Diffuse optical tomography using multi-directional sources and detectors

Sub-mm resolution tomographic imaging in turbid media by an ultra-high density multichannel approach

We demonstrate an ultra-high-density source-detector (SD) diffuse optical tomography system scalable to thousands of combinatorial SD pairs per cm3 of total voxel volume. We demonstrate the imaging of dynamic targets (including phantom arteries) with 100 um resolution at over 10 Hz frame rate within turbid media (> 60 MFP). Further, as a step toward a wearable mobile imager, we introduce monolithic mm-size dense semiconductor laser array chips as sources for potential unobtrusive epidermal tomographic use.

Optical diagnostic imaging and therapy for thyroid cancer

Thyroid cancer, as one of the most common endocrine cancers, has seen a surge in incidence in recent years. This is most likely due to the lack of specificity and accuracy of its traditional diagnostic modalities, leading to the overdiagnosis of thyroid nodules. Although there are several treatment options available, they are limited to surgery and ¹³¹I radiation therapy that come with significant side effects and hence cannot meet the treatment needs of anaplastic thyroid carcinoma with very high malignancy. Optical imaging that utilizes optical absorption, refraction and scattering properties, not only observes the structure and function of cells, tissues, organs, or even the whole organism to assist in diagnosis, but can also be used to perform optical therapy to achieve targeted non-invasive and precise treatment of thyroid cancer. These applications of screening, diagnosis, and treatment, lend to optical imaging's promising potential within the realm of thyroid cancer surgical navigation. Over the past decade, research on optical imaging in the diagnosis and treatment of thyroid cancer has been growing year by year, but no comprehensive review on this topic has been published. Here, we review key advances in the application of optical imaging in the diagnosis and treatment of thyroid cancer and discuss the challenges and potential for clinical translation of this technology.

A Data Self-Calibration Method Based on High-Density Parallel Plate Diffuse Optical Tomography for Breast Cancer Imaging

When performing the diffuse optical tomography (DOT) of the breast, the mismatch between the forward model and the experimental conditions will significantly hinder the reconstruction accuracy. Therefore, the reference measurement is commonly used to calibrate the measured data before the reconstruction. However, it is complicated to customize corresponding reference phantoms based on the breast shape and background optical parameters of different subjects in clinical trials. Furthermore, although high-density (HD) DOT configuration has been proven to improve imaging quality, a large number of source-detector (SD) pairs also increase the difficulty of multi-channel correction. To enhance the applicability of the breast DOT, a data self-calibration method based on an HD parallel-plate DOT system is proposed in this paper to replace the conventional relative measurement on a reference phantom. The reference predicted data can be constructed directly from the measurement data with the support of the HD-DOT system, which has nearly a hundred sets of measurements at each SD distance. The proposed scheme has been validated by Monte Carlo (MC) simulation, breast-size phantom experiments, and clinical trials, exhibiting the feasibility in ensuring the quality of the DOT reconstruction while effectively reducing the complexity associated with relative measurements on reference phantoms.

Resting-State Functional Connectivity Estimated With Hierarchical Bayesian Diffuse Optical Tomography

Resting-state functional connectivity (RSFC) has been generally assessed with functional magnetic resonance imaging (fMRI) thanks to its high spatial resolution. However, fMRI has several disadvantages such as high cost and low portability. In addition, fMRI may not be appropriate for people with metal or electronic implants in their bodies, with claustrophobia and who are pregnant. Diffuse optical tomography (DOT), a method of neuroimaging using functional near-infrared spectroscopy (fNIRS) to reconstruct three-dimensional brain activity images, offers a non-invasive alternative, because fNIRS as well as fMRI measures changes in deoxygenated hemoglobin concentrations and, in addition, fNIRS is free of above disadvantages. We recently proposed a hierarchical Bayesian (HB) DOT algorithm and verified its performance in terms of task-related brain responses. In this study, we attempted to evaluate the HB DOT in terms of estimating RSFC. In 20 healthy males (21-38 years old), 10 min of resting-state data was acquired with 3T MRI scanner or high-density NIRS on different days. The NIRS channels consisted of 96 long (29-mm) source-detector (SD) channels and 56 short (13-mm) SD channels, which covered bilateral frontal and parietal areas. There were one and two resting-state runs in the fMRI and fNIRS experiments, respectively. The reconstruction performances of our algorithm and the two currently prevailing algorithms for DOT were evaluated using fMRI signals as a reference. Compared with the currently prevailing algorithms, our HB algorithm showed better performances in both the similarity to fMRI data and inter-run reproducibility, in terms of estimating the RSFC.

Development of multi-directional functional near-infrared spectroscopy system for human neuroimaging studies

Multi-directional measurement using multi-directional light sources and multi-directional photodetectors drastically increases the amount of observation data without increasing the number of optical probes. In this study, we developed a novel multi-directional functional near-infrared spectroscopy (fNIRS) system for human neuroimaging studies. We tested our system by measuring the cortical hemodynamic changes of a single subject during a motor task and compared them with the same subject's functional magnetic resonance imaging (fMRI) data. We detected the direction-dependent fNIRS signals that originate from the cortical hemodynamic changes that are consistent with the fMRI data.