1298 Radiomics features to predict immune checkpoint inhibitor-related pneumonitis (CIP) in NSCLC patients treated with immunotherapy

• Published in: Journal for immunotherapy of cancer Vol. 11; no. Suppl 1; pp. A1442 - A1443
• Main Authors: Lee, Jeeyeon, Kim, Haseok, Aguilera Chuchuca, Maria Jose, Um, Taegyu, Jenkin, Madeline, Nam, Myungwoo, Chung, Liam Il-Young, Yu, Jisang, Djunadi, Trie Arni, Kim, Hyeonseon, Soliman, Moataz, Gennaro, Nicolo, Kim, Leeseul, Oh, Youjin, Yoon, Sung Mi, Shah, Zunairah, Lee, Soowon, Nam, Cecilia, Hong, Timothy, Velichko, Yury S, Chae, Young Kwang
• Format: Journal Article
• Language: English
• Published: London BMJ Publishing Group Ltd 01.11.2023; BMJ Publishing Group LTD; BMJ Publishing Group
• Subjects: Chemotherapy; Immunotherapy; Lung cancer; Radiation; Radiomics; Regular and Young Investigator Award Abstracts
• ISSN: 2051-1426
• DOI: 10.1136/jitc-2023-SITC2023.1298

BackgroundAs immunotherapy is more widely used for advanced non-small cell lung cancer (NSCLC), important challenges remain with adverse events including checkpoint inhibitor-associated pneumonitis (CIP). CIP usually requires discontinuation of immunotherapy even if the tumor responds, and effective models for predicting CIP are still limited. This study aims to investigate radiomic features using artificial intelligence (AI) algorithms to predict CIP in patients with NSCLC.MethodsData from 132 patients with stage III-IV NSCLC treated with immunotherapy were analyzed. Tumor response was evaluated based on immune-related RECIST (irRECIST) (tables 1 and 2). Patients were categorized into two groups: durable responders (including complete response [CR], partial response [PR], or stable disease [SD]) and non-responders (progressive disease [PD]). Segmentation was performed by three physicians using LIFEx software (IMIV/CEA, Orsay, France). 3D-radiomic features were collected from the tumor and peritumoral regions on contrast enhanced CT imaging. The lesion size was measured as a volume-of-Interest (VOI). Linear mixed-effects (LME) regression model was used to evaluate the association between radiomic features and the size of the VOI, with CIP and radiation-related pneumonitis status specific variables for slope and intercept. The chemotherapy containing regimen was considered as a random factor. The corresponding p-values were used to assess differences in LME regression slope and/or intercept between all groups.ResultsCIP was more common in the non-responder group [durable responder: 8/91 (8.8%) vs non-responder: 6/41 (14.6%) (p=0.049)] (table 2). Higher platelet counts at baseline (≥400K) was more prevalent in the non-responder group (p<0.001) and patients who received chemotherapy containing regimen were more likely to be durable responders (p<0.001) (table 1).Association between some CT-based radiomic features and the tumor size demonstrates statistically significant difference between radiation-related and CIP. Significant difference in the intercept (0.05, 95%CI[0.04, 0.05] p<0.001) and the slope (-0.01, 95%CI[-0.007, 0.012], p<0.001) of Neighboring Gray Tone Difference Matrix (NGTDM) coarseness computed for primary tumors was found with CIP (intercept difference -0.07, 95%CI[-0.1, -0.4], p<0.001 and slope difference 0.02, 95%CI[0.01, 0.02], p<0.001). For the peritumoral space, Intensity Histogram Maximum Histogram Gradient Grey Level, also showed significant difference in the intercept (30, 95%CI [19.7–40.3], p<0.001) and the slope (-2.96, 95%CI[-5.3, -0.6], p<0.015) and CIP associated difference in the intercept equal 42.7 (95%CI[12.76, -70.4], p<0.03) and slope difference -10.5 (95%CI[-15.3, -4.76], p<0.002).ConclusionsNon-responders among NSCLC patients treated with immunotherapy had a higher incidence of CIP, and CT-based radiomic features may assist in the prediction of CIP.Ethics ApprovalNorthwestern IRB approved: STU00207117EnterWrite to Liam Il-Young ChungAbstract 1298 Table 1Clinicopathologic characteristic of 132 patient with non-small cell lung cancer (NSCLC) who recevied immunotherapy, categorized by responder and non-responder based on the immune-related RECIST (irRECIST)Abstract 1298 Table 2Outcomes after immunotherapy Outcomes after immunotherapy of 132 patients with non-small cell lung cancer (NSCLC) who received immunotherapy, categorized by responder and non-responder based on the immune-related RECIST (irRECIST)