Spatial Frequency Domain Imaging Research Articles

GMOPNet: A GAN-MLP two-stage network for optical properties measurement of kiwifruit and peaches with spatial frequency domain imaging

Spatial frequency domain imaging (SFDI) is an imaging technique using spatially modulated illumination for measurement of optical properties. Conventional SFDI methods require capturing at least six images, making it time-consuming. This study presents a Generative Adversarial Network-Multi-Layer Perceptron (GAN-MLP) two-stage network (GMOPNet) for extracting high-precision optical properties of kiwifruit and peaches from a single SFDI image, enabling real-time continuous wide-band SFDI. The GMOPNet we proposed leverages the GAN to predict diffuse reflectance, followed by the MLP with Monte Carlo prior knowledge to predict optical properties. Our method achieves mean absolute percentage errors (MAPE) of 5.91 % for the absorption coefficient (μa) and 5.23 % for the reduced scattering coefficient (μs′), reducing acquisition and processing time significantly, with single inference taking 31.13 ms. The MAPE of the μa and the μs′ were 6.73 % and 6.34 % for kiwifruit and 5.80 % and 6.65 % for peaches, respectively.

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 real-time 3D profile correction

Single snapshot spatial frequency domain imaging with real-time 3D profile correction

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.

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

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.

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.

Multi-frequency spatial frequency domain imaging: a depth-resolved optical scattering model to isolate scattering contrast in thin layers of skin.

Current methods for wound healing assessment rely on visual inspection, which gives qualitative information. Optical methods allow for quantitative non-invasive measurements of optical properties relevant to wound healing. Spatial frequency domain imaging (SFDI) measures the absorption and reduced scattering coefficients of tissue. Typically, SFDI assumes homogeneous tissue; however, layered structures are present in skin. We evaluate a multi-frequency approach to process SFDI data that estimates depth-specific scattering over differing penetration depths. Multi-layer phantoms were manufactured to mimic wound healing scattering contrast in depth. An SFDI device imaged these phantoms and data were processed according to our multi-frequency approach. The depth sensitive data were then compared with a two-layer scattering model based on light fluence. The measured scattering from the phantoms changed with spatial frequency as our two-layer model predicted. The performance of two models solutions for SFDI was consistently better than the standard diffusion approximation. We presented an approach to process SFDI data that returns depth-resolved scattering contrast. This method allows for the implementation of layered optical models that more accurately represent physiologic parameters in thin tissue structures as in wound healing.

MicroRNA-155 mediates multiple gene regulations pertinent to the role of human adipose-derived mesenchymal stem cells in skin regeneration.

Introduction: The role of Adipose-derived mesenchymal stem cells (AD-MSCs) in skin wound healing remains to be fully characterized. This study aims to evaluate the regenerative potential of autologous AD-MSCs in a non-healing porcine wound model, in addition to elucidate key miRNA-mediated epigenetic regulations that underlie the regenerative potential of AD-MSCs in wounds. Methods: The regenerative potential of autologous AD-MSCs was evaluated in porcine model using histopathology and spatial frequency domain imaging. Then, the correlations between miRNAs and proteins of AD-MSCs were evaluated using an integration analysis in primary human AD-MSCs in comparison to primary human keratinocytes. Transfection study of AD-MSCs was conducted to validate the bioinformatics data. Results: Autologous porcine AD-MSCs improved wound epithelialization and skin properties in comparison to control wounds. We identified 26 proteins upregulated in human AD-MSCs, including growth and angiogenic factors, chemokines and inflammatory cytokines. Pathway enrichment analysis highlighted cell signalling-associated pathways and immunomodulatory pathways. miRNA-target modelling revealed regulations related to genes encoding for 16 upregulated proteins. miR-155-5p was predicted to regulate Fibroblast growth factor 2 and 7, C-C motif chemokine ligand 2 and Vascular cell adhesion molecule 1. Transfecting human AD-MSCs cell line with anti-miR-155 showed transient gene silencing of the four proteins at 24h post-transfection. Discussion: This study proposes a positive miR-155-mediated gene regulation of key factors involved in wound healing. The study represents a promising approach for miRNA-based and cell-free regenerative treatment for difficult-to-heal wounds. The therapeutic potential of miR-155 and its identified targets should be further explored in-vivo.

Spatial frequency domain imaging combining profile correction enables accurate real-time quantitative mapping of optical properties of apples

Spatial frequency domain imaging technology enables non-contact, wide-field quantitative analysis of optical properties in strong turbid media, thereby enhancing bruise detection in fruits based on changes in optical property values. However, precise and real-time measurement of the optical properties of curved biological materials is challenging due to the significant influence of tissue contours. This paper primarily presents a research study on real-time correction method based on the property that DC component diffuse reflectance (Rd_DC) and AC component diffuse reflectance (Rd_AC) are influenced by the contour trend of the tissue in a similar manner. The aim of this method is to eliminate the significant impact of sample contour angle on demodulation and enhance the detection of apple bruise. Sinusoidal illumination at a spatial frequency of 0.2 mm−1 was projected at 730 nm, with the experiments carried out on standard reflector, polytetrafluoroethylene sphere, and non-bruised and bruised apples. The results showed that, the relative error of the planar standard reflector decreased from the maximum value of 52.85–4.74%. The median of the Rd_AC for the polytetrafluoroethylene spherical standard, which fluctuated between 0.6 and 0.8, was corrected to the theoretical value of 1. For normal apples, the maximum fluctuation in the standard deviation of Rd_AC, after median filtering, reduced from 172.94% at 300×300 pixels to 18.69%. The boxplot of Rd_AC for bruised apples became smaller, with the lower fence being corrected from nearly 0–0.1750, which closely matched the theoretical value of 0.17. Additionally, the correlation of reduced scattering coefficient (μs′) in the ideal region of interest (100×100 pixels) remained at 0.9785 before and after correction, while other areas were corrected, making the bruising more pronounced. The correction method did not require additional experiments, with the consumed time in millisecond level.

Deep-learning approach to stratified reconstructions of tissue absorption and scattering in time-domain spatial frequency domain imaging.

The conventional optical properties (OPs) reconstruction in spatial frequency domain (SFD) imaging, like the lookup table (LUT) method, causes OPs aliasing and yields only average OPs without depth resolution. Integrating SFD imaging with time-resolved (TR) measurements enhances space-TR information, enabling improved reconstruction of absorption () and reduced scattering () coefficients at various depths. To achieve the stratified reconstruction of OPs and the separation between and , using deep learning workflow based on the temporal and spatial information provided by time-domain SFD imaging technique, while enhancing the reconstruction accuracy. Two data processing methods are employed for the OPs reconstruction with TR-SFD imaging, one is full TR data, and the other is the featured data extracted from the full TR data (, continuous-wave component, , mean time of flight). We compared their performance using a series of simulation and phantom validations. Compared to the LUT approach, utilizing full TR, and datasets yield high-resolution OPs reconstruction results. Among the three datasets employed, full TR demonstrates the optimal accuracy. Utilizing the data obtained from SFD and TR measurement techniques allows for achieving high-resolution separation reconstruction of and at different depths within 5mm.

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

This publisher's note contains a correction to Opt. Lett.48, 5443 (2023)10.1364/OL.495099.

Wide-field illumination diffuse optical tomography within a framework of single-pixel time-domain spatial frequency domain imaging.

We present a wide-field illumination time-domain (TD) diffusion optical tomography (DOT) for three-dimensional (3-D) reconstruction within a shallow region under the illuminated surface of the turbid medium. The methodological foundation is laid on the single-pixel spatial frequency domain (SFD) imaging that facilitates the adoption of the well-established time-correlated single-photon counting (TCSPC)-based TD detection and generalized pulse spectrum techniques (GPST)-based reconstruction. To ameliorate the defects of the conventional diffusion equation (DE) in the forward modeling of TD-SFD-DOT, mainly the low accuracy in the near-field region and in profiling early-photon migration, we propose a modified model employing the time-dependent δ-P1 approximation and verify its improved accuracy in comparison with both the Monte Carlo and DE-based ones. For a simplified inversion process, a modified GPST approach is extended to TD-SFD-DOT that enables the effective separation of the absorption and scattering coefficients using a steady-state equivalent strategy. Furthermore, we set up a single-pixel TD-SFD-DOT system that employs the TCSPC-based TD detection in the SFD imaging framework. For assessments of the reconstruction approach and the system performance, phantom experiments are performed for a series of scenarios. The results show the effectiveness of the proposed methodology for rapid 3-D reconstruction of the absorption and scattering coefficients within a depth range of about 5 mean free pathlengths.

Ultra-miniature dual-wavelength spatial frequency domain imaging for micro-endoscopy.

There is a need for a cost-effective, quantitative imaging tool that can be deployed endoscopically to better detect early stage gastrointestinal cancers. Spatial frequency domain imaging (SFDI) is a low-cost imaging technique that produces near-real time, quantitative maps of absorption and reduced scattering coefficients, but most implementations are bulky and suitable only for use outside the body. We aim to develop an ultra-miniature SFDI system comprising an optical fiber array (diameter 0.125mm) and a micro camera ( package) to displace conventionally bulky components, in particular, the projector. First, we fabricated a prototype with an outer diameter of 3mm, although the individual component dimensions could permit future packaging to a diameter. We developed a phase-tracking algorithm to rapidly extract images with fringe projections at three equispaced phase shifts to perform SFDI demodulation. To validate the performance, we first demonstrate comparable recovery of quantitative optical properties between our ultra-miniature system and a conventional bench-top SFDI system with an agreement of 15% and 6% for absorption and reduced scattering, respectively. Next, we demonstrate imaging of absorption and reduced scattering of tissue-mimicking phantoms providing enhanced contrast between simulated tissue types (healthy and tumour), done simultaneously at wavelengths of 515 and 660nm. Using a support vector machine classifier, we estimate that sensitivity and specificity values of are feasible for detecting simulated squamous cell carcinoma. This device shows promise as a cost-effective, quantitative imaging tool to detect variations in optical absorption and scattering as indicators of cancer.

Motion-resistant three-wavelength spatial frequency domain imaging system with ambient light suppression using an 8-tap CMOS image sensor.

We present a motion-resistant three-wavelength spatial frequency domain imaging (SFDI) system with ambient light suppression using an 8-tap complementary metal-oxide semiconductor (CMOS) image sensor (CIS) developed at Shizuoka University. The system addresses limitations in conventional SFDI systems, enabling reliable measurements in challenging imaging scenarios that are closer to real-world conditions. Our study demonstrates a three-wavelength SFDI system based on an 8-tap CIS. We demonstrate and evaluate the system's capability of mitigating motion artifacts and ambient light bias through tissue phantom reflectance experiments and in vivo volar forearm experiments. We incorporated the Hilbert transform to reduce the required number of projected patterns per wavelength from three to two per spatial frequency. The 8-tap image sensor has eight charge storage diodes per pixel; therefore, simultaneous image acquisition of eight images based on multi-exposure is possible. Taking advantage of this feature, the sensor simultaneously acquires images for planar illumination, sinusoidal pattern projection at three wavelengths, and ambient light. The ambient light bias is eliminated by subtracting the ambient light image from the others. Motion artifacts are suppressed by reducing the exposure and projection time for each pattern while maintaining sufficient signal levels by repeating the exposure. The system is compared to a conventional SFDI system in tissue phantom experiments and then in vivo measurements of human volar forearms. The 8-tap image sensor-based SFDI system achieved an acquisition rate of 9.4 frame sets per second, with three repeated exposures during each accumulation period. The diffuse reflectance maps of three different tissue phantoms using the conventional SFDI system and the 8-tap image sensor-based SFDI system showed good agreement except for high scattering phantoms. For the in vivo volar forearm measurements, our system successfully measured total hemoglobin concentration, tissue oxygen saturation, and reduced scattering coefficient maps of the subject during motion (16.5cm/s) and under ambient light (28.9lx), exhibiting fewer motion artifacts compared with the conventional SFDI. We demonstrated the potential for motion-resistant three-wavelength SFDI system with ambient light suppression using an 8-tap CIS.

Quantifying tissue properties and absolute hemodynamics using coherent spatial imaging.

Measuring hemodynamic function is crucial for health assessment. Optical signals provide relative hemoglobin concentration changes, but absolute measurements require costly, bulky technology. Speckleplethysmography (SPG) uses coherent light to detect speckle fluctuations. Combining SPG with multispectral measurements may provide important physiological information on blood flow and absolute hemoglobin concentration. To develop an affordable optical technology to measure tissue absorption, scattering, hemoglobin concentrations, tissue oxygen saturation (), and blood flow. We integrated reflectance spectroscopy and laser speckle imaging to create coherent spatial imaging (CSI). CSI was validated against spatial frequency domain imaging (SFDI) using phantom-based measurements. In vivo arterial and venous occlusion experiments compared CSI with diffuse optical spectroscopy/diffuse correlation spectroscopy (DOS/DCS) measurements. CSI and SFDI agreed on tissue absorption and scattering in phantom tests. CSI and DOS/DCS showed similar trends and agreement in arterial occlusion results. During venous occlusion, both uncorrected and corrected blood flow decreased with increasing pressure, with an difference in overall blood flow decrease between the methods. CSI and DOS/DCS data showed expected hemoglobin concentrations, , and blood flow trends. CSI provides affordable and comprehensive hemodynamic information. It can potentially detect dysfunction and improve measurements, such as blood pressure, , and metabolism.