Paul J.C. Hughes1, Marta Tibiletti2, Matthew J. Heaton2, Ho-Fung Chan1, Guilhem J. Collier1, Matthew Austin1, Laurie J. Smith1,3, Jim Lithgow1, Josephine H. Naish2,4, Jim M. Wild1,5, and Geoff J.M. Parker2,6
1POLARIS, Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, United Kingdom, 2Bioxydyn, Manchester, United Kingdom, 3Sheffield Children's Hospital NHS Foundation Trust, Sheffield, United Kingdom, 4Division of Cardiovascular Sciences, University of Manchester, Manchester, United Kingdom, 5Insigneo Institute for in silico Medicine, The University of Sheffield, Sheffield, United Kingdom, 6Centre for Medical Image Computing, University College London, London, United Kingdom
Synopsis
Hyperpolarised xenon-129 MRI has shown
utility in longitudinal assessment of lung structure and function, and has been
shown to be a repeatable method. Oxygen enhanced MRI is a cheaper method of
imaging different aspects of lung function. This work aimed to assess a
single-centre repeatability of multiple metrics from both imaging methods in
volunteers, and assess any correlations between xenon-129 and oxygen enhanced
metrics of lung function.
Introduction
Hyperpolarized
xenon-129 (129Xe) is able to assess both structure1 and
function2-4 of the lungs. Oxygen enhanced MRI (OE-MRI) is a low-cost
and easier to implement proton MRI acquisition method that may provide
alternative functional metrics5,6 to 129Xe. We studied
the repeatability of 129Xe and OE-MRI parameters in a population of
adult healthy volunteers, and evaluated the degree of correlation between the
resulting metrics.Methods
Nine
healthy volunteers (26 - 75 yo, 3 females) were scanned twice using a 1.5 T GE
Signa HDxt, in separate sessions 4 to 7 days apart. The full protocol comprises
129Xe MR imaging followed by OE-MRI imaging (Figure 1).
129Xe MRI: All
129Xe imaging
was carried out using a flexible quadrature transmit/receive vest coil (Clinical MR Solutions,
Brookfield, Wisconsin, USA). Participants underwent three hyperpolarized
129Xe
7
scans:
- Ventilation-weighted imaging2 (500mL 129Xe and 500mL N2). Prior to this acquisition a structural 1H image
was acquired. This 1H image is then co-registered to the 129Xe image to calculate percentage lung ventilated volume
(%VV), median coefficient of variation of 129Xe signal intensity (Median CV) and
ventilation heterogeneity index (VHI)3,8
- 3D diffusion-weighted imaging1 (550mL 129Xe and 450mL N2). Providing apparent diffusion coefficient (ADC) and diffusive
length scale (LmD)1
- 129Xe Spectroscopy4
(500mL 129Xe and 500mL N2). Providing the red blood cell to tissue plasma (RBC:TP)
ratio
129Xe
metrics are reported as whole lung means.
OE
MRI: All OE MRI was acquired using an 8-element
chest receiver coil. A
free-breathing protocol based on an inversion-prepared centric ordered single
shot 3D-turbo field echo sequence was used. A baseline proton T1 map
was calculated from a series of 6 acquisitions with variable TI (40, 100, 300,
1100, 2000 and 5000 ms). This was followed by a dynamic OE acquisition lasting
15 min (TI=1100 ms) with a temporal resolution of 10 s, during which gas was
delivered at 10 L/min via a disposable non-rebreathing mask and switched at
minute 2 from medical air to 100% O2, and back to air at minute 10.
Images were registered to correct for
respiratory motion using a non-linear registration algorithm9. Lungs
were manually segmented from identified target images using in-house VoxelFlow software.
The following parameters were extracted:
- Baseline proton
T1 values (IR-T1)5
- O2
wash-in time (τup)5
- Change in
partial pressure of O2 (ΔPO2)5
- OE-MRI
Ventilated volume fraction (OE-VVF): a pixel within the lung is considered
ventilated when the Akaike information criterion (AIC) favours an exponential
fit to the dynamic time series OE signal change over a constant function.
Whole lung median values of IR-T1,
τup, ΔPO2 and OE-VVF are reported.
Statistical
analysis: All statistical analysis was carried out
using Graphpad Prism version 7 for Mac (GraphPad Software, La Jolla California
USA). Bland-Altman analysis was
carried out on each of the metrics described above to assess repeatability,
along with the calculation of the repeatability metric10.
Additionally, paired t-tests, or Wilcoxon matched pairs tests were carried out
(depending on the result of the Shapiro-Wilk normality test) to assess
differences between each visit. Finally, Spearman/Pearson correlations were
carried out to assess the relationship between OE and
129Xe metrics (note for this analysis
the average measure over both visits was used).
Results
All
volunteers tolerated both 129Xe and OE scanning with no adverse
events. An example of the obtained parameter maps (129Xe left, OE
right) in one 29 year old healthy volunteer is given in Figure 2. Table 1 shows
the results of the Bland-Altman analysis (bias±limits of agreement),
repeatability metric and paired t-tests/Wilcoxon matched-pairs tests for all
considered metrics. Only τup showed
a significant change between visits. Significant correlations were observed
between ΔPO2 and median CV (r=-0.91, p=0.0006), and ΔPO2
and VHI (r=-0.73, p=0.03) (Figure 3).Discussion
All
129Xe metrics had bias close to zero, as assessed by Bland-Altman
analysis, with ADC, LmD and RBC:TP being the most repeatable.
Furthermore, all 129Xe metrics had narrow limits of agreement suggesting
these metrics to be suitable for longitudinal assessment of patients. OE-VVF
was the most repeatable OE-MRI metric, with the remaining three having
reasonable repeatability, strongly influenced by one subject (HV03) who showed
large variability between visits. The existence of a correlation between ΔPO2
and 129Xe ventilation heterogeneity measures in healthy
volunteers requires further investigation. Conclusions
129Xe and OE MRI
metrics are reproducible and it is feasible to acquire images using both
methods in volunteers.Acknowledgements
The
research leading to these results received funding from the Innovative
Medicines Initiatives 2 Joint Undertaking under grant agreement No 116106. This
Joint Undertaking receives support from the European Union’s Horizon 2020
research and innovation programme and EFPIA. This work was also supported by
the NIHR (RP-R3-12-027),
MRC (MR/M008894/1)
and GlaxoSmithKline (PJCH:BIDS3000032592).References
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