Non-invasive assessment of response to transcatheter arterial chemoembolization for hepatocellular carcinoma with the deep neural networks-based radiomics nomogram.

BACKGROUND: Transcatheter arterial chemoembolization (TACE) is a mainstay treatment for intermediate and advanced hepatocellular carcinoma (HCC), with the potential to enhance patient survival. Preoperative prediction of postoperative response to TACE in patients with HCC is crucial. PURPOSE: To develop a deep neural network (DNN)-based nomogram for the non-invasive and precise prediction of TACE response in patients with HCC. MATERIAL AND METHODS: We retrospectively collected clinical and imaging data from 110 patients with HCC who underwent TACE surgery. Radiomics features were extracted from specific imaging methods. We employed conventional machine-learning algorithms and a DNN-based model to construct predictive probabilities (RScore). Logistic regression helped identify independent clinical risk factors, which were integrated with RScore to create a nomogram. We evaluated diagnostic performance using various metrics. RESULTS: Among the radiomics models, the DNN_LASSO-based one demonstrated the highest predictive accuracy (area under the curve [AUC] = 0.847, sensitivity = 0.892, specificity = 0.791). Peritumoral enhancement and alkaline phosphatase were identified as independent risk factors. Combining RScore with these clinical factors, a DNN-based nomogram exhibited superior predictive performance (AUC = 0.871, sensitivity = 0.844, specificity = 0.873). CONCLUSION: In this study, we successfully developed a deep learning-based nomogram that can noninvasively and accurately predict TACE response in patients with HCC, offering significant potential for improving the clinical management of HCC.

Radiological assessment of immunotherapy effects and immune checkpoint-related pneumonitis for lung cancer.

Immune checkpoint inhibitors (ICIs) therapy have revolutionized advanced lung cancer care. Interestingly, the host responses for patients received ICIs therapy are distinguishing from those with cytotoxic drugs, showing potential initial transient worsening of disease burden, pseudoprogression and delayed time to treatment response. Thus, a new imaging criterion to evaluate the response for immunotherapy should be developed. ICIs treatment is associated with unique adverse events, including potential life-threatening immune checkpoint inhibitor-related pneumonitis (ICI-pneumonitis) if treated patients are not managed promptly. Currently, the diagnosis and clinical management of ICI-pneumonitis remain challenging. As the clinical manifestation is often nonspecific, computed tomography (CT) scan and X-ray films play important roles in diagnosis and triage. This article reviews the complications of immunotherapy in lung cancer and illustrates various radiologic patterns of ICI-pneumonitis. Additionally, it is tried to differentiate ICI-pneumonitis from other pulmonary pathologies common to lung cancer such as radiation pneumonitis, bacterial pneumonia and coronavirus disease of 2019 (COVID-19) infection in recent months. Maybe it is challenging to distinguish radiologically but clinical presentation may help.