Task-based quantification of image quality using a model observer in abdominal CT: a multicentre study

Abstract

ObjectiveWe investigated the variability in diagnostic information inherent in computed tomography (CT) images acquired at 68 different CT units, with the selected acquisition protocols aiming to answer the same clinical question.MethodsAn anthropomorphic abdominal phantom with two optional rings was scanned on 68 CT systems from 62 centres using the local clinical acquisition parameters of the portal venous phase for the detection of focal liver lesions. Low-contrast detectability (LCD) was assessed objectively with channelised Hotelling observer (CHO) using the receiver operating characteristic (ROC) paradigm. For each lesion size, the area under the ROC curve (AUC) was calculated and considered as a figure of merit. The volume computed tomography dose index (CTDIvol) was used to indicate radiation dose exposure.ResultsThe median CTDIvol used was 5.8 mGy, 10.5 mGy and 16.3 mGy for the small, medium and large phantoms, respectively. The median AUC obtained from clinical CT protocols was 0.96, 0.90 and 0.83 for the small, medium and large phantoms, respectively.ConclusionsOur study used a model observer to highlight the difference in image quality levels when dealing with the same clinical question. This difference was important and increased with growing phantom size, which generated large variations in patient exposure. In the end, a standardisation initiative may be launched to ensure comparable diagnostic information for well-defined clinical questions. The image quality requirements, related to the clinical question to be answered, should be the starting point of patient dose optimisation.Key Points• Model observers enable to assess image quality objectively based on clinical tasks.• Objective image quality assessment should always include several patient sizes.• Clinical diagnostic image quality should be the starting point for patient dose optimisation.• Dose optimisation by applying DRLs only is insufficient for ensuring clinical requirements.

A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre—A phantom study

“…In line with the findings of previous studies [ 45 – 52 ], we revealed appreciable differences in all CT image quality indices across scanners/acquisitions protocols. Noise level ( Table 4 ), peak position of NPS curve ( Table 5 ), f 50% ( Table 7 ), f 10% ( Table 7 ) and contrast threshold for a typical object size of 3 mm ( Fig 4 ) differed across scanners/acquisition protocols up to 62.8%, 42.8%, 35.7%, 23.8% and 56.7%, respectively.…”

“…Therefore, a number of CT scanners with different models or by different manufacturers are often installed in a hospital centre and used by various departments. Previous phantom studies, mainly focused on body applications, have shown that CT image quality can vary substantially across scanners [ 45 – 48 ], even when similar acquisition protocols are employed [ 49 – 52 ]. For instance, in a multicentre study, Racine et al [ 45 ] have compared the image quality of 68 scanners, in terms of only low contrast detectability, using local clinical acquisition protocols for abdominal CT examinations.…”

“…Indeed, these indices have the potential to serve as a basis for guiding and optimizing clinical protocols [ 42 – 44 ]. In this regard, previous phantom studies have shown that CT image quality can vary substantially when acquisitions are performed on different scanners [ 45 – 48 ], even using similar acquisition protocols [ 49 – 52 ]. Therefore, a careful assessment of image quality for each specific CT imaging technique and application is recommended.…”

Reconstruction of PET Images Using Cross-Entropy and Field of Experts

“…To quantitatively evaluate image quality in the Digimouse, a channelized Hoteling observer [ 23 , 24 ] was used in the context of lesion detectability. The area under the curve (AUC) was used as a figure of merit.…”

Effect of obesity on ability to lower exposure for detection of low‐attenuation liver lesions

“…Iterative reconstruction techniques have been introduced as one potential method for improving contrast‐to‐noise ratio while reducing radiation exposure in CT. However, for the assessment of CT performance with iterative reconstruction at reduced exposure, task‐based studies of image quality are preferred to studies measuring contrast‐to‐noise ratio and subjective assessments of image quality, 4 as noise equivalence and subjective imaging preference are not sufficient substitutes for diagnostic efficacy. Some examples of task‐based studies assessing CT performance at reduced exposure include those assessing the detection of renal calculi, 5–7 lung nodules, 8,9 and simulated low‐contrast low‐attenuation (LCLA) liver lesions 10,11 …”