A Pilot Study Shows Altered Orientation Dispersion Index in Patients with Sickle Cell Disease
Poster No:
1288
Submission Type:
Abstract Submission
Authors:
Elizabeth Meinert-Spyker1, Tales Santini2, Joel Dzidzorvi Kwame Disu1, Lara Abdelmohsen1, Sossena Wood1
Institutions:
1Carnegie Mellon University, Pittsburgh, PA, 2University of Pittsburgh, Pittsburgh, PA
First Author:
Co-Author(s):
Introduction:
Sickle cell disease (SCD) is a genetic condition that results in the formation of an abnormal hemoglobin, HbS, leading to chronic hemolysis, anemia, abnormal perfusion, and decreased oxygen delivery to various tissues. As neurological function is reliant on adequate blood and oxygen delivery, it is common for neurological complications such as white matter tissue damage to arise in patients with SCD. In this pilot study, we use diffusion MRI (dMRI) to compare neurite orientation dispersion and density imaging (NODDI) and standard diffusion tensor imaging metrics to quantify the severity of microstructure integrity between patients with SCD and healthy controls. We hypothesized that fractional anisotropy (FA) and neurite density index (NDI) would be significantly decreased in patients with SCD compared to controls while radial diffusivity (RD), mean diffusivity (MD), axial diffusivity (AD), and FISO (isotropic fraction or free water fraction) metrics would be increased.
Methods:
4 healthy controls (aged 29±9) and 5 patients with SCD (aged 31±6) were included. We recruited patients with various SCD genotypes (3 HbSS, 1 HbSC, and 1 HbSβ+ thalassemia). DTI data was acquired with a 3T MRI scanner (Prisma, Siemens), and a 64 channel head coil. The sequence parameters were: 144 directions with b-values of 5-3000 ms/µm2, 7 acquisitions without diffusion gradients (with and without reversed phase encoding direction), 1.5 mm isotropic resolution, multi-band factor of 4, TE/TR=90.6/3230 ms, total acquisition time of 8 minutes. T1-weighted MPRAGE scans were acquired with 1 mm isotropic resolution, acquisition time of 5.02 mins, and TE/TR=1.99/2300 ms. Preprocessing of the data was conducted with the softwares MRtrix (Tournier et al., 2019) and FSL (Smith et al., 2004). Preprocessing included denoising, removing Gibb's ringing artifacts, and motion and distortion correction. Tract-based spatial statistics (TBSS) was used to register diffusion images and compare diffusion metrics between healthy controls and patients with SCD (Smith et al., 2006). Voxelwise statistics was then conducted correcting for age and sex. Average metrics for each participant were calculated over the JHU ICBM-DTI-81 white-matter labels atlas (Morriset al., 2008) using MATLAB.
Results:
Voxelwise comparisons of the diffusion and NODDI metrics only showed significant differences (p<0.05) in the orientation dispersion index (ODI) (Figure 1), with patients having greater values than controls. Trends towards significance (p<0.1) were also visible in RD (patients>controls) and FISO (patients>controls). Boxplots of diffusion and NODDI metrics can be visualized in Figure 2. On average, FA was lower in patients compared to controls, while all other metrics were greater in patients than controls.
Conclusions:
Results indicate significant differences between ODI in patients with sickle cell disease and controls. Patients had significantly higher ODI values, which indicates a high degree of variability in the orientation of neurites. High ODI has been implicated with diseases such as ischemia and may indicate decreased myelination and neuroinflammation (Kamiya et al., 2020). Clinically, neuroinflammation may be linked to the cognitive deficits (Hardy et al., 2021) and pain experienced by patients with SCD (Lei et al., 2021). The non-significant trends in RD and FISO were as hypothesized (patients>controls) and further illuminate the white matter tissue damage in patients with SCD. Due to our limited sample size, we expect to find more significant findings as our sample size increases, further highlighting the differences between the control brain and the brain of patients with SCD. This study establishes the feasibility of analyzing differences in NODDI and diffusion metrics between patients with SCD and healthy controls. This study also showcases the importance of studies that analyze the brains of patients with SCD.
Genetics:
Genetics Other 2
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 1
Novel Imaging Acquisition Methods:
Diffusion MRI
Keywords:
ADULTS
Degenerative Disease
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Sickle Cell Disease
1|2Indicates the priority used for review
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Provide references using APA citation style.
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