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Recent years have ushered in a transformative era in in vitro modeling with the advent of organoids, three-dimensional structures derived from stem cells or patient tumor cells. Still, fully harnessing the potential of organoids requires advanced imaging technologies and analytical tools to quantitatively monitor organoid growth. Optical coherence tomography (OCT) is a promising imaging modality for organoid analysis due to its high-resolution, label-free, non-destructive, and real-time 3D imaging capabilities, but accurately identifying and quantifying organoids in OCT images remain challenging due to various factors. Here, we propose an automatic deep learning-based pipeline with convolutional neural networks that synergistically includes optimized preprocessing steps, the implementation of a state-of-the-art deep learning model, and ad-hoc postprocessing methods, showcasing good generalizability and tracking capabilities over an extended period of 13 days. The proposed tracking algorithm thoroughly documents organoid evolution, utilizing reference volumes, a dual branch analysis, key attribute evaluation, and probability scoring for match identification. The proposed comprehensive approach enables the accurate tracking of organoid growth and morphological changes over time, advancing organoid analysis and serving as a solid foundation for future studies for drug screening and tumor drug sensitivity detection based on organoids.
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Purpose: To investigate the visualization capabilities of high-speed swept-source optical coherence tomography (SS-OCT) in cataract surgery. Methods: Cataract surgery was simulated in wet labs with ex vivo porcine eyes. Each phase of the surgery was visualized with a novel surgical microscope-integrated SS-OCT with a variable imaging speed of over 1 million A-scans per second. It was designed to provide four-dimensional (4D) live-volumetric videos, live B-scans, and volume capture scans. Results: Four-dimensional videos, B-scans, and volume capture scans of corneal incision, ophthalmic viscosurgical device injection, capsulorrhexis, phacoemulsification, intraocular lens (IOL) injection, and position of unfolded IOL in the capsular bag were recorded. The flexibility of the SS-OCT system allowed us to tailor the scanning parameters to meet the specific demands of dynamic surgical steps and static pauses. The entire length of the eye was recorded in a single scan, and unfolding of the IOL was visualized dynamically. Conclusions: The presented novel visualization method for fast ophthalmic surgical microscope-integrated intraoperative OCT imaging in cataract surgery allowed the visualization of all major steps of the procedure by achieving large imaging depths covering the entire eye and high acquisition speeds enabling live volumetric 4D-OCT imaging. This promising technology may become an integral part of routine and advanced robotic-assisted cataract surgery in the future. Translational Relevance: We demonstrate the visualization capabilities of a cutting edge swept-source OCT system integrated into an ophthalmic surgical microscope during cataract surgery.
Subject(s)
Cataract , Lenses, Intraocular , Ophthalmology , Swine , Animals , Tomography, Optical Coherence , EyeABSTRACT
Organoid and spheroid technology provide valuable insights into developmental biology and oncology. Optical coherence tomography (OCT) is a label-free technique that has emerged as an excellent tool for monitoring the structure and function of these samples. However, mature organoids are often too opaque for OCT. Access to multi-angle views is highly desirable to overcome this limitation, preferably with non-contact sample handling. To fulfil these requirements, we present an ultrasound-induced reorientation method for multi-angle-OCT, which employs a 3D-printed acoustic trap inserted into an OCT imaging system, to levitate and reorient zebrafish larvae and tumor spheroids in a controlled and reproducible manner. A model-based algorithm was developed for the physically consistent fusion of multi-angle data from a priori unknown angles. We demonstrate enhanced penetration depth in the joint 3D-recovery of reflectivity, attenuation, refractive index, and position registration for zebrafish larvae, creating an enabling tool for future applications in volumetric imaging.
Subject(s)
Neoplasms , Tomography, Optical Coherence , Animals , Tomography, Optical Coherence/methods , Zebrafish , UltrasonographyABSTRACT
PURPOSE: To compare detection rates of microaneurysms (MAs) on high-speed megahertz optical coherence tomography angiography (MHz-OCTA), fluorescein angiography (FA) and colour fundus photography (CF) in patients with diabetic retinopathy (DR). METHODS: For this exploratory cross-sectional study, MHz-OCTA data were acquired with a swept-source OCT prototype (A-scan rate: 1.7 MHz), and FA and CF imaging was performed using Optos® California. MA count was manually evaluated on en face MHz-OCTA/FA/CF images within an extended ETDRS grid. Detectability of MAs visible on FA images was evaluated on corresponding MHz-OCTA and CF images. MA distribution and leakage were correlated with detectability on OCTA and CF imaging. RESULTS: 47 eyes with severe DR (n = 12) and proliferative DR (n = 35) were included. MHz-OCTA and CF imaging detected on average 56% and 36% of MAs, respectively. MHz-OCTA detection rate was significantly higher than CF (p < 0.01). The combination of MHz-OCTA and CF leads to an increased detection rate of 70%. There was no statistically significant association between leakage and MA detectability on OCTA (p = 0.13). For CF, the odds of detecting leaking MAs were significantly lower than non-leaking MAs (p = 0.012). Using MHz-OCTA, detection of MAs outside the ETDRS grid was less likely than MAs located within the ETDRS grid (outer ring, p < 0.01; inner ring, p = 0.028). No statistically significant difference between rings was observed for CF measurements. CONCLUSIONS: More MAs were detected on MHz-OCTA than on CF imaging. Detection rate was lower for MAs located outside the macular region with MHz-OCTA and for leaking MAs with CF imaging. Combining both non-invasive modalities can improve MA detection.
Subject(s)
Diabetic Retinopathy , Fluorescein Angiography , Fundus Oculi , Microaneurysm , Retinal Vessels , Tomography, Optical Coherence , Humans , Diabetic Retinopathy/diagnosis , Diabetic Retinopathy/diagnostic imaging , Tomography, Optical Coherence/methods , Cross-Sectional Studies , Microaneurysm/diagnosis , Microaneurysm/etiology , Fluorescein Angiography/methods , Male , Female , Middle Aged , Retinal Vessels/diagnostic imaging , Retinal Vessels/pathology , AgedABSTRACT
Modern artificial intelligence (AI) approaches mainly rely on neural network (NN) or deep NN methodologies. However, these approaches require large amounts of data to train, given, that the number of their trainable parameters has a polynomial relationship to their neuron counts. This property renders deep NNs challenging to apply in fields operating with small, albeit representative datasets such as healthcare. In this paper, we propose a novel neural network architecture which trains spatial positions of neural soma and axon pairs, where weights are calculated by axon-soma distances of connected neurons. We refer to this method as distance-encoding biomorphic-informational (DEBI) neural network. This concept significantly minimizes the number of trainable parameters compared to conventional neural networks. We demonstrate that DEBI models can yield comparable predictive performance in tabular and imaging datasets, where they require a fraction of trainable parameters compared to conventional NNs, resulting in a highly scalable solution.
Subject(s)
Artificial Intelligence , Neural Networks, Computer , Algorithms , Diagnostic Imaging , NeuronsABSTRACT
PURPOSE: To evaluate the association of microvascular lesions on ultrawidefield (UWF) color fundus (CF) images with retinal nonperfusion (RNP) up to the midperiphery on single-capture widefield (WF) OCT angiography (OCTA) in patients with diabetic retinopathy (DR). DESIGN: Cross-sectional study. SUBJECTS: Seventy-five eyes of 50 patients with mild to severe nonproliferative DR (NPDR) and proliferative DR (PDR) were included in this analysis. METHODS: ETDRS level and presence of predominantly peripheral lesions (PPLs) were assessed on UWF-CF images acquired with a Zeiss Clarus 700. Single-capture 65°-WF-OCTA was performed using a PlexElite prototype (Carl Zeiss Meditec, Inc.). A custom grid consisting of a central ETDRS grid extended by 2 rings reaching up to the midperiphery was overlaid to subdivide retinal areas visible on WF-OCTA en face images. Retinal nonperfusion was measured in each area and in total. Nonperfusion index (NPI) was calculated from total RNP. On UWF-CF images, the number of microaneurysms, hemorrhages, neovascularizations, and areas with intraretinal microvascular abnormalities (IRMAs) were evaluated using the same grid. MAIN OUTCOME MEASURES: Association of diabetic lesions with RNP was calculated using Spearman correlations (rs). RESULTS: Median RNP on WF-OCTA was 0 mm2 (0-0.9), 4.9 mm2 (1.9-5.4), 23.4 mm2 (17.8-37), and 68.4 mm2 (40.8-91.7) in mild, moderate, and severe NPDR and PDR, respectively. We found a statistically significant correlation (P < 0.01) of overall RNP (rs = 0.96,) and NPI (rs = 0.97) on WF-OCTA with ETDRS level. Number of grid-fields affected by IRMAs on CF images was highly associated with NPI (rs = 0.86, P < 0.01). Intraretinal microvascular abnormalities and RNPs had similar topographic distributions with high correlations in affected areas. Eyes with PPLs (n = 43 eyes, 57%) on CF images had a significantly higher NPI (P = 0.014) than eyes without PPLs. CONCLUSION: The combination of UWF-CF imaging and single-capture WF-OCTA allows precise and noninvasive analysis of the retinal vasculature up to the midperiphery in patients with DR. The presence and extent of IRMAs on CF images may serve as an indicator for underlying RNP, which is more pronounced in eyes with PPLs. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Subject(s)
Diabetes Mellitus , Diabetic Retinopathy , Humans , Cross-Sectional Studies , Fluorescein Angiography/methods , Retina/pathology , Diabetic Retinopathy/diagnosis , Diabetic Retinopathy/complications , Multimodal ImagingABSTRACT
Optical Coherence Tomography (OCT) has recently gained attention as a promising technology for in-line monitoring of pharmaceutical film-coating processes for (single-layered) tablet coatings and end-point detection with commercial systems. An increasing interest in the investigation of multiparticulate dosage forms with mostly multi-layered coatings below 20 µm final film thickness demands advancement in OCT technology for pharmaceutical imaging. We present an ultra-high-resolution (UHR-) OCT and investigate its performance based on three different multiparticulate dosage forms with different layer structures (one single-layered, two multi-layered) with layer thicknesses in a range from 5 to 50 µm. The achieved system resolution of 2.4 µm (axial) and 3.4 µm (lateral, both in air) enables the assessment of defects, film thickness variability and morphological features within the coating, previously unattainable using OCT. Despite the high transverse resolution, the provided depth of field was found sufficient to reach the core region of all dosage forms under test. We further demonstrate an automated segmentation and evaluation of UHR-OCT images for coating thicknesses, where human experts struggle using today's standard OCT systems.
Subject(s)
Tomography, Optical Coherence , Humans , Tomography, Optical Coherence/methods , Tablets , Surface PropertiesABSTRACT
Swept-source optical coherence tomography (SS-OCT) demonstrates superior performance in comparison to spectral domain OCT with regard to depth ranging. The main driver of cost for SS-OCT systems is, however, the price of the source. Here we show a low-cost alternative swept source that uses a thermally tuned vertical-cavity surface-emitting laser (VCSEL) at 850â nm. Its center wavelength can be tuned by adjusting the operating temperature through modulation of the injection current. At 2 kHz sweep rate, the depth range of the system was 5â cm, with a sensitivity roll-off of under -3â dB across this range. The system achieved a sensitivity of 97â dB with a sample beam power of 0.3â mW and an axial resolution of 50â µm in air. To demonstrate the system performance in vivo, an eye of a healthy volunteer was measured, and full-eye scans were acquired at 25 and 50 kHz from the cornea to the retina. Based on our results, we believe that this technology can be used as a cost-effective alternative OCT for point-of-care diagnostics.
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Diabetic retinopathy (DR), a pathologic change of the human retinal vasculature, is the leading cause of blindness in working-age adults with diabetes mellitus. Optical coherence tomography angiography (OCTA), a functional extension of optical coherence tomography, has shown potential as a tool for early diagnosis of DR through its ability to visualize the retinal vasculature in all spatial dimensions. Previously introduced deep learning-based classifiers were able to support the detection of DR in OCTA images, but require expert labeling at the pixel level, a labor-intensive and expensive process. We present a multiple instance learning-based network, MIL-ResNet,14 that is capable of detecting biomarkers in an OCTA dataset with high accuracy, without the need for annotations other than the information whether a scan is from a diabetic patient or not. The dataset we used for this study was acquired with a diagnostic ultra-widefield swept-source OCT device with a MHz A-scan rate. We were able to show that our proposed method outperforms previous state-of-the-art networks for this classification task, ResNet14 and VGG16. In addition, our network pays special attention to clinically relevant biomarkers and is robust against adversarial attacks. Therefore, we believe that it could serve as a powerful diagnostic decision support tool for clinical ophthalmic screening.
Subject(s)
Diabetes Mellitus , Diabetic Retinopathy , Adult , Humans , Diabetic Retinopathy/diagnostic imaging , Diabetic Retinopathy/pathology , Fluorescein Angiography/methods , Tomography, Optical Coherence/methods , Retinal Vessels/pathology , Early Diagnosis , Diabetes Mellitus/pathologyABSTRACT
By providing three-dimensional visualization of tissues and instruments at high resolution, live volumetric optical coherence tomography (4D-OCT) has the potential to revolutionize ophthalmic surgery. However, the necessary imaging speed is accompanied by increased noise levels. A high data rate and the requirement for minimal latency impose major limitations for real-time noise reduction. In this work, we propose a low complexity neural network for denoising, directly incorporated into the image reconstruction pipeline of a microscope-integrated 4D-OCT prototype with an A-scan rate of 1.2 MHz. For this purpose, we trained a blind-spot network on unpaired OCT images using a self-supervised learning approach. With an optimized U-Net, only a few milliseconds of additional latency were introduced. Simultaneously, these architectural adaptations improved the numerical denoising performance compared to the basic setup, outperforming non-local filtering algorithms. Layers and edges of anatomical structures in B-scans were better preserved than with Gaussian filtering despite comparable processing time. By comparing scenes with and without denoising employed, we show that neural networks can be used to improve visual appearance of volumetric renderings in real time. Enhancing the rendering quality is an important step for the clinical acceptance and translation of 4D-OCT as an intra-surgical guidance tool.
Subject(s)
Deep Learning , Neural Networks, Computer , Image Processing, Computer-Assisted/methods , Algorithms , Tomography, Optical Coherence/methods , Signal-To-Noise RatioABSTRACT
Intraoperative optical coherence tomography is still not overly pervasive in routine ophthalmic surgery, despite evident clinical benefits. That is because today's spectral-domain optical coherence tomography systems lack flexibility, acquisition speed, and imaging depth. We present to the best of our knowledge the most flexible swept-source optical coherence tomography (SS-OCT) engine coupled to an ophthalmic surgical microscope that operates at MHz A-scan rates. We use a MEMS tunable VCSEL to implement application-specific imaging modes, enabling diagnostic and documentary capture scans, live B-scan visualizations, and real-time 4D-OCT renderings. The technical design and implementation of the SS-OCT engine, as well as the reconstruction and rendering platform, are presented. All imaging modes are evaluated in surgical mock maneuvers using ex vivo bovine and porcine eye models. The applicability and limitations of MHz SS-OCT as a visualization tool for ophthalmic surgery are discussed.
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Purpose: Modern techniques for improved tumor visualization have the aim to maximize the extent of resection during brain tumor surgery and thus improve patient prognosis. Optical imaging of autofluorescence is a powerful and non-invasive tool to monitor metabolic changes and transformation in brain tumors. Cellular redox ratios can be retrieved from fluorescence emitted by the coenzymes reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD). Recent studies point out that the influence of flavin mononucleotide (FMN) has been underestimated. Experimental design: Fluorescence lifetime imaging and fluorescence spectroscopy were performed through a modified surgical microscope. We acquired 361 flavin fluorescence lifetime (500-580 nm) and fluorescence spectra (430-740 nm) data points on freshly excised different brain tumors: low-grade gliomas (N=17), high-grade gliomas (N=42), meningiomas (N=23), metastases (N=26) and specimens from the non-tumorous brain (N=3). Results: Protein-bound FMN fluorescence in brain tumors did increase with a shift toward a more glycolytic metabolism (R=-0.87). This increased the average flavin fluorescence lifetime in tumor entities with respect to the non-tumorous brain. Further, these metrics were characteristic for the different tumor entities and showed promise for machine learning based brain tumor classification. Conclusions: Our results shed light on FMN fluorescence in metabolic imaging and outline the potential for supporting the neurosurgeon in visualizing and classifying brain tumor tissue during surgery.
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AIM: To assess the detection rate of retinal neovascularisation (NV) in eyes with proliferative diabetic retinopathy (PDR) using widefield optical coherence tomography angiography (WF-OCTA) in comparison to ultrawidefield fluorescein angiography (UWF-FA). METHODS: Single-capture 65°-WF-OCTA-imaging was performed in patients with NV at the disc or elsewhere (NVE) detected on UWF-FA using a modified PlexElite system and B-scans were examined for blood flow signals breaching the internal limiting membrane. Sensitivity of WF-OCTA and UWF colour fundus (UWF-CF) photography for correct diagnosis of PDR was determined and interdevice agreement (Fleiss' κ) between WF-OCTA and UWF-FA for detection of NV in the total gradable area and each retinal quadrant was evaluated. RESULTS: Fifty-nine eyes of 41 patients with PDR detected on UWF-FA were included. Sensitivity of detecting PDR on WF-OCTA scans was 0.95 in contrast to 0.78 on UWF-CF images. Agreement in detecting NVE between WF-OCTA and UWF-FA was high in the superotemporal (κ=0.98) and inferotemporal (κ=0.94) and weak in the superonasal (κ=0.24) and inferonasal quadrants (κ=0.42). On UWF-FA, 63% of NVEs (n=153) were located in the temporal quadrants with 93% (n=142) of them being detected on WF-OCTA scans. CONCLUSION: The high reliability of non-invasive WF-OCTA imaging in detecting PDR can improve clinical examination with the potential to replace FA as a single diagnostic tool.
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Gastrointestinal (GI) endoscopy is a common medical diagnostic procedure used for esophageal cancer detection. Current emerging capsule optoacoustic endoscopes, however, suffer from low pulse repetition rates and slow scanning units limit attainable imaging frame rates. Consequently, motion artifacts result in inaccurate spatial mapping and misinterpretation of data. To overcome these limitations, we report a 360º, 50 Hz frame rate, distal scanning capsule optoacoustic endoscope. The translational capability of the instrument for human GI tract imaging was characterized with an Archimedean spiral phantom consisting of twelve 100 µm sutures, a stainless steel mesh with a pitch of 3 mm and an ex vivo pig esophagus sample. We estimated an imaging penetration depth of ~0.84 mm in vivo by immersing the mesh phantom in intralipid solution to simulate light scattering in human esophageal tissue and validated our findings ex vivo using pig esophagus. This proof-of-concept study demonstrates the translational potential of the proposed video-rate endoscope for human GI tract imaging.
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Ocular aberrometry is an essential technique in vision science and ophthalmology. We demonstrate how a phase-sensitive single mode fiber-based swept source optical coherence tomography (SS-OCT) setup can be employed for quantitative ocular aberrometry with digital adaptive optics (DAO). The system records the volumetric point spread function at the retina in a de-scanning geometry using a guide star pencil beam. Succeeding test-retest repeatability assessment with defocus and astigmatism analysis on a model eye within ± 3 D dynamic range, the feasibility of technique is demonstrated in-vivo at a B-scan rate of >1 kHz in comparison with a commercially available aberrometer.
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Achieving high resolution in optical coherence tomography typically requires the continuous extension of the spectral bandwidth of the light source. This work demonstrates an alternative approach: combining two discrete spectral windows located in the visible spectrum with a trained conditional generative adversarial network (cGAN) to reconstruct a high-resolution image equivalent to that generated using a continuous spectral band. The cGAN was trained using OCT image pairs acquired with the continuous and discontinuous visible range spectra to learn the relation between low- and high-resolution data. The reconstruction performance was tested using 6000 B-scans of a layered phantom, micro-beads and ex-vivo mouse ear tissue. The resultant cGAN-generated images demonstrate an image quality and axial resolution which approaches that of the high-resolution system.
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The pyramid wavefront sensor (P-WFS) has replaced the Shack-Hartmann (SH-) WFS as the sensor of choice for high-performance adaptive optics (AO) systems in astronomy. Many advantages of the P-WFS, such as its adjustable pupil sampling and superior sensitivity, are potentially of great benefit for AO-supported imaging in ophthalmology as well. However, so far no high quality ophthalmic AO imaging was achieved using this novel sensor. Usually, a P-WFS requires modulation and high precision optics that lead to high complexity and costs of the sensor. These factors limit the competitiveness of the P-WFS with respect to other WFS devices for AO correction in visual science. Here, we present a cost-effective realization of AO correction with a non-modulated P-WFS based on standard components and apply this technique to human retinal in vivo imaging using optical coherence tomography (OCT). P-WFS based high quality AO imaging was successfully performed in 5 healthy subjects and smallest retinal cells such as central foveal cone photoreceptors are visualized. The robustness and versatility of the sensor is demonstrated in the model eye under various conditions and in vivo by high-resolution imaging of other structures in the retina using standard and extended fields of view. As a quality benchmark, the performance of conventional SH-WFS based AO was used and successfully met. This work may trigger a paradigm shift with respect to the wavefront sensor of choice for AO in ophthalmic imaging.
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Objective: Despite advancements of intraoperative visualization, the difficulty to visually distinguish adenoma from adjacent pituitary gland due to textural similarities may lead to incomplete adenoma resection or impairment of pituitary function. The aim of this study was to investigate optical coherence tomography (OCT) imaging in combination with a convolutional neural network (CNN) for objectively identify pituitary adenoma tissue in an ex vivo setting. Methods: A prospective study was conducted to train and test a CNN algorithm to identify pituitary adenoma tissue in OCT images of adenoma and adjacent pituitary gland samples. From each sample, 500 slices of adjacent cross-sectional OCT images were used for CNN classification. Results: OCT data acquisition was feasible in 19/20 (95%) patients. The 16.000 OCT slices of 16/19 of cases were employed for creating a trained CNN algorithm (70% for training, 15% for validating the classifier). Thereafter, the classifier was tested on the paired samples of three patients (3.000 slices). The CNN correctly predicted adenoma in the 3 adenoma samples (98%, 100% and 84% respectively), and correctly predicted gland and transition zone in the 3 samples from the adjacent pituitary gland. Conclusion: Trained convolutional neural network computing has the potential for fast and objective identification of pituitary adenoma tissue in OCT images with high sensitivity ex vivo. However, further investigation with larger number of samples is required.
Subject(s)
Adenoma/diagnosis , Algorithms , Neural Networks, Computer , Pituitary Neoplasms/diagnosis , Tomography, Optical Coherence/methods , Adenoma/diagnostic imaging , Adult , Aged , Biopsy , Cross-Sectional Studies , Female , Follow-Up Studies , Humans , Male , Middle Aged , Pituitary Neoplasms/diagnostic imaging , Prognosis , Prospective StudiesABSTRACT
Maximal safe resection is a key strategy for improving patient prognosis in the management of brain tumors. Intraoperative fluorescence guidance has emerged as a standard in the surgery of high-grade gliomas. The administration of 5-aminolevulinic acid prior to surgery induces tumor-specific accumulation of protoporphyrin IX, which emits red fluorescence under blue-light illumination. The technology, however, is substantially limited for low-grade gliomas and weakly tumor-infiltrated brain, where low protoporphyrin IX concentrations are outweighed by tissue autofluorescence. In this context, fluorescence lifetime imaging has shown promise to distinguish spectrally overlapping fluorophores. We integrated frequency-domain fluorescence lifetime imaging in a surgical microscope and combined it with spatially registered fluorescence spectroscopy, which can be considered a research benchmark for sensitive protoporphyrin IX detection. Fluorescence lifetime maps and spectra were acquired for a representative set of fresh ex-vivo brain tumor specimens (low-grade gliomas n = 15, high-grade gliomas n = 80, meningiomas n = 41, and metastases n = 35). Combining the fluorescence lifetime with fluorescence spectra unveiled how weak protoporphyrin IX accumulations increased the lifetime respective to tissue autofluorescence. Infiltration zones (4.1ns ± 1.8ns, p = 0.017) and core tumor areas (4.8ns ± 1.3ns, p = 0.040) of low-grade gliomas were significantly distinguishable from non-pathologic tissue (1.6ns ± 0.5ns). Similarly, fluorescence lifetimes for infiltrated and reactive tissue as well as necrotic and core tumor areas were increased for high-grade gliomas and metastasis. Meningioma tumor specimens showed strongly increased lifetimes (12.2ns ± 2.5ns, p = 0.005). Our results emphasize the potential of fluorescence lifetime imaging to optimize maximal safe resection in brain tumors in future and highlight its potential toward clinical translation.
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A novel fast proximal scanning method, to the best of our knowledge, termed fiber-core-targeted scanning (FCTS), is proposed for illuminating individual fiber cores sequentially to remove the pixelation effect in fiber bundle (FB) imaging. FCTS is based on a galvanometer scanning system. Through a dynamic control of the scan trajectory and speed using the prior knowledge of fiber core positions, FCTS experimentally verifies a precise sequential delivery of laser pulses into fiber cores at a maximal speed of 45,000 cores per second. By applying FCTS on a FB-based photoacoustic forward-imaging probe, the results demonstrate that FCTS eliminates the pixelation effect and improves the imaging quality.