TY - JOUR
T1 - Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group
AU - Bisgaard, Anne L H
AU - Keesman, Rick
AU - van Lier, Astrid L H M W
AU - Coolens, Catherine
AU - van Houdt, Petra J
AU - Tree, Alison
AU - Wetscherek, Andreas
AU - Romesser, Paul B
AU - Tyagi, Neelam
AU - Lo Russo, Monica
AU - Habrich, Jonas
AU - Vesprini, Danny
AU - Lau, Angus Z
AU - Mook, Stella
AU - Chung, Peter
AU - Kerkmeijer, Linda G W
AU - Gouw, Zeno A R
AU - Lorenzen, Ebbe L
AU - van der Heide, Uulke A
AU - Schytte, Tine
AU - Brink, Carsten
AU - Mahmood, Faisal
N1 - 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)
PY - 2023/9
Y1 - 2023/9
N2 - 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 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.
AB - 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 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.
KW - Adaptive radiotheray
KW - ADC reproducibility
KW - Apparent diffusion coefficient
KW - Diffusion-weighted magnetic resonance imaging
KW - MRI biomarkers
KW - MRI-Linac
UR - http://www.scopus.com/inward/record.url?scp=85166630111&partnerID=8YFLogxK
U2 - 10.1016/j.radonc.2023.109803
DO - 10.1016/j.radonc.2023.109803
M3 - Article
C2 - 37437609
SN - 0167-8140
VL - 186
JO - Radiotherapy & Oncology
JF - Radiotherapy & Oncology
M1 - 109803
ER -