Image reconstruction for novel time domain near infrared optical tomography: towards clinical applications

Using spectral derivatives to remove the influence of hair on optical images of the static absorbing properties of tissue-like turbid media

Significance

Although measurements of near-infrared light diffusely reflected from the head and other biological tissues are commonly used to generate images revealing changes in the concentrations of oxy- and deoxy-hemoglobin, static imaging of absolute concentrations has been inhibited by the unknown and variable coupling between the optical probe and the skin, to which hair is often a significant contributor. Measurements of spectral derivatives provide a means of overcoming this shortcoming.

Aim

The aim is to demonstrate experimentally that measurements of the derivative of the attenuation of the detected signal with respect to wavelength can be used to achieve images that are immune to the spatial variation of hair on the surface. The objective is to generate topographic images representative of static absorbing properties rather than retrieving absolute optical coefficients, which requires a tomographic approach.

Approach

The surface of a tissue-equivalent phantom, containing targets with different concentrations of absorbing dye, was coated with a layer of dark hair. The phantom was then imaged using a broadband source and spectrometer, and prior knowledge of the absorbing characteristics of the dye and of melanin was used to acquire separate images of each.

Results

The targets within the phantom are revealed with remarkable clarity, although a nonlinear relationship between the target contrast and absorption was observed. This nonlinear behavior was confirmed and explained using a Monte Carlo model of light propagation in a slab of similar absorbing properties.

Conclusions

A spectral derivative approach could be an effective tool for in vivo topographic imaging of the static optical properties of the brain and other tissues, avoiding the deleterious effects of hair.

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.

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.

Image Reconstruction Using Deep Learning for Near-Infrared Optical Tomography: Generalization Assessment

Time is one of the most critical factors in preventing brain lesions due to hypoxic ischemia in preterm infants. Since early detection of low oxygenation is vital and the time window for therapy is narrow, near-infrared optical tomography (NIROT) must be able to process the high-dimensional data provided by today's advanced systems in the shortest possible time. Deep learning approaches are attractive because they can exploit such high information density while reducing inference time. The aim of this study was to evaluate the performance of a hybrid convolutional neural network, designed for NIROT image reconstruction and trained on synthetic data. Generalization capability was assessed using measurements on phantoms of a surface topology more divergent than the range of variation in the geometries of the in-silico data, with unseen, non-spherical inclusion shapes, and with source and detector arrangements different from those used for data generation. Substantial gains in speed, localization accuracy, and high image quality were achieved even under the highly varied measurement conditions.

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.

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.

In Phantom Validation of Time-Domain Near-Infrared Optical Tomography Pioneer for Imaging Brain Hypoxia and Hemorrhage

The neonatal brain is a vulnerable organ, and lesions due to hemorrhage and/or ischemia occur frequently in preterm neonates. Even though neuroprotective therapies exist, there is no tool available to detect the ischemic lesions. To address this problem, we have recently designed and built the new time-domain near-infrared optical tomography (TD NIROT) system - Pioneer. Here we present the results of a phantom study of the system performance. We used silicone phantoms to mimic risky situations for brain lesions: hemorrhage and hypoxia. Employing Pioneer, we were able to reconstruct accurately both position and optical properties of these inhomogeneities.

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

In many clinical applications it is relevant to observe dynamic changes in oxygenation. Therefore the ability of dynamic imaging with time domain (TD) near-infrared optical tomography (NIROT) will be important. But fast imaging is a challenge. The data acquisition of our handheld TD NIROT system based on single photon avalanche diode (SPAD) camera and 11 light sources was consequently accelerated. We tested the system on a diffusive medium simulating tissue with a moving object embedded. With 3D image reconstruction, the moving object was correctly located using only 0.2 s exposure time per source.