MR imaging-based risk stratification scoring system to predict clinical outcomes in carotid body tumors
Abhishek Mahajan1,2,3, Atif Shaikh3, Shreya Shukla3
1Department of Imaging, The Clatterbridge Cancer Centre NHS Foundation Trust, Liverpool, United Kingdom.
Objectives:
This study aims to evaluate the role of pretherapy MRI in predicting outcomes in carotid body tumors and propose a grading system for high- and low-risk characteristics.
Materials And Methods:
A retrospective observational study of 44 patients with 51 lesions was carried out from year 2005 to 2020. MR images were reviewed for characteristics of carotid body tumor, and a score was given that was correlated with intra- and postoperative findings. The various other classifications and our proposed Mahajan classification were compared with Shamblin's classification. The area under the curve and ROC curves were used to present the accuracy of different predictive models.
Results:
Our scoring system allotted a score of 0 to 15 on the basis of MRI characteristics, with scores calculated for patients in our study ranging from 0 to 13. Lesions with scores of 0-6 were considered low risk (45%), and scores of 7-15 were regarded as high risk for surgery (55%). The Mahajan classification stages tumors into four grades: I (10%), II (20%), IIIa (8%), and IIIb (62%). The frequency of vascular injury was 50% in category I and 64% in category IIIb. The frequency of cranial nerve injury was 50%, 66%, and 27% in categories I, II, and IIIb.
Conclusion:
The Mahajan classification of CBTs evaluates high-risk factors like the distance of the tumor from the skull base and the angle of contact with ICA, which form the major predictors of neurovascular damage and morbidity associated with its surgery. Though the Shamblin classification of CBT is the most widely accepted classification, our proposed Mahajan classification system provides an imaging-based alternative to prognosticate surgical candidates preoperatively.
