Intraoperative multi-layer perceptron-based artificial intelligence-assisted pure-vision and hyperspectral imaging reclassifies sleeve-resection candidates as eligible for lobectomy after neoadjuvant chemoimmunotherapy: A multicenter retrospective cohort and prospective exploratory study

Background Centrally located non-small cell lung cancer (NSCLC) traditionally requires sleeve resection or pneumonectomy. We investigated whether neoadjuvant chemoimmunotherapy (NeoCIT) could enable conversion to standard lobectomy and evaluated an artificial intelligence (AI)-assisted pure-vision and hyperspectral imaging (HSI) system for intraoperative margin assessment. Methods This multicenter cohort study enrolled patients from six tertiary referral centers in China between January 2019 and December 2025. The retrospective cohort ( n =56, January 2019–December 2024) and prospective exploratory cohort ( n =28, January–December 2025) included adults with histologically confirmed centrally located NSCLC initially indicated for sleeve resection who received neoadjuvant chemoimmunotherapy followed by surgical resection. Primary endpoints were event-free survival (EFS) and overall survival (OS), analyzed by Kaplan-Meier methods and multivariable Cox regression. The prospective cohort additionally underwent intraoperative bronchial margin assessment using an AI-assisted system combining hyperspectral imaging (HSI, 600–950 nm, 16 spectral bands) with a multi-layer perceptron (MLP)-based deep learning classifier for real-time pixel-wise tissue classification. Results In the retrospective cohort, 57.1% of patients achieved major pathologic response (MPR) or pathologic complete response (pCR), and 71.4% of them transitioned from sleeve lobectomy to lobectomy. The postoperative complication rate was significantly lower in the lobectomy group (10.0%) compared to the sleeve lobectomy group (38.5%, P =0.031). Two-year EFS was 69.9% for lobectomy versus 80.2% for sleeve resection (HR=0.76, P =0.665), with similar OS (84.0% vs 90.9%, HR=0.68, P =0.713). Multivariable analysis identified pCR/MPR, age, Eastern Cooperative Oncology Group (ECOG) status, and pathological nodal stage after neoadjuvant therapy (ypN) stage as independent prognostic factors. For the prospective cohort, the AI-assisted pure-vision and HSI system accurately assessed negative margins in real-time, showing high sensitivity (100%) and specificity (96.2%) compared to frozen-section pathology. Conclusion NeoCIT safely enables surgical conversion from sleeve resection to lobectomy in centrally located NSCLC without compromising oncologic outcomes, and AI-assisted hyperspectral imaging provides accurate real-time intraoperative bronchial margin assessment.