Evaluating the predictive power of pump-probe imaging contrast of melanin for metastatic outcome: A 71-patient study
Abstract
Significance: Most melanoma deaths arise from metastatic spread, yet current staging imperfectly identifies which primary tumors will progress. Melanin structure is altered during malignant transformation, and pump-probe microscopy (PPM) measures melanin excited-state dynamics in standard biopsy sections, offering molecular contrast that is complementary to morphology-based assessment. Aim: To determine whether PPM-derived melanin excited-state dynamics in primary cutaneous melanoma can predict metastatic outcome. Approach: We imaged unstained sections from 71 primary cutaneous melanomas and 18 melanoma metastases. Transient absorption curves were fit to a biexponential excited-state model, and the fit parameters were used as features for learning classifiers to predict metastatic outcome. Results: Melanin dynamics separated primary from metastatic tissue: both excited-state lifetimes were shorter in primaries, with common-language effect sizes up to 0.26. The same parameters did not separate primary tumors by outcome (effect sizes 0.41-0.61), and univariate logistic regression found no significant association for either the excited-state lifetimes or the ESA/GSB ratio. The best classifier reached 74% patient-level accuracy (AUC 0.73), a plateau reached by several unrelated architectures. Conclusions: PPM robustly distinguishes primary from metastatic melanoma tissue, consistent with progressive melanin disaggregation. While it is clear that pump-probe features of melanin thus correlate with tissue differences, melanin dynamics in single sections of the primary tumor, confounded by heterogeneity, do not give robust predictions of metastatic outcome.
Related
- Uncovering Hidden Structural and Mechanical Contrast via Spectral Photoacoustic Imaging
- Orthogonal Inline Microscopy: Continuous Determination of Microparticle Size, Shape, and Concentration via contrast-gated Flow Imaging
- Effects of X-ray absorption on grating-based and propagation-based phase-contrast imaging
- The MIRI/MRS Library. III. Detector-based optimal spectral extraction and high-contrast imaging applications
- Multi-Angle Beam Scanning Transmission Electron Microscopy for Diffraction-Contrast-Free Magnetic Imaging
BibTeX
@misc{grass2026evaluating,
title = {{Evaluating the predictive power of pump-probe imaging contrast of melanin for metastatic outcome: A 71-patient study}},
author = {David Grass and Emma Bao and Martin C. Fischer and M. Angelica Selim and Georgia M. Beasley and Warren S. Warren},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.08814},
eprint = {2609.08814},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.08814},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Evaluating the predictive power of pump-probe imaging contrast of melanin for metastatic outcome: A 71-patient study
AU - David Grass
AU - Emma Bao
AU - Martin C. Fischer
AU - M. Angelica Selim
AU - Georgia M. Beasley
AU - Warren S. Warren
PY - 2026
DA - 2026/09/08
PB - arXiv
DO - 10.48550/arxiv.2609.08814
UR - https://arxiv.org/abs/2609.08814
AB - Significance: Most melanoma deaths arise from metastatic spread, yet current staging imperfectly identifies which primary tumors will progress. Melanin structure is altered during malignant transformation, and pump-probe microscopy (PPM) measures melanin excited-state dynamics in standard biopsy sections, offering molecular contrast that is complementary to morphology-based assessment. Aim: To determine whether PPM-derived melanin excited-state dynamics in primary cutaneous melanoma can predict metastatic outcome. Approach: We imaged unstained sections from 71 primary cutaneous melanomas and 18 melanoma metastases. Transient absorption curves were fit to a biexponential excited-state model, and the fit parameters were used as features for learning classifiers to predict metastatic outcome. Results: Melanin dynamics separated primary from metastatic tissue: both excited-state lifetimes were shorter in primaries, with common-language effect sizes up to 0.26. The same parameters did not separate primary tumors by outcome (effect sizes 0.41-0.61), and univariate logistic regression found no significant association for either the excited-state lifetimes or the ESA/GSB ratio. The best classifier reached 74% patient-level accuracy (AUC 0.73), a plateau reached by several unrelated architectures. Conclusions: PPM robustly distinguishes primary from metastatic melanoma tissue, consistent with progressive melanin disaggregation. While it is clear that pump-probe features of melanin thus correlate with tissue differences, melanin dynamics in single sections of the primary tumor, confounded by heterogeneity, do not give robust predictions of metastatic outcome.
ER -