MRI variables and peripheral inflammatory response biomarkers predict severity and prognosis in patients with acute cervical traumatic spinal cord injury

doi:10.21203/rs.3.rs-3799514/v1

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Research Article

MRI variables and peripheral inflammatory response biomarkers predict severity and prognosis in patients with acute cervical traumatic spinal cord injury

https://doi.org/10.21203/rs.3.rs-3799514/v1

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Journal Publication

published 12 Nov, 2024

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Objective: Traumatic spinal cord injury (TSCI) stands as one of the most profoundly damaging and debilitating conditions. This study aims to explore the potential of magnetic resonance imaging (MRI) variables and peripheral inflammatory indicators as promising biomarkers. It aims to understand their significance in evaluating the severity and predicting the prognosis of TSCI. Furthermore, the study aims to ascertain whether combining these indicators could enhance the accuracy of injury assessment and predictive prognostic ability.

Methods: A multicentre retrospective cohort study was conducted to assess the severity and prognostic value of MRI variables and peripheral inflammatory response biomarkers in patients with acute cervicalTSCI. The study involved 374 patients with acute cervicalTSCI drawn from the First Affiliated Hospital of Nanchang University and the Second Affiliated Hospital of Nanchang University. The severity and prognosis of patients with acute cervical TSCI were assessed using the American Spinal Injury Association Impairment Scale (AIS). The correlation between MRI variables, peripheral inflammatory response biomarkers, admission severity, and the 1-year follow-up prognosis was analysed.

Results: After the initial assessment using the AIS grading system, 169 (49.2%) patients fell into the non-severe category for cervical TSCI (AIS A–B), while 205 (50.8%) patients were classified as severe cases (AIS C–E). The MRI variables (intramedullary lesion length [IMLL], Brain and Spinal Injury Centre [BASIC], maximum spinal cord compression [MSCC], and maximum canal compromise [MCC]) and inflammatory response biomarkers (white blood cells [WBCs], neutrophils, and C-reactive protein [CRP]) exhibited a consistent decrease correlating with the severity grades noted upon admission. Among the 374 patients assessed, 147 (39.3%) experienced a poor prognosis, as indicated by the AIS grade during the 1-year follow-up. MRI variables and peripheral inflammatory response biomarkers declined in correspondence with the follow-up AIS grades. Sex (p <0.001), IMLL (p <0.001), MSCC (p<0.001), MCC (p <0.001), BASIC (p <0.001), WBC (p<0.001), neutrophils (p <0.001), and CRP (p <0.001) were statistically significant in predicting poor outcomes. Through multiple logistic regression analysis, BASIC score and CRP emerged as independent predictors of poor prognosis. Notably, the model combining the BASIC score and CRP yielded a larger area under the curve compared to models using only the BASIC score or CRP individually.

Conclusions: The BASIC score and CRP are crucial biomarkers for evaluating the severity of cervical TSCI and predicting prognosis. Their combination proved to be a more robust determinant of injury severity and a better predictor of neurological recovery.

BASIC score

Biomarker

C-reactive protein

MRI variables

Traumatic spinal cord injury

Traumatic spinal cord injury (TSCI) stands as an immensely devastating and debilitating condition, with nearly half of all patients experiencing complete functional loss, and one-third of the affected individuals enduring lifelong quadriplegia(1). The aftermath of TSCI, marked by severe functional limitations and diminished quality of life, imposes significant burdens on patients, families, and society due to reduced productivity and increased medical expenses(2, 3). Presently, reliance on clinical assessments remains the cornerstone for evaluating TSCI treatments. However, these assessments often lack precision, particularly in severe impairment cases(4, 5). The American Spinal Injury Association Impairment Scale (AIS) serves as a critical measure, evaluating the severity encompassing sensory and motor functions, and holds significant prognostic values in TSCI cases(6, 7). Nevertheless, the use of AIS grade for severity assessment and prediction is uncertain because it can rapidly change during the early stages of TSCI, owing to spinal shock(8). Hence, there is a pressing need for the rapid development of objective TSCI biomarkers. These markers, when used independently or in conjunction, are crucial in distinguishing injury severity and enhancing the accuracy of prognostic predictions.

Lately, there has been growing attention towards quantifiable variables within magnetic resonance imaging (MRI) and biomarkers of inflammatory response concerning injury severity and prognosis. Acute TSCI triggers a systemic immune response in circulating white blood cells (WBCs). Research indicates that peripheral inflammatory response biomarkers, including WBCs and neutrophils, correlate with injury severity and can predict prognosis in patients with TSCI(9). Early circulating neutrophil counts might predict the long-term recovery potential after TSCI(10). Moreover, the widespread use of MRI has led to numerous studies exploring the potential of MRI parameters as markers for acute TSCI(11–22). Currently, MRI investigations focus on two primary aspects. First, they examine abnormal T2 signals within the spinal cord, such as abnormal T2 signal height (intramedullary lesion length [IMLL]) and Brain and Spinal Cord Injury Centre (BASIC) scores. Second, they delve into secondary MRI biomarkers such as maximum canal damage (MCC) and maximum spinal cord compression (MSCC). These MRI variables play an essential role in assessing TSCI severity and predicting neurological prognosis.

Given the promise exhibited by MRI variables and peripheral inflammatory indicators as potential biomarkers, this study aimed to ascertain their respective efficacy in classifying injury severity and predicting neurological prognosis. Additionally, it sought to explore the possibility of using them in tandem to enhance the accuracy of injury assessment and predictive prognostic ability. Specifically focused on patients with acute cervical TSCI who underwent peripheral blood sampling and MRI scanning, our findings revealed that MRI biomarkers outperformed peripheral blood inflammatory biomarkers in assessing and predicting prognosis. Moreover, the combined analysis of the BASIC score and C-reactive protein (CRP) enhanced the sensitivity and specificity of prognostic prediction. Notably, the model combining the BASIC score with CRP (area under the curve [AUC] = 0.973; 95% confidence interval [CI], 0.959–0.987) demonstrated superior prognostic value compared to models using the BASIC score or CRP individually.

Study population

A retrospective review encompassing 374 patients with acute cervical TSCI who were admitted to the First Affiliated Hospital of Nanchang University and the Second Affiliated Hospital of Nanchang University between December 2015 and September 2022 was conducted. The inclusion criteria were as follows: 1) individuals aged ≥ 16 years; 2) a Glasgow Coma Scale score of 15; 3) peripheral blood tests conducted within 12 h and MRI scans within 48 h after injury. The exclusion criteria were as follows: 1) severe concomitant traumatic brain injury or significant trauma to the chest or pelvis or multiple severe injuries; 2) pre-existing major neurological deficits or conditions; 3) haematological disorders; 4) incomplete or missing data. The Ethics Review Committees of the First Affiliated Hospital of Nanchang University and the Second Affiliated Hospital of Nanchang University approved the study. All methodologies adhered to relevant guidelines and regulations.

Severe cervical TSCI was defined as AIS grades A–B and non-severe cervical TSCI as AIS grades C–E(9). The clinical data primarily encompassed age, sex, injury mechanism, admission and 1-year follow-up AIS grades, laboratory examinations, and MRI variables. Our assessment of the 1-year prognosis of patients with cervical TSCI primarily involved outpatient follow-ups or post-discharge telephonic counselling. The prognosis of cervical TSCI patients who completed follow-up was categorised into two groups: poor (AIS A–C) and good (AIS D–E)(23).

MRI analysis

The study analysed four MRI variables as potential predictors of injury severity and prognosis: (1) IMLL, (2) MSCC, (3) MCC, and (4) BASIC score. IMLL represented the length of the median sagittal T2 signal change after acute TSCI (Fig. 1A)(12, 21). Additionally, Talbott et al. introduced the BASIC score, a new axial plane scoring system categorising the grades from 0 to 4 based on the extent of T2 signal change within the spinal cord (grade 1: T2 signal change limited to the central grey matter; grade 2: T2 signal change beyond the grey matter, involving the white matter but not involving the entire spinal cord; grade 3: T2 signal change involving the entire transverse extent of the spinal cord; grade 4: grade 3 + T2 low-signal foci consistent with haemorrhage) (Fig. 1B)(11). Calculation methods from previous studies were applied to assess MCC and MSCC by dividing the anteroposterior diameter of the spinal canal (sagittal T1 for MCC) and the anteroposterior diameter of the spinal cord (sagittal T2 for MSCC) by the mean of the vertebral canals or upper and lower spinal cords on the midsagittal image. Specifically, the following formulae were used: MCC (%) = 1-[Di/(Da + Db)/2]×100% (Fig. 1C); MSCC (%) = 1-[di/(da + db)/2]×100% (12, 21) (Fig. 1D).

Statistical analysis

All statistical analyses were performed using SPSS software. Categorical variables are represented using percentages, while continuous variables are represented as the mean ± standard deviation (SD) or median (interquartile range). The study aimed to investigate the relationship of these factors with injury severity and prognosis among patients with TSCI. Spearman rank correlation was used to analyse bivariate correlations. Univariate analysis of factors was performed to identify statistically significant variables, and risk factors with p-values < 0.1 were incorporated into the multivariate logistic regression model. The independent effects of the BASIC score and CRP on prognosis were assessed through logistic regression analysis, followed by calculating and comparing the AUC. The combined effect of the BASIC score and CRP was further assessed using the receiver operating characteristic (ROC) curve analysis. Statistical significance was set at p < 0.05.

This study encompassed 374 patients with acute cervical TSCI, comprising 313 males and 61 females. Table 1 exhibits their characteristics, MRI variables, and peripheral inflammatory response biomarkers. The patients' ages ranged from 23 to 84 (mean, 54.67) years. Falls accounted for the most common injury mechanism (45.7%), followed by motor vehicle accidents (32.1%), struck-by-object incidents (7.2%), and other unspecified mechanisms (15%). Upon admission, the AIS grades indicated frequencies of 124 (33.2%) for grade A, 45 (12%) for grade B, 50 (13.4%) for grade C, and 155 (41.4%) for grade D injuries. After 1-year follow-up, the distribution of AIS grades was as follows: 87 (23.2%) for grade A, 19 (5.1%) for grade B, 41 (11%) for grade C, 185 (49.5%) for grade D, and 42 (11.2%) for grade E. Table 2 outlines MRI variables and inflammatory response biomarkers for all 374 patients. The mean IMLL was 26.46 mm (SD ± 22.25 mm), the mean MCC was 40.42% (SD ± 18.72%), and the mean MSCC was 22.80% (SD ± 17.43%). Regarding peripheral inflammatory response biomarkers, our focus primarily centred on WBCs, neutrophils, and CRP, with mean values of 10.48 (SD ± 3.38), 9.14 (SD ± 3.31), and 14.02 (SD ± 12.67), respectively.

Table 1

Patient Characteristics
Age (years)(mean (SD))	54.67 ± 12.28
Sex (%)	Male = 313 (83.7); Female = 61 (16.3)
Trauma Mechanism (%)	Fall = 171 (45.7); MVA = 120 (32.1); Struck-by-object = 27 (7.2); Others = 56(15)
AIS at admission (%)	A = 124 (33.2); B = 45 (12); C = 50 (13.4); D = 155 (41.4)
1-year AIS (%)	A = 87 (23.3); B = 19 (5.1); C = 41 (11); D = 185 (49.5); E = 42 (11.2)
BASIC score (%)	0 = 82 (21.9); 1 = 44 (11.8); 2 = 74 (19.8); 3 = 41 (11); 4 = 133 (35.6)
IMLL(mm)(mean (SD))	26.46 ± 22.25
MCC (%)(mean (SD))	40.42 ± 18.72
MSCC (%)(mean (SD))	22.80 ± 17.43
WBC (×10⁹/L)(mean (SD))	10.48 ± 3.38
Neutrophils (×10⁹/L)(mean (SD))	9.14 ± 3.31
CRP(mg/L)(mean (SD))	14.02 ± 12.67

AIS, American spinal injury association Impairment Scale; BASIC, Brain and spinal cord injury center; IMLL, Intramedullary lesion length; ROC, Receiver operating characteristic; MCC, Maximum canal compromise; MSCC, Maximum spinal cord compression; SD, Standard deviation; WBCs, White blood cells

Table 2

The differences in clinical features and laboratory data between severe and non-severe cervical TSCI
Characteristics	Non-severe cervical TSCI	Severe cervical TSCI	P value
n	205	169
Sex, n (%)			< 0.001
Age, median (IQR)	55 (48, 63)	55 (47, 64)	0.837
Males	158 (42.2%)	155 (41.4%)
Females	47 (12.6%)	14 (3.7%)
Mechanism of injury, n (%)			0.275
Fall	87 (23.3%)	84 (22.5%)
Motor vehicle accident	68 (18.2%)	52 (13.9%)
Struck-by-object	19 (5.1%)	8 (2.1%)
Others	31 (8.3%)	25 (6.7%)
IMLL, median (IQR)	8.95 (0, 21.15)	41.03 (31.47, 51.92)	< 0.001
MSCC(%), median (IQR)	18.94 (8.19, 29.825)	25.64 (14.36, 38.36)	< 0.001
MCC(%), median (IQR)	29.41 (19.89, 42.25)	51.843 (41.07, 60.68)	< 0.001
BASIC			< 0.001
0	81 (21.66%)	1 (0.28%)
1	44 (11.76%)	0 (0.00%)
2	58 (15.51%)	16 (4.28%)
3	11 (2.94%)	30 (8.02%)
4	11 (2.94%)	122 (32.62%)
WBC(×10⁹ /L), median (IQR)	8.88 (7.55, 11.14)	10.85 (9.39, 13.31)	< 0.001
Neutrophil (×10⁹/L), median (IQR)	7.46 (6.1, 9.77)	9.83 (8.21, 12.11)	< 0.001
CRP (mg/L), median (IQR)	7.91 (4.68, 11.6)	16.21 (10.68, 22.68)	< 0.001

There were 169 (49.2%) patients classified as non-severe cervical TSCI (AIS A-B) and 205 (50.8%) patients classified as severe cervical TSCI (AIS C-E) (Table 2). Significant differences emerged between the severe and non-severe cervical TSCI groups concerning sex (p < 0.001), IMLL (p < 0.001), MSCC (p < 0.001), MCC (p < 0.001), BASIC (p < 0.001), WBCs (p < 0.001), neutrophils (p < 0.001), and CRP (p < 0.001) (Table 2). Further exploration into the relationship of MRI variables and inflammatory response biomarkers with admission AIS grades revealed a graded reduction in MRI variables (IMLL, BASIC, MSCC, and MCC) aligned with decreasing admission AIS grades. Similarly, inflammatory response biomarkers (WBCs, neutrophils, and CRP) displayed a graded decrease corresponding to admission AIS grades (Table 3). Notably, the imaging variable BASIC score exhibited a significantly stronger correlation with admission AIS grade compared to other imaging biomarkers. Additionally, the inflammatory response biomarker CRP demonstrated a significantly stronger correlation with admission AIS grade compared to WBCs and neutrophils (Table 3).

Table 3

Spearman rank correlation and regression analysis results
AIS grade at admission	Spearman correlation
	R	P
IMLL	−0.717	< 0.001
MSCC	−0.225	< 0.001
MCC	−0.530	< 0.001
BASIC score	−0.832	< 0.001
WBCs	−0.216	< 0.001
Neutrophils	−0.287	< 0.001
CRP	−0.422	< 0.001
1-year AIS grade	Spearman correlation
	R	P
IMLL	−0.731	< 0.001
MSCC	−0.234	< 0.001
MCC	−0.529	< 0.001
BASIC score	−0.779	< 0.001
WBCs	−0.202	< 0.001
Neutrophils	−0.265	< 0.001
CRP	−0.472	< 0.001
AIS, American spinal injury association Impairment Scale; Brain and spinal cord injury center; CRP, C-reactive protein; IMLL, Intramedullary lesion length; MCC, Maximum canal compromise; MSCC, Maximum spinal cord compression; WBCs, White blood cells

Based on the 1-year follow-up AIS grade, 147 (39.3%) patients faced a poor prognosis (AIS A–C), while 227 (60.7%) patients experienced a good prognosis (AIS D–E) (Table 4). Examining the correlation between MRI variables, peripheral inflammatory response biomarkers, and the follow-up AIS grade revealed a declining trend based on the severity of the AIS grade during follow-up (Table 3). Further exploration to identify variables influencing cervical TSCI prognosis indicated significant differences between the good and poor outcome groups in terms of sex (p < 0.001), IMLL (p < 0.001), MSCC (p < 0.001), MCC (p < 0.001), BASIC (p < 0.001), WBCs (p < 0.001), neutrophils (p < 0.001), and CRP (p < 0.001) through univariate analysis (Table 4). In the subsequent multivariate logistic regression analysis, the MRI variable BASIC score (p < 0.001) and the inflammatory response biomarker CRP (p < 0.001) emerged as significant prognostic factors influencing the 1-year prognosis of patients with cervical TSCI. Conversely, other imaging variables (MSCC, MCC, and IMLL) and inflammatory biomarkers (WBCs and neutrophils) did not significantly affect prognosis (Table 5). Additionally, the cervical TSCI severity upon admission remained an independent predictor of 1-year prognosis. Previous analysis also highlighted the effectiveness of the BASIC score and CRP as prognostic factors. To assess their predictive capability, ROC analysis was conducted, demonstrating good predictive values for CRP (AUC: 0.833 [95% CI, 0.792–0.874] and BASIC score (AUC: 0.958 [95% CI, 0.939–0.976]) in predicting cervical TSCI prognosis. Furthermore, combining the BASIC score and CRP in a model resulted in a larger AUC compared to models using only the BASIC score or CRP (Fig. 2), indicating enhanced predictive power when used in combination.

Table 4

Results of statistical analysis of the risk factors for poor prognosis in cervical TSCI
Characteristics	Poor outcome	Good outcome	P value
n	147	227
Sex, n (%)			0.004
Males	133 (35.6%)	180 (48.1%)
Females	14 (3.7%)	47 (12.6%)
Age, median (IQR)	55 (47, 64)	55 (48, 62.5)	0.673
Mechanism of injury, n (%)			0.203
Fall	76 (20.3%)	95 (25.4%)
Motor vehicle accident	43 (11.5%)	77 (20.6%)
Struck-by-object	7 (1.9%)	20 (5.3%)
Others	21 (5.6%)	35 (9.4%)
Severity of TSCI, n (%)			< 0.001
Severe cervical TSCI	144 (38.5%)	25 (6.7%)
Non-severe cervical TSCI	3 (0.8%)	202 (54%)
IMLL, median (IQR)	43.18 (34.37, 54.06)	10.69 (0, 22.55)	< 0.001
MSCC(%), median (IQR)	25.641 (14.14, 39.22)	20.308 (8.91, 30.86)	< 0.001
MCC(%), median (IQR)	52.666 (41.43, 61.70)	31.401 (20.42, 45.67)	< 0.001
BASIC			< 0.001
0	0 (0.00%)	82 (21.93%)
1	0 (0.00%)	44 (11.76%)
2	3 (0.80%)	71 (18.98%)
3	23 (6.15%)	18 (4.81%)
4	121 (32.35%)	12 (3.20%)
WBCs(×10⁹ /L), median (IQR)	10.83 (9.42, 13.09)	9.06 (7.58, 11.67)	< 0.001
Neutrophils (×10⁹/L), median (IQR)	9.83 (8.53, 11.57)	7.65 (6.16, 10.31)	< 0.001
CRP (mg/L), median (IQR)	17.4 (11.52, 25.23)	8.14 (5.34, 12.23)	< 0.001
BASIC, Brain and spinal cord injury center; ; CRP, C-reactive protein; IMLL, Intramedullary lesion length; MCC, Maximum canal compromise; MSCC, Maximum spinal cord compression; WBCs, White blood cells

Table 5

Multivariate logistic regression analysis for risk factors of poor outcome in cervical TSCI.
Characteristics	OR (95% CI)	P value
Sex, n (%)	1.812 (0.193–17.047)	0.603
Severity of cervical TSCI	182.86 (22.76–1469.01)	< 0.001
IMLL	0.976 (0.919–1.037)	0.44
MSCC	0.987 (0.934–1.044)	0.656
MCC	1.009 (0.946–1.077)	0.783
BASIC		0.001
WBCs	0.06 (0.963–6.600)	0.06
Neutrophils	0.066 (0.142–89.933)	0.066
CRP	0.878 (0.780–0.988)	0.031
AIS, American spinal injury association Impairment Scale; BASIC, Brain and spinal cord injury center; IMLL, Intramedullary lesion length; ROC, Receiver operating characteristic; MCC, Maximum canal compromise; MSCC, Maximum spinal cord compression; WBCs, White blood cells

This research represents the initial integration of MRI variables alongside peripheral inflammatory response biomarkers to evaluate the correlation between injury severity and 1-year prognosis among patients with cervical TSCI. Our study established a significant association between admission MRI variables, peripheral inflammatory response biomarkers, and injury severity in individuals with cervical TSCI. Furthermore, a robust correlation was highlighted between MRI variables, peripheral inflammatory response biomarkers, and poor prognosis. When conducting multiple logistic regression analysis encompassing all peripheral inflammatory response biomarkers and MRI variables to predict 1-year prognosis in patients with cervical TSCI, only CRP and the BASIC score emerged as statistically significant and were retained within the model. Ultimately, our findings underscored the enhanced predictive accuracy achieved by combining the BASIC score with CRP to predict prognostic outcomes more precisely

The AIS grade has long served as a prominent prognostic predictor of TSCI. Our study reaffirms the significance of TSCI injury severity at admission (AIS grade) as an independent and significant predictor in determining patient outcomes. However, employing the AIS grade in clinical practice poses certain limitations. First, uncertainty arises in patients with spinal shock, wherein spontaneous recovery within hours post-injury is acknowledged(24). Second, patients with TSCI, particularly those under sedation or with polytrauma, can impede accurate physician judgment(25). Hence, there is an imperative not only for further diagnostic and predictive modelling concerning acute TSCI but also for frameworks to identify valuable biomarkers enhancing assessment and prediction accuracy. Currently, various alternative injury biomarkers have made significant strides in clinical advancements, including admission blood tests, cerebrospinal fluid sampling, motor-evoked potential monitoring, and MRI(15, 16, 26–30). The routine nature of blood tests and imaging upon admission, their typically rapid turnaround, and minimal disruption to prompt intensive care and surgical interventions render peripheral inflammatory response biomarkers and MRI biomarkers particularly appealing

In recent years, post-traumatic inflammation has garnered escalating interest, with numerous studies indicating its pivotal role in the pathogenesis and progression of TSCI. Acute TSCI has been linked to a systemic immune response that involves circulating WBCs. Zhou et al. observed a significant increase in WBCs and neutrophils among patients with severe TSCI(9). These findings suggest that early changes in WBC counts among patients with TSCI might shed light on the potential relationship between concomitant injury factors and neurological prognosis. Moreover, their study highlighted a positive correlation between acute neutrophilia in patients with TSCI and TSCI severity scores, yet a negative correlation with neurological prognosis(31). Similarly, our univariate analysis revealed markedly higher WBCs and neutrophils among patients with severe TSCI. The early stages of TSCI disrupt the blood-spinal cord barrier (BSCB), leading to altered BSCB permeability and the subsequent release of inflammatory factors (such as interleukin [IL]-6, IL-1β, tumour necrosis factor-α, etc.) into the peripheral bloodstream via the BSCB(32, 33). These inflammatory factors prompt an increased expression of serum CRP(34). In this study, serum CRP emerged as a peripheral inflammatory response biomarker and the sole prognostic factor for patients with cervical TSCI.

In addition to peripheral inflammatory response biomarkers, there has been an increasing interest in certain variables in routine MRI studies, such as IMLL, MSCC, MCC, and the BASIC score. However, these MRI variables have yet to establish themselves as sufficiently accurate biomarkers for assessing injury severity and long-term neurological prognosis in TSCI. In previous studies, the predictive role of MSCC and MCC in neurological recovery remains inconclusive(21, 35–37). Our findings revealed that although MSCC and MCC displayed strong associations with admission injury severity and follow-up AIS grade, they did not emerge as potential predictors of TSCI prognosis in multivariate logistic regression analysis. Haefeli et al.(21) and Mabray et al.(38), using the non-linear principal component analysis method (NL-PCA), assessed various MRI metrics' validity in predicting early neurological impairment and similarly found MCC and MSCC to be ineffective predictors. Our findings align with this, suggesting that MSCC and MCC might not be pivotal MRI variables for predicting TSCI prognosis due to two primary reasons. First, MSCC and MCC primarily correlate with admission injury severity, and their impact was negligible when initial injury severity was considered the strongest predictor of neurological recovery. Second, MSCC and MCC illustrate structural changes in post-traumatic compression on MRI, potentially underestimating the actual spinal cord compression during the traumatic event, leading to irreversible spinal cord damage.

A strong correlation was observed between abnormal signalling variables within the spinal cord (BASIC score and IMLL) and admission AIS grade and follow-up AIS grade. Previous research highlights that quantitative T2 signalling measurements (IMLL or BASIC) are significantly superior predictors of neurological prognosis 1 year after cervical TSCI when compared to MCC and MSCC. Although both BASIC score and IMLL focus on T2 signalling alterations within the spinal cord, they differ significantly in many ways. The BASIC score, an axial imaging scale, primarily reflects the degree of white matter preservation, with the most severe degree involving haemorrhage combined with oedema. In contrast, IMLL serves as a longitudinal imaging scale but lacks detailed insights into the degree of white matter preservation Talbott et al.(11) introduced the BASIC score based on axial MRI findings in 2015, demonstrating its strong association with neurological symptoms upon hospitalisation and discharge. Concurrently, a series of clinical studies have underscored the superior efficacy of the BASIC score over other MRI variables in assessing severity and predicting TSCI prognosis(12, 19, 21). Our study similarly identified the BASIC score as the sole significant predictor among MRI variables in the multivariate logistic regression analysis.

TThe MRI variable BASIC score and the peripheral inflammation response biomarker CRP exhibit reliable predictive capacities for prognosis. Our analysis also revealed a larger AUC in the model combining the BASIC score with CRP, indicating its superior predictability. Nevertheless, several factors can influence the validity of AUC outcomes. Factors such as, the timing(39) and types(40) of decompression surgery might be affected by spinal cord signalling abnormalities and the degree of spinal cord compression, potentially affecting prognosis.

Limitations

This study has several limitations. First, its retrospective nature could have introduced selection bias and hindered control over confounding variables. Second, during the acute injury phase, MRI might not fully reveal the nature and extent of the lesion, including potential daily increases in IMLL. Third, the employed clinical assessment (AIS grade) was relatively crude and subjective, potentially constraining the correlation's robustness, as more detailed measures were not utilised. Additionally, our study focused solely on admission MRI variables and peripheral inflammatory response biomarkers as indicators, overlooking the dynamic changes in these indicators over time. Thus, prospective studies are imperative to further validate our findings.

Our study demonstrated that the MRI variable BASIC score and the inflammation-related biomarker CRP are important indicators for assessing the severity of cervical TSCI and predicting prognosis. We compared or combined for the first time these promising MRI variables with peripheral blood inflammatory biomarkers. In this case, the BASIC score combined with CRP was a stronger classifier of injury severity and predictor of neurologic recovery. We recommend combining the joint effect of BASIC score and the serum CRP to assess the severity and predict prognostic in patients with cervical TSCI. Prospective and larger studies are needed to define these admission parameters more precisely to further validate our findings in the future.

AIS

American spinal injury association Impairment Scale

AUC

Area under the curve

BASIC

Brain and spinal cord injury center

CRP

C-reactive protein

GCS

Glasgow Coma Scale

Interleukin

IMLL

Intramedullary lesion length

ROC

Receiver operating characteristic

MCC

Maximum canal compromise

MRI

Magnetic resonance imaging

MSCC

Maximum spinal cord compression

NL-PCA

Nonlinear principal component analysis

Standard deviation

TNF

Tumor necrosis factor

TSCI

Traumatic spinal cord injury

WBCs

White blood cells

Acknowledgements

Not applicable.

Authors’ contributions

ZHD and WZ: study design, data collection and manuscript writing; DLW: data collection and analyzation; LL: data collection and analyzation; CYW: data collection and analyzation; CLW: study design, data analyzation and manuscript final revision. The author(s) read and approved the final manuscript.

Funding

This work was funded by The National Natural Science Foundation of China (grant no. 82260525)

Data Availability

The datasets used and/or analysed during the current study available from the

corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by Ethics Review Committee of the First Affiliated Hospital of Nanchang University and the second Affiliated Hospital of Nanchang University. Informed consent was obtained from all individual participants.

Consent for publication

Not Applicable.

Competing interests

The authors report no conflicts of interest.

Author details

¹Department of Neurosurgery, the 1^staffiliated hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Street, Nanchang 330006, Jiangxi, China.

² Department of Neurosurgery, the 2^staffiliated hospital, Jiangxi Medical College, Nanchang University, China.

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No competing interests reported.

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MRI variables and peripheral inflammatory response biomarkers predict severity and prognosis in patients with acute cervical traumatic spinal cord injury

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