Evaluation of a second-generation monoenergetic reconstruction algorithm for lesion contrast and venous invasion in pancreatic ductal adenocarcinomas

Eur Rev Med Pharmacol Sci. 2019 Nov;23(21):9341-9350. doi: 10.26355/eurrev_201911_19427.

Abstract

Objective: At lower energy levels, virtual monochromatic imaging by dual-energy computed tomography improves lesion attenuation but produces greater image noise with the conventional monoenergetic reconstruction algorithm (Mono). Recently, a second-generation algorithm (Mono+) was introduced to overcome this limitation. We compared the quality of images obtained with these algorithms and investigated the optimal energy selection for pancreatic ductal adenocarcinomas (PDACs).

Patients and methods: Image data from 54 PDAC cases were generated at 40, 50, 60, 70, and 80 keV using Mono and Mono+. Image quality was objectively assessed by comparing the signal-to-noise ratios (SNRs), noise, and the contrast-to-noise ratios (CNRs) at different keV levels and between these algorithms at the same keV level. Lesion conspicuity and venous invasion were subjectively assessed.

Results: For Mono, the mean pancreas and tumour SNRs peaked at 70 keV (p<0.001). The noise increased as the energy level decreased (p<0.001). CNRtumour remained unchanged. For Mono+, the mean pancreas SNR peaked at 40 keV (p<0.001). The mean tumour SNR and noise remained unchanged. The tumour CNRs were highest at 40 keV (4.9 times the CNR of Mono 40 keV, p<0.001). Subjectively, lesion conspicuity was best at Mono+ 40 keV (p<0.001) and it showed higher diagnostic performance levels on venous invasion assessment against Mono.

Conclusions: Mono+ produced better image quality, and 40 keV is recommended for the diagnosis of PDAC.

MeSH terms

  • Algorithms*
  • Carcinoma, Pancreatic Ductal / diagnostic imaging*
  • Humans
  • Image Processing, Computer-Assisted*
  • Pancreatic Neoplasms / diagnostic imaging*
  • Retrospective Studies
  • Tomography, X-Ray Computed*