Automated Restarting Fast Proximal Gradient Descent Method for Single-View Cone-Beam X-ray Luminescence Computed Tomography Based on Depth Compensation.

Single-view cone-beam X-ray luminescence computed tomography (CB-XLCT) has recently gained attention as a highly promising imaging technique that allows for the efficient and rapid three-dimensional visualization of nanophosphor (NP) distributions in small animals. However, the reconstruction performance is hindered by the ill-posed nature of the inverse problem and the effects of depth variation as only a single view is acquired. To tackle this issue, we present a methodology that integrates an automated restarting strategy with depth compensation to achieve reconstruction.

Cone-beam X-ray luminescence computed tomography based on MLEM with adaptive FISTA initial image.

Background And Objective: As an emerging dual-mode optical molecular imaging, cone-beam X-ray luminescence computed tomography (CB-XLCT) has shown potential in early tumor diagnosis and other applications with increased depth and little autofluorescence. However, due to the low transfer efficiency of PNPs to convert X-ray energy to visible or near-infrared (NIR) light and X-ray dose limitation, the signal to noise ratio of projections is quite low, making the quality of CB-XLCT relatively poor.

Methods: To improve the reconstruction quality of low-counts CB-XLCT imaging, an adaptive reconstruction algorithm (named ADFISTA-MLEM) based on the maximum likelihood expectation estimation (MLEM) framework is proposed for CB-XLCT reconstruction from Poisson distributed projections.

Limited view cone-beam x-ray luminescence tomography based on depth compensation and group sparsity prior.

As a promising hybrid imaging technique with x-ray excitable nanophosphors, cone-beam x-ray luminescence computed tomography (CB-XLCT) has been proposed for in-depth biological imaging applications. In situations in which the full rotation of the imaging object (or x-ray source) is inapplicable, the x-ray excitation is limited by geometry, or a lower x-ray excitation dose is mandatory, limited view CB-XLCT reconstruction would be essential. However, this will result in severe ill-posedness and poor image quality.

Low-Dose X-ray Excited Photodynamic Therapy Based on NaLuF:Tb-Rose Bengal Nanocomposite.

X-ray excited photodynamic therapy (X-PDT), which utilizes X-rays as the energy source and X-ray luminescent nanoparticles (XLNPs) as the transducer to excite photosensitizers (PS), resolves the penetration problem of light in traditional PDT to enable the treatment of deep-seated tumors. Nevertheless, the high X-ray dosage used in X-PDT hampers its potential applications in clinics. In this study, to alleviate the dose problem, β-NaLuF:Tb spherical nanoparticles (NPs) with ultrastrong green X-ray excited optical luminescence (XEOL) due to the less nonradiative relaxation probability and high X-ray absorption mass coefficient, which perfectly matches the absorption spectrum of a photosensitizer named rose bengal (RB), were synthesized and employed as the energy transducer for X-PDT.

Regularized reconstruction based on joint L and total variation for sparse-view cone-beam X-ray luminescence computed tomography.

As an emerging hybrid imaging modality, cone-beam X-ray luminescence computed tomography (CB-XLCT) has been proposed based on the development of X-ray excitable nanoparticles. Owing to the high degree of absorption and scattering of light through tissues, the CB-XLCT inverse problem is inherently ill-conditioned. Appropriate priors or regularizations are needed to facilitate reconstruction and to restrict the search space to a specific solution set.

Spectral-resolved cone-beam X-ray luminescence computed tomography with principle component analysis.

Cone-beam X-ray luminescence computed tomography (CB-XLCT) has become a promising technique for its higher utilization of X-ray and shorter scanning time compared to the narrow-beam XLCT, but it suffers from the low-spatial resolution that results in the insufficiency to resolve the adjacent multiple probes. In multispectral CB-XLCT, multiple probes show different emission behaviors in the dimension of the spectrum. In this work, a spectral-resolved CB-XLCT method combining multispectral CB-XLCT with principle component analysis (PCA) was proposed to improve the imaging resolution.

Ultra-high FRET efficiency NaGdF: Tb-Rose Bengal biocompatible nanocomposite for X-ray excited photodynamic therapy application.

The limitation of light penetration depth invalidates the application of photodynamic therapy in deep-seated tumors. X-ray excited photodynamic therapy (X-PDT), which is based on X-rays excited luminescent nanoparticles (XLNP), provides a new strategy for PDT in deep tissues. However, the high X-ray dosage used and non-specific cytotoxicity of the nanoparticle-photosensitizer nanocomposite (NPs-PS) hamper in-vivo X-PDT applications.

Sparse view cone beam X-ray luminescence tomography based on truncated singular value decomposition.

Cone beam X-ray luminescence computed tomography (CB-XLCT) has been proposed as a promising hybrid imaging technique. Though it has the advantage of fast imaging, the inverse problem of CB-XLCT is seriously ill-conditioned, making the image quality quite poor, especially for imaging multi-targets. To achieve fast imaging of multi-targets, which is essential for in vivo applications, a truncated singular value decomposition (TSVD) based sparse view CB-XLCT reconstruction method is proposed in this study.

Cone-beam x-ray luminescence computed tomography based on x-ray absorption dosage.

With the advances of x-ray excitable nanophosphors, x-ray luminescence computed tomography (XLCT) has become a promising hybrid imaging modality. In particular, a cone-beam XLCT (CB-XLCT) system has demonstrated its potential in in vivo imaging with the advantage of fast imaging speed over other XLCT systems. Currently, the imaging models of most XLCT systems assume that nanophosphors emit light based on the intensity distribution of x-ray within the object, not completely reflecting the nature of the x-ray excitation process.

Resolving adjacent nanophosphors of different concentrations by excitation-based cone-beam X-ray luminescence tomography.

Cone-beam X-ray luminescence computed tomography (CB-XLCT) has been proposed as a new molecular imaging modality recently. It can obtain both anatomical and functional tomographic images of an object efficiently, with the excitation of nanophosphors or by cone-beam X-rays. However, the ill-posedness of the CB-XLCT inverse problem degrades the image quality and makes it difficult to resolve adjacent luminescent targets with different concentrations, which is essential in the monitoring of nanoparticle metabolism and drug delivery.

Three-dimensional texture features from intensity and high-order derivative maps for the discrimination between bladder tumors and wall tissues via MRI.

Purpose: This study aims to determine the three-dimensional (3D) texture features extracted from intensity and high-order derivative maps that could reflect textural differences between bladder tumors and wall tissues, and propose a noninvasive, image-based strategy for bladder tumor differentiation preoperatively.

Methods: A total of 62 cancerous and 62 wall volumes of interest (VOI) were extracted from T2-weighted MRI datasets of 62 patients with pathologically confirmed bladder cancer. To better reflect heterogeneous distribution of tumor tissues, 3D high-order derivative maps (the gradient and curvature maps) were calculated from each VOI.