Turkish Neurosurgery
Added Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Predicting Response to Somatostatin Analogs in Patients with Acromegaly
Emine Sebnem Durmaz1, Burak Kocak2, Pinar Kadioglu3, Nil Comunoglu4, Mustafa Onur Ulu5, Naci Kocer1, Civan Islak1, Osman Kizilkilic1
1Istanbul University-Cerrahpasa, Cerrahpasa School of Medicine, Radiology, Istanbul,
2Istanbul Training and Research Hospital, Radiology, Istanbul,
3Istanbul University-Cerrahpasa, Cerrahpasa School of Medicine, Endocrinology, Istanbul,
4Istanbul University-Cerrahpasa, Cerrahpasa School of Medicine, Pathology, Istanbul,
5Istanbul University-Cerrahpasa, Cerrahpasa School of Medicine, Neurosurgery, Istanbul,
DOI: 10.5137/1019-5149.JTN.26003-19.1
Aim:To investigate the added value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) sequences in predicting somatostatin analog (SSA) responses in patients with acromegaly.Material and Methods:This study included 55 active acromegaly patients with macroadenoma. Mean and maximum signal intensities were measured using region of interests in T2-weighted (T2W) and DCE-MRI sequences. Semi-quantitative values indicating relative signal intensity ratios and contrast-enhanced kinetics were obtained. Bivariate and multivariate analyses were used to determine whether the pathological granulation pattern of adenomas (dense versus others) was associated with patients’ demographic variables and semi-quantitative MRI parameters.Results:Three parameters formed the logistic model, χ2(3)=23.278, p<0.0001: age (odds ratio [OR]=1.08), hypointensity of adenomas in T2W images (OR=15.45), and high maximum enhancement ratio in the second interval (ER2 max) values (OR=2195.74). The overall accuracy of this model was 85.45% with an area under the curve of 0.880. Sensitivity, specificity, positive predictive, and negative predictive values of the model were 68.75%, 92.31%, 78.58%, and 87.8%, respectively.Conclusion:In patients with newly diagnosed acromegaly, the model created based on the relative T2W signal intensity, patient’s age, and ER2 max parameter from DCE-MRI sequences might be used to more accurately predict SSA responses.
Corresponding author : Osman Kizilkilic