ArticleBiophotonics discovery2025
Exploring racial differences in second-harmonic-generation-based prognostic indicators of metastasis in breast and colon cancer.
Article in Biophotonics discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Whole-slide mapping of tumor tissue fiber architecture via computational scattered light imaging.Biomedical optics express · 2026Article
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Authors and funding
10 authors.
Funding
Abstract
Significance: Second-harmonic generation (SHG) analysis of collagen internal structure and overall organization in the tumor microenvironment may enhance current metastasis prediction methods, which do not prognosticate with the same accuracy for patients of different races. For these optical tools to be clinically available, a multicenter trial is needed. We investigate if SHG-based prognostic signals vary with patient race, providing insight for designing such a trial. Aim: SHG imaging was performed on colon adenocarcinoma (CRC) and invasive ductal carcinoma (IDC) patient samples to derive two prognostic indicators. We assessed the association between these indicators and patient race. Approach: SHG images were analyzed as previously described to determine the forward- to backward-SHG scattering ratio (F/B) and fiber angle variability (FAV). Both prognostic measurements were compared between Black and White patients. Results: In the IDC cohort, F/B from the tumor-stroma interface differed significantly between demographic groups. For the CRC cohort, a trend was observed in the tumor-stroma interface and tumor bulk. FAV did not vary by race in either cohort. Conclusions: F/B variation with patient race suggests the relationship between F/B and metastatic outcome may vary with patient race. These findings highlight the potential need for race-specific prognostic algorithms to improve metastasis prediction for all patients.
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