Perfusion MR imaging detection of carcinoma arising from preexisting salivary gland pleomorphic adenoma by computer-assisted analysis of time-signal intensity maps

Abstract

Tumor perfusion can be evaluated by analyzing the time-signal intensity curve (TIC) after dynamic contrast-enhanced (DCE) MR imaging. Accordingly, TIC profiles are characteristic of some benign and malignant salivary gland tumors. A carcinoma ex pleomorphic adenoma (CXPA) arises from a long-standing pleomorphic adenoma (PA) and has a distinctive prognostic risk depending on the tumor growth potential such as invasion beyond the preexisting capsule. Differentiating CXPA from PA can be very challenging. In this study, we have attempted to discriminate CXPA from PA based on a two-dimensional TIC mapping algorithm. TIC mapping analysis was performed on 8 patients with CXPA and 20 patients with PA after dynamic contrast-enhanced (DCE) MR imaging using a 1.5-T MR system. The TIC profiles obtained were automatically categorized into 5 types based on the enhancement ratio, maximum time, and washout ratio (Type 1 TIC with flat profile, Type 2 TIC with slow uptake, Type 3 TIC with rapid uptake and a low washout ratio, Type 4 TIC with rapid uptake and a high washout ratio, and Type 5 TIC not otherwise specific). The percentage tumor areas with each of the 5 TIC types were compared between CXPAs and PAs. Stepwise differentiation and cluster analysis using multiple TIC cut-off thresholds distinguished CXPAs from PAs with 75% sensitivity, 95% specificity, 86% accuracy, and 86% positive and 90% negative predictive values, when tumors with ≤1.1% Type 1 and ≥15% Type 4, or those with ≤1.1% Type 1, ≥78.1% Type 2, ≥16.1% Type 3, and <15% Type 4, or those with >1.1% Type 1, ≥78.1% Type 2, and ≥16.1% Type 3 areas were diagnosed as CXPAs. The overall TIC profiles predicted some aggressive CXPA growth patterns. These results suggest that stepwise differentiation based on TIC mapping is helpful in differentiating CXPAs from PAs.

Imaging biomarkers in the diagnosis of salivary gland tumors: the value of lesion/parenchyma ratio of perfusion-MR pharmacokinetic parameters

“…Most of the literature studies investigating the potential of perfusion and diffusion MR imaging in the characterization of salivary gland tumors [10][11][12][13][14][15] described different imaging post-processing methods that are often not readily available for clinical routine. On the other hand, software applications using extended Tofts model [19] for permeability analysis of MR images nowadays are quite popular and generally easy to handle.…”

“…However, FNAC presents limited sensitivity and a high number of non-diagnostic samples [7] while CNB, despite the diagnostic superiority [8], is still not considered the reference standard due to invasiveness, possible false negatives, and risk of tumor seeding [9]. For these reasons, many efforts are recently put into determining if multiparametric and advanced MR sequences such as diffusion-weighted imaging (DwI) and dynamic contrast-enhanced (DCE) imaging could have a role in characterizing salivary gland tumors [10][11][12][13] and differentiating benign from malignant lesions [12][13][14][15], with various results.…”