Rectal neuroendocrine tumor

Endoscopic treatment and management of rectal neuroendocrine tumors less than 10 mm in diameter

Rectal neuroendocrine tumors (rNETs) measuring less than 10 mm in diameter are defined as small rNETs. Due to the low risk of distant invasion and metastasis, endoscopic treatments, including modified endoscopic mucosal resection, endoscopic submucosal dissection, and other transanal surgical procedures, are effective. This review article proposes a follow-up plan according to the size and histopathology of the tumor after operation.

UNDERWATER ENDOSCOPIC MUCOSAL RESECTION FOR SMALL RECTAL NEUROENDOCRINE TUMORS

BACKGROUND

A common site of neuroendocrine tumors (NETs) is the rectum. The technique most often used is endoscopic mucosal resection with saline injection. However, deep margins are often difficult to obtain because submucosal invasion is common. Underwater endoscopic mucosal resection (UEMR) is a technique in which the bowel lumen is filled with water rather than air, precluding the need for submucosal lifting.

OBJECTIVE

This study aimed to evaluate the efficacy and safety of UEMR for removing small rectal neuroendocrine tumors (rNETs).

METHODS

Retrospective study with patients who underwent UEMR in two centers. UEMR was performed using a standard colonoscope. No submucosal injection was performed. Board-certified pathologists conducted histopathologic assessment.

RESULTS

UEMR for small rNET was performed on 11 patients (nine female) with a mean age of 55.8 years and 11 lesions (mean size 7 mm, range 3-12 mm). There were 9 (81%) patients with G1 rNET and two patients with G2, and all tumors invaded the submucosa with only one restricted to the mucosa. None case showed vascular or perineural invasion. All lesions were removed en bloc. Nine (81%) resections had free margins. Two patients had deep margin involvement; one had negative biopsies via endoscopic surveillance, and the other was lost to follow-up. No perforations or delayed bleeding occurred.

CONCLUSION

UEMR appeared to be an effective and safe alternative for treatment of small rNETs without adverse events and with high en bloc and R0 resection rates. Further prospective studies are needed to compare available endoscopic interventions and to elucidate the most appropriate endoscopic technique for resection of rNETs.

Prediction of the World Health Organization Grade of rectal neuroendocrine tumors based on CT histogram analysis

OBJECTIVES

To investigate the diagnostic value of contrast-enhanced computed tomography (CECT) histogram analysis in predicting the World Health Organization (WHO) grade of rectal neuroendocrine tumors (R-NETs).

MATERIALS AND METHODS

A total of 61 (35 G1, 12 G2, 10 G3, and 4 NECs) patients who underwent preoperative CECT and treated with surgery to be confirmed as R-NETs were included in this study from January 2014 to May 2019. We depicted ROIs and measured the CECT texture parameters (mean, median, 10th, 25th, 75th, 90th percentiles, skewness, kurtosis, and entropy) from arterial phase (AP) and venous phase (VP) images by two radiologists. We calculated intraclass correlation coefficient (ICC) and compared the histogram parameters between low-grade (G1) and higher grade (HG) (G2/G3/NECs) by applying appropriate statistical method. We obtained the optimal parameters to identify G1 from HG using receiver operating characteristic (ROC) curves.

RESULTS

The capability of AP and VP histogram parameters for differentiating G1 from HG was similar in several histogram parameters (mean, median, 10th, 25th, 75th, and 90th percentiles) (all p < 0.001). Skewness, kurtosis, and entropy on AP images showed no significant differences between G1 and HG (p = 0.853, 0.512, 0.557, respectively). Entropy on VP images was significantly different (p = 0.017) between G1 and HG, however, skewness and kurtosis showed no significant differences (p = 0.654, 0.172, respectively). ROC analysis showed a good predictive performance between G1 and HG, and the 75th (AP) generated the highest area under the curve (AUC = 0.871), followed by the 25th (AP), mean (VP), and median (VP) (AUC = 0.864). Combined the size of tumor and the 75th (AP) generated the highest AUC.

CONCLUSIONS

CECT histogram parameters, including arterial and venous phases, can be used as excellent indicators for predicting G1 and HG of rectal neuroendocrine tumors, and the size of the tumor is also an important independent predictor.

Incidental diagnosis of very small rectal neuroendocrine neoplasms: when should endoscopic submucosal dissection be performed? A single ENETS centre experience

PURPOSE

The management of small (≤5 mm) rectal neuroendocrine neoplasms (r-NENs), incidentally removed during colonoscopy, still remains under debate.

METHODS

All consecutive patients affected by r-NENs from January 2013 to December 2017 were studied. The inclusion criteria were: (1) patients having an incidental pathological diagnosis of very small (≤5 mm) polypoid r-NENs; (2) patients treated with a standard polypectomy as first-line therapy and (3) patients treated by endoscopic submucosal dissection (ESD) as salvage therapy. The primary endpoint was to identify the factors related to residual disease after a standard polypectomy. The secondary endpoint was to calculate the accuracy of endoscopic ultrasound (EUS), grading and size in predicting residual disease.

RESULTS

Starting from a prospective database of 123 consecutive patients affected by r-NENs, only 31 met the inclusion criteria. A final pathological examination of an ESD specimen showed residual disease in 7 out of 31 patients (22.6%). A multivariate analysis showed that the size of the polyps was the only independent factor related to residual disease with an odds ratio of 8.7 ± 7.5 (P = 0.013) for each millimetre. The accuracy of EUS, grading and tumour size (3.1 mm cut-off point) and area under the curves were 0.661 ± 0.111, 0.631 ± 0.109 and 0.821 ± 0.109, respectively.

CONCLUSIONS

When the r-NEN polyp was larger than 3 mm, ESD was indicated. Unlike the size of the tumour, grading and EUS features did not accurately predict residual disease.