NASS 2022: Baseline quantitative MRI can predict probability of deterioration and intervention in DCM patients

Muhammad Ali Akbar

Baseline quantitative magnetic resonance imaging (qMRI) is able to accurately predict the likelihood of deterioration and surgical intervention in degenerative cervical myelopathy (DCM) patients, new research suggests. 

Presented at the North American Spine Society’s (NASS) annual meeting (12–15 October, Chicago, USA) by Muhammad Ali Akbar (Toronto Western Hospital, Toronto, Canada), where the study won a Resident and Fellow Research Award, the findings also indicated that qMRI canpotentially play an important role in screening patient populations for surgical candidates or those who are at high risk of deterioration.

The prospective cohort study aimed to investigate whether or not qMRI metrics can predict which patients with DCM are likely to deteriorate clinically and require surgery within one year of presentation.

According to the researchers, “the definitive management of DCM is surgical decompression in moderate to severe cases. The evidence for early surgical intervention in mild DCM patients is less definitive and therefore, current guidelines are less clear on the relative merits of operative versus non-operative intervention in this group of patients”.

“According to the best available evidence, anywhere from 20–62% of patients with mild DCM will deteriorate within six years; however, there is no reliable way to predict such a deterioration. However, advances in microstructural MRI may afford a novel approach to address this knowledge gap since these imaging techniques allow one to assess pathological changes such as demyelination, scarring and axonal/neuronal loss,” they add.

In total, 58 DCM patients were included in the study and the key outcome measures were qMRI metrics and Modified Japanese Orthopaedic Association (mJOA) score.

Data were stratified into patients who required surgery within one year of follow-up and those who remained stable and continued in the non-operative group. All patients underwent a multiparametric qMRI scan protocol including diffusion tensor imaging (DTI), magnetisation transfer (MT) and T2* weighted imaging at the initial visit.

Quantitative metrics including cross sectional area (CSA), fractional anisotropy (FA), magnetisation transfer ratio (MTR), and T2* white matter to grey matter ratio (T2*WI WM/GM) were measured in the cervical spine at the rostral, caudal and most compressed levels (MCL).

Statistical analysis multivariable logistic regression was performed using baseline FA, MTR and T2*WI WM/GM in the rostral spine and CSA at the MCL as predictor variables. Surgical decompression at one year was used as the dependent variable. Model discrimination and reliability were measured using c-index and Brier’s score respectively. Validation and calibration were performed using the bootstrap method with 100 repetitions.

A total of 33 mild (mJOA 15–17), 15 moderate (mJOA 12–14) and 10 severe (mJOA 0–11) DCM patients were included in the study. Twenty-nine patients had undergone surgical decompression at one-year follow-up, whereas the other 29 remained in non-operative management.

Baseline qMRI was found to be able to identify patients requiring surgery, with an accuracy of 81.6% (area under curve or c-index). The researchers note that the model showed good reliability with a Brier score of 0.18 and Somers’ Dxy rank correlation of 0.63. Calibration using the bootstrap method showed overall good predictive ability with slight over-prediction at higher observed probability of surgery.

Speaking to Spinal News International, Akbar said: “I am honoured to be included in the list of award winners and given the opportunity to present my work at the 2022 NASS conference. Our research aims to improve imaging biomarkers in DCM as well as spinal cord injury (SCI). In our work we describe a 30-minute multiparametric qMRI protocol including DTI, magnetisation transfer and T2* weighted imaging. We show that in patients with DCM, an adverse qMRI profile at baseline is predictive of surgery.

“This suggests that patients with similar mJOA scores may have varying degrees of neurological injury such as demyelination and atrophy which is reflected in the qMRI metrics of the spinal cord. This research highlights the clinical feasibility of advanced qMRI techniques as well as their utility.

“Although further work is required, these qMRI metrics could potentially aid in reclassifying DCM patients by degree of tissue injury rather than symptomology and improve management of this disease, especially in the mild DCM population. In translation, the same qMRI metrics could also be explored for outcome prediction in SCI and show utility as outcome measures in new clinical trials”


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