Differential Diagnosis of Oral Salivary Gland Carcinoma and Squamous Cell Carcinoma Using Quantitative Dynamic Contrast-Enhanced MRI

TL;DR

This study shows how MRI scans can help doctors tell the difference between two types of mouth cancer before surgery.

Contribution

A new MRI-based model using specific imaging parameters improves preoperative differentiation of oral SCC and SGC.

Findings

qDCE-MRI parameters Kep, MAXSlope, and tumor location are independent predictors for distinguishing SCC from SGC.

The qDCE-MRI model outperformed clinical models with an AUC of 0.945.

All qDCE-MRI parameters showed excellent interobserver agreement.

Abstract

Background/Objectives: Preoperative differentiation between oral squamous cell carcinoma (SCC) and minor salivary gland carcinoma (SGC) remains clinically challenging due to overlapping imaging characteristics. This study aimed to develop a diagnostic model based on quantitative dynamic contrast-enhanced MRI (qDCE-MRI) parameters to distinguish SCC from SGC prior to surgery. Methods: Patients with histopathologic confirmed SCC or minor SGC who underwent preoperative 3.0T qDCE-MRI were recruited. Clinical characteristics and pharmacokinetic parameters, including volume transfer constant (Ktrans), reverse reflux rate constant (Kep), volume fraction of extravascular extracellular space (Ve), plasma volume fraction (Vp), time to peak (TTP), maximum concentration (MAXConc), maximal slope (MAXSlope), and area under the concentration-time curve (AUCt), along with the apparent diffusion coefficient (ADC), were extracted. Univariate and multivariable logistic regression analyses were performed to identify independent discriminators. Diagnostic performance was assessed using receiver operating characteristic analysis, and model comparisons were conducted with the DeLong test. Interobserver agreement was evaluated using intraclass correlation coefficients (ICC). Results: All qDCE-MRI parameters demonstrated excellent interobserver agreement (ICC range, 0.82–0.94). Multivariable analysis identified Kep (OR = 2620.172, p = 0.001), maximal slope (OR = 1.715, p = 0.024), and tumor location (OR = 5.561, p = 0.027) as independent predictors. The qDCE-MRI model achieved superior diagnostic performance compared with the clinical model (AUC: 0.945 vs. 0.747; p = 0.012). Conclusions: A qDCE-MRI–based model incorporating Kep and MAXSlope was shown to provide excellent accuracy for preoperative differentiation between oral SCC and minor SGC.

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