Multi-parametric magnetic resonance imaging assessment of whole tumour heterogeneity for chemoradiotherapy response prediction in rectal cancer.


Journal

Physics and imaging in radiation oncology
ISSN: 2405-6316
Titre abrégé: Phys Imaging Radiat Oncol
Pays: Netherlands
ID NLM: 101704276

Informations de publication

Date de publication:
Apr 2021
Historique:
received: 09 11 2020
revised: 03 02 2021
accepted: 18 03 2021
entrez: 14 7 2021
pubmed: 15 7 2021
medline: 15 7 2021
Statut: epublish

Résumé

Prediction of chemoradiotherapy response (CRT) in locally advanced rectal cancer would enable stratification of management. The purpose was to prospectively evaluate multi-parametric magnetic resonance imaging (MRI) assessment of tumour heterogeneity combining diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) MRI for the prediction of CRT response in locally advanced rectal cancer. Patients with Stage II or III rectal adenocarcinoma undergoing neoadjuvant CRT and surgery underwent MRI (DWI and DCE) before, during (week 3), and after CRT (1 week before surgery). Patients with histopathology tumour regression grade (TRG) 0-1 were classified as responders, and TRG 2-3 were classified as non-responders. A whole tumour voxel-wise technique was used to produce apparent diffusion coefficient (ADC) and K Thirty-three patients were included in this analysis; 16 responders, and 17 non-responders. On heterogeneity analysis, odds of being a responder were significantly higher after CRT (before surgery) for higher ADC 75th (p = 0.049) and ADC 90th (p = 0.034) percentile values. The K DWI-MRI after CRT (before surgery) incorporating a histogram analysis of whole tumour heterogeneity was predictive of CRT response in patients with locally advanced rectal cancer. DCE-MRI did not add value in response prediction. Australian New Zealand Clinical Trials Registry (ANZCTR) number ACTRN12616001690448.

Sections du résumé

BACKGROUND AND PURPOSE OBJECTIVE
Prediction of chemoradiotherapy response (CRT) in locally advanced rectal cancer would enable stratification of management. The purpose was to prospectively evaluate multi-parametric magnetic resonance imaging (MRI) assessment of tumour heterogeneity combining diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) MRI for the prediction of CRT response in locally advanced rectal cancer.
MATERIALS AND METHODS METHODS
Patients with Stage II or III rectal adenocarcinoma undergoing neoadjuvant CRT and surgery underwent MRI (DWI and DCE) before, during (week 3), and after CRT (1 week before surgery). Patients with histopathology tumour regression grade (TRG) 0-1 were classified as responders, and TRG 2-3 were classified as non-responders. A whole tumour voxel-wise technique was used to produce apparent diffusion coefficient (ADC) and K
RESULTS RESULTS
Thirty-three patients were included in this analysis; 16 responders, and 17 non-responders. On heterogeneity analysis, odds of being a responder were significantly higher after CRT (before surgery) for higher ADC 75th (p = 0.049) and ADC 90th (p = 0.034) percentile values. The K
CONCLUSIONS CONCLUSIONS
DWI-MRI after CRT (before surgery) incorporating a histogram analysis of whole tumour heterogeneity was predictive of CRT response in patients with locally advanced rectal cancer. DCE-MRI did not add value in response prediction.
CLINICAL TRIAL REGISTRATION BACKGROUND
Australian New Zealand Clinical Trials Registry (ANZCTR) number ACTRN12616001690448.

Identifiants

pubmed: 34258404
doi: 10.1016/j.phro.2021.03.003
pii: S2405-6316(21)00017-8
pmc: PMC8254202
doi:

Types de publication

Journal Article

Langues

eng

Pagination

26-33

Informations de copyright

© 2021 The Authors.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Trang Thanh Pham (TT)

Ingham Institute for Applied Medical Research, South West Sydney Clinical School, Faculty of Medicine, University of New South Wales, Sydney, PO Box 3151, Liverpool, NSW 2170, Australia.
Department of Radiation Oncology, Liverpool Cancer Therapy Centre, Liverpool Hospital, Sydney, Locked Bag 7103, Liverpool BC, NSW 1871, Australia.

Gary Liney (G)

Ingham Institute for Applied Medical Research, South West Sydney Clinical School, Faculty of Medicine, University of New South Wales, Sydney, PO Box 3151, Liverpool, NSW 2170, Australia.

Karen Wong (K)

Department of Radiation Oncology, Liverpool Cancer Therapy Centre, Liverpool Hospital, Sydney, Locked Bag 7103, Liverpool BC, NSW 1871, Australia.

Christopher Henderson (C)

Department of Anatomical Pathology, Liverpool Hospital, Sydney, Locked Bag 7103, Liverpool BC, NSW, 1871, Australia.

Robba Rai (R)

Department of Radiation Oncology, Liverpool Cancer Therapy Centre, Liverpool Hospital, Sydney, Locked Bag 7103, Liverpool BC, NSW 1871, Australia.

Petra L Graham (PL)

Centre for Economic Impacts of Genomic Medicine, Macquarie Business School and Department of Mathematics and Statistics, Faculty of Science and Engineering, Macquarie University, Sydney, Macquarie University, NSW 2109, Australia.

Nira Borok (N)

Department of Radiology, Liverpool Hospital, Sydney, Locked Bag 7103, Liverpool BC, NSW 1871, Australia.

Minh Xuan Truong (MX)

Department of Radiology, Liverpool Hospital, Sydney, Locked Bag 7103, Liverpool BC, NSW 1871, Australia.

Mark Lee (M)

Department of Radiation Oncology, Liverpool Cancer Therapy Centre, Liverpool Hospital, Sydney, Locked Bag 7103, Liverpool BC, NSW 1871, Australia.

Joo-Shik Shin (JS)

Department of Anatomical Pathology, Liverpool Hospital, Sydney, Locked Bag 7103, Liverpool BC, NSW, 1871, Australia.
School of Medicine, Western Sydney University, Sydney, Locked Bag 1797, Penrith, NSW 2751, Australia.

Malcolm Hudson (M)

NHMRC Clinical Trials Centre, Sydney, Locked Bag 77, Camperdown, NSW 1450, Australia.

Michael B Barton (MB)

Ingham Institute for Applied Medical Research, South West Sydney Clinical School, Faculty of Medicine, University of New South Wales, Sydney, PO Box 3151, Liverpool, NSW 2170, Australia.

Classifications MeSH