Multiple randomized studies have shown that combination of chemotherapy and immune checkpoint inhibitors (ICIs) leads to better response rates and survival as compared to chemotherapy alone in the advanced stage of NSCLC. Data suggesting a benefit to using ICIs in the neoadjuvant therapy of patients with early stage NSCLC are emerging. Eligible subjects were treatment naïve patients with stage IB, II, and resectable IIIA NSCLC. Patients received three cycles of neoadjuvant chemotherapy with four doses of avelumab every 2 weeks. Patients with squamous cell cancer received cisplatin or carboplatin on day 1 and gemcitabine on days 1 and 8 of each cycle of chemotherapy. Patients with nonsquamous histology received cisplatin or carboplatin with pemetrexed on day 1 of each cycle. Patients then proceeded to their planned surgery. Out of 15 patients accrued as part of stage 1 of the study, four had a radiologic response (1 complete response), lower than the minimum of six responses needed to continue to phase 2 of the study. The study was therefore terminated. Majority had adenocarcinoma histology and stage IIIA disease. The treatment was well tolerated with no unexpected side effects. Four patients (26.7%) had grade III/IV CTCAE toxicity. This study confirms that the preoperative administration of chemotherapy and avelumab is safe. There was no indication of increased surgical complications. The benefit of adding immunotherapy to chemotherapy did not appear to enhance the overall response rate of patients in the neoadjuvant setting in patients with resectable NSCLC because this study failed to meet its primary endpoint.

Chest radiographs (CXR) are the most performed imaging tests and rank high among the radiographic exams with suboptimal quality and high rejection rates. Suboptimal CXRs can cause delays in patient care and pitfalls in radiographic interpretation, given their ubiquitous use in the diagnosis and management of acute and chronic ailments. Suboptimal CXRs can also compound and lead to high inter-radiologist variations in CXR interpretation. While advances in radiography with transitions to computerized and digital radiography have reduced the prevalence of suboptimal exams, the problem persists. Advances in machine learning and artificial intelligence (AI), particularly in the radiographic acquisition, triage, and interpretation of CXRs, could offer a plausible solution for suboptimal CXRs. We review the literature on suboptimal CXRs and the potential use of AI to help reduce the prevalence of suboptimal CXRs.