Eye (London, England) · 2025
Radiomics to predict high risk features in intraocular retinoblastoma.
СтатьяНазвание и аннотация: Перевод в очереди
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Ramasubramanian Aparna, Lu Kun-Han, Dalvin Lauren A, Riemann Monique, Abruzzo Todd, Wong Chi Wah, Tomasetti Cristian, Moser Justin, Libling William Adam, Korn Ron
Аннотация
INTRODUCTION: Detecting high risk characteristics in intraocular retinoblastoma is important for determining metastatic risk.
METHODS: In this pilot study, preoperative Magnetic Resonance Imaging (MRI) radiomics data were compared to high-risk histopathology features after enucleation. A total of 2142 MRI features were extracted, and relevant features were selected to create predictive models for optic nerve and choroidal invasion.
RESULTS: Among 31 eyes of 29 patients, 14 eyes had optic nerve invasion and 6 had choroidal invasion. The predictive model for optic nerve (ON) invasion achieved Area under the receiver operating characteristic curve (AUROC) of 0.85 (accuracy 0.84, sensitivity 0.93, specificity 0.76) using the radiomic features of maximum 2D diameter slice on the unaffected optic nerve (ON), correlation of grey level co-occurrence matrix (GLCM) on the affected ON, and kurtosis of affected ON. For choroidal invasion the model achieved AUROC of 0.86 (accuracy 0.94, sensitivity 0.83, specificity 0.96) using the radiomic features of sphericity of affected vitreous and surface volume ratio of affected ON.
CONCLUSIONS: Radiomics could be useful to guide the decision of globe salvage versus enucleation in advanced retinoblastoma. Larger studies are required to validate and enhance this predictive model.
METHODS: In this pilot study, preoperative Magnetic Resonance Imaging (MRI) radiomics data were compared to high-risk histopathology features after enucleation. A total of 2142 MRI features were extracted, and relevant features were selected to create predictive models for optic nerve and choroidal invasion.
RESULTS: Among 31 eyes of 29 patients, 14 eyes had optic nerve invasion and 6 had choroidal invasion. The predictive model for optic nerve (ON) invasion achieved Area under the receiver operating characteristic curve (AUROC) of 0.85 (accuracy 0.84, sensitivity 0.93, specificity 0.76) using the radiomic features of maximum 2D diameter slice on the unaffected optic nerve (ON), correlation of grey level co-occurrence matrix (GLCM) on the affected ON, and kurtosis of affected ON. For choroidal invasion the model achieved AUROC of 0.86 (accuracy 0.94, sensitivity 0.83, specificity 0.96) using the radiomic features of sphericity of affected vitreous and surface volume ratio of affected ON.
CONCLUSIONS: Radiomics could be useful to guide the decision of globe salvage versus enucleation in advanced retinoblastoma. Larger studies are required to validate and enhance this predictive model.