Risk Factor Analysis of Lymph Node Metastasis for Rectal Neuroendocrine Tumors: Who Needs a Radical Resection in Rectal Neuroendocrine Tumors Sized 1-2 cm?

BACKGROUND: Rectal neuroendocrine tumors (NETs) have malignant potential, and lymph node (LN) or distant metastases can occur; however, treatment of NETs 1-2 cm in size is controversial. OBJECTIVE: This study aimed to identify predictive factors for LN metastasis and prognostic factors for recurrence of rectal NETs, especially tumors 1‒2 cm in size. METHODS: Between October 2004 and November 2020, 453 patients underwent endoscopic or surgical treatment for rectal NETs in Seoul National University Hospital. The data on these patients were prospectively collected in our database and reviewed retrospectively. In cases of local excision, we evaluated LN metastasis with radiologic imaging, including computed tomography or magnetic resonance imaging before treatment and during the follow-up periods. RESULTS: LN metastasis was observed in 40 patients (8.8%). A higher rate of LN metastasis was observed in larger-sized tumors, advanced T stage, lymphovascular invasion (LVI), perineural invasion (PNI), and high tumor grade. In multivariable analysis, the significant risk factors for LN metastasis were tumor size (1 ≤ size < 2 cm: hazard ratio [HR] 64.07; size ≥2 cm: HR 102.37, p < 0.001) and tumor grade (G2: HR 3.63, p = 0.034; G3: HR 5.09, p = 0.044). In multivariable analysis for tumors 1-2 cm in size, the risk factor for LN metastasis was tumor grade (G2: HR 6.34, p = 0.013). CONCLUSIONS: Tumor grade and size are important predictive factors for LN metastasis. In NETs 2 cm in size, tumor grade is also important for LN metastasis, and radical resection should be considered.

Three-dimensional body composition parameters using automatic volumetric segmentation allow accurate prediction of colorectal cancer outcomes.

BACKGROUND: Parameters obtained from two-dimensional (2D) cross-sectional images have been used to determine body composition. However, data from three-dimensional (3D) volumetric body images reflect real body composition more accurately and may be better predictors of patient outcomes in cancer. This study aimed to assess the 3D parameters and determine the best predictive factors for patient prognosis. METHODS: Patients who underwent surgery for colorectal cancer (CRC) between 2010 and 2016 were included in this study. Preoperative computed tomography images were analysed using an automatic segmentation program. Body composition parameters for muscle, muscle adiposity, subcutaneous fat (SF) and abdominal visceral fat (AVF) were assessed using 2D images at the third lumbar (L3) level and 3D images of the abdominal waist (L1-L5). The cut-off points for each parameter were determined using X-tile software. A Cox proportional hazards regression model was used to identify the association between the parameters and the treatment outcomes, and the relative influence of each parameter was compared using a gradient boosting model. RESULTS: Overall, 499 patients were included in the study. At a median follow-up of 59 months, higher 3D parameters of the abdominal muscles and SF from the abdominal waist were found to be associated with longer overall survival (OS) and disease-free survival (all P < 0.001). Although the 3D parameters of AVF were not related to survival outcomes, patients with a high AVF volume and mass experienced higher rate of postoperative complications than those with low AVF volume (27.4% vs. 18.7%, P = 0.021, for mass; 27.1% vs. 19.0%, P = 0.028, for volume). Low muscle mass and volume (hazard ratio [HR] 1.959, P = 0.016; HR 2.093, P = 0.036, respectively) and low SF mass and volume (HR 1.968, P = 0.008; HR 2.561, P = 0.003, respectively), both in the abdominal waist, were identified as independent prognostic factors for worse OS. Along with muscle mass and volume, SF mass and volume in the abdominal waist were negatively correlated with mortality (all P < 0.001). Both AVF mass and volume in the abdominal waist were positively correlated with postoperative complications (P < 0.05); 3D muscle volume and SF at the abdominal waist were the most influential factors for OS. CONCLUSIONS: 3D volumetric parameters generated using an automatic segmentation program showed higher correlations with the short- and long-term outcomes of patients with CRC than conventional 2D parameters.