Evidence map›Paper›PMID 42205507›Full record

ArticleJournal of biomedical optics2026

Quantitative second harmonic generation microscopy for characterizing collagen remodeling in papillary thyroid carcinoma.

Wesley Poon, Lin Wang, Orhun Davarci, Reid Master, Hong Zhao, Jun Liu, Helmi S Khadra, Elizabeth M Jacobi, Raksha Raghunathan, Stephen T C Wong

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Wesley PoonHouston Methodist Neal Cancer Center, Department of Systems Medicine and Bioengineering, Houston, Texas, United States.ORCID https://orcid.org/0000-0002-9774-3673
Lin WangHouston Methodist Neal Cancer Center, Department of Systems Medicine and Bioengineering, Houston, Texas, United States.
Orhun DavarciHouston Methodist Neal Cancer Center, Department of Systems Medicine and Bioengineering, Houston, Texas, United States.ORCID https://orcid.org/0000-0002-4209-3474
Reid MasterHouston Methodist Neal Cancer Center, Department of Systems Medicine and Bioengineering, Houston, Texas, United States.ORCID https://orcid.org/0009-0006-0066-1249
Hong ZhaoHouston Methodist Neal Cancer Center, Department of Systems Medicine and Bioengineering, Houston, Texas, United States.ORCID https://orcid.org/0000-0001-8991-7824
Jun LiuShanghai General Hospital, Shanghai Jiao Tong University, Department of Breast-Thyroid-Vascular Surgery, Shanghai, China.
Helmi S KhadraHouston Methodist Hospital, Department of Surgery, Houston, Texas, United States.
Elizabeth M JacobiHouston Methodist Hospital, Department of Pathology and Genomic Medicine, Houston, Texas, United States.ORCID https://orcid.org/0000-0002-2870-8436
Raksha RaghunathanHouston Methodist Neal Cancer Center, Department of Systems Medicine and Bioengineering, Houston, Texas, United States.ORCID https://orcid.org/0000-0002-2434-425X
Stephen T C WongHouston Methodist Neal Cancer Center, Department of Systems Medicine and Bioengineering, Houston, Texas, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: Thyroid cancer is the most common endocrine malignancy. Although fine needle aspiration (FNA) is the gold standard for diagnosis, 10% to 20% of FNAs yield indeterminate cytology, of which 20% to 30% prove malignant. Such diagnostic uncertainty drives repeat FNAs, costly molecular tests, and unnecessary surgeries, leading to increased healthcare costs, reduced quality of life, and emotional distress to patients. Current methods provide limited structural information about the extra-cellular matrix, despite collagen remodeling being a hallmark of malignancy. A rapid, label-free, and architecture-based diagnostic approach has the potential to significantly improve real-time or near-real-time decision-making and reduce unnecessary biopsies and interventions. Aim: We use a systematic, quantitative framework based on second harmonic generation (SHG) microscopy to differentiate between normal and cancerous (papillary thyroid carcinoma [PTC]) human thyroid tissues through collagen architecture signatures. Approach: Formalin-fixed paraffin-embedded unstained tissue sections ( Results: Of the 35 metrics evaluated, 19 remained statistically significant after false discovery rate (FDR) adjustment for multiple comparisons. The corresponding effect sizes ranged from moderate to large, indicating substantial separation between normal and cancerous samples. Five of the remaining 16 metrics, although not statistically significant, were consistently either higher or lower in one group compared with the other, suggesting directional consistency. This revealed robust and biologically coherent alterations in collagen organization despite small cohort size. These included consistent increases in spectral power across multiple spatial frequency bands and greater collagen heterogeneity in cancer tissue. Conclusions: The convergence of significant and directionally consistent metrics underscores the strong diagnostic potential of SHG-derived collagen architecture. Integrating these quantitative features into an automated analysis platform could enable rapid, objective, and reproducible optical biopsies, with the potential to reduce indeterminate FNAs, guide intraoperative decision-making, and improve diagnostic accuracy in routine thyroid cancer care.

Indexed as

CollagenSecond Harmonic Generation MicroscopyThyroid Cancer, PapillaryThyroid NeoplasmsHumansMicroscopy, Fluorescence, MultiphotonThyroid GlandCollagenlabel-free imagingnonlinear optical imagingsecond harmonic generation microscopythyroid cancer

Identifiers

PMID42205507
PMCPMC13210880

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.