Diffuse optical tomography (DOT) is a biomedical imaging modality that can reconstruct hemoglobin concentration and associated oxygen saturation by using detected light passing through a biological medium. Various clinical applications of DOT such as the diagnosis of breast cancer and functional brain imaging are expected. However, it has been difficult to obtain high spatial resolution and quantification accuracy with DOT because of diffusive light propagation in biological tissues with strong scattering and absorption. In recent years, various image reconstruction algorithms have been proposed to overcome these technical problems. Moreover, with progress in related technologies, such as artificial intelligence and supercomputers, the circumstances surrounding DOT image reconstruction have changed. To support the applications of DOT image reconstruction in clinics and new entries of related technologies in DOT, we review the recent efforts in image reconstruction of DOT from the viewpoint of (i) the forward calculation process, including the radiative transfer equation and its approximations to simulate light propagation with high precision, and (ii) the optimization process, including the use of sparsity regularization and prior information to improve the spatial resolution and quantification.

By measuring the adult human head during carotid endarterectomy, we investigate the depth sensitivity of two methods for deriving the absorption coefficient changes $\left(\Delta {\text{μ}}_a\right)$ from time-resolved reflectance data to absorption changes in inhomogeneous media: (1) the curve-fitting method based on the diffusion equation (DE-fit method) and (2) the time-independent calculation based on the modified Lambert–Beer law (MLB method). Remarkable differences in the determined values of $\Delta {\text{μ}}_a$ caused by clamping the external carotid artery and subsequently clamping the common carotid artery were observed between the methods. The DE-fit method was more sensitive to ${\text{μ}}_a$ changes in cerebral tissues, whereas the MLB method was rather sensitive to ${\text{μ}}_a$ changes in the extracerebral tissues. Our results indicated that the DE-fit was useful for monitoring the cerebral blood circulation and oxygenation during neurosurgical operations. In addition, the combined evaluation of ${\text{μ}}_a$ changes with the DE-fit and MLB methods will provide us with more available information about the hemodynamic changes in the depth direction.

Thyroid cancer is usually diagnosed by ultrasound imaging and fine-needle aspiration biopsy. However, diagnosis of follicular thyroid carcinomas (FTC) is difficult because FTC lacks nuclear atypia and a consensus on histological interpretation. Diffuse optical tomography (DOT) offers the potential to diagnose FTC because it can measure tumor hypoxia, while image reconstruction of the thyroid is still challenging mainly due to the complex anatomical features of the neck. In this study, we attempted to solve this issue by creating a finite element model of the human neck excluding the trachea (a void region). By reconstruction of the absorption coefficients at three wavelengths, 3D tissue oxygen saturation maps of the human thyroid are obtained for the first time by DOT.

SignificanceA shared understanding of terminology is essential for clear scientific communication and minimizing misconceptions. This is particularly challenging in rapidly expanding, interdisciplinary domains that utilize functional near-infrared spectroscopy (fNIRS), where researchers come from diverse backgrounds and apply their expertise in fields such as engineering, neuroscience, and psychology.AimThe fNIRS Glossary Project was established to develop a community-sourced glossary covering key fNIRS terms, including those related to the continuous-wave (CW), frequency-domain (FD), and time-domain (TD) NIRS techniques.ApproachThe glossary was collaboratively developed by a diverse group of 76 fNIRS researchers, representing a wide range of career stages (from PhD students to experts) and disciplines. This collaborative process, structured across five phases, ensured the glossary’s depth and comprehensiveness.ResultsThe glossary features over 300 terms categorized into six key domains: analysis, experimental design, hardware, neuroscience, mathematics, and physics. It also includes abbreviations, symbols, synonyms, references, alternative definitions, and figures where relevant.ConclusionsThe fNIRS glossary provides a community-sourced resource that facilitates education and effective scientific communication within the fNIRS community and related fields. By lowering barriers to learning and engaging with fNIRS, the glossary is poised to benefit a broad spectrum of researchers, including those with limited access to educational resources.

An accurate knowledge of tissue optical properties (absorption coefficients, μ_a, and reduced scattering coefficients, μ_s’) is critical for precise modeling of light propagation in biological tissue, essential for developing diagnostic and therapeutic optical techniques that utilize diffusive photons. A great number of studies have explored the optical properties of various tissue, and these values are not known in detail due to difficulties in the experimental determination and significant variations in tissue constitution. Especially, in situ estimates of the optical properties of brain tissue, a common measurement target in optical imaging, is a challenge because of its layer structure (where the thin gray matter covers the white matter). Here, we report an approach to in situ estimates of the μ_a and μ_s’ of the gray and white matter in living rat and monkey brains by using femtosecond time-resolved measurements and Monte Carlo simulation. The results demonstrate that the μ_a of the gray matter is larger than that of the white matter, while there was no significant difference in the μ_s’ between the gray and white matter. The optical properties of the rat brain were very similar to those of the monkey brain except for the μ_a of the gray matter here.