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Background Inferior mesenteric artery lymph node (station 253 node) metastasis occurs in approximately 0.3% to 13.9% of rectal cancer patients. This study examined whether carbon nanoparticles could aid in harvesting more station 253 nodes and evaluated the relationship between the number of station 253 nodes retrieved and station 253 node metastasis. Method A total of 480 consecutive rectal cancer patients were enrolled in this prospective cohort study between August 2014 and October 2018. Ninety-one patients (18.96%) received a preoperative submucosal injection of carbon nanoparticles (CN+ group), and 389 patients did not receive an injection (CN- group). The number of lymph node retrievals was analyzed, and the relevant risk factors for station 253 node metastasis were identified using univariate and multivariate analyses. Results The mean number of station 251, 252, and 253 lymph nodes and total lymph nodes retrieved in the CN+ group were higher than that retrieved in the CN- group. The percentage of patients with ≥4 station 253 nodes retrieved (54.0% vs 28.3%, P = .004) were higher in the CN+ group than in the CN- group. Retrieval of ≥4 station 253 nodes was an independent risk factor for station 253 node metastasis (OR: 2.40, 95% CI: 1.22–4.74, P = .012). Conclusion The preoperative submucosal injection of carbon nanoparticles was helpful for increasing the number of station 253 nodes harvested, and a minimum of 4 examined station 253 nodes was necessary for standard D3 lymph node dissection in rectal cancer.

Background: Collagen in the tumour microenvironment is recognized as a potential biomarker for predicting treatment response. This study investigated whether the collagen features are associated with pathological complete response (pCR) in locally advanced rectal cancer (LARC) patients receiving neoadjuvant chemoradiotherapy (nCRT) and develop and validate a prediction model for individualized prediction of pCR. Methods: The prediction model was developed in a primary cohort (353 consecutive patients). In total, 142 collagen features were extracted from the multiphoton image of pretreatment biopsy, and the least absolute shrinkage and selection operator (Lasso) regression was applied for feature selection and collagen signature building. A nomogram was developed by multivariable analysis. The performance of the nomogram was assessed with respect to its discrimination, calibration, and clinical utility. An independent cohort (153 consecutive patients) was used to validate the model. Findings: The collagen signature comprised 4 collagen features significantly associated with pCR both in the two cohorts (P