Technical Note: Validation of TG 233 phantom methodology to characterize noise and dose in patient CT data

Abstract

Purpose: Phantoms are useful tools in diagnostic CT, but practical limitations reduce phantoms to being only a limited patient surrogate. Furthermore, a phantom with a single cross sectional area cannot be used to evaluate scanner performance in modern CT scanners that use dose reduction techniques such as automated tube current modulation (ATCM) and iterative reconstruction (IR) algorithms to adapt x-ray flux to patient size, reduce radiation dose, and achieve uniform image noise. A new multisized phantom (Mercury Phantom, MP) has been introduced, representing multiple diameters. This work aimed to ascertain if measurements from MP can predict radiation dose and image noise in clinical CT images to prospectively inform protocol design. Methods: The adult MP design included four different physical diameters (18.5, 23.0, 30.0, and 37.0 cm) representing a range of patient sizes. The study included 1457 examinations performed on two scanner models from two vendors, and two clinical protocols (abdominopelvic with and chest without contrast). Attenuating diameter, radiation dose, and noise magnitude (average pixel standard deviation in uniform image) was automatically estimated in patients and in the MP using a previously validated algorithm. An exponential fit of CTDI vol and noise as a function of size was applied to patients and MP data. Lastly, the fit equations from the phantom data were used to fit the patient data. In each patient distribution fit, the normalized root mean square error (nRMSE) values were calculated in the residuals' plots as a metric to indicate how well the phantom data can predict dose and noise in clinical operations as a function of size. Results: For dose across patient size distributions, the difference between nRMSE from patient fit and MP model data prediction ranged between 0.6% and 2.0% (mean 1.2%). For noise across patient size distributions, the nRMSE difference ranged between 0.1% and 4.7% (mean 1.4%). Conclusions: The Mercury Phantom provided a close prediction of radiation dose and image noise in clinical patient images. By assessing dose and image quality in a phantom with multiple sizes, protocol parameters can be designed and optimized per patient size in a highly constrained setup to predict clinical scanner and ATCM system performance.

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“…It is known that different vendors pursue different strategies in the management of dose and image quality across clinical populations. 24,25 However, the differences in dose magnitude are not large enough to affect a population risk study. Lastly, this study only focused on radiation risk associated with imaging.…”

Structured mentorship program for the ABR international medical graduates alternate pathway for medical physicists in diagnostic imaging

“…The candidate completed the six clinical rotations, performed 51 equipment evaluations, and three clinical quality improvement projects, which led to four conference presentations and two peer-reviewed publications. 5,6 Furthermore, the candidate passed ABR Part-1 exam in 2018. Throughout the mentorship, bi-monthly, recurring individual meetings were scheduled between the candidate and the Facility Supervisor to review SMP progress, including rotation competencies and projects.…”

Image quality assessment of deep learning image reconstruction in computed tomography using tube current modulation: a phantom study

“…Object size modulation phantom Mercury 4.0 Phantom (Gammex, Middleton, WI, USA) was developed to evaluate the TCM installed in a CT system [20,21]. This phantom was approved by the American Association of Physicists in Medicine (AAPM) Task Group (TG) 233 [21].…”

“…Solomon et al [14] used the Mercury Phantom V3.0 to evaluate the image quality of DLIR and evaluated different object sizes using a xed tube current (FTC), which was necessary to maintain measurement accuracy. However, the Mercury Phantom is useful only for clinical evaluation of TCM [15]. Thus, in this study, we assumed a clinical CT of the torso, and the task of image quality assessment targeted two low-to medium-contrast inserts of polystyrene (≈Δ50HU) and water (≈Δ90HU) in the Mercury Phantom.…”