Literature DB >> 30097234

Imaging predictors of treatment outcomes in rectal cancer: An overview.

Lakshmi Shree Mahadevan1, Jim Zhong2, BhanuPrasad Venkatesulu1, Harmeet Kaur3, Shreerang Bhide4, Bruce Minsky1, William Chu5, Martijn Intven6, Uulke A van der Heide7, Baukelien van Triest7, Sunil Krishnan8, William A Hall9.   

Abstract

The treatment protocols for rectal cancer continue to evolve, with increasing acceptance of a watch-and-wait policy for clinical complete responders to neoadjuvant chemoradiation therapy. It still, however, remains unclear who is likely to achieve a pathological complete response, which unequivocally portends a very favorable overall prognosis. Evolution of modern imaging techniques has paved the way for potential prediction of treatment response based on baseline, on-treatment, early post-treatment and subsequent follow-up imaging alone. Independent of tumor grade and stage, tumor marker levels, tumor size, radiation dose and fractionation, chemotherapy regimen, and extent/type of surgery, imaging biomarkers like circumferential resection margin (CRM), extramural venous space invasion (EMVI), imaging-based tumor regression grade, perfusion/diffusion-based functional imaging parameters, and imaging-based metabolic response have the ability to predict the likelihood of local recurrence and/or distant metastases. Textural features of images can add a further dimension to the predictive power of imaging. Finally, integration of genomic data with imaging biomarkers can potentially discern molecular mechanisms associated with distinct radiographic attributes of tumors. In this review, we evaluate and summarize the evidence to date of each imaging modality as a biomarker and its contribution to personalized decision making in rectal cancer.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Chemoradiation; Computed tomography; Imaging; Magnetic resonance; Positron emission; Rectal cancer; Response

Mesh:

Year:  2018        PMID: 30097234     DOI: 10.1016/j.critrevonc.2018.06.009

Source DB:  PubMed          Journal:  Crit Rev Oncol Hematol        ISSN: 1040-8428            Impact factor:   6.312


  5 in total

1.  Value of combined multiparametric MRI and FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation.

Authors:  Niels W Schurink; Lisa A Min; Maaike Berbee; Wouter van Elmpt; Joost J M van Griethuysen; Frans C H Bakers; Sander Roberti; Simon R van Kranen; Max J Lahaye; Monique Maas; Geerard L Beets; Regina G H Beets-Tan; Doenja M J Lambregts
Journal:  Eur Radiol       Date:  2020-02-07       Impact factor: 5.315

2.  Preoperative Prediction of Perineural Invasion Status of Rectal Cancer Based on Radiomics Nomogram of Multiparametric Magnetic Resonance Imaging.

Authors:  Yang Zhang; Jiaxuan Peng; Jing Liu; Yanqing Ma; Zhenyu Shu
Journal:  Front Oncol       Date:  2022-04-11       Impact factor: 5.738

3.  Assessing Rectal Cancer Treatment Response Using Coregistered Endorectal Photoacoustic and US Imaging Paired with Deep Learning.

Authors:  Xiandong Leng; K M Shihab Uddin; William Chapman; Hongbo Luo; Sitai Kou; Eghbal Amidi; Guang Yang; Deyali Chatterjee; Anup Shetty; Steve Hunt; Matthew Mutch; Quing Zhu
Journal:  Radiology       Date:  2021-03-23       Impact factor: 11.105

4.  MRI radiomics independent of clinical baseline characteristics and neoadjuvant treatment modalities predicts response to neoadjuvant therapy in rectal cancer.

Authors:  Maxiaowei Song; Shuai Li; Hongzhi Wang; Ke Hu; Fengwei Wang; Huajing Teng; Zhi Wang; Jin Liu; Angela Y Jia; Yong Cai; Yongheng Li; Xianggao Zhu; Jianhao Geng; Yangzi Zhang; XiangBo Wan; Weihu Wang
Journal:  Br J Cancer       Date:  2022-04-02       Impact factor: 9.075

5.  Imaging for guiding a more tailored approach in rectal cancer patients.

Authors:  Gaya Spolverato; Filippo Crimì; Salvatore Pucciarelli
Journal:  Ann Transl Med       Date:  2022-08
  5 in total

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