| Autor: |
Chandrakanth Jayachandran Preetha, MSc, Hagen Meredig, MD, Gianluca Brugnara, MD, Mustafa A Mahmutoglu, MD, Martha Foltyn, MD, Fabian Isensee, PhD, Tobias Kessler, MD, Irada Pflüger, MD, Marianne Schell, MD, Ulf Neuberger, MD, Jens Petersen, PhD, Antje Wick, MD, Sabine Heiland, ProfPhD, Jürgen Debus, ProfMD, Michael Platten, ProfMD, Ahmed Idbaih, MD, Alba A Brandes, ProfMD, Frank Winkler, ProfMD, Martin J van den Bent, ProfMD, Burt Nabors, ProfMD, Roger Stupp, ProfMD, Klaus H Maier-Hein, ProfPhD, Thierry Gorlia, PhD, Jörg-Christian Tonn, ProfMD, Michael Weller, ProfMD, Wolfgang Wick, ProfMD, Martin Bendszus, ProfMD, Philipp Vollmuth, MD |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
The Lancet: Digital Health, Vol 3, Iss 12, Pp e784-e794 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2589-7500 |
| DOI: |
10.1016/S2589-7500(21)00205-3 |
| Popis: |
Summary: Background: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibility and diagnostic value of synthetic post-contrast T1-weighted MRI generated from pre-contrast MRI sequences through deep convolutional neural networks (dCNN) for tumour response assessment in neuro-oncology. Methods: In this multicentre, retrospective cohort study, we used MRI examinations to train and validate a dCNN for synthesising post-contrast T1-weighted sequences from pre-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery sequences. We used MRI scans with availability of these sequences from 775 patients with glioblastoma treated at Heidelberg University Hospital, Heidelberg, Germany (775 MRI examinations); 260 patients who participated in the phase 2 CORE trial (1083 MRI examinations, 59 institutions); and 505 patients who participated in the phase 3 CENTRIC trial (3147 MRI examinations, 149 institutions). Separate training runs to rank the importance of individual sequences and (for a subset) diffusion-weighted imaging were conducted. Independent testing was performed on MRI data from the phase 2 and phase 3 EORTC-26101 trial (521 patients, 1924 MRI examinations, 32 institutions). The similarity between synthetic and true contrast enhancement on post-contrast T1-weighted MRI was quantified using the structural similarity index measure (SSIM). Automated tumour segmentation and volumetric tumour response assessment based on synthetic versus true post-contrast T1-weighted sequences was performed in the EORTC-26101 trial and agreement was assessed with Kaplan-Meier plots. Findings: The median SSIM score for predicting contrast enhancement on synthetic post-contrast T1-weighted sequences in the EORTC-26101 test set was 0·818 (95% CI 0·817–0·820). Segmentation of the contrast-enhancing tumour from synthetic post-contrast T1-weighted sequences yielded a median tumour volume of 6·31 cm3 (5·60 to 7·14), thereby underestimating the true tumour volume by a median of −0·48 cm3 (−0·37 to −0·76) with the concordance correlation coefficient suggesting a strong linear association between tumour volumes derived from synthetic versus true post-contrast T1-weighted sequences (0·782, 0·751–0·807, p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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