1
|
Singh AP, Göb M, Ahrens M, Eixmann T, Schulte B, Schulz-Hildebrandt H, Hüttmann G, Ellrichmann M, Huber R, Rahlves M. Virtual Hall sensor triggered multi-MHz endoscopic OCT imaging for stable real-time visualization. OPTICS EXPRESS 2024; 32:5809-5825. [PMID: 38439298 DOI: 10.1364/oe.514636] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 01/18/2024] [Indexed: 03/06/2024]
Abstract
Circumferential scanning in endoscopic imaging is crucial across various disciplines, and optical coherence tomography (OCT) is often the preferred choice due to its high-speed, high-resolution, and micron-scale imaging capabilities. Moreover, real-time and high-speed 3D endoscopy is a pivotal technology for medical screening and precise surgical guidance, among other applications. However, challenges such as image jitter and non-uniform rotational distortion (NURD) are persistent obstacles that hinder real-time visualization during high-speed OCT procedures. To address this issue, we developed an innovative, low-cost endoscope that employs a brushless DC motor for scanning, and a sensorless technique for triggering and synchronizing OCT imaging with the scanning motor. This sensorless approach uses the motor's electrical feedback (back electromotive force, BEMF) as a virtual Hall sensor to initiate OCT image acquisition and synchronize it with a Fourier Domain Mode-Locked (FDML)-based Megahertz OCT system. Notably, the implementation of BEMF-triggered OCT has led to a substantial reduction in image jitter and NURD (<4 mrad), thereby opening up a new window for real-time visualization capabilities. This approach suggests potential benefits across various applications, aiming to provide a more accurate, deployable, and cost-effective solution. Subsequent studies can explore the adaptability of this system to specific clinical scenarios and its performance under practical endoscopic conditions.
Collapse
|
2
|
In Vivo Intravascular Optical Coherence Tomography (IVOCT) Structural and Blood Flow Imaging Based Mechanical Simulation Analysis of a Blood Vessel. Cardiovasc Eng Technol 2022; 13:685-698. [PMID: 35112317 DOI: 10.1007/s13239-022-00608-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 01/04/2022] [Indexed: 01/27/2023]
Abstract
INTRODUCTION Computer modelling of blood vessels based on biomedical imaging provides important hemodynamic and biomechanical information for vascular disease studies and diagnosis. However due to lacking well-defined physiological blood flow profiles, the accuracy of the simulation results is often not guaranteed. Flow velocity profiles of a specific cross section of a blood vessel were obtained by in vivo Doppler intravascular optical coherence tomography (IVOCT) lately. However due to the influence of the catheter, the velocity profile imaged by IVOCT can't be applied to simulation directly. METHODS A simulation-experiment combined method to determine the inlet flow boundary based on in vivo porcine carotid Doppler IVOCT imaging is proposed. A single conduit carotid model was created from the 3D IVOCT structural images using an image processing-computer aided design combined method. RESULTS With both high- resolution arterial model and near physiological blood flow profile, stress analysis by fluid-structure interaction and computational fluid dynamics were performed. The influence of the catheter to the wall shear stress, the hemodynamics and the stresses of the carotid wall under the measured inlet flow and various outlet pressure boundary conditions, are analyzed. CONCLUSION This study provides a solution to the difficulty of getting inlet flow boundary for numerical simulation of arteries. It paves the way for developing IVOCT based vascular stress analysis and imaging methods for the studies and diagnosis of vascular diseases.
Collapse
|
3
|
Wang T, Pfeiffer T, Akyildiz A, van Beusekom HMM, Huber R, van der Steen AFW, van Soest G. Intravascular optical coherence elastography. BIOMEDICAL OPTICS EXPRESS 2022; 13:5418-5433. [PMID: 36425628 PMCID: PMC9664873 DOI: 10.1364/boe.470039] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/30/2022] [Accepted: 08/31/2022] [Indexed: 05/07/2023]
Abstract
Optical coherence elastography (OCE), a functional extension of optical coherence tomography (OCT), visualizes tissue strain to deduce the tissue's biomechanical properties. In this study, we demonstrate intravascular OCE using a 1.1 mm motorized catheter and a 1.6 MHz Fourier domain mode-locked OCT system. We induced an intraluminal pressure change by varying the infusion rate from the proximal end of the catheter. We analysed the pixel-matched phase change between two different frames to yield the radial strain. Imaging experiments were carried out in a phantom and in human coronary arteries in vitro. At an imaging speed of 3019 frames/s, we were able to capture the dynamic strain. Stiff inclusions in the phantom and calcification in atherosclerotic plaques are associated with low strain values and can be distinguished from the surrounding soft material, which exhibits elevated strain. For the first time, circumferential intravascular OCE images are provided side by side with conventional OCT images, simultaneously mapping both the tissue structure and stiffness.
Collapse
Affiliation(s)
- Tianshi Wang
- Thoraxcentre, Erasmus University Medical Centre, Rotterdam 3015 AA, The Netherlands
| | - Tom Pfeiffer
- Institut für Biomedizinische Optik, Universität zu Lübeck, Lübeck 23562, Germany
| | - Ali Akyildiz
- Thoraxcentre, Erasmus University Medical Centre, Rotterdam 3015 AA, The Netherlands
- Department of Biomechanical Engineering, Delft University of Technology, Delft 2600 AA, The Netherlands
| | | | - Robert Huber
- Institut für Biomedizinische Optik, Universität zu Lübeck, Lübeck 23562, Germany
| | - Antonius F. W. van der Steen
- Thoraxcentre, Erasmus University Medical Centre, Rotterdam 3015 AA, The Netherlands
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518005, China
- Department of Imaging Science and Technology, Delft University of Technology, Delft 2600 AA, The Netherlands
| | - Gijs van Soest
- Thoraxcentre, Erasmus University Medical Centre, Rotterdam 3015 AA, The Netherlands
| |
Collapse
|
4
|
Ma F, Dai C, Meng J, Li Y, Zhao J, Zhang Y, Wang S, Zhang X, Cheng R. Classification-based framework for binarization on mice eye image in vivo with optical coherence tomography. JOURNAL OF BIOPHOTONICS 2022; 15:e202100336. [PMID: 35305080 DOI: 10.1002/jbio.202100336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 02/27/2022] [Accepted: 03/16/2022] [Indexed: 06/14/2023]
Abstract
Optical coherence tomography (OCT) angiography has drawn much attention in the medical imaging field. Binarization plays an important role in quantitative analysis of eye with optical coherence tomography. To address the problem of few training samples and contrast-limited scene, we proposed a new binarization framework with specific-patch SVM (SPSVM) for low-intensity OCT image, which is open and classification-based framework. This new framework contains two phases: training model and binarization threshold. In the training phase, firstly, the patches of target and background from few training samples are extracted as the ROI and the background, respectively. Then, PCA is conducted on all patches to reduce the dimension and learn the eigenvector subspace. Finally, the classification model is trained from the features of patches to get the target value of different patches. In the testing phase, the learned eigenvector subspace is conducted on the pixels of each patch. The binarization threshold of patch is obtained with the learned SVM model. We acquire a new OCT mice eye (OCT-ME) database, which is publicly available at https://mip2019.github.io/spsvm. Extensive experiments were performed to demonstrate the effectiveness of the proposed SPSVM framework.
Collapse
Affiliation(s)
- Fei Ma
- School of Computer Science, Qufu Normal University, Shandong, China
| | - Cuixia Dai
- College Science, Shanghai Institute of Technology, Shanghai, China
| | - Jing Meng
- School of Computer Science, Qufu Normal University, Shandong, China
| | - Ying Li
- School of Computer Science, Qufu Normal University, Shandong, China
| | - Jingxiu Zhao
- School of Computer Science, Qufu Normal University, Shandong, China
| | - Yuanke Zhang
- School of Computer Science, Qufu Normal University, Shandong, China
| | - Shengbo Wang
- School of Computer Science, Qufu Normal University, Shandong, China
| | - Xueting Zhang
- School of Computer Science, Qufu Normal University, Shandong, China
| | - Ronghua Cheng
- School of Computer Science, Qufu Normal University, Shandong, China
| |
Collapse
|
5
|
Deen AD, Van Beusekom HMM, Pfeiffer T, Stam M, Kleijn DD, Wentzel J, Huber R, Van Der Steen AFW, Soest GV, Wang T. Spectroscopic thermo-elastic optical coherence tomography for tissue characterization. BIOMEDICAL OPTICS EXPRESS 2022; 13:1430-1446. [PMID: 35414978 PMCID: PMC8973171 DOI: 10.1364/boe.447911] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 01/15/2022] [Accepted: 01/17/2022] [Indexed: 06/14/2023]
Abstract
Optical imaging techniques that provide free space, label free imaging are powerful tools in obtaining structural and biochemical information in biological samples. To date, most of the optical imaging technologies create images with a specific contrast and require multimodality integration to add additional contrast. In this study, we demonstrate spectroscopic Thermo-elastic Optical Coherence Tomography (TE-OCT) as a potential tool in tissue identification. TE-OCT creates images based on two different forms of contrast: optical reflectance and thermo-elastic deformation. TE-OCT uses short laser pulses to induce thermo-elastic tissue deformation and measures the resulting surface displacement using phase-sensitive OCT. In this work we characterized the relation between thermo-elastic displacement and optical absorption, excitation, fluence and illumination area. The experimental results were validated with a 2-dimensional analytical model. Using spectroscopic TE-OCT, the thermo-elastic spectra of elastic phantoms and tissue components in coronary arteries were extracted. Specific tissue components, particularly lipid, an important biomarker for identifying atherosclerotic lesions, can be identified in the TE-OCT spectral response. As a label-free, free-space, dual-contrast, all-optical imaging technique, spectroscopic TE-OCT holds promise for biomedical research and clinical pathology diagnosis.
Collapse
Affiliation(s)
- Aaron Doug Deen
- Department of Cardiology, Erasmus University Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands
| | - Heleen M. M. Van Beusekom
- Department of Cardiology, Erasmus University Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands
| | - Tom Pfeiffer
- Institut für Biomedizinische Optik, Universität zu Lübeck, Peter-Monnik-Weg 4, 23562 Lübeck, Germany
| | - Mathijs Stam
- Department of Cardiology, Erasmus University Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands
| | - Dominique De Kleijn
- University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Jolanda Wentzel
- Department of Cardiology, Erasmus University Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands
| | - Robert Huber
- Institut für Biomedizinische Optik, Universität zu Lübeck, Peter-Monnik-Weg 4, 23562 Lübeck, Germany
| | - Antonius F. W. Van Der Steen
- Department of Cardiology, Erasmus University Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055 Shenzhen, China
- Department Imaging Science and Technology, Delft University of Technology, Delft 2600 AA, The Netherlands
| | - Gijs Van Soest
- Department of Cardiology, Erasmus University Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands
| | - Tianshi Wang
- Department of Cardiology, Erasmus University Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands
| |
Collapse
|
6
|
Pakdaman Zangabad R, Iskander-Rizk S, van der Meulen P, Meijlink B, Kooiman K, Wang T, van der Steen AFW, van Soest G. Photoacoustic flow velocity imaging based on complex field decorrelation. PHOTOACOUSTICS 2021; 22:100256. [PMID: 33868919 PMCID: PMC8040274 DOI: 10.1016/j.pacs.2021.100256] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/16/2021] [Accepted: 02/21/2021] [Indexed: 05/18/2023]
Abstract
Photoacoustic (PA) imaging can be used to monitor flowing blood inside the microvascular and capillary bed. Ultrasound speckle decorrelation based velocimetry imaging was previously shown to accurately estimate blood flow velocity in mouse brain (micro-)vasculature. Translating this method to photoacoustic imaging will allow simultaneous imaging of flow velocity and extracting functional parameters like blood oxygenation. In this study, we use a pulsed laser diode and a quantitative method based on normalized first order field autocorrelation function of PA field fluctuations to estimate flow velocities in an ink tube phantom and in the microvasculature of the chorioallantoic membrane of a chicken embryo. We demonstrate how the decorrelation time of signals acquired over frames are related to the flow speed and show that the PA flow analysis based on this approach is an angle independent flow velocity imaging method.
Collapse
Affiliation(s)
- Reza Pakdaman Zangabad
- Biomedical Engineering, Department of Cardiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Sophinese Iskander-Rizk
- Biomedical Engineering, Department of Cardiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Pim van der Meulen
- Department of Microelectronics, Delft University of Technology, Delft, The Netherlands
| | - Bram Meijlink
- Biomedical Engineering, Department of Cardiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Klazina Kooiman
- Biomedical Engineering, Department of Cardiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tianshi Wang
- Biomedical Engineering, Department of Cardiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Antonius F W van der Steen
- Biomedical Engineering, Department of Cardiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Imaging Science and Physics, Delft University of Technology, Delft, The Netherlands
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Gijs van Soest
- Biomedical Engineering, Department of Cardiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| |
Collapse
|