Using algebraic reconstruction in computed tomography

Tang, Nate D.; Ruiter, Niels de; Mohr, J L; Butler, Anthony; Butler, P. H.; Raja, Aamir

doi:10.1145/2425836.2425881

Cited by 12 publications

(12 citation statements)

References 9 publications

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“…For example, compressed sensing can reduce noise by exploiting correlations across energy bins . Pixelated detectors have high fill factors (>95%) but with randomly distributed dead areas and truncated data owing to detector overflow . Algebraic and statistical reconstruction methods are better suited to pixelated detectors whereas filtered back‐projection is better suited to scintillating detectors used in conventional CT.…”

Section: Spectral Molecular Imaging Of Atherosclerosismentioning

confidence: 99%

Clinical applications of spectral molecular imaging: potential and challenges

Anderson

Butler

2014

Contrast Media & Molecular

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Spectral molecular imaging is a new X-ray-based imaging technology providing highly specific 3D imaging at high spatial resolution that has the potential to measure disease activity and response to treatment noninvasively. The ability to identify and quantify components of tissue and biomarkers of disease activity derive from the properties of the photon-processing detector. Multiple narrow sections of the energy spectrum are sampled simultaneously, providing a range of energy dependent Hounsfield units. As each material has a specific measurable X-ray spectrum, spectroscopic imaging allows for multiple materials to be quantified and differentiated from each other simultaneously. The technology, currently in its infancy, is set to grow rapidly, much as magnetic resonance did. The critical clinical applications have not yet been established, but it is likely to play a major role in identifying and directing treatment for unstable atherosclerotic plaque, assessing activity and response to treatment of a range of inflammatory diseases, and monitoring biomarkers of cancer and its treatment. If combined with Positron-emission tomography (PET), spectral molecular imaging could have a far greater effective role in cancer diagnosis and treatment monitoring than PET-CT does at present. It is currently used for small animal and specimen imaging. There are many challenges to be overcome before spectral imaging can be introduced into clinical medicine - these include technological improvements to detector design, bonding to the semiconductor layer, image reconstruction and display software, identifying which biomarkers are of most relevance to the disease in question, and accelerating drug discovery enabled by the new capabilities provided by spectral imaging.

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Section: Spectral Molecular Imaging Of Atherosclerosismentioning

confidence: 99%

Clinical applications of spectral molecular imaging: potential and challenges

Anderson

Butler

2014

Contrast Media & Molecular

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“…The raw data from the specimen scans were reconstructed using MARS Bioimaging’s iterative reconstruction algorithm. 49 ImageJ software (National Institutes of Health, USA) was used to measure the linear attenuation coefficients due to iodine and gadolinium. Regions of interest (ROIs) were selected for the three zones of the cartilage (superficial: top 100 μ m; middle: 100–200 μ m; deep: 200–600 μ m), which corresponded to the histological and biochemical results.…”

Section: Methodsmentioning

confidence: 99%

“…After the scan, data were reconstructed using an iterative reconstruction algorithm and material decomposition was completed as described above. 49 After material decomposition was completed, a heat map was produced for iodine and gadolinium concentrations using the maximum concentration at the surface as the end point and the start point as the first value below 5 mg/ml of iodine or gadolinium adjacent to the bone. The inverse relationship to GAG was based on a linear relationship determined in healthy bovine samples and overlaid on the human OA cartilage images for proof of concept as zonal DMMB layer analysis is not practical in non-healthy OA tissue due to its varying thickness, significantly reduced GAG content, and etiology related damage and superficial layer erosion.…”

Section: Methodsmentioning

confidence: 99%

Spectral CT imaging of human osteoarthritic cartilage via quantitative assessment of glycosaminoglycan content using multiple contrast agents

et al. 2021

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Detection of early osteoarthritis to stabilize or reverse the damage to articular cartilage would improve patient function, reduce disability, and limit the need for joint replacement. In this study, we investigated nondestructive photon-processing spectral computed tomography (CT) for the quantitative measurement of the glycosaminoglycan (GAG) content compared to destructive histological and biochemical assay techniques in normal and osteoarthritic tissues. Cartilage-bone cores from healthy bovine stifles were incubated in 50% ioxaglate (Hexabrix ® ) or 100% gadobenate dimeglumine (MultiHance ® ). A photon-processing spectral CT (MARS) scanner with a CdTe-Medipix3RX detector imaged samples. Calibration phantoms of ioxaglate and gadobenate dimeglumine were used to determine iodine and gadolinium concentrations from photon-processing spectral CT images to correlate with the GAG content measured using a dimethylmethylene blue assay. The zonal distribution of GAG was compared between photon-processing spectral CT images and histological sections. Furthermore, discrimination and quantification of GAG in osteoarthritic human tibial plateau tissue using the same contrast agents were demonstrated. Contrast agent concentrations were inversely related to the GAG content. The GAG concentration increased from 25 μ g/ml (85 mg/ml iodine or 43 mg/ml gadolinium) in the superficial layer to 75 μ g/ml (65 mg/ml iodine or 37 mg/ml gadolinium) in the deep layer of healthy bovine cartilage. Deep zone articular cartilage could be distinguished from subchondral bone by utilizing the material decomposition technique. Photon-processing spectral CT images correlated with histological sections in healthy and osteoarthritic tissues. Post-imaging material decomposition was able to quantify the GAG content and distribution throughout healthy and osteoarthritic cartilage using Hexabrix ® and MultiHance ® while differentiating the underlying subchondral bone.

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“…The stitched and corrected projections and the detector's bad-pixel mask were then submitted to an iterative reconstruction algorithm (provided by the vendor) in order to generate tomographic images. 23 During reconstruction, inputs from "bad pixels" identified on the mask are simply ignored, and this is acceptable due to the iterative algorithm's ability to tolerate slightly sparse projection datasets without significant degradation.…”

Section: Measurement Techniquementioning

confidence: 99%

Evaluation of a photon counting Medipix3RX cadmium zinc telluride spectral x-ray detector

et al. 2018

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We assess the performance of a cadmium zinc telluride (CZT)-based Medipix3RX energy-resolving and photon-counting x-ray detector as a candidate for spectral microcomputed tomography (micro-CT) imaging. It features an array of 128 × 128, 110-μm 2 pixels, each with four simultaneous threshold counters that utilize realtime charge summing. Each pixel's response is assessed by imaging with a range of incident x-ray intensities and detector integration times. Energy-related assessments are made by exposing the detector to the emission from an I-125 radioisotope brachytherapy seed. Long-term stability is assessed by repeating identical exposures over the course of 1 h. The high yield of properly functioning pixels (98.8%), long-term stability (linear regression of whole-chip response over 1 h of acquisitions: y ¼ −0.0038x þ 2284; standard deviation: 3.7 counts), and energy resolution [2.5 keV full-width half-maximum (FWHM) (single pixel), 3.7 keV FWHM (across the full image)] make this device suitable for spectral micro-CT.

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Using algebraic reconstruction in computed tomography

Cited by 12 publications

References 9 publications

Clinical applications of spectral molecular imaging: potential and challenges

Clinical applications of spectral molecular imaging: potential and challenges

Spectral CT imaging of human osteoarthritic cartilage via quantitative assessment of glycosaminoglycan content using multiple contrast agents

Evaluation of a photon counting Medipix3RX cadmium zinc telluride spectral x-ray detector

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