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Patient demographics and MRI-based measurements predict redundant nerve roots in lumbar spinal stenosis: a retrospective database cohort comparison

BMC Musculoskeletal Disorders volume 19, Article number: 452 (2018) Cite this article

Abstract

Background

Up to 40% of patients diagnosed with lumbar spinal stenosis (LSS) show evidence of redundant nerve roots (RNR) of the cauda equina on their magnetic resonance images (MRI). The etiology of RNR is still unclear. Preoperative evidence of RNR is associated with a worse postsurgical outcome. Consequently, potential predictors of RNR could have a prognostic value. The aim was to test whether patient demographics and MRI-based measurements can predict RNR in LSS patients.

Methods

In a retrospective database-based cohort study the preoperative data of 300 patients, 150 with (RNR+) and 150 without (RNR-) evidence of RNR on their MRI were analyzed. Three independent researchers performed the MRI reads. Potential predictors were age, gender, body height (BH), length of lumbar spine (LLS), segmental length of lumbar spine (SLLS), lumbar spine alignment deviation (LSAD), relative LLS (rLLS), relative SLLS (rSLLS), number of stenotic levels (LSS-level), and grade of LSS severity (LLS-grade, increasing from A to D). Binomial logistic regression models were performed.

Results

RNR+ patients were 2.6 years older (p = 0.01). Weak RNR+ predictors were a two-years age increase (OR 1.06; p = 0.02), 3 cm BH decrease (OR 1.09; p = 0.01) and a 5 mm SLLS decrease (OR 1.34; p < 0.001). Strong RNR+ predictors were a 1% rLLS decrease (OR 2.17; p < 0.001), LSS-level ≥ 2 (OR 2.59; p = 0.001), LLS-grade C (OR 5.86; p = 0.02) and LLS-grade D (OR 18.4; p < 0.001). The mean rSLLS of RNR+ patients was 0.6% shorter (p < 0.001; 95% C.I. 0.4 to 0.8) indicating a disproportionate shorter lumbar spine.

Conclusions

We identified LSS severity grade and LSS levels as the strongest predictors of RNR. In addition to previous studies, we conclude that a shortened lumbar spine by degeneration is involved in the development of RNR.

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Background

Lumbar spinal stenosis (LSS) is the most common reason for lumbar spine surgery in patients older than 65 years [1]. Around 40% of all LSS patients scheduled for decompression surgery show evidence of RNRs of the cauda equina on their preoperative MRI [2,3,4].

RNRs were described as thickened, buckling or coiled nerve roots that typically assume serpentine or loop-shape in T2-weighted MR images [5]. When the standard T2-weighted sequence is equivocal, adding a single slice MRI-myelography sequence may help to identify RNRs. RNRs were mostly observed above the stenotic level, but can also be found below, or both above and below the stenotic level [6, 7].

Reports indicated that LSS patients with preoperative evidence of RNRs (RNR+) have a significantly longer mean duration of neurological symptoms and experience less improvement in their ability to walk after surgery in comparison to patients without RNRs (RNR-) [2, 6, 8, 9].

The etiology and pathogenesis of RNRs are still unclear. RNRs seem to be a negative prognostic factor in LSS patients. Therefore, the investigation of factors that may predict the presence of RNRs is of clinical importance. The present study aimed to investigate whether patients’ demographics and MRI-based measurements can predict RNRs in patients scheduled for LLS decompression surgery.

Methods

Study design and sample

This is a retrospective database-based cohort comparison study. Reporting of the present study follows the STROBE Statement guidelines for reporting observational studies [10]. The inclusion criteria were symptomatic lumbar spinal canal stenosis requiring surgical decompression without fixation and availability of preoperative MRI that were performed in a scanner with at least 1.5 Tesla, including sagittal T1- and T2-weighted images and axial T2-weighted images in the picture archive and communication system (PACS) of the institution. Exclusion criteria were previous history of lumbar spine surgery, lumbar deformity as scoliosis or vertebral slip requiring fixation and congenital, traumatic, infectious or neoplastic diseases of the lumbar spine.

Sample size was calculated with the use of G*Power version 3.1.9.2 (Psychology Department, Duesseldorf University, Germany) [11]. For sample size calculation the variable LSS-level was chosen and the following assumptions were used: 68% of RNR+ patients show one stenotic level and 32% show two or more stenotic levels; oppositely 84% of RNR- patients show one stenotic level and 16% show two or more stenotic levels. Based on these assumptions an odds ratio of 2.47 was calculated. Thereby, if α = 0.05 and 1-ß error probability = 0.90, there is a 90% chance of correctly rejecting the null hypothesis that a particular value of the main predictor variable (LSS-Level) is not associated with the outcome variable, with a total sample size of 300 patients (150 per group).

The preoperative data of 300 consecutive LSS patients who underwent single- or multi-level microsurgical bilateral decompression via a unilateral approach (also known as “cross over” or “over the top” technique) without any fixation were evaluated. The surgeries were performed by six different surgeons with a level of experience ranging from 4 to 35 years. The ipsilateral facet was resected one third and the contralateral was left alone whereas the thickened yellow ligament was completely removed. The surgeries were performed between December 2012 and August 2016 at the same institution. During this time window 2273 patients underwent decompression surgery for LSS. Thereof 2113 underwent decompression surgery without fixation. Out of this second group patients with and without RNR on their preoperative MRIs were selected from August 2016 backwards, until both groups each contained 150 patients.

The Ethics Committee of the Federal State of Hamburg deliberated upon the research proposal of the present study (File PV5817). According to the ethics committee retrospective database-based studies do not require an approval, whenever the data was acquired, saved and treated anonymously. This applies to the present study.

The database used for this research is not publicly available, it is property of the Schoen Clinic Group, whose access is regulated by the rules of procedure of its in-house Science Office.

The following patient-related and MRI-based factors were used as potential predictors: age, gender, body height (BH), length of the lumbar spine (LLS), segmental length of the lumbar spine (SLLS), relative LLS (rLLS), relative SLLS (rSLLS), the amount of lumbar spine alignment deviation (LSAD), as given by the difference between SLLS and LLS, the number of stenotic levels involved (LSS-level) and the grade of severity of the stenosis (LSS-grade) on a progressive scale from A to D [12].

Firstly, the 300 patients were assigned to either the RNR+ or the RNR- group by a senior radiologist, a senior orthopedic surgeon and a senior neurosurgeon independently. Their experience levels were 15, 10 and 35 years respectively.

The definition of RNR used to assign the patients into the groups was the following: RNR were defined as serpentines [13] when in sagittal T2-WI a sinusoidal deflection (complete crest-trough wave) occurred within the height of a vertebral body without any horizontalization of the involved roots (Fig. 1b). RNR were defined as loops when in sagittal T2-WI at least in two different areas dots or horizontalized roots (Fig. 2a) were combined with tortuous roots in the axial T2-WI (Fig. 2c). Mixed serpentine and loop findings were scored as loops, as the latter deformation seems to be the more relevant one [14].

Fig. 1
figure1

Sagittal T2-WI of spinal canal stenosis (a) without and (b) with evidence of RNR a) Sagittal T2-WI of spinal canal stenosis L4/L5 (axial: upper corner left) with no evidence of RNR since the spatial distribution of the cauda nerve roots is not influenced by the stenotic level (white arrow). b) Sagittal T2-WI of spinal canal stenosis L3/L4 (axial: upper corner left) with evidence of serpentine-shaped RNR deflection (white arrows)

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Fig. 2
figure2

Sagittal T2-WI of spinal canal stenosis with evidence of loop-shaped RNR a) Sagittal T2-WI of spinal canal stenosis L2/L3. At this level caudal straightened nerve roots switch to loop like RNR (white arrows); b) The coronal Myelo-MRI shows the horizontalized loops (white arrows); c) Axial T2-WI shows segments of the loops (white arrows); d) Axial T2-WI of a normal lumbar spinal canal: the cauda roots appear as dots

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The agreement between the three raters concerning patients’ group affiliation was almost perfect (Fleiss k = .92; p < 0.001). The transition between a normal course of the cauda equina nerve roots and a very beginning type of serpentine RNR is sometimes subtle and may lead to disagreements between the raters. In such cases the amount of straight roots on the one side of the reference stenotic level and the amount of serpentine RNR on the opposite side of the stenotic level was evaluated. If the pathologic pattern (serpentine RNR) was agreed to be prevalent (most of the roots show a serpentine shape) the case was considered as RNR+. Eighteen disagreements were reclassified in a consensus conference. Secondly, LLS and SLLS were measured. Finally, LSS-level, and LSS-grade were assessed for each patient.

Length of lumbar spine (LLS) and segmental length of lumbar spine (SLLS) measurements

Three authors (LP, JL, TF) measured LLS and SLLS independently on the sagittal T2-weighted slice showing the midplane of the conus using the AGFA Impax 6 software (AGFA Health Care, GmbH, Bonn, Germany). For LLS measurements a straight line was drawn from the posterior-superior corner of the L1 vertebral body to the posterior-superior corner of the S1 vertebral body (Fig. 3, red line). For SLLS measurements a line was drawn from the posterior-superior corner of the L1 vertebral body to the posterior-superior corner of the L2 vertebral body. The procedure was repeated until the line reached the posterior-superior corner of the S1 vertebral body (Fig. 3, blue line). LLS and SLLS were both determined by the length of the line (mm) [15]. Inter-rater reliability for both measurements was tested previously. The estimated intraclass correlation coefficient (ICC) calculated with a two-way mixed effects model with an absolute agreement definition was .99 (95% C.I. ranging from .98 to .99) and .99 (95% C.I ranging from .97 to .99) for LLS and SLLS measurements, respectively.

Fig. 3
figure3

Sagittal T2-WI used for length of lumbar spine (LLS, red vector) and segmental length of lumbar spine (sLLS, blue vector) measurements

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Calculation of rLLS and rSLLS

Absolute LLS and SLLS values were used to compute relative (%) rLLS and rSLLS values in relation to the patients’ body height.

Calculation of the amount of lumbar spine alignment deviation (LSAD)

The arithmetic difference between the SLLS and LLS values of each patient was calculated as an indicator of the degree of alignment deviations of the lumbar spine (LSAD). Greater differences are caused by higher degrees of alignment deviations such as hyper-lordosis or scoliosis.

Qualitative assessment of LSS-grade

There is no consensus regarding the specific diagnostic criteria for lumbar spinal stenosis (LSS) based on magnetic resonance imaging (MRI) [16]. A qualitative grading system based on the root-cerebrospinal fluid (CSF) relationship was described by Schizas et al. and was found to have a prognostic value [12]. The classification includes four progressive LSS grades, with grades A and B usually responding to conservative treatment, while grades C and D often require surgical decompression [17] (Fig. 4).

Fig. 4
figure4

Qualitative LSS severity grade classification according to Schizas et al. (2010). Normal: The roots lie dorsally and occupy less than half of the dural sac area. Grade A: (a) Cerebro-spinal fluid (CSF) is clearly visible within the dural sac and the distribution of the roots is irregular. Grade B: (b) The roots are distributed through the entire cross section of the thecal sac but they can still be individualized. Some CSF is still present, giving the sac a grainy appearance. Grade C: (c) single roots cannot be recognized anymore. They appear as one gray mass that completely fills the narrowed thecal sac. There is an epidural triangle of fat (2) between the arch (1) and thecal sac. Grade D: (d) In contrast to grade C, the triangle of fat has been completely squeezed out

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Three raters independently classified the LSS-grade of the patients, and the few cases with classification discrepancies were discussed in a consensus conference.

Quantitative assessment of LSS-level

The number of LSS-levels involved was assessed on the MRI images. A level was defined as stenotic if affected by a grade B or higher narrowing of the spinal canal. Patients were classified in three groups according to the number of stenotic levels: group 1 = one stenotic segment, group 2 = two stenotic segments, and group 3 = three or more stenotic segments involved.

Statistical analysis

The study sample was characterized with the use of mean ± standard deviation (SD) values for continuous variables (age, BH, LLS, SLLS, rLLS, rSLLS, LSAD) and frequencies for categorical variables (gender, RNR, LSS-grade, LSS-level). Demographic data comparisons between the groups were performed with t-tests for independent samples for continuous variables. In cases in which the variable data were expressed in frequencies, chi-square tests were used to test for group dependency. Binomial logistic regressions were carried out to investigate whether the presence of RNR could be predicted by patient demographics and MRI-based measurements. Age, gender, BH, LLS, SLLS, rLLS, rSLLS, LSAD, LSS-grade and LSS-level were considered as independent variables (potential predictors). The dependent variable was group affiliation (RNR+ or RNR-). For the logistic regression LSS-grade categories A and B and LSS-levels 2 and 3 were merged due to the low number of cases in one of the categories. Single predictors were tested in the 10 models. IBM SPSS software version 21 for Macintosh (IBM Corp. Armonk, New York) was used for all statistical analyses. The 0.05 level of probability was set as the criterion for statistical significance.

Results

Demographic data comparisons between groups (RNR+ vs. RNR-)

RNR+ patients were 2.6 years older (p = 0.01) and their BH was significantly shorter by 2.9 cm (p = 0.01) in comparison to RNR- patients. There was no significant difference in the distribution of male and female patients in both groups (p = 0.3).

The mean LLS and SLLS in the RNR+ group were significantly shorter by 8.9 mm (p < 0.001) and 7.5 mm (p < 0.001), respectively. The patients in the RNR+ group had a shorter lumbar spine in relation to their BH as evidenced by their significantly smaller rLLS and rSLLS (p < 0.001). There were no differences between the groups concerning the amount of LSAD (p = 0.07) (Table 1).

Table 1 Demographic data
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The distribution of patients across the LSS-grade categories was significantly different between the RNR+ and RNR- groups (p < 0.001). In the RNR+ and RNR- groups there were 33.3 and 12.7% of patients with LSS-grade D, respectively. Patients with LSS-grade C were balanced distributed in both groups with 65.3 and 78.0% for RNR+ and RNR-, respectively. There were also significantly more patients with two and three stenotic levels in the RNR+ group (p < 0.001) (Table 2).

Table 2 Distribution of LSS-grade and LSS-level
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Predictors of RNRs

Gender was not a significant predictor of RNRs (p = 0.3). The likelihood of RNR+ (Odds Ratio) increased 1.06 times as patients’ age increased by two years (p = 0.02). A 3 cm decrease in BH increased the chance of RNR+ group membership by 1.09 times (p = 0.01).

As LLS and SLLS decreased by 5 mm, the likelihood of RNR+ increased by 1.36 and 1.34 times, respectively (p < 0.001). A 1% decrease in rLLS and rSLLS increased the odds of RNR+ by 2.26 and 2.17 times, respectively (p < 0.001).

The amount of LSAD was not a significant RNR predictor (p = 0.07).

In patients with LSS-levels 2 and 3 the odds of RNR+ increased 2.59 times compared to patients with LSS-level 1 (p = 0.001) (Fig. 5).

Fig. 5
figure5

Significant predictors of RNR with the estimated odds ratios

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Patients with LSS-grade C were 5.86 times more likely to show RNR signs (p = 0.02), and LSS-grade D had a 18.4 times increased chance of RNR+ (p < 0.001) when comparing with patients affected by LSS-grade A and B (Table 3).

Table 3 Results of the binomial logistic regression models
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Discussion

The reported prevalence rates of RNR among LSS patients vary and range from 15% [7] to 45.5% [18], with the majority of studies reporting RNR prevalence rates around 40% [2, 3, 19]. Although some studies have evidenced the negative prognostic effect of RNR on postsurgical recovery of LSS-patients [2, 8, 14], no work previously investigated the potential weight of patient demographics and MRI-based measurements in predicting RNRs in LSS-patients. The main findings of the present study are as follows:

Patient-related and MRI-based measurements can predict the presence of RNR in LSS patients. The strongest predictors of RNR were LSS severity grade D, OR = 18.4, 95% C.I. [3.8 to 88.8], LSS severity grade C, OR = 5.8, 95% C.I. [1.3 to 26.4], LSS-level, OR = 2.5, 95% C.I. [1.4 to 4.5] and rLLS, OR = 2.2, 95% C.I. [1.7 to 2.9].

In the present study the patients in the RNR+ group were 2.6 years older (p = 0.01). This finding is in line with previous observations [6, 7, 9, 19] and a recent published meta-analysis [20]. In the literature the mean age difference between patients with or without RNR varies and ranges from 7.8 years [6] to 13.8 years [9]. Comparable mean ages between patients with or without RNR signs were reported in only two former studies [3, 21].

The mean BH of RNR+ patients was shorter by 2.9 cm (p = 0.01) and their LLS and SLLS were also significantly shorter by 8.9 mm and 7.5 mm, respectively (p < 0.001). Interesting is also the fact that the rLLS in RNR+ was shorter by 0.7% in relation to patients BH in comparison to RNR- patients (p < 0.001). The same was observed for rSLLS (mean diff. 0.6%, p < 0.0001). In view of these findings, the question is whether an aging-related degeneration of the lumbar spine with an absolute and a relative shortening of LLS and consequently a reduction in the length of the spinal canal plays a role in the pathogenesis of RNR?

The pathogenesis of RNR is still unclear. Suzuki et al. suggested that the squeezing force from the constricted spinal canal acting on the nerve roots causes the elongation and is the origin of RNR [9]. This explanation has not been questioned ever since. In the present study we have searched for significant predictors of RNR among patient-related factors. To the authors’ best knowledge, no previous study measured and compared the LLS, SLLS, rLLS and rSLLS in patients with or without RNR.

In the mid eighties Tsuji et al. [18] raised the hypothesis that age-dependent shortening of the lumbar spine may be connected to the pathogenesis of RNR. This assumption was never investigated since then but the present results seem to confirm it. rLLS and rSLLS were both significant predictors of RNR+ (p < 0.001). A 1% reduction in rLLS increased the odds of RNR+ by 2.26 times. The rLLS was the third strongest patient-related predictor of RNR.

Our results are also consistent with the explanation suggested by Suzuki et al. [9], since compression of the cauda equina nerve roots (LSS-grade) was the strongest RNR+ predictor. LLS-grade C increased the odds of RNR+ by 5.8 times, 95% C.I. [1.3 to 26.4], and LLS-grade D increased the chance of RNR+ by 18.42 times, 95% C.I. [3.8 to 88.8]. Our results also identified additional important factors in the pathogenesis of RNR, like the number of stenotic levels involved and the rLLS or rSLLS (Fig. 5).

When considering LSS severity, it is interesting to note that patients with LLS-grade C were similarly distributed in RNR+ (65.3%) and RNR- (78.0%) groups. Furthermore, 12.7% of RNR- patients were classified as LSS-grade D. How can the high percentage of RNR- patients (77%) that did not develop RNRs although affected by LSS-grade C or D be explained? Age-related LLS shrinking could make the difference. To clarify this question further investigation is needed.

Based on the present results the lumbar spine could be considered as the discal-osseous-ligamentous “container” of the cauda equina nerve roots. The nerve roots could be considered as the “content”. The container shrinks due to aging-related degenerative changes in the lumbar spine, but at the same time the roots of the cauda equina, fixed between conus medullaris and intraforaminal ganglia, keep their length. It sounds plausible that a progressive mismatch between container and content could origin a relative “over-length” of the cauda nerve roots. These can develop a serpentine-like shape at the beginning and a loop-like course in a further stage. The mismatch seems to ground on individual changes in the relationship between “container” and “content” and is evidenced by a smaller rLLS in relation to patients’ body height.

There was a significant difference in the distribution of LSS-levels between RNR+ and RNR- patients (p = 0.002) (Table 2). Thirty-two percent of RNR+ but only 15.4% of RNR- patients had two or more stenotic levels. Multi-segmental stenosis seems to interfere more with the natural course of the cauda nerve roots than single-level stenosis. This result confirms the one reported by Hur et al. [3]. It also confirms the importance of the “total amount” of compression in the pathogenesis of RNR that could be quantified as sum of LSS-grade and LSS-levels.

Poureisa et al. [7] reported that age (OR = 1.0, p = 0.01), the location of the stenosis (OR = 2.5, p < 0.001) and the presence of a sharp intracanal protuberance at the stenotic level (OR = 7.2, p < 0.001) were significantly and independently associated with RNR. Chen et al. [2] recently demonstrated that greater lumbar lordosis angles in extension and in neutral position, as well as a greater overall range of motion, were significantly associated with RNR. These results reinforce the assumption that RNR in LSS patients are caused by multiple factors and not only by compression.

Degenerative spondylolisthesis of grade higher than “1” according to the Meyerding [22] classification was an exclusion criterion in the present study. This probably explains why the amount of lumbar spine alignment deviation (LSAD) was not different between both groups (p = 0.07) and was not a significant RNR predictor. In contrast, Savarese et al. included patients with any degree of spondylolisthesis and reported that vertebral slip increased the prevalence of RNR by 3.5 times [19]. They also concluded that spondylolisthesis is an independent risk factor for RNR. For this reason we have decided, in the planning stage of the present work, to exclude patients diagnosed with LSS secondary to spondylolisthesis from the sample.

Due to the retrospective study design the number of potential predictors was restricted to the available data. This is a study limitation. There were no available data on clinical scores. A future study with a prospective study design should consider the assessment of clinical scores and functional data, such as the preoperative walking distance.

Conclusions

Patient-related factors were different between patients with or without RNR signs. Multiple factors are associated with the presence of RNR in LSS patients. Severe stenosis grade D or grade C, two or more stenotic levels and a shorter relative length of the lumbar spine were strong determinants of RNR.

Abbreviations

BH:

Body height

CSF:

Cerebro spinal fluid

LLS:

Length of lumbar spine

LSAD:

Lumbar spine alignment deviation

LSS:

Lumbar spinal stenosis

MRI:

Magnetic resonance imaging

OR:

Odds ratio

rLLS:

Relative length of lumbar spine

RNR-:

No evidence of RNR

RNR + :

Evidence of RNR.

RNRs:

Redundant nerve roots

rSLLS:

Relative segmental length of lumbar spine

SLLS:

Segmental length of lumbar spine

References

  1. 1.

    Deyo RA. Treatment of lumbar spinal stenosis: a balancing act. Spine J. 2010;10(7):625–7.

    Article  Google Scholar 

  2. 2.

    Chen J, Wang J, Wang B, Xu H, Lin S, Zhang H. Post-surgical functional recovery, lumbar lordosis, and range of motion associated with MR-detectable redundant nerve roots in lumbar spinal stenosis. Clin Neurol Neurosurg. 2016;140:79–84.

    Article  Google Scholar 

  3. 3.

    Hur JW, Hur JK, Kwon TH, Park YK, Chung HS, Kim JH. Radiological significance of ligamentum flavum hypertrophy in the occurrence of redundant nerve roots of central lumbar spinal stenosis. J Korean Neurosurg Soc. 2012;52(3):215–20.

    Article  Google Scholar 

  4. 4.

    Suzuki K, Takatsu T, Inoue H, Teramoto T, Ishida Y, Ohmori K. Redundant nerve roots of the cauda equina caused by lumbar spinal canal stenosis. Spine (Phila Pa 1976). 1992;17(11):1337–42.

    CAS  Article  Google Scholar 

  5. 5.

    Banse X, Manil O, Lecouvet F, Duprez T. Roots trajectory abnormalities and stenosis severity. Eur Spine J. 2010;19(Suppl 3):311–2.

    Google Scholar 

  6. 6.

    Min JH, Jang JS, Lee SH. Clinical significance of redundant nerve roots of the cauda equina in lumbar spinal stenosis. Clin Neurol Neurosurg. 2008;110(1):14–8.

    Article  Google Scholar 

  7. 7.

    Poureisa M, Daghighi MH, Eftekhari P, Bookani KR, Fouladi DF. Redundant nerve roots of the cauda equina in lumbar spinal canal stenosis, an MR study on 500 cases. Eur Spine J. 2015;24(10):2315–20.

    Article  Google Scholar 

  8. 8.

    Ono A, Suetsuna F, Irie T, Yokoyama T, Numasawa T, Wada K, Toh S. Clinical significance of the redundant nerve roots of the cauda equina documented on magnetic resonance imaging. J Neurosurg Spine. 2007;7(1):27–32.

    Article  Google Scholar 

  9. 9.

    Suzuki K, Ishida Y, Ohmori K, Sakai H, Hashizume Y. Redundant nerve roots of the cauda equina: clinical aspects and consideration of pathogenesis. Neurosurgery. 1989;24(4):521–8.

    CAS  Article  Google Scholar 

  10. 10.

    von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP, Initiative S. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453–7.

    Article  Google Scholar 

  11. 11.

    Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses using G*power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149–60.

    Article  Google Scholar 

  12. 12.

    Schizas C, Theumann N, Burn A, Tansey R, Wardlaw D, Smith FW, Kulik G. Qualitative grading of severity of lumbar spinal stenosis based on the morphology of the dural sac on magnetic resonance images. Spine (Phila Pa 1976). 2010;35(21):1919–24.

    Article  Google Scholar 

  13. 13.

    Duncan AW, Kido DK. Serpentine cauda equina nerve roots. Radiology. 1981;139(1):109–11.

    CAS  Article  Google Scholar 

  14. 14.

    Yokoyama K, Kawanishi M, Yamada M, Tanaka H, Ito Y, Hirano M, Kawabata S, Kuroiwa T. Clinical significance of postoperative changes in redundant nerve roots after decompressive laminectomy for lumbar spinal canal stenosis. World Neurosurg. 2014;82(6):e825–30.

    Article  Google Scholar 

  15. 15.

    Belavy DL, Armbrecht G, Gast U, Richardson CA, Hides JA, Felsenberg D. Countermeasures against lumbar spine deconditioning in prolonged bed rest: resistive exercise with and without whole body vibration. J Appl Physiol (1985). 2010;109(6):1801–11.

    Article  Google Scholar 

  16. 16.

    Tomkins-Lane CC, Quint DJ, Gabriel S, Melloh M, Haig AJ. Nerve root sedimentation sign for the diagnosis of lumbar spinal stenosis: reliability, sensitivity, and specificity. Spine (Phila Pa 1976). 2013;38(24):E1554–60.

    Article  Google Scholar 

  17. 17.

    Schizas C, Kulik G. Decision-making in lumbar spinal stenosis: a survey on the influence of the morphology of the dural sac. J Bone Joint Surg Br. 2012;94(1):98–101.

    CAS  Article  Google Scholar 

  18. 18.

    Tsuji H, Tamaki T, Itoh T, Yamada H, Motoe T, Tatezaki S, Noguchi T, Takano H. Redundant nerve roots in patients with degenerative lumbar spinal stenosis. Spine (Phila Pa 1976). 1985;10(1):72–82.

    CAS  Article  Google Scholar 

  19. 19.

    Savarese LG, Ferreira-Neto GD, Herrero CF, Defino HL, Nogueira-Barbosa MH. Cauda equina redundant nerve roots are associated to the degree of spinal stenosis and to spondylolisthesis. Arq Neuropsiquiatr. 2014;72(10):782–7.

    Article  Google Scholar 

  20. 20.

    Marques CJ, Hillebrand H, Papavero L. The clinical significance of redundant nerve roots of the cauda equina in lumbar spinal stenosis patients: a systematic literature review and meta-analysis. Clin Neurol Neurosurg. 2018;174:40–7.

    Article  Google Scholar 

  21. 21.

    Hakan T, Celikoglu E, Aydoseli A, Demir K. The redundant nerve root syndrome of the cauda equina. Turk Neurosurg. 2008;18(2):204–6.

    PubMed  Google Scholar 

  22. 22.

    Meyerding HW. Spondylolisthesis. Surg Gynecol Obstet. 1932;54:371–7.

    Google Scholar 

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Acknowledgments

The authors thank Mrs. Sibylle Bartsch for her creative support and exchange of ideas, the former patient Mr. Dieter Witt for sponsoring the Open Access publication and Mr. Roy Hammond for proofreading the final draft of the manuscript.

Funding

None of the authors or their institution received funding for this work.

Availability of data and materials

Raw data files or the SPSS output files may be provided by the corresponding author upon request.

Author information

Author notes

  1. Luca Papavero and Carlos J. Marques contributed equally to this work, they share the first authorship.

Affiliations

  1. Clinic for Spine Surgery, Schoen Clinic Hamburg Eilbek, Dehnhaide 120, D-22081, Hamburg, Germany

    Luca Papavero & Jens Lohmann

  2. Science Office of the Orthopedic and Joint Replacement Department, Schoen Clinic Hamburg Eilbek, Dehnhaide 120, D-22081, Hamburg, Germany

    Carlos J. Marques

  3. Department of Radiology, Schoen Clinic Hamburg Eilbek, Dehnhaide 120, D-22081, Hamburg, Germany

    Thies Fitting

  4. Non-Medical PhD Program, Faculty of Medicine (UKE), University of Hamburg, Hamburg, Germany

    Carlos J. Marques

Authors
  1. Luca Papavero
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  2. Carlos J. Marques
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  3. Jens Lohmann
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  4. Thies Fitting
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Contributions

LP and CJM contributed equally to this work and share the first authorship. LP planned the study and performed the database search; LP, JL and TF analyzed the MRIs. CJM designed the study, performed the statistical analysis and wrote the first draft of the manuscript; LP and CJM edited the first draft of the manuscript. All authors have read and approved the final version of the manuscript.

Corresponding author

Correspondence to Carlos J. Marques.

Ethics declarations

Ethics approval and consent to participate

The Ethics Committee of the Federal State of Hamburg deliberated upon this research project (File PV5817). According to the Ethics Committee, retrospective database-based studies do not require an ethic committee approval, whenever the data was acquired, saved and treated anonymously. This applies to the present study. According to the same Ethics Committee, the need for written or verbal consent is unnecessary in studies with the characteristics of the present one.

The database used for this research is not publicly available, it is property of the Schoen Clinic Group, whose access is regulated by the rules of procedure of its in-house Science Office.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Papavero, L., Marques, C.J., Lohmann, J. et al. Patient demographics and MRI-based measurements predict redundant nerve roots in lumbar spinal stenosis: a retrospective database cohort comparison. BMC Musculoskelet Disord 19, 452 (2018). https://doi.org/10.1186/s12891-018-2364-4

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Keywords

  • Redundant nerve roots
  • Lumbar spinal stenosis
  • Classification of lumbar spinal stenosis
  • Length of lumbar spine
  • Cauda equina claudication

BMC Musculoskeletal Disorders

ISSN: 1471-2474

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