Apparent diffusion coefficient (ADC) histogram analysis: differentiation of benign from malignant parotid gland...

Area of Science:

• Radiology
• Oncology
• Medical Imaging

Background:

• Parotid gland tumors are common, and accurate differentiation is crucial for treatment.
• Distinguishing between pleomorphic adenomas, Warthin tumors, and malignant tumors can be challenging.
• Apparent diffusion coefficient (ADC) histogram analysis shows promise in characterizing tissue properties.

Purpose of the Study:

• To evaluate the effectiveness of whole-lesion ADC histogram analysis in differentiating common parotid gland tumors.
• To assess the diagnostic performance of various ADC histogram parameters using readout-segmented diffusion-weighted imaging (RESOLVE).

Main Methods:

• Retrospective analysis of 80 patients with parotid gland tumors (pleomorphic adenomas, Warthin tumors, malignant tumors).
• Acquisition of RESOLVE diffusion-weighted imaging data on a 3T MR system.
• Calculation of eleven whole-lesion histogram parameters and receiver operating characteristic (ROC) curve analysis.

Main Results:

• Nine ADC histogram parameters were statistically significant for differentiating all three tumor groups (p < 0.05).
• High diagnostic efficiency (AUC > 0.97) was observed for ADC_mean, ADC_50th, and skewness in distinguishing pleomorphic adenomas from Warthin tumors.
• Significant differences were also found between pleomorphic adenomas and malignant tumors, with ADC_mean, ADC_10th, and ADC_50th showing high efficiency (AUC > 0.84).

Conclusions:

• Whole-lesion ADC histogram analysis is a valuable tool for differentiating common parotid gland tumors.
• Specific ADC histogram parameters demonstrate high diagnostic performance in distinguishing between benign and malignant parotid lesions.