Marianthi-Vasiliki Papoutsaki1, Alex Weller1, Matthew R Orton1, and Nandita M de Souza1
1Radiotherapy and Imaging, The Institute of Cancer Research, Sutton, London, United Kingdom
Synopsis
Standardization
of diffusion-weighted (DW) protocols in multi-centre clinical trials is
challenging. Prior to protocol development, the effect of inter-vendor related sequence
variations on the apparent diffusion coefficient (ADC) reliability should be explored.
In this study, the reliability of ADC estimates of lung lesions using two
optimised DW protocols was assessed by mimicking vendor-related sequence
variations. Patients with lung lesions were scanned twice using two DW
protocols with different fat suppression techniques, diffusion gradient modes
and TEs. These key variations increased the coefficient of variation of the ADC
estimates of lung lesions, although absolute values did not differ
significantly.INTRODUCTION
In lung cancer,
diffusion weighted MRI (DW-MRI) is used to derive an apparent diffusion coefficient
(ADC) from malignant lesions, as ADC is recognised as a potential biomarker for
both lesion characterisation and response evaluation (1, 2). Standardization of
DW protocols for use in multicentre clinical trials is challenging due to
inter-vendor variations. Initially, it is informative to explore the effect of common
sequence variations related to inter-vendor deviations (e.g fat suppression
technique, diffusion gradient mode and echo time) on the ADC reliability
(reproducibility/ repeatability) individually at each centre before protocol
development in multi-centre clinical trials.
PURPOSE
To assess
the reliability of ADC estimates of lung lesions using two optimised DW protocols
together and separately by mimicking common vendor-related sequence variations.
METHODS
8
patients with malignant lung masses, having at least one lesion >2 cm, were
recruited for a single centre study with their informed consent. They were scanned twice with a time separation
ranging from 1 hour to 1 week. Anatomical and DW imaging were performed using a
Siemens Avanto 1.5T MR scanner with 2 anterior phased-array body coils. Axial
T
1-weighted and T
2-weighted images were acquired. Two DW protocols (DW-STIR and
DW-SPAIR) were employed with the following parameters: free-breathing, single
shot echo planar imaging, FoV=380x273mm, acquired matrix=128x92, pixel=3x3mm,
parallel imaging factor=2, PE direction=AP, TR=8500ms (DW-STIR) or 9000ms
(DW-SPAIR), TE=72ms (DW-STIR) or 83ms (DW-SPAIR), short time inversion recovery
(STIR) fat suppression (DW-STIR) or spectral adiabatic inversion recovery
(SPAIR) fat suppression (DW-SPAIR), three scan trace (DW-STIR) or three orthogonal
directions (DW-SPAIR), single spin echo, b=100, 500, 800 s/mm
2, 25
to 40 slices, slice thickness=5mm, NSA=1 repeated 4 times. A mono-exponential
decay model for all b-values from all the acquisitions was applied for the
production of the calculated ADC maps and computed DW images using in
house-built software using the geometric mean image of the three acquired
directions of both DW protocols assuming isotropic diffusion. Regions of
interest (ROIs) were drawn on the computed DW-MRI (b=800 s/mm
2) (3)
encompassing the larger area of the lesion on three central contiguous slices.
The calculated ADC values of all pixels within these slices were combined in
order to give a volume of interest (VOI) per examination and the mean ADC value
of the whole volume was recorded. The ADC comparisons between the DW protocols
and the repeatability of each protocol were assessed by performing a t-test and
by using coefficient of variation (CoV) and Bland Altman plots.
RESULTS
T-tests
showed no difference comparing the ADC estimates of the DW-STIR and DW-SPAIR
protocols (p=0.93) and by comparing the two baselines of each protocol
separately (p=0.52 for DW-STIR and p=0.58 for DW-SPAIR). This result was in
agreement with the CoV (Table 1) and the Bland Altman plot (Figure 1a) of the
ADC estimates comparing the two DW protocols exhibiting only one outlier. By
removing this outlier, the CoV was 3.5%. The Bland Altman plots (Figure 1b, 1c)
presented a good repeatability of the ADC estimates of each protocol exhibiting
similar CoVs.
DISCUSSION
In
multi-centre clinical trials, there are vendor specific variations of the DW sequence
parameters in measurement protocols across the centres. These technical factors
are most commonly related to the fat suppression technique, the diffusion
gradient mode and the gradient performance. We explored these key variations
comparing STIR, which is less sensitive to B
0 inhomogeneity, but
results in loss of signal and a T
1-weighted contrast contribution, to SPAIR,
which is sensitive to B
0 inhomogeneity and provides higher SNR due
to its spectrally selective fat suppression character. Different diffusion
gradient modes were also used for further optimisation of the fat suppression
techniques resulting in different echo times (TE). These differences impact on
ADC estimates with the CoVs being increased between the 2 protocols (CoV=7.7%) compared
to each protocol individually (CoV
DW-STIR=3.7% and CoV
DW-SPAIR=4,6%).
However, no significant influence was observed on the absolute ADC estimates using
different fat suppression techniques, diffusion gradient modes and TEs in this
study.
CONCLUSION
In
a single centre study, several of the most common protocol variations in DW-MRI
were employed. The selection of the fat suppression technique, the diffusion
gradient mode and the different TE increased the CoV of the ADC estimates of
lung lesions using together the 2 DW protocols to using each one separately,
although absolute values did not differ significantly.
Acknowledgements
We
acknowledge CRUK and EPSRC support to the Cancer Imaging
Centre at ICR and RMH in association with MRC & Dept of Health
C1060/A10334, C1060/A16464 and NHS funding to the NIHR Biomedicine Research
Centre and the Clinical Research Facility in Imaging. M.-V. P. was funded by Innovative Medicines Initiative Joint Undertaking
under grant agreement number 115151.References
1)
Charles-Edwards EM, deSouza N. Cancer Imaging 2006;6:135-143. 2) Bains
L J et al. Cancer Imaging 2012;
12: 395. 3) Blackledge M et al.
Radiology 2011;261: 573-581