Nonlinear spectral imaging of human hypertrophic scar based on two-photon excited fluorescence and second-harmonic generation
Bibliographic record
Abstract
BACKGROUND: A noninvasive method using microscopy and spectroscopy for analysing the morphology of collagen and elastin and their biochemical variations in skin tissue will enable better understanding of the pathophysiology of hypertrophic scars and facilitate improved clinical management and treatment of this disease. OBJECTIVE: To obtain simultaneously microscopic images and spectra of collagen and elastin fibres in ex vivo skin tissues (normal skin and hypertrophic scar) using a nonlinear spectral imaging method, and to compare the morphological structure and spectral characteristics of collagen and elastin fibres in hypertrophic scar tissues with those of normal skin, to determine whether this approach has potential for in vivo assessment of the pathophysiology of human hypertrophic scars and for monitoring treatment responses as well as for tracking the process of development of hypertrophic scars in clinic. METHODS: Ex vivo human skin specimens obtained from six patients aged from 10 to 50 years old who were undergoing skin plastic surgery were examined. Five patients had hypertrophic scar lesions and one patient had no scar lesion before we obtained his skin specimen. A total of 30 tissue section samples of 30 mum thickness were analysed by the use of a nonlinear spectral imaging system consisting of a femtosecond excitation light source, a high-throughput scanning inverted microscope, and a spectral imaging detection system. The high-contrast and high-resolution second harmonic generation (SHG) images of collagen and two-photon excited fluorescence (TPEF) images of elastin fibres in hypertrophic scar tissues and normal skin were acquired using the extracting channel tool of the system. The emission spectra were analysed using the image-guided spectral analysis method. The depth-dependent decay constant of the SHG signal and the image texture characteristics of hypertrophic scar tissue and normal skin were used to quantitatively assess the amount, distribution and orientation of their collagen and elastin components. RESULTS: Our experiments and data analyses demonstrated apparent differences between hypertrophic scar tissue and normal skin in terms of their morphological structure and the spectral characteristics of collagen and elastin fibres. These differences can potentially be used to distinguish hypertrophic scar tissues from normal skin and to evaluate treatment responses. CONCLUSIONS: All the measurements were performed in backscattering geometry and demonstrated that nonlinear spectral imaging has the ability to differentiate hypertrophic scar tissue from normal skin based on noninvasive SHG imaging, and TPEF imaging revealed the microstructure and spectral features of collagen and elastin fibres. With the advances in spectral imaging apparatus miniaturization, we have good reason to believe that this approach can become a valuable tool for the in vivo pathophysiology study of human skin hypertrophic scars and for assessing the treatment responses of this disfiguring disease in clinic. It can also be used to track the development of hypertrophic scars and to study wound healing processes in a noninvasive fashion without biopsy, fixation, sectioning and the use of exogenous dyes or stains.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".