Frequency Domain Imaging Research Articles

Successful stent-less treatment of acute myocardial infarction using an excimer laser combined with long inflation using perfusion balloon: Findings of optical frequency domain imaging.

Successful stent-less treatment of acute myocardial infarction using an excimer laser combined with long inflation using perfusion balloon: Findings of optical frequency domain imaging.

The Vascular Response After Balloon Angioplasty of Infrapopliteal Intermediate Stenosis Evaluated by Optical Frequency Domain Imaging.

We often experience worsening of stenosis by balloon angioplasty of infrapopliteal (IP) lesion compared with the initial stenosis. However, reports on this phenomenon are limited. The main purpose of this study is to evaluate vascular response after balloon angioplasty of IP artery stenosis. Thirteen patients (15 arteries) who underwent endovascular treatment (EVT) and follow-up angiography with optical frequency domain imaging (OFDI) of intermediate IP stenosis were included. Serial OFDI images at 3 time points (before and after EVT and at follow-up) were analyzed. Diameter and area of external elastic lamina, internal elastic lamina, and lumen were measured, and plaque area and plaque burden (PB) were calculated. PB before EVT was classified into mild, moderate, and severe by 0%-20%, 21%-40%, and 41%-60%, respectively. Analyzed were 229 cross sections. External elastic lamina diameter did not change significantly among three time points (3.8 ± 0.5 [95% confidence interval (CI): 3.7 to 3.9] mm, 3.9 ± 0.4 [95% CI: 3.8 to 4.0] mm, 3.9 ± 0.4 [95% CI: 3.8 to 4.0] mm, p = 0.06). Lumen area increased after EVT but became smaller at follow-up than before EVT (4.5 ± 1.5 [95% CI: 4.3 to 4.7] mm2, 5.3 ± 1.3 [95% CI: 5.1 to 5.5] mm2, 3.7 ± 1.2 [95% CI: 3.5 to 3.9] mm2, p < 0.001). Plaque area became smaller after EVT and larger at follow-up than before EVT (3.0 ± 1.7 [95% CI: 2.8 to 3.2] mm2, 2.4 ± 1.5 [95% CI: 2.2 to 2.6] mm2, 4.0 ± 1.6 [95% CI: 3.8 to 4.2] mm2, p < 0.001). Lumen area was significantly smaller at follow-up than before EVT in mild and moderate PB groups, but it was not different in severe PB group (mild PB group: 5.1 ± 1.5 [95% CI: 4.7 to 5.5] mm2 vs. 4.0 ± 1.3 [95% CI: 3.7 to 4.3] mm2, p < 0.001, moderate PB group: 4.6 ± 1.3 [95% CI: 4.4 to 4.8] mm2 vs. 3.6 ± 1.2 [95% CI: 3.4 to 3.8] mm2, p < 0.001, severe PB group: 3.0 ± 1.4 [95% CI: 2.5 to 3.5] mm2 vs. 3.1 ± 1.0 [95% CI: 2.7 to 3.5] mm2, p = 0.93). Balloon angioplasty of intermediate IP artery stenosis with mild or moderate PB led to smaller lumen area at follow-up than before EVT.

Abstract 4136597: Atherosclerotic plaque healing as a marker of plaque vulnerability: Insight from intracoronary polarization-sensitive optical frequency domain imaging

Background: Collagen is the major extracellular matrix that imparts mechanical strength to fibrous caps covering fibroatheromas. Intracoronary polarimetry with polarization-sensitive (PS) optical frequency domain imaging (OFDI) measures polarization properties, such as birefringence and depolarization (Figure 1). Birefringence is elevated in collagen and collagen-synthesizing smooth muscle cells, while depolarization is increased by the presence of macrophages and lipid/necrotic cores. Purpose: This study aimed to investigate polarimetric signatures of coronary lesions with healed coronary plaques (HCP) in patients with ACS and chronic coronary syndrome (CCS). Furthermore, we aimed to investigate diagnostic value for birefringence and depolarization of ACS culprit lesions discriminating from CCS target lesions. Methods: We conducted a single center prospective registry of intracoronary PS-OFDI imaging in patients with coronary artery disease (n = 50). A total of 862 OFDI frames selected from culprit or target lesions were analyzed. Coronary plaque phenotypes were assessed using conventional OFDI imaging. HCP was defined as plaques with one or more layers of different optical density and a clear demarcation from underlying components on intensity images. Birefringence and depolarization of the newer intima was measured in cross-sectional images. Birefringence and depolarization of ACS- and CCS-lesions were compared using a generalized estimating equation model. Receiver operating characteristic (ROC) analysis was used to investigate the diagnostic performance of polarimetric signatures for identifying ACS-lesions. Results: Compared to CCS-lesions, ACS-lesions featured significantly higher lipid-burden index and maximum lipid arc (both p &lt; 0.05). Compared to the CCS-lesions, ACS-lesions exhibited significantly lower birefringence (p &lt; 0.05) and higher depolarization (p &lt; 0.05). In the ROC analysis for differentiating ACS-lesions from CCS-lesions, area under the curves (AUC) for birefringence and depolarization were 0.712 and 0.672, respectively. In the multivariable ROC analysis in diagnosing ACS lesions, combination of birefringence with depolarization improved the AUC to 0.755 (p ＝ 0.025). Conclusions: Intracoronary polarimetry provides quantitative assessment of plaque composition in patients. Further research is warranted to investigate whether birefringence can serve as a marker of healing failure following plaque rupture and erosion.

Polarimetry terahertz imaging of human breast cancer surgical specimens.

We investigate terahertz (THz) polarimetry imaging of seven human breast cancer surgical specimens. The goal is to enhance image contrast between adjacent tissue types of cancer, healthy collagen, and fat in excised breast tumors. Based on the biological perception of random growth of cancer and invasion of surrounding healthy tissues in the breast, we hypothesize that cancerous cells interact with the THz electric field in a different manner compared with healthy cells. This difference can be best captured using multiple polarizations instead of single polarization. Time domain pulsed signals are experimentally collected from each pixel of the specimen in horizontal-horizontal, vertical-horizontal, vertical-vertical, and horizontal-vertical polarizations. The time domain pulses are transformed to the frequency domain to obtain the power spectra and 16 Mueller matrix images. The whole-slide pathology imaging was used to interpret and label all images. The results of the cross and co-polarization power spectrum images demonstrated a strong dependency on the tissue orientation with respect to the emitted and detected electric fields. At the 130-deg rotation angle of the scanned samples, the detector showed the strongest reflected signal in cross-polarization. Furthermore, the Mueller matrix images consistently demonstrated patterns in fresh and block tissues confirming the differentiation between tissue types in breast tumor specimens. THz polarimetry imaging shows a potential for improving image contrast in excised tumor tissues compared with single polarization imaging. Cross-polarization signals demonstrated smaller amplitudes compared with co-polarized signals. However, averaging the signal during measurements has tremendously improved the image. Furthermore, in post-processing, averaging the frequency domain images and the Mueller matrix elements with respect to frequency has led to better image contrast. Some patterns in the Mueller matrix images were difficult to interpret leading to the necessity of more investigation of the Mueller matrix and its physiological interpretation of breast tumor tissues.

Concrete crack classification based on fourier image enhancement and convolutional neural network

This paper investigates the application of Fourier image enhancement combined with Convolutional Neural Networks (CNNs) for detecting cracks in concrete structures. Fourier enhancement is used to preprocess crack images, improving their clarity and reducing noise, which in turn enhances the performance of the CNN in accurately classifying cracks. The results demonstrate that this combination improves the classification accuracy, with the enhanced images achieving a higher accuracy compared to non-enhanced images. Additionally, the study examines the effects of this preprocessing on CNN training time. However, accuracy varies depending on the dataset used, with one dataset reaching a maximum accuracy of 95% after enhancement. These findings highlight the potential of using frequency-domain image enhancement techniques in conjunction with deep learning models for structural health monitoring.

A Survey On Image Registration Techniques Using FFT

Image Registration is the process of straightening two or more images of the same scene with testimonial to a particular image. The images are captured from various sensors at different times and at multiple viewpoints. Thus, to get a better picture of any change of a scene/object over a considerable period of time image registration is important. Image registration finds application in medical sciences, remote sensing and in computer vision. This paper presents a detailed review of several approaches which are classified accordingly along with their contributions and drawbacks. The main steps of an image registration procedure are also discussed. Different performance measures are presented that determine the registration quality and accuracy. The scope for the future research are presented as well. Applications based on Fast Fourier Transform (FFT) such as signal and image processing require high computational power, plus the ability to experiment with algorithms. Reconfigurable hardware devices in the form of Field Programmable Gate Arrays (FPGAs) have been proposed as a way of obtaining high performance at an economical price. At present, however, users must program FPGAs at a very low level and have a detailed knowledge of the architecture of the device being used. To try to reconcile the dual requirements of high performance and ease of development, this paper reports on the design and realization of a High-Level framework for the implementation of 1-D and 2-D FFTs for real-time applications. Results show that the parallel implementation of 2-D FFT achieves virtually linear speed-up and real-time performance for large matrix sizes. Finally, an FPGA-based parametrizable environment based on the developed parallel 2-D FFT architecture is presented as a solution for frequency domain image filtering application

Deep learning-enabled fluorescence imaging for surgical guidance: in silico training for oral cancer depth quantification.

Oral cancer surgery requires accurate margin delineation to balance complete resection with post-operative functionality. Current in vivo fluorescence imaging systems provide two-dimensional margin assessment yet fail to quantify tumor depth prior to resection. Harnessing structured light in combination with deep learning (DL) may provide near real-time three-dimensional margin detection. A DL-enabled fluorescence spatial frequency domain imaging (SFDI) system trained with in silico tumor models was developed to quantify the depth of oral tumors. A convolutional neural network was designed to produce tumor depth and concentration maps from SFDI images. Three in silico representations of oral cancer lesions were developed to train the DL architecture: cylinders, spherical harmonics, and composite spherical harmonics (CSHs). Each model was validated with in silico SFDI images of patient-derived tongue tumors, and the CSH model was further validated with optical phantoms. The performance of the CSH model was superior when presented with patient-derived tumors ( ). The CSH model could predict depth and concentration within 0.4mm and , respectively, for in silico tumors with depths less than 10mm. A DL-enabled SFDI system trained with in silico CSH demonstrates promise in defining the deep margins of oral tumors.

Single snapshot spatial frequency domain imaging with synchronous 3D profile correction.

We have proposed a novel single-snapshot spatial frequency domain imaging method with synchronous three-dimensional (3D) profile correction that addresses the confounding effects of involuntary jitter in tissue under examination and the 3D profile of the tissue on the measurements of optical parameters during in vivo examinations. I. In this scheme, orthogonal composite sinusoidal modulated light is projected onto the tissue to be measured. The single-snapshot multi-frequency demodulation theory, combined with the different sensitivity of different directional fringes to heights, simultaneously recovers the 3D profile and the modulated diffuse reflectance of the tissue to be measured. Finally, the modulated diffuse reflectance is corrected by establishing the correction function of height and angle versus modulated diffuse reflectance, and the optical parameters of the tissue are inverted by the diffusion model. The accuracy of the 3D profile measurement of the scheme was verified using models with different morphologies, and the mean value of the measurement error was found to be lower than 3%. The accuracy of modulation diffuse reflectance measurement was verified using a hemispherical homogeneous phantom made of PTFE. After correction with this method, the standard deviation of the measured diffuse reflectance is reduced by up to 72.2%. Finally, the measurement effect of optical parameters is verified by in vivo experiments and compared with the standard three-phase method. The results demonstrated that the 3D-SSMD method exhibits enhanced stability and efficiency. This introduces an innovative technology for achieving real-time spatial frequency domain imaging, applicable in clinical settings.

Monte Carlo simulation of spatial frequency domain imaging for breast tumors during compression.

Near-infrared optical imaging methods have shown promise for monitoring response to neoadjuvant chemotherapy (NAC) for breast cancer, with endogenous contrast coming from oxy- and deoxyhemoglobin. Spatial frequency domain imaging (SFDI) could be used to detect this contrast in a low-cost and portable format, but it has limited imaging depth. It is possible that local tissue compression could be used to reduce the effective tumor depth. To evaluate the potential of SFDI for therapy response prediction, we aim to predict how changes to tumor size, stiffness, and hemoglobin concentration would be reflected in contrast measured by SFDI under tissue compression. Finite element analysis of compression on an inclusion-containing soft material is combined with Monte Carlo simulation to predict the measured optical contrast. When the effect of compression on blood volume is not considered, contrast gain from compression increases with the size and stiffness of the inclusion and decreases with the inclusion depth. With a model of reduction of blood volume from compression, compression reduces imaging contrast, an effect that is greater for larger inclusions and stiffer inclusions at shallower depths. This computational modeling study represents a first step toward tracking tumor changes induced by NAC using SFDI and local compression.

Enhanced peripheral tissue oxygenation and hemoglobin concentration after a high-fat meal measured with spatial frequency domain imaging

Enhanced peripheral tissue oxygenation and hemoglobin concentration after a high-fat meal measured with spatial frequency domain imaging

Using spatial frequency domain imaging to monitor a skin biopsy wound: a pilot study.

Surgical wound infection is a global postoperative issue adding a significant clinical burden and increasing healthcare costs. Early detection and subsequent diagnosis of infection is vital for accurate, early, and effective treatments. In this paper, we report a pilot study exploring spatial frequency domain imaging (SFDI) to monitor, in-vivo, a biopsy wound in human skin. The reduced scattering coefficient, , absorption coefficient, and the oxygen saturation, StO 2, were measured using a SFDI system at 617 and 850 nm. We found the was better capable of monitoring structural changes, possible pus within the wound, re-epithelialization, and collagen fiber remodeling, than with the eye alone. The map is capable of revealing the total hemoglobin distribution in the wound area but was limited in some regions due to the scab covering. This case study indicates SFDI's potential for monitoring and quantifying the process of surgical wound healing and infection.

Impact of scattering phase function and polarization on the accuracy of diffuse and sub-diffuse spatial frequency domain imaging.

Although spatial frequency domain imaging (SFDI) has been well characterized under diffuse optical conditions, tissue measurements made outside the diffuse regime can provide new diagnostic information. Before such measurements can become clinically relevant, however, the behavior of sub-diffuse SFDI and its effect on the accuracy of derived tissue parameters must be assessed. We aim to characterize the impact that both the assumed scattering phase function (SPF) and the polarization state of the illumination light source have on the accuracy of SFDI-derived optical properties when operating under diffuse or sub-diffuse conditions, respectively. Through the use of a set of well-characterized optical phantoms, SFDI accuracy was assessed at four wavelengths (395, 545, 625, and 850nm) and two different spatial frequencies (0.3 and ), which provided a broad range of diffuse and sub-diffuse conditions, using three different SPFs. To determine the effects of polarization, the SFDI accuracy was assessed using both unpolarized and cross-polarized illumination. It was found that the assumed SPF has a direct and significant impact on the accuracy of the SFDI-derived optical properties, with the best choice of SPF being dictated by the polarization state. As unpolarized SFDI retains the sub-diffuse portion of the signal, optical properties were found to be more accurate when using the full SPF that includes forward and backscattering components. By contrast, cross-polarized SFDI yielded accurate optical properties when using a forward-scattering SPF, matching the behavior of cross-polarization to attenuate the immediate backscattering of sub-diffuse reflectance. Using the correct pairings of SPF and polarization enabled using a reflectance standard, instead of a more subjective phantom, as the reference measurement. These results provide the foundation for a more thorough understanding of SFDI and enable new applications of this technology in which sub-diffuse conditions dominate (e.g., ) or high spatial frequencies are required.

Optical frequency domain imaging-guided versus intravascular ultrasound-guided percutaneous coronary intervention for acute coronary syndromes: the OPINION ACS randomised trial.

The clinical benefits of optical frequency domain imaging (OFDI)-guided percutaneous coronary intervention (PCI) for acute coronary syndrome (ACS) remain unclear. We sought to compare intravascular ultrasound (IVUS)- and OFDI-guided PCI in patients with ACS. OPINION ACS is a multicentre, prospective, randomised, non-inferiority trial that compared OFDI-guided PCI with IVUS-guided PCI using current-generation drug-eluting stents in ACS patients (n=158). The primary endpoint was in-stent minimum lumen area (MLA), assessed using 8-month follow-up OFDI. Patients presented with ST-segment elevation myocardial infarction (55%), non-ST-segment elevation myocardial infarction (29%), or unstable angina pectoris (16%). PCI procedural success was achieved in all patients, with comparably low periprocedural complications rates in both groups. Immediately after PCI, the minimum stent area (p=0.096) tended to be smaller for OFDI versus IVUS guidance. Proximal stent edge dissection (p=0.012) and irregular protrusion (p=0.03) were significantly less frequent in OFDI-guided procedures than in IVUS-guided procedures. Post-PCI coronary flow, assessed using corrected Thrombolysis in Myocardial Infarction frame counts, was significantly better in the OFDI-guided group than in the IVUS-guided group (p<0.001). The least squares mean (95% confidence interval [CI]) in-stent MLA at 8 months was 4.91 (95% CI: 4.53-5.30) mm2 and 4.76 (95% CI: 4.35-5.17) mm2 in the OFDI- and IVUS-guided groups, respectively, demonstrating the non-inferiority of OFDI guidance (pnon-inferiority<0.001). The average neointima area tended to be smaller in the OFDI-guided group. The frequency of major adverse cardiac events was similar. Among ACS patients, OFDI-guided PCI and IVUS-guided PCI were equally safe and feasible, with comparable in-stent MLA at 8 months. OFDI guidance may be a potential option in ACS patients. This study was registered in the Japan Registry of Clinical Trials (jrct.niph.go.jp: jRCTs052190093).

Soybean seed pest damage detection method based on spatial frequency domain imaging combined with RL-SVM

Soybean seeds are susceptible to damage from the Riptortus pedestris, which is a significant factor affecting the quality of soybean seeds. Currently, manual screening methods for soybean seeds are limited to visual inspection, making it difficult to identify seeds that are phenotypically defect-free but have been punctured by stink bugs on the sub-surface. To facilitate the convenient and efficient identification of healthy soybean seeds, this paper proposes a soybean seed pest detection method based on spatial frequency domain imaging combined with RL-SVM. Firstly, soybean optical data is obtained using single integration sphere technique, and the vigor index of soybean seeds is obtained through germination experiments. Then, based on the above two data items using feature extraction algorithms (the successive projections algorithm and the competitive adaptive reweighted sampling algorithm), the characteristic wavelengths of soybeans are identified. Subsequently, the spatial frequency domain imaging technique is used to obtain the sub-surface images of soybean seeds in a forward manner, and the optical coefficients such as the reduced scattering coefficient μ′s\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\mu }{\\prime}}_{s}$$\\end{document} and absorption coefficient μa\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mu }_{a}$$\\end{document} of soybean seeds are inverted. Finally, RL-MLR, RL-GRNN, and RL-SVM prediction models are established based on the ratio of the area of insect-damaged sub-surface to the entire seed, soybean varieties, and μa\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mu }_{a}$$\\end{document} at three wavelengths (502 nm, 813 nm, and 712 nm) for predicting and identifying soybean the stinging and sucking pest damage levels of soybean seeds. The experimental results show that the spatial frequency domain imaging technique yields small errors in the optical coefficients of soybean seeds, with errors of less than 15% for μa\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mu }_{a}$$\\end{document} and less than 10% for μ′s\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\mu }{\\prime}}_{s}$$\\end{document}. After parameter adjustment through reinforcement learning, the Macro-Recall metrics of each model have improved by 10%-15%, and the RL-SVM model achieves a high Macro-Recall value of 0.9635 for classifying the pest damage levels of soybean seeds.

A modified spatial frequency domain imaging configuration with reduced speckle noise images

A modified spatial frequency domain imaging configuration with reduced speckle noise images

Crack detection method for concrete surface based on feature fusion

In recent years, detection methods based on deep learning have received widespread attention in the field of concrete crack detection. In view of the shortcomings of traditional image detection methods, a concrete crack detection method based on feature fusion is proposed. The Fourier frequency domain processed image is used as the input of the deep learning neural network. The original time domain image and the frequency domain image are respectively input into two feature extraction modules to extract high-level features, and then the two features are fused to fully characterize the characteristics of the time domain and frequency domain, and finally the concrete crack detection results of the feature fusion are obtained. The performance of the proposed method is compared with VGG-16, AlexNet and DenseNet. Experiments show that the accuracy of the proposed method is higher than VGG-16, AlexNet and DenseNet. The proposed method has good results in concrete crack detection. To verify the generalization ability of the proposed model, the Concrete Crack Images for Classification data set was input into the proposed model for testing. The experimental results show that the proposed model has good generalization ability.

Multimodal optical imaging of the oculofacial region using a solid tissue-simulating facial phantom.

Spatial frequency domain imaging (SFDI) applies patterned near-infrared illumination to quantify the optical properties of subsurface tissue. The periocular region is unique due to its complex ocular adnexal anatomy. Although SFDI has been successfully applied to relatively flat in vivo tissues, regions that have significant height variations and curvature may result in optical property inaccuracies. We characterize the geometric impact of the periocular region on SFDI imaging reliability. SFDI was employed to measure the reduced scattering coefficient ( ) and absorption coefficient ( ) of the periocular region in a cast facial tissue-simulating phantom by capturing images along regions of interest (ROIs): inferior temporal quadrant (ITQ), inferior nasal quadrant (INQ), superior temporal quadrant (STQ), central eyelid margin (CEM), rostral lateral nasal bridge (RLNB), and forehead (FH). The phantom was placed on a chin rest and imaged nine times from an "en face" or "side profile" position, and the flat back of the phantom was measured 15 times. The measured and of a cast facial phantom are accurate when comparing the ITQ, INQ, STQ, and FH to its flat posterior surface. Paired tests of ITQ, INQ, STQ, and FH and concluded that there is not enough evidence to suggest that imaging orientation impacted the measurement accuracy. Regions of extreme topographical variation, i.e., CEM and RLNB, did exhibit differences in measured optical properties. We are the first to evaluate the geometric implications of wide-field imaging along the periocular region using a solid tissue-simulating facial phantom. Results suggest that the ITQ, INQ, STQ, and FH of a generalized face have minimal impact on the SFDI measurement accuracy. Areas with heightened topographic variation exhibit measurement variability. Device and facial positioning do not appear to bias measurements. These findings confirm the need to carefully select ROIs when measuring optical properties along the periocular region.

Optical frequency domain imaging (OFDI) represents a novel technique for the diagnosis of giant cell arteritis

Background/ObjectivesGiant cell arteritis (GCA) is an inflammatory vascular disease in which prompt and accurate diagnosis is critical. The efficacy of temporal artery biopsy (TAB) is limited by ‘skip’ lesions and a delay in histological analysis. This first-in-man ex-vivo study aims to assess the accuracy of optical frequency domain imaging (OFDI) in diagnosing GCA.Subjects/Methods29 TAB samples of patients with suspected GCA were submerged in 0.9% sodium chloride and an OFDI catheter was passed through the lumen to create cross-sectional images prior to histological analysis. The specimens were then preserved in formalin for histological examination. Mean intimal thickness (MIT) on OFDI was measured, and the presence of both multinucleate giant cells (MNGCs) and fragmentation of the internal elastic lamina (FIEL) was assessed and compared with histology, used as the diagnostic gold standard.ResultsMIT in patients with/without histological evidence of GCA was 0.425 mm (±0.43) and 0.13 mm (±0.06) respectively compared with 0.215 mm (±0.09) and 0.135 mm (±0.07) on OFDI. MIT measured by OFDI was significantly higher in patients with histologically diagnosed arteritis compared to those without (p = 0.0195). For detecting FIEL and MNGCs, OFDI had a sensitivity of 75% and 28.6% and a specificity of 100% and 77.3% respectively. Applying diagnostic criteria of MIT > 0.20 mm, or the presence of MNGCs or FIEL, the sensitivity of detecting histological arteritis using OFDI was 91.4% and the specificity 94.1%.ConclusionsOFDI provided rapid imaging of TAB specimens achieving a diagnostic accuracy comparable to histological examination. In-vivo imaging may allow imaging of a longer arterial section.

Innovative methodology for noninvasive spatial mapping of gold nanoparticle distribution in tissues: potential applications in biomedical imaging and therapy

Gold nanoparticles (AuNPs) have emerged as versatile agents in biomedical applications, particularly for enhancing contrast in tagged biological tissues for tumor imaging and diagnostics due to their strong absorption cross-section. In this study, we present a methodology for quantifying the spatial distribution of AuNPs within superficial tissue volumes. Utilizing silicone tissue phantoms as a background medium and spatial frequency domain imaging (SFDI) to measure the tissues’ optical properties, we constructed a lookup table (LUT) to infer the optical properties of embedded AuNPs with varying spatial concentrations and depths across multiple spatial frequencies. An analytical solution derived from the LUT facilitated the determination of embedded NP concentration in-depth as a function of measured spatial frequency-dependent optical absorption. Notably, SFDI enabled the spatial localization of NPs in three dimensions. These findings lay the foundation for future in vivo studies on mapping NPs and hold significant promise for advancing biomedical imaging techniques.

An efficient sub-aperture millimeter-wave imaging technique based on boundary-type MIMO array

Millimeter-wave (MMW) 3-D imaging based on multiple-input-multiple-output (MIMO) radar has been widely studied due to its unique advantages in human security screening. However, more research has been done on the use of scanning 1-D MIMO array and the fast imaging methods that match them. This limits the rate of data acquisition and imaging speed to some extent. It is necessary to study frame rate imaging system as well as efficient imaging methods. In this article, a boundary-type MIMO array is designed, based on which an efficient frequency-domain imaging algorithm with sub-aperture is proposed. The proposed algorithm solves the target reflectivity function by dividing the uniform array into two sub-apertures and solving the echo signals of each sub-aperture separately. The final target reflectivity function is obtained by superposing all the solutions. Compared with the advanced RMA, FSA and FωK algorithms, the proposed sub-aperture frequency-domain imaging algorithm (SFA) does not require a large amount of zero-padding to satisfy the requirements of fast Fourier transform (FFT) in all dimensions. It greatly improves the speed of imaging and saves the space required for computation. We derive the theoretical formulation of SFA applied to MIMO array and analyze its computational complexity and phase error. Simulation and experiment verify the efficiency of the proposed SFA.