Abstract
It has recently been suggested that multicenter preclinical stroke studies should be carried out to improve translation from bench to bedside, but the accuracy of magnetic resonance imaging (MRI) scanners routinely used in experimental stroke has not yet been evaluated. We aimed to assess and compare geometric accuracy of preclinical scanners and examine the longitudinal stability of one scanner using a simple quality assurance (QA) protocol. Six 7 Tesla animal scanners across six different preclinical imaging centers throughout Europe were used to scan a small structural phantom and estimate linear scaling errors in all orthogonal directions and volumetric errors. Between-scanner imaging consisted of a standard sequence and each center’s preferred sequence for the assessment of infarct size in rat models of stroke. The standard sequence was also used to evaluate the drift in accuracy of the worst performing scanner over a period of six months following basic gradient calibration. Scaling and volumetric errors using the standard sequence were less variable than corresponding errors using different stroke sequences. The errors for one scanner, estimated using the standard sequence, were very high (above 4% scaling errors for each orthogonal direction, 18.73% volumetric error). Calibration of the gradient coils in this system reduced scaling errors to within ±1.0%; these remained stable during the subsequent 6-month assessment. In conclusion, despite decades of use in experimental studies, preclinical MRI still suffers from poor and variable geometric accuracy, influenced by the use of miscalibrated systems and various types of sequences for the same purpose. For effective pooling of data in multicenter studies, centers should adopt standardized procedures for system QA and in vivo imaging.
Highlights
Animal studies of disease models often use geometric measurements from structural magnetic resonance imaging (MRI) data as primary outcomes for evaluating the efficacy of tested interventions
Inspection of 2D deformation maps (Fig 3) and corresponding MRI images through the center of the phantom (S2 Fig) reveals that overall distortion is characterized by two differing patterns; images from scanner “A” have an almost isotropic expansion, whereas images from the rest of the scanners show the presence of minor non-linearities, across phase encoding and predominantly in stroke sequences
Despite that the use of preclinical MRI systems in experimental research was intensified long ago by the need of in vivo assessment of injury over extensive periods of time, individual centers still rely on annual maintenance of their systems that is performed at different times across centers [18], and hardware and protocols for in vivo imaging are highly heterogeneous between centers [9]
Summary
Animal studies of disease models often use geometric measurements from structural magnetic resonance imaging (MRI) data as primary outcomes for evaluating the efficacy of tested interventions. Conventional techniques, such as T1-weighted or T2-weighted imaging, are employed to quantify the extent of tissue injury in stroke [1], cancer [2] and multiple sclerosis [3], among other diseases. MRI methodology including scanning protocols and data analysis techniques vary significantly between research centers [9] The impact of these shortfalls will become more evident in the future, as animal experimentation is set to shift from single-center to multicenter studies [10, 11]. Such studies will have high demands for accuracy, reproducibility and concordance of measurements between scanners for efficient pooling of data and valid statistical inferences, and unless the conduct of MRI is of a sufficient standard across preclinical imaging centers these requirements cannot be met
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
