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

Abstract

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 (CTDI_vol), contrast-to-noise ratio (CNR) and lesion detectability index (d’) were compared between the standard protocol and ATPS examinations.

Results

CTDI_vol 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.

Appendix 1 Automatic Tube Potential Selection (ATPS) (CARE kV, Siemens Healthcare)

CARE kV is a commercially available ATPS software tool which automatically selects a combination of tube potential and tube current according to patient size, prescribed image quality, and examination indication. The patient size is estimated by the use of the CT radiograph localizer (topogram). To define the examination indication and to prescribe the reference image quality, the CARE kV tool uses three parameters: the quality reference mAs, the reference kVp, and the examination type. The quality reference mAs is needed by the automated exposure control system (CARE Dose 4D, Siemens Healthcare). The reference kVp is to be set according to an institution’s established routine clinical protocols, which in conjunction with the defined quality reference mAs are known to provide consistent image quality for a reference patient weighting 70 kg. The examination indication is defined with an incremental slider bar with settings 1 to 12. Lower settings (1–4) are best suited for non-contrast examinations where CARE kV expects the user will accept little or no increase in image noise. Mid-range settings (5–8) are best suited for contrast-enhanced examinations where CARE kV assumes the user will accept a small increase in image noise that will be balanced by a boost of iodine contrast when a lower kVp is selected. Higher settings (9–12) are best suited for CTA examinations where the user expects gains in iodine contrast at lower kVp to offset increased image noise at the lower kVp values. CARE kV aims to maintain the desired CNR as defined by the reference kVp and quality reference mAs.

Appendix 2 Image Analysis with IMQUEST analysis software

Image analysis software developed specifically for the proprietary phantom was used for image analysis. Square ROIs were drawn by a single investigator (40 mm side length for contrast evaluation and 50 mm side length for noise evaluation) with semiautomated measurement of image contrast (contrast = HU_insert - HU_{polytethylene body}) and image noise (noise = pixel standard deviation of ROIs placed within the uniform phantom body). Contrast-to-noise ratios (CNR = contrast_insert /noise) were calculated for the iodine and soft tissue inserts. A previously validated lesion detectability index, d’, for the iodine and soft tissue inserts was calculated, presented in a simplified format:

$$ \mathrm{d}{'}^2 = {\left(\int \int\ {\mathrm{W}}^2 \cdot {\mathrm{TTF}}^2 \cdot {\mathrm{E}}^2\right)}^2/\ \left(\int \int\ {\mathrm{W}}^2 \cdot {\mathrm{TTF}}^2 \cdot {\mathrm{E}}^4 \cdot \mathrm{N}\mathrm{P}\mathrm{S}\right) $$

where W is the task function, set for the detection of a reference 5 mm designer nodule [31]; TTF is the task transfer function, a measure of system resolution as a function of spatial frequency; E is the Eye Filter, reflecting human visual response characteristics at a typical 60 cm viewing distance; and NPS is the noise power spectrum, a measure of the magnitude and texture characteristics of noise. The d’ values were adjusted to represent a reference feature contrast of 50 Hounsfield Units at 120 kVp for the 12 cm phantom.