scholarly journals Tracking and characterizing the head motion of unanaesthetized rats in positron emission tomography

2012 ◽  
Vol 9 (76) ◽  
pp. 3094-3107 ◽  
Author(s):  
Andre Kyme ◽  
Steven Meikle ◽  
Clive Baldock ◽  
Roger Fulton

Positron emission tomography (PET) is an important in vivo molecular imaging technique for translational research. Imaging unanaesthetized rats using motion-compensated PET avoids the confounding impact of anaesthetic drugs and enables animals to be imaged during normal or evoked behaviour. However, there is little published data on the nature of rat head motion to inform the design of suitable marker-based motion-tracking set-ups for brain imaging—specifically, set-ups that afford close to uninterrupted tracking. We performed a systematic study of rat head motion parameters for unanaesthetized tube-bound and freely moving rats with a view to designing suitable motion-tracking set-ups in each case. For tube-bound rats, using a single appropriately placed binocular tracker, uninterrupted tracking was possible greater than 95 per cent of the time. For freely moving rats, simulations and measurements of a live subject indicated that two opposed binocular trackers are sufficient (less than 10% interruption to tracking) for a wide variety of behaviour types. We conclude that reliable tracking of head pose can be achieved with marker-based optical-motion-tracking systems for both tube-bound and freely moving rats undergoing PET studies without sedation.

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Carlos Velasco ◽  
Adriana Mota-Cobián ◽  
Jesús Mateo ◽  
Samuel España

Abstract Background Multi-tracer positron emission tomography (PET) imaging can be accomplished by applying multi-tracer compartment modeling. Recently, a method has been proposed in which the arterial input functions (AIFs) of the multi-tracer PET scan are explicitly derived. For that purpose, a gamma spectroscopic analysis is performed on blood samples manually withdrawn from the patient when at least one of the co-injected tracers is based on a non-pure positron emitter. Alternatively, these blood samples required for the spectroscopic analysis may be obtained and analyzed on site by an automated detection device, thus minimizing analysis time and radiation exposure of the operating personnel. In this work, a new automated blood sample detector based on silicon photomultipliers (SiPMs) for single- and multi-tracer PET imaging is presented, characterized, and tested in vitro and in vivo. Results The detector presented in this work stores and analyzes on-the-fly single and coincidence detected events. A sensitivity of 22.6 cps/(kBq/mL) and 1.7 cps/(kBq/mL) was obtained for single and coincidence events respectively. An energy resolution of 35% full-width-half-maximum (FWHM) at 511 keV and a minimum detectable activity of 0.30 ± 0.08 kBq/mL in single mode were obtained. The in vivo AIFs obtained with the detector show an excellent Pearson’s correlation (r = 0.996, p < 0.0001) with the ones obtained from well counter analysis of discrete blood samples. Moreover, in vitro experiments demonstrate the capability of the detector to apply the gamma spectroscopic analysis on a mixture of 68Ga and 18F and separate the individual signal emitted from each one. Conclusions Characterization and in vivo evaluation under realistic experimental conditions showed that the detector proposed in this work offers excellent sensibility and stability. The device also showed to successfully separate individual signals emitted from a mixture of radioisotopes. Therefore, the blood sample detector presented in this study allows fully automatic AIFs measurements during single- and multi-tracer PET studies.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Johannes Notni ◽  
Florian T. Gassert ◽  
Katja Steiger ◽  
Peter Sommer ◽  
Wilko Weichert ◽  
...  

Following publication of the original article [1], the authors have reported an error in the ‘Histopathology’ (under ‘Materials and methods’) section of the article that compromises the reproducibility of the paper.


Sign in / Sign up

Export Citation Format

Share Document