PURPOSE: Although specific positron emission tomography (PET) scanners have been developed for small animals, spatial resolution remains one of the most critical technical limitations, particularly in the evaluation of the rodent brain. The purpose of the present study was to examine the reliability of voxel-based statistical analysis (Statistical Parametric Mapping, SPM) applied to (18)F-fluorodeoxyglucose (FDG) PET images of the rat brain, acquired on a small animal PET not specifically designed for rodents. The gold standard for the validation of the PET results was the autoradiography of the same animals acquired under the same physiological conditions, reconstructed as a 3-D volume and analysed using SPM. METHODS: Eleven rats were studied under two different conditions: conscious or under inhalatory anaesthesia during (18)F-FDG uptake. All animals were studied in vivo under both conditions in a dedicated small animal Philips MOSAIC PET scanner and magnetic resonance images were obtained for subsequent spatial processing. Then, rats were randomly assigned to a conscious or anaesthetized group for postmortem autoradiography, and slices from each animal were aligned and stacked to create a 3-D autoradiographic volume. Finally, differences in (18)F-FDG uptake between conscious and anaesthetized states were assessed from PET and autoradiography data by SPM analysis and results were compared. RESULTS: SPM results of PET and 3-D autoradiography are in good agreement and led to the detection of consistent cortical differences between the conscious and anaesthetized groups, particularly in the bilateral somatosensory cortices. However, SPM analysis of 3-D autoradiography also highlighted differences in the thalamus that were not detected with PET. CONCLUSION: This study demonstrates that any difference detected with SPM analysis of MOSAIC PET images of rat brain is detected also by the gold standard autoradiographic technique, confirming that this methodology provides reliable results, although partial volume effects might make it difficult to detect slight differences in small regions.
PURPOSE: Although specific positron emission tomography (PET) scanners have been developed for small animals, spatial resolution remains one of the most critical technical limitations, particularly in the evaluation of the rodent brain. The purpose of the present study was to examine the reliability of voxel-based statistical analysis (Statistical Parametric Mapping, SPM) applied to (18)F-fluorodeoxyglucose (FDG) PET images of the rat brain, acquired on a small animal PET not specifically designed for rodents. The gold standard for the validation of the PET results was the autoradiography of the same animals acquired under the same physiological conditions, reconstructed as a 3-D volume and analysed using SPM. METHODS: Eleven rats were studied under two different conditions: conscious or under inhalatory anaesthesia during (18)F-FDG uptake. All animals were studied in vivo under both conditions in a dedicated small animal Philips MOSAIC PET scanner and magnetic resonance images were obtained for subsequent spatial processing. Then, rats were randomly assigned to a conscious or anaesthetized group for postmortem autoradiography, and slices from each animal were aligned and stacked to create a 3-D autoradiographic volume. Finally, differences in (18)F-FDG uptake between conscious and anaesthetized states were assessed from PET and autoradiography data by SPM analysis and results were compared. RESULTS: SPM results of PET and 3-D autoradiography are in good agreement and led to the detection of consistent cortical differences between the conscious and anaesthetized groups, particularly in the bilateral somatosensory cortices. However, SPM analysis of 3-D autoradiography also highlighted differences in the thalamus that were not detected with PET. CONCLUSION: This study demonstrates that any difference detected with SPM analysis of MOSAIC PET images of rat brain is detected also by the gold standard autoradiographic technique, confirming that this methodology provides reliable results, although partial volume effects might make it difficult to detect slight differences in small regions.
Authors: Julie L Wang; Shunichi Oya; Ajit K Parhi; Brian P Lieberman; Karl Ploessl; Catherine Hou; Hank F Kung Journal: Nucl Med Biol Date: 2010-05 Impact factor: 2.408
Authors: Petra Schweinhardt; Peter Fransson; Lars Olson; Christian Spenger; Jesper L R Andersson Journal: J Neurosci Methods Date: 2003-10-30 Impact factor: 2.390
Authors: Cindy Casteels; Peter Vermaelen; Johan Nuyts; Annemie Van Der Linden; Veerle Baekelandt; Luc Mortelmans; Guy Bormans; Koen Van Laere Journal: J Nucl Med Date: 2006-11 Impact factor: 10.057
Authors: Vesna Sossi; Katherine Dinelle; Geoffrey J Topping; James E Holden; Doris Doudet; Michael Schulzer; Thomas J Ruth; A Jon Stoessl; Raul de la Fuente-Fernandez Journal: J Neurochem Date: 2009-01-22 Impact factor: 5.372
Authors: Michael Michaelides; Sarah Ann R Anderson; Mala Ananth; Denis Smirnov; Panayotis K Thanos; John F Neumaier; Gene-Jack Wang; Nora D Volkow; Yasmin L Hurd Journal: J Clin Invest Date: 2013-11-15 Impact factor: 14.808
Authors: M Kessler; M Mamach; R Beutelmann; M Lukacevic; S Eilert; P Bascuñana; A Fasel; F M Bengel; J P Bankstahl; T L Ross; G M Klump; G Berding Journal: Mol Imaging Biol Date: 2020-04 Impact factor: 3.488
Authors: Pablo Bascuñana; James T Thackeray; M Bankstahl; Frank M Bengel; Jens P Bankstahl Journal: Mol Imaging Biol Date: 2019-12 Impact factor: 3.488
Authors: Boris von Reutern; Barbara Grünecker; Behrooz H Yousefi; Gjermund Henriksen; Michael Czisch; Alexander Drzezga Journal: Mol Imaging Biol Date: 2013-10 Impact factor: 3.488
Authors: Pablo Bascuñana; Julián Javela; Mercedes Delgado; Rubén Fernández de la Rosa; Ahmed Anis Shiha; Luis García-García; Miguel Ángel Pozo Journal: Mol Imaging Biol Date: 2016-10 Impact factor: 3.488
Authors: Tsang-Wei Tu; Wael G Ibrahim; Neekita Jikaria; Jeeva P Munasinghe; Jaclyn A Witko; Dima A Hammoud; Joseph A Frank Journal: Sci Rep Date: 2018-01-12 Impact factor: 4.379