Preliminary Application of High-Definition Computed Tomographic Gemstone Spectral Imaging in Lung Cancer

Abstract

High-definition computed tomographic GSI technique might be helpful to differentiate lung cancer from lung benign lesions by providing qualitative and quantitative information.

Can spectral computed tomography imaging improve the differentiation between malignant and benign pulmonary lesions manifesting as solitary pure ground glass, mixed ground glass, and solid nodules?

“…Our results were inconsistent with previous research in that the two parameters, λHU and IC, in benign nodules were lower than in malignant nodules . There are several reasons to explain this paradoxical condition.…”

“…Another related condition, benign nodules were principally inflammatory (61.1%). The IC was highest in the active inflammatory group, followed by the malignant group, which has been confirmed by previous studies . The active inflammatory nodule is stimulated by inflammatory agents, which leads to the arteriole and blood capillary becoming more obviously dilated and the vascular permeability increased.…”

“…Moreover, the monochromatic spectral images of single energy levels provide information about the attenuation changes in different materials as a function of X‐ray photon energy . Spectral CT material decomposition images enable the iodine component of SPNs to be measured on iodine‐enhanced images, which is considered comparable to the real value (net enhancement) of the extent of enhancement …”

“…2,4 Spectral CT material decomposition images enable the iodine component of SPNs to be measured on iodine-enhanced images, which is considered comparable to the real value (net enhancement) of the extent of enhancement. 2,3,5 To identify lung nodules using spectral CT images, several studies have used multiple parameters, including iodine concentrations (IC), normalized iodine concentrations (NIC), CT numbers of 40 or 70 keV monochromatic images (CT40keV or CT70keV), and the slope of the spectral attenuation curve (λHU) to distinguish among inflammatory, granuloma, benign nodules, and malignant tumors. [5][6][7][8][9][10][11] These studies showed that spectral CT is one of the most promising imaging techniques with potential clinical applications, although controversy and disagreement remain.…”

“…2,3,5 To identify lung nodules using spectral CT images, several studies have used multiple parameters, including iodine concentrations (IC), normalized iodine concentrations (NIC), CT numbers of 40 or 70 keV monochromatic images (CT40keV or CT70keV), and the slope of the spectral attenuation curve (λHU) to distinguish among inflammatory, granuloma, benign nodules, and malignant tumors. [5][6][7][8][9][10][11] These studies showed that spectral CT is one of the most promising imaging techniques with potential clinical applications, although controversy and disagreement remain. Thus, our aim was to prospectively evaluate the usefulness of these parameters (IC, NIC, CT40keV, CT70keV, and λHU) for differentiating malignant and benign SPNs manifesting as pure ground glass nodules (pGGNs), mixed ground glass nodules (mGGNs), and solid nodules (SNs).…”