Radiological diagnosis of hepatocellular carcinoma.
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ABSTRACT:
SUBMITTER: Russo MW
PROVIDER: S-EPMC6499298 | biostudies-literature | 2012 Dec
REPOSITORIES: biostudies-literature
Publications
Radiological diagnosis of hepatocellular carcinoma.
Russo Mark W MW Wald Christoph C
Clinical liver disease 20121201 6
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Project description:Background & aimsThe diagnosis of hepatocellular carcinoma (HCC) in patients with cirrhosis relies on non-invasive criteria based on international guidelines. The advent of systemic therapies warrants reconsideration of the role of biopsy specimens in the diagnosis of HCC. Accordingly, we investigated the diagnostic performance of the LI-RADS 2018 and the AASLD 2011 criteria.MethodsConsecutive patients with cirrhosis who underwent a biopsy for suspected HCC between 2015 and 2020 were included. The available imaging studies (computed tomography and/or magnetic resonance imaging) were blindly reviewed by two independent radiologists. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were assessed for LI-RADS, AASLD, and biopsies.ResultsIn total, 167 patients underwent both available biopsy and imaging. Of the 137 relevant biopsies, 114 patients had HCC (83.2%), 12 (9%) had non-HCC malignant lesions, and 11 (8%) had benign nodules. The PPV and NPV of the biopsies were 100% and 62%, respectively; 30 biopsies were non-contributive. The PPV and NPV of the LI-RADS categories were 89% and 32.8% for LR-5 and 85.5% and 54.5% for LR-4 + 5 + TIV, respectively. The PPV and NPV of the 2011 AASLD criteria were 93.2% and 35.6%, respectively. The interobserver kappa (k = 0.380) for the LR-5 categories was reasonable. Of 100 LR-5 nodules, 11 were misclassified, in particular one case was a colorectal metastasis, and two cases were cholangiocarcinomas, of which nine were identified through biopsy, whereas six were correctly classified according to LI-RADS (LR-M or LR-TIV). Fifty percent of macrotrabecular HCC and 48.4% of poorly differentiated HCC (Edmonson 3 and 4) were not classified as LR-5.ConclusionsLI-RADS 2018 did not outperform the AASLD 2011 score as a non-invasive diagnosis of HCC. Tumor biopsy allowed restoration of an accurate diagnosis in 11% of LR-5 cases. A combined radiological and histological diagnosis should be considered mandatory for good treatment assessment.Impact and implicationsAlthough biopsy is not required for hepatocellular carcinoma diagnosis when the LI-RADS criteria are met according to current guidelines, our study underscores the limits of radiology and the need for biopsy when hepatocellular carcinoma is suspected. Histological findings could change therapeutics of liver tumors even if only for a small proportion of patients. Histological proof of the type of cancer is a standard in oncology.
| S-EPMC10792651 | biostudies-literature
Project description:Many advances have been made in the imaging diagnosis and in the histopathological evaluation of HCC. However, the classic imaging and histopathological features of HCC are still inadequate to define patient's prognosis. We aimed to find the link between new proposed morphovascular patterns of hepatocellular carcinoma (HCC) and magnetic resonance imaging (MRI) features to identify pre-operatory markers of biologically aggressive HCC. Thirty-nine liver nodules in 22 patients were consecutively identified. Histopathological analysis and immunohistochemistry for CD34 and Nestin were performed to identify the four different HCC morphovascular patterns. MRI was performed using gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid. Three out of four morphovascular HCC patterns showed peculiar MRI features: in particular Pattern D (solid aggressive HCCs with CD34+/Nestin+ new-formed arteries) were isointense on T1-WI in 83% of cases and hyperintense on T2-WI in 50%. Five histologically-diagnosed HCC were diagnosed as non-malignant nodules on MRI due to their early vascularization and low aggressiveness (Pattern A). The comparison between histology and MRI confirms that a subclassification of HCC is possible in a pre-operatory setting. MRI seems to reinforce once more the identity of the different morphovascular HCC patterns and the possibility to pre-operatively identify HCCs with features of biological aggressiveness.
| S-EPMC6791846 | biostudies-literature
Project description:This is a narrative review of various treatment modalities for advanced hepatocellular carcinoma (HCC), with a focus on recent updates in radiological treatments, as well as novel treatment concepts related to immune checkpoint inhibitors and combination therapies with locoregional treatments. Interventional radiologists have made efforts toward developing alternative and/or combination treatments for first-line systemic treatment of patients with advanced HCC. Locoregional treatments with or without systemic therapy may be considered in the selected patients. Various treatment modalities for advanced HCC are emerging, and several randomized controlled trials, including those of combination treatments with immunotherapy, are ongoing.
| S-EPMC8546136 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) ranks fourth in cancer-related deaths worldwide. Semiannual surveillance of the disease for patients with cirrhosis or hepatitis B virus allows for early detection with more favorable outcomes. The current underuse of surveillance programs demonstrates the need for intervention at both the patient and provider level. Mail outreach along with navigation provision has proven to increase surveillance follow-up in patients, while provider-targeted electronic medical record reminders and compliance reports have increased provider awareness of HCC surveillance. Imaging is the primary mode of diagnosis in HCC with The Liver Imaging Reporting and Data System (LI-RADS) being a widely accepted comprehensive system that standardizes the reporting and data collection for HCC. The management of HCC is complex and requires multidisciplinary team evaluation of each patient based on their preference, the state of the disease, and the available medical and surgical interventions. Staging systems are useful in determining the appropriate intervention for HCC. Early-stage HCC is best managed by curative treatment modalities, such as liver resection, transplant, or ablation. For intermediate stages of the disease, transarterial local regional therapies can be applied. Advanced stages of the disease are treated with systemic therapies, for which there have been recent advances with new drug combinations. Previously sorafenib was the mainstay systemic treatment, but the recent introduction of atezolizumab plus bevacizumab proves to have a greater impact on overall survival. Although there is a current lack of improved outcomes in Phase III trials, neoadjuvant therapies are a potential avenue for HCC management in the future.
| S-EPMC10647678 | biostudies-literature
Project description:The interdisciplinary guidelines at the S3 level on the diagnosis of and therapy for hepatocellular carcinoma (HCC) constitute an evidence- and consensus-based instrument that is aimed at improving the diagnosis of and therapy for HCC since these are very challenging tasks. The purpose of the guidelines is to offer the patient (with suspected or confirmed HCC) adequate, scientifically based and up-to-date procedures in diagnosis, therapy and rehabilitation. This holds not only for locally limited or focally advanced disease but also for the existence of recurrences or distant metastases. Besides making a contribution to an appropriate health-care service, the guidelines should also provide the foundation for an individually adapted, high-quality therapy. The explanatory background texts should also enable non-specialist but responsible colleagues to give sound advice to their patients concerning specialist procedures, side effects and results. In the medium and long-term this should reduce the morbidity and mortality of patients with HCC and improve their quality of life.
| S-EPMC6318804 | biostudies-literature
Project description:To develop diagnostic and prognostic biomarkers, we compared methylation profiles of HCC tissues and normal blood by analyzing 485,000 CpG markers and identified a HCC enriched methylation marker panel compared to that of normal blood. We found there was a highly correlation of methylation profiles between DNA from HCC cancer tissue and matched plasma ctDNA within the same patient. We then selected 10 markers from this panel and created a combined diagnosis score (cd-score) which showed high diagnostic specificity and sensitivity in both a training cohort and an independent validation cohort. We also showed the cd-score correlate highly with tumor load, treatment response and stage and is superior to that by AFP. We also showed the cd-score correlate highly with tumor load, treatment response and stage and is superior to that by AFP. Additional, we generated 8 markers from unicox and LASSO-cox analysis and created a combined prognosis score (cp-score) which could predict prognosis and survival. Together, these findings demonstrated the utility of ctDNA methylation markers in the diagnosis, treatment evaluation and prognosis of HCC.
2019-01-01 | GSE93203 | GEO
Project description:Hepatocellular carcinoma (HCC) is one of the most prevalent cancers globally. In contrast to the declining death rates observed for all other common cancers such as breast, lung, and prostate cancers, the death rates for HCC continue to increase by ~2-3% per year because HCC is frequently diagnosed late and there is no curative therapy for an advanced HCC. The early diagnosis of HCC is truly a big challenge. Over the past years, the early diagnosis of HCC has relied on surveillance with ultrasonography (US) and serological assessments of alpha-fetoprotein (AFP). However, the specificity and sensitivity of US/AFP is not satisfactory enough to detect early onset HCC. Recent technological advancements offer hope for early HCC diagnosis. Herein, we review the progress made in HCC diagnostics, with a focus on emerging imaging techniques and biomarkers for early disease diagnosis.
| S-EPMC7452544 | biostudies-literature
Project description:IntroductionGlobally, the incidence, as well as mortality, related to hepatocellular carcinoma (HCC) is on the rise, owing to relatively few curative options. Underlying cirrhosis is the most common etiology leading to HCC, but risk factors of cirrhosis show great regional variability. Over the years, there has been a steady development in the diagnostic and therapeutic modalities of HCC, including the availability of a wide range of systemic chemotherapeutic agents. We aim to review the recent advancements in the diagnostic and therapeutic strategies for HCC.MethodologyThe literature search was done using databases PubMed, Cochrane, and Science Direct, and the latest relevant articles were reviewed.FindingsScreening of HCC is a pivotal step in the early diagnosis of the disease. Current guidelines recommend using ultrasound and alfa fetoprotein but various new biomarkers are under active research that might aid in diagnosing very small tumors, not picked up by the current screening methods. Treatment options are decided based upon the overall performance of the patient and the extent of the disease, as per the Barcelona classification. There are very few options that offer a cure for the disease, ranging from liver resection and transplantation to tumor ablation. Downstaging has proven to have a significant role in the course of the disease. An attempt to control the disease can be made via radiological interventions, such as transarterial chemoembolization, transarterial radioembolization, or radiation therapy. For advanced disease, sorafenib used to be the only option until a couple of years ago. Recently, many other systemic agents have received approval as first-line and second-line therapies for HCC. Genomics is an area of active clinical research as understanding the mutations and genomics involved in the evolution of HCC might lead to a breakthrough therapy.How to cite this articleRaees A, Kamran M, Özkan H, et al. Updates on the Diagnosis and Management of Hepatocellular Carcinoma. Euroasian J Hepato-Gastroenterol 2021;11(1):32-40.
| S-EPMC8286363 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) has a high mortality rate owing to its complexity. Identification of abnormally expressed genes in HCC tissues compared to those in normal liver tissues is a viable strategy for investigating the mechanisms of HCC tumorigenesis and progression as a means of developing novel treatments. A significant advantage of the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) is that the data therein were collected from different independent researchers and may be integrated, allowing for a more robust data analysis. Accordingly, in the present study, the gene expression profiles for HCC and control samples were downloaded from the GEO and TCGA. Functional enrichment analysis was performed using a Metascape dataset, and a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins (STRING) online database. The prognostic value of mRNA for HCC was assessed using the Kaplan-Meier Plotter, a public online tool. A gene mRNA heatmap and DNA amplification numbers were obtained from cBioPortal. A total of 2,553 upregulated genes were identified. Functional enrichment analysis revealed that these differentially expressed genes (DEGs) were mainly accumulated in metabolism of RNA and the cell cycle. Considering the complexity and heterogeneity of the molecular alterations in HCC, multiple genes for the prognostication of patients with HCC are more reliable than a single gene. Thus, the PPI network and univariate Cox regression analysis were applied to screen candidate genes (small nuclear ribonucleoprotein polypeptide B and B1, nucleoporin 37, Rac GTPase activating protein 1, kinesin family member 20A, minichromosome maintenance 10 replication initiation factor, ubiquitin conjugating enzyme E2 C and hyaluronan mediated motility receptor) that are associated with the overall survival and progression-free survival of patients with HCC. In conclusion, the present study identified a set of genes that are associated with overall survival and progression-free survival of patients with HCC, providing valuable information for the prognosis of HCC.
| S-EPMC8630445 | biostudies-literature
Project description:AimThe diagnosis of hepatocellular carcinoma (HCC) in the early stage is crucial to the application of curative treatments which are the only hope for increasing the life expectancy of patients. Recently, several large-scale studies have shed light on this problem through analysis of gene expression profiles to identify markers correlated with HCC progression. However, those marker sets shared few genes in common and were poorly validated using independent data. Therefore, we developed a systems biology based classifier by combining the differential gene expression with topological features of human protein interaction networks to enhance the ability of HCC diagnosis.Methods and resultsIn the Oncomine platform, genes differentially expressed in HCC tissues relative to their corresponding normal tissues were filtered by a corrected Q value cut-off and Concept filters. The identified genes that are common to different microarray datasets were chosen as the candidate markers. Then, their networks were analyzed by GeneGO Meta-Core software and the hub genes were chosen. After that, an HCC diagnostic classifier was constructed by Partial Least Squares modeling based on the microarray gene expression data of the hub genes. Validations of diagnostic performance showed that this classifier had high predictive accuracy (85.88?92.71%) and area under ROC curve (approximating 1.0), and that the network topological features integrated into this classifier contribute greatly to improving the predictive performance. Furthermore, it has been demonstrated that this modeling strategy is not only applicable to HCC, but also to other cancers.ConclusionOur analysis suggests that the systems biology-based classifier that combines the differential gene expression and topological features of human protein interaction network may enhance the diagnostic performance of HCC classifier.
| S-EPMC3145651 | biostudies-literature