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$Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy$

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Published on: January 10, 2025

Spectral CT Analysis of Solitary Pulmonary Nodules for Differentiating Malignancy from Benignancy: The Value of

Linyu Wu¹, Guoquan Cao¹, Liang Zhao¹

¹Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325035, China.

Biomed Research International

|January 11, 2019

Abstract

Objective:

The objective is to assess the value of spatial distribution difference in iodine concentration between malignant and benign solitary pulmonary nodules (SPNs) by analyzing multiple parameters of spectral CT.

Methods:

Sixty patients with 39 malignant nodules and 21 benign nodules underwent chest contrast CT scans using spectral imaging mode during pulmonary arterial phase (PP), arterial phase (AP), and venous phase (VP). Iodine concentrations of proximal and distal regions in pulmonary nodules on iodine-based material decomposition images were recorded. Normalized iodine concentration (NIC) and the differences in NIC between the proximal and the distal regions (dNIC) were calculated. The two-sample t-test and Mann-Whitney U-test were performed to compare the multiple parameters generated from spectral CT between malignant and benign nodules. Receiver operating characteristic (ROC) curves were generated to calculate sensitivity and specificity.

Results:

NIC in the proximal region (NIC_pro) and NIC in the distal region (NIC_dis) between malignant and benign nodules at AP (NIC_pro, P=0.012; NIC_dis, P=0.024), and VP (NIC_pro, P=0.005; NIC_dis, P =0.004) were significantly different. NIC_pro at PP (P = 0.037) was also found significantly different between malignant and benign nodules; however, no significant differences were found in NIC_dis at PP (P = 0.093). In addition, the dNIC of malignant nodules was significantly higher than that of benign ones at PP (median and interquartiles (0.31, 0.11, 0.57 versus -0.26, -0.5, -0.1); p≤0.001), AP (mean dNIC, 0.093 ±0.094 versus -0.075±0.060; p≤0.001), and VP (mean dNIC, 0.171±0.137 versus -0.183±0.127; p≤0.001). The sensitivity and specificity (93%, 95%, respectively) of dNIC during VP were higher than other parameters, with a threshold value of -0.07.

Conclusions:

Spectral CT imaging with multiple parameters such as NIC_pro, NIC_dis, and dNIC may be a new method for differentiating malignant SPNs from benign ones.

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