Huimin Zhang1, Qiyong Ai1, Queenie Chan2, Ann D. King1, and Weitian Chen1
1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, Hong Kong, 2Philips Healthcare, Hong Kong, Hong Kong
Synopsis
T1ρ
relaxation, known as the spin‐lattice
relaxation time in the rotating frame, is sensitive to
molecular interactions including dipolar interactions, chemical exchange, and
diffusion. T1ρ
is often measured by mono-exponential relaxation models. Bi-exponential T1ρ
relaxation have been previously observed in muscle, cartilage, menisci and
brain. We report our observation of bi-exponential T1ρ relaxation in parotid
glands.
Introduction
$$$T_{1\rho}$$$ relaxation, known as the spin‐lattice relaxation time
in the rotating frame, is sensitive to
molecular interactions including dipolar interactions, chemical exchange, and
diffusion. In the head and neck, $$$T_{1\rho}$$$ relaxation has been used to
evaluate the early irradiated change in the parotid gland 1 and differentiate
the inflammatory and normal tissue 2. In these studies, $$$T_{1\rho}$$$ is measured by
using a mono-exponential relaxation model. However, the compartmentation of
tissues may lead to bi- or multi-exponential $$$T_{1\rho}$$$ relaxation. Preliminary
studies showed that $$$T_{1\rho}$$$ relaxation in muscle 3, cartilage 4, menisci 5 and brain 6 follows a bi-exponential decay. In this work, we report our observation of bi-exponential $$$T_{1\rho}$$$ relaxation
in parotid glands on human subjects.Method
Nine healthy volunteers (age $$$25.5\pm 3.5$$$, $$$3$$$ females and $$$6$$$ males) were scanned on a
Philips Achieva 3.0T scanner (Philips Healthcare, Best, the
Netherlands) under the approval
of the institutional review board. The
body RF coil was used as the transmitter and a 16-channel Philips neurovascular
phased-array coil which covers the entire parotid glands was used as the
receiver. Imaging parameters include:
resolution 1.2 mm × 1.2 mm, slice thickness 5 mm with total 9 slices, TE/TR
4.9 ms/2500 ms, 12 TSLs for [0 5 8 12 15 25 35 45 60 70 80 90] ms, spin-lock
frequency 400 Hz.
The data sets at 12 TSLs were fit to a mono-exponential
model, $$$S_{mono}=S_{0}\cdot e^{-TSL/T_{1\rho, mono}}$$$ and a
bi-exponential model based on Levenberg-Marquardt algorithm, $$$S_{bi}=S_{01}\cdot e^{-TSL/T_{1\rho, long}}+S_{02}\cdot e^{-TSL/T_{1\rho, short}}$$$,
where $$$S_{0}$$$ and $$$S_{01}+S_{02}$$$ are scaling constants; $$$T_{1\rho, mono}$$$ is the $$$T_{1\rho}$$$ value fitted by the mono-exponential model; $$$T_{1\rho, long}$$$ and $$$T_{1\rho, short}$$$ represent the long and short component of the $$$T_{1\rho}$$$ in the bi-exponential model, respectively. The fractions of the pools with long
and short $$$T_{1\rho}$$$ are defined as $$$f_{long} = S_{01}/(S_{01}+S_{02})$$$ and $$$f_{long} = S_{02}/(S_{01}+S_{02})$$$, respectively.
Six ROIs for each subjects were contoured manually on the left parotid
gland. The $$$T_{1\rho, mono}$$$, $$$T_{1\rho, long}$$$ and $$$T_{1\rho, short}$$$ and $$$f_{long}$$$ of six ROIs were calculated.
The residual sum of squares (RSS) of mono-exponential
fitting and bi-exponential fitting were calculated to compare the goodness of
fit. To quantitatively evaluate the significance of their difference, F test
was performed. The F-ratio is defined
as $$F=\frac{(RSS_{1}-RSS_{2})/(NV_{2}-NV_{1})}{RSS_{2}/(N-NV_{2}))},$$ where $$$RSS_{1}$$$ and $$$RSS_{2}$$$ correspond to the mono-exponential and bi-exponential models, respectively; N represents the data points acquired (N=12); and $$$NV_{1}$$$ and $$$NV_{2}$$$ are the
numbers of variables in each model. Results
In parotid glands, the long and short $$$T_{1\rho}$$$ were of ~59-70 msec
with a fraction of ~0.73-0.91 and ~10-25 msec with a fraction of ~0.09-0.27 respectively, while mono $$$T_{1\rho}$$$ ~50-61 msec. The F ratios of 9 subjects range
from 10 to 174 with a P value of 0.01. There is a significantly improvement of
fitting by using bi-exponential model compared to mono-exponential model. Figure 1 displays typical raw-images at different TSLs for $$$T_{1\rho}$$$ quantification. Figure 2a illustrates 6 ROIs drawn on the left parotid gland. Figure 2b plots the $$$T_{1\rho}$$$ fitting curves of mono- and bi-exponential models from the 6th ROI. Figure 3 lists the measured parameters from two models and the corresponding F ratios. Figure 4 shows adjusted R-squared maps of mono- and bi-exponential fitting models. Figure 5 shows $$$T_{1\rho, mono}$$$,$$$T_{1\rho, short}$$$, $$$T_{1\rho, long}$$$ maps and the fraction map of long $$$T_{1\rho}$$$ component.Discussion and Conclusion
The
fitting results show that bi-exponential fitting curve matches to raw data
better than the mono-exponential fitting curve. Note
that there are regions in the bi-exponential fitting maps (e.g. long and short
$$$T_{1\rho}$$$ maps, fraction map) with extreme values. This may due to blood vessels
and gland ducts in the parotid area. When drawing ROIs, we carefully avoid
these regions by selecting areas which are homogeneous and with values satisfying certain criteria ( $$$T_{1\rho, short}$$$<$$$T_{1\rho, mono}$$$, $$$T_{1\rho, long}$$$>$$$T_{1\rho, mono}$$$, $$$T_{1\rho, short}$$$>0, $$$T_{1\rho, long}$$$<100 ms). Bi-exponential fitting appears to be more susceptible to the
presence of noise compared to mono-exponential fitting. Higher SNR of images is required to achieve reliable
fitting results. It is worthy of further investigation how much SNR is needed
to achieve reliable bi-exponential fitting in our application.
Bi-exponential $$$T_{1\rho}$$$ relaxation observed in
parotid glands may be caused by combination of free water and constrained
water. The long and short $$$T_{1\rho}$$$ values and their fraction in the tissue may
have high sensitivity to the structural changes of parotid gland and have potential
clinical use. Further study is needed to explain the reasons causing bi-exponential
relaxation at a cellular level and demonstrate its possible clinical
applications.Acknowledgements
This
study is supported by a grant from the Research Grants Council of the Hong Kong
SAR (Project SEG CUHK02).References
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