Threshold for Enhancement in Treated Hepatocellular Carcinoma on MDCT: Effect on Necrosis Quantification

Identification of CT Values That Could Be Predictive of Necrosis (N-CTav) in Hepatocellular Carcinoma after Lenvatinib Treatment

Purpose: To assess the utility of measurement of the computed tomography (CT) attenuation value (CTav) in predicting tumor necrosis in hepatocellular carcinoma (HCC) patients who achieve a complete response (CR), defined using modified Response Evaluation Criteria in Solid Tumors (mRECIST), after lenvatinib treatment. Method: We compared CTav in arterial phase CT images with postoperative histopathology in four patients who underwent HCC resection after lenvatinib treatment, to determine CTav thresholds indicative of histological necrosis (N-CTav). Next, we confirmed the accuracy of the determined N-CTav in 15 cases with histopathologically proven necrosis in surgical specimens. Furthermore, the percentage of the tumor with N-CTav, i.e., the N-CTav occupancy rate, assessed using Image J software in 30 tumors in 12 patients with CR out of 571 HCC patients treated with lenvatinib, and its correlation with local recurrence following CR were examined. Results: Receiver operating characteristic (ROC) curve analysis revealed an optimal cut-off value of CTav of 30.2 HU, with 90.0% specificity and 65.0% sensitivity in discriminating between pathologically identified necrosis and degeneration, with a CTav of less than 30.2 HU indicating necrosis after lenvatinib treatment (N30-CTav). Furthermore, the optimal cut-off value of 30.6% for the N30-CTav occupancy rate by ROC analysis was a significant indicator of local recurrence following CR with 76.9% specificity and sensitivity (area under the ROC curve; 0.939), with the CR group with high N30-CTav occupancy (≥30.6%) after lenvatinib treatment showing significantly lower local recurrence (8.3% at 1 year) compared with the low (<30.6%) N30-CTav group (p < 0.001, 61.5% at 1 year). Conclusion: The cut-off value of 30.2 HU for CTav (N30-CTav) might be appropriate for identifying post-lenvatinib necrosis in HCC, and an N30-CTav occupancy rate of >30.6% might be a predictor of maintenance of CR. Use of these indicators have the potential to impact systemic chemotherapy for HCC.

Evolution of Radioembolization in Treatment of Hepatocellular Carcinoma: A Pictorial Review

Transarterial radioembolization (TARE) with yttrium 90 has increasingly been performed to treat hepatocellular carcinoma (HCC). TARE was historically used as a palliative lobar therapy for patients with advanced HCC beyond surgical options, ablation, or transarterial chemoembolization, but recent advancements have led to its application across the Barcelona Clinic Liver Cancer staging paradigm. Newer techniques, termed radiation lobectomy and radiation segmentectomy, are being performed before liver resection to facilitate hypertrophy of the future liver remnant, before liver transplant to bridge or downstage to transplant, or as a definite curative treatment. Imaging assessment of therapeutic response to TARE is challenging as the intent of TARE is to deliver local high-dose radiation to tumors through microembolic microspheres, preserving blood flow to promote radiation injury to the tumor. Because of the microembolic nature, early imaging assessment after TARE cannot rely solely on changes in size. Knowledge of the evolving methods of TARE along with the tools to assess posttreatment imaging and response is essential to optimize TARE as a therapeutic option for patients with HCC. ^©RSNA, 2021.

Clinical value of artificial intelligence in hepatocellular carcinoma: Current status and prospect

Hepatocellular carcinoma (HCC) is the most commonly diagnosed type of liver cancer and the fourth leading cause of cancer-related mortality worldwide. The early identification of HCC and effective treatments for it have been challenging. Due to the sufficient compensatory ability of early patients and its nonspecific symptoms, HCC is more likely to escape diagnosis in the incipient stage, during which patients can achieve a more satisfying overall survival if they undergo resection or liver transplantation. Patients at advanced stages can profit from radical therapies in a limited way. In order to improve the unfavorable prognosis of HCC, diagnostic ability and treatment efficiency must be improved. The past decade has seen rapid advancements in artificial intelligence, underlying its unique usefulness in almost every field, including that of medicine. Herein, we sought and reviewed studies that put emphasis on artificial intelligence and HCC.

Influence of feature calculating parameters on the reproducibility of CT radiomic features: a thoracic phantom study

Background

Existing studies have demonstrated that imaging parameters may affect radiomic features. However, the influence of feature calculating parameters has been overlooked. The purpose of this study is to investigate the influence of feature calculating parameters (gray-level range and bin size) on the reproducibility of CT radiomic features.

Methods

Thirty-six CT scans from an anthropomorphic thoracic phantom were acquired with different imaging parameters including effective dose, pitch, slice thicknesses and reconstruction kernels. The influence of feature calculating parameters was investigated in terms of three gray-level ranges and eleven gray-level bin sizes. Feature reproducibility was assessed by the intraclass correlation coefficient (ICC) with the cutoff value of 0.8 and the coefficient of variation (CV) with the cutoff value of 20%. The agreements of reproducible features in different ranges and bin sizes were analyzed by Kendall's W test and Kappa test. The proportions of reproducible features, in terms of two calculating, four imaging and two segmentation parameters, were evaluated using Cochran's Q test and Dunn's test.

Results

For the three gray-level ranges, 50% (44/88) of features were reproducible with a perfect agreement (Kendall's W coefficient 0.844, P<0.001). Of the 72 features that may be influenced by gray-level bin size, 33.3% (24/72) were reproducible for 11 bin sizes with a perfect agreement (Kendall's W coefficient 0.879, P<0.001). For the proportions of reproducible features, there was no statistically significant difference among three ranges (P=0.420), but there was among eleven bin sizes (P=0.013). The proportions of reproducible features in feature calculating parameters were statistically significantly lower than those in imaging parameters (adjusted P<0.05).

Conclusions

Feature calculating parameters may have a greater influence than imaging parameters on the reproducibility of CT radiomic features, which should be given special attention in clinical applications.

Evaluation of Early Response to Treatment of Hepatocellular Carcinoma with Yttrium-90 Radioembolization Using Quantitative Computed Tomography Analysis

Objective

To identify an imaging predictor for the assessment of early treatment response to yttrium-90 transarterial radioembolization (TARE) in patients with hepatocellular carcinoma (HCC), using a quantitative assessment of dynamic computed tomography (CT) images.

Materials and Methods

Dynamic contrast-enhanced CT was obtained pre- and 4 weeks post-TARE in 44 patients (34 men, 10 women; mean age, 60 years) with HCC. Computer software was developed for measuring the percentage increase in the combined delayed-enhancing area and necrotic area (pD + N) and the percentage increase in the necrotic area (pNI) in the tumor-containing segments pre- and post-TARE. Local progression-free survival (PFS) was compared between patient groups using Cox regression and Kaplan-Meier analyses.

Results

Post-TARE HCC with pD + N ≥ 35.5% showed significantly longer PFS than those with pD + N < 35.5% (p = 0.001). The local tumor progression hazard ratio was 17.3 (p = 0.009) for pD + N < 35.5% versus pD + N ≥ 35.5% groups. HCCs with a high pNI tended to have longer PFS, although this difference did not reach statistical significance.

Conclusion

HCCs with a larger pD + N are less likely to develop local progression after TARE.

Assessment of the response of hepatocellular carcinoma to interventional radiology treatments

According to Barcelona Clinic Liver Cancer (BCLC) guidelines, interventional radiology procedures are valuable treatment options for many hepatocellular carcinomas (HCCs) that are not amenable to resection or transplantation. Accurate assessment of the efficacy of therapies at earlier stages enables completion of treatment, optimal follow-up and to prevent potentially unnecessary treatments, side effects and costly failure. The goal of this review is to summarize and describe the radiological strategies that have been proposed to predict survival and to stratify HCC responses after interventional radiology therapies. New techniques currently in development are also described.

2017 Version of LI-RADS for CT and MR Imaging: An Update

The Liver Imaging Reporting and Data System (LI-RADS) is a reporting system created for the standardized interpretation of liver imaging findings in patients who are at risk for hepatocellular carcinoma (HCC). This system was developed with the cooperative and ongoing efforts of an American College of Radiology-supported committee of diagnostic radiologists with expertise in liver imaging and valuable input from hepatobiliary surgeons, hepatologists, hepatopathologists, and interventional radiologists. In this article, the 2017 version of LI-RADS for computed tomography and magnetic resonance imaging is reviewed. Specific topics include the appropriate population for application of LI-RADS; technical recommendations for image optimization, including definitions of dynamic enhancement phases; diagnostic and treatment response categories; definitions of major and ancillary imaging features; criteria for distinguishing definite HCC from a malignancy that might be non-HCC; management options following LI-RADS categorization; and reporting. ^©RSNA, 2017.