Effects of automatic tube potential selection on radiation dose index, image quality, and lesion detectability in pediatric abdominopelvic CT and CTA: a phantom study.

OBJECTIVES: To assess the effect of automatic tube potential selection (ATPS) on radiation dose, image quality, and lesion detectability in paediatric abdominopelvic CT and CT angiography (CTA). METHODS: A paediatric modular phantom with contrast inserts was examined with routine pitch (1.4) and high pitch (3.0) using a standard abdominopelvic protocol with fixed 120 kVp, and ATPS with variable kVp in non-contrast, contrast-enhanced, and CTA mode. The volume CT dose index (CTDIvol), contrast-to-noise ratio (CNR) and lesion detectability index (d') were compared between the standard protocol and ATPS examinations. RESULTS: CTDIvol was reduced in all routine pitch ATPS examinations, with dose reductions of 27-52 % in CTA mode (P < 0.0001), 15-33 % in contrast-enhanced mode (P = 0.0003) and 8-14 % in non-contrast mode (P = 0.03). Iodine and soft tissue insert CNR and d' were improved or maintained in all ATPS examinations. kVp and dose were reduced in 25 % of high pitch ATPS examinations and in none of the full phantom examinations obtained after a single full phantom localizer. CONCLUSIONS: ATPS reduces radiation dose while maintaining image quality and lesion detectability in routine pitch paediatric abdominopelvic CT and CTA, but technical factors such as pitch and imaging range must be considered to optimize ATPS benefits. KEY POINTS: ATPS automatically individualizes CT scan technique for each patient. ATPS lowers radiation dose in routine pitch pediatric abdominopelvic CT and CTA. There is no loss of image quality or lesion detectability with ATPS. Pitch and scan range impact the effectiveness of ATPS dose reduction.

Improved nuclear medicine uniformity assessment with noise texture analysis.

UNLABELLED: Because γ cameras are generally susceptible to environmental conditions and system vulnerabilities, they require routine evaluation of uniformity performance. The metrics for such evaluations are commonly pixel value-based. Although these metrics are typically successful at identifying regional nonuniformities, they often do not adequately reflect subtle periodic structures; therefore, additional visual inspections are required. The goal of this project was to develop, test, and validate a new uniformity analysis metric capable of accurately identifying structures and patterns present in nuclear medicine flood-field uniformity images. METHODS: A new uniformity assessment metric, termed the structured noise index (SNI), was based on the 2-dimensional noise power spectrum (NPS). The contribution of quantum noise was subtracted from the NPS of a flood-field uniformity image, resulting in an NPS representing image artifacts. A visual response filter function was then applied to both the original NPS and the artifact NPS. A single quantitative score was calculated on the basis of the magnitude of the artifact. To verify the validity of the SNI, an observer study was performed with 5 expert nuclear medicine physicists. The correlation between the SNI and the visual score was assessed with Spearman rank correlation analysis. The SNI was also compared with pixel value-based assessment metrics modeled on the National Electrical Manufacturers Association standard for integral uniformity in both the useful field of view (UFOV) and the central field of view (CFOV). RESULTS: The SNI outperformed the pixel value-based metrics in terms of its correlation with the visual score (ρ values for the SNI, integral UFOV, and integral CFOV were 0.86, 0.59, and 0.58, respectively). The SNI had 100% sensitivity for identifying both structured and nonstructured nonuniformities; for the integral UFOV and CFOV metrics, the sensitivities were only 62% and 54%, respectively. The overall positive predictive value of the SNI was 87%; for the integral UFOV and CFOV metrics, the positive predictive values were only 67% and 50%, respectively. CONCLUSION: The SNI accurately identified both structured and nonstructured flood-field nonuniformities and correlated closely with expert visual assessment. Compared with traditional pixel value-based analysis, the SNI showed superior performance in terms of its correlation with visual perception. The SNI method is effective for detecting and quantifying visually apparent nonuniformities and may reduce the need for more subjective visual analyses.

A methodology for image quality evaluation of advanced CT systems.

PURPOSE: This work involved the development of a phantom-based method to quantify the performance of tube current modulation and iterative reconstruction in modern computed tomography (CT) systems. The quantification included resolution, HU accuracy, noise, and noise texture accounting for the impact of contrast, prescribed dose, reconstruction algorithm, and body size. METHODS: A 42-cm-long, 22.5-kg polyethylene phantom was designed to model four body sizes. Each size was represented by a uniform section, for the measurement of the noise-power spectrum (NPS), and a feature section containing various rods, for the measurement of HU and the task-based modulation transfer function (TTF). The phantom was scanned on a clinical CT system (GE, 750HD) using a range of tube current modulation settings (NI levels) and reconstruction methods (FBP and ASIR30). An image quality analysis program was developed to process the phantom data to calculate the targeted image quality metrics as a function of contrast, prescribed dose, and body size. RESULTS: The phantom fabrication closely followed the design specifications. In terms of tube current modulation, the tube current and resulting image noise varied as a function of phantom size as expected based on the manufacturer specification: From the 16- to 37-cm section, the HU contrast for each rod was inversely related to phantom size, and noise was relatively constant (<5% change). With iterative reconstruction, the TTF exhibited a contrast dependency with better performance for higher contrast objects. At low noise levels, TTFs of iterative reconstruction were better than those of FBP, but at higher noise, that superiority was not maintained at all contrast levels. Relative to FBP, the NPS of iterative reconstruction exhibited an ~30% decrease in magnitude and a 0.1 mm(-1) shift in the peak frequency. CONCLUSIONS: Phantom and image quality analysis software were created for assessing CT image quality over a range of contrasts, doses, and body sizes. The testing platform enabled robust NPS, TTF, HU, and pixel noise measurements as a function of body size capable of characterizing the performance of reconstruction algorithms and tube current modulation techniques.