An MRI-based radiomics nomogram for preoperative prediction of Ki-67 index in nasopharyngeal carcinoma: a two-center study

Background: The expression level of Ki-67 in nasopharyngeal carcinoma (NPC) affects the prognosis and treatment options of patients. Our study developed and validated an MRI-based radiomics nomogram for preoperative evaluation of Ki-67 expression levels in nasopharyngeal carcinoma (NPC).

Methods: In all, 133 patients with pathologically-confirmed (post-operatively) NPC who underwent MRI examination in one of two medical centers. Data from one medical center (n=105; Ki-67: ≥50% [n=57], <50% [n=48]) formed the training set, while data from another medical center (n=28; Ki-67: ≥50% [n=15], <50% [n=13]) formed the test set. Clinical data and routine MRI results were reviewed to determine significant predictive factors. The minimum absolute shrinkage and selection operator method was used to select key radiomics features to form a radiomics signatures from resonance imaging (MRI), and a radiomics score (Rad-score) was calculated. Subsequently, a radiomics nomogram was established using a logistic regression (LR) algorithm. The predictive performance of the nomogram was evaluated using operating characteristics curve (ROC), decision curve analysis (DCA), and the area under the curve (AUC).

Results: Five radiomics features were selected to build the radiomics signature. The radiomics nomogram incorporating the clinical factors and radiomics signature showed favorable predictive value for expression level of Ki-67, with AUC 0.841 (95% confidence intervals: 0.654 -0.951) for the test set. Decision curve analysis showed that the nomogram outperformed a clinical model in terms of clinical usefulness.

Conclusions: The radiomics nomogram based on MRI effectively predicted the pre-surgical expression level of Ki-67.