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MRI criteria for the diagnosis of pleomorphic adenoma: a validation study
Soroush Zaghi1, Leenoy Hendizadeh1, Tony Hung1
1Department of Head and Neck Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Objectives:
To validate an MRI algorithm characteristic of pleomorphic adenoma (PA).
Study Design:
Cross-sectional analysis.
Setting:
Academic tertiary-care medical center.
Methods:
A radiologic algorithm for the MRI diagnosis of PA was developed on the basis of five "high probability" criteria that all must be fulfilled for the MRI to qualify as a positive test result: bright T2-signal, sharp margins, heterogeneous nodular enhancement, lobulated contours, T2-dark rim. We then identified MRI images from our institutional database to test the diagnostic accuracy of the proposed algorithm.
Results:
A total of 103 parotidectomy cases with adequate MRI studies were identified (pleomorphic adenoma n=41, mucoepidermoid carcinoma n=11, Warthin's tumor n=8, adenoid cystic carcinoma n=6, oncocytoma n=6, acinic cell carcinoma n=5, salivary duct carcinoma n=5, and other n=21). Eighteen of 21 cases that met all five "high probability" MRI criteria were consistent with PA on final histopathology; 3 were consistent with carcinoma. MRI had a specificity of 95.1% [95% confidence interval: 85.6-98.7%] and sensitivity of 43.9% [95% C.I.: 28.8-60.1%] for PA. The positive predictive value was 85.7% [95% C.I.: 70.4-100%] and the negative predictive value was 71.9% [95% C. I.: 62.0-81.9%]. The overall diagnostic accuracy was 74.8% [95% C.I.: 66.2-83.3%].
Conclusion:
A "high probability" MRI is about 95% specific for pleomorphic adenoma. A subset of patients with MRI imaging that is highly suggestive of PA may reliably avoid further workup. The value of MRI in this setting is especially useful if preoperative fine needle aspiration is not readily available. A significant proportion of PAs, however, have indeterminate imaging features that overlap considerably with other benign and malignant lesions.
Insights
This study validates an MRI algorithm for diagnosing pleomorphic adenoma (PA), finding it highly specific (95%) but with moderate sensitivity. This imaging tool can help identify PA cases, potentially reducing the need for further invasive procedures.
Area of Science:
- Radiology
- Oncology
- Pathology
Background:
- Pleomorphic adenoma (PA) is the most common salivary gland tumor.
- Accurate preoperative diagnosis of PA is crucial for appropriate management.
- Magnetic Resonance Imaging (MRI) is a key imaging modality for salivary gland lesions.
Purpose of the Study:
- To validate a specific MRI algorithm for diagnosing pleomorphic adenoma (PA).
- To assess the diagnostic accuracy, including specificity and sensitivity, of the proposed MRI criteria for PA.
Main Methods:
- Cross-sectional analysis of 103 parotidectomy cases with MRI studies.
- Development of an MRI algorithm based on five "high probability" criteria for PA.
- Evaluation of the algorithm's performance against histopathological diagnoses.
Main Results:
- The MRI algorithm demonstrated high specificity (95.1%) for pleomorphic adenoma.
- Sensitivity for PA was moderate (43.9%), with a positive predictive value of 85.7%.
- Overall diagnostic accuracy was 74.8%, with some PAs showing indeterminate imaging features.
Conclusions:
- The validated MRI algorithm is highly specific for pleomorphic adenoma, aiding in diagnosis.
- A subset of patients with highly suggestive MRI findings may avoid further workup.
- The algorithm's utility is notable when fine needle aspiration is unavailable, though indeterminate features exist.
