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12 pages, 4874 KiB

Open AccessArticle

Diffuse Optical Tomography Provides a High Sensitivity at the Sensory-Motor Gyri: A Functional Region of Interest Approach

by Estefania Hernandez-Martin, Francisco Marcano, Oscar Perez-Diaz, Cristina de Dios and Jose Luis Gonzalez-Mora

Appl. Sci. 2023, 13(23), 12686; https://doi.org/10.3390/app132312686 - 27 Nov 2023

Viewed by 718

Abstract

Diffuse optical tomography (DOT) technology enables a differentiation between oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the sensory and motor cerebral gyri, resulting in greater sensitivity for cerebral activation compared to functional magnetic resonance imaging (fMRI). Here, we introduce a novel approach where functional [...] Read more.

Diffuse optical tomography (DOT) technology enables a differentiation between oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the sensory and motor cerebral gyri, resulting in greater sensitivity for cerebral activation compared to functional magnetic resonance imaging (fMRI). Here, we introduce a novel approach where functional regions of interest (ROIs) are created based on the specific signal behavior observed in DOT measurements in contrast to the conventional use of structural-ROI obtained from anatomical information. The generation of cerebral activation maps involves using the general linear model (GLM) to compare the outcomes obtained from both the functional and structural-ROI approaches. DOT-derived maps are then compared with maps derived from fMRI datasets, which are considered the gold standard for assessing functional brain activity. The results obtained demonstrate the effectiveness of employing functional-ROI to improve the spatial location of functional activations in the sensory and motor cerebral gyri by leveraging the neural synchronization data provided by DOT. Furthermore, this methodology simplifies data processing, where anatomical differences can pose challenges. By incorporating functional-ROI prior to GLM application, this study offers enhancements to DOT analysis techniques and broadens its applicability. Full article

(This article belongs to the Special Issue Near-Infrared Optical Tomography)

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14 pages, 2522 KiB

Open AccessArticle

Deep Learning of Diffuse Optical Tomography Based on Time-Domain Radiative Transfer Equation

by Yuichi Takamizu, Masayuki Umemura, Hidenobu Yajima, Makito Abe and Yoko Hoshi

Appl. Sci. 2022, 12(24), 12511; https://doi.org/10.3390/app122412511 - 07 Dec 2022

Cited by 4 | Viewed by 1564

Abstract

Near infrared diffuse optical tomography (DOT) is a potential tool for diagnosing cancer by image reconstruction of tissue optical properties. A variety of image reconstruction methods for DOT have been attempted, in general, based on the diffusion equation (DE). However, the image quality [...] Read more.

Near infrared diffuse optical tomography (DOT) is a potential tool for diagnosing cancer by image reconstruction of tissue optical properties. A variety of image reconstruction methods for DOT have been attempted, in general, based on the diffusion equation (DE). However, the image quality is still insufficient to clinical use, which is mainly attributed to the fact that the DE is invalid in some regions, such as low-scattering regions, and the inverse problem is inherently ill-posed. In contrast, the radiative transfer equation (RTE) accurately describes light propagation in biological tissue and also the DOT by deep learning is recently thought to be an alternative approach to the inverse problem. Distribution of time of flight (DTOF) of photons estimated by the time-domain RTE lends itself to deep learning along a temporal sequence. In this study, we propose a new DOT image reconstruction algorithm based on a long-short-term memory and the time-domain RTE. In simulation studies, using this algorithm, we succeeded in detection of an absorbing inclusion with a diameter of 5 mm, an absorber mimicking cancer, which was embedded in a two-dimensional square model (4 cm × 4 cm) with an optically homogeneous background. Multiple absorbers and a bigger absorber embedded in this model were also detected. We also demonstrate that, if simulation data by beam injection from multiple directions are employed as a training set, the accuracy of detection is improved especially for multiple absorbers. Full article

(This article belongs to the Special Issue Near-Infrared Optical Tomography)

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11 pages, 2342 KiB

Open AccessArticle

Three Dimensional Lifetime-Multiplex Tomography Based on Time-Gated Capturing of Near-Infrared Fluorescence Images

by Masakazu Umezawa, Keiji Miyata, Kyohei Okubo and Kohei Soga

Appl. Sci. 2022, 12(15), 7721; https://doi.org/10.3390/app12157721 - 31 Jul 2022

Cited by 1 | Viewed by 1820

Abstract

We report a computed tomography (CT) technique for mapping near-infrared fluorescence (NIRF) lifetime as a multiplex three-dimensional (3D) imaging method, using a conventional NIR camera. This method is achieved by using a time-gated system composed of a pulsed laser and an NIR camera [...] Read more.

We report a computed tomography (CT) technique for mapping near-infrared fluorescence (NIRF) lifetime as a multiplex three-dimensional (3D) imaging method, using a conventional NIR camera. This method is achieved by using a time-gated system composed of a pulsed laser and an NIR camera synchronized with a rotatable sample stage for NIRF-CT imaging. The fluorescence lifetimes in microsecond-order of lanthanides were mapped on reconstructed cross-sectional and 3D images, via back-projection of two-dimensional projected images acquired from multiple angles at each time point showing fluorescence decay. A method to select slopes (the observed decay rates in time-gated imaging) used for the lifetime calculation, termed as the slope comparison method, was developed for the accurate calculation of each pixel, resulting in reduction of image acquisition time. Time-gated NIRF-CT provides a novel choice for multiplex 3D observation of deep tissues in biology. Full article

(This article belongs to the Special Issue Near-Infrared Optical Tomography)

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10 pages, 2627 KiB

Open AccessArticle

Motion Deblurring for Single-Pixel Spatial Frequency Domain Imaging

by Mai Dan, Meihui Liu and Feng Gao

Appl. Sci. 2022, 12(15), 7402; https://doi.org/10.3390/app12157402 - 23 Jul 2022

Viewed by 1172

Abstract

The single-pixel imaging technique is applied to spatial frequency domain imaging (SFDI) to bring significant performance advantages in band extension and sensitivity enhancement. However, the large number of samplings required can cause severe quality degradations in the measured image when imaging a moving [...] Read more.

The single-pixel imaging technique is applied to spatial frequency domain imaging (SFDI) to bring significant performance advantages in band extension and sensitivity enhancement. However, the large number of samplings required can cause severe quality degradations in the measured image when imaging a moving target. This work presents a novel method of motion deblurring for single-pixel SFDI. In this method, the Fourier coefficients of the reflected image are measured by the Fourier single-pixel imaging technique. On this basis, a motion-degradation-model-based compensation, which is derived by the phase-shift and frequency-shift properties of Fourier transform, is adopted to eliminate the effects of target displacements on the measurements. The target displacements required in the method are obtained using a fast motion estimation approach. A series of numerical and experimental validations show that the proposed method can effectively deblur the moving targets and accordingly improves the accuracy of the extracted optical properties, rendering it a potentially powerful way of broadening the clinical application of single-pixel SFDI. Full article

(This article belongs to the Special Issue Near-Infrared Optical Tomography)

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11 pages, 2370 KiB

Open AccessCommunication

Optical Property Measurement and Temperature Monitoring in High-Intensity Focused Ultrasound Therapy by Diffuse Optical Tomography: A Correlation Study

by Hao Yang, Sean Aleman and Huabei Jiang

Appl. Sci. 2022, 12(14), 7093; https://doi.org/10.3390/app12147093 - 14 Jul 2022

Cited by 2 | Viewed by 1255

Abstract

In this article, we propose a new approach utilizing diffuse optical tomography (DOT) to monitoring the changes in tissues’ optical properties and temperature in high-intensity focused ultrasound (HIFU) therapy. By correlating the tissue reduced scattering coefficient (

μ_{s}^{’}

) reconstructed by [...] Read more.

In this article, we propose a new approach utilizing diffuse optical tomography (DOT) to monitoring the changes in tissues’ optical properties and temperature in high-intensity focused ultrasound (HIFU) therapy. By correlating the tissue reduced scattering coefficient (

μ_{s}^{’}

) reconstructed by DOT and the temperature measured by a thermocouple, the quantitative relationship between

μ_{s}^{’}

and temperature in HIFU treatment was explored. The experiments were conducted using porcine and chicken breast muscle tissues during HIFU; the temperature of each tissue sample was recorded using a thermocouple. To incorporate the temperature dependency of tissue optical properties, both polynomial and exponential models were utilized to fit the experimental data. The results show that the change of

μ_{s}^{’}

during HIFU treatment could be detected in real-time using DOT and that this change of

μ_{s}^{’}

is quantitatively correlated with tissue temperature. Furthermore, while the tissue-type-dependent relationship between

μ_{s}^{’}

and temperature is non-linear in nature, it is stable and repeatable. Therefore, our approach has the potential to be used to predict temperature of tissue during HIFU treatment. Full article

(This article belongs to the Special Issue Near-Infrared Optical Tomography)

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16 pages, 3319 KiB

Open AccessArticle

Diagnostic Evaluation of Rheumatoid Arthritis (RA) in Finger Joints Based on the Third-Order Simplified Spherical Harmonics (SP₃) Light Propagation Model

by Stephen Hyunkeol Kim, Ludguier Montejo and Andreas Hielscher

Appl. Sci. 2022, 12(13), 6418; https://doi.org/10.3390/app12136418 - 24 Jun 2022

Cited by 1 | Viewed by 1249

Abstract

This work focuses on the evaluation of third-order simplified spherical harmonics (SP₃) model-based image reconstruction with respect to its clinical utility to diagnose rheumatoid arthritis (RA). The existing clinical data of 219 fingers was reconstructed for both absorption and scattering maps [...] Read more.

This work focuses on the evaluation of third-order simplified spherical harmonics (SP₃) model-based image reconstruction with respect to its clinical utility to diagnose rheumatoid arthritis (RA). The existing clinical data of 219 fingers was reconstructed for both absorption and scattering maps in fingers by using the reduced-Hessian sequential quadratic programming (rSQP) algorithm that employs the SP₃ model of light propagation. The

k

-fold cross validation method was used for feature extraction and classification of SP₃-based tomographic images. The performance of the SP₃ model was compared to the DE and ERT models with respect to diagnostic accuracy and computational efficiency. The results presented here show that the SP₃ model achieves clinically relevant sensitivity (88%) and specificity (93%) that compare favorably to the ERT while maintaining significant computational advantage over the ERT (i.e., the SP₃ model is 100 times faster than the ERT). Furthermore, it is also shown that the SP₃ is similar in speed but superior in diagnostic accuracy to the DE. Therefore, it is expected that the method presented here can greatly aid in the early diagnosis of RA with clinically relevant accuracy in near real-time at a clinical setting. Full article

(This article belongs to the Special Issue Near-Infrared Optical Tomography)

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12 pages, 1346 KiB

Open AccessArticle

Numerical Study of Near-Infrared Light Propagation in Aqueous Alumina Suspensions Using the Steady-State Radiative Transfer Equation and Dependent Scattering Theory

by Hiroyuki Fujii, Iori Terabayashi, Toshiaki Aoki, Yuki Inoue, Hyeonwoo Na, Kazumichi Kobayashi and Masao Watanabe

Appl. Sci. 2022, 12(3), 1190; https://doi.org/10.3390/app12031190 - 24 Jan 2022

Cited by 2 | Viewed by 2213

Abstract

Understanding light propagation in liquid phantoms, such as colloidal suspensions, involves fundamental research of near-infrared optical imaging and spectroscopy for biological tissues. Our objective is to numerically investigate light propagation in the alumina colloidal suspensions with the mean alumina particle diameter of 55 [...] Read more.

Understanding light propagation in liquid phantoms, such as colloidal suspensions, involves fundamental research of near-infrared optical imaging and spectroscopy for biological tissues. Our objective is to numerically investigate light propagation in the alumina colloidal suspensions with the mean alumina particle diameter of 55 nm at the volume fraction range 1–20%. We calculated the light scattering properties using the dependent scattering theory (DST) on a length scale comparable to the optical wavelength. We calculated the steady-state radiative transfer and photon diffusion equations (RTE and PDE) using the DST results based on the finite difference method in a length scale of the mean free path. The DST calculations showed that the scattering and reduced scattering coefficients become more prominent at a higher volume fraction. The anisotropy factor is almost zero at all the volume fractions, meaning the scattering is isotropic. The comparative study of the RTE with the PDE showed that the diffusion approximation holds at the internal region with all the volume fractions and the boundary region with the volume fraction higher than 1%. Our findings suggest the usefulness of the PDE as a light propagation model for the alumina suspensions rather than the RTE, which provides accurate but complicated computation. Full article

(This article belongs to the Special Issue Near-Infrared Optical Tomography)

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Review

Jump to: Research

30 pages, 1241 KiB

Open AccessReview

A Review of Image Reconstruction Algorithms for Diffuse Optical Tomography

by Shinpei Okawa and Yoko Hoshi

Appl. Sci. 2023, 13(8), 5016; https://doi.org/10.3390/app13085016 - 17 Apr 2023

Cited by 2 | Viewed by 2821

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Near-Infrared Optical Tomography)

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