To assess the diagnostic accuracy of nerve thickening on MRI to predict early-stage postlaminar optic nerve invasion (PLONI) in retinoblastoma. Furthermore, this study aimed to incorporate measurements into a multiparametric model for radiological determination of PLONI.
In this retrospective multicenter case-control study, high-spatial-resolution 3D T2-weighted MR images were used to measure the distal optic nerve. Histopathology was the reference standard for PLONI. Two neuroradiologists independently measured the optic nerve width, height, and surface at 0, 3, and 5 mm from the most distal part of the optic nerve. Subsequently, PLONI was scored on contrast-enhanced T1-weighted and 3D T2-weighted images, blinded for clinical data. Optic nerve measurements with the highest diagnostic accuracy for PLONI were incorporated into a prediction model for radiological determination of PLONI.
One hundred twenty-four retinoblastoma patients (median age, 22 months [range, 0-113], 58 female) were included, resulting in 25 retinoblastoma eyes with histopathologically proven PLONI and 206 without PLONI. ROC analysis of axial optic nerve width measured at 0 mm yielded the best area under the curve of 0.88 (95% confidence interval: 0.79, 0.96; p < 0.001). The optimal width cutoff was ≥ 2.215 mm, with a sensitivity of 84% (95% CI: 64, 95%) and specificity of 83% (95% CI: 75, 89%) for detecting PLONI. Combining width measurements with the suspicion of PLONI on MRI sequences resulted in a prediction model with an improved sensitivity and specificity of respectively up to 88% and 92%.
Postlaminar optic nerve thickening can predict early-stage postlaminar optic nerve invasion in retinoblastoma.
This study provides an additional tool for clinicians to help determine postlaminar optic nerve invasion, which is a risk factor for developing metastatic disease in retinoblastoma patients.
• The diagnostic accuracy of contrast-enhanced MRI for detecting postlaminar optic nerve invasion is limited in retinoblastoma patients. • Optic nerve thickening can predict postlaminar optic nerve invasion. • A prediction model combining MRI features has a high sensitivity and specificity for detecting postlaminar optic nerve invasion.