Synopsis
Associations between quantitative MRI
biomarkers in the lumbar spine and pain in chronic low back pain
patients (CLBP) were studied. These biomarkers are currently being explored as
quantitative metrics of disc degeneration. Since most CLBP cases are associated
with pathologic disc degeneration processes, these biomarkers might provide
clues about the actual source of pain. For analysis, the discs from each subject were pooled from the least to the most
degenerated one using a semi-quantitative metric. Results showed that these biomarkers
might aid in identifying the source of pain in CLBP patients.Introduction and Purpose
Chronic low back pain (CLBP) is a major health
problem in working age adults. CLBP is usually associated with the degeneration
of intervertebral disc, although the disc itself might not be the source of the
pain. Despite the prevalence of this problem, the mechanisms of pathological
degeneration or how it is distinguished from the normal aging processes is
still unclear. One of the reasons is the lack of quantitative and objective
diagnostic tools to investigate disc degeneration1 and mechanisms that lead to CLBP. Currently accepted methods generally
use qualitative assessment of diagnostic images, which has relatively low
sensitivity with limited clinical importance2,3. However, recent studies utilizing quantitative imaging techniques
such as DCE-MRI, T1ρ, diffusion weighted imaging
(DWI) and T2 weighted (T2W) MRI showed promising results,
potentially offering quantitative biomarkers of pathologic disc degeneration4,5.
The goal of this study was to explore associations between
such imaging biomarkers and pain. The findings might aid in identifying the potential
source of CLBP.
Methods
76 adult participants were scanned using a 3T GE
MR750 system. The participants were interviewed and their medical charts were
reviewed to ensure that other clinical conditions, such as malignancies or bone
disease, were not the source of pain. The study was approved by the IRB and
written consents were obtained from participants. The subjects with CLBP were administered the Oswestry disability index6 (ODI) questionnaire and
their scores were recorded. Control
subjects without CLBP were assigned an ODI score of zero. Demographic characteristics of the participants were
given in Table 1. During the imaging session, T2W (NnoCLBP=46/NCLBP=30),
DWI (NnoCLBP=45/NCLBP=30), T1ρ (NnoCLBP=44/NCLBP=29) and DCE-MRI
(NnoCLBP=39/NCLBP=25) data were acquired4,5,7. Images with noticeable artifacts were excluded. Eight
biomarkers were derived from the images: disc height index (DHI)5, normalized T2W intensity (nT2W)5, apparent diffusion coefficient (ADC)5, T1ρ7, and DCE-MRI enhancements in four regions of interest (ROI)4. These ROIs were drawn over the cranial and caudal subchondral bone
(SB) and cartilaginous endplate (CEP)4 regions, which are critical for disc health. All biomarkers were checked
using Hoaglin et. al.’s outlier labeling rule8.
Note that the DHI metric is normalized across
subjects, but it also varies with lumbar level within each subject. To minimize
that variation, a new biomarker, nDHI, was defined. nDHI is DHI normalized with
respect to disc level (L1L2:1.000, L2L3:1.156, L3L4:1.316, L4L5:1.485,
L5S1:1.337). These ratios were calculated from 19 healthy participants (Age:29±9y, Female:7, H:67±4inch, W:154±27lbs, BMI:24±4kg/m2) who had no disc degeneration
(Pfirrmann grade9≤II).
For
analysis, the lumbar discs of each subject were sorted into five pools
according to the product of nDHI*nT2W. This multiplication was used
as a semi-quantitative parameter to sort the discs according to their disc
degeneration level, analogous to Pfirrmann classification9. However,
unlike Pfirrmann that uses a universal classification, our pooling was done for each subject individually. The
first pool represents relatively the least degenerated disc in each subject,
and the last pool represents the most degenerated disc. This sorting scheme was
used because we do not know which disc might actually be causing the pain,
although current understanding is that the disc with the most degeneration is
the most likely culprit. Statistical analyses were performed using IBM SPSS v21.
Differences in MRI biomarkers between controls and CLBP patients in each pool
were analyzed using a t-test. A statistical significance (α) level of 0.05
was used. The workflow is shown in Fig.1.
Results
By using Hoaglin
et.al.’s outlier labeling rule, four discs from three participants were labeled as outliers and excluded from
analysis. The results of the
t-tests were listed in Table 2.
Discussion
and Conclusion
The ODI scores from our cohort (44.8±17.6) were similar
to retrospective ODI scores reported for chronic back pain (43.3±10to21)6 from 25 different studies. This shows that our cohort was a good
representation of a typical CLBP patient population.
It is interesting that the biomarkers from even the
“least degenerated disc” in CLBP patients showed significant associations with
pain. This might indicate that most lumbar discs of a CLBP patient undergo similar
pathological changes. However, one metric stood out among others. The Caudal
CEP Enhancement was
significantly associated with CLBP only for the most degenerated disc pool, but
not others. This might help identify the most likely source of pain, but further
studies are needed to validate this hypothesis. As a general trend, ADC and
T1ρ demonstrated a tendency of increasing t-scores with increasing degeneration
pool and DCE-MRI related biomarkers had a tendency of larger negative t-scores.
This pooling approach might also provide a useful means to label potentially
problematic discs and endplates.
Acknowledgements
This study is supported in part by funds from AHW28
FP00002161 and AOSpine Clinical Priority program. We would like to thank Ali
Ersoz, Daniel Olson, Adam Pfaller, Judeen Richeen and study participants for
their help.References
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