Radiomics for differentiating tumor deposits from lymph node metastasis in rectal cancer

ARTICLE HIGHLIGHTS

Research background

Tumor deposits (TDs) are not equivalent to lymph node (LN) metastasis (LNM) but have become independent adverse prognostic factors in patients with rectal cancer (RC). If TDs can be differentiated from LNM before therapy, individualized treatment and patient prognosis may greatly improve.

Research motivation

Currently, preoperative differentiation of TDs and LNM can be challenging.

Research objectives

To establish a radiomics model for preoperatively differentiating between TDs and LNM in patients with RC.

Research methods

The present study retrospectively enrolled 219 patients with RC [TDs⁺LNM^- (n = 89); LNM⁺TDs^- (n = 115); TDs⁺LNM⁺ (n = 15)] from a single center between September 2016 and September 2021. Single-positive patients (TDs⁺LNM^- and LNM⁺TDs^-) were classified into training (n = 163) and validation (n = 41) sets. Rad-scores were established based on the main tumor and largest peritumoral nodule. After validating Rad-score, we further evaluated its performance for diagnosing double-positive patients (i.e., TDs⁺LNM⁺) by outlining all peritumoral nodules with diameters > 3 mm (short axis).

Research results

Rad-score 1 (radiomics signature of the main tumor) had an area under the curve (AUC) of 0.768 on the training dataset and 0.700 on the validation dataset. Rad-score 2 (radiomics signature of the largest peritumoral nodule) had a higher AUC (training set: 0.940; validation set: 0.918) than Rad-score 1. For the diagnosis of double-positive patients in the mixed group [TDs⁺LNM⁺ (n = 15); single-positive (n = 15)], Rad-score 2 demonstrated moderate performance (sensitivity, 73.3%; specificity, 66.6%; and accuracy, 70%).

Research conclusions

The radiomics signature of the largest peritumoral nodule could provide individualized preoperative differentiation of TDs and LNM. Moreover, it was helpful in diagnosing patients who were TDs⁺LNM⁺.

Research perspectives

To improve the model, surgeons, radiologists, and pathologists should collaborate through prospective research to achieve node-to-node correspondence between CT images and pathological examinations in the future.