Evaluation of techniques for slice sensitivity profile measurement and analysis

Greene, T; Rong, Xiujiang

doi:10.1120/jacmp.v15i2.4042

Cited by 17 publications

(17 citation statements)

References 48 publications

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“…A micro-CT slice sensitivity profile (SSP) phantom (QRM, GmbH, Möhrendorf, Germany) was used to determine the cross-plane (z-direction) spatial resolution of the system. This phantom has been used in previous studies to measure the cross-plane resolution [23, 24]. The resin made phantom has an inserted gold platelet of 1 mm diameter and 10 μm thickness as shown in Fig.…”

Section: Methodsmentioning

confidence: 99%

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Investigation of spatial resolution characteristics of an in vivo microcomputed tomography system

Ghani

Zhou

Ren

et al. 2016

Nuclear Instruments and Methods in Physics Research Section A:

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The spatial resolution characteristics of an in vivo micro computed tomography (CT) system was investigated in the in-plane (x-y), cross plane (z) and projection imaging modes. The micro CT system utilized in this study employs a flat panel detector with a 127 μm pixel pitch, a micro focus x-ray tube with a focal spot size ranging from 5-30 μm, and accommodates three geometric magnifications (M) of 1.72, 2.54 and 5.10. The in-plane modulation transfer function (MTF) curves were measured as a function of the number of projections, geometric magnification (M), detector binning and reconstruction magnification (MRecon). The in plane cutoff frequency (10% MTF) ranged from 2.31 lp/mm (M=1.72, 2×2 binning) to 12.56 lp/mm (M=5.10, 1×1 binning) and a bar pattern phantom validated those measurements. A slight degradation in the spatial resolution was observed when comparing the image reconstruction with 511 and 918 projections, whose effect was visible at the lower frequencies. Small value of MRecon has little or no impact on the in-plane spatial resolution owning to a stable system. Large value of MRecon has implications on the spatial resolution and it was evident when comparing the bar pattern images reconstructed with MRecon=1.25 and 2.5. The cross plane MTF curves showed that the spatial resolution increased as the slice thickness decreased. The cutoff frequencies in the projection imaging mode yielded slightly higher values as compared to the in-plane and cross plane modes at all the geometric magnifications (M). At M=5.10, the cutoff resolution of the projection and cross plane on an ultra-high contrast resolution bar chip phantom were 14.9 lp/mm and 13-13.5 lp/mm. Due to the finite focal spot size of the x-ray tube, the detector blur and the reconstruction kernel functions, the system's spatial resolution does not reach the limiting spatial resolution as defined by the Nyquist's detector criteria with an ideal point source. The geometric magnification employed in the micro CTs provide a tradeoff between field of view and spatial resolution for a wide range of applications.

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Section: Methodsmentioning

confidence: 99%

“…1(b). In standard imaging science dialect, SSP is the LSF along the z-direction of the CT scanner [23]. Similar to most of the in vivo based micro CT systems, this system also come with projection or live mode imaging for different purposes.…”

Section: Methodsmentioning

confidence: 99%

Investigation of spatial resolution characteristics of an in vivo microcomputed tomography system

Ghani

Zhou

Ren

et al. 2016

Nuclear Instruments and Methods in Physics Research Section A:

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“…This information is necessary not only in terms of the level of CNR needed for a robust TTF measurement (i.e., >15, noted above), but also with respect to the fact that in nonlinear CT systems, TTF can be a function of contrast and noise. Note that z‐axis TTF and the slice sensitivity profile reflect similar performance attributes of a CT system. This analysis is illustrated in Fig.…”

Section: Operational Performancementioning

confidence: 99%

Performance evaluation of computed tomography systems: Summary of AAPM Task Group 233

et al. 2019

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Background: The rapid development and complexity of new x-ray computed tomography (CT) technologies and the need for evidence-based optimization of image quality with respect to radiation and contrast media dose call for an updated approach towards CT performance evaluation. Aims: This report offers updated testing guidelines for testing CT systems with an enhanced focus on the operational performance including iterative reconstructions and automatic exposure control (AEC) techniques. Materials and Methods: The report was developed based on a comprehensive review of best methods and practices in the scientific literature. The detailed methods include the assessment of 1) CT noise (magnitude, texture, nonuniformity, inhomogeneity), 2) resolution (task transfer function under varying conditions and its scalar reflections), 3) task-based performance (detectability, estimability), and 4) AEC performance (spatial, noise, and mA concordance of attenuation and exposure modulation). The methods include varying reconstruction and tube current modulation conditions, standardized testing protocols, and standardized quantities and metrology to facilitate tracking, benchmarking, and quantitative comparisons. Results: The methods, implemented in cited publications, are robust to provide a representative reflection of CT system performance as used operationally in a clinical facility. The methods include recommendations for phantoms and phantom image analysis. Discussion: In line with the current professional trajectory of the field toward quantitation and operational engagement, the stated methods offer quantitation that is more predictive of clinical performance than specification-based approaches. They can pave the way to approach performance testing of new CT systems not only in terms of acceptance testing (i.e., verifying a device meets predefined specifications), but also system commissioning (i.e., determining how the system can be used most effectively in clinical practice). Conclusion: We offer a set of common testing procedures that can be utilized towards the optimal clinical utilization of CT imaging devices, benchmarking across varying systems and times, and a basis to develop future performance-based criteria for CT imaging.

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“…The boundary of the vessel edge was defined using a visual estimation of the full width at half maximum of the slicesensitivity profile. 12 The background SI was estimated by the average SI in 2 circular ROIs (with an area of 15-20 mm 2 ) placed symmetrically on both sides of the background on the same MIP image. The FF was calculated according to the following formula: FF ϭ (Distal SI Ϫ Background SI) / (Proximal SI Ϫ Background SI).…”

Section: Fractional Flow Measured On 3d-tof-mramentioning

confidence: 99%

Association of Fractional Flow on 3D-TOF-MRA with Cerebral Perfusion in Patients with MCA Stenosis

Ge¹,

Zhao²,

Zhou³

et al. 2019

AJNR Am J Neuroradiol

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BACKGROUND AND PURPOSE: Fractional flow measured on 3D-TOF-MRA was proposed to quantify cerebral hemodynamic changes in patients with artery stenosis. We investigated the association between fractional flow and cerebral perfusion changes in patients with symptomatic MCA stenosis. MATERIALS AND METHODS: This prospective study was approved by the institutional review board, and all participants provided written informed consent. From June 2015 to May 2018, four hundred twenty-nine patients with symptomatic intracranial arterial stenosis were consecutively recruited and underwent conventional brain MR imaging, 3D-TOF-MRA, and brain CTP. A total of 91 patients with unilateral M1 segment stenosis of the MCA and a stenosis degree of 50%ϳ99% were included in the analysis. Fractional flow was measured by comparing distal and proximal signal intensity changes across the stenosis on 3D-TOF-MRA. The cutoff value for fractional flow for discriminating between normal perfusion and hypoperfusion was obtained from the receiver operating characteristic curve. Associations between fractional flow and hypoperfusion were assessed using univariate and multivariate analyses. RESULTS: The receiver operating characteristic curve showed a significant fractional flow threshold value at 0.90 (sensitivity, 70.1%; 95% CI, 55.9%-81.2%; specificity, 69.6%; 95% CI, 47.6%-84.1%). Participants with a fractional flow of Յ0.90 were independently associated with cerebral hypoperfusion downstream from the stenosis site (adjusted OR, 3.68; 95% CI, 1.63-11.62; P ϭ .027). CONCLUSIONS: Fractional flow measured on 3D-TOF-MRA may serve as a noninvasive and practical tool for determining the cerebral hypoperfusion in patents with symptomatic MCA stenosis. ABBREVIATIONS: FF ϭ fractional flow; ICAS ϭ intracranial arterial stenosis; rMTT ϭ relative (affected side/contralateral side) MTT; rTTP ϭ relative (affected side/contralateral side) TTP; SAG-C ϭ stressed autoregulation compensated; SAG-D ϭ stressed autoregulation decompensated; SI ϭ signal intensity

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Evaluation of techniques for slice sensitivity profile measurement and analysis

Cited by 17 publications

References 48 publications

Investigation of spatial resolution characteristics of an in vivo microcomputed tomography system

Investigation of spatial resolution characteristics of an in vivo microcomputed tomography system

Performance evaluation of computed tomography systems: Summary of AAPM Task Group 233

Association of Fractional Flow on 3D-TOF-MRA with Cerebral Perfusion in Patients with MCA Stenosis

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