Efficacy and Safety of Radiation Segmentectomy with 90Y Resin Microspheres for Hepatocellular Carcinoma.

Background Limited data are available on radiation segmentectomy (RS) for treatment of hepatocellular carcinoma (HCC) using yttrium 90 (90Y) resin microsphere doses determined by using a single-compartment medical internal radiation dosimetry (MIRD) model. Purpose To evaluate the efficacy and safety of RS treatment of HCC with 90Y resin microspheres using a single-compartment MIRD model and correlate posttreatment dose with outcomes. Materials and Methods This retrospective single-center study included adult patients with HCC who underwent RS with 90Y resin microspheres between July 2014 and December 2022. Posttreatment PET/CT and dosimetry were performed. Adverse events were assessed using the Common Terminology Criteria for Adverse Events, version 5.0. Per-lesion and overall response rates (ie, complete response [CR], objective response, disease control, and duration of response) were assessed at imaging using the Modified Response Evaluation Criteria in Solid Tumors, and overall survival (OS) was assessed using Kaplan-Meier analysis. Results Among 67 patients (median age, 69 years [IQR, 63-78 years]; 54 male patients) with HCC, median tumor absorbed dose was 232 Gy (IQR, 163-405 Gy). At 3 months, per-lesion and overall (per-patient) CR was achieved in 47 (70%) and 41 (61%) of 67 patients, respectively. At 6 months (n = 46), per-lesion rates of objective response and disease control were both 94%, and per-patient rates were both 78%. A total of 88% (95% CI: 79 99) and 72% (95% CI: 58, 90) of patients had a per-lesion and overall duration of response of 1 year or greater. At 1 month, a grade 3 clinical adverse event (abdominal pain) occurred in one of 67 (1.5%) patients. Median posttreatment OS was 26 months (95% CI: 20, not reached). Disease progression at 2 years was lower in the group that received 300 Gy or more than in the group that received less than 300 Gy (17% vs 61%; P = .047), with no local progression in the former group through the end of follow-up. Conclusion Among patients with HCC who underwent RS with 90Y resin microspheres, 88% and 72% achieved a per-lesion and overall duration of response of 1 year or greater, respectively, with one grade 3 adverse event. In patients whose tumors received 300 Gy or more according to posttreatment dosimetry, a disease progression benefit was noted. © RSNA, 2024 Supplemental material is available for this article.

SPONTANEOUS REGRESSION OF HEPATOCELLULAR CARCINOMA: FOCUSING IN THE ASSOCIATED RISK FACTORS.

BACKGROUND: Spontaneous regression (SR) is defined as the partial or complete disappearance of a tumor, in the absence of a specific treatment. Evidence of the SR in hepatocellular carcinoma (HCC) is rare. OBJECTIVE: The authors aimed to review all the cases of SR of HCC in two reference centers of Southern Brazil, highlighting the main characteristics. METHODS: Data of all patients with HCC were retrospectively reviewed looking for the occurrence of SR in patients from two tertiary centers in Southern Brazil, in the last five years. The diagnosis of cirrhosis was established according to clinical, laboratory and imaging data, as well as upper endoscopy or histopathological examination when necessary. The diagnosis of HCC was based on typical findings according to radiologic criteria (LIRADS) or histopathological examination. Spontaneous regression was defined as a partial or complete involution of a HCC in the absence of a specific therapy. RESULTS: From all cases of HCC in the last 5 years (n=433), there were five cases of SR. Three (60%) were men, the mean age was 62.6 (50.0-76.0) years, and the etiology was HCV in 3 (60%). Complete regression was observed in three patients (60%), one patient (20%) presented partial regression, and one (20%) relapesed and died. The time of follow-up varied between 12 and 21 months. In this presentation, it was highlighted one case of SR observed after COVID-19 infection in a patient with cirrhosis. The possible mechanisms involved in this situation were reviewed, emphasizing the most common like hypoxia and immunological. There were also one patient submitted to a surgical procedure as a possible fator involved and three patients without obvious risk factors. CONCLUSION: This phenomenon will possibly contribute to a better understanding of the pathophysiological mechanisms of HCC.

Hepatic perivascular epithelioid cell tumors: Benign, malignant, and uncertain malignant potential.

In 2013, the World Health Organization defined perivascular epithelioid cell tumor (PEComa) as "a mesenchymal tumor which shows a local association with vessel walls and usually expresses melanocyte and smooth muscle markers." This generic definition seems to better fit the PEComa family, which includes angiomyolipoma, clear cell sugar tumor of the lung, lymphangioleiomyomatosis, and a group of histologically and immunophenotypically similar tumors that include primary extrapulmonary sugar tumor and clear cell myomelanocytic tumor. Clear cell tumors with this immunophenotypic pattern have also had their malignant variants described. When localizing to the liver, preoperative radiological diagnosis has proven to be very difficult, and most patients have been diagnosed with hepatocellular carcinoma, focal nodular hyperplasia, hemangioma, or hepatic adenoma based on imaging findings. Examples of a malignant variant of the liver have been described. Finally, reports of malignant variants of these lesions have increased in recent years. Therefore, we support the use of the Folpe criteria, which in 2005 established the criteria for categorizing a PEComa as benign, malignant, or of uncertain malignant potential. Although they are not considered ideal, they currently seem to be the best approach and could be used for the categorization of liver tumors.

Preoperative MRI radiomic analysis for predicting local tumor progression in colorectal liver metastases before microwave ablation.

PURPOSE: Radiomics may aid in predicting prognosis in patients with colorectal liver metastases (CLM). Consistent data is available on CT, yet limited data is available on MRI. This study assesses the capability of MRI-derived radiomic features (RFs) to predict local tumor progression-free survival (LTPFS) in patients with CLMs treated with microwave ablation (MWA). METHODS: All CLM patients with pre-operative Gadoxetic acid-MRI treated with MWA in a single institution between September 2015 and February 2022 were evaluated. Pre-procedural information was retrieved retrospectively. Two observers manually segmented CLMs on T2 and T1-Hepatobiliary phase (T1-HBP) scans. After inter-observer variability testing, 148/182 RFs showed robustness on T1-HBP, and 141/182 on T2 (ICC > 0.7).Cox multivariate analysis was run to establish clinical (CLIN-mod), radiomic (RAD-T1, RAD-T2), and combined (COMB-T1, COMB-T2) models for LTPFS prediction. RESULTS: Seventy-six CLMs (43 patients) were assessed. Median follow-up was 14 months. LTP occurred in 19 lesions (25%).CLIN-mod was composed of minimal ablation margins (MAMs), intra-segment progression and primary tumor grade and exhibited moderately high discriminatory power in predicting LTPFS (AUC = 0.89, p = 0.0001). Both RAD-T1 and RAD-T2 were able to predict LTPFS: (RAD-T1: AUC = 0.83, p = 0.0003; RAD-T2: AUC = 0.79, p = 0.001). Combined models yielded the strongest performance (COMB-T1: AUC = 0.98, p = 0.0001; COMB-T2: AUC = 0.95, p = 0.0003). Both combined models included MAMs and tumor regression grade; COMB-T1 also featured 10th percentile of signal intensity, while tumor flatness was present in COMB-T2. CONCLUSION: MRI-based radiomic evaluation of CLMs is feasible and potentially useful for LTP prediction. Combined models outperformed clinical or radiomic models alone for LTPFS prediction.

Predicting response of hepatoblastoma primary lesions to neoadjuvant chemotherapy through contrast-enhanced computed tomography radiomics.

OBJECTIVE: To investigate the clinical value of contrast-enhanced computed tomography (CECT) radiomics for predicting the response of primary lesions to neoadjuvant chemotherapy in hepatoblastoma. METHODS: Clinical and CECT imaging data were retrospectively collected from 116 children with hepatoblastoma who received neoadjuvant chemotherapy. Tumor response was assessed according to the Response Evaluation Criteria in Solid Tumors (RECIST). Subsequently, they were randomly stratified into a training cohort and a test cohort in a 7:3 ratio. The clinical model was constructed using univariate and multivariate logistic regression, while the radiomics model was developed based on selected radiomics features employing the support vector machine algorithm. The combined clinical-radiomics model incorporated both clinical and radiomics features. RESULTS: The area under the curve (AUC) for the clinical, radiomics, and combined models was 0.704 (95% CI: 0.563-0.845), 0.830 (95% CI: 0.704-0.959), and 0.874 (95% CI: 0.768-0.981) in the training cohort, respectively. In the validation cohort, the combined model achieved the highest mean AUC of 0.830 (95% CI 0.616-0.999), with a sensitivity, specificity, accuracy, precision, and f1 score of 72.0%, 81.1%, 78.5%, 57.2%, and 63.5%, respectively. CONCLUSION: CECT radiomics has the potential to predict primary lesion response to neoadjuvant chemotherapy in hepatoblastoma.

[Videofluorescence navigation during parenchymal-sparing liver resections using a domestic fluorescence imaging system]. / Videofluorestsentnaya navigatsiya pri parenkhimosokhrannykh rezektsiyakh pecheni s ispol'zovaniem otechestvennoi sistemy fluorestsentnoi vizualizatsii.

Parenchyma- sparing liver resections are aimed at maximizing the possible preservation of parenchyma not affected by the tumor - a current trend in hepatopancreatobiliary surgery. On the other hand, a prerequisite for operations is to ensure their radicality. To effectively solve this problem, all diagnostic imaging methods available in the arsenal are used, which make it possible to comprehensively solve the issues of perioperative planning of the volume and technical features of the planned operation. Diagnostic imaging methods that allow intraoperative navigation through intraoperative, instrumentally based determination of the tumor border and resection plane have additional value. One of the methods of such mapping is ICG video fluorescence intraoperative navigation. An analysis of the clinical use of the domestic video fluorescent navigation system "MARS" for parenchymal-sparing resections of focal liver lesions is presented. An assessment was made of the dynamics of the distribution of the contrast agent during ICG videofluorescent mapping during parenchymal-sparing resection interventions on the liver, with the analysis of materials from histological examination of tissues taking into account three-zonal videofluorescent marking of the resection edge, performed using the domestic videofluorescence imaging system «MARS¼.

Combination and Optimal Sequencing of Systemic and Locoregional Therapies in Hepatocellular Carcinoma: Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel.

Hepatocellular carcinoma, historically, has had a poor prognosis with very few systemic options. Furthermore, most patients at diagnosis are not surgical candidates. Therefore, locoregional therapy (LRT) has been widely used, with strong data supporting its use. Over the last 15 years, there has been progress in the available systemic agents. This has led to the updated Barcelona Clinic Liver Cancer (BCLC) algorithm's inclusion of these new systemic agents, with advocacy of earlier usage in those who progress on LRT or have tumor characteristics that make them less likely to benefit from LRT. However, neither the adjunct of LRT nor the specific sequencing of combination therapies is addressed directly. This Research Consensus Panel sought to highlight research priorities pertaining to the combination and optimal sequencing of LRT and systemic therapy, assessing the greatest needs across BCLC stages.

Noninvasive assessment of liver fibrosis can predict clinical outcomes at late follow-up after a sustained virological response in HCV patients?

OBJECTIVES: The primary objective was to evaluate Liver-Related Events (LREs), including hepatic decompensation (ascites, hemorrhagic varices and encephalopathy) and Hepatocellular Carcinoma (HCC), as well as changes in liver stiffness during the follow-up period among patients who achieved a Sustained Virological Response (SVR) after treatment for chronic Hepatitis C Virus (HCV) infection. METHODS: A total of 218 patients with HCV were treated, and those who achieved an SVR were followed up for 3-years. Transient Elastography (TE) using FibroScan® was performed at various time points: before treatment, at the end of treatment, at 6-months post-treatment, at 1-year post-treatment, at 2-years post-treatment, and at 3-years post-treatment. RESULTS: At 6-months post-treatment, a Liver Stiffness Measurement (LSM) cutoff of > 19 KPa was identified, leading to a 14.5-fold increase in the hazard of negative outcomes, including decompensation and/or HCC. The analysis of relative changes in liver stiffness between pre-treatment and 6-months posttreatment revealed that a reduction in LSM of -10 % was associated with a -12 % decrease in the hazard of decompensation and/or HCC, with this trend continuing as the LSM reduction reached -40 %, resulting in a -41 % hazard of decompensation and/or HCC. Conversely, an increase in the relative change during this period, such as an LSM increase of +10 %, led to a + 14 % increase in the hazard of decompensation. In cases where this relative change in LSM was +50 %, the hazard of decompensation increased to +92. CONCLUSION: Transient elastography using FibroScan® can be a good tool for monitoring HCV patients with SVR after treatment to predict LREs in the long term.

Role of peritumoral tissue analysis in predicting characteristics of hepatocellular carcinoma using ultrasound-based radiomics.

Predicting the biological characteristics of hepatocellular carcinoma (HCC) is essential for personalized treatment. This study explored the role of ultrasound-based radiomics of peritumoral tissues for predicting HCC features, focusing on differentiation, cytokeratin 7 (CK7) and Ki67 expression, and p53 mutation status. A cohort of 153 patients with HCC underwent ultrasound examinations and radiomics features were extracted from peritumoral tissues. Subgroups were formed based on HCC characteristics. Predictive modeling was carried out using the XGBOOST algorithm in the differentiation subgroup, logistic regression in the CK7 and Ki67 expression subgroups, and support vector machine learning in the p53 mutation status subgroups. The predictive models demonstrated robust performance, with areas under the curves of 0.815 (0.683-0.948) in the differentiation subgroup, 0.922 (0.785-1) in the CK7 subgroup, 0.762 (0.618-0.906) in the Ki67 subgroup, and 0.849 (0.667-1) in the p53 mutation status subgroup. Confusion matrices and waterfall plots highlighted the good performance of the models. Comprehensive evaluation was carried out using SHapley Additive exPlanations plots, which revealed notable contributions from wavelet filter features. This study highlights the potential of ultrasound-based radiomics, specifically the importance of peritumoral tissue analysis, for predicting HCC characteristics. The results warrant further validation of peritumoral tissue radiomics in larger, multicenter studies.

Liver Imaging Reporting and Data System Contrast-Enhanced US Nonradiation Treatment Response Assessment Version 2024.

The American College of Radiology Liver Imaging Reporting and Data System (LI-RADS) standardizes the imaging technique, reporting lexicon, disease categorization, and management for patients with or at risk for hepatocellular carcinoma (HCC). LI-RADS encompasses HCC surveillance with US; HCC diagnosis with CT, MRI, or contrast-enhanced US (CEUS); and treatment response assessment (TRA) with CT or MRI. LI-RADS was recently expanded to include CEUS TRA after nonradiation locoregional therapy or surgical resection. This report provides an overview of LI-RADS CEUS Nonradiation TRA v2024, including a lexicon of imaging findings, techniques, and imaging criteria for posttreatment tumor viability assessment. LI-RADS CEUS Nonradiation TRA v2024 takes into consideration differences in the CEUS appearance of viable tumor and posttreatment changes within and in close proximity to a treated lesion. Due to the high sensitivity of CEUS to vascular flow, posttreatment reactive changes commonly manifest as areas of abnormal perilesional enhancement without washout, especially in the first 3 months after treatment. To improve the accuracy of CEUS for nonradiation TRA, different diagnostic criteria are used to evaluate tumor viability within and outside of the treated lesion margin. Broader criteria for intralesional enhancement increase sensitivity for tumor viability detection. Stricter criteria for perilesional enhancement limit miscategorization of posttreatment reactive changes as viable tumor. Finally, the TRA algorithm reconciles intralesional and perilesional tumor viability assessment and assigns a single LI-RADS treatment response (LR-TR) category: LR-TR nonviable, LR-TR equivocal, or LR-TR viable.

Prognostication of Hepatocellular Carcinoma Using Artificial Intelligence.

Hepatocellular carcinoma (HCC) is a biologically heterogeneous tumor characterized by varying degrees of aggressiveness. The current treatment strategy for HCC is predominantly determined by the overall tumor burden, and does not address the diverse prognoses of patients with HCC owing to its heterogeneity. Therefore, the prognostication of HCC using imaging data is crucial for optimizing patient management. Although some radiologic features have been demonstrated to be indicative of the biologic behavior of HCC, traditional radiologic methods for HCC prognostication are based on visually-assessed prognostic findings, and are limited by subjectivity and inter-observer variability. Consequently, artificial intelligence has emerged as a promising method for image-based prognostication of HCC. Unlike traditional radiologic image analysis, artificial intelligence based on radiomics or deep learning utilizes numerous image-derived quantitative features, potentially offering an objective, detailed, and comprehensive analysis of the tumor phenotypes. Artificial intelligence, particularly radiomics has displayed potential in a variety of applications, including the prediction of microvascular invasion, recurrence risk after locoregional treatment, and response to systemic therapy. This review highlights the potential value of artificial intelligence in the prognostication of HCC as well as its limitations and future prospects.

The Future Role of Abdominal US in Hepatocellular Carcinoma Surveillance.

Abdominal US is currently the best-validated surveillance strategy for hepatocellular carcinoma (HCC) in at-risk patients. It is the only modality shown to have completed all five phases of validation and can achieve high sensitivity and specificity for HCC detection, especially when conducted by expert sonographers in high-volume centers. However, US also has limitations, including operator dependency and varying sensitivity in clinical practice. Further, the sensitivity of US for early-stage HCC detection is lower in patients with obesity or nonviral liver disease, increasingly common populations undergoing surveillance. Imaging-based and blood-based surveillance strategies, including abbreviated MRI and biomarker panels, may overcome some limitations of US-based surveillance. Both strategies have promising test performance in phase II and phase III biomarker studies and are undergoing prospective validation. Considering the variation in HCC risk and test performance between patients, there will likely be a shift away from a one-size-fits-all approach and toward precision screening, in which the "best" test is selected based on individual patient characteristics. In this upcoming era of precision HCC screening among patients with cirrhosis, US will likely continue to have an important, albeit reduced, surveillance role.

Hepatic Radioembolization: A Multistep Theragnostic Procedure.

This article provides a thorough overview of the practice and multistep approach of hepatic radioembolization. The current literature on hepatic radioembolization in primary or metastatic liver tumors as well as future perspectives are discussed.

A rat-based preclinical platform facilitating transcatheter hepatic arterial infusion in immunodeficient rats with liver xenografts of patient-derived pancreatic ductal adenocarcinoma.

Liver metastases from pancreatic ductal adenocarcinoma (PDAC) are highly fatal. A rat-based patient-derived tumor xenograft (PDX) model is available for transcatheter therapy. This study aimed to create an immunodeficient rat model with liver xenografts of patient-derived primary PDAC and evaluate efficacy of hepatic arterial infusion chemotherapy with cisplatin in this model. Three patient-derived PDACs were transplanted into the livers of 21 rats each (totally, 63 rats), randomly assigned into hepatic arterial infusion, systemic venous infusion, and control groups (n = 7 each) four weeks post-implantation. Computed tomography evaluated tumor volumes before and four weeks after treatment. Post-euthanasia, resected tumor specimens underwent histopathological examination. A liver-implanted PDAC PDX rat model was established in all 63 rats, with first CT identifying all tumors. Four weeks post-treatment, arterial infusion groups exhibited significantly smaller tumor volumes than controls for all three tumors on second CT. Xenograft tumors histologically maintained adenocarcinoma features compared to original patient tumors. Ki67 expression was significantly lower in arterial infusion groups than in the other two for the three tumors, indicating reduced tumor growth in PDX rats. A liver-implanted PDAC PDX rat model was established as a rat-based preclinical platform. Arterial cisplatin infusion chemotherapy represents a potential therapy for PDAC liver metastasis.

Microinvasion in hepatocellular carcinoma: predictive factor and application for definition of clinical target volume for radiotherapy.

BACKGROUND: To investigate the correlation between microinvasion and various features of hepatocellular carcinoma (HCC), and to clarify the microinvasion distance from visible HCC lesions to subclinical lesions, so as to provide clinical basis for the expandable boundary of clinical target volume (CTV) from gross tumor volume (GTV) in the radiotherapy of HCC. METHODS: HCC patients underwent hepatectomy of liver cancer in our hospital between July 2019 and November 2021 were enrolled. Data on various features and tumor microinvasion distance were collected. The distribution characteristics of microinvasion distance were analyzed to investigate its potential correlation with various features. Tumor size compared between radiographic and pathologic samples was analyzed to clarify the application of pathologic microinvasion to identify subclinical lesions of radiographic imaging. RESULTS: The average microinvasion distance was 0.6 mm, with 95% patients exhibiting microinvasion distance less than 3.0 mm, and the maximum microinvasion distance was 4.0 mm. A significant correlation was found between microinvasion and liver cirrhosis (P = 0.036), serum albumin level (P = 0.049). Multivariate logistic regression analysis revealed that HCC patients with cirrhosis had a significantly lower risk of microinvasion (OR = 0.09, 95%CI = 0.02 ~ 0.50, P = 0.006). Tumor size was overestimated by 1.6 mm (95%CI=-12.8 ~ 16.0 mm) on radiographic size compared to pathologic size, with a mean %Δsize of 2.96% (95%CI=-0.57%~6.50%). The %Δsize ranged from - 29.03% to 34.78%. CONCLUSIONS: CTV expanding by 5.4 mm from radiographic GTV could include all pathologic microinvasive lesions in the radiotherapy of HCC. Liver cirrhosis was correlated with microinvasion and were independent predictive factor of microinvasion in HCC.

Screening for exclusion of high-risk bleeding features of esophageal varices in cirrhosis through CT and MRI.

BACKGROUND & AIM: Esophageal varices (EV) screening guidelines have evolved with improved risk stratification to avoid unnecessary esophagogastroduodenoscopy (EGD) in individuals with low bleeding risks. However, uncertainties persist in the recommendations for certain patient groups, particularly those with hepatocellular carcinoma (HCC) and/or receiving non-selective beta-blockers (NSBB) without prior endoscopy. This study assessed the efficacy of imaging in ruling out EVs and their high-risk features associated with bleeding in patients with cirrhosis and with HCC. We also evaluated the impact of NSBB on the detection of these characteristics. METHODS: A total of 119 patients undergoing EGD with CT and/or MRI within 90 days of the procedure were included. 87 patients had HCC. A new imaging grading system was developed utilizing the size of EVs and the extent of their protrusion into the esophagus lumen. The negative predictive value (NPV) of EVimaging(-) versus EVimaging (+) (grades 1-3) in ruling out the presence of EV and/or high-risk features by EGD was calculated. The predictive performance of imaging was determined by logistic regression. RESULTS: The NPV of imaging for detecting EV and high-risk features was 81 % and 92 %, respectively. Among HCC patients, the NPV for EV and high-risk features was 80 % and 64 %, respectively. Being on NSBB didn't statistically impact the imaging detection of EV. Imaging was a better predictor of high-risk EGD findings than Child-Turcotte-Pugh scores. CONCLUSIONS: Our results suggest that imaging can effectively rule out the presence of EV and high-risk features during EGD, even in patients with HCC and/or receiving NSBB.

Early detection of HCC in patients with cirrhosis using AI; a Systematic Review.

Introduction: Hepatocellular carcinoma constitutes for approximately 75% of primary cancers of liver. Around 80- 90% of patients with HCC have cirrhosis at the time of diagnosis. Use of AI has recently gained significance in the field of hepatology, especially for the detection of HCC, owing to its increasing incidence and specific radiological features which have been established for its diagnostic criteria. Objectives: A systematic review was performed to evaluate the current literature for early diagnosis of hepatocellular carcinoma in cirrhotic patients. METHODS: Systematic review was conducted using PRISMA guidelines and the relevant studies were narrated in detail with assessment of quality for each paper. RESULTS: This systematic review displays the significance of AI in early detection and prognosis of HCC with the pressing need for further exploration in this field. CONCLUSIONS: AI can have a significant role in early diagnosis of HCC in cirrhotic patients.

Quick and easy assessment of sarcopenia in cirrhosis: Can ultrasound be the solution?

Cirrhosis is frequently associated with sarcopenia, with reported rates of over 80% in patients with decompensated alcohol-related liver disease. Sarcopenia negatively impacts the prognosis of cirrhotic patients and affects the response to treatment of patients with hepatocellular carcinoma (HCC). For these reasons, identifying an easy-to-perform method to assess sarcopenia in is a key element in the optimization of care in this patient population. Assessment of muscle mass by computed tomography is considered the standard of care for the diagnosis of sarcopenia, but exposure to radiation and high costs limit its application in this setting, especially for repeated assessments. We believe that ultrasound, a cheap and harmless technique also used for HCC screening in cirrhotic patients, could have an expanding role in the diagnosis and follow-up of sarcopenia in these patients.