Use of dual-layer spectral detector computed tomography in the diagnosis of pancreatic neuroendocrine neoplasms

Abstract

Purpose: To explore the optimal energy level of dual-layer spectral detector computed tomography (DLCT) images of pancreatic neuroendocrine neoplasms (pNENs) and investigate the value in their detection.

Methods: This retrospective analysis included 134 pNEN patients with 136 lesions; they underwent contrast-enhanced DLCT scanning with histopathological confirmation of pNENs. Virtual monoenergetic images (VMI) of 40-100 keV, iodine concentration map (IC map), Z-effective atomic number map (Zeff map), and conventional images were analysed. The optimal energy level was obtained by comparing the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The lesion detection rates of DLCT and conventional images were compared. Subjective image analysis was performed by two readers who assessed the image quality and lesion conspicuity on a 5-point scale.

Results: The SNR of VMIs from 40 to 80 keV (arterial phase, P < 0.001; venous phase, P < 0.05) and CNR from 40 to 60 keV (arterial and venous phases, each P < 0.05) were higher than that of conventional images; VMI_40keV showed the highest SNR and CNR. There was a good inter-reader agreement between the two reviewers (Kappa values > 0.61); the scores of Zeff and IC maps were higher than those of conventional images and VMI_40keV (P < 0.05). The detection performance of DLCT images was better than conventional images.

Conclusions: The VMI_40keV demonstrated the best CNR and SNR of pNENs compared to other VMIs. Zeff and IC maps improve objective image quality and reader preference compared to conventional images. These findings could possess important clinical implications in formulating treatment strategies.

Keywords: Dual-layer spectral detector computed tomography (DLCT); Neuroendocrine cells; Pancreatic neuroendocrine tumours; Virtual monoenergetic images.