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\begin{document}

\title{Changes of ``brain-GI'' interplay in Parkinson's disease: a pilot study
of dynamic total-body {[}11C{]}CFT PET/CT and kinetic modeling}



\author[1]{Mei Xin}%
\author[2]{Yihan Wang}%
\author[2]{Xinlan Yang}%
\author[1]{Lianghua Li}%
\author[1]{Cheng Wang}%
\author[2]{Yue Gu}%
\author[1]{Chenpeng Zhang}%
\author[1]{Gang Huang}%
\author[2]{Yun Zhou}%
\author[1]{Jianjun Liu}%
\affil[1]{Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital}%
\affil[2]{Central Research Institute, United Imaging Healthcare Group Co, Ltd, Shanghai, China.}%


\vspace{-1em}



  
  \date{May 25, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
Purpose: Parkinson's disease (PD) is a neurodegenerative disease
characterized by progressive loss of dopaminergic neurons in the brain.
To achieve better explorations of dopamine changes both centrally and
peripherally, we employed uEXPLORER dynamic {[}11C{]}CFT PET/CT imaging
combined with voxel-wise kinetic modeling. Methods: Eleven participants
(five patients, PD and six healthy volunteers, HC) underwent 75-min
dynamic scans were enrolled. Volumes of interest for four nigrostriatal
nuclei (caudate, putamen, pallidum and substantial nigra) and three
digestive organs (pancreas, stomach and duodenum) were delineated.
Total-body parametric images of relative transporter rate constant (R1)
and distribution volume ratio (DVR) using the simplified reference
tissue model (SRTM2) were quantitatively generated by a linear
regression with spatial-constraint algorithm. Standardized uptake value
ratio (SUVR) at early and late phase were calculated as the
semi-quantitative substitutes. Results: Significant differences between
the two groups were identified in DVR and SUVRLP of putamen (P
\textless{} 0.05) and SUVREP of stomach (P \textless{} 0.01). For HC
group, negative correlations of R1 were achieved between stomach and
both putamen and substantial nigra (all P \textless{} 0.05); positive
correlations of DVR were identified between pancreas and all four brain
nuclei (all P \textless{} 0.05). Yet in PD group, correlations of R1 or
DVR between the targeted digestive and brain areas were considerably
diminished. Similar trends in correlations were also found in SUVR
analysis. Conclusions: We introduced a pioneering approach using dynamic
total-body {[}11C{]}CFT PET/CT imaging to investigate distinctive
patterns of potential ``brain-GI'' interplays, which may provide new
insights towards the understanding of PD.%
\end{abstract}%



\sloppy


\textbf{Changes of} \textbf{``brain-GI'' interplay in Parkinson's
disease: a pilot study of dynamictotal-body
{[}\textsuperscript{11}C{]}CFT PET/CT and kinetic modeling}

Running title: Total-body PET on ``brain-GI'' interplay

\textbf{Mei Xin \textsuperscript{1+}, Yihan Wang \textsuperscript{2+},
Xinlan Yang \textsuperscript{2}, Lianghua Li \textsuperscript{1}, Cheng
Wang \textsuperscript{1}, Yue Gu\textsuperscript{2}, Chenpeng Zhang
\textsuperscript{1}, Gang Huang\textsuperscript{1}, Yun Zhou
\textsuperscript{2*}, Jianjun Liu\textsuperscript{1*}}

\textsuperscript{\textbf{1}} Department of Nuclear Medicine, Renji
Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai
200127, China

\textsuperscript{\textbf{2}} Central Research Institute, United Imaging
Healthcare Group Co, Ltd, Shanghai 201807, China.

\textsuperscript{\textbf{+}} \textbf{These authors contribute equally to
the article.}

\textbf{* Corresponding Authors} : \textbf{Yun Zhou} , 2258 Chengbei
Road, Shanghai 201807, China, Tel: 862167076888, Fax: 862167076889,
Email: yun.zhou@united-imaging.com; \textbf{Jianjun Liu} , 160 Pujian
Road, Shanghai 200127, China, Tel: 862168383098, Fax: none, Email:
nuclearj@163.com

\textbf{Conflict of interest} : All authors declare that they have no
conflict of interest.

\textbf{Funding} : This work was supported by the National Key Research
and Development Program of China (Grant number 2021YFA0910000), and the
National Natural Science Foundation of China (Grant number 82171972).



\textbf{Abstract}

\textbf{Purpose:} Parkinson's disease (PD) is a neurodegenerative
disease characterized by progressive loss of dopaminergic neurons in the
brain. To achieve better explorations of dopamine changes both centrally
and peripherally, we employed uEXPLORER dynamic
{[}\textsuperscript{11}C{]}CFT PET/CT imaging combined with voxel-wise
kinetic modeling.

\textbf{Methods:} Eleven participants (five patients, PD and six healthy
volunteers, HC) underwent 75-min dynamic scans were enrolled. Volumes of
interest for four nigrostriatal nuclei (caudate, putamen, pallidum and
substantial nigra) and three digestive organs (pancreas, stomach and
duodenum) were delineated. Total-body parametric images of relative
transporter rate constant (R\textsubscript{1}) and distribution volume
ratio (DVR) using the simplified reference tissue model (SRTM2) were
quantitatively generated by a linear regression with spatial-constraint
algorithm. Standardized uptake value ratio (SUVR) at early and late
phase were calculated as the semi-quantitative substitutes.

\textbf{Results:} Significant differences between the two groups were
identified in DVR and SUVR\textsubscript{LP} of putamen
(\emph{P}\textless{} 0.05) and SUVR\textsubscript{EP} of stomach
(\emph{P}\textless{} 0.01). For HC group, negative correlations of
R\textsubscript{1} were achieved between stomach and both putamen and
substantial nigra (all \emph{P} \textless{} 0.05); positive correlations
of DVR were identified between pancreas and all four brain nuclei
(all\emph{P} \textless{} 0.05). Yet in PD group, correlations of
R\textsubscript{1} or DVR between the targeted digestive and brain areas
were considerably diminished. Similar trends in correlations were also
found in SUVR analysis.

\textbf{Conclusions:} We introduced a pioneering approach using dynamic
total-body {[}\textsuperscript{11}C{]}CFT PET/CT imaging to investigate
distinctive patterns of potential ``brain-GI'' interplays, which may
provide new insights towards the understanding of PD.

\textbf{Key words:} Total-body PET/CT; Parkinson's disease; ``Brain-GI''
interplay; {[}\textsuperscript{11}C{]}CFT; Parametric imaging



\textbf{Introduction}

Parkinson's disease (PD) is a progressive neurodegenerative disorder
common in elderly population that increases in prevalence with age. The
principal pathophysiological change of PD lies in the depletion of
nigrostriatal dopaminergic neurons, leading to a series of motor
symptoms including bradykinesia, tremor, rigidity and gait
instability\textsuperscript{1}. With the broaden understanding of the
disease timeline, both the ``brain-first'' or ``body-first'' etiologic
hypotheses emphasize on the integrity of the organism and the
interactions between the central and peripheral nerve systems,
particularly in relation to the gastrointestinal (GI)
organs\textsuperscript{2}. Widely distributed across the GI tract, the
enteric nerve system (ENS), termed as ``the second brain'', accounts for
the largest division of the peripheral nerve system \textsuperscript{3,
4}. Recent studies have suggested that the communication between the
brain and digestive systems may be mediated by certain agents present in
both areas, potentially influencing the disease occurrence, development,
and modulation\textsuperscript{5}.

Dopamine transporter (DAT) is a neurotransmitter protein on the
presynaptic membrane that is responsible for the reuptake of
extracellular dopamine (DA) from the synaptic cleft and regulates the DA
neurotransmission and homeostasis. Besides the nigrostriatal pathway
within the brain, the expression of DAT can also be found at several
peripheral sites \textsuperscript{6}, and in turn influences numerous
peripheral functions including gastrointestinal motility, functioning in
a variety of neuropsychiatric disorders in PD. Immunohistochemical and
in situ hybridization studies indicated that DATs are abundantly
expressed in the GI track, including the two important nerve branches --
Meissner's and Auerbach's plexuses of the ENS, the gastric parietal
cells and mucosal blood vessel endothelia, duodenal lamina propria,
pancreatic excreting ducts and islets \textsuperscript{7-10}. Several
studies have also demonstrated the association between the striatal DAT
binding and the activities of gut microbes, suggesting DAT modulations
through the ``brain-GI'' axis\textsuperscript{11, 12}.

However, few suitable approaches are available to make a systemic and
quantitative analysis of DAT kinetic distribution in both the central
and peripheral organs of human. Nowadays, progress has been made to
understand the etiology of neurodegenerative diseases at molecular level
with the visualization of the imaging biomarkers. The most widely
accessible imaging approach is the use of PET or SPECT tracers for the
DAT
targets.\textsuperscript{11}C-2-beta-carbomethoxy-3-beta-(4-fluorophenyl)tropane
({[}\textsuperscript{11}C{]}CFT), a mature DAT positron imaging agent,
has been commonly used in brain imaging for the diagnosis of
PD\textsuperscript{13-15}. Moreover , in animal models, highly specific
uptakes of DAT radioligand {[}\textsuperscript{18}F{]}CFT have been
demonstrated in both the striatum and pancreas with the treatment of
selective DAT antagonist\textsuperscript{16}, showing the potential of
radionuclide-labeled CFT compound used to evaluate the interplay between
the central and GI regions. Meanwhile, breaking through the technical
limitations from the standard PET/CT with multi-beds scanning, the
super-high temporal-spatial resolution and 194 cm-super-long axial field
of view (AFOV) total-body PET/CT enables us to track the dynamic changes
of the internal tracer distribution in a real-time and quantitative
way\textsuperscript{17-19}. Precise time-activity curves (TACs) enables
the simultaneous study of the kinetic interplay between organs, which
may lead to better understanding of coordination between the brain
function and other physiological activities \textsuperscript{20}.
Compared to the conventional a-priori volume of interest (VOI) kinetic
analysis approach, the parametric imaging offers additional quantitative
values into varied pathophysiological alterations, which may emerge as a
standard for visualizing pathophysiology, diagnosing, monitoring
neurodegenerative disease progression, and assessing therapeutic
outcomes \textsuperscript{21}.

In this study, we employed two image-based methods to measure the
total-body dynamic {[}\textsuperscript{11}C{]}CFT kinetics between the
PD patients and healthy volunteers -- the quantitative analysis using a
simplified reference tissue model (SRTM2) and the semi-quantitative
measurement based on the standardized uptake value ratio (SUVR). Based
on the novel technical platform of dynamic
{[}\textsuperscript{11}C{]}CFT total-body PET/CT imaging, our study
aimed to explore the potential variation and correlations in the tracer
kinetics between the selected brain and GI regions.

\textbf{Methods}

\textbf{Participants}

Eleven participants including five untreated patients diagnosed as PD
(PD group) and six healthy volunteers as controls (HC group) underwent
{[}\textsuperscript{11}C{]}CFT total-body PET/CT scans in our department
from January to December 2021. The neurologic assessment for patients
including the third part of Unified Parkinson Disease Rating Scale (UPDRS
III), modified Hoehn and Yahr stage (mH-Y), and Non-motor Symptoms Scale
(NMSS) were recorded. The detailed characteristics of all participants
were listed in \textbf{Table 1} . Healthy volunteers were sourced from
health screening participants with no history of significant medical,
neuropsychiatric illnesses, or neoplastic diseases, which were excluded
using {[}\textsuperscript{18}F{]}FDG PET/CT. This retrospective study
followed the principles of the Declaration of Helsinki and has been
approved by the ethics committee of Renji Hospital with written informed
consent waived.

\textbf{Radiopharmaceutical Preparation}

The radionuclide, \textsuperscript{11}CO\textsubscript{2}, was prepared
by the medical cyclotron (HM-10, Sumitomo) in our department.
{[}\textsuperscript{11}C{]}CFT was produced by an automatic synthesis
module (CFN-MPS-200, Sumitomo) according to the previously reported
method\textsuperscript{22}. The radiochemical purity of
{[}\textsuperscript{11}C{]}CFT was above 95\%.

\textbf{Dynamic Total-Body PET/CT Acquisition and Reconstruction}

All participants underwent dynamic {[}\textsuperscript{11}C{]}CFT PET
imaging using a total-body PET/CT scanner (uEXPLORER, United Imaging
Healthcare). CT images were collected from vertex to toes for
attenuation correction prior to PET acquisition. A 75-min PET scan was
performed on each participant immediately after a lower limb intravenous
bolus injection of 431.4\selectlanguage{ngerman}±75.6 MBq \textsuperscript{11}C-CFT. The dynamic
PET images were corrected for radioactive decay, scatter, attenuation,
and random, and were reconstructed into a matrix with voxel size of 2.34
×2.34×2.89 mm\textsuperscript{3} in x, y, z direction with ordered
subset expectation maximization (OSEM) algorithm, time-of-flight (TOF)
and point-spread function (PSF). The images were split into 97 frames
(30×2 s, 12×5 s, 6×10 s, 4×30 s, 25×60 s, 15×120 s, 5×180
s)\textsuperscript{23, 24}.

\textbf{Dynamic PET Image Processing}

VOIs were manually drawn within descending aorta, duodenum, pancreas,
and stomach using PMOD 4.3 software (PMOD Technologies Ltd.), where the
descending aorta was selected to reflect the blood radiotracer
concentration. To extract the TACs from the brain regions, all PET
images were first processed by head motion correction and spatial
normalization, both using Statistical Parametric Mapping software
(SPM12, Wellcome Department of Imaging Neuroscience) in the MATLAB
(2019b, The MathWorks Inc.) environment, followed by the co-registration
of the PET images to the standard Montreal Neurologic Institute (MNI)
space based on an MRI template\textsuperscript{25}. Caudate, putamen,
pallidum, and substantial nigra, which are the major brain regions
associated with PD, were selected for the analysis. TACs of all organs
were then extracted for kinetic analysis. The mean standardized uptake
value (SUV\textsubscript{mean}) curves, which can be calculated as the
average radioactivity within each VOI at each frame normalized by the
ratio between the decay-corrected injected radiolabeled dose and body
weight of the participant, were generated based on the TACs. In the
SUV\textsubscript{mean} curve analysis of the brain nuclei, the
separation time was calculated as the time when the difference in group
means between the SUV\textsubscript{mean} of HC and PD reached to at
least 10\% of the mean SUV\textsubscript{mean} of HC group.

\textbf{Reference Tissue-based Kinetic Modeling}

The SRTM2 was used for the voxel-wise {[}\textsuperscript{11}C{]}CFT
kinetic analysis\textsuperscript{21, 26, 27}, which generated two
parametric images: R\textsubscript{1} (the ratio between the transport
rate constants of target and reference tissues) and DVR (distribution
volume ratio between the target and reference tissues). The
R\textsubscript{1} represents the relative transporter rate constant of
tracer from vascular space to the target organs or brain regions,
whereas DVR reflects the tracer specific binding to DAT. The occipital
lobe region lacking DAT distribution was selected as the reference
tissue. A linear regression with spatial constraint algorithm was used
to generate parametric images of R\textsubscript{1} and
DVR\textsuperscript{21, 28}.

To the best of our knowledge, no clinical studies have yet conducted a
total-body dynamic {[}\textsuperscript{11}C{]}CFT analysis utilizing the
voxel-wise SRTM2 method. Thus, we additionally performed the VOI-based
one-tissue compartmental modeling (1T2K) with the metabolite-corrected
TAC of descending aorta as the input function using PMOD to validate our
SRTM2 estimates \textsuperscript{28}. The tracer transport rate constant
(K\textsubscript{1}) and total distribution volume (V\textsubscript{T})
as the estimates for early blood perfusion and later tracer density were
generated to validate the use of R\textsubscript{1} and DVR,
respectively.

\textbf{Kinetic Analysis with Semi-Quantification Approach}

SUVR, calculated as the ratio between the SUV of the targeted area and
occipital lobe reference region, served as an approximation of early
blood perfusion and DAT expression level with an advantage of shorter
scan acquisition time for clinical setting. The whole dynamic scanning
period of {[}\textsuperscript{11}C{]}CFT was subdivided into the early
phase (SUVR\textsubscript{EP} for 1-3 min) and late phase
(SUVR\textsubscript{LP} for 60-75 min), where SUVR\textsubscript{EP} was
used to estimate R\textsubscript{1} and SUVR\textsubscript{LP} can be
used as an approximation of the tracer specific binding to DAT
resembling DVR \textsuperscript{21}.

\textbf{Statistical Analysis}

All statistical analysis were performed using R (version 4.2.0) and
GraphPad (version 9.0) software. The descriptive data of
SUV\textsubscript{mean} curve characteristics and quantification
estimates were presented as mean (standard deviation, SD). Pearson's
correlation analysis was used to compare the relationship between the
targeted areas, as well as assessing the agreement between the estimates
generated by different approaches. \emph{P} \textless{} 0.05 was
considered statistically significant.

\textbf{Results}

\textbf{Total-body dynamic {[}\textsuperscript{11}C{]}CFT PET Imaging}

The schematic PET/CT acquisition protocol, representative maximum
intensity projection (MIP) images, and the transverse views of cerebral
nuclei and GI organs acquired at different time points were shown
in\textbf{Figure 1} . In the total-body dynamic
{[}\textsuperscript{11}C{]}CFT PET imaging, the tracer uptake in the
central and peripheral regions throughout the entire body were clearly
visualized, even in deep brain areas like the substantial nigra, which
was usually limited by resolution with conventional PET scanner. Based
on the visual assessment, the uptake of {[}\textsuperscript{11}C{]}CFT
in the nigrostriatal nuclei of HC is intact and persistent, while PD
patients displayed asymmetric DAT depletion in the corresponding areas.
No distinct difference was observed from the visual assessment of GI
organ regions between the HC and PD groups.

\textbf{Characterization of SUV\textsubscript{mean} curve}

The SUV\textsubscript{mean} curves of descending aorta and occipital
lobe in the HC and PD groups were depicted in \textbf{Figure 2A}
and\textbf{B} , demonstrating negligible difference in curve pattern of
both regions between the two groups. As the time went on, the ascending
curves of the brain nuclei in the two groups started to separate: while
the {[}\textsuperscript{11}C{]}CFT uptake of HC group kept increasing,
the uptake of PD group tended to reach the ``plateau'' in advance
(\textbf{Figure 2C , Table 2} ). In putamen,
{[}\textsuperscript{11}C{]}CFT uptake of the two groups first showed an
early distinction (separation time = 2 min), and the statistical
significance was found in the highest SUV\textsubscript{mean} between
the two groups (\emph{P} \textless{}0.05).

The SUV\textsubscript{mean} curve patterns of the pancreas and duodenum
could be characterized as ``fast-in and slow-out'' in both groups, where
the peak activities of the HC group in these two organs were higher than
the PD group. In the stomach, a relatively faster rising uptake in PD
patients was observed in the early stage, yet the final
SUV\textsubscript{mean} of the HC group at 75 min appeared to be higher
(\textbf{Figure 2D} and \textbf{Table 2)} .

\textbf{Kinetic analysis features}

The total-body {[}\textsuperscript{11}C{]}CFT PET parametric images
based on the SRTM2 model were generated. The schematic formula of SRTM2
and representative R\textsubscript{1} and DVR parametric images of HC
and PD participants were illustrated in \textbf{Figure 3A} and\textbf{B}
. The statistically significant correlation was observed between the
parameters of quantitative and semi-quantitative analysis, including
R\textsubscript{1} and SUVR\textsubscript{EP} (\emph{r} =0.776,\emph{P}
\textless{}0.001), DVR and SUVR\textsubscript{LP}(\emph{r}
=0.921,\emph{P} \textless{}0.001), suggesting an agreement between the
two analysis approaches (\textbf{Figure 3C} ). In the comparison of the
quantitative parameters between HC and PD groups, statistical
significances were found between the HC and PD groups in terms of
SUVR\textsubscript{EP} of stomach (\emph{P} \textless{}0.01) and both
DVR and SUVR\textsubscript{LP}of putamen (\emph{P} \textless{}0.05)
(\textbf{Figure 3D} ).

We further demonstrated that the R\textsubscript{1} and DVR estimated
from the SRTM2 using the occipital lobe as the reference was highly
correlated with the K\textsubscript{1} and V\textsubscript{T} generated
from the 1T2K models (\emph{r} = 0.84 and 0.83, respectively,
both\emph{P} \textless{}0.0001) (\textbf{Supplemental Figure 1A}
and\textbf{B} ), suggesting the accurate tracer quantification without
arterial sampling.

\textbf{Correlations between the specific brain nuclei and GI organs}

Pairwise comparisons within the digestive and cerebral regions of the HC
and PD group were separately summarized (\textbf{Figure 4-5} ). For the
inter-nigrostriatal region correlations, strong positive correlation for
R\textsubscript{1}, DVR, SUVR\textsubscript{EP} and
SUVR\textsubscript{LP} were found among nearly all the four
nigrostriatal nuclei within the HC group (all \emph{P} \textless{}0.05).
Conversely, these correlations were notably diminished in the PD cohort.

For the ``brain-GI'' correlations within the HC group, the significant
negative correlations were revealed between the stomach and putamen for
both the early perfusion parameters R\textsubscript{1} (\emph{r}
=-0.833, \emph{P} \textless{}0.05) and SUVR\textsubscript{EP} (\emph{r}
=-0.821, \emph{P} \textless{}0.05). Meanwhile, the significant positive
correlation relationships of the tracer density parameters DVR and
SUVR\textsubscript{LP} were identified between pancreas and all the four
brain nuclei including caudate (\emph{r} =0.918, \emph{P}
\textless{}0.05 for DVR; \emph{r} =0.899,\emph{P} \textless{}0.05 for
SUVR\textsubscript{LP}), putamen (\emph{r} =0.977, \emph{P}
\textless{}0.001 for DVR; \emph{r} =0.993,\emph{P} \textless{}0.001 for
SUVR\textsubscript{LP}), pallidum (\emph{r} =0.909, \emph{P}
\textless{}0.05 for DVR; \emph{r} =0.828,\emph{P} \textless{}0.05 for
SUVR\textsubscript{LP}) and substantial nigra (\emph{r} =0.894, \emph{P}
\textless{}0.05 for DVR; \emph{r} =0.964,\emph{P} \textless{}0.01 for
SUVR\textsubscript{LP}). In contrast, among PD patients, significant
correlations between most of the brain nuclei and digestive organ
targets were absent, except for a positive correlation was observed
between the pancreas and pallidum (\emph{r}=0.912, \emph{P}
\textless{}0.05 for DVR; \emph{r} =0.904,\emph{P} \textless{}0.05 for
SUVR\textsubscript{LP}), and substantia nigra (\emph{r} =0.912, \emph{P}
\textless{}0.05 for SUVR\textsubscript{LP}). Additionally, the
V\textsubscript{T} of pancreas and putamen estimated using the VOI-based
1T2K were also significantly correlated in the HC group rather than PD
group (\textbf{Supplemental Figure 1C} ).

\textbf{Discussion}

Since discovered 200 years ago, the practice of exploring PD has never
stopped. According to the various and systemic symptoms of PD
populations, herein we attempted to break out the limitation of single
studies confined to the brain, with the application of
{[}\textsuperscript{11}C{]}CFT tracer targeting DAT and advantages of
the integrated dynamic total-body PET/CT imaging, aimed to
systematically evaluate the potential patterns related to the
dopaminergic changes and interactions among the digestive and cerebral
regions. Dopamine serves as a protective agent for human GI system,
preventing gastric and intestinal mucosa from injury, resisting against
peptic ulcer, and promoting ulcer healing\textsuperscript{29}. PD
patients also have a relatively high incidence of duodenal ulcers, while
the GI dysfunction or dysmotility are often likely due to the DA
deficiency or peripheral DAT depletion\textsuperscript{30}. Most of the
previous reports on DA and DAT focused on their neurotransmitter
function only in the central nerve system (CNS). However, certain
peripheral organs also have abundant DAT expression. Recent studies have
indicated that at the time when pathological \selectlanguage{greek}α-\selectlanguage{english}synuclein aggregation was
found in the submucosal and myenteric neurons, there also existed
abnormal changes of dopaminergic neurons in these enteric plexuses both
in PD patients and animal models\textsuperscript{31-33}. However, it is
unknown whether peripheral DAT uptake capacity and/or its level are
changed. A potential relationship between peripheral and central DAT may
assess the disease progression and the effectiveness of
pharmacotherapies in PD\textsuperscript{34}. Therefore, it is necessary
to employ a macroscopic, whole-body approach to make an integrated
evaluation of the DA signaling and homeostasis both in the CNS and ENS.

From the SUV\textsubscript{mean} curve analysis of the cerebral core
areas (caudate, putamen, pallidum and substantial nigra), the tracer
activities of the four nuclei in healthy volunteers continuously
increased over time, suggesting the integrity of the dopaminergic
function of the nigrostriatal system in healthy brains. Moreover, the
strong positive correlations between the quantitative parameters among
these brain nuclei also yielded similar network connections. Instead,
the {[}\textsuperscript{11}C{]}CFT uptakes of the targeted nuclei in PD
patients tended to approach the ``plateau'' in advance, especially in
the putamen with the earlier occurrence of dopamine loss. This is in
accordance with the caudal-rostral gradient rule of striatal dopamine
depletion in the disease progress. In the pancreas and duodenum, the
peak {[}\textsuperscript{11}C{]}CFT activity of healthy participants was
higher than that of the patients, indicating a potential peripheral
dopaminergic neuron impairment in these two regions that may be related
to PD. In the stomach, due to the natural peristole influence of this
motional organ, resulted in a consistent fluctuation of the
SUV\textsubscript{mean} curve over time. Despite this, the final tracer
uptake remained higher in the healthy volunteers, suggesting a potential
binding reduction of the stomach in PD patients.

The quantitative method incorporated with kinetic modeling provides
direct information on the specific biologic process, representing the
tissue density of DAT and relative transporter rate constant of the
tracer , whereas the semi-quantitative method of SUVR requires shorter
scan acquisition and thus is often favored in clinical setting to
estimate such parameters\textsuperscript{21}. Our prior study found
certain correlations between the pancreas, duodenum, stomach and the
nigrostriatal nuclei in the healthy participants rather than PD patients
in the correlation analysis based on {[}\textsuperscript{11}C{]}CFT
total-body dynamic PET/CT imaging with SUV\textsubscript{mean}
measurements for the ``brain-GI'' targeted areas\textsuperscript{35}. In
this study, we further introduced voxel-based quantitative analysis
based on SRTM2 modeling together with the SUVR semi-quantitative
analysis to explore the interplay between the digestive and cerebral
regions. For the healthy population, there was a negative correlation of
the relative blood perfusion estimate R\textsubscript{1} between stomach
and the certain brain nuclei, whereas in terms of the DAT density
estimate DVR, the significant positive correlation between pancreas and
the specific brain nuclei were also demonstrated. In addition, both the
semi-quantitative estimates, SUVR\textsubscript{EP} and
SUVR\textsubscript{LP}, indicated similar correlation results from the
quantification approach in most of the region pairs. This indicated that
there may exist an original intrinsic correlation upon the ``brain-GI''
neuronal chain in healthy individuals rather than the PD patients.
Previous research on animal models of DAT specific SPECT tracers
(\textsuperscript{99m}Tc-TRODAT-1) suggested specific high uptakes in
the gastric mucosa \textsuperscript{36}. Herein the correlation
relationship between the stomach and core brain nuclei probably may
attribute to the early perfusion of the tracer from the gastric mucosal
vascular epithelium. Huang et al.\textsuperscript{37} found a high
pancreas uptake by using standard {[}\textsuperscript{11}C{]}CFT PET/CT
in healthy individuals. The correlation discrepancies between the HC and
PD groups in our findings indicated the native ``healthy'' interplay
pattern related to the digestive and cerebral dopaminergic interaction
might be diminished with the disease occurrence.

The simplified reference region model demonstrated a higher
computational efficiency and voxel-level stability compared to that of
nonlinear least squares method in describing the kinetic of
{[}\textsuperscript{11}C{]}CFT in rats, suggested by Gunn et
al.\textsuperscript{27}. Other advantages of the SRTM2 method also
include the avoidance of arterial cannulation and metabolite
measurements\textsuperscript{38}. As the compartmental modeling approach
with plasma input are usually considered the ``gold standard'' in
kinetic analysis, we additionally performed the VOI-based 1T2K kinetic
modeling to verify the estimates from the SRTM2\textsuperscript{21, 26,
27, 38}. The results of the highly correlated DVR estimated from SRTM2
using the occipital lobe as the reference and the V\textsubscript{T}
generated from the 1T2K models suggested the accurate tracer
quantification without arterial sampling. The significant correlation in
V\textsubscript{T} of pancreas and putamen in the HC group rather than
PD group was consistent to the results represented by DVR and
SUVR\textsubscript{LP}, providing more evidence towards the interplay
alteration due to the PD occurrence.

Using the correlation analysis between the brain nuclei and digestive
organs is a primary attempt to investigate the complex interplay between
the digestive and cerebral regions in PD based on noninvasive molecular
imaging. Prospective studies with more participants and more records of
GI symptoms will be needed to confirm the findings. Since long scanning
time in dynamic PET/CT acquisition may be challenging for the PD
patients, our results on the high consistency between the quantitative
and semi-quantitative estimates will support the semi-quantitative
measurements to be the potential surrogates for estimating tracer
kinetics with shorter scanning time, facilitating the participant
recruitment in the future prospective studies. Moreover, several
image-based systematic approaches in brain analysis have been applied to
the study of organ-level total-body metabolic network of
rodent\textsuperscript{39}, which may have potential prospect in the
interpretation of PD etiology and disease evaluation in the clinical
practice.

\textbf{Conclusion}

With the pilot application of the dynamic total-body
{[}\textsuperscript{11}C{]}CFT PET/CT imaging along with the
quantitative and semi-quantitative approaches, we observed the
distinctive uptake patterns in correlative interplays between the
digestive and cerebral regions of HC and PD, which may provide new
insights towards the understanding of disease.

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\textbf{Tables}

\textbf{TABLE 1.} Patient Characteristics.\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
& \textbf{Healthy volunteers as control (HC, n=6)} & \textbf{Parkinson's
disease patient (PD, n=5)}\tabularnewline
\midrule
\endhead
\textbf{Age, mean (SD), year} & 42 (15) & 58 (8)\tabularnewline
\textbf{Weight, mean (SD), kg} & 67.0 (12.1) & 78.6 (5.2)\tabularnewline
\textbf{Injected dose, mean (SD), MBq} & 418.8 (71.8) & 443.8
(78.2)\tabularnewline
\textbf{UPDRS III, mean (SD)} & N/A & 16 (9)\tabularnewline
\textbf{mH-Y, mean (SD)} & N/A & 2 (1)\tabularnewline
\textbf{NMSS, mean (SD)} & N/A & 47 (48)\tabularnewline
\bottomrule
\end{longtable}

Abbreviation: UPDRS III, Unified Parkinson's Disease Rating Scale III;
mH-Y, modified Hoehn and Yahr Scale; NMSS, Non-Motor Symptoms Scale.

\textbf{TABLE 2.} The SUV\textsubscript{mean} curve characteristics of
the target regions.\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\textbf{Uptake pattern} & \textbf{Organs} & \textbf{Separation time,
minute, minutes} & \textbf{Highest SUV\textsubscript{mean}, mean (SD),
g/mL} & \textbf{Highest SUV\textsubscript{mean}, mean (SD), g/mL} &
\textbf{Highest SUV\textsubscript{mean}, mean (SD), g/mL}\tabularnewline
\midrule
\endhead
& & & \textbf{HC} & \textbf{PD} & \emph{P} \textbf{value}\tabularnewline
\textbf{Gradually increasing} & Caudate & 6.5 & 7.2 (1.5) & 5.4 (1.7) &
0.130\tabularnewline
& Putamen & 2.0 & 8.6 (1.8) & 5.1 (2.0) &
0.0198\textsuperscript{*}\tabularnewline
& Pallidum & 6.5 & 4.5 (1.2) & 3.4 (1.0) & 0.188\tabularnewline
& SN & 13.5 & 3.9 (0.7) & 3.3 (0.8) & 0.324\tabularnewline
\textbf{Increasing with fluctuation} & Stomach & N/A & 11.8 (5.0) & 10.0
(2.4) & 0.492\tabularnewline
\textbf{Rapid increasing and slow decreasing} & Duodenum & N/A & 5.3
(1.7) & 3.8 (1.6) & 0.220\tabularnewline
& Pancreas & N/A & 9.6 (3.2) & 7.8 (2.1) & 0.345\tabularnewline
\bottomrule
\end{longtable}

* \emph{P} \textless{} 0.05.

Abbreviations: SD, standard deviation; HC, healthy control; PD,
Parkinson's disease patient; SN, substantia nigra.

\textbf{Figure Legends}

\textbf{FIGURE 1} (\textbf{A)}Total-body dynamic
{[}\textsuperscript{11}C{]}CFT PET/CT scanning protocol (75 min, 97
frames). (\textbf{B-D)} Selected view from
{[}\textsuperscript{11}C{]}CFT dynamic reconstructed images of a
53-year-old healthy volunteer (HC) and a 57-year-old Parkinson's disease
patient (PD). (\textbf{B)} Total-body maximum intensity projection
(MIP). (\textbf{C)} Transverse views of cerebral nuclei both in the
striatal and substantial nigra plane. The {[}\textsuperscript{11}C{]}CFT
uptake in HC developed earlier and increased over time, while the
nigrostriatal dopamine depletion was finally found in PD with a
caudal-rostral gradient tendency especially in the left side.
(\textbf{D)} Transverse views of the upper abdomen. Abbreviation: HC,
healthy controls; PD, Parkinson's disease patients.

\textbf{FIGURE 2} Comparison of averaged SUV\textsubscript{mean} curves
in HC and PD group at the (\textbf{A)} descending aorta,
(\textbf{B)}occipital lobe, selected (\textbf{C)} cerebral nuclei
regions and (\textbf{D)} GI organs. Data are represented by mean \selectlanguage{ngerman}±
standard error mean (SEM). Separation time between the averaged
SUV\textsubscript{mean}curves of HC and PD groups were marked for the
cerebral nuclei regions.

\textbf{FIGURE 3} \textbf{(A)} Schematic representation of the
simplified reference tissue model (SRTM2). \textbf{(B)} Total-body
maximum intensity projection (MIP) generated from the voxel-based SRTM2
modeling (left column), and representative striatal and substantial
nigra planes of the R\textsubscript{1} and DVR parametric images in HC
and PD representatives (right column). \textbf{(C)} Correlation between
the quantitative and semi-quantitative measurements. The
semi-quantitative estimation for early perfusion
(SUVR\textsubscript{EP}) (left) and dopamine transporter density
(SUVR\textsubscript{LP}) (right) were both significantly correlated to
the quantitative parameters (R\textsubscript{1} and DVR,
respectively).\textbf{(D)} Significant differences between the HC and PD
groups in SUVR\textsubscript{EP} of stomach (left) and both DVR (middle)
and SUVR\textsubscript{LP} (right) of putamen.

\textbf{FIGURE 4} Correlative assessment of the
\textbf{(A)}R\textsubscript{1} and \textbf{(B)} SUVR\textsubscript{EP}
of stomach and substantial nigra, and the \textbf{(C)} DVR and
\textbf{(D)}SUVR\textsubscript{LP} of pancreas and putamen in the HC and
PD groups. Abbreviation: SN, substantia nigra

\textbf{FIGURE 5} Correlation based on the quantitative measurements of
(\textbf{A)} R\textsubscript{1} and (\textbf{B)} DVR, and
semi-quantitative estimation of (\textbf{C)} SUVR\textsubscript{EP}
and\textbf{(D)} SUVR\textsubscript{LP} between the cerebral nuclei and
GI organs in healthy controls (HC) and Parkinson's disease patients
(PD). Upper triangle gives the graphical demonstration of the
correlation, where the orientations of the ellipses represent the signs
of the correlation coefficient (upper-left to lower-right, negative;
lower-left to upper-right, positive), and colors and width represent the
magnitude of the coefficients. The asterisks represent the significance
(*,\emph{P} \textless{}0.05; **, \emph{P} \textless{}0.01; ***,\emph{P}
\textless{}0.001). The lower triangle displays the correlation
coefficient \emph{r} . Abbreviation: SN, substantia nigra.



\textbf{Figures}

\textbf{FIGURE 1}\selectlanguage{english}
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