Clinical Integration of Automated Processing for Brain Quantitative Susceptibility Mapping: Multi‐Site Reproducibility and Single‐Site Robustness

Pascal Spincemaille (1) , Zhe Liu (2) , Shun Zhang (3) , Ilhami Kovanlikaya , Matteo Ippoliti , Marcus Makowski , Richard Watts (4) , Ludovic de Rochefort (5, 6, 7, 8) , Ludovic De Rochefort (5, 6, 7, 8) , Vijay Venkatraman , Patricia Desmond (9) , Mathieu D. Santin (10) , Stéphane Lehéricy (11) , Brian H. Kopell (12) , Patrice Péran (13) , Yi Wang (14)

1 Cornell University [New York]
2 SnT - Interdisciplinary Centre for Security, Reliability and Trust
3 State Key Lab CAD&CG [HangZhou]
4 CRM internatinoal
5 CRMBM - Centre de résonance magnétique biologique et médicale
6 AMU - Aix Marseille Université
7 CNRS - Centre National de la Recherche Scientifique
8 CEMEREM - Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - APHM]
9 University of Melbourne
10 LIP - Laboratoire d'Imagerie Paramétrique
11 ICM - Institut du Cerveau = Paris Brain Institute
12 Department of Neurosurgery
13 ToNIC - Toulouse NeuroImaging Center
14 LML - Laboratoire de Mécanique de Lille - FRE 3723

acquisition. In this work, a server system that automatically reconstructs QSM and exchange images with the scanner using the DICOM standard is demonstrated using a multi-site, multi-vendor reproducibility study and a large, single-site, multi-scanner image quality review study in in a clinical environment. Methods: A single healthy subject was scanned with a 3D multi-echo gradient echo sequence at 9 sites around the world using scanners from three manufacturers. A high resolution (HiRes, 0.5×0.5×1mm 3 reconstructed) and standard resolution (StdRes, 0.5×0.5×3mm 3) protocol was performed. ROI analysis of various white matter and gray matter regions was performed to investigate reproducibility across sites. At one institution, a retrospective multi-scanner image quality review was carried out of all clinical QSM images acquired consecutively in one month. Results: Reconstruction times using a GPU were 29±22s (StdRes), and 55±39s (HiRes). ROI standard deviation across sites was below 24ppb (StdRes) and 17ppb (HiRes). Correlations between ROI averages across sites were on average 0.92 (StdRes) and 0.96 (HiRes). Image quality review of 873 consecutive patients revealed diagnostic or excellent image quality in 96% of patients. Conclusion: Online QSM reconstruction for a variety of sites and scanner platforms with low cross-site ROI standard deviation is demonstrated. Image quality review revealed diagnostic or excellent image quality in 96% of 873 patients.

Mots clés: Quantitative Susceptibility Mapping; Software; Clinic

Domaines: Sciences du Vivant [q-bio]

Pascal Spincemaille, Zhe Liu, Shun Zhang, Ilhami Kovanlikaya, Matteo Ippoliti, et al.. Clinical Integration of Automated Processing for Brain Quantitative Susceptibility Mapping: Multi‐Site Reproducibility and Single‐Site Robustness. Journal of Neuroimaging, 2019, ⟨10.1111/JON.12658⟩. ⟨hal-02299783⟩