Exploring the Haralick Texture Parameters of MRI and CT for the Diagnosis of Value of Benign and Malignant Pulmonary Nodules
Objective This study leverages Haralick texture parameters to analyze image characteristics of benign and malignant pulmonary nodules,assessing the diagnostic efficacy of MRI and CT imaging in differentiating these conditions.Methods A total of 40 patients with pulmonary subsolid nodules from Sanya Central Hospital were selected for the study.Based on pathological results,the patients were divided into a benign group(n=20)and a malignant group(n=20).Each patient underwent both CT and MRI scans.From the clearest lesion images,five texture features were extracted:angular second moment,contrast,autocorrelation,inverse difference moment,and entropy.One-way ANOVA was used to compare the differences in these texture features between the benign and malignant groups.Results In the CT group,entropy was not statistically significant(P＞0.05),while the other texture parameters were statistically significant.In the T1WI and T2WI groups,both inverse difference moment and entropy were statistically significant(P＜0.05),whereas angular second moment,contrast,and autocorrelation were not statistically significant(P＞0.05).In the DWI group,only contrast was statistically significant(P＜0.05).Comparing the AUC values across groups,the CT group generally had higher AUC values,with the highest AUC value observed for entropy in the T1WI group(AUC=0.970).Conclusion CT texture analysis still has certain advantages,but incorporating multiple MRI sequences can improve the diagnostic accuracy for distinguishing between benign and malignant pulmonary nodules.
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