X-ray micro-modulated luminescence tomography (XMLT)

Cong, Wenxiang; Liu, Fenglin; Wang, Chao; Wang, Ge

doi:10.1364/oe.22.005572

Cited by 10 publications

(8 citation statements)

References 35 publications

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“…Liu et al applied a cone beam based XLCT to small animal imaging with the XLCT reconstruction from measurements at a single-view and they reported a location error of 1.43 mm [8]. To improve spatial resolution, Cong et al proposed a micro-modulated X-ray scanning method utilizing focused X-ray beams onto a spot of a few micrometers in size [9,10]. And we designed a microscopic XLCT (microXLCT) system by using a superfine single pinhole collimator, in which X-ray beams from the X-ray source were collimated by a small pinhole with a diameter of 100 µm [11].…”

Section: Introductionmentioning

confidence: 99%

Multiple pinhole collimator based X-ray luminescence computed tomography

Zhang

Zhu

Lun

et al. 2016

Biomed. Opt. Express

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X-ray luminescence computed tomography (XLCT) is an emerging hybrid imaging modality, which is able to improve the spatial resolution of optical imaging to hundreds of micrometers for deep targets by using superfine X-ray pencil beams. However, due to the low X-ray photon utilization efficiency in a single pinhole collimator based XLCT, it takes a long time to acquire measurement data. Herein, we propose a multiple pinhole collimator based XLCT, in which multiple X-ray beams are generated to scan a sample at multiple positions simultaneously. Compared with the single pinhole based XLCT, the multiple X-ray beam scanning method requires much less measurement time. Numerical simulations and phantom experiments have been performed to demonstrate the feasibility of the multiple X-ray beam scanning method. In one numerical simulation, we used four X-ray beams to scan a cylindrical object with 6 deeply embedded targets. With measurements from 6 angular projections, all 6 targets have been reconstructed successfully. In the phantom experiment, we generated two X-ray pencil beams with a collimator manufactured in-house. Two capillary targets with 0.6 mm edgeto-edge distance embedded in a cylindrical phantom have been reconstructed successfully. With the two beam scanning, we reduced the data acquisition time by 50%. From the reconstructed XLCT images, we found that the Dice similarity of targets is 85.11% and the distance error between two targets is less than 3%. We have measured the radiation dose during XLCT scan and found that the radiation dose, 1.475 mSv, is in the range of a typical CT scan. We have measured the changes of the collimated X-ray beam size and intensity at different distances from the collimator. We have also studied the effects of beam size and intensity in the reconstruction of XLCT.

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Section: Introductionmentioning

confidence: 99%

Multiple pinhole collimator based X-ray luminescence computed tomography

Zhang

Zhu

Lun

et al. 2016

Biomed. Opt. Express

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“…4). Theoretically, the MTCM method can produce confident estimation on any 'dynamic contrast-enhanced' imaging data with sufficient quality (e.g., spatial and temporal resolution) [23][24][25] . However, we should emphasize that there are a few fundamental assumptions behind the MTCM methodology, as specified in the newly proved theorems (e.g., linear convex combination, existence of pure-tissue pixels).…”

Section: Supplementary Discussion)mentioning

confidence: 99%

Unsupervised Deconvolution of Dynamic Imaging Reveals Intratumor Vascular Heterogeneity and Repopulation Dynamics

et al. 2014

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With the existence of biologically distinctive malignant cells originated within the same tumor, intratumor functional heterogeneity is present in many cancers and is often manifested by the intermingled vascular compartments with distinct pharmacokinetics. However, intratumor vascular heterogeneity cannot be resolved directly by most in vivo dynamic imaging. We developed multi-tissue compartment modeling (MTCM), a completely unsupervised method of deconvoluting dynamic imaging series from heterogeneous tumors that can improve vascular characterization in many biological contexts. Applying MTCM to dynamic contrast-enhanced magnetic resonance imaging of breast cancers revealed characteristic intratumor vascular heterogeneity and therapeutic responses that were otherwise undetectable. MTCM is readily applicable to other dynamic imaging modalities for studying intratumor functional and phenotypic heterogeneity, together with a variety of foreseeable applications in the clinic.

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“…Hence, multi-modality hybridization/fusion is necessary for superior structural, functional and molecular imaging [5]. An example of multi-physics hybridization was proposed for x-ray micro-modulated luminescence tomography (XMLT) [6]. As evidenced by the successes of SPECT-CT and PET-CT scanners, modality fusion imaging is clearly effective and synergistic and has had tremendous impact on both experimental discovery and clinical care [7-11].…”

Section: Introductionmentioning

confidence: 99%

“…As evidenced by the successes of SPECT-CT and PET-CT scanners, modality fusion imaging is clearly effective and synergistic and has had tremendous impact on both experimental discovery and clinical care [7-11]. Other hybrid technologies like PET-MRI and XMLT remain on the horizon with tremendous potential [6, 12]. …”

Section: Introductionmentioning

confidence: 99%

Simultaneous CT-MRI Reconstruction for Constrained Imaging Geometries Using Structural Coupling and Compressive Sensing

Zhao

Bennett

et al. 2016

IEEE Trans. Biomed. Eng.

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Objective A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. Significance Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. Methods In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and hence would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. Results Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset based experiments, and has yielded promising results.

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X-ray micro-modulated luminescence tomography (XMLT)

Cited by 10 publications

References 35 publications

Multiple pinhole collimator based X-ray luminescence computed tomography

Multiple pinhole collimator based X-ray luminescence computed tomography

Unsupervised Deconvolution of Dynamic Imaging Reveals Intratumor Vascular Heterogeneity and Repopulation Dynamics

Simultaneous CT-MRI Reconstruction for Constrained Imaging Geometries Using Structural Coupling and Compressive Sensing

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