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Young T. Hong

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

4 papers

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YNIMG Journal 2021 Journal Article

Validation of a combined image derived input function and venous sampling approach for the quantification of [18F]GE-179 PET binding in the brain

Marian Galovic
Kjell Erlandsson
Tim D. Fryer
Young T. Hong
Roido Manavaki
Hasan Sari
Sarah Chetcuti
Benjamin A. Thomas

Blood-based kinetic analysis of PET data relies on an accurate estimate of the arterial plasma input function (PIF). An alternative to invasive measurements from arterial sampling is an image-derived input function (IDIF). However, an IDIF provides the whole blood radioactivity concentration, rather than the required free tracer radioactivity concentration in plasma. To estimate the tracer PIF, we corrected an IDIF from the carotid artery with estimates of plasma parent fraction (PF) and plasma-to-whole blood (PWB) ratio obtained from five venous samples. We compared the combined IDIF+venous approach to gold standard data from arterial sampling in 10 healthy volunteers undergoing [18F]GE-179 brain PET imaging of the NMDA receptor. Arterial and venous PF and PWB ratio estimates determined from 7 patients with traumatic brain injury (TBI) were also compared to assess the potential effect of medication. There was high agreement between areas under the curves of the estimates of PF (r = 0. 99, p<0. 001), PWB ratio (r = 0. 93, p<0. 001), and the PIF (r = 0. 92, p<0. 001) as well as total distribution volume (VT ) in 11 regions across the brain (r = 0. 95, p<0. 001). IDIF+venous VT had a mean bias of −1. 7% and a comparable regional coefficient of variation (arterial: 21. 3 ± 2. 5%, IDIF+venous: 21. 5 ± 2. 0%). Simplification of the IDIF+venous method to use only one venous sample provided less accurate V T estimates (mean bias 9. 9%; r = 0. 71, p<0. 001). A version of the method that avoids the need for blood sampling by combining the IDIF with population-based PF and PWB ratio estimates systematically underestimated VT (mean bias −20. 9%), and produced VT estimates with a poor correlation to those obtained using arterial data (r = 0. 45, p<0. 001). Arterial and venous blood data from 7 TBI patients showed high correlations for PF (r = 0. 92, p = 0. 003) and PWB ratio (r = 0. 93, p = 0. 003). In conclusion, the IDIF+venous method with five venous samples provides a viable alternative to arterial sampling for quantification of [18F]GE-179 VT.

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YNICL Journal 2020 Journal Article

Correlation of microglial activation with white matter changes in dementia with Lewy bodies

Nicolas Nicastro
Elijah Mak
Guy B. Williams
Ajenthan Surendranathan
W Richard Bevan-Jones
Luca Passamonti
Patricia Vàzquez Rodrìguez
Li Su

C]-PK11195 binding in frontal, temporal, and occipital lobes. However, microglial activation was not significantly associated with grey matter changes. Our study suggests that increased microglial activation is associated with a relative preservation of white matter and cognition in DLB, positioning neuroinflammation as a potential early marker of DLB etio-pathogenesis.

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YNIMG Journal 2011 Journal Article

Quantification of receptor–ligand binding potential in sub-striatal domains using probabilistic and template regions of interest

Natalia del Campo
Roger J. Tait
Julio Acosta-Cabronero
Young T. Hong
David Izquierdo-Garcia
Rob Smith
Franklin I. Aigbirhio
Barbara J. Sahakian

Sub-striatal regions of interest (ROIs) are widely used in PET studies to investigate the role of dopamine in the modulation of neural networks implicated in emotion, cognition and motor function. One common approach is that of Mawlawi et al. (2001) and Martinez et al. (2003), where each striatum is divided into five sub-regions. This study focuses on the use of two spatial normalization-based alternatives to manual sub-striatal ROI delineation per subject: manual ROI delineation on a template brain and the production of probabilistic ROIs from a set of subject-specific manually delineated ROIs. Two spatial normalization algorithms were compared: SPM5 unified segmentation and ART. The ability of these methods to quantify sub-striatal regional non-displaceable binding potential (BPND) and BPND % change (following methylphenidate) was tested on 32 subjects (16 controls and 16 ADHD patients) scanned with the dopamine D2/D3 ligand [18F]fallypride. Probabilistic ROIs produced by ART provided the best results, with similarity index values against subject-specific manual ROIs of 0. 75–0. 89 (mean 0. 84) compared to 0. 70–0. 85 (mean 0. 79) for template ROIs. Correlations (r) for BPND and BPND % change between subject-specific manual ROIs and these probabilistic ROIs of 0. 90–0. 98 (mean 0. 95) and 0. 98–1. 00 (mean 0. 99) respectively were superior overall to those obtained with template ROIs, although only marginally so for BPND % change. The significance of relationships between BPND measures and both behavioural tasks and methylphenidate plasma levels was preserved with ART combined with both probabilistic and template ROIs. SPM5 virtually matched the performance of ART for BPND % change estimation but was inferior for BPND estimation in caudate sub-regions. ART spatial normalization combined with probabilistic ROIs and to a lesser extent template ROIs provides an efficient and accurate alternative to time-consuming manual sub-striatal ROI delineation per subject, especially when the parameter of interest is BPND % change.

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YNIMG Journal 2010 Journal Article

Kinetic modelling using basis functions derived from two-tissue compartmental models with a plasma input function: General principle and application to [18F]fluorodeoxyglucose positron emission tomography

Young T. Hong
Tim D. Fryer

A kinetic modelling method for the determination of influx constant, K i is given that utilises basis functions derived from plasma input two-tissue compartmental models (BAFPIC). Two forms of the basis functions are given: BAFPICI with k 4 =0 (no product loss) and BAFPICR with k 4 non-zero. Simulations were performed using literature rate constant values for [18F]fluorodeoxyglucose (FDG) in both normal and abnormal brain pathology. Both homogeneous and heterogeneous tissues were simulated and this data was also used as input for other methods commonly used to determine K i: non-linear least squares compartmental modelling (NLLS), autoradiographic method and Patlak–Gjedde graphical analysis (PGA). The four methods were also compared for real FDG positron emission tomography (PET) data. For both k 4 =0 and k 4 non-zero simulated data BAFPIC had the best bias properties of the four methods. The autoradiographic method was always the best for variability but BAFPICI had lower variability than PGA and NLLS. For non-zero k 4 data, the variance of BAFPICR was inferior to PGA but still significantly superior to NLLS. K i maps calculated from real data substantiate the simulation results, with BAFPICI having lower noise than PGA. Voxel K i values from BAFPICI correlated well with those from PGA (r 2 =0. 989). BAFPIC is easy to implement and combines low bias with good noise properties for voxel-wise determination of K i for FDG. BAFPIC is suitable for determining K i for other tracers well characterised by a serial two-tissue compartment model and has the advantage of also producing values for individual kinetic constants and blood volume.

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