Linhui Wu

Combined hemoglobin and fluorescence diffuse optical tomography for breast tumor diagnosis: a pilot study on time-domain methodology

A combined time-domain fluorescence and hemoglobin diffuse optical tomography (DOT) system and the image reconstruction methods are proposed for enhancing the reliability of breast-dedicated optical measurement. The system equipped with two pulsed laser diodes at wavelengths of 780 nm and 830 nm that are specific to the peak excitation and emission of the FDA-approved ICG agent, and works with a 4-channel time-correlated single photon counting device to acquire the time-resolved distributions of the light re-emissions at 32 boundary sites of tissues in a tandem serial-to-parallel mode. The simultaneous reconstruction of the two optical (absorption and scattering) and two fluorescent (yield and lifetime) properties are achieved with the respective featured-data algorithms based on the generalized pulse spectrum technique. The performances of the methodology are experimentally assessed on breast-mimicking phantoms for hemoglobin- and fluorescence-DOT alone, as well as for fluorescence-guided hemoglobin-DOT. The results demonstrate the efficacy of improving the accuracy of hemoglobin-DOT based on a priori fluorescence localization.

Shape-parameterized diffuse optical tomography holds promise for sensitivity enhancement of fluorescence molecular tomography.

A fundamental approach to enhancing the sensitivity of the fluorescence molecular tomography (FMT) is to incorporate diffuse optical tomography (DOT) to modify the light propagation modeling. However, the traditional voxel-based DOT has been involving a severely ill-posed inverse problem and cannot retrieve the optical property distributions with the acceptable quantitative accuracy and spatial resolution. Although, with the aid of an anatomical imaging modality, the structural-prior-based DOT method with either the hard- or soft-prior scheme holds promise for in vivo acquiring the optical background of tissues, the low robustness of the hard-prior scheme to the segmentation error and inferior performance of the soft-prior one in the quantitative accuracy limit its further application. We propose in this paper a shape-parameterized DOT method for not only effectively determining the regional optical properties but potentially achieving reasonable structural amelioration, lending itself to FMT for comparably improved recovery of fluorescence distribution.

Enhancement of fluorescence molecular tomography with structural-prior-based diffuse optical tomography: combating optical background uncertainty.

The common approach in fluorescence molecular tomography (FMT) assumes homogeneous distributions of the optical properties and normally results in reconstructions of low sensitivity. A natural enhancement is to incorporate diffuse optical tomography (DOT) to FMT. However, the traditional voxel-based DOT has been a severely ill-posed inverse problem and cannot retrieve the optical property distributions accurately. We present a structural-prior-based DOT method to effectively acquire the heterogeneous optical background with the aid of some imperfect structural priors from x-ray computed tomography and/or magnetic resonance imaging anatomical imaging modalities, and quantitatively compare its hard- and soft-prior schemes for achieving an improved recovery of the fluorescence distribution. Numerical simulations are conducted on a region-labeled three-dimensional (3D) digital mouse model to investigate the performance of this method. Physical experiments on a cylindrical phantom are also conducted to assess this methodology. Our simulated and experimental reconstruction results indicate that the structural-prior-based DOT guided FMT approach can significantly improve the sensitivity of FMT reconstruction, as well as its imaging resolution and quantitative accuracy.

Performance Enhancement of Pharmacokinetic Diffuse Fluorescence Tomography by Use of Adaptive Extended Kalman Filtering.

Due to both the physiological and morphological differences in the vascularization between healthy and diseased tissues, pharmacokinetic diffuse fluorescence tomography (DFT) can provide contrast-enhanced and comprehensive information for tumor diagnosis and staging. In this regime, the extended Kalman filtering (EKF) based method shows numerous advantages including accurate modeling, online estimation of multiparameters, and universal applicability to any optical fluorophore. Nevertheless the performance of the conventional EKF highly hinges on the exact and inaccessible prior knowledge about the initial values. To address the above issues, an adaptive-EKF scheme is proposed based on a two-compartmental model for the enhancement, which utilizes a variable forgetting-factor to compensate the inaccuracy of the initial states and emphasize the effect of the current data. It is demonstrated using two-dimensional simulative investigations on a circular domain that the proposed adaptive-EKF can obtain preferable estimation of the pharmacokinetic-rates to the conventional-EKF and the enhanced-EKF in terms of quantitativeness, noise robustness, and initialization independence. Further three-dimensional numerical experiments on a digital mouse model validate the efficacy of the method as applied in realistic biological systems.

GPU-accelerated Monte-Carlo modeling for fluorescence propagation in turbid medium

In biomedical optics, the Monte Carlo (MC) simulation is widely recognized as a gold standard for its high accuracy and versatility. However, in fluorescence regime, due to the requirement for tracing a huge number of the consecutive events of an excitation photon migration, the excitation-to-emission convention and the resultant fluorescent photon migration in tissue, the MC method is prohibitively time-consuming, especially when the tissue has an optically heterogeneous structure. To overcome the difficulty, we present a parallel implementation of MC modeling for fluorescence propagation in tissue, on the basis of the Graphics Processing Units (GPU) and the Compute Unified Device Architecture (CUDA) platform. By rationalizing the distribution of blocks and threads a certain number of photon migration procedures can be processed synchronously and efficiently, with the single-instruction-multiple-thread execution mode of GPU. We have evaluated the implementation for both homogeneous and heterogeneous scenarios by comparing with the conventional CPU implementations, and shown that the GPU method can obtain significant acceleration of about 20-30 times for fluorescence modeling in tissue, indicating that the GPU-based fluorescence MC simulation can be a practically effective tool for methodological investigations of tissue fluorescence spectroscopy and imaging.

A time-domain diffuse optical/fluorescent tomography using multi-dimensional TCSPC design

Techniques of time-correlated single-photon counting (TCSPC) have been widely used in diffuse optical tomography (DOT) and diffuse fluorescence tomography (DFT). While a multi-channel TCSPC-based DOT/DFT system can be conveniently constructed using independent modules, the state-of-the-art TCSPC technique has extended its multidimensional function by facilitating a compact and cost-effective design of the multi-channel as well as multi-wavelength data-acquisition. We herein present a revised multi-channel TCSPC system that is based the multidimensional function of the TCSPC device. We also design a series of DOT and DFT experiments to validate effectiveness of the system.

Improving diffuse optical tomography with structural a priori from fluorescence diffuse optical tomography

We obtain absorption and scattering reconstructed images by incorporating a priori information of target location obtained from fluorescence diffuse optical tomography (FDOT) into the diffuse optical tomography (DOT). The main disadvantage of DOT lies in the low spatial resolution resulting from highly scattering nature of tissue in the near-infrared (NIR), but one can use it to monitor hemoglobin concentration and oxygen saturation simultaneously, as well as several other cheomphores such as water, lipids, and cytochrome-c-oxidase. Up to date, extensive effort has been made to integrate DOT with other imaging modalities such as MRI, CT, to obtain accurate optical property maps of the tissue. However, the experimental apparatus is intricate. In this study, DOT image reconstruction algorithm that incorporates a prior structural information provided by FDOT is investigated in an attempt to optimize recovery of a simulated optical property distribution. By use of a specifically designed multi-channel time-correlated single photon counting system, the proposed scheme in a transmission mode is experimentally validated to achieve simultaneous reconstruction of the fluorescent yield, lifetime, absorption and scattering coefficient. The experimental results demonstrate that the quantitative recovery of the tumor optical properties has doubled and the spatial resolution improves as well by applying the new improved method.

Time-domain fluorescence-guided diffuse optical tomography based on the third-order simplified harmonics approximation.

Extensive efforts have been made to integrate diffuse optical tomography (DOT) with other imaging modalities, such as magnetic-resonance imaging and x-ray computerized tomography, for its performance improvement. However, the experimental apparatus is in general intricate and costly due to adoption of the physically distinct radiation regimes. In this study, a time-domain fluorescence-guided DOT methodology that incorporates a priori localization information provided by diffuse fluorescence tomography (DFT) is investigated in an attempt to optimize recovery of the optical property distributions. The methodology is based on a specifically designed multichannel time-correlated single-photon-counting DOT/DFT system as well as a featured-data image reconstruction scheme that is developed within the framework of the generalized pulse spectrum technique and employs the third-order simplified harmonics approximation to the radiative transfer equation as the forward model. We have validated the methodology using phantom experiments and demonstrated that, with the guidance of fluorescence a priori, the quantitativeness and spatial resolution of the recovered optical target can be considerably improved in terms of the absorption and scattering images.

An adaptive extended Kalman filter for fluorescence diffuse optical tomography of tumor pharmacokinetics

According to the morphological differences in the vascularization between healthy and diseased tissues, pharmacokinetic-rate images of fluorophore can provide diagnostic information for tumor differentiation, and especially have the potential for staging of tumors. In this paper, fluorescence diffuse optical tomography method is firstly used to acquire metabolism-related time-course images of the fluorophore concentration. Based on a two-compartment model comprised of plasma and extracelluar-extravascular space, we next propose an adaptive-EKF framework to estimate the pharmacokinetic-rate images. With the aid of a forgetting factor, the adaptive-EKF compensate the inaccuracy initial values and emphasize the effect of the current data in order to realize a better online estimation compared with the conventional EKF. We use simulate data to evaluate the performance of the proposed methodology. The results suggest that the adaptive-EKF can obtain preferable pharmacokinetic-rate images than the conventional EKF with higher quantitativeness and noise robustness.

Towards diffuse optical tomography of arbitrarily heterogeneous turbid medium using GPU-accelerated Monte-Carlo forward calculation

At present, the most widely accepted forward model in diffuse optical tomography (DOT) is the diffusion equation, which is derived from the radiative transfer equation by employing the P1 approximation. However, due to its validity restricted to highly scattering regions, this model has several limitations for the whole-body imaging of small-animals, where some cavity and low scattering areas exist. To overcome the difficulty, we presented a Graphic-Processing- Unit(GPU) implementation of Monte-Carlo (MC) modeling for photon migration in arbitrarily heterogeneous turbid medium, and, based on this GPU-accelerated MC forward calculation, developed a fast, universal DOT image reconstruction algorithm. We experimentally validated the proposed method using a continuous-wave DOT system in the photon-counting mode and a cylindrical phantom with a cavity inclusion.