Literature DB >> 31101691

Early evaluation using a radiomic signature of unresectable hepatic metastases to predict outcome in patients with colorectal cancer treated with FOLFIRI and bevacizumab.

Thomas Aparicio1,2, Christine Hoeffel3,4, Anthony Dohan5,1,6, Benoit Gallix6,7,8, Boris Guiu9,10, Karine Le Malicot11,12, Caroline Reinhold6, Philippe Soyer5,1, Jaafar Bennouna13, Francois Ghiringhelli14, Emilie Barbier11,12, Valérie Boige15, Julien Taieb1,16, Olivier Bouché17, Eric François18, Jean-Marc Phelip19, Christian Borel20, Roger Faroux21, Jean-Francois Seitz22, Stéphane Jacquot23, Meher Ben Abdelghani20, Faiza Khemissa-Akouz24, Dominique Genet25, Jean Louis Jouve26, Yves Rinaldi27, Françoise Desseigne28, Patrick Texereau29, Etienne Suc30, Come Lepage12,26.   

Abstract

PURPOSE: The objective of this study was to build and validate a radiomic signature to predict early a poor outcome using baseline and 2-month evaluation CT and to compare it to the RECIST1·1 and morphological criteria defined by changes in homogeneity and borders.
METHODS: This study is an ancillary study from the PRODIGE-9 multicentre prospective study for which 491 patients with metastatic colorectal cancer (mCRC) treated by 5-fluorouracil, leucovorin and irinotecan (FOLFIRI) and bevacizumab had been analysed. In 230 patients, computed texture analysis was performed on the dominant liver lesion (DLL) at baseline and 2 months after chemotherapy. RECIST1·1 evaluation was performed at 6 months. A radiomic signature (Survival PrEdiction in patients treated by FOLFIRI and bevacizumab for mCRC using contrast-enhanced CT TextuRe Analysis (SPECTRA) Score) combining the significant predictive features was built using multivariable Cox analysis in 120 patients, then locked, and validated in 110 patients. Overall survival (OS) was estimated with the Kaplan-Meier method and compared between groups with the logrank test. An external validation was performed in another cohort of 40 patients from the PRODIGE 20 Trial.
RESULTS: In the training cohort, the significant predictive features for OS were: decrease in sum of the target liver lesions (STL), (adjusted hasard-ratio(aHR)=13·7, p=1·93×10-7), decrease in kurtosis (ssf=4) (aHR=1·08, p=0·001) and high baseline density of DLL, (aHR=0·98, p<0·001). Patients with a SPECTRA Score >0·02 had a lower OS in the training cohort (p<0·0001), in the validation cohort (p<0·0008) and in the external validation cohort (p=0·0027). SPECTRA Score at 2 months had the same prognostic value as RECIST at 6 months, while non-response according to RECIST1·1 at 2 months was not associated with a lower OS in the validation cohort (p=0·238). Morphological response was not associated with OS (p=0·41).
CONCLUSION: A radiomic signature (combining decrease in STL, density and computed texture analysis of the DLL) at baseline and 2-month CT was able to predict OS, and identify good responders better than RECIST1.1 criteria in patients with mCRC treated by FOLFIRI and bevacizumab as a first-line treatment. This tool should now be validated by further prospective studies. TRIAL REGISTRATION: Clinicaltrial.gov identifier of the PRODIGE 9 study: NCT00952029.Clinicaltrial.gov identifier of the PRODIGE 20 study: NCT01900717. © Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  chemotherapy; clinical decision making; colorectal cancer; colorectal metastases; computerised image analysis

Year:  2019        PMID: 31101691     DOI: 10.1136/gutjnl-2018-316407

Source DB:  PubMed          Journal:  Gut        ISSN: 0017-5749            Impact factor:   23.059


  27 in total

Review 1.  CT and MRI of pancreatic tumors: an update in the era of radiomics.

Authors:  Marion Bartoli; Maxime Barat; Anthony Dohan; Sébastien Gaujoux; Romain Coriat; Christine Hoeffel; Christophe Cassinotto; Guillaume Chassagnon; Philippe Soyer
Journal:  Jpn J Radiol       Date:  2020-10-21       Impact factor: 2.374

2.  Retrospective Analysis of the Value of Enhanced CT Radiomics Analysis in the Differential Diagnosis Between Pancreatic Cancer and Chronic Pancreatitis.

Authors:  Xi Ma; Yu-Rui Wang; Li-Yong Zhuo; Xiao-Ping Yin; Jia-Liang Ren; Cai-Ying Li; Li-Hong Xing; Tong-Tong Zheng
Journal:  Int J Gen Med       Date:  2022-01-06

3.  Response prediction of neoadjuvant chemoradiation therapy in locally advanced rectal cancer using CT-based fractal dimension analysis.

Authors:  Toru Tochigi; Sophia C Kamran; Anushri Parakh; Yoshifumi Noda; Balaji Ganeshan; Lawrence S Blaszkowsky; David P Ryan; Jill N Allen; David L Berger; Jennifer Y Wo; Theodore S Hong; Avinash Kambadakone
Journal:  Eur Radiol       Date:  2021-10-13       Impact factor: 7.034

Review 4.  A primer on texture analysis in abdominal radiology.

Authors:  Natally Horvat; Joao Miranda; Maria El Homsi; Jacob J Peoples; Niamh M Long; Amber L Simpson; Richard K G Do
Journal:  Abdom Radiol (NY)       Date:  2021-11-26

5.  Interobserver Variability in CT-based Morphologic Tumor Response Assessment of Colorectal Liver Metastases.

Authors:  Nina J Wesdorp; Ruby Kemna; Jaap Stoker; Geert Kazemier; Karen Bolhuis; Jan H T M van Waesberghe; Irene M G C Nota; Femke Struik; Ikrame Oulad Abdennabi; Saffire S K S Phoa; Susan van Dieren; Martinus J van Amerongen; Thiery Chapelle; Cornelis H C Dejong; Marc R W Engelbrecht; Michael F Gerhards; Dirk Grünhagen; Thomas M van Gulik; John J Hermans; Koert P de Jong; Joost M Klaase; Mike S L Liem; Krijn P van Lienden; I Quintus Molenaar; Gijs A Patijn; Arjen M Rijken; Theo M Ruers; Cornelis Verhoef; Johannes H W de Wilt; Rutger-Jan Swijnenburg; Cornelis J A Punt; Joost Huiskens
Journal:  Radiol Imaging Cancer       Date:  2022-05

6.  An MRI radiomics approach to predict survival and tumour-infiltrating macrophages in gliomas.

Authors:  Guanzhang Li; Lin Li; Yiming Li; Zenghui Qian; Fan Wu; Yufei He; Haoyu Jiang; Renpeng Li; Di Wang; You Zhai; Zhiliang Wang; Tao Jiang; Jing Zhang; Wei Zhang
Journal:  Brain       Date:  2022-04-29       Impact factor: 15.255

7.  Impact of inter-reader contouring variability on textural radiomics of colorectal liver metastases.

Authors:  Francesco Rizzetto; Francesca Calderoni; Cristina De Mattia; Arianna Defeudis; Valentina Giannini; Simone Mazzetti; Lorenzo Vassallo; Silvia Ghezzi; Andrea Sartore-Bianchi; Silvia Marsoni; Salvatore Siena; Daniele Regge; Alberto Torresin; Angelo Vanzulli
Journal:  Eur Radiol Exp       Date:  2020-11-10

8.  Differentiating High-Grade Gliomas from Brain Metastases at Magnetic Resonance: The Role of Texture Analysis of the Peritumoral Zone.

Authors:  Csaba Csutak; Paul-Andrei Ștefan; Lavinia Manuela Lenghel; Cezar Octavian Moroșanu; Roxana-Adelina Lupean; Larisa Șimonca; Carmen Mihaela Mihu; Andrei Lebovici
Journal:  Brain Sci       Date:  2020-09-16

9.  Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer.

Authors:  Zhuokai Zhuang; Zongchao Liu; Juan Li; Xiaolin Wang; Peiyi Xie; Fei Xiong; Jiancong Hu; Xiaochun Meng; Meijin Huang; Yanhong Deng; Ping Lan; Huichuan Yu; Yanxin Luo
Journal:  J Transl Med       Date:  2021-06-10       Impact factor: 5.531

Review 10.  Evaluation of liver tumour response by imaging.

Authors:  Jules Gregory; Marco Dioguardi Burgio; Giuseppe Corrias; Valérie Vilgrain; Maxime Ronot
Journal:  JHEP Rep       Date:  2020-04-28
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