Literature DB >> 33936966

Preoperative volumetric synthetic magnetic resonance imaging of the primary tumor for a more accurate prediction of lymph node metastasis in rectal cancer.

Li Zhao1, Meng Liang1, Zhuo Shi1, Lizhi Xie2, Hongmei Zhang1, Xinming Zhao1.   

Abstract

BACKGROUND: An accurate assessment of lymph node (LN) status in patients with rectal cancer is important for treatment planning and an essential factor for predicting local recurrence and overall survival. In this study, we explored the potential value of histogram parameters of synthetic magnetic resonance imaging (SyMRI) in predicting LN metastasis in rectal cancer and compared their predictive performance with traditional morphological characteristics and chemical shift effect (CSE).
METHODS: A total of 70 patients with pathologically proven rectal adenocarcinoma who received direct surgical resection were enrolled in this prospective study. Preoperative rectal MRI, including SyMRI, were performed, and morphological characteristics and CSE of LN were assessed. Histogram parameters were extracted on a T1 map, T2 map, and proton density (PD) map, including mean, variance, maximum, minimum, 10th percentile, median, 90th percentile, energy, kurtosis, entropy, and skewness. Receiver operating characteristic (ROC) curves were used to explore their predictive performance for assessing LN status.
RESULTS: Significant differences in the energy of the T1, T2, and PD maps were observed between LN-negative and LN-positive groups [all P<0.001; the area under the ROC curve (AUC) was 0.838, 0.858, and 0.823, respectively]. The maximum and kurtosis of the T2 map, maximum, and variance of PD map could also predict LN metastasis with moderate diagnostic power (P=0.032, 0.045, 0.016, and 0.047, respectively). Energy of the T1 map [odds ratio (OR) =1.683, 95% confidence interval (CI): 1.207-2.346, P=0.002] and extramural venous invasion on MRI (mrEMVI) (OR =10.853, 95% CI: 2.339-50.364, P=0.002) were significant predictors of LN metastasis. Moreover, the T1 map energy significantly improved the predictive performance compared to morphological features and CSE (P=0.0002 and 0.0485).
CONCLUSIONS: The histogram parameters derived from SyMRI of the primary tumor were associated with LN metastasis in rectal cancer and could significantly improve the predictive performance compared with morphological features and CSE. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Lymphatic metastasis; magnetic resonance imaging (MRI); rectal neoplasms

Year:  2021        PMID: 33936966      PMCID: PMC8047345          DOI: 10.21037/qims-20-659

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  33 in total

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Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-07-15       Impact factor: 9.236

2.  The feasibility of synthetic MRI in breast cancer patients: comparison of T2 relaxation time with multiecho spin echo T2 mapping method.

Authors:  Yongsik Jung; Sung-Min Gho; Seung Nam Back; Taeyang Ha; Doo Kyoung Kang; Tae Hee Kim
Journal:  Br J Radiol       Date:  2018-09-21       Impact factor: 3.039

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Journal:  AJNR Am J Neuroradiol       Date:  2017-04-27       Impact factor: 3.825

4.  Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

Authors:  Yanfen Cui; Xiaotang Yang; Xiaosong Du; Zhizheng Zhuo; Lei Xin; Xintao Cheng
Journal:  Eur Radiol       Date:  2017-10-23       Impact factor: 5.315

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Authors:  Lanqing Yang; Dan Liu; Xin Fang; Ziqiang Wang; Yue Xing; Ling Ma; Bing Wu
Journal:  Eur Radiol       Date:  2019-07-05       Impact factor: 5.315

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7.  Role of Quantitative Dynamic Contrast-Enhanced MRI in Evaluating Regional Lymph Nodes With a Short-Axis Diameter of Less Than 5 mm in Rectal Cancer.

Authors:  Xinyue Yang; Yan Chen; Ziqiang Wen; Baolan Lu; Bingqi Shen; Xiaojuan Xiao; Shenping Yu
Journal:  AJR Am J Roentgenol       Date:  2018-10-24       Impact factor: 3.959

8.  Multiparametric radiomics improve prediction of lymph node metastasis of rectal cancer compared with conventional radiomics.

Authors:  Li-Da Chen; Jin-Yu Liang; Hui Wu; Zhu Wang; Shu-Rong Li; Wei Li; Xin-Hua Zhang; Jian-Hui Chen; Jin-Ning Ye; Xin Li; Xiao-Yan Xie; Ming-De Lu; Ming Kuang; Jian-Bo Xu; Wei Wang
Journal:  Life Sci       Date:  2018-07-07       Impact factor: 5.037

9.  Computational Radiomics System to Decode the Radiographic Phenotype.

Authors:  Joost J M van Griethuysen; Andriy Fedorov; Chintan Parmar; Ahmed Hosny; Nicole Aucoin; Vivek Narayan; Regina G H Beets-Tan; Jean-Christophe Fillion-Robin; Steve Pieper; Hugo J W L Aerts
Journal:  Cancer Res       Date:  2017-11-01       Impact factor: 12.701

10.  Comparison of the eighth version of the American Joint Committee on Cancer manual to the seventh version for colorectal cancer: A retrospective review of our data.

Authors:  Guo-Jun Tong; Gui-Yang Zhang; Jian Liu; Zhao-Zheng Zheng; Yan Chen; Ping-Ping Niu; Xu-Ting Xu
Journal:  World J Clin Oncol       Date:  2018-11-10
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  1 in total

1.  Diagnostic performance of synthetic magnetic resonance imaging in the prognostic evaluation of rectal cancer.

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Journal:  Quant Imaging Med Surg       Date:  2022-07
  1 in total

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