Added value of spectral parameters for the assessment of lymph node metastasis of lung cancer with dual-layer spectral detector computed tomography

Abstract

Background: Lymph node (LN) metastasis is an important factor affecting the treatment of lung cancer. The purpose of this article was to investigate the benefits of dual-layer spectral detector computed tomography (SDCT) for the evaluation of metastatic LNs in lung cancer.Methods: Data from 93 patients with lung cancer who underwent dual-phase enhanced scanning with SDCT were retrospectively analyzed. According to the pathological findings, 166 LNs were grouped as metastatic (n=80) or non-metastatic (n=86). LNs in station 4 (n=80) and station 7 (n=35) accounted for the majority of the LNs (approximately 69.23%). The short-axis diameter of the LN, arterial enhancement fraction (AEF), normalized iodine concentration (NIC), and the slope of the spectral Hounsfield unit curve (λ HU ) during the arterial phase (AP) and venous phase (VP) were measured. The Mann-Whitney U test was used to statistically compare these quantitative parameters. Receiver operating characteristic (ROC) curves were plotted to identify the cutoff values, and decision curve analysis (DCA) was performed to determine the net benefit of each parameter. The diagnostic performance, obtained by combining the short-axis diameter with each of the above parameters, was also studied. Results:The short-axis LN diameter, AEF, NIC, and λ HU during the AP and VP all showed significant differences between the metastatic and non-metastatic groups (P<0.05). Of the parameters, the AEF had the greatest diagnostic efficiency for metastatic LNs [area under the ROC curve (AUC) AEF =0.885] with a threshold of 86.40%. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and 95% confidence interval were 90.00%, 89.53%, 88.89%, 90.59%, and 0.830-0.944, respectively.When the quantitative parameters were combined with the short-axis diameter, the AUCs of the parameters, except the AEF, were significantly improved (P<0.05). Conclusions:The iodine quantitative parameters from SDCT, such as the AEF, demonstrated high diagnostic performances in the differentiation of metastatic and non-metastatic LNs.

Diagnosis of Metastatic Lymph Nodes in Patients With Hepatocellular Carcinoma Using Dual-Energy Computed Tomography

“…Imaging studies are usually the first choice for evaluating suspected metastatic lymph nodes. It has been shown that metastatic lymph nodes are significantly larger than nonmetastatic lymph nodes 14–16 . However, our study showed that the sensitivity and specificity of lymph node size in diagnosing metastatic lymph nodes were both quite low.…”

“…It has been shown that metastatic lymph nodes are significantly larger than nonmetastatic lymph nodes. [14][15][16] However, our study showed that the sensitivity and specificity of lymph node size in diagnosing metastatic lymph nodes were both quite low. The size or morphology of lymph nodes can be affected by several factors, such as inflammation and chemotherapy, 17 and may not reflect the nature of lymph node metastasis.…”

Value of spectral computed tomography-derived quantitative parameters based on full volume analysis in the diagnosis of benign/malignant and pathological subtypes of solitary pulmonary nodules

“…This approach is being increasingly used clinically and has high diagnostic accuracy for many organ diseases (13). Several studies have demonstrated that spectral CT has potential value for distinguishing benign and malignant lung lesions, tissue subtypes, and lymphatic metastases (14)(15)(16)(17)(18). However, most previous studies (14)(15)(16)(17)(18) have obtained the various parameters from regions of interest (ROIs) drawn manually on the largest lesion slices.…”

“…Several studies have demonstrated that spectral CT has potential value for distinguishing benign and malignant lung lesions, tissue subtypes, and lymphatic metastases (14)(15)(16)(17)(18). However, most previous studies (14)(15)(16)(17)(18) have obtained the various parameters from regions of interest (ROIs) drawn manually on the largest lesion slices. This may lead to measurement sampling bias, which is often the only parameter used and cannot reflect information on the tissue characteristics of the entire lesion and, therefore, cannot adequately assess intralesional heterogeneity.…”

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

“…In dual-layer spectral detector CT (DLCT), which is a recent, novel energy-spectrum imaging method, the mutual interference between different energy rays is avoided and the accuracy of data is guaranteed ( 5 ). It also has the characteristics of synchronization, homology, and simultaneity, which can produce better data registration and image consistency at different stages, thus reducing measurement error ( 6 ).…”