# Predicting induction chemotherapy response based on tumor-stroma ratio and pretreatment synthetic MRI in nasopharyngeal carcinoma

## TL;DR

Researchers developed a model combining tumor-stroma ratio and MRI data to predict chemotherapy response in nasopharyngeal cancer patients.

## Contribution

A novel nomogram integrating tumor-stroma ratio and synthetic MRI features for predicting induction chemotherapy response in nasopharyngeal carcinoma.

## Key findings

- The nomogram achieved an AUC of 0.836 in predicting IC response, outperforming other models.
- TSR and synthetic MRI parameters like T1map_mean and PDmap_Kurtosis were key predictors.
- High TSR was associated with better sensitivity to induction chemotherapy.

## Abstract

There is no satisfactory model for predicting the therapeutic response to chemotherapy of nasopharyngeal carcinoma (NPC). We developed a nomogram using tumor-stroma ratio (TSR) and histogram features from pretreatment synthetic magnetic resonance MRI (SyMRI) to assess induction chemotherapy (IC) response in NPC.

Data from 185 NPC patients were retrospectively collected from July 2022 to November 2023 (training cohort), and 82 NPC patients were prospectively enrolled from December 2023 to July 2024 (test cohort). A nomogram was developed to predict IC response using logistic regression based on clinicopathological and imaging features from SyMRI T1-, T2-, and proton density (PD)-weighted images, and apparent diffusion coefficient (ADC) maps. The nomogram was validated in the test cohort.

Among the 267 patients (187 males, 80 females), with a mean age of 52.2 years (ranging 43.5–58.7), 181 were responders. Histogram features from ADC and T2-map did not differentiate non-responders (all p ≥ 0.220). A clinicopathological model based on TSR and a SyMRI model using T1map_mean and PDmap_Kurtosis were developed. In the test cohort, The nomogram, combining TSR, T1map_mean, and PDmap_Kurtosis, achieved an area under the curve (AUC) of 0.836 (95% CI: 0.690–0.914), outperforming the clinicopathological model (AUC of 0.711, 95% CI: 0.577–0.809, p = 0.015) and SyMRI model (AUC of 0.774, 95% CI: 0.623–0.822, p = 0.003).

The nomogram combining TSR and histogram parameters from pretreatment SyMRI showed a good performance in predicting IC response for NPC, superior to those of clinicopathological and SyMRI models.

A nomogram based on pretreatment synthetic MRI and clinicopathological features can help in selecting patients as candidates for IC.

NPC patients with high TSR demonstrated sensitivity to IC.The nomogram, integrating TSR and synthetic MRI parameters, achieved a significantly high predictive performance.The nomogram may be a reliable tool for predicting the response to IC.

NPC patients with high TSR demonstrated sensitivity to IC.

The nomogram, integrating TSR and synthetic MRI parameters, achieved a significantly high predictive performance.

The nomogram may be a reliable tool for predicting the response to IC.