FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2076139701> ?p ?o ?g. }

• W2076139701 endingPage "1100" @default.
• W2076139701 startingPage "1094" @default.
• W2076139701 abstract "In-vivo quantification of serotonin transporters (SERT) in human brain has been a mainstay of molecular imaging in the field of neuropsychiatric disorders and helped to explore the underpinnings of several medical conditions, therapeutic and environmental influences. The emergence of PET/MR hybrid systems and the heterogeneity of SERT binding call for the development of efficient methods making the investigation of larger or vulnerable populations with limited scanner time and simultaneous changes in molecular and functional measures possible. We propose [11C]DASB bolus plus constant infusion for these applications and validate it against standard analyses of dynamic PET data.[11C]DASB bolus/infusion optimization was performed on data acquired after [11C]DASB bolus in 8 healthy subjects. Subsequently, 16 subjects underwent one scan using [11C]DASB bolus plus constant infusion with Kbol 160–179 min and one scan after [11C]DASB bolus for inter-method reliability analysis. Arterial blood sampling and metabolite analysis were performed for all scans. Distribution volumes (VT) were obtained using Logan plots for bolus scans and ratios between tissue and plasma parent activity for bolus plus infusion scans for different time spans of the scan (VT-70 for 60–70 min after start of tracer infusion, VT-90 for 75–90 min, VT-120 for 100–120 min) in 9 subjects. Omitting blood data, binding potentials (BPND) obtained using multilinear reference tissue modeling (MRTM2) and cerebellar gray matter as reference region were compared in 11 subjects.A Kbol of 160 min was observed to be optimal for rapid equilibration in thalamus and striatum. VT-70 showed good intraclass correlation coefficients (ICCs) of 0.61–0.70 for thalamus, striatal regions and olfactory cortex with bias ≤5.1% compared to bolus scans. ICCs increased to 0.72–0.78 for VT-90 and 0.77–0.93 for VT-120 in these regions. BPND-90 had negligible bias ≤2.5%, low variability ≤7.9% and ICCs of 0.74–0.87; BPND-120 had ICCs of 0.73–0.90. Low-binding cortical regions and cerebellar gray matter showed a positive bias of ~8% and ICCs 0.57–0.68 at VT-90. Cortical BPND suffered from high variability and bias, best results were obtained for olfactory cortex and anterior cingulate cortex with ICC=0.74–0.75 for BPND-90. High-density regions amygdala and midbrain had a negative bias of −5.5% and −22.5% at VT-90 with ICC 0.70 and 0.63, respectively.We have optimized the equilibrium method with [11C]DASB bolus plus constant infusion and demonstrated good inter-method reliability with accepted standard methods and for SERT quantification using both VT and BPND in a range of different brain regions. With as little as 10–15 min of scanning valid estimates of SERT VT and BPND in thalamus, amygdala, striatal and high-binding cortical regions could be obtained. Blood sampling seems vital for valid quantification of SERT in low-binding cortical regions. These methods allow the investigation of up to three subjects with a single radiosynthesis." @default.
• W2076139701 created "2016-06-24" @default.
• W2076139701 creator A5044995419 @default.
• W2076139701 date "2014-01-01" @default.
• W2076139701 modified "2023-09-26" @default.
• W2076139701 title "PET Neuroimaging: The White Elephant Packs His Trunk?" @default.
• W2076139701 cites W1524830540 @default.
• W2076139701 cites W1964724689 @default.
• W2076139701 cites W1968641461 @default.
• W2076139701 cites W1970324570 @default.
• W2076139701 cites W1971169197 @default.
• W2076139701 cites W1971320702 @default.
• W2076139701 cites W1973142065 @default.
• W2076139701 cites W1979289529 @default.
• W2076139701 cites W1980092933 @default.
• W2076139701 cites W1980294910 @default.
• W2076139701 cites W1982352919 @default.
• W2076139701 cites W1983078779 @default.
• W2076139701 cites W1984198260 @default.
• W2076139701 cites W1984935060 @default.
• W2076139701 cites W1987110004 @default.
• W2076139701 cites W1987223490 @default.
• W2076139701 cites W1989613983 @default.
• W2076139701 cites W1995007472 @default.
• W2076139701 cites W1995043424 @default.
• W2076139701 cites W1996153970 @default.
• W2076139701 cites W2000292092 @default.
• W2076139701 cites W2001639140 @default.
• W2076139701 cites W2003804842 @default.
• W2076139701 cites W2003816004 @default.
• W2076139701 cites W2004564253 @default.
• W2076139701 cites W2010021812 @default.
• W2076139701 cites W2012095191 @default.
• W2076139701 cites W2012689537 @default.
• W2076139701 cites W2014341650 @default.
• W2076139701 cites W2014418634 @default.
• W2076139701 cites W2015259521 @default.
• W2076139701 cites W2017046927 @default.
• W2076139701 cites W2017195811 @default.
• W2076139701 cites W2018376941 @default.
• W2076139701 cites W2021571976 @default.
• W2076139701 cites W2030905688 @default.
• W2076139701 cites W2035522843 @default.
• W2076139701 cites W2035969994 @default.
• W2076139701 cites W2039250772 @default.
• W2076139701 cites W2040558597 @default.
• W2076139701 cites W2042102706 @default.
• W2076139701 cites W2042879184 @default.
• W2076139701 cites W2051471104 @default.
• W2076139701 cites W2051725147 @default.
• W2076139701 cites W2052041752 @default.
• W2076139701 cites W2053923183 @default.
• W2076139701 cites W2054964655 @default.
• W2076139701 cites W2056647705 @default.
• W2076139701 cites W2057025290 @default.
• W2076139701 cites W2062325737 @default.
• W2076139701 cites W2065912590 @default.
• W2076139701 cites W2070988431 @default.
• W2076139701 cites W2071156130 @default.
• W2076139701 cites W2072747415 @default.
• W2076139701 cites W2073303281 @default.
• W2076139701 cites W2074584947 @default.
• W2076139701 cites W2080613300 @default.
• W2076139701 cites W2080951328 @default.
• W2076139701 cites W2083307968 @default.
• W2076139701 cites W2086080603 @default.
• W2076139701 cites W2088789882 @default.
• W2076139701 cites W2095377654 @default.
• W2076139701 cites W2096407697 @default.
• W2076139701 cites W2099916848 @default.
• W2076139701 cites W2104260785 @default.
• W2076139701 cites W2105888777 @default.
• W2076139701 cites W2106565313 @default.
• W2076139701 cites W2112278807 @default.
• W2076139701 cites W2112596612 @default.
• W2076139701 cites W2117568811 @default.
• W2076139701 cites W2130722147 @default.
• W2076139701 cites W2132614734 @default.
• W2076139701 cites W2137787635 @default.
• W2076139701 cites W2139849835 @default.
• W2076139701 cites W2155107321 @default.
• W2076139701 cites W2156851696 @default.
• W2076139701 cites W2165757806 @default.
• W2076139701 cites W4250150389 @default.
• W2076139701 doi "https://doi.org/10.1016/j.neuroimage.2013.08.020" @default.
• W2076139701 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23959198" @default.
• W2076139701 hasPublicationYear "2014" @default.
• W2076139701 type Work @default.
• W2076139701 sameAs 2076139701 @default.
• W2076139701 citedByCount "12" @default.
• W2076139701 countsByYear W20761397012014 @default.
• W2076139701 countsByYear W20761397012015 @default.
• W2076139701 countsByYear W20761397012017 @default.
• W2076139701 countsByYear W20761397012019 @default.
• W2076139701 countsByYear W20761397012022 @default.
• W2076139701 countsByYear W20761397012023 @default.
• W2076139701 crossrefType "journal-article" @default.
• W2076139701 hasAuthorship W2076139701A5044995419 @default.

• next