Frequency Domain Imaging Research Articles

Extended Kalman filtering for enhancing a cyclic pattern-updating scheme of single-pixel dynamic fluorescence spatial frequency domain imaging.

A single-pixel imaging technique applied to fluorescence spatial frequency domain imaging (f-SFDI) brings many positive benefits, but its low frame rate will also lead to severe quantitative degradation when dynamically imaging a vibrant target. This work presents a novel, to the best of our knowledge, single-pixel imaging approach that combines the extended Kalman filtering (EKF) and a cyclic one-pattern updating for an enhanced dynamic f-SFDI. The cyclic one-pattern updating scheme enables the dynamic imaging at a high frame rate, and on this basis, the imaging process of an intensity temporally varying target (assuming no structure motion in the scene) is dynamically modelled, and accordingly, the surface intensities and images at each sampling time point simultaneously estimated via the EKF. Simulation and phantom validations demonstrate that the method can improve the quantitative accuracy of the results. An in vivo experiment performed on two mice for dynamic monitoring of photosensitizer doses in a photodynamic therapy further demonstrates the clinical feasibility of the proposed method.

Damage localization using acoustic emission sensors via convolutional neural network and continuous wavelet transform

Due to aging structures, deterioration is becoming an essential issue in the engineering and facility management industry. Especially for nuclear power plants, the deterioration of structures could be directly related to safety issues. One of the popular methods for localizing damage such as cracks in nuclear power plants in the early stage is using acoustic emission sensors. The conventional methods for localizing damage using the acoustic emission sensor include methods such as time of arrival, time difference of arrival, and received signal strength indicator measurements. However, the conventional methods have large errors especially when the material is not homogeneous, or the propagation path of signals is non-straight. In this study, we propose a new deep learning-based damage localization method using acoustic emission sensors to automate the damage localization process and improve accuracy. First, the signals from acoustic emission sensors were collected and transformed into time–frequency domain images using continuous wavelet transform. Next, the convolutional neural networks were designed to localize the damage using the continuous wavelet transform images as the input. Finally, the trained convolutional neural networks were used to estimate the location or coordinates of damages. To validate the performance of the proposed method, experimental tests were conducted in the concrete panel and cube with artificially generated damages. The results express that the proposed method is effective and progressive.

FRI606 Changes In The Pedal Microcirculation Of Diabetic Patients With Poor Glycemic Control Detected Using Non Invasive Optical Imaging

Abstract Disclosure: I.K. Bolakale-Rufai: None. S. French: None. J.C. Arias: None. K. Concha-Moore: None. T. Tan: None. D.G. Armstrong: None. A. Mazhar: Employee; Self; Modulim. C.C. Weinkauf: None. Background: Microvascular disease (MVD) describes systemic changes in the small vessels (∼100 υm diameter) that impair tissue oxygenation and perfusion. Emerging evidence has shown that MVD (which is prevalent in diabetics) is clinically relevant as it synergistically acts with peripheral arterial disease to increase the risk of limb loss by 22.7-fold. Poor glycemic control has been linked to clinical microvascular disease (nephropathy and retinopathy) However, the direct impact of poor glycemic control on the microcirculation of the feet is unknown as there are currently no standardized non-invasive methods used clinically to assess and quantify MVD of the lower limbs. Spatial frequency domain imaging (SFDI) is a novel non-invasive optical technology that can detect and quantify microvascular disease of the foot by measuring the amount of hemoglobin(HbT1) in the capillaries of the superficial dermis up to 1-2mm deep and oxygenation (StO2) in the dermal micro-circulation. We hypothesize that poor glycemic control in DM affects pedal microcirculation and the changes can be detected using the SFDI technology. Methods: 307 patients (600 lower extremity limbs) were prospectively enrolled at a single institution, Banner University Medicine, Tucson, AZ from 2016- 2023. Diabetic patients were stratified into three groups based on their HbA1c level: ≤6.7%, 6.8-9.9%, and ≥10%. Mann U Whitney test and Spearman rank correlation were used in testing the association between HbA1C and SFDI-metrics with p<.05 considered as statistical significance. Results: We included 230 lower limbs belonging to diabetic patients. The mean age of the patients was 61.7 years. Clinical neuropathy and retinopathy were found in 79% and 30.7% of patients, respectively. SFDI-derived biomarkers of microcirculation were compared among diabetics categorized by HbA1C levels. We observed a significant reduction in papillary dermal perfusion (HbT1) as the glycemic control (HbA1C) of the patients worsened (p<0.001). Although tissue oxygenation (StO2) was not statistically different across diabetic groups, the St02/HbT1 ratio which represents the ratio of tissue oxygenation to perfusion, increased with elevated HbA1C levels. This indicated that poorly controlled diabetics had less oxygen being extracted from their poorly perfused micro-circulation. Conclusions: This study suggests that poor glycemic control directly affects the microcirculation of the feet in diabetic patients. The SFDI technology is a promising noninvasive tool to evaluate microvascular disease of the feet and potentially may be utilized clinically to stratify diabetic patients at risk for foot ulceration or limb loss based on glycemic control over time. Presentation: Friday, June 16, 2023

TCT-136 Optical Frequency Domain Imaging Versus Intravascular Ultrasound in Percutaneous Coronary Intervention in Patients With Acute Coronary Syndrome: Primary Result From the OPINION ACS Trial

TCT-136 Optical Frequency Domain Imaging Versus Intravascular Ultrasound in Percutaneous Coronary Intervention in Patients With Acute Coronary Syndrome: Primary Result From the OPINION ACS Trial

Evaluation of the thickness of coronary calcium by 60-MHz intravascular ultrasound: head-to-head comparison with optical frequency domain imaging.

The region behind the coronary calcium could not be visualized by intravascular ultrasound (IVUS) because of acoustic shadow. However, some pathological studies have shown that IVUS delineated the vessel border behind thin coronary calcium sheets. This study aimed to reveal whether recent IVUS can visualize the region behind thin coronary calcium sheets. Using 534 cross-sectional optical frequency domain images (OFDI), including severe calcified coronary lesions, calcium sheet thickness was measured by every 1°. Accordingly, the visibility of the vessel border behind the coronary calcium sheet was evaluated using 60-MHz IVUS images, which were longitudinally linked with OFDI ones. After carefully coordinating with the axial position, the association between the IVUS-derived permeability of the coronary calcium sheet and calcium thickness was evaluated. The maximum and mean calcium thickness by OFDI was 0.88 ± 0.39 and 0.62 ± 0.30mm, respectively. By 60-MHz IVUS, 12.1% of the coronary calcium sheets had permeable segments. Comparing between OFDI and IVUS images, 48.6% of the coronary calcium sheets with maximum thickness ≤ 0.3mm were sometimes permeable by 60-MHz IVUS, whereas most > 0.5mm thick calcium sheets were impermeable. In the receiver operating characteristic curve analysis, the best cutoff values for the maximum and mean thickness of permeable calcium were 0.48 and 0.31mm, respectively. Thus, 60-MHz IVUS can occasionally visualize the region behind a thin coronary calcium sheet. When using 60-MHz IVUS, this finding may be a predictive marker of calcium sheet with a thickness of < 0.5mm.

Generic and Model-Based Calibration Method for Spatial Frequency Domain Imaging with Parameterized Frequency and Intensity Correction.

Spatial frequency domain imaging (SFDI) is well established in biology and medicine for non-contact, wide-field imaging of optical properties and 3D topography. Especially for turbid media with displaced, tilted or irregularly shaped surfaces, the reliable quantitative measurement of diffuse reflectance requires efficient calibration and correction methods. In this work, we present the implementation of a generic and hardware independent calibration routine for SFDI setups based on the so-called pinhole camera model for both projection and detection. Using a two-step geometric and intensity calibration, we obtain an imaging model that efficiently and accurately determines 3D topography and diffuse reflectance for subsequently measured samples, taking into account their relative distance and orientation to the camera and projector, as well as the distortions of the optical system. Derived correction procedures for position- and orientation-dependent changes in spatial frequency and intensity allow the determination of the effective scattering coefficient μs' and the absorption coefficient μa when measuring a spherical optical phantom at three different measurement positions and at nine wavelengths with an average error of 5% and 12%, respectively. Model-based calibration allows the characterization of the imaging properties of the entire SFDI system without prior knowledge, enabling the future development of a digital twin for synthetic data generation or more robust evaluation methods.

Multi-Label Fault Diagnosis of Rotary Machine via Domain Adversarial Neural Network-Based Domain Generalization Targeting High Range Rotating Speed

Research on deep learning has been increasing in recent years in the field of fault diagnosis in rotary machine. However, compared to training data, real world data is collected from different system conditions and environments. Therefore, real world data has different datadistribution and various noise with the training data, leading to domain shift between data. Due to the problem mentioned above, deep learning often fails to apply on industrial data.Domain generalization is an emerging deep learning technique to generalize domain discrepancy. In this study, domain adversarial neural network (DANN)-based domaingeneralization is proposed for multi-label fault diagnosis of rotary machine. Frequency domain image data were generated via implementing short time fourier transform(STFT) to the sensor data collected from the test rig. Then, the features are utilized as training data to diagnosis multi-label fault via DANN-based domain generalization. Moreover, the upper boundary of rotating speed domain of the rotary machine where domain generalization can effectively diagnosis multi-label fault is suggested.

Importance of optimal rewiring guided by 3-dimensional optical frequency domain imaging during double-kissing culotte stenting demonstrated through a novel bench model

The usefulness of optical frequency domain imaging (OFDI) guidance on two-stenting at left main bifurcation has not been evaluated. Here, we used a novel bench model to investigate whether pre-defined optimal rewiring with OFDI-guidance decreases acute incomplete stent apposition (ISA) at the left main bifurcation segment. A novel bench simulation system was developed to simulate the foreshortening and overlapping of daughter vessels as well as left main bifurcation motion under fluoroscopy. Double-kissing (DK) culotte stenting was performed using the novel bench model under fluoroscopy with or without OFDI-guidance. In the OFDI-guidance group, if the guidewire did not pass through the pre-defined optimal cell according to the 3-dimensional OFDI, additional attempts of rewiring into the jailed side branch were performed. The success rate of optimal jailed side branch rewiring after implantation of the first and second stent under OFDI-guidance was significantly higher than that under only angio-guidance. After completion of the DK-culotte stenting, the incidence and volume of ISA at the bifurcation segment in the OFDI-guidance group was significantly lower than that in the angio-guidance group. Online 3-dimensional OFDI-guided DK-culotte stenting according to a pre-defined optimal rewiring point might be superior to only angio-guided rewiring for reducing ISA at the bifurcation.

Diabetic Foot Ulcer Imaging: An Overview and Future Directions.

Diabetic foot ulcers (DFUs) affect one in every three people with diabetes. Imaging plays a vital role in objectively complementing the gold-standard visual yet subjective clinical assessments of DFUs during the wound treatment process. Herein, an overview of the various imaging techniques used to image DFUs is summarized. Conventional imaging modalities (e.g., computed tomography, magnetic resonance imaging, positron emission tomography, single-photon emitted computed tomography, and ultrasound) are used to diagnose infections, impact on the bones, foot deformities, and blood flow in patients with DFUs. Transcutaneous oximetry is a gold standard to assess perfusion in DFU cases with vascular issues. For a wound to heal, an adequate oxygen supply is needed to facilitate reparative processes. Several optical imaging modalities can assess tissue oxygenation changes in and around the wounds apart from perfusion measurements. These include hyperspectral imaging, multispectral imaging, diffuse reflectance spectroscopy, near-infrared (NIR) spectroscopy, laser Doppler flowmetry or imaging, and spatial frequency domain imaging. While perfusion measurements are dynamically monitored at point locations, tissue oxygenation measurements are static two-dimensional spatial maps. Recently, we developed a spatio-temporal NIR-based tissue oxygenation imaging approach to map for the extent of asynchrony in the oxygenation flow patterns in and around DFUs. Researchers also measure other parameters such as thermal maps, bacterial infections (from fluorescence maps), pH, collagen, and trans-epidermal water loss to assess DFUs. A future direction for DFU imaging would ideally be a low-cost, portable, multi-modal imaging platform that can provide a visual and physiological assessment of wounds for comprehensive wound care intervention and management.

Profile-based diffuse reflectance corrections for improved optical property measurement of spherical fruit with spatial frequency domain imaging

Diffuse reflectance (Rd), demodulated from spatial frequency domain imaging (SFDI), is strongly influenced by the surface profile of target sample, and the optical properties (absorption coefficient μa and reduced scattering coefficient μ's) extracted from the Rd are prone to large estimation errors caused by curved surface of the fruit. This study proposes a profile-based Rd correction method, aiming to improve the accuracy of optical property measurement for spherical fruit, such as apples, as well as enhance fruit bruise detection through improved optical properties. Firstly, the surface height of the test object was obtained by performing the phase-measuring profilometry (PMP) in SFDI. Secondly, the object surface reflection angle was calculated using the proposed angle calculation method for spherical samples. The Modified Lambertian Correction (MLC) method was then refined to minimize the effect of the incident angle on the Rd correction. The performance of the Rd correction method was validated using standard reflector and Teflon spheres. The results showed that the average error of the PMP measurement with the height range of 0–50 mm was within 1 mm, the relative error of the corrected Rd was within 2 %, and the standard deviation of the Rd for the Teflon sphere was reduced by about 60 % after correction. Finally, the proposed Rd correction method was applied to measure the optical properties of four spherical fruit (‘Golden Delicious’, ‘Red Fuji’ apples, lemons, and oranges). The results revealed that the standard deviations of the measured μa and μ's of the spherical fruit were greatly reduced by about 70 % and 40 % after correction. The improved optical property mappings enhanced the early bruise detection of apples due to the fact that the optical property contrast between the non-bruised and bruised tissues were significantly increased.

Painterly Image Harmonization in Dual Domains

Image harmonization aims to produce visually harmonious composite images by adjusting the foreground appearance to be compatible with the background. When the composite image has photographic foreground and painterly background, the task is called painterly image harmonization. There are only few works on this task, which are either time-consuming or weak in generating well-harmonized results. In this work, we propose a novel painterly harmonization network consisting of a dual-domain generator and a dual-domain discriminator, which harmonizes the composite image in both spatial domain and frequency domain. The dual-domain generator performs harmonization by using AdaIN modules in the spatial domain and our proposed ResFFT modules in the frequency domain. The dual-domain discriminator attempts to distinguish the inharmonious patches based on the spatial feature and frequency feature of each patch, which can enhance the ability of generator in an adversarial manner. Extensive experiments on the benchmark dataset show the effectiveness of our method. Our code and model are available at https://github.com/bcmi/PHDNet-Painterly-Image-Harmonization.

CWAN: Self-supervised learning for deep grape disease image composition

Grape leaf diseases seriously affect grape yield and directly lead to the loss of the industrial economy. An accurate diagnosis is crucial for effective spraying and control. Presently, the combination of image blending and a deep recognition model is the most effective method for accurately identifying grape leaf diseases. Existing methods of image blending depend primarily on single-channel and multi-scale channel blending, computing and optimizing the Poisson equation, and the iterative optimization of learning-based methods for simple composite results. Although these methods have had some success, they are not able to simultaneously address lesion and leaf gap size, color bleeding, and edge smoothness. In this paper, we propose a novel image blending method named cascade wavelet attention network (CWAN). Specifically, CWAN consists of a cascade wavelet attention (CWA) and a blending autoencoder. First, we build a CWA to decompose the image into a multi-level and multi-scale frequency domain image. Then, the detailed features of the source and target domains are extracted, and the edges are smoothed. Following this, a shared decoder is designed to fuse these features in the corresponding frequency-domain layers, and the result serves as the attention feature. Finally, we design a blending autoencoder with a feature fusion mechanism to seamlessly blend lesions and leaves enhanced by CWA. We also construct a weighted blended loss function to avoid leaf color infiltration into the lesion in the blended image. Comprehensive experiments on two grape leaf disease datasets. Qualitative and quantitative results demonstrate the superiority and effectiveness of our model.

Spatial frequency domain imaging for the assessment of scleroderma skin involvement.

Systemic sclerosis (SSc) is an autoimmune disease characterized by the widespread deposition of excess collagen in the skin and internal organs, as well as vascular dysfunction. The current standard of care technique used to quantify the extent of skin fibrosis in SSc patients is the modified Rodnan skin score (mRSS), which is an assessment of skin thickness based on clinical palpation. Despite being considered the gold standard, mRSS testing requires a trained physician and suffers from high inter-observer variability. In this study, we evaluated the use of spatial frequency domain imaging (SFDI) as a more quantitative and reliable method for assessing skin fibrosis in SSc patients. SFDI is a wide-field and non-contact imaging technique that utilizes spatially modulated light to generate a map of optical properties in biological tissue. The SFDI data were collected at six measurement sites (left and right forearms, hands, and fingers) of eight control subjects and ten SSc patients. mRSS were assessed by a physician, and skin biopsies were collected from subject's forearms and used to assess for markers of skin fibrosis. Our results indicate that SFDI is sensitive to skin changes even at an early stage, as we found a significant difference in the measured optical scattering () between healthy controls and SSc patients with a local mRSS score of zero (no appreciable skin fibrosis by gold standard). Furthermore, we found a strong correlation between the diffuse reflectance (Rd) at a spatial frequency of 0.2 mm-1 and the total mRSS between all subjects (Spearman correlation coefficient = -0.73, p-value < 0.0028), as well as high correlation with histology results. The healthy volunteer results show excellent inter- and intra-observer reliability (ICC > 0.8). Our results suggest that the measurement of tissue and Rd at specific spatial frequencies and wavelengths can provide an objective and quantitative assessment of skin involvement in SSc patients, which could greatly improve the accuracy and efficiency of monitoring disease progression and evaluating drug efficacy.

A Comparison of Spectroscopy and Imaging Techniques Utilizing Spectrally Resolved Diffusely Reflected Light for Intraoperative Margin Assessment in Breast-Conserving Surgery: A Systematic Review and Meta-Analysis.

Up to 19% of patients require re-excision surgery due to positive margins in breast-conserving surgery (BCS). Intraoperative margin assessment tools (IMAs) that incorporate tissue optical measurements could help reduce re-excision rates. This review focuses on methods that use and assess spectrally resolved diffusely reflected light for breast cancer detection in the intraoperative setting. Following PROSPERO registration (CRD42022356216), an electronic search was performed. The modalities searched for were diffuse reflectance spectroscopy (DRS), multispectral imaging (MSI), hyperspectral imaging (HSI), and spatial frequency domain imaging (SFDI). The inclusion criteria encompassed studies of human in vivo or ex vivo breast tissues, which presented data on accuracy. The exclusion criteria were contrast use, frozen samples, and other imaging adjuncts. 19 studies were selected following PRISMA guidelines. Studies were divided into point-based (spectroscopy) or whole field-of-view (imaging) techniques. A fixed-or random-effects model analysis generated pooled sensitivity/specificity for the different modalities, following heterogeneity calculations using the Q statistic. Overall, imaging-based techniques had better pooled sensitivity/specificity (0.90 (CI 0.76-1.03)/0.92 (CI 0.78-1.06)) compared with probe-based techniques (0.84 (CI 0.78-0.89)/0.85 (CI 0.79-0.91)). The use of spectrally resolved diffusely reflected light is a rapid, non-contact technique that confers accuracy in discriminating between normal and malignant breast tissue, and it constitutes a potential IMA tool.

Designing and simulating realistic spatial frequency domain imaging systems using open-source 3D rendering software.

Spatial frequency domain imaging (SFDI) is a low-cost imaging technique that maps absorption and reduced scattering coefficients, offering improved contrast for important tissue structures such as tumours. Practical SFDI systems must cope with various imaging geometries including imaging planar samples ex vivo, imaging inside tubular lumen in vivo e.g. for endoscopy, and measuring tumours or polyps of varying morphology. There is a need for a design and simulation tool to accelerate design of new SFDI systems and simulate realistic performance under these scenarios. We present such a system implemented using open-source 3D design and ray-tracing software Blender that simulates media with realistic absorption and scattering in a wide range of geometries. By using Blender's Cycles ray-tracing engine, our system simulates effects such as varying lighting, refractive index changes, non-normal incidence, specular reflections and shadows, enabling realistic evaluation of new designs. We first demonstrate quantitative agreement between Monte-Carlo simulated absorption and reduced scattering coefficients with those simulated from our Blender system, achieving discrepancy in absorption coefficient and in reduced scattering coefficient. However, we then show that using an empirically derived look-up table the errors reduce to and respectively. Next, we simulate SFDI mapping of absorption, scattering and shape for simulated tumour spheroids, demonstrating enhanced contrast. Finally we demonstrate SFDI mapping inside a tubular lumen, which highlighted a important design insight: custom look-up tables must be generated for different longitudinal sections of the lumen. With this approach we achieved absorption error and scattering error. We anticipate our simulation system will aid in the design of novel SFDI systems for key biomedical applications.

Intrinsic, widefield optical imaging of hemodynamics in rodent models of Alzheimer's disease and neurological injury.

The complex cerebrovascular network is critical to controlling local cerebral blood flow (CBF) and maintaining brain homeostasis. Alzheimer's disease (AD) and neurological injury can result in impaired CBF regulation, blood-brain barrier breakdown, neurovascular dysregulation, and ultimately impaired brain homeostasis. Measuring cortical hemodynamic changes in rodents can help elucidate the complex physiological dynamics that occur in AD and neurological injury. Widefield optical imaging approaches can measure hemodynamic information, such as CBF and oxygenation. These measurements can be performed over fields of view that range from millimeters to centimeters and probe up to the first few millimeters of rodent brain tissue. We discuss the principles and applications of three widefield optical imaging approaches that can measure cerebral hemodynamics: (1)optical intrinsic signal imaging, (2)laser speckle imaging, and (3)spatial frequency domain imaging. Future work in advancing widefield optical imaging approaches and employing multimodal instrumentation can enrich hemodynamic information content and help elucidate cerebrovascular mechanisms that lead to the development of therapeutic agents for AD and neurological injury.

Model for the diffuse reflectance in spatial frequency domain imaging.

In spatial frequency domain imaging (SDFI), tissue is illuminated with sinusoidal intensity patterns at different spatial frequencies. For low spatial frequencies, the reflectance is diffuse and a model derived by Cuccia etal. (doi 10.1117/1.3088140) is commonly used to extract optical properties. An improved model resulting in more accurate optical property extraction could lead to improved diagnostic algorithms. To develop a model that improves optical property extraction for the diffuse reflectance in SFDI compared to the model of Cuccia etal. We derive two analytical models for the diffuse reflectance, starting from the theoretical radial reflectance for a pencil-beam illumination under the partial current boundary condition (PCBC) and the extended boundary condition (EBC). We compare both models and the model of Cuccia etal. to Monte Carlo simulations. The model based on the PCBC resulted in the lowest errors, improving median relative errors compared to the model of Cuccia etal. by 45% for the reflectance, 10% for the reduced scattering coefficient and 64% for the absorption coefficient. For the diffuse reflectance in SFDI, the model based on the PCBC provides more accurate results than the currently used model by Cuccia etal.

Prediction of the debulking effect of rotational atherectomy using optical frequency domain imaging: a prospective study

This study determined the predictive accuracy of optical frequency domain imaging (OFDI) on debulking effects of rotational atherectomy (RA) and compared the predictive accuracy of OFDI catheter-based with Rota wire-based prediction methods. This prospective, single-center, observational study included 55 consecutive patients who underwent OFDI-guided RA. On pre-RA OFDI images, a circle, identical to the Rota burr was drawn at the center of the OFDI catheter (OFDI catheter-based prediction method) or wire (wire-based prediction method). The area overlapping the vessel wall was defined as the predicted ablation area (P-area). The actual ablated area (A-area) was measured by superimposing the OFDI images before and after RA. The overlapping P-area and A-area were defined as overlapped ablation area (O-area), and the predictive accuracy was evaluated by %Correct area (O-area/P-area) and %Error area (A-area − O-area/A-area). The median %Correct and %Error areas were 47.8% and 41.6%, respectively. Irrelevant ablation (low %Correct-/high % Error areas) and over ablation (high %Correct-/high % Error areas) were related to deep vessel injury and intimal flap outside the P-area. The predictive accuracy was better in the OFDI catheter-based prediction method than the wire-based prediction method in the cross sections where the OFDI catheter and wire came in contact. However, it was better in the latter than the former where the OFDI catheter and wire were not in contact. OFDI-based simulation of the RA effect is feasible though accuracy may be affected by the OFDI catheter and wire position. OFDI-based simulation of RA effect might reduce peri-procedural complications during RA.

Ultrasonic imaging of damage in plates in spectral ripple frequency domain

The ultrasonic C-scan method is a well-known non-destructive inspection method which typically analyzes ultrasound echoes in time domain. Although demonstrated for a variety of defects and materials, it has certain challenges in correctly assessing complex and distributed defects in multi-layer heterogeneous materials, e.g. barely visible impact damage in composite laminates.This paper proposes a C-scan imaging technique in the spectral ripple frequency domain by exploiting interference phenomena between multiple ultrasonic echoes in the response signal. The spectral ripple frequency domain imaging method processes the full A-scan signal without having to define an evaluation time gate. As such, it is highly suited for inspection of curved or tilted parts, or parts having different thickness sections. The method is demonstrated on several 5.5 mm thick carbon fiber reinforced polymer laminates with barely visible impact damage, revealing its capability to resolve neighboring delaminations and small defect fragments over the entire depth of the sample. The spectral ripple frequency domain imaging method shows good performance on datasets with high noise levels and/or low sampling rates, and is computationally very efficient, allowing real-time defect imaging.

The Height and Mobility of Protruding Plaque After Carotid Artery Stenting Are Associated with Postoperative Ischemic Lesions.

Tissue protrusion (TP) is a possible cause of cerebral infarction after carotid artery stenting (CAS). Using optical frequency domain imaging (OFDI) and angioscopy, we investigated the relationship between the morphological features of TP and postoperative new ischemic lesions on magnetic resonance imaging (MRI)-diffusion weighted imaging (DWI) after CAS. Fifty patients who underwent CAS and subsequent poststenting intravascular evaluation using both OFDI and angioscopy were included. CAS was performed for proximal protection via the femoral artery approach, and intravascular evaluation with OFDI and angioscopy were performed after stent placement. We compared the background and poststenting intravascular findings between patients with and without postoperative new ischemic lesions on MRI-DWI. TP was observed in 42 patients (84%), and postoperative new ischemic lesions on MRI-DWI were observed in 32 patients (64%). The frequency of TP did not differ between the 2 groups, but the height of TP was higher in the DWI-positive group (0.62mm vs. 0.29mm, P=0.0028), and mobile TP was observed only in the DWI-positive group. The height of TP (P= 0.023) was an independent predictor of new periprocedural ischemic brain lesions after CAS, and its cut-off value for mobility was 0.55mm on the receiver operating characteristic curve (area under the curve, 0.93). The height of TP on OFDI and mobile-TP on angioscopy after CAS were associated with postoperative new ischemic lesions on MRI-DWI. The intravascular evaluation using OFDI and angioscopy could be helpful for a detailed evaluation of TP.