Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group
Bisgaard, Anne L H; Keesman, Rick; van Lier, Astrid L H M W; Coolens, Catherine; van Houdt, Petra J; Tree, Alison; Wetscherek, Andreas; Romesser, Paul B; Tyagi, Neelam; Lo Russo, Monica; Habrich, Jonas; Vesprini, Danny; Lau, Angus Z; Mook, Stella; Chung, Peter; Kerkmeijer, Linda G W; Gouw, Zeno A R; Lorenzen, Ebbe L; van der Heide, Uulke A; Schytte, Tine; Brink, Carsten; Mahmood, Faisal
(2023) Radiotherapy & Oncology, volume 186
(Article)
Abstract
Background and purpose: The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it. Materials and methods: Nine centres
... read more
received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0–500 vs. 150–500 s/mm 2, region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CV D) and calculation methods (CV C). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group. Results: The median (range) CV D and CV C were 0.06 (0.02–0.32) and 0.17 (0.08–0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CV C to 0.04 (0.01–0.16). CV D was comparable between ROI types. Conclusion: Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations.
show less
Download/Full Text
Keywords: Adaptive radiotheray, ADC reproducibility, Apparent diffusion coefficient, Diffusion-weighted magnetic resonance imaging, MRI biomarkers, MRI-Linac, Hematology, Oncology, Radiology Nuclear Medicine and imaging, Journal Article
ISSN: 0167-8140
Publisher: Elsevier Ireland Ltd
Note: Funding Information: AB, FM acknowledges the support of the Danish Cancer Society (Grant no. R231-356 A13852), Danish Comprehensive Cancer Center RT (Danish Cancer Society grant) (Grant no. R191-A11526), and by MANTRA (New MAgNetic resonance Technology for Response Adapted radiotherapy), a Frontline research center based at Odense University Hospital, Denmark. Funding Information: MLR acknowledges the support of the German Research Council (DFG, Grant no. ZI 736/2–1; PAK997/1), the University Hospital Tübingen and the Medical Faculty Tübingen. Funding Information: We thank Marco Luzzara, Senior Director of Medical Affairs and Clinical Research, Elekta, for his support in facilitating data sharing and analysis in ProKnow, Elekta. We thank Liam Lawrence, Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada, and Edward Taylor, Department of Medical Physics, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada, for their contributions to the data analysis. Funding Information: AT acknowledges the support of Cancer Research UK grant numbers C7224/A28724 and C33589/A28284. Further, AT acknowledges NHS funding to the NIHR Biomedical Research Centre at The Royal Marsden and The Institute of Cancer Research. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care. Publisher Copyright: © 2023 The Author(s)
(Peer reviewed)
