Histopathological assessment of optic nerve invasion guided by radiological findings in enucleated globes with retinoblastoma.

BACKGROUND

Optic nerve (ON) invasion is an important high-risk feature, and an indicator for neoadjuvant chemotherapy and prognosis. We aim through this study to correlate the detected-ON invasion by Magnetic resonance imaging (MRI) with the corresponding confirmed histopathological level of invasion.

METHODS

A retrospective study of enucleated globes with the diagnosis of retinoblastoma received in the histopathology department(s) from January 2015 to December 2016 (2 years). Slides were reviewed for ON invasion assessment, charts were reviewed for basic demographic data. All patients underwent MRI under sedation upon diagnosis and MRI findings were collected for the above correlation.

RESULTS

A total of 38 patients were included: 21 males and 17 females. 29 (77.3%) had unilateral involvement, 7 (18.4%) had bilateral involvement and 2 cases had trilateral disease. The overall mean age at diagnosis was 22.63 ± 15.15 months. Histopathological examination revealed ON invasion in 28 cases (74%) distributed as follows: prelaminar (31.6%), laminar (18.4%), and post-laminar (23.7%). MRI confirmed post-laminar ON invasion in 8 cases (true positive) but failed to detect this in 1 case. Additionally, MRI detected another 8 cases of ON invasion that were false positive on histopathology (accuracy: 63.3%; sensitivity: 88.9%; specificity: 72.4%; Positive predictive value (PPV): 50%; Negative predictive value (NPV): 95.5%).

CONCLUSIONS

MRI is found to be less sensitive in evaluating prelaminar and laminar ON invasion (0.0 and 42.9%) compared to post-laminar invasion (88.9%). MRI has generally better specificity in detecting ON invasion irrespective of the invasion level. In our study, obtaining deeper and/or additional histologic sections from the other surface of the tissue block in cases where a post-laminar ON invasion by MRI is found but not confirmed histopathologically in routine sections is essential to avoid missing such an important high-risk feature.