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The changes in stromal collagen play a crucial role during the pathogenesisand progression of pancreatic intraepithelial neoplasm (PanIN) to pancreaticductal adenocarcinoma (PDAC) while misdiagnosis of PanIN is common because ofthe resemblance to chronic pancreatitis (CP) in its symptoms and subsequentevaluations similarities. To visualize fibrillar collagen in tissues, secondharmonic generation microscopy is now utilized as a gold standard in variousstromal-based research analyses. However, a technical approach that can performa quantitative analysis of fibrillar collagen directly on standard slidesstained with H&E can (i) discard the need for specialized and costly equipmentor labels, (ii) further supplement the conventional histopathological insightsand, (iii) potentially be integrated within the framework of standardhistopathology workflow. In this study, the whole-core brightfield H&E-stainedimages of pancreatic tissues were translated computationally into the newcollagen images. Subsequently, collagen characteristics of PDAC, PanIN, CP, andnormal pancreatic tissues (control) were extracted and compared. The highestalignment (p < 0.01, R2 = 0.2594) was observed in PDAC cores in comparison tothe remaining three groups, while the lowest fiber density (p < 0.0001, R2 =0.3569) was observed in case of normal tissue cores. Moreover, the collagenarea and fiber length had shown higher area under curve (0.83 and 0.81,respectively) in discriminating neoplastic and non-neoplastic tissues based ontheir receiver operating characteristics. The study demonstrated that thecomputationally generated collagen images can provide a quantitative assessmentof collagen remodeling in pancreatic lesions. The cross-modality imagesynthesis may further lead towards better histopathological and tissuemicroenvironment insights without the need of specialized imaging equipment orlabels.

Quantitative analysis of collagen remodeling in pancreatic lesions using  computationally translated collagen images derived from brightfield  microscopy images