Literature DB >> 26102418

MRI of Rectal Cancer: An Overview and Update on Recent Advances.

Kartik S Jhaveri1, Hooman Hosseini-Nik1.   

Abstract

OBJECTIVE: MRI is the modality of choice for rectal cancer staging. The high soft-tissue contrast of MRI accurately assesses the extramural tumor spread and relation to mesorectal fascia and the sphincter complex. This article reviews the role of MRI in the staging and treatment of rectal cancer. The relevant anatomy, MRI techniques, preoperative staging, post-chemoradiation therapy (CRT) imaging, and tumor recurrence are discussed with special attention to recent advances in knowledge.
CONCLUSION: MRI is the modality of choice for staging rectal cancer to assist surgeons in obtaining negative surgical margins. MRI facilitates the accurate assessment of mesorectal fascia and the sphincter complex for surgical planning. Multiparametric MRI may also help in the prediction and estimation of response to treatment and in the detection of recurrent disease.

Entities:  

Keywords:  MRI; chemoradiation therapy; rectal cancer; recurrence; staging

Mesh:

Substances:

Year:  2015        PMID: 26102418     DOI: 10.2214/AJR.14.14201

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  36 in total

1.  Multiparametric MRI of rectal cancer-repeatability of quantitative data: a feasibility study.

Authors:  Bengi Gürses; Emre Altınmakas; Medine Böge; M Serhat Aygün; Onur Bayram; Emre Balık
Journal:  Diagn Interv Radiol       Date:  2020-03       Impact factor: 2.630

Review 2.  MRI of Rectal Cancer: Tumor Staging, Imaging Techniques, and Management.

Authors:  Natally Horvat; Camila Carlos Tavares Rocha; Brunna Clemente Oliveira; Iva Petkovska; Marc J Gollub
Journal:  Radiographics       Date:  2019-02-15       Impact factor: 5.333

3.  Preoperative radiomic signature based on multiparametric magnetic resonance imaging for noninvasive evaluation of biological characteristics in rectal cancer.

Authors:  Xiaochun Meng; Wei Xia; Peiyi Xie; Rui Zhang; Wenru Li; Mengmeng Wang; Fei Xiong; Yangchuan Liu; Xinjuan Fan; Yao Xie; Xiangbo Wan; Kangshun Zhu; Hong Shan; Lei Wang; Xin Gao
Journal:  Eur Radiol       Date:  2018-11-09       Impact factor: 5.315

4.  MRI radiomics analysis for predicting preoperative synchronous distant metastasis in patients with rectal cancer.

Authors:  Huanhuan Liu; Caiyuan Zhang; Lijun Wang; Ran Luo; Jinning Li; Hui Zheng; Qiufeng Yin; Zhongyang Zhang; Shaofeng Duan; Xin Li; Dengbin Wang
Journal:  Eur Radiol       Date:  2018-11-09       Impact factor: 5.315

5.  Improving the completeness of structured MRI reports for rectal cancer staging.

Authors:  Anna H Zhao; Shanna A Matalon; Atul B Shinagare; Leslie K Lee; Giles W Boland; Ramin Khorasani
Journal:  Abdom Radiol (NY)       Date:  2020-09-19

6.  The Diagnostic Performance of MRI for Detection of Extramural Venous Invasion in Colorectal Cancer: A Systematic Review and Meta-Analysis of the Literature.

Authors:  Tae-Hyung Kim; Sungmin Woo; Sangwon Han; Chong Hyun Suh; Hebert Alberto Vargas
Journal:  AJR Am J Roentgenol       Date:  2019-05-07       Impact factor: 3.959

7.  MRI can be used to assess advanced T-stage colon carcinoma as well as rectal carcinoma.

Authors:  Akitoshi Inoue; Shinichi Ohta; Norihisa Nitta; Masahiro Yoshimura; Tomoharu Shimizu; Masaji Tani; Ryoji Kushima; Kiyoshi Murata
Journal:  Jpn J Radiol       Date:  2016-10-18       Impact factor: 2.374

8.  Polypoid endometriosis: a mimic of malignancy.

Authors:  Soleen Ghafoor; Yulia Lakhman; Kay J Park; Iva Petkovska
Journal:  Abdom Radiol (NY)       Date:  2020-06

9.  Low prevalence of deficient mismatch repair (dMMR) protein in locally advanced rectal cancers (LARC) and treatment outcomes.

Authors:  Vikas Ostwal; Nikhil S Pande; Reena Engineer; Avanish Saklani; Ashwin deSouza; Mukta Ramadwar; Suvarna Sawant; Sarika Mandavkar; Sameer Shrirangwar; Pritam Kataria; Prachi Patil; Omshree Shetty; Anant Ramaswamy
Journal:  J Gastrointest Oncol       Date:  2019-02

10.  Development of a Joint Prediction Model Based on Both the Radiomics and Clinical Factors for Predicting the Tumor Response to Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer.

Authors:  Yang Liu; Feng-Jiao Zhang; Xi-Xi Zhao; Yuan Yang; Chun-Yi Liang; Li-Li Feng; Xiang-Bo Wan; Yi Ding; Yao-Wei Zhang
Journal:  Cancer Manag Res       Date:  2021-04-13       Impact factor: 3.989

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