Dynamic optical coherence tomography for industrial inline inspection: Real-time motion artifact compensation via adaptive galvanometer scanning

This study aimed to examine potential discriminatory characteristics of dermatoscopy and dynamic optical coherence tomography (D-OCT) on vulvar high-grade squamous intraepithelial lesions (vHSIL) and lichen sclerosus (LS) compared with healthy vulvar skin. A prospective observational clinical trial was performed in 10 healthy volunteers, 5 vHSIL and 10 LS patients. Noninvasive imaging measurements using dermatoscopy and D-OCT were obtained at several time points, including lesional and nonlesional vulvar skin. Morphologic features of vHSIL and LS were compared with healthy controls. Epidermal thickness and blood flow were determined using D-OCT. Patients reported tolerability of each study procedure, including reference vulvar biopsies. The main outcome measures were feasibility and tolerability of imaging modalities, dermatoscopy and OCT characteristics, OCT epidermal thickness and D-OCT dermal blood flow. The application of dermatoscopy and D-OCT is feasible and tolerable. In vHSIL, dermatoscopic warty structures were present. In LS, sclerotic areas and arborizing vessels were observed. Structural OCT in the vulvar area aligned with histology for hyperkeratosis and dermal-epidermal junction visualization. Currently, the OCT algorithm is unable to calculate the epidermal thickness of the uneven vulvar area. Dynamic optical coherence tomography showed statistically significant increased blood flow in LS patients (mean ± SD, 0.053 ± 0.029) to healthy controls (0.040 ± 0.012; p = .0024). The application of dermatoscopy and D-OCT is feasible and tolerable in vHSIL and LS patients. Using dermatoscopy and D-OCT, the authors describe potential characteristics to aid differentiation of diseased from healthy vulvar skin, which could complement clinical assessments.

Background: Keloids are fibroproliferative scars with a prominent vascular component, and pulsed dye laser (PDL) is an established treatment, but objective imaging biomarkers of response are lacking. Objective: To evaluate whether dynamic optical coherence tomography (D-OCT) can provide quantitative, depth-resolved monitoring of keloid vascular remodeling under PDL and to explore candidate metrics for hypothesis-generating assessment in future studies. Methods: We conducted a prospective single-case pilot, hypothesis-generating study of a thoracic keloid treated with three sessions of 595 nm PDL, acquiring D-OCT scans at baseline and approximately 30, 60, and 90 days over a standardized 4 × 4 mm region of interest at 0.15, 0.30, and 0.50 mm depths. Primary D-OCT metrics included vascular en-face area, vessel length density, junction density, and mean vessel caliber. Results: The superficial layer (0.15 mm) showed an almost complete collapse of vascular signal (area −88% vs. baseline), the intermediate layer at 0.30 mm exhibited a sustained ~39% reduction in vascular area with parallel decreases in length and caliber at stable branching, and the deep layer at 0.50 mm showed modest area changes with longer but thinner vessels. These depth-resolved changes were consistent with clinical improvement in Vancouver Scar Scale and POSAS scores. Conclusions: D-OCT yielded quantitative, clinically interpretable vascular metrics that align with the expected effects of PDL in this single patient. In this patient, the percentage reduction in vascular area at 0.30 mm by week 8 emerged as a candidate quantitative metric for response monitoring; thresholds in the order of ≥25% could be tested prospectively as hypothesis-generating cut-offs in future controlled and reliability-tested studies, but are not proposed here as validated clinical criteria.

3D cell cultures are widely used in biomedical research for the recapitulation of in vivo microenvironments. Viability assessment and monitoring of these intricate conformations remain an open problem as standard cell viability protocols based on colorimetry or microscopy are not directly applicable to intact 3D samples. Optical coherence tomography (OCT) has been explored extensively for subsurface structural and quasi-functional analysis of 3D cell cultures and tissue. Recent studies of dynamic OCT as a source of cellular contrast have found qualitative associations with necrosis in cell spheroids, suggesting potential as a viability marker. We present empirical and validated evidence for dynamic OCT as a quantitative indicator of cell viability in 3D cultures. We analysed over 240 MCF-7 cancer cell spheroids with dynamic OCT and corresponding viability measurements using the trypan blue exclusion assay. Significant effects of common reagents dimethyl sulfoxide (DMSO) and phosphate-buffered saline (PBS) on OCT readouts were noted. We proposed a regression-based OCT brightness normalisation technique that removed reagent-induced OCT intensity biases and helped improve correspondence to the viability assay. These results offer a quantitative biological foundation for further advances of dynamic OCT as a novel non-invasive modality for 3D culture monitoring.

BackgroundSystemic sclerosis is a rare connective tissue disorder characterized by a triad of inflammation, vasculopathy, and fibrosis. Vasculopathic disease manifestations occur early in disease development and include Raynaud’s phenomenon, acral...

Clinical grading of actinic keratosis (AK) is based on skin surface features, while subclinical alterations are not taken into consideration. Dynamic optical coherence tomography (D-OCT) enables quantification of the skin´s vasculature, potentially helpful to improve the link between clinical and subclinical features. We aimed to compare microvascular characteristics across AK grades using D-OCT with automated vascular analysis. This explorative study examined AK and photodamaged skin (PD) on the face or scalp. AKs were clinically graded according to the Olsen Classification scheme before D-OCT assessment. Using an open-source software tool, the OCT angiographic analyzer (OCTAVA), we quantified vascular network features, including total and mean vessel length, mean vessel diameter, vessel area density (VAD), branchpoint density (BD), and mean tortuosity from enface maximum intensity projection images. Additionally, we performed subregional analyses on selected scans to overcome challenges associated with imaging through hyperkeratosis (each lesion group; n = 18). Our study included 45 patients with a total of 205 AKs; 93 grade I lesions, 65 grade II, 47 grade III and 89 areas with PD skin. We found that all AK grades were more extensively vascularized relative to PD, as shown by greater total vessel length and VAD (p ≤ 0.009). Moreover, AKs displayed a disorganized vascular network, with higher BD in AK I-II (p < 0.001), and mean tortuosity in AK II-III (p ≤ 0.001) than in PD. Vascularization also increased with AK grade, showing significantly greater total vessel length in AK III than AK I (p = 0.029). Microvascular quantification of AK unveiled subclinical, quantitative differences among AK grades I-III and PD skin. D-OCT-based microvascular assessment may serve as a supplement to clinical AK grading, potentially raising perspectives to improve management strategies.

We demonstrate a novel approach to generate contrast between healthy and cancerous human breast tissue based on changes in mechanical properties using dynamic optical coherence tomography, validated using co-registered histology.

Kidney transplantation remains the preferred treatment for patients with end-stage kidney disease. However, the ongoing shortage of donor organs continues to limit the availability of transplant treatments. Existing evaluation methods, such as the kidney donor profile index (KDPI) and pre-transplant donor biopsy (PTDB), have various limitations, including low discriminative power, invasiveness, and sampling errors, which reduce their effectiveness in organ quality assessment and contribute to the risk of unnecessary organ discard. In this study, we explored the dynamic optical coherence tomography (DOCT) as a label-free, non-invasive approach to monitor the viability of ex vivo mouse kidneys during static cold storage over 48 hours. The dynamic metrics logarithmic intensity variance (LIV), early OCT correlation decay speed (OCDSe), and late OCT correlation decay speed (OCDSl) were extracted from OCT signal fluctuations to quantify temporal and spatial tissue activity and deterioration. Our results demonstrate that DOCT provides complementary information relevant to tissue viability, in addition to the morphological assessment offered by conventional OCT imaging, showing potential to improve pre-transplant organ evaluation and clinic decision-making.

This study aims at demonstrating label-free drug-response-patterns assessment of different tumor spheroids and drug types by dynamic optical coherence tomography (D-OCT). The study involved human breast cancer (MCF-7) and colon cancer (HT-29) spheroids. The MCF-7 and HT-29 spheroids were treated with paclitaxel (Taxol; PTX) and the active metabolite of irinotecan SN-38, respectively. The drugs were applied with 0 (control), 0.1, 1, and 10 μM concentrations and the treatment durations were 1, 3, and 6 days. A swept-source OCT microscope equipped with a repeated raster scanning protocol was used to scan the spheroids. Logarithmic intensity variance (LIV) and late OCT correlation decay speed (OCDS_l) algorithms were used to visualize the tumor spheroid dynamics. LIV and OCDS_l images visualized different response patterns of the two types of spheroids. In addition, spheroid morphology, LIV, and OCDS_l quantification showed different time-courses among the spheroid and drug types. These results may indicate different action mechanisms of the drugs. The results showed the feasibility of D-OCT for the evaluation of drug response patterns of different cell spheroids and drug types and suggest that D-OCT can perform anti-cancer drug testing.

Conventional scanned optical coherence tomography (OCT) suffers from the frame rate/resolution tradeoff, whereby increasing image resolution leads to decreases in the maximum achievable frame rate. To overcome this limitation, we propose two variants of machine learning (ML)-based adaptive scanning approaches: one using a ConvLSTM-based sequential prediction model and another leveraging a temporal attention unit (TAU)-based parallel prediction model for scene dynamics prediction. These models are integrated with a kinodynamic path planner based on the clustered traveling salesperson problem to create two versions of ML-based adaptive scanning pipelines. Through experimental validation with novel deterministic phantoms based on a digital light processing board, our techniques achieved mean frame rate speed-ups of up to 40% compared to conventional raster scanning and the probabilistic adaptive scanning method without compromising image quality. Furthermore, these techniques reduced scene-dependent manual tuning of system parameters to demonstrate better generalizability across scenes of varying types, including those of intrasurgical relevance. In a real-time surgical tool tracking experiment, our technique achieved an average speed-up factor of over 3.2× compared to conventional scanning methods, without compromising image quality.

The current pathological diagnosis of lymph node metastasis is time-consuming, labor-intensive, and dependent on sectioning of paraffin blocks. Herein, in a prospective cohort of patients with breast cancer, we validated dynamic full-field optical coherence tomography (D-FFOCT), a virtual pathology tool integrating deep learning for nodal metastasis detection, and offering rapid and label-free histologic approximations of fresh tissues. In a prospective dual-center cohort of 155 patients with breast cancer, 747 freshly bisected lymph node slides were obtained via D-FFOCT. Surgeons interpreted each slide with histopathology as the gold standard. A deep learning model was trained on 28,911 patches (corresponding to 590 slides) and tested on 7,736 patches (corresponding to 157 slides). The results were mapped to the slide level for potential intraoperative evaluation. D-FFOCT strongly correlated with hematoxylin and eosin (H&E)-stained histological images. Surgeons achieved 97.10% specificity in nodal diagnosis with D-FFOCT. The performance of the artificial intelligence (AI) model was not inferior to that of human experts and had a sensitivity/specificity of 87.88%/91.94% and an area under the receiver operating characteristic curve of 0.899 at the slide level. The human-AI collaborative system reduced labor requirements by 75% and increased the specificity by 6.5%, to 98.39%. D-FFOCT has excellent potential as a tool for assessing lymph node metastatic status without tissue preparation or consumption. The integration of D-FFOCT with deep learning decreases labor demands and maintains high accuracy, thereby enabling streamlined nodal prediction independent of routine pathology procedures.

Dynamic contrast optical coherence tomography (DyC-OCT), an emerging imaging method, utilizes fluctuation patterns in OCT signals to enhance contrast, thereby enabling non-invasive label-free volumetric live cell imaging. In this mini review, we explain the core concepts behind DyC-OCT image formation and its system configurations, serving as practical guidance for future DyC-OCT users. Subsequently, we explore its applications in delivering high-quality, contrast-enhanced images of cellular morphology, as well as in monitoring changes in cellular activity/viability assay experiments.

An intraoperative diagnosis is critical for precise cancer surgery. However, traditional intraoperative assessments based on hematoxylin and eosin (H&E) histology, such as frozen section, are time-, resource-, and labor-intensive, and involve specimen-consuming concerns. Here, we report a near-real-time automated cancer diagnosis workflow for breast cancer that combines dynamic full-field optical coherence tomography (D-FFOCT), a label-free optical imaging method, and deep learning for bedside tumor diagnosis during surgery. To classify the benign and malignant breast tissues, we conducted a prospective cohort trial. In the modeling group (n = 182), D-FFOCT images were captured from April 26 to June 20, 2018, encompassing 48 benign lesions, 114 invasive ductal carcinoma (IDC), 10 invasive lobular carcinoma, 4 ductal carcinoma in situ (DCIS), and 6 rare tumors. Deep learning model was built up and fine-tuned in 10,357 D-FFOCT patches. Subsequently, from June 22 to August 17, 2018, independent tests (n = 42) were conducted on 10 benign lesions, 29 IDC, 1 DCIS, and 2 rare tumors. The model yielded excellent performance, with an accuracy of 97.62%, sensitivity of 96.88% and specificity of 100%; only one IDC was misclassified. Meanwhile, the acquisition of the D-FFOCT images was non-destructive and did not require any tissue preparation or staining procedures. In the simulated intraoperative margin evaluation procedure, the time required for our novel workflow (approximately 3 min) was significantly shorter than that required for traditional procedures (approximately 30 min). These findings indicate that the combination of D-FFOCT and deep learning algorithms can streamline intraoperative cancer diagnosis independently of traditional pathology laboratory procedures.

FRI0370 Three-dimensional nailfold capillary imaging by dynamic optical coherence tomography in systemic sclerosis: a validation study using nailfold video-capillaroscopy

Dynamic optical coherence tomography (D-OCT) allows in vivo visualization of blood vessels in the skin and in malignant tumours. Vessel patterns in malignant melanoma may be associated with tumour stage. The aim of this study was to describe blood vessel patterns in melanomas and to correlate them with stage. One hundred fifty-nine malignant melanomas were assessed in a multicentre study. Every tumour was imaged using D-OCT prior to surgery and histologic evaluation. The tumour data such as thickness and ulceration as well as the staging at primary diagnosis and a follow-up of at least 40months resulted in a stage classification. The vessel patterns were assessed according to predefined categories, compared with healthy adjacent skin, and correlated to stage. Melanomas contained more blood vessels in different patterns compared with healthy adjacent skin. In particular, irregular vascular shapes such as blobs, coils, curves and serpiginous vessels were more common in melanomas. In addition, these patterns were significantly more often found in high-risk and metastatic melanomas than in low-risk lesions. In melanomas, the density of the blood vessels is increased, and irregular vascular patterns are more frequent. At higher stages, especially in metastatic melanomas, these atypical vessels are significantly more common.

Optical coherence tomography (OCT) is becoming a popular modality for skin tumor diagnosis and assessment of tumor size and margin status. We conducted a number of imaging experiments on periocular basal cell carcinoma (BCC) specimens using an OCT configuration. This configuration employs a dynamic focus (DF) procedure where the coherence gate moves synchronously with the peak of the confocal gate, which ensures better signal strength and preservation of transversal resolution from all depths. A DF-OCT configuration is used to illustrate morphological differences between the BCC and its surrounding healthy skin in OCT images. The OCT images are correlated with the corresponding histology images. To the best of our knowledge, this is the first paper to look at DF-OCT imaging in examining periocular BCC.