Dynamic time domain near-infrared optical tomography based on a SPAD camera

Imaging Cerebral Blood Vessels Using Near-Infrared Optical Tomography: A Simulation Study

Cerebral veins have received increasing attention due to their importance in preoperational planning and the brain oxygenation measurement. There are different modalities to image those vessels, such as magnetic resonance angiography (MRA) and recently, contrast-enhanced (CE) 3D gradient-echo sequences. However, the current techniques have certain disadvantages, i.e., the long examination time, the requirement of contrast agents or inability to measure oxygenation. Near-infrared optical tomography (NIROT) is emerging as a viable new biomedical imaging modality that employs near infrared light (650-950 nm) to image biological tissue. It was proven to easily penetrate the skull and therefore enables the brain vessels to be assessed. NIROT utilizes safe non-ionizing radiation and can be applied in e.g., early detection of neonatal brain injury and ischemic strokes. The aim is to develop non-invasive label-free dynamic time domain (TD) NIROT to image the brain vessels. A simulation study was performed with the software (NIRFAST) which models light propagation in tissue with the finite element method (FEM). Both a simple shape mesh and a real head mesh including all the segmented vessels from MRI images were simulated using both FEM and a hybrid FEM-U-Net network, we were able to visualize the superficial vessels with NIROT with a Root Mean Square Error (RMSE) lower than 0.079.

BIAN: A Multilayer Microfluidic-Based Tissue-Mimicking Phantom for Near-Infrared Imaging

Near-infrared spectroscopy (NIRS) is a non-invasive optical method for monitoring cerebral oxygenation. Changes in regional blood flow and oxygenation due to neurovascular coupling are important biomarkers of neuronal activation. So far, there has been little research on multilayer tissue phantoms with tuneable blood flow, blood volume, and optical properties to simulate local changes in oxygenation at different depths. The aim of this study is to design, fabricate and characterize a complex dynamic phantom based on multilayer microfluidics with controllable blood flow, blood volume, and optical properties for testing NIRS instruments. We developed a phantom prototype with two microfluidic chips embedded at two depths inside a solid silicone phantom to mimic the vessels in the scalp and in the cortex. To simulate the oxygenation and perfusion of tissue, a solution with blood-like optical properties was sent into the microchannels by a pump with a programmable pressure controller. The pressure adjusted the volume of the microfluidic chips representing a distension of blood vessels. The optical changes in the superficial and deep layers were measured by a commercially available frequency domain NIRS instrument. The NIRS successfully detected the changes in light intensity elicited by the changes in the pressure input to the two layers. In conclusion, the microfluidics-based imaging phantom was successfully designed and fabricated and mimics brain functional activity. This technique has great potential for testing other optical devices, e.g., diffuse correlation spectroscopy, pulse oximetry, and optical coherence tomography.

Time Domain Near-Infrared Optical Tomography Utilizing Full Temporal Data: A Simulation Study

The analysis of full temporal data in time-domain near-infrared optical tomography (TD NIROT) measurements enables valuable information to be obtained about tissue properties with good temporal and spatial resolution. However, the large amount of data obtained is not easy to handle in the image reconstruction. The goal of the project is to employ full-temporal data from a TD NIROT modality. We improved TD data-based 3D image reconstruction and compared the performance with other methods using frequency domain (FD) and temporal moments. The iterative reconstruction algorithm was evaluated in simulations with both noiseless and noisy in-silico data. In the noiseless cases, a superior image quality was achieved by the reconstruction using full temporal data, especially when dealing with inclusions at 20 mm and deeper in the tissue. When noise similar to measured data was present, the quality of the recovered image from full temporal data was no longer superior to the one obtained from the analysis of FD data and temporal moments. This indicates that denoising methods for TD data should be developed. In conclusion, TD data contain richer information and yield better image quality.

Resolution and penetration depth of reflection-mode time-domain near infrared optical tomography using a ToF SPAD camera

In a turbid medium such as biological tissue, near-infrared optical tomography (NIROT) can image the oxygenation, a highly relevant clinical parameter. To be an efficient diagnostic tool, NIROT has to have high spatial resolution and depth sensitivity, fast acquisition time, and be easy to use. Since many tissues cannot be penetrated by near-infrared light, such tissue needs to be measured in reflection mode, i.e., where light emission and detection components are placed on the same side. Thanks to the recent advance in single-photon avalanche diode (SPAD) array technology, we have developed a compact reflection-mode time-domain (TD) NIROT system with a large number of channels, which is expected to substantially increase the resolution and depth sensitivity of the oxygenation images. The aim was to test this experimentally for our SPAD camera-empowered TD NIROT system. Experiments with one and two inclusions, i.e., optically dense spheres of 5mm radius, immersed in turbid liquid were conducted. The inclusions were placed at depths from 10mm to 30mm and moved across the field-of-view. In the two-inclusion experiment, two identical spheres were placed at a lateral distance of 8mm. We also compared short exposure times of 1s, suitable for dynamic processes, with a long exposure of 100s. Additionally, we imaged complex geometries inside the turbid medium, which represented structural elements of a biological object. The quality of the reconstructed images was quantified by the root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), and dice similarity. The two small spheres were successfully resolved up to a depth of 30mm. We demonstrated robust image reconstruction even at 1s exposure. Furthermore, the complex geometries were also successfully reconstructed. The results demonstrated a groundbreaking level of enhanced performance of the NIROT system based on a SPAD camera.

Development and Validation of Robust and Cost-Effective Liquid Heterogeneous Phantom for Time Domain Near-Infrared Optical Tomography

Diffused light imaging techniques, such as near-infrared optical tomography (NIROT), require a stable platform for testing and validation that imitates tissue optical properties. The aim of this work was to build a robust, but flexible liquid phantom for BORL time-domain NIROT system Pioneer. The phantom was designed to assess penetration depth and resolution of the system, and to provide a heterogeneous inner structure that can be changed in controllable manner with adjustable optical properties. We used only in-house produced 3D-printed elements and mechanics of a budget 3D-printer to build the phantom, and managed to keep the overall costs below $500. We achieved stable and repeatable movement of an arbitrary structure in 3+1 degree of freedom inside the phantom and demonstrated its performance in a series of tests. Thus, we presented a universal and cost-effective solution for testing NIROT, that can be easily customised to various systems or testing paradigms.

2.5 Hz sample rate time-domain near-infrared optical tomography based on SPAD-camera image tissue hemodynamics

Time-domain near-infrared optical tomography (TD NIROT) techniques based on diffuse light were gaining performance over the last years. They are capable of imaging tissue at several centimeters depth and reveal clinically relevant information, such as tissue oxygen saturation. In this work, we present the very first in vivo results of our SPAD camera-based TD NIROT reflectance system with a temporal resolution of ∼116 ps. It provides 2800 time of flight source-detector pairs in a compact probe of only 6 cm in diameter. Additionally, we describe a 3-step reconstruction procedure that enables accurate recovery of structural information and of the optical properties. We demonstrate the system's performance firstly in reconstructing the 3D-structure of a heterogeneous tissue phantom with tissue-like scattering and absorption properties within a volume of 9 cm diameter and 5 cm thickness. Furthermore, we performed in vivo tomography of an index finger located within a homogeneous scattering medium. We employed a fast sampling rate of 2.5 Hz to detect changes in tissue oxygenation. Tomographic reconstructions were performed in true 3D, and without prior structural information, demonstrating the powerful capabilities of the system. This shows its potential for clinical applications.

Photon detection probability enhancement using an anti-reflection coating in CMOS-based SPADs

This work presents a simulation and experimental study of the photon detection probability (PDP) enhancement in CMOS single-photon avalanche diodes (SPADs) using an anti-reflection coating (ARC) above the sensitive area. It is shown how the ARC layer can improve the PDP, not only by improving the optical transmission, but also by eliminating the penetration of the standing wave into a shallow region close to the silicon surface, where the multiplication region of the SPAD is formed. Furthermore, the appropriate ARC layer thickness corresponding to maximum PDP enhancement at different wavelengths over the visible spectrum is extracted to provide insight regarding the ARC selection if different ARC thicknesses are available within the CMOS process.

Noise and Breakdown Characterization of SPAD Detectors with Time-Gated Photon-Counting Operation

Being ready-to-detect over a certain portion of time makes the time-gated single-photon avalanche diode (SPAD) an attractive candidate for low-noise photon-counting applications. A careful SPAD noise and performance characterization, however, is critical to avoid time-consuming experimental optimization and redesign iterations for such applications. Here, we present an extensive empirical study of the breakdown voltage, as well as the dark-count and afterpulsing noise mechanisms for a fully integrated time-gated SPAD detector in 0.35-μm CMOS based on experimental data acquired in a dark condition. An "effective" SPAD breakdown voltage is introduced to enable efficient characterization and modeling of the dark-count and afterpulsing probabilities with respect to the excess bias voltage and the gating duration time. The presented breakdown and noise models will allow for accurate modeling and optimization of SPAD-based detector designs, where the SPAD noise can impose severe trade-offs with speed and sensitivity as is shown via an example.

The Use of Supercontinuum Laser Sources in Biomedical Diffuse Optics: Unlocking the Power of Multispectral Imaging

Optical techniques based on diffuse optics have been around for decades now and are making their way into the day-to-day medical applications. Even though the physics foundations of these techniques have been known for many years, practical implementation of these technique were hindered by technological limitations, mainly from the light sources and/or detection electronics. In the past 20 years, the developments of supercontinuum laser (SCL) enabled to unlock some of these limitations, enabling the development of system and methodologies relevant for medical use, notably in terms of spectral monitoring. In this review, we focus on the use of SCL in biomedical diffuse optics, from instrumentation and methods developments to their use for medical applications. A total of 95 publications were identified, from 1993 to 2021. We discuss the advantages of the SCL to cover a large spectral bandwidth with a high spectral power and fast switching against the disadvantages of cost, bulkiness, and long warm up times. Finally, we summarize the utility of using such light sources in the development and application of diffuse optics in biomedical sciences and clinical applications.

Efficient numerical modelling of time-domain light propagation in curved 3D absorbing and scattering media with finite differences

An efficient approach is introduced for modelling light propagation in the time domain in 3D heterogeneous absorbing and scattering media (e.g. biological tissues) with curved boundaries. It relies on the finite difference method (FDM) in conjuction with the Crank-Nicolson method for accurately solving the optical diffusion equation (DE). The strength of the FDM lies in its simplicity and efficiency, since the equations are easy to set up, and accessing neighboring grid points only requires simple memory operations, leading to efficient code execution. Owing to its use of Cartesian grids, the FDM is generally thought cumbersome compared to the finite element method (FEM) for dealing with media with curved boundaries. However, to apply the FDM to such media, the blocking-off method can be resorted to. To account for the change of the refractive index at the boundary, Robin-type boundary conditions are considered. This requires the computation of surface normals. We resort here for the first time to the Sobel operator borrowed from image processing to perform this task. The Sobel operator is easy to implement, fast, and allows obtaining a smooth field of normal vectors along the boundary. The main contribution of this work is to arrive at a complete numerical FDM-based model of light propagation in the time domain in 3D absorbing and scattering media with curved geometries, taking into account realistic refractive index mismatch boundary conditions. The fluence rate obtained with this numerical model is shown to reproduce well that obtained with independent gold-standard Monte Carlo simulations.