MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1007/s10439-026-04345-w

Медицинская библиотека · Annals of biomedical engineering · 2026

Characterization of Collagen Fiber Organization in Breast Cancer via Model-Free Multiscale pSHG Image Analysis.

Lombardo Giuseppe, Mercatelli Raffaella, Bernava Giuseppe Massimo, Cicchi Riccardo

СтатьяПеревод пока не подготовлен

Аннотация

PURPOSE: Alterations in collagen micro-architecture are hallmarks of tumor progression. Conventional polarization second-harmonic generation (pSHG) analyses rely on rigid symmetry assumptions that often fail in heterogeneous tissue microenvironments. We present a fully automated model-free, multiscale, computational framework designed for the unbiased quantification of complex collagen organization in breast cancer tissue.

METHODS

Breast tumor and adjacent perilesional tissues were imaged using a custom pSHG microscope and analyzed at micro- and meso-scale levels. Collagen centerlines were extracted via U-Net-based segmentation to estimate fiber orientations, while global alignment was quantified using 2D-FFT angular spectra. Structural organization was characterized with model-free descriptors, including scalar and biaxial order parameters and semi-variogram-based spatial autocorrelation.

RESULTS

Across a limited proof-of-concept dataset ( n = 14 FoVs), the proposed multiscale framework effectively discriminated tumor from adjacent perilesional collagen architecture. The trigonal polarization model yielded smoother, more robust orientation maps than the cylindrical approach, showing strong agreement with deep learning fiber centerline analysis ( C C C = 0.985 ). Tumor regions exhibited significantly longer spatial coherence length (87.3 ± 22.1 µm vs. 44.2 ± 11.3 µm, P = 0.01), higher scalar order (0.81 ± 0.06 vs. 0.56 ± 0.05, P = 0.01), and elevated biaxial order (0.12 ± 0.02 vs. 0.06 ± 0.06, P < 0.05).

CONCLUSIONS

This seminal framework provides a robust and assumption-free methodology to extract quantitative collagen descriptors across spatial scales. By integrating deep learning, frequency-domain analysis, and spatial statistics, it captures both local and long-range organizational features, supporting collagen architecture as a potential quantitative multiscale biomarker of tumor-associated extracellular matrix remodeling.

Для цитирования: Lombardo Giuseppe, Mercatelli Raffaella, Bernava Giuseppe Massimo, Cicchi Riccardo. Characterization of Collagen Fiber Organization in Breast Cancer via Model-Free Multiscale pSHG Image Analysis.. Annals of biomedical engineering. 2026. DOI: 10.1007/s10439-026-04345-w.
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.