Dataset Information

Identification of Arterial Hyperenhancement in CT and MRI in Patients with Hepatocellular Carcinoma: Value of Unenhanced Images.

ABSTRACT:

Objective

According to the current guidelines, arterial hyperenhancement for diagnosis of hepatocellular carcinoma (HCC) is determined using the arterial phase only. We investigated the optimal definition of arterial hyperenhancement in patients with HCC using computed tomography (CT) and magnetic resonance imaging (MRI).

Materials and methods

The Institutional Review Board approved this retrospective study. The requirement for informed consent was waived. Between January 2011 and September 2013, 147 consecutive patients with surgically proven HCCs with both pre-operative CT and MRI were included. Identification rates of arterial hyperenhancement on CT and magnetic resonance (MR) images using arterial phase only, dual phase (unenhanced and arterial phases), and also subtraction MR images were assessed qualitatively.

Results

The identification rates for arterial hyperenhancement on CT were significantly different between arterial phase and dual phase (72.8% vs. 90.5%; p < 0.001), whereas the rates were similar on MRI (91.8% vs. 93.9%; p = 0.257). The identification rate of arterial hyperenhancement in MRI increased to 98.6% using subtraction MR images.

Conclusion

Visual comparison of arterial and unenhanced phases could be recommended instead of conventional qualitative arterial phase alone assessment to determine arterial hyperenhancement of HCCs, especially when using CT.

SUBMITTER: Kim M

PROVIDER: S-EPMC6342759 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Publications

Identification of Arterial Hyperenhancement in CT and MRI in Patients with Hepatocellular Carcinoma: Value of Unenhanced Images.

Kim Mimi M Kang Tae Wook TW Cha Dong Ik DI Jang Kyoung Mi KM Kim Young Kon YK Kim Seong Hyun SH Sinn Dong Hyun DH Kim Kyunga K

Korean journal of radiology 20190201 2

<h4>Objective</h4>According to the current guidelines, arterial hyperenhancement for diagnosis of hepatocellular carcinoma (HCC) is determined using the arterial phase only. We investigated the optimal definition of arterial hyperenhancement in patients with HCC using computed tomography (CT) and magnetic resonance imaging (MRI).<h4>Materials and methods</h4>The Institutional Review Board approved this retrospective study. The requirement for informed consent was waived. Between January 2011 and ...[more]

PMID: 30672163

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Project description:PurposeAccurate lesion segmentation is a prerequisite for radiomic feature extraction. It helps to reduce the features variability so as to improve the reporting quality of radiomics study. In this research, we aimed to conduct a radiomic feature reproducibility test of inter-/intra-observer delineation variability in hepatocellular carcinoma using 3D-CT images, 4D-CT images and multiple-parameter MR images.Materials and methodsFor this retrospective study, 19 HCC patients undergoing 3D-CT, 4D-CT and multiple-parameter MR scans were included in this study. The gross tumor volume (GTV) was independently delineated twice by two observers based on contrast-enhanced computed tomography (CECT), maximum intensity projection (MIP), LAVA-Flex, T2W FRFSE and DWI-EPI images. We also delineated the peritumoral region, which was defined as 0 to 5 mm radius surrounding the GTV. 107 radiomic features were automatically extracted from CECT images using 3D-Slicer software. Quartile coefficient of dispersion (QCD) and intraclass correlation coefficient (ICC) were applied to assess the variability of each radiomic feature. QCD<10% and ICC≥0.75 were considered small variations and excellent reliability. Finally, the principal component analysis (PCA) was used to test the feasibility of dimensionality reduction.ResultsFor tumor tissues, the numbers of radiomic features with QCD<10% indicated no obvious inter-/intra-observer differences or discrepancies in 3D-CT, 4D-CT and multiple-parameter MR delineation. However, the number of radiomic features (mean 89) with ICC≥0.75 was the highest in the multiple-parameter MR group, followed by the 3DCT group (mean 77) and the MIP group (mean 73). The peritumor tissues also showed similar results. A total of 15 and 7 radiomic features presented excellent reproducibility and small variation in tumor and peritumoral tissues, respectively. Two robust features showed excellent reproducibility and small variation in tumor and peritumoral tissues. In addition, the values of the two features both represented statistically significant differences among tumor and peritumoral tissues (P<0.05). The PCA results indicated that the first seven principal components could preserve at least 90% of the variance of the original set of features.ConclusionDelineation on multiple-parameter MR images could help to improve the reproducibility of the HCC CT radiomic features and weaken the inter-/intra-observer influence.

Project description:BackgroundThis study aimed to develop a computed tomography (CT) model to predict Ki-67 expression in hepatocellular carcinoma (HCC) and to examine the added value of radiomics to clinico-radiological features.MethodsA total of 208 patients (training set, n = 120; internal test set, n = 51; external validation set, n = 37) with pathologically confirmed HCC who underwent contrast-enhanced CT (CE-CT) within 1 month before surgery were retrospectively included from January 2014 to September 2021. Radiomics features were extracted and selected from three phases of CE-CT images, least absolute shrinkage and selection operator regression (LASSO) was used to select features, and the rad-score was calculated. CE-CT imaging and clinical features were selected using univariate and multivariate analyses, respectively. Three prediction models, including clinic-radiologic (CR) model, rad-score (R) model, and clinic-radiologic-radiomic (CRR) model, were developed and validated using logistic regression analysis. The performance of different models for predicting Ki-67 expression was evaluated using the area under the receiver operating characteristic curve (AUROC) and decision curve analysis (DCA).ResultsHCCs with high Ki-67 expression were more likely to have high serum α-fetoprotein levels (P = 0.041, odds ratio [OR] 2.54, 95% confidence interval [CI]: 1.04-6.21), non-rim arterial phase hyperenhancement (P = 0.001, OR 15.13, 95% CI 2.87-79.76), portal vein tumor thrombus (P = 0.035, OR 3.19, 95% CI: 1.08-9.37), and two-trait predictor of venous invasion (P = 0.026, OR 14.04, 95% CI: 1.39-144.32). The CR model achieved relatively good and stable performance compared with the R model (AUC, 0.805 [95% CI: 0.683-0.926] vs. 0.678 [95% CI: 0.536-0.839], P = 0.211; and 0.805 [95% CI: 0.657-0.953] vs. 0.667 [95% CI: 0.495-0.839], P = 0.135) in the internal and external validation sets. After combining the CR model with the R model, the AUC of the CRR model increased to 0.903 (95% CI: 0.849-0.956) in the training set, which was significantly higher than that of the CR model (P = 0.0148). However, no significant differences were found between the CRR and CR models in the internal and external validation sets (P = 0.264 and P = 0.084, respectively).ConclusionsPreoperative models based on clinical and CE-CT imaging features can be used to predict HCC with high Ki-67 expression accurately. However, radiomics cannot provide added value.

Dataset Information

Identification of Arterial Hyperenhancement in CT and MRI in Patients with Hepatocellular Carcinoma: Value of Unenhanced Images.

Objective

Materials and methods

Results

Conclusion

Publications

Identification of Arterial Hyperenhancement in CT and MRI in Patients with Hepatocellular Carcinoma: Value of Unenhanced Images.

Similar Datasets

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