Quantitative Multiphoton Elastin-Collagen Imaging Differentiates Histologically Ambiguous Lung Adenocarcinoma Subtypes

Accurate differentiation of lung adenocarcinoma subtypes is critical for personalized surgical strategies, particularly in intraoperative differentiation between adenocarcinoma in situ (AIS) and invasive adenocarcinoma (IA). However, tissue distortions such as alveolar rupture or collapse induced during surgery frequently lead to subtype misclassification. Conventional histological staining limited by their inability to quantitatively characterize collagen and elastin fibers, fail to address this clinical challenge. To overcome these limitations, we developed a quantitative Multiphoton Elastin-Collagen Imaging (qMECI) method, specifically targeting diagnostic ambiguities between AIS and IA. qMECI employs label-free multiphoton microscopy to simultaneously capture microarchitectural features of collagen and elastin fibers, extracting ten quantitative metrics encompassing fiber distribution patterns, spatial arrangement, and morphological parameters. Experimental results demonstrate that qMECI identifies critical discriminative signatures of extracellular matrix remodeling, including collagen-elastin coverage, hyperplastic reorganization, and vascular-aligned growth patterns. By integrating quantitative biomarkers such as relative fiber distribution and area ratios, qMECI enables objective differentiation of two diagnostically challenging scenarios: alveolar collapse-type AIS versus acinar-pattern IA and alveolar rupture-type AIS versus papillary IA. This method holds significant potential to refine intraoperative diagnosis workflows, thereby reducing misdiagnosis risks and overtreatment.