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Updated: May 5, 2026

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy
Published on: January 10, 2025
Kurtosis and skewness assessments of solid lung nodule density histograms: differentiating malignant from benign
Ayano Kamiya1, Sadayuki Murayama, Hisashi Kamiya
1Department of Radiology, Graduate School of Medical Science, University of the Ryukyus, 207 Uehara, Nishihara, Okinawa, 903-0215, Japan, ayano1242004@yahoo.co.jp.
Purpose:
The purpose of our study was to assess pulmonary nodule characteristics using density histogram kurtosis and skewness and to distinguish malignant from benign nodules.
Materials And Methods:
Ninety-three lung nodules on CT were analyzed, including 72 malignant and 21 benign nodules. They were completely solid or solid with limited ground-glass opacity. Based on their CT characteristics, nodules were categorized into type A, homogeneous nodules with uniform internal structures and clear margins, and type B, inhomogeneous nodules with heterogeneous structures or uneven margins. Kurtosis and skewness were calculated from density histograms to compare type A and B nodules and malignant and benign nodules. Receiver-operating characteristic (ROC) curves were generated to assess kurtosis and skewness for discriminating between different nodule types.
Results:
Type A nodules (n = 35) had greater kurtosis and reduced skewness (p < 0.001) compared to type B nodules (n = 58). Malignant tumor kurtosis was greater than that of benign nodules (type A, p < 0.05; type B, p = 0.001). Type B malignant tumors had reduced skewness compared to benign nodules (p < 0.05). ROC curves provided relatively high values for the area under the curve (0.71-0.83).
Conclusion:
Kurtosis and skewness assessments of density histograms may be useful for differentiating malignant from benign nodules.
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