A growing body of evidence shows improved overall survival and progression-free survival after thermal ablation in non-small cell lung carcinoma (NSCLC) patients with a limited number of metastases, combined with chemotherapy or tyrosine kinase inhibitors or after local recurrence. Radiofrequency ablation and microwave ablation are the most evaluated modalities, and target tumor size <3 cm (and preferably <2 cm) is a key factor of technical success and efficacy. Although thermal ablation offers some advantages over surgery and radiotherapy in terms of repeatability, safety, and quality of life, optimal management of these patients requires a multidisciplinary approach, and further randomized controlled trials are required to help refine patient selection criteria. In this article, we present a comprehensive review of available thermal ablation modalities and recent results supporting their use in oligometastatic and oligoprogressive NSCLC disease along with their potential future implications in the emerging field of immunotherapy.

Adoptive cell therapy with chimeric antigen receptors (CAR) T cells has proven effective for hematologic malignancies, but success in solid tumors has been impeded by poor intratumoral infiltration, exhaustion of effector cells from antigen burden, and an immunosuppressive tumor microenvironment. Results from recent clinical trials and preclinical studies lend promising evidence of locoregional approaches for CAR T cell delivery, priming the tumor microenvironment, and performing adjuvant therapies that sustain T cell activity. Interventional oncology is a subspeciality of interventional radiology where imaging guidance is used to perform percutaneous and catheter-directed procedures for localized, non-surgical therapy or interrogation of solid tumors. Interventional oncology provides unique synergies with immunotherapy, which has been well-studied to improve treatment efficacy while reducing toxicities associated with systemic treatment. Besides aiding in CAR T cell delivery, priming, or the stimulation of the tumor microenvironment to promote effector survival and function, interventional oncology can also aid in the monitoring of treatment response through selective, multiplex tumor sampling and catheter-based venous sampling. This review presents an overview of interventional oncology, its various procedures, and its potential for advancing CAR T cell immunotherapy of solid tumors.

Assessment of computed tomography (CT)/magnetic resonance imaging Liver Imaging Reporting and Data System (LI-RADS) v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. We assessed the performance and added-value of a machine learning (ML)-based algorithm in assessing CT LI-RADS major features and categorisation of liver observations compared with qualitative assessment performed by a panel of radiologists. High-risk patients as per LI-RADS v2018 with pathologically proven liver lesions who underwent multiphase contrast-enhanced CT at diagnosis between January 2015 and March 2019 in seven centres in five countries were retrospectively included and randomly divided into a training set (n = 84 lesions) and a test set (n = 345 lesions). An ML algorithm was trained to classify non-rim arterial phase hyperenhancement, washout, and enhancing capsule as present, absent, or of uncertain presence. LI-RADS major features and categories were compared with qualitative assessment of two independent readers. The performance of a sequential use of the ML algorithm and independent readers were also evaluated in a triage and an add-on scenario in LR-3/4 lesions. The combined evaluation of three other senior readers was used as reference standard. A total of 318 patients bearing 429 lesions were included. Sensitivity and specificity for LR-5 in the test set were 0.67 (95% CI, 0.62–0.72) and 0.91 (95% CI, 0.87–0.96) respectively, with 242 (70.1%) lesions accurately categorised. Using the ML algorithm in a triage scenario improved the overall performance for LR-5. (0.86 and 0.93 sensitivity, 0.82 and 0.76 specificity, 78% and 82.3% accuracy for the two independent readers). Quantitative assessment of CT LI-RADS v2018 major features is feasible and diagnoses LR-5 observations with high performance especially in combination with the radiologist’s visual analysis in patients at high-risk for HCC. Assessment of CT/MRI LI-RADS v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. Rather than replacing radiologists, our results highlight the potential benefit from the radiologist–artificial intelligence interaction in improving focal liver lesions characterisation by using the developed algorithm as a triage tool to the radiologist’s visual analysis. Such an AI-enriched diagnostic pathway may help standardise and improve the quality of analysis of liver lesions in patients at high risk for HCC, especially in non-expert centres in liver imaging. It may also impact the clinical decision-making and guide the clinician in identifying the lesions to be biopsied, for instance in patients with multiple liver focal lesions.