Yeefan Lee1,2, Kuan-Hung Cho3, Chih-Hsing Tang2, Chia-Wen Chiang3, Shih-Yen Lin4, Chen-Hsiang Kuan5, Chien-Yuan Lin6, Hsiao-Ling Lee6, and Li-Wei Kuo3
1Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan, 2Department of Medical imaging, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan, 3Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli County, Taiwan, 4Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan, 5Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan, 6GE Healthcare, Taipei, Taiwan
Synopsis
Lymphedema is defined as accumulation of fluid and fibroadipose tissues due to disruption of lymphatic flow. Our results demonstrate a significant difference of diffusion measures between lymphedema and normal groups. DKI and DTI derivatives have similar tendency when comparing lymphedema patients with healthy subjects. The diffusion properties may aid the diagnosis of lymphedema and have the potential for evaluating the severity in postoperative follow-up.
Introduction
Lymphedema is a pathologic condition of the
lymphatic system in which protein-containing fluid accumulates in the
interstitial tissue leading to tissue inflammation, fibrosis, and adipose
hypertrophy1. The International Society of Lymphology Lymphedema Staging
Guidelines characterizes the severity of lymphedema by two criteria to diagnose
and classify lymphedema: the "softness" or "firmness" of
the limb (reflecting fibrotic soft tissue changes) and the outcome after
elevation2. However, the clinical staging system cannot quantify the severity of
lymphedema and delineate the edematous and fibrous tissue distribution within
the limbs. Several imaging techniques like lymphoscintigraphy3,4, magnetic
resonance lymphangiography (MRL)5, or indocyanine green lymphangiography (ICGL)6 help further assess lymphedema. However, they can only provide qualitative or
semi-quantitative results, which highly limits the feasibility of evaluating
the preoperative planning and postoperative follow-up. Therefore, how to
effectively assess the improvement of lymphatic drainage is of great clinical
interest. Diffusion MRI has been widely used in many
clinical studies, including breast and body7,8,9,10. It enables to provide quantitative metrics (e.g.,
mean diffusivity relating to edema and inflammation, and mean kurtosis relating
to heterogeneity, cellularity, and inflammation) for clinical diagnosis and
disease characterization. This study aims to investigate the role of diffusion imaging for the
quantitative assessment of lymphedema.Methods
This study was approved by the local IRB of the
National Taiwan University Hospital Hsin-Chu Branch. All volunteers provided
informed consent before the commencement of the study. Three normal subjects
and one patient with lower extremity lymphedema and two patients with upper
extremity lymphedema were enrolled in this study. All patients have clinical
stage II to III lymphedema. MRI experiments were performed on a 1.5 T system
(SIGNA ARTIST, GE Healthcare, USA) using a 16-channel large flex coil. The diffusion
weighted images were acquired using Multishot Diffusion‐Weighted
Echo Planar Imaging sequence with Multiplexed Sensitivity Encoding (MUSE)
technique11. The b values were set to 0, 200, 400, 800 and
1200 s/mm2 and 15 non-collinear gradient directions were
encoded. The image processing procedures include motion correction12 for minimizing the effect from subject movement during
MRI scan, followed by ANOLM denoising13. Diffusion tensor
imaging (DTI) and Diffusion kurtosis
imaging (DKI) were reconstructed based on the
algorithms proposed by Basser, P.J., et al.14 and Tabesh, A., et al.15 respectively. Lymphedema is typically confined to the
epifascial space of the skin and subcutaneous tissue sparing muscle16,17.
Region-of-interests were selected by segmenting the extremity into inner and
outer parts (figure 1a and 1e), where inner part mainly contains muscle tissue,
and the outer part contains skin and subcutaneous tissue. DTI- and DKI-derived
measures, including mean diffusivity (MD), fractional anisotropy (FA) and mean
kurtosis (MK), were used for comparison. Student’s t-test was performed. Statistical
significance was defined at p<0.05. All
values are presented as mean±SD.Results
Figure
1 showed the representative results of DKI-derived MD (figure 1b and 1f), FA
(figure 1c and 1g) and MK (figure 1d and 1h) maps from a normal subject and an
upper extremity lymphedema patient. Figure 2 shows the comparison between
normal subjects and lymphedema patients on DTI- and DKI-derived MD. It can be
observed that at outer region both DTI- and DKI-derived MD values from
lymphedema patients are significantly higher than that from normal subjects. At
inner region, no significant difference between two groups is observed. Figure
3 shows the results of DTI- and DKI-derived FA values. At outer region the FA
values from lymphedema patients are significantly lower than that from normal
subjects. At inner region there is no significant difference between normal
subjects and lymphedema patients. Figure 4 shows the comparison of MK between
normal subjects and lymphedema patients. The MK value from lymphedema patients is
obviously lower than that from normal subjects at outer region but is similar to
that from normal subjects at inner region. Discussion & conclusion
Our
preliminary results demonstrate that higher MD values, lower FA and MK values
present at the outer part of the extremities of the lymphedema patients than
healthy controls. These results demonstrate the feasibility for the diagnosis
of extremity lymphedema using diffusion measures. The inner part of the
lymphedema extremities shows similar diffusion properties to healthy controls.
This result indicates that lymphedema does not occur in muscle tissue,
consistent with the prior clinical observations16,17. Our results also show that
DTI-derived MD and FA values are slightly different from DKI derivatives owing
to different modeling of diffusion signals. However, we can still conduct the
same conclusion since the tendency is similar when comparing lymphedema patients
with healthy subjects. In conclusion, derivatives from DTI and DKI can be
applied to differentiate lymphedema patients from healthy controls. The
diffusion properties may be helpful in the diagnosis of lymphedema and have the
potential for evaluating the severity in postoperative follow-up. Acknowledgements
I would like to thank all those who are related to this project.References
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