Dual-layer spectral detector computed tomography parameters can improve diagnostic efficiency of lung adenocarcinoma grading

Abstract

Background: It is difficult to distinguish the pathological grade of lung adenocarcinoma (LUAD) with traditional computed tomography (CT). The aim of this study was to assess tumor differentiation by duallayer spectral detector CT combined with morphological parameters. Methods:In this prospective study, a total of 67 patients with pathologically diagnosed LUAD were enrolled: 39 patients in the well-and moderately-differentiated group (14 and 25 patients, respectively) and 28 patients in the poorly-differentiated group. Morphological parameters, non-enhanced CT number, double-enhanced CT number, effective atomic number, monoenergetic CT images (40 and 70 keV), iodine density, and thoracic aorta iodine density of tumors were measured. The slope of the spectral curve and normalized iodine density were calculated. The diagnostic efficiency of the spectral parameters alone, and the combined spectral and morphological parameters were obtained by statistical analysis. Results:The morphological signs of LUAD (the vessel convergence sign, bronchus encapsulated air sign, and liquefactive necrosis) were higher in the poorly-differentiated group than in the well-moderatelydifferentiated group (57.1% vs. 30.8%, 40.0%; 60.7% vs. 28.2%, 32.0%; 64.3% vs. 28.2%, 24.0%; all P<0.05). There were significant differences in normalized iodine density (arterial phase: 0.10±0.04 vs. 0.12±0.05, 0.13±0.04; venous phase: 0.31±0.07 vs. 0.39±0.17, 0.40±0.17) among the poorly-differentiated group and moderately-differentiated group as well as the well-differentiated group (all P<0.05). Receiver operating characteristic (ROC) curves of the poorly-differentiated group and well-moderately-differentiated group showed that the normalized iodine density had the best diagnostic efficiency in the arterial phase, with an area under the curve (AUC) of 0.817, sensitivity of 92.9%, and specificity of 82.1% (P<0.001). The AUC increased to 0.916 when the morphological parameters were included, and sensitivity and specificity were 96.4% and 82.1% (P<0.001), respectively. Conclusions:The parameters of dual-layer spectral detector CT can help discriminate the pathological grade of LUAD. Among the spectral parameters, the normalized iodine density in the arterial phase has the best diagnostic efficiency, and the combination of spectral and morphological parameters improves the pathological grading of LUAD.

Dual-layer spectral-detector CT for predicting microsatellite instability status and prognosis in locally advanced gastric cancer

“…Tsurumaru et al speculated that intratumoral fibrosis, tumor cell infiltration patterns, and lack of neovascularity might contribute to the marked contrast enhancement in VP [ 30 , 31 ], which might result in an obvious difference in CT attenuation and DLCT parameters in VP between different types of GC. DLCT has been successfully used to detect iodine concentration in vitro [ 32 ] and reflect quantified tissue blood flow in vivo [ 33 ]. NIC may reduce variations caused by individual differences in hemodynamics between individuals, thereby more accurately reflecting tissue blood supply in the tumor [ 20 ].…”

Feasibility of using 8 mL of iodinated contrast media in cerebral computed tomographic angiography with a dual-layer spectral detector

“…Dual-layer spectral detector computed tomography (SDCT) adopts a single-source dual-detector imaging mode and simultaneously measures high-energy and low-energy projection data in 2 detector layers at the same space and angular position ( 12 - 15 ). SDCT uses an anticorrelation noise reduction algorithm to maintain low noise in all energy levels of virtual monoenergetic images (VMIs) ( 16 - 18 ).…”

The Evaluation of Quantitative Parameters of Dual-layer spectral detector CT for Discrimination of Differentiation grade, T Stage, and Lymph Node Metastasis stage of Colorectal Adenocarcinoma

“…Dual-layer spectral detector CT (SDCT) extends the single parameter scanning mode of traditional CT and is a new energy spectrum imaging method. It greatly improves the resolution of soft tissue and can provide multiple quantitative parameter information without increasing the radiation dose, such as monochromatic images (VMI) of 40 to 200 keV energy levels, iodine concentration (IC) maps, effective atomic number (Zeff) images, and slope maps [5,6].…”