Imaging of hypodense gliotic lesions in photon counting computed tomography using virtual monoenergetic images

Abstract

Objectives

Glioses appear as hypodense lesions in non-contrast CT examinations of the head. Photon counting CT (PCCT) enables the calculation of virtual monoenergetic images (VMI). The aim of this study is to investigate in which VMI hypodense gliotic lesions can be delineated best.

Materials and methods

35 patients with an MRI-confirmed gliotic lesion and a non-contrast PCCT of the head were retrospectively included. All available VMI from 40 keV to 190 keV were calculated. In a quantitative analysis, conventional image quality parameters were calculated, in particular the contrast-to-noise ratio (CNR) of the hypodense lesion compared to the white matter. In a qualitative analysis, selected VMI were rated by experienced radiologists.

Results

The absolute maximum of CNR was 8.12 ± 5.64 in the VMI 134 keV, in post hoc testing, there were significant differences in comparison to VMI with keV ≤110 and keV ≥180 (corrected p < .05). In the qualitative analysis, there were only very slight differences in the rating of the VMI with 66 keV, 80 keV, 100 keV, and 134 keV with overall low agreement between the readers.

Conclusions

The quantitative superiority of VMI 134 keV for the delineation of hypodense gliotic lesions did not translate into a superiority in the qualitative analysis. Therefore, it remains uncertain if the reconstruction of a high keV VMIs for the detection of hypodense gliotic lesions is useful in everyday clinical practice. However, more studies, are necessary to further assess this issue.

Keywords

Photon counting computed tomography photon counting detector image quality virtual monoenergetic images hypodense lesions

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