In:
Physics in Medicine & Biology, IOP Publishing, Vol. 66, No. 11 ( 2021-06-07), p. 115003-
Abstract:
In the context of reducing the patient dose coming from CT scanner examinations without penalizing the diagnosis, the assessment of both patient dose and image quality (IQ) with relevant metrics is crucial. The present study represents the first stage in a larger work, aiming to compare and optimize CT protocols using dose and IQ new metrics. We proposed here to evaluate the capacity of the Non-PreWhitening matched filter with an eye (NPWE) model observer to be a robust and accurate estimation of IQ. We focused our work on two types of clinical tasks: a low contrast detection task and a discrimination task. We designed a torso-shaped phantom, including Plastic Water ® slabs with cylindrical inserts of different diameters, sections and compositions. We led a human observer study with 13 human observers on images acquired in multiple irradiation and reconstruction scanning conditions (voltage, pitch, slice thickness, noise level of the reconstruction algorithm, energy level in dual-energy mode and dose), to evaluate the behavior of the model observer compared to the human responses faced to changing conditions. The model observer presented the same trends as the human observers with generally better results. We rescaled the NPWE model on the human responses by scanning conditions (kVp, pitch, slice thickness) to obtain the best agreement between both observer types, estimated using the Bland-Altman method. The impact of some scanning parameters was estimated using the correct answer rate given by the rescaled NPWE model, for both tasks and each insert size. In particular, the comparison between the dual-energy mode at 74 keV and the single-energy mode at 120 kVp showed that, if the 120 kVp voltage provided better results for the smallest insert at the lower doses for both tasks, their responses were equivalent in many cases.
Type of Medium:
Online Resource
ISSN:
0031-9155
,
1361-6560
DOI:
10.1088/1361-6560/abfad8
Language:
Unknown
Publisher:
IOP Publishing
Publication Date:
2021
detail.hit.zdb_id:
1473501-5
SSG:
12
