Literature DB >> 31153550

Predicting lymph node metastasis in pancreatobiliary cancer with magnetic resonance imaging: A prospective analysis.

Ju Hee Lee1, Sung-Sik Han2, Eun Kyung Hong3, Hwa Jin Cho4, Jungnam Joo5, Eun Young Park4, Sang Myung Woo6, Tae Hyun Kim6, Woo Jin Lee6, Sang-Jae Park7.   

Abstract

OBJECTIVES: To prospectively investigate the diagnostic potential of lymph node (LN) magnetic resonance (MR) imaging features.
METHODS: A radiologist determined the maximum diameters in the short and long axes, shape, signal intensities on T1- and T2-weighted imaging, pattern of enhancement, and apparent diffusion coefficient (ADC) on diffusion-weighted MR images of LNs and annotated measurable (≥5 mm in short-axis diameter) LNs. Surgically harvested LNs were correlated with the pathologic findings. Univariable and multivariable generalized estimating equation analyses were performed to evaluate predictive power.
RESULTS: Of 80 LNs, 29 (36.3%) were positive and 51 (63.7%) negative for metastasis. The mean short-axis diameter of metastatic LNs (10.59 ± 4.30 mm) was larger than that of benign LNs (7.96 ± 2.10 mm). The ADC was significantly (P < 0.001) lower in metastatic than non-metastatic LNs. The area under the curve (AUC) of a univariable model using only the mean ADC was 0.845 (95% confidence interval [CI], 0.743-0.927), and the mean-ADC cutoff value for predicting LN metastasis was 0.901 × 10-3 mm2/s. The AUC of a multivariable model including round shape, heterogeneous enhancement, and the mean ADC was 0.917 (95% CI, 0.845-0.972), with a sensitivity, specificity, overall accuracy, and positive and negative predictive values of 89.7%, 82.4%, 85.0%, 74.3%, and 93.3%, respectively.
CONCLUSION: The short-axis diameter and ADC were different between benign and metastatic LNs in pancreatobiliary cancer. However, round shape, heterogeneous enhancement, and a low ADC value (<0.901 × 10-3 mm2/s) may be the most reliable diagnostic features of multiple metastatic LNs.
Copyright © 2019. Published by Elsevier B.V.

Entities:  

Keywords:  Biliary tract neoplasms; Diffusion magnetic resonance imaging; Lymph nodes; Pancreatic neoplasms

Mesh:

Year:  2019        PMID: 31153550     DOI: 10.1016/j.ejrad.2019.04.007

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  6 in total

1.  Preoperative Prediction of Lymph Node Metastasis of Pancreatic Ductal Adenocarcinoma Based on a Radiomics Nomogram of Dual-Parametric MRI Imaging.

Authors:  Lin Shi; Ling Wang; Cuiyun Wu; Yuguo Wei; Yang Zhang; Junfa Chen
Journal:  Front Oncol       Date:  2022-07-06       Impact factor: 5.738

2.  An application study of CT perfusion imaging in assessing metastatic involvement of perigastric lymph nodes in patients with T1 gastric cancer.

Authors:  Zongqiong Sun; Shudong Hu; Jie Li; Teng Wang; Zhihui Xie; Linfang Jin
Journal:  Br J Radiol       Date:  2019-12-03       Impact factor: 3.039

3.  The Role of CT in Assessment of Extraregional Lymph Node Involvement in Pancreatic and Periampullary Cancer: A Diagnostic Accuracy Study.

Authors:  Dorine S J Tseng; Bobby K Pranger; Maarten S van Leeuwen; Jan Pieter Pennings; Lodewijk A Brosens; Nadja Haj Mohammad; Vincent E de Meijer; Hjalmar C van Santvoort; Joris I Erdmann; I Quintus Molenaar
Journal:  Radiol Imaging Cancer       Date:  2021-03-19

4.  Establishment of a multi-parameters MRI model for predicting small lymph nodes metastases (<10 mm) in patients with resected pancreatic ductal adenocarcinoma.

Authors:  Yan-Jie Shi; Bo-Nan Liu; Xiao-Ting Li; Hai-Tao Zhu; Yi-Yuan Wei; Bo Zhao; Shao-Shuai Sun; Ying-Shi Sun; Chun-Yi Hao
Journal:  Abdom Radiol (NY)       Date:  2021-11-20

5.  Classifying primary central nervous system lymphoma from glioblastoma using deep learning and radiomics based machine learning approach - a systematic review and meta-analysis.

Authors:  Amrita Guha; Jayant S Goda; Archya Dasgupta; Abhishek Mahajan; Soutik Halder; Jeetendra Gawde; Sanjay Talole
Journal:  Front Oncol       Date:  2022-10-03       Impact factor: 5.738

6.  Impact of Borderline Resectability in Pancreatic Head Cancer on Patient Survival: Biology Matters According to the New International Consensus Criteria.

Authors:  Casper van Eijck; Stefan Löb; Friedrich Anger; Anna Döring; Jacob van Dam; Johan Friso Lock; Ingo Klein; Max Bittrich; Christoph-Thomas Germer; Armin Wiegering; Volker Kunzmann
Journal:  Ann Surg Oncol       Date:  2020-09-12       Impact factor: 5.344

  6 in total

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