Literature DB >> 28497403

Locally advanced rectal cancer: predicting non-responders to neoadjuvant chemoradiotherapy using apparent diffusion coefficient textures.

Ming Liu1,2, Han Lv3, Li-Heng Liu4,5, Zheng-Han Yang3, Er-Hu Jin3, Zhen-Chang Wang6.   

Abstract

PURPOSE: The purpose of the study is to evaluate whether apparent diffusion coefficient (ADC) textures could identify patient with locally advanced rectal cancer (LARC) who would not respond to neoadjuvant chemoradiotherapy (NCRT).
METHOD: Twenty-six patients who underwent MRI including diffusion-weighted imaging at a 3.0 T system before NCRT were enrolled. Texture analysis of pre-therapy ADC mapping was carried out, and a total of 133 ADC textures as well as routine mean ADC value of the primary tumor were extracted for each patient. Texture parameters and mean ADC were compared between responsive group and non-responsive group. Logistic regression was used to determine the independent predictors for non-responders. Receiver operating characteristic curve (ROC) was performed to evaluate the predictive performance of the significant parameters.
RESULTS: Eighteen of the 133 texture parameters significantly differed between responsive and non-responsive groups (p < 0.05). Further, energy variance and SdGa47 were identified as independent predictors for non-responders to NCRT; this logistic model achieved an area under the curve (AUC) of 0.908.
CONCLUSION: Texture analysis based on pre-therapy ADC mapping could potentially be helpful to identify patients with LARC who would not respond to NCRT.

Entities:  

Keywords:  Apparent diffusion coefficient; Neoadjuvant; Rectal cancer; Response; Texture analysis

Mesh:

Year:  2017        PMID: 28497403     DOI: 10.1007/s00384-017-2835-3

Source DB:  PubMed          Journal:  Int J Colorectal Dis        ISSN: 0179-1958            Impact factor:   2.571


  12 in total

1.  Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival.

Authors:  B Ganeshan; K Skogen; I Pressney; D Coutroubis; K Miles
Journal:  Clin Radiol       Date:  2011-09-23       Impact factor: 2.350

2.  Visual versus quantitative assessment of intratumor 18F-FDG PET uptake heterogeneity: prognostic value in non-small cell lung cancer.

Authors:  Florent Tixier; Mathieu Hatt; Clemence Valla; Vincent Fleury; Corinne Lamour; Safaa Ezzouhri; Pierre Ingrand; Remy Perdrisot; Dimitris Visvikis; Catherine Cheze Le Rest
Journal:  J Nucl Med       Date:  2014-06-05       Impact factor: 10.057

3.  Texture analysis as imaging biomarker of tumoral response to neoadjuvant chemoradiotherapy in rectal cancer patients studied with 3-T magnetic resonance.

Authors:  Carlo N De Cecco; Balaji Ganeshan; Maria Ciolina; Marco Rengo; Felix G Meinel; Daniela Musio; Francesca De Felice; Nicola Raffetto; Vincenzo Tombolini; Andrea Laghi
Journal:  Invest Radiol       Date:  2015-04       Impact factor: 6.016

4.  Diffusion-weighted magnetic resonance imaging in monitoring rectal cancer response to neoadjuvant chemoradiotherapy.

Authors:  Brunella Barbaro; Renata Vitale; Vincenzo Valentini; Sonia Illuminati; Fabio M Vecchio; Gianluca Rizzo; Maria Antonietta Gambacorta; Claudio Coco; Antonio Crucitti; Roberto Persiani; Luigi Sofo; Lorenzo Bonomo
Journal:  Int J Radiat Oncol Biol Phys       Date:  2011-11-16       Impact factor: 7.038

Review 5.  Neoadjuvant Treatment Strategies for Locally Advanced Rectal Cancer.

Authors:  S Gollins; D Sebag-Montefiore
Journal:  Clin Oncol (R Coll Radiol)       Date:  2015-11-29       Impact factor: 4.126

6.  Determination of regional lymph node status using (18)F-FDG PET/CT parameters in oesophageal cancer patients: comparison of SUV, volumetric parameters and intratumoral heterogeneity.

Authors:  Seong-Jang Kim; Kyoungjune Pak; Samuel Chang
Journal:  Br J Radiol       Date:  2015-11-26       Impact factor: 3.039

7.  The Impact of Optimal Respiratory Gating and Image Noise on Evaluation of Intratumor Heterogeneity on 18F-FDG PET Imaging of Lung Cancer.

Authors:  Willem Grootjans; Florent Tixier; Charlotte S van der Vos; Dennis Vriens; Catherine C Le Rest; Johan Bussink; Wim J G Oyen; Lioe-Fee de Geus-Oei; Dimitris Visvikis; Eric P Visser
Journal:  J Nucl Med       Date:  2016-06-09       Impact factor: 10.057

8.  Spatial heterogeneity in drug concentrations can facilitate the emergence of resistance to cancer therapy.

Authors:  Feng Fu; Martin A Nowak; Sebastian Bonhoeffer
Journal:  PLoS Comput Biol       Date:  2015-03-19       Impact factor: 4.475

9.  PET/CT with Fluorodeoxyglucose During Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.

Authors:  Laura L Travaini; Maria G Zampino; Marzia Colandrea; Mahila E Ferrari; Laura Gilardi; Maria C Leonardi; Luigi Santoro; Roberto Orecchia; Chiara M Grana
Journal:  Ecancermedicalscience       Date:  2016-03-29

10.  Intra-tumor genetic heterogeneity in rectal cancer.

Authors:  Karin M Hardiman; Peter J Ulintz; Rork D Kuick; Daniel H Hovelson; Christopher M Gates; Ashwini Bhasi; Ana Rodrigues Grant; Jianhua Liu; Andi K Cani; Joel K Greenson; Scott A Tomlins; Eric R Fearon
Journal:  Lab Invest       Date:  2015-11-16       Impact factor: 5.662

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  4 in total

1.  Ability of Delta Radiomics to Predict a Complete Pathological Response in Patients with Loco-Regional Rectal Cancer Addressed to Neoadjuvant Chemo-Radiation and Surgery.

Authors:  Valerio Nardone; Alfonso Reginelli; Roberta Grassi; Giovanna Vacca; Giuliana Giacobbe; Antonio Angrisani; Alfredo Clemente; Ginevra Danti; Pierpaolo Correale; Salvatore Francesco Carbone; Luigi Pirtoli; Lorenzo Bianchi; Angelo Vanzulli; Cesare Guida; Roberto Grassi; Salvatore Cappabianca
Journal:  Cancers (Basel)       Date:  2022-06-18       Impact factor: 6.575

2.  MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study.

Authors:  Arianna Defeudis; Simone Mazzetti; Jovana Panic; Monica Micilotta; Lorenzo Vassallo; Giuliana Giannetto; Marco Gatti; Riccardo Faletti; Stefano Cirillo; Daniele Regge; Valentina Giannini
Journal:  Eur Radiol Exp       Date:  2022-05-03

3.  Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer.

Authors:  Davide Prezzi; Katarzyna Owczarczyk; Paul Bassett; Muhammad Siddique; David J Breen; Gary J R Cook; Vicky Goh
Journal:  Eur Radiol       Date:  2019-03-18       Impact factor: 5.315

4.  Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging.

Authors:  Yuhui Qin; Xiaoping Yu; Jing Hou; Ying Hu; Feiping Li; Lu Wen; Qiang Lu; Yi Fu; Siye Liu
Journal:  Medicine (Baltimore)       Date:  2018-07       Impact factor: 1.889

  4 in total

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