Title:Identifying Tumor Deposits in Patients with Locally Advanced Rectal Cancer:
using Multiplanar High-Resolution T2WI
Volume: 20
Author(s): Baohua Lv, Xiaojuan Cheng, Yanling Cheng, Zhaohua Wang and Erhu Jin*
Affiliation:
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
Keywords:
Rectal cancer, Tumor deposits, Lymph node, EMVI, Magnetic resonance imaging, Nomogram.
Abstract:
Background:
The prognosis of postoperative tumor deposits (TDs) is worse than positive lymph node metastases alone.
Objective:
To detect TDs by using multiplanar high-resolution T2-weighted imaging (HRT2WI).
Material and Methods:
This retrospective study enrolled 130 patients with locally advanced rectal cancer (LARC). Using pathology-proven tumor deposits (pTDs) as the
gold standard, all patients were divided into the pTDs-negative and pTDs-positive groups, the correlation of clinicopathological factors and image
features [such as MRI-detected tumor deposits (mTDs), MRI-detected metastatic lymph node (mLN), MRI-detected extramural vascular invasion
(mEMVI), maximal extramural depth (EMD), etc.] with pTDs were analyzed by univariate analysis and multivariate binary logistic regression
analysis, and the nomogram was established based on the latter. The diagnostic efficiency was evaluated by the receiver operating characteristic
curve (ROC) analysis and area under curve (AUC).
Results:
mTDs, mLN, mEMVI, and EMD were significantly different between the pTDs-positive and pTDs-negative groups (P < 0.05), with the AUC of
0.767, 0.746, 0.664 and 0.644, respectively. mTDs and mLN were independent risk factors for pTDs (odds ratio: 5.74 and 3.90, P < 0.05). The
AUC, sensitivity, specificity, negative predictive value, and accuracy of the nomogram were 0.814 (95% CI: 0.720 ~ 0.908), 73.9%, 79.4%, 93.4%,
and 78.5%, respectively. Seventeen of 23 patients with pTDs were identified as mTDs, with a moderate agreement between pTDs and mTDs
(Kappa=0.419).
Conclusion:
Multiplanar HRT2WI can be used as a preoperative diagnostic tool to identify TDs in LARC. The combined model constructed by mTDs and mLN
shows a good diagnostic performance for TDs.