Positron Emission Tomographic Imaging of The

Supplementary Online Content

Oquendo MA, Galfalvy H, Sullivan GM, et al. Positron emission tomographic imaging of the

serotonergic system and prediction of risk and lethality of future suicidal behavior.

JAMA Psychiatry. Published online July 27, 2016. doi:10.1001/jamapsychiatry.2016.1478.

eMethods. Image Acquisition and Analysis

This supplementary material has been provided by the authors to give readers additional information about their work.

Downloaded From: https://jamanetwork.com/ on 09/24/2021 eMethods. Image Acquisition and Analysis

Radiochemistry and Input Function Measurement

Synthesis of [11C]WAY-100635 and [11C]DASB and assessment of arterial input function,

29,30 metabolites, and plasma free fraction (fP) measurements were as previously described.

Radioligand metabolite data were collected for the first 60 minutes of scan time.

Image Acquisition

PET imaging was performed with a ECAT HR+ (Siemens/CTI, Knoxville, TN, USA).

Briefly, a venous catheter was placed for radiotracer injection and an arterial catheter to obtain

samples for the input function. A polyurethane head holder system (Soule Medical, Tampa, FL,

USA) was molded around the subject’s head for immobilization purposes. A 10-minute

transmission scan was obtained prior to each radiotracer injection. At the end of the

transmission scan, [11C]DASB was administered intravenously as a bolus over 30 seconds.

Emission data were collected in 3D mode for 100 minutes with 19 frames of increasing

duration.31 Similarly, emission data for [11C]WAY-100635 were collected for 110 minutes as 20

frames of increasing duration after obtaining a transmission scan. Additional details of the PET

protocols for [11C]DASB and [11C]WAY-100635 are described elsewhere.31

Image Analysis

Image analysis was performed in MATLAB 2006b (The Mathworks, Natick, MA) using

Functional Magnetic Resonance Imaging of the Brain’s Linear Image Registration Tool (FLIRT)

v5.2.,32 Brain Extraction Tool v1.2,33 Statistical Parametric Mapping (SPM5) normalization,34

and segmentation routines.35 De-noising filter techniques were applied to all PET images

starting at frame five to correct for motion. Frames were aligned using rigid body FLIRT to the

Downloaded From: https://jamanetwork.com/ on 09/24/2021 MRI using FLIRT. T1-weighted magnetic resonance images (MRI) for PET image co-

registration and identification of regions of interest (ROIs) were acquired using a 1.5 T Signa

Advantage or a 3 T Signa HDx system (General Electric, Milwaukee, WI) as previously

described.30 An automated algorithm was used to obtain ROIs in this study using nonlinear

registration techniques to warp 18 manually outlined MRIs to the target image.36 At each voxel,

the probability of being within an ROI was calculated as the number of transformed template

ROIs assigned to that voxel divided by 18. Non-midline ROIs were averaged across

hemispheres. In previous work, this approach yielded very high correlations of binding as

compared to those obtained with manually-drawn ROIs (r2>0.98; 36).

Derivation of Regional Outcome Measures for Midbrain 5-HTT Binding Potential

Since no brain region appears devoid of specific binding with [11C]DASB, our outcome

37 measure does not rely on a reference region : VT/fP (where VT = volume of distribution in the

9 11 region of interest) [for details see Miller et al ]. [ C]DASB regional VT values were derived using

likelihood estimation in the graphical approach, to reduce its inherent noise-dependent bias.38,39

Brain activity was corrected for the plasma activity contribution, assuming a 5% blood volume

contribution to the region of interest (midbrain). In addition, we calculated other 5-HTT binding

40 outcome measures: BPF, BPP and BPND which were examined in sensitivity analyses.

Derivation of Regional Outcome Measures for 5-HT1A ROI Binding Potential

Although the optimal outcome measure in PET neuroreceptor studies is the number of

receptors available (Bavail), current technology only permits measurement of BPF=Bavail/KD.

41 Fortunately, there is no evidence for alterations in 5-HT1A KD in depression. Kinetic analysis

using an arterial input function and a two-tissue compartment (2T) model yields regional

11 30 volumes of (V) of distribution for [ C]WAY-100635. VND and VS are the distribution volumes of

40 the nondisplaceable and specific compartments, respectively. VT is the total regional

Downloaded From: https://jamanetwork.com/ on 09/24/2021 a 2T model, with the K1/k2 ratio fixed to that of the cerebellar white matter (CWM), a reference

29 region with virtually no 5-HT1A binding. A 1T model was used for CWM. BPF was calculated

as (VT(ROI)–VT(CWM))/fP. Plasma total activity was calculated assuming a 5% blood volume in the

ROI and subtracted from the regional activity. Kinetic parameters were derived by nonlinear

regression using MATLAB. ROI contours were processed using the segmented MRI to confine

analyses to gray matter voxels. The ROIs included: raphe nucleus, amygdala, hippocampus;

parahippocampal gyrus, anterior cingulate, medial and dorsolateral PFC, insular, parietal,

temporal, orbital and occipital cortex. A fixed volume elliptical ROI (2cm3) was placed on the RN

in dorsal midbrain on a mean PET image, as previously described.42 A cylindrical ROI was

drawn in the CWM.29

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