Moiz Ahmad

Synergistic assembly of heavy metal clusters and luminescent organic bridging ligands in metal-organic frameworks for highly efficient X-ray scintillation.

We have designed two metal–organic frameworks (MOFs) to efficiently convert X-ray to visible-light luminescence. The MOFs are constructed from M6(μ3-O)4(μ3-OH)4(carboxylate)12 (M = Hf or Zr) secondary building units (SBUs) and anthracene-based dicarboxylate bridging ligands. The high atomic number of Zr and Hf in the SBUs serves as effective X-ray antenna by absorbing X-ray photons and converting them to fast electrons through the photoelectric effect. The generated electrons then excite multiple anthracene-based emitters in the MOF through inelastic scattering, leading to efficient generation of detectable photons in the visible spectrum. The MOF materials thus serve as efficient X-ray scintillators via synergistic X-ray absorption by the metal-cluster SBUs and optical emission by the bridging ligands.

A reference dataset for deformable image registration spatial accuracy evaluation using the COPDgene study archive

Landmark point-pairs provide a strategy to assess deformable image registration (DIR) accuracy in terms of the spatial registration of the underlying anatomy depicted in medical images. In this study, we propose to augment a publicly available database (www.dir-lab.com) of medical images with large sets of manually identified anatomic feature pairs between breath-hold computed tomography (BH-CT) images for DIR spatial accuracy evaluation. Ten BH-CT image pairs were randomly selected from the COPDgene study cases. Each patient had received CT imaging of the entire thorax in the supine position at one-fourth dose normal expiration and maximum effort full dose inspiration. Using dedicated in-house software, an imaging expert manually identified large sets of anatomic feature pairs between images. Estimates of inter- and intra-observer spatial variation in feature localization were determined by repeat measurements of multiple observers over subsets of randomly selected features. 7298 anatomic landmark features were manually paired between the 10 sets of images. Quantity of feature pairs per case ranged from 447 to 1172. Average 3D Euclidean landmark displacements varied substantially among cases, ranging from 12.29 (SD: 6.39) to 30.90 (SD: 14.05) mm. Repeat registration of uniformly sampled subsets of 150 landmarks for each case yielded estimates of observer localization error, which ranged in average from 0.58 (SD: 0.87) to 1.06 (SD: 2.38) mm for each case. The additions to the online web database (www.dir-lab.com) described in this work will broaden the applicability of the reference data, providing a freely available common dataset for targeted critical evaluation of DIR spatial accuracy performance in multiple clinical settings. Estimates of observer variance in feature localization suggest consistent spatial accuracy for all observers across both four-dimensional CT and COPDgene patient cohorts.

X-Ray Luminescence and X-Ray Fluorescence Computed Tomography: New Molecular Imaging Modalities

X-ray luminescence and X-ray fluorescence computed tomography (CT) are two emerging technologies in X-ray imaging that provide functional and molecular imaging capability. Both emission-type tomographic imaging modalities use external X-rays to stimulate secondary emissions, either light or secondary X-rays, which are then acquired for tomographic reconstruction. These modalities surpass the limits of sensitivity in current X-ray imaging and have the potential of enabling X-ray imaging to extract molecular imaging information. These new modalities also promise to break through the spatial resolution limits of other in vivo molecular imaging modalities. This paper reviews the development of X-ray luminescence and X-ray fluorescence CT and their relative merits. The discussion includes current problems and future research directions and the role of these modalities in future molecular imaging applications.

Extracting respiratory signals from thoracic cone beam CT projections.

The patient respiratory signal associated with the cone beam CT (CBCT) projections is important for lung cancer radiotherapy. In contrast to monitoring an external surrogate of respiration, such a signal can be extracted directly from the CBCT projections. In this paper, we propose a novel local principal component analysis (LPCA) method to extract the respiratory signal by distinguishing the respiration motion-induced content change from the gantry rotation-induced content change in the CBCT projections. The LPCA method is evaluated by comparing with three state-of-the-art projection-based methods, namely the Amsterdam Shroud method, the intensity analysis method and the Fourier-transform-based phase analysis method. The clinical CBCT projection data of eight patients, acquired under various clinical scenarios, were used to investigate the performance of each method. We found that the proposed LPCA method has demonstrated the best overall performance for cases tested and thus is a promising technique for extracting a respiratory signal. We also identified the applicability of each existing method.

Four-dimensional volume-of-interest reconstruction for cone-beam computed tomography-guided radiation therapy

PURPOSE Data sufficiency are a major problem in four-dimensional cone-beam computed tomography (4D-CBCT) on linear accelerator-integrated scanners for image-guided radiotherapy. Scan times must be in the range of 4-6 min to avoid undersampling artifacts. Various image reconstruction algorithms have been proposed to accommodate undersampled data acquisitions, but these algorithms are computationally expensive, may require long reconstruction times, and may require algorithm parameters to be optimized. The authors present a novel reconstruction method, 4D volume-of-interest (4D-VOI) reconstruction which suppresses undersampling artifacts and resolves lung tumor motion for undersampled 1-min scans. The 4D-VOI reconstruction is much less computationally expensive than other 4D-CBCT algorithms. METHODS The 4D-VOI method uses respiration-correlated projection data to reconstruct a four-dimensional (4D) image inside a VOI containing the moving tumor, and uncorrelated projection data to reconstruct a three-dimensional (3D) image outside the VOI. Anatomical motion is resolved inside the VOI and blurred outside the VOI. The authors acquired a 1-min. scan of an anthropomorphic chest phantom containing a moving water-filled sphere. The authors also used previously acquired 1-min scans for two lung cancer patients who had received CBCT-guided radiation therapy. The same raw data were used to test and compare the 4D-VOI reconstruction with the standard 4D reconstruction and the McKinnon-Bates (MB) reconstruction algorithms. RESULTS Both the 4D-VOI and the MB reconstructions suppress nearly all the streak artifacts compared with the standard 4D reconstruction, but the 4D-VOI has 3-8 times greater contrast-to-noise ratio than the MB reconstruction. In the dynamic chest phantom study, the 4D-VOI and the standard 4D reconstructions both resolved a moving sphere with an 18 mm displacement. The 4D-VOI reconstruction shows a motion blur of only 3 mm, whereas the MB reconstruction shows a motion blur of 13 mm. With graphics processing unit hardware used to accelerate computations, the 4D-VOI reconstruction required a 40-s reconstruction time. CONCLUSIONS 4D-VOI reconstruction effectively reduces undersampling artifacts and resolves lung tumor motion in 4D-CBCT. The 4D-VOI reconstruction is computationally inexpensive compared with more sophisticated iterative algorithms. Compared with these algorithms, our 4D-VOI reconstruction is an attractive alternative in 4D-CBCT for reconstructing target motion without generating numerous streak artifacts.

Hard X-ray-induced optical luminescence via biomolecule-directed metal clusters.

Here, we demonstrate that biomolecule-directed metal clusters are applicable in the study of hard X-ray excited optical luminescence, promising a new direction in the development of novel X-ray-activated imaging probes.

Order of Magnitude Sensitivity Increase in X-ray Fluorescence Computed Tomography (XFCT) Imaging With an Optimized Spectro-Spatial Detector Configuration: Theory and Simulation

The purpose of this study was to increase the sensitivity of XFCT imaging by optimizing the data acquisition geometry for reduced scatter X-rays. The placement of detectors and detector energy window were chosen to minimize scatter X-rays. We performed both theoretical calculations and Monte Carlo simulations of this optimized detector configuration on a mouse-sized phantom containing various gold concentrations. The sensitivity limits were determined for three different X-ray spectra: a monoenergetic source, a Gaussian source, and a conventional X-ray tube source. Scatter X-rays were minimized using a backscatter detector orientation (scatter direction > 110° to the primary X-ray beam). The optimized configuration simultaneously reduced the number of detectors and improved the image signal-to-noise ratio. The sensitivity of the optimized configuration was 10 μg/mL (10 pM) at 2 mGy dose with the mono-energetic source, which is an order of magnitude improvement over the unoptimized configuration (102 pM without the optimization). Similar improvements were seen with the Gaussian spectrum source and conventional X-ray tube source. The optimization improvements were predicted in the theoretical model and also demonstrated in simulations. The sensitivity of XFCT imaging can be enhanced by an order of magnitude with the data acquisition optimization, greatly enhancing the potential of this modality for future use in clinical molecular imaging.

High Resolution X-ray-Induced Acoustic Tomography

Absorption based CT imaging has been an invaluable tool in medical diagnosis, biology, and materials science. However, CT requires a large set of projection data and high radiation dose to achieve superior image quality. In this letter, we report a new imaging modality, X-ray Induced Acoustic Tomography (XACT), which takes advantages of high sensitivity to X-ray absorption and high ultrasonic resolution in a single modality. A single projection X-ray exposure is sufficient to generate acoustic signals in 3D space because the X-ray generated acoustic waves are of a spherical nature and propagate in all directions from their point of generation. We demonstrate the successful reconstruction of gold fiducial markers with a spatial resolution of about 350 μm. XACT reveals a new imaging mechanism and provides uncharted opportunities for structural determination with X-ray.

A method for automatic identification of water and fat images from a symmetrically sampled dual-echo Dixon technique

Sampling water and fat signals symmetrically (i.e., at 0 degrees and 180 degrees relative phase angles) in a dual-echo Dixon technique offers high intrinsic tolerance to phase fluctuations in postprocessing and maximum signal-to-noise performance for the separated water and fat images. However, identification of which image is water and which image is fat after their separation is not possible based on the phase information alone. In this work, we proposed a semiempirical automatic image identification method that is based on the intrinsic asymmetry between the water and fat chemical shift spectra. Specifically, the approximately bimodal feature of the fat spectra and the observation that most in vivo tissues are either predominantly water or predominantly fat are used to construct a spectrum-based algorithm. Additional refinement is accomplished by considering the spatial distribution of the tissues that may have a coexistence of water and fat. The final improved algorithm was tested on a total of 131 three-dimensional patient datasets collected from different scanners and found to yield correct water and fat identification in all datasets.

Dose calculation with respiration-averaged CT processed from cine CT without a respiratory surrogate

Dose calculation for thoracic radiotherapy is commonly performed on a free-breathing helical CT despite artifacts caused by respiratory motion. Four-dimensional computed tomography (4D-CT) is one method to incorporate motion information into the treatment planning process. Some centers now use the respiration-averaged CT (RACT), the pixel-by-pixel average of the ten phases of 4D-CT, for dose calculation. This method, while sparing the tedious task of 4D dose calculation, still requires 4D-CT technology. The authors have recently developed a means to reconstruct RACT directly from unsorted cine CT data from which 4D-CT is formed, bypassing the need for a respiratory surrogate. Using RACT from cine CT for dose calculation may be a means to incorporate motion information into dose calculation without performing 4D-CT. The purpose of this study was to determine if RACT from cine CT can be substituted for RACT from 4D-CT for the purposes of dose calculation, and if increasing the cine duration can decrease differences between the dose distributions. Cine CT data and corresponding 4D-CT simulations for 23 patients with at least two breathing cycles per cine duration were retrieved. RACT was generated four ways: First from ten phases of 4D-CT, second, from 1 breathing cycle of images, third, from 1.5 breathing cycles of images, and fourth, from 2 breathing cycles of images. The clinical treatment plan was transferred to each RACT and dose was recalculated. Dose planes were exported at orthogonal planes through the isocenter (coronal, sagittal, and transverse orientations). The resulting dose distributions were compared using the gamma index within the planning target volume (PTV). Failure criteria were set to 2%/1 mm. A follow-up study with 50 additional lung cancer patients was performed to increase sample size. The same dose recalculation and analysis was performed. In the primary patient group, 22 of 23 patients had 100% of points within the PTV pass y criteria. The average maximum and mean y indices were very low (well below 1), indicating good agreement between dose distributions. Increasing the cine duration generally increased the dose agreement. In the follow-up study, 49 of 50 patients had 100% of points within the PTV pass the y criteria. The average maximum and mean y indices were again well below 1, indicating good agreement. Dose calculation on RACT from cine CT is negligibly different from dose calculation on RACT from 4D-CT. Differences can be decreased further by increasing the cine duration of the cine CT scan.