Diffusion-weighted magnetic resonance imaging combined with neutrophil-to-lymphocyte ratio predicts pathological response to neoadjuvant chemoradiotherapy in locally advanced esophageal squamous cell carcinoma

Background: Accurate prediction of pathologic response to neoadjuvant chemoradiotherapy (nCRT) in esophageal squamous cell carcinoma (ESCC) patients is essential for optimizing individualized treatment strategies. This study investigates the potential of diffusion-weighted magnetic resonance imaging (DWI-MRI) and the neutrophil-to-lymphocyte ratio (NLR) at baseline as predictive biomarkers for the pathologic response to nCRT in patients with ESCC.

Methods: A retrospective analysis was conducted at Zhengzhou University Affiliated Cancer Hospital on a cohort of thirty ESCC patients who underwent nCRT followed by surgery between December 2013 and July 2017. Baseline DWI-MRI parameters and hematology data were collected within one week before initiating nCRT. The NLR and average apparent diffusion coefficient (ADC) value of the tumor were calculated. Receiver operating characteristic (ROC) curves were employed to evaluate the accuracy of ADC, NLR, and a combined index in predicting the pathologic response to nCRT.

Results: Among the thirty patients, twenty exhibited a favorable pathologic response to nCRT. High ADC values (>1.86×10 mm²/s) and low NLR (≤2.31) at baseline were significantly associated with a positive pathologic response in ESCC patients. ROC analysis revealed area under the curves (AUCs) of 0.750 and 0.758 for ADC value and NLR, respectively, with optimal cut-off values of 1.86×10⁻³ mm²/s [sensitivity: 80.0%, specificity: 70.0%, positive predictive value (PPV): 84.2%, negative predictive value (NPV): 63.6%] and 2.31 (sensitivity: 75.0%, specificity: 80.0%, PPV: 88.2%, NPV: 61.5%). The combined index demonstrated an improved sensitivity (95.0%) and NPV (87.5%) at an optimal threshold of 0.48, yielding an AUC of 0.840.

Conclusions: In conclusion, the pre-treatment ADC-NLR index is a promising biomarker that may guide personalized nCRT strategies in ESCC by identifying patients for treatment modification, a potential that now requires validation in prospective trials to impact clinical care.