Focal nodular hyperplasia: what are the indications for resection?
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ABSTRACT:
SUBMITTER: Hsee LC
PROVIDER: S-EPMC2043107 | biostudies-other | 2005
REPOSITORIES: biostudies-other
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Project description:The molecular landscape and pathogenesis of focal nodular hyperplasia (FNH) have yet to be elucidated. We performed multi-omics approaches on FNH and paired normal liver tissues from 22 patients, followed by multi-level bioinformatic analyses and experimental validations. Generally, FNH had low mutation burden with low variant allele frequencies, and the mutation frequency significantly correlated with proliferation rate. Although no recurrently deleterious genomic events were found, some putative tumor suppressors or oncogenes were involved. Mutational signatures indicated potential impaired mismatch function and possible poison contact. Integrated analyses unveiled a group of FNH specific endothelial cells that uniquely expressed SOST and probably had strong interaction with fibroblasts through PDGFB/PDGFRB pathway to promote fibrosis. Notably, in one atypical FNH (patient No.11) with pronounced copy number variations, we observed a unique immune module. Most FNH are benign, but molecularly atypical FNH still exist; endothelial cell derived PDGFB probably promotes the fibrogenic process in FNH.
| S-EPMC9436768 | biostudies-literature
Project description:INTRODUCTION: Unlike malignant liver tumours, the indications for hepatic resection for benign disease are not well defined. This is particularly true for focal nodular hyperplasia (FNH). Here we summarize a single-centre experience of the diagnosis and management of FNH. MATERIALS AND METHODS: Using a prospectively collected database, a retrospective analysis of consecutive patients who were managed at our centre for FNH between January 1997 and December 2006 was performed. RESULTS: The cohort was divided into two groups of patients: those who were managed surgically (n=15) and those managed conservatively (n=37). There was no correlation between tumour size and number of lesions with oral contraceptive use (p=0.07 and 0.90, respectively) and pregnancy (p=0.45 and 0.60, respectively). However, tumour size (p=0.006) and number of lesions (p=0.02) were associated with the occurrence of pain in these patients. Pain was the commonest symptom of patients (13/15) who were managed surgically. All patients underwent radiological imaging before diagnosis. The sensitivities of ultrasound, CT scanning and MRI scanning in characterizing these lesions were 30%, 70% and 87%, respectively. There were no postoperative deaths and three postoperative complications that were successfully managed non-operatively. With a median follow-up of 24 months in the surgically treated group, one patient has developed recurrent symptoms of pain. CONCLUSION. In this series, there was no mortality directly due to the surgical procedure and a modest morbidity, justifying surgical resections in selected patients.
| S-EPMC2225515 | biostudies-other
Project description:Background: We conduct a study in developing and validating two radiomics-based models to preoperatively distinguish hepatic epithelioid angiomyolipoma (HEAML) from hepatic carcinoma (HCC) as well as focal nodular hyperplasia (FNH). Methods: Totally, preoperative contrast-enhanced computed tomography (CT) data of 170 patients and preoperative contrast-enhanced magnetic resonance imaging (MRI) data of 137 patients were enrolled in this study. Quantitative texture features and wavelet features were extracted from the regions of interest (ROIs) of each patient imaging data. Then two radiomics signatures were constructed based on CT and MRI radiomics features, respectively, using the random forest (RF) algorithm. By integrating radiomics signatures with clinical characteristics, two radiomics-based fusion models were established through multivariate linear regression and 10-fold cross-validation. Finally, two diagnostic nomograms were built to facilitate the clinical application of the fusion models. Results: The radiomics signatures based on the RF algorithm achieved the optimal predictive performance in both CT and MRI data. The area under the receiver operating characteristic curves (AUCs) reached 0.996, 0.879, 0.999, and 0.925 for the training as well as test cohort from CT and MRI data, respectively. Then, two fusion models simultaneously integrated clinical characteristics achieved average AUCs of 0.966 (CT data) and 0.971 (MRI data) with 10-fold cross-validation. Through decision curve analysis, the fusion models were proved to be excellent models to distinguish HEAML from HCC and FNH in comparison between the clinical models and radiomics signatures. Conclusions: Two radiomics-based models derived from CT and MRI images, respectively, performed well in distinguishing HEAML from HCC and FNH and might be potential diagnostic tools to formulate individualized treatment strategies.
| S-EPMC7573543 | biostudies-literature
Project description:AimTo identify clonality and genetic alterations in focal nodular hyperplasia (FNH) and the nodules derived from it.MethodsTwelve FNH lesions were examined. Twelve hepatocellular adenomas (HCAs) and 22 hepatocellular carcinomas (HCCs) were used as references. Nodules of different types were identified and isolated from FNH by microdissection. An X-chromosome inactivation assay was employed to describe their clonality status. Loss of heterozygosity (LOH) was detected, using 57 markers, for genetic alterations.ResultsNodules of altered hepatocytes (NAH), the putative precursors of HCA and HCC, were found in all the FNH lesions. Polyclonality was revealed in 10 FNH lesions from female patients, and LOH was not detected in any of the six FNH lesions examined, the results apparently showing their polyclonal nature. In contrast, monoclonality was demonstrated in all the eight HCAs and in four of the HCCs from females, and allelic imbalances were found in the HCAs (9/9) and HCCs (15/18), with chromosomal arms 11p, 13q and 17p affected in the former, and 6q, 8p, 11p, 16q and 17p affected in the latter lesions in high frequencies (> or = 30%). Monoclonality was revealed in 21 (40%) of the 52 microdissected NAH, but was not found in any of the five ordinary nodules. LOH was found in all of the 13 NAH tested, being highly frequent at six loci on 8p, 11p, 13q and 17p.ConclusionFNH, as a whole, is polyclonal, but some of the NAH lesions derived from it are already neoplastic and harbor similar allelic imbalances as HCAs.
| S-EPMC2754518 | biostudies-literature
Project description:PURPOSE: The aim of this study was to assess the enhancement patterns of hepatic focal nodular hyperplasia (FNH) on gadoxetic acid-enhanced MRI and diffusion-weighted (DW) MRI. METHODS: This retrospective study had institutional review board approval. Gadoxetic acid-enhanced and DW MR images were evaluated in 23 patients with 30 FNHs (26 histologically proven and 4 radiologically diagnosed). The lesion enhancement patterns of the hepatobiliary phase images were classified as heterogeneous or homogeneous signal intensity (SI), and as dominantly high/iso or low SI compared with those of adjacent liver parenchyma. Heterogeneous (any) SI lesions and homogeneous low SI lesions were categorised into the fibrosis group, whereas homogeneous high/iso SI lesions were categorised into the non-fibrosis group. Additionally, lesion SI on T2 weighted images, DW images and apparent diffusion coefficient (ADC) values were compared between the two groups. RESULTS: The lesions showed heterogeneous high/iso SI (n=16), heterogeneous low SI (n=5), homogeneous high/iso SI (n=7) or homogeneous low SI (n=2) at the hepatobiliary phase MR images. The fibrosis group lesions were more likely to show high SI on DW images and T2 weighted images compared with those in the non-fibrosis group (p<0.05). ADC values tended to be lower in the fibrosis group than those in the non-fibrosis group without significance. CONCLUSION: FNH showed variable enhancement patterns on hepatobiliary phase images during gadoxetic acid-enhanced MRI. SI on DW and T2 weighted images differed according to the fibrosis component contained in the lesion. ADVANCES IN KNOWLEDGE: FNH shows a wide spectrum of imaging findings on gadoxetic acid-enhanced MRI and DW MRI.
| S-EPMC3745063 | biostudies-other
Project description:OBJECTIVE: To explore the potential of quantitative analysis of contrast-enhanced ultrasonography (CEUS) in differentiating focal nodular hyperplasia (FNH) from hepatocellular carcinoma (HCC). METHODS: 34 cases of FNH and 66 cases of HCC (all lesions <5 cm) were studied using CEUS to evaluate enhancement patterns and using analytic software Sonoliver® (Image-Arena™ v.4.0, TomTec Imaging Systems, Munich, Germany) to obtain quantitative features of CEUS in the region of interest. The quantitative features of maximum of intensity (IMAX), rise slope (RS), rise time (RT) and time to peak (TTP) were compared between the two groups and applied to further characterise both FNH and HCC with hypoenhancing patterns in the late phase on CEUS. RESULTS: The sensitivity and specificity of CEUS for diagnosis of FNH were 67.6% and 93.9%, respectively. For quantitative analysis, IMAX and RS in FNHs were significantly higher than those in HCCs (p<0.05), while RT and TTP in FNHs were significantly shorter (p<0.05). Both the 11 FNHs and 62 HCCs with hypo-enhancing patterns in the late phase were further characterised with their quantitative features, and the sensitivity and specificity of IMAX for diagnosis of FNH were 90.9% and 43.5%, RS 81.8% and 80.6%, RT 90.9% and 71.0%, and TTP 90.9% and 71.0%, respectively. CONCLUSION: The quantitative features of CEUS in FNH and HCC were significantly different, and they could further differentiate FNH from HCC following conventional CEUS. ADVANCES IN KNOWLEDGE: Our findings suggest that quantitative analysis of CEUS can improve the accuracy of differentiating FNH from HCC.
| S-EPMC3608056 | biostudies-other
Project description:Background and aimsHepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. This study was designed to investigate the value of computed tomography (CT) spectral imaging in differentiating HCC from hepatic hemangioma (HH) and focal nodular hyperplasia (FNH).MethodsThis was a retrospective study of 51 patients who underwent spectral multiple-phase CT at 40-140 keV during the arterial phase (AP) and portal venous phase (PP). Slopes of the spectral curves, iodine density, water density derived from iodine- and water-based material decomposition images, iodine uptake ratio (IUR), normalized iodine concentration, and the ratio of iodine concentration in liver lesions between AP and PP were measured or calculated.ResultsAs energy level decreased, the CT values of HCC (n=31), HH (n=17), and FNH (n=7) increased in both AP and PP. There were significant differences in IUR in the AP, IUR in the PP, normalized iodine concentration in the AP, slope in the AP, and slope in the PP among HCC, HH, and FNH. The CT values in AP, IUR in the AP and PP, normalized iodine concentration in the AP, slope in the AP and PP had high sensitivity and specificity in differentiating HH and HCC from FNH. Quantitative CT spectral data had higher sensitivity and specificity than conventional qualitative CT image analysis during the combined phases.ConclusionsMean CT values at low energy (40-90 keV) and quantitative analysis of CT spectral data (IUR in the AP) could be helpful in the differentiation of HCC, HH, and FNH.
| S-EPMC8237149 | biostudies-literature
Project description:Focal nodular hyperplasia (FNH) and hepatocellular adenoma (HCA) are benign hepatocellular tumors. The risk of bleeding and malignant transformation of HCA are strong arguments to differentiate HCA from FNH. Despite great progress that has been made in the differential radiological diagnosis of the 2 types of nodules, liver biopsy is sometimes necessary to separate the 2 entities. Identification of HCA subtypes using immunohistochemical techniques, namely, HNF1A-inactivated HCA (35-40%), inflammatory HCA (IHCA), and beta-catenin-mutated inflammatory HCA (b-IHCA) (50-55%), beta-catenin-activated HCA (5-10%), and unclassified HCA (10%) has greatly improved the diagnostic accuracy of benign hepatocellular nodules. If HCA malignant transformation occurs in all HCA subgroups, the risk is by far the highest in the ? -catenin-mutated subgroups (b-HCA, b-IHCA). In the coming decade the management of HCA will be more dependent on the identification of HCA subtypes, particularly for smaller nodules (<5?cm) in terms of imaging, follow-up, and resection.
| S-EPMC3654480 | biostudies-literature
Project description:BackgroundThe typical enhancement patterns of hepatocellular carcinoma (HCC) on contrast-enhanced ultrasound (CEUS) are hyper-enhanced in the arterial phase and washed out during the portal venous and late phases. However, atypical variations make a differential diagnosis both challenging and crucial. We aimed to investigate whether machine learning-based ultrasonic signatures derived from CEUS images could improve the diagnostic performance in differentiating focal nodular hyperplasia (FNH) and atypical hepatocellular carcinoma (aHCC).Patients and methodsA total of 226 focal liver lesions, including 107 aHCC and 119 FNH lesions, examined by CEUS were reviewed retrospectively. For machine learning-based ultrasomics, 3,132 features were extracted from the images of the baseline, arterial, and portal phases. An ultrasomics signature was generated by a machine learning model. The predictive model was constructed using the support vector machine method trained with the following groups: ultrasomics features, radiologist's score, and combination of ultrasomics features and radiologist's score. The diagnostic performance was explored using the area under the receiver operating characteristic curve (AUC).ResultsA total of 14 ultrasomics features were chosen to build an ultrasomics model, and they presented good performance in differentiating FNH and aHCC with an AUC of 0.86 (95% confidence interval [CI]: 0.80, 0.89), a sensitivity of 76.6% (95% CI: 67.5%, 84.3%), and a specificity of 80.5% (95% CI: 70.6%, 85.9%). The model trained with a combination of ultrasomics features and the radiologist's score achieved a significantly higher AUC (0.93, 95% CI: 0.89, 0.96) than that trained with the radiologist's score (AUC: 0.84, 95% CI: 0.79, 0.89, P < 0.001). For the sub-group of HCC with normal AFP value, the model trained with a combination of ultrasomics features, and the radiologist's score remain achieved the highest AUC of 0.92 (95% CI: 0.87, 0.96) compared to that with the ultrasomics features (AUC: 0.86, 95% CI: 0.74, 0.89, P < 0.001) and radiologist's score (AUC: 0.86, 95% CI: 0.79, 0.91, P < 0.001).ConclusionsMachine learning-based ultrasomics performs as well as the staff radiologist in predicting the differential diagnosis of FNH and aHCC. Incorporating an ultrasomics signature into the radiologist's score improves the diagnostic performance in differentiating FNH and aHCC.
| S-EPMC8033198 | biostudies-literature
Project description:BackgroundFocal nodular hyperplasia (FNH) is typically considered a benign tumor of the liver without malignant potential. The co-occurrence of FNH and hepatocellular carcinoma (HCC) has been reported in rare cases. In this study we sought to investigate the clonal relationship between these lesions in a patient with FNH-HCC co-occurrence.MethodsA 74-year-old female patient underwent liver tumor resection. The resected nodule was subjected to histologic analyses using hematoxylin and eosin stain and immunohistochemistry. DNA extracted from microdissected FNH and HCC regions was subjected to whole exome sequencing. Clonality analysis were performed using PyClone.ResultsHistologic analysis reveals that the nodule consists of an FNH and two adjoining HCC components with distinct histopathological features. Immunophenotypic characterization and genomic analyses suggest that the FNH is clonally related to the HCC components, and is composed of multiple clones at diagnosis, that are likely to have progressed to HCC through clonal selection and/or the acquisition of additional genetic events.ConclusionTo the best of our knowledge, our work is the first study showing a clonal relationship between FNH and HCC. We show that FNH may possess the capability to undergo malignant transformation and to progress to HCC in very rare cases.
| S-EPMC9053256 | biostudies-literature