin by mass spectrometry. The antibodies titers in sera corresponding to four of these six antigens were measured by ELISA and compared between 35 MVI (+) patients and 26 MVI (-) patients. The titers of anti-HSP 70 antibodies were significantly higher in MVI (-) patients than those in MVI (+) patients; and the titers of anti-Eno-1 antibodies were significantly lower in MVI (-) patients than those in MVI (+) patients. The results were subjected to multivariate analysis together with other clinicopathologic factors, suggesting that antibodies against HSP 70 and Eno-1 in sera are potential biomarkers for predicting MVI in HCC prior to surgical resection. These biomarkers should be further investigated as potential therapeutic targets.
| S-EPMC4941320 | biostudies-literature
Project description:BackgroundRadiomics has emerged as a new approach that can help identify imaging information associated with tumor pathophysiology. We developed and validated a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).MethodsTwo hundred and eight patients with pathologically confirmed HCC (training cohort: n = 146; validation cohort: n = 62) who underwent preoperative gadoxetic acid-enhanced magnetic resonance (MR) imaging were included. Least absolute shrinkage and selection operator logistic regression was applied to select features and construct signatures derived from MR images. Univariate and multivariate analyses were used to identify the significant clinicoradiological variables and radiomics signatures associated with MVI, which were then incorporated into the predictive nomogram. The performance of the radiomics nomogram was evaluated by its calibration, discrimination, and clinical utility.ResultsHigher α-fetoprotein level (p = 0.046), nonsmooth tumor margin (p = 0.003), arterial peritumoral enhancement (p < 0.001), and the radiomics signatures of hepatobiliary phase (HBP) T1-weighted images (p < 0.001) and HBP T1 maps (p < 0.001) were independent risk factors of MVI. The predictive model that incorporated the clinicoradiological factors and the radiomic features derived from HBP images outperformed the combination of clinicoradiological factors in the training cohort (area under the curves [AUCs] 0.943 vs. 0.850; p = 0.002), though the validation did not have a statistical significance (AUCs 0.861 vs. 0.759; p = 0.111). The nomogram based on the model exhibited C-index of 0.936 (95% CI 0.895-0.976) and 0.864 (95% CI 0.761-0.967) in the training and validation cohort, fitting well in calibration curves (p > 0.05). Decision curve analysis further confirmed the clinical usefulness of the nomogram.ConclusionsThe nomogram incorporating clinicoradiological risk factors and radiomic features derived from HBP images achieved satisfactory preoperative prediction of the individualized risk of MVI in patients with HCC.
| S-EPMC6873064 | biostudies-literature