Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and third leading cause of cancer-related mortality worldwide. While surgical resection and transplantation are the standard first-line treatments for early-stage HCC, most patients do not fulfill criteria for surgery. Fortunately, catheter-directed and percutaneous locoregional approaches have evolved as major treatment modalities for unresectable HCC. Improved outcomes have been achieved with novel techniques which can be employed for diverse applications ranging from curative-intent for small localized tumors, to downstaging or bridging to resection and transplantation for early and intermediate disease, and locoregional control and palliation for advanced disease. This review explores recent advances in liver-directed techniques for HCC including bland transarterial embolization, chemoembolization, radioembolization, and ablative therapies, with a focus on patient selection, procedural technique, periprocedural management, and outcomes.

Artificial intelligence (AI) uses computer algorithms to process and interpret data as well as perform tasks, while continuously redefining itself. Machine learning, a subset of AI, is based on reverse training in which evaluation and extraction of data occur from exposure to labeled examples. AI is capable of using neural networks to extract more complex, high-level data, even from unlabeled data sets, and better emulate, or even exceed, the human brain. Advances in AI have and will continue to revolutionize medicine, especially the field of radiology. Compared to the field of interventional radiology, AI innovations in the field of diagnostic radiology are more widely understood and used, although still with significant potential and growth on the horizon. Additionally, AI is closely related and often incorporated into the technology and programming of augmented reality, virtual reality, and radiogenomic innovations which have the potential to enhance the efficiency and accuracy of radiological diagnoses and treatment planning. There are many barriers that limit the applications of artificial intelligence applications into the clinical practice and dynamic procedures of interventional radiology. Despite these barriers to implementation, artificial intelligence in IR continues to advance and the continued development of machine learning and deep learning places interventional radiology in a unique position for exponential growth. This review describes the current and possible future applications of artificial intelligence, radiogenomics, and augmented and virtual reality in interventional radiology while also describing the challenges and limitations that must be addressed before these applications can be fully implemented into common clinical practice.

Hepatocellular carcinoma locoregional therapies: Outcomes and future horizons

Intrahepatic cholangiocarcinoma (ICC) has a poor prognosis, and surgical resection (SR) offers the only potential for cure. Unfortunately, only a small proportion of patients are eligible for resection due to locally advanced or metastatic disease. Locoregional therapies (LRT) are often used in unresectable liver-only or liver-dominant ICC. This review explores the role of these therapies in the treatment of ICC, including radiofrequency ablation (RFA), microwave ablation (MWA), transarterial chemoembolization (TACE), transarterial radioembolization (TARE), external beam radiotherapy (EBRT), stereotactic body radiotherapy (SBRT), hepatic arterial infusion (HAI) of chemotherapy, irreversible electroporation (IE), and brachytherapy. A search of the current literature was performed to examine types of LRT currently used in the treatment of ICC. We examined patient selection, technique, and outcomes of each type. Overall, LRTs are well-tolerated in the treatment of ICC and are effective in improving overall survival (OS) in this patient population. Further studies are needed to reduce bias from heterogenous patient populations and small sample sizes, as well as to determine whether certain LRTs are superior to others and to examine optimal treatment selection.

Interventional radiology (IR) is a unique specialty that incorporates a diverse set of skills ranging from imaging, procedures, consultation, and patient management. Understanding how IR generates value to the healthcare system is important to review from various perspectives. IR specialists need to understand how to meet demands from various stakeholders to expand their practice improving patient care. Thus, this review discusses the domains of value contributed to medical systems and outlines the parameters of success. IR benefits five distinct parties: patients, practitioners, payers, employers, and innovators. Value to patients and providers is delivered through a wide set of diagnostic and therapeutic interventions. Payers and hospital systems financially benefit from the reduced cost in medical management secondary to fast patient recovery, outpatient procedures, fewer complications, and the prestige of offering diverse expertise for complex patients. Lastly, IR is a field of rapid innovation implementing new procedural technology and techniques. Overall, IR must actively advocate for further growth and influence in the medical field as their value continues to expand in multiple domains. Despite being a nascent specialty, IR has become indispensable to modern medical practice.

Metastatic disease to the liver: Locoregional therapy strategies and outcomes