Photon-counting spectral computed tomography using silicon strip detectors: a feasibility study

Bornefalk, Hans; Danielsson, Mats

doi:10.1088/0031-9155/55/7/014

Cited by 165 publications

(184 citation statements)

References 33 publications

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“…23,27,[30][31][32][47][48][49][50][51] With 16 layers per pixel and 8 energy thresholds per layer, the PCDs have achieved high count rates (see Table I). The small atomic number of silicon is overcome by increasing the total thickness up to 30 mm in the depth direction.…”

Section: A Basic Architectures and Detection Mechanismmentioning

confidence: 99%

Vision 20/20: Single photon counting x‐ray detectors in medical imaging

2013

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Photon counting detectors (PCDs) with energy discrimination capabilities have been developed for medical x-ray computed tomography (CT) and x-ray (XR) imaging. Using detection mechanisms that are completely different from the current energy integrating detectors and measuring the material information of the object to be imaged, these PCDs have the potential not only to improve the current CT and XR images, such as dose reduction, but also to open revolutionary novel applications such as molecular CT and XR imaging. The performance of PCDs is not flawless, however, and it seems extremely challenging to develop PCDs with close to ideal characteristics. In this paper, the authors offer our vision for the future of PCD-CT and PCD-XR with the review of the current status and the prediction of (1) detector technologies, (2) imaging technologies, (3) system technologies, and (4) potential clinical benefits with PCDs.

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Section: A Basic Architectures and Detection Mechanismmentioning

confidence: 99%

Vision 20/20: Single photon counting x‐ray detectors in medical imaging

2013

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“…33 Therefore, with the help of the dedicated breast CT, it is possible to accurately characterize the chemical composition of a lesion in terms of water, lipid, and protein contents. [34][35][36][37] The proposed three-compartment measurement may be used in addition to diagnostic mammography to improve the positive predictive value in malignant tumor detection.…”

Section: Introductionmentioning

confidence: 99%

Measurement of breast tissue composition with dual energy cone‐beam computed tomography: A postmortem study

2013

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Purpose:To investigate the feasibility of a three-material compositional measurement of water, lipid, and protein content of breast tissue with dual kVp cone-beam computed tomography (CT) for diagnostic purposes. Methods: Simulations were performed on a flat panel-based computed tomography system with a dual kVp technique in order to guide the selection of experimental acquisition parameters. The expected errors induced by using the proposed calibration materials were also estimated by simulation. Twenty pairs of postmortem breast samples were imaged with a flat-panel based dual kVp cone-beam CT system, followed by image-based material decomposition using calibration data obtained from a three-material phantom consisting of water, vegetable oil, and polyoxymethylene plastic. The tissue samples were then chemically decomposed into their respective water, lipid, and protein contents after imaging to allow direct comparison with data from dual energy decomposition. Results: Guided by results from simulation, the beam energies for the dual kVp cone-beam CT system were selected to be 50 and 120 kVp with the mean glandular dose divided equally between each exposure. The simulation also suggested that the use of polyoxymethylene as the calibration material for the measurement of pure protein may introduce an error of −11.0%. However, the tissue decomposition experiments, which employed a calibration phantom made out of water, oil, and polyoxymethylene, exhibited strong correlation with data from the chemical analysis. The average root-mean-square percentage error for water, lipid, and protein contents was 3.58% as compared with chemical analysis. Conclusions:The results of this study suggest that the water, lipid, and protein contents can be accurately measured using dual kVp cone-beam CT. The tissue compositional information may improve the sensitivity and specificity for breast cancer diagnosis.

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“…Decomposition noise induced by image misregistration or spectral overlap may easily reduce the signal-to-noise ratio to the level where no reliable measurement can be obtained. Recent advances in spectral breast computed tomography (CT) based on energy-resolved photoncounting x-ray detectors offer unique advantages in such imaging tasks (22)(23)(24)(25)(26). Photon-counting detectors are able to count individual photons and sort them according to their energies with a typical energy resolution of a few kiloelectron-volts (27).…”

Section: Methodsmentioning

confidence: 99%

Breast Tissue Characterization with Photon-counting Spectral CT Imaging: A Postmortem Breast Study

Ding¹,

Klopfer²,

Ducote³

et al. 2014

Radiology

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Purpose:To investigate the feasibility of breast tissue characterization in terms of water, lipid, and protein contents with a spectral computed tomographic (CT) system based on a cadmium zinc telluride (CZT) photon-counting detector by using postmortem breasts. Materials and Methods:Nineteen pairs of postmortem breasts were imaged with a CZT-based photon-counting spectral CT system with beam energy of 100 kVp. The mean glandular dose was estimated to be in the range of 1.8-2.2 mGy. The images were corrected for pulse pile-up and other artifacts by using spectral distortion corrections. Dual-energy decomposition was then applied to characterize each breast into water, lipid, and protein contents. The precision of the three-compartment characterization was evaluated by comparing the composition of right and left breasts, where the standard error of the estimations was determined. The results of dual-energy decomposition were compared by using averaged root mean square to chemical analysis, which was used as the reference standard.

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Photon-counting spectral computed tomography using silicon strip detectors: a feasibility study

Cited by 165 publications

References 33 publications

Vision 20/20: Single photon counting x‐ray detectors in medical imaging

Vision 20/20: Single photon counting x‐ray detectors in medical imaging

Measurement of breast tissue composition with dual energy cone‐beam computed tomography: A postmortem study

Breast Tissue Characterization with Photon-counting Spectral CT Imaging: A Postmortem Breast Study

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