Effects of computing parameters and measurement locations on the estimation of 3D NPS in non-stationary MDCT images

A comparative analysis of head computed tomography scans protocols and thyroid dosimetry

Computed Tomography (CT) is currently one of the most widely used imaging modalities for disease identification, benefiting numerous patients with its advanced technology. However, there is a concern regarding its inappropriate use, which can lead to higher radiation doses in patients and consequently increase the potential risks of developing stochastic effects. Therefore, it is crucial to explore methodologies for optimizing patient doses, particularly in organs with higher radiosensitivity. Within this context, the aim of the proposed study is to compare absorbed dose and noise among different head CT scans using a polymethylmethacrylate (PMMA) phantom, proposing a better relationship between image quality and dose reduction for protocol and thyroid in head CT scans. The tests were conducted using head acquisition protocols on two CT scanners: a GE LightSpeed VCT with 64 channels and a Toshiba CT with 4 channels. The PMMA head-neck phantom consisted of two cylinders, one with a diameter of 16 cm and another with a diameter of 11 cm was used in this work. Radiochromic films and an ionization chamber were also utilized. The study evaluated discrepancies in CT scans, including Noise Power Spectrum (NPS), dose profiles, and punctual doses in thyroid. Protocols P1A and P2B had the lowest and highest CTDIvol values, respectively. Radiochromic films facilitated precise dose analysis, identifying position 12 with the highest dose. NPS analysis revealed variations in noise distribution between the protocols.

Task-Based Model Observer Assessment of A Partial Model-Based Iterative Reconstruction Algorithm in Thoracic Oncologic Multidetector CT

To investigate the impact of a partial model-based iterative reconstruction (ASiR-V) on image quality in thoracic oncologic multidetector computed tomography (MDCT), using human and mathematical model observers. Twenty cancer patients examined with regular-dose thoracic-abdominal-pelvic MDCT were retrospectively included. Thoracic images reconstructed using a sharp kernel and filtered back-projection (reference) or ASiR-V (0-100%, 20% increments; follow-up) were analysed by three thoracic radiologists. Advanced quantitative physical metrics, including detectability indexes of simulated 4-mm-diameter solid non-calcified nodules and ground-glass opacities, were computed at regular and reduced doses using a custom-designed phantom. All three radiologists preferred higher ASiR-V levels (best = 80%). Increasing ASiR-V substantially decreased noise magnitude, with slight changes in noise texture. For high-contrast objects, changing the ASiR-V level had no major effect on spatial resolution; whereas for lower-contrast objects, increasing ASiR-V substantially decreased spatial resolution, more markedly at reduced dose. For both high- and lower-contrast pulmonary lesions, detectability remained excellent, regardless of ASiR-V and dose levels, and increased significantly with increasing ASiR-V levels (all p < 0.001). While high ASiR-V levels (80%) are recommended to detect solid non-calcified nodules and ground-glass opacities in regular-dose thoracic oncologic MDCT, care must be taken because, for lower-contrast pulmonary lesions, high ASiR-V levels slightly change noise texture and substantially decrease spatial resolution, more markedly at reduced dose.

Practical approaches to approximating MTF and NPS in CT with an example application to task-based observer studies

PURPOSE

To investigate two methods of approximating the Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) in computed tomography (CT) for a range of scan parameters, from limited image acquisitions.

METHODS

The two methods consist of 1) using a linear systems approach to approximate the NPS for different filtered backprojection (FBP) kernels with a filter function derived from the kernel ratio of determined MTFs and 2) using an empirical fitted model to approximate the MTF and NPS. In both cases a scaling function accounts for variations in mAs and kV. The two methods of approximating the MTF/NPS are further investigated by comparing image quality figure of merits (FOM) d' and AUC calculated using approximations of the MTF/NPS and MTF/NPS that have been determined for different mAs/kV levels and reconstruction kernels.

RESULTS

The greatest RMSE for NPS approximated for a range of mAs/kVp/convolution kernels using both methods and compared to determined NPS was 0.05 of the peak value. The RMSE for FOM with the kernel ratio method were at most 0.1 for d' and 0.01 for the AUC. Using the empirical model method, the RMSE for FOM were at most 0.02 for d' and 0.001 for the AUC.

CONCLUSIONS

The two methods proposed in this paper can provide a convenient way of approximating the MTF and NPS for use in, among other things, mathematical observer studies. Both methods require a relatively small number of direct determinations of NPS from scan acquisitions to model the NPS/MTF for arbitrary mAs and kV.

Association between power law coefficients of the anatomical noise power spectrum and lesion detectability in breast imaging modalities

Previous research has demonstrated that a parameter extracted from a power function fit to the anatomical noise power spectrum, β, may be predictive of breast mass lesion detectability in x-ray based medical images of the breast. In this investigation, the value of β was compared with a number of other more widely used parameters, in order to determine the relationship between β and these other parameters. This study made use of breast CT data sets, acquired on two breast CT systems developed in our laboratory. A total of 185 breast data sets in 183 women were used, and only the unaffected breast was used (where no lesion was suspected). The anatomical noise power spectrum computed from two-dimensional region of interests (ROIs), was fit to a power function (NPS(f) = α f(-β)), and the exponent parameter (β) was determined using log/log linear regression. Breast density for each of the volume data sets was characterized in previous work. The breast CT data sets analyzed in this study were part of a previous study which evaluated the receiver operating characteristic (ROC) curve performance using simulated spherical lesions and a pre-whitened matched filter computer observer. This ROC information was used to compute the detectability index as well as the sensitivity at 95% specificity. The fractal dimension was computed from the same ROIs which were used for the assessment of β. The value of β was compared to breast density, detectability index, sensitivity, and fractal dimension, and the slope of these relationships was investigated to assess statistical significance from zero slope. A statistically significant non-zero slope was considered to be a positive association in this investigation. All comparisons between β and breast density, detectability index, sensitivity at 95% specificity, and fractal dimension demonstrated statistically significant association with p < 0.001 in all cases. The value of β was also found to be associated with patient age and breast diameter, parameters both related to breast density. In all associations between other parameters, lower values of β were associated with increased breast cancer detection performance. Specifically, lower values of β were associated with lower breast density, higher detectability index, higher sensitivity, and lower fractal dimension values. While causality was not and probably cannot be demonstrated, the strong, statistically significant association between the β metric and the other more widely used parameters suggest that β may be considered as a surrogate measure for breast cancer detection performance. These findings are specific to breast parenchymal patterns and mass lesions only.