Signal detection and location-dependent noise in cone-beam computed tomography using the spatial definition of the Hotelling SNR.

PURPOSE: Quality assurance in computed tomography (CT) is commonly performed with the Fourier-based modulation transfer function (MTF) and the noise variance, while more recently the noise power spectrum (NPS) has increased in popularity. The Fourier-based methods make assumptions such as shift-invariance and cyclostationarity. These assumptions are violated in real clinical systems and consequently are expected to result in systematic errors. A spatial approach, based on the object transfer matrix (T) and the covariance matrix (K) theory, does not require these assumptions and can provide a more general description of the imaging system. In this paper, the authors present an experimental methodology and data treatment for quality assessment of a lab cone-beam CT system by comparing the spatial with the Fourier approach in 2D reconstructed slices. METHODS: In order to have control over all experimental parameters and image reconstruction, a bench-top flat-panel-based cone-beam CT scanner and a cylindrical water-filled poly(methyl methacrylate) (PMMA) phantom were used for the noise measurements. An aluminum foil inserted in the water phantom enabled the estimation of the line response function (LRF) with a limited number of assumptions. The authors evaluated the spatial blur, the noise and the signal-to-noise ratio (SNR) using the spatial approach as well as the Fourier-based approach. In order to evaluate the degree of noise nonstationarity of their cone-beam CT system, the authors evaluated both the local and global CT noise properties and compared them using both approaches. RESULTS: For the laboratory cone-beam CT, the location-dependent noise evaluation showed that in addition to the noise variance, the NPS and covariance eigenvector symmetry depend on the location in the image. The estimated signal transfer was similar for both approaches. Unlike the Fourier approach which uses the same exponential wave function basis for both MTF and NPS, the eigenvectors of T and K were significantly different. CONCLUSIONS: By using the eigenvectors of the noise and object transfer to characterize the system, the spatial approach provides additional information to the Fourier approach and is therefore an important tool for a thorough understanding of a CT system.

Material-specific transfer function model and SNR in CT.

This study presents an analytical model for the edge spread function (ESF) of a clinical CT system that allows reliable fits of noisy ESF data. The model was used for the calculation of the material-specific transfer function TF and an estimation of the signal transfer and the signal-to-noise ratio (SNR) in 2D. Images of the Catphan phantom were acquired with a clinical Siemens Somatom Sensation Cardiac 64 CT scanner combining four different x-ray tube outputs (40, 150, 250 and 350 mAs) with four different reconstruction filters, which covered the range from very smooth (B10s) to very sharp (B70s). The images of the high- and mid-contrast cylinders of the phantom's 'Geometry and Sensitometry' module (air, Teflon, Delrin and PMP) were used to sample material-specific ESF curves. The ESF curves were fitted with the analytical model we developed based on a linear combination of Boltzmann and Gaussian functions. The analytical model of the ESF was used to obtain the Fourier-based material-specific transfer function TF, as well as the spatial-domain point spread function (PSF). TF was subsequently used to estimate the signal transfer, which was compared to the actual reconstructed image of a 3.0 mm diameter Teflon pin. The noise power spectrum (NPS) was calculated from images of a uniform water phantom under the same technique parameters. The task-specific SNR was calculated for all technique parameters from the model-based TF, the measured NPS and simulated 3 mm diameter disc signals modeling the aforementioned materials. Bootstrapping was performed to estimate the standard deviation of the TF and the SNR. The analytical model we developed accurately captured the features of the CT ESF data. The coefficient of determination R(2), a metric that describes the goodness of the fit, had a median value of 0.9995, and decreased for low tube output, low contrast and the sharp reconstruction filter. Our analysis showed that ESF, PSF and TF depended not only on the reconstruction filter, but also on the tube output and the material of the cylinders. For B40s and B70s, the TF of Delrin was significantly higher than the TF of other materials in the frequency range of 0.4-0.9 mm(-1). The estimated signal transfer agreed well with the actual reconstructed image of the Teflon pin. For the technique parameters we used the SNR values ranged between [64, 320], [64, 281], [37, 137] and [33, 117] for air, Teflon, Delrin and PMP respectively. While for high-contrast materials the smoothest reconstruction filter resulted in the highest SNR, for mid-contrast materials the standard filter gave the best results. The presented approach provides an accurate, analytical description of the material-specific ESF, PSF and TF as well as an estimate of the signal transfer. The transfer function TF together with the NPS and simulated signals allow the calculation of a task-specific SNR.

CT head-scan dosimetry in an anthropomorphic phantom and associated measurement of ACR accreditation-phantom imaging metrics under clinically representative scan conditions.

PURPOSE: To measure radiation absorbed dose and its distribution in an anthropomorphic head phantom under clinically representative scan conditions in three widely used computed tomography (CT) scanners, and to relate those dose values to metrics such as high-contrast resolution, noise, and contrast-to-noise ratio (CNR) in the American College of Radiology CT accreditation phantom. METHODS: By inserting optically stimulated luminescence dosimeters (OSLDs) in the head of an anthropomorphic phantom specially developed for CT dosimetry (University of Florida, Gainesville), we measured dose with three commonly used scanners (GE Discovery CT750 HD, Siemens Definition, Philips Brilliance 64) at two different clinical sites (Walter Reed National Military Medical Center, National Institutes of Health). The scanners were set to operate with the same data-acquisition and image-reconstruction protocols as used clinically for typical head scans, respective of the practices of each facility for each scanner. We also analyzed images of the ACR CT accreditation phantom with the corresponding protocols. While the Siemens Definition and the Philips Brilliance protocols utilized only conventional, filtered back-projection (FBP) image-reconstruction methods, the GE Discovery also employed its particular version of an adaptive statistical iterative reconstruction (ASIR) algorithm that can be blended in desired proportions with the FBP algorithm. We did an objective image-metrics analysis evaluating the modulation transfer function (MTF), noise power spectrum (NPS), and CNR for images reconstructed with FBP. For images reconstructed with ASIR, we only analyzed the CNR, since MTF and NPS results are expected to depend on the object for iterative reconstruction algorithms. RESULTS: The OSLD measurements showed that the Siemens Definition and the Philips Brilliance scanners (located at two different clinical facilities) yield average absorbed doses in tissue of 42.6 and 43.1 mGy, respectively. The GE Discovery delivers about the same amount of dose (43.7 mGy) when run under similar operating and image-reconstruction conditions, i.e., without tube current modulation and ASIR. The image-metrics analysis likewise showed that the MTF, NPS, and CNR associated with the reconstructed images are mutually comparable when the three scanners are run with similar settings, and differences can be attributed to different edge-enhancement properties of the applied reconstruction filters. Moreover, when the GE scanner was operated with the facility's scanner settings for routine head exams, which apply 50% ASIR and use only approximately half of the 100%-FBP dose, the CNR of the images showed no significant change. Even though the CNR alone is not sufficient to characterize the image quality and justify any dose reduction claims, it can be useful as a constancy test metric. CONCLUSIONS: This work presents a straightforward method to connect direct measurements of CT dose with objective image metrics such as high-contrast resolution, noise, and CNR. It demonstrates that OSLD measurements in an anthropomorphic head phantom allow a realistic and locally precise estimation of magnitude and spatial distribution of dose in tissue delivered during a typical CT head scan. Additional objective analysis of the images of the ACR accreditation phantom can be used to relate the measured doses to high contrast resolution, noise, and CNR.

Experimental estimates of peak skin dose and its relationship to the CT dose index using the CTDI head phantom.

A straightforward method is presented to estimate peak skin doses (PSDs) delivered by computed tomography (CT) scanners. The measured PSD values are related to the well-known volume CT dose index (CTDI(vol)), displayed on the console of CT scanners. PSD measurement estimates were obtained, in four CT units, by placing radiochromic film on the surface of a CTDI head phantom. Six different X-ray tube currents including the maximum allowed value were used to irradiate the phantom. PSD and CTDI(vol) were independently measured and later related to the CTDI(vol) value displayed on the console. A scanner-specific relationship was found between the measured PSD and the associated CTDI(vol) displayed on the console. The measured PSD values varied between 27 and 136 mGy among all scanners when the routine head scan parameters were used. The results of this work allow relating the widely used CTDI(vol) to an actual radiation dose delivered to the skin of a patient.