Osteoporosis in spine surgery patients: what is the best way to diagnose osteoporosis in this population?

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  • 1 Mayo Clinic School of Medicine, Rochester, Minnesota;
  • 2 Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota;
  • 3 Department of Orthopedics and Rehabilitative Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin;
  • 4 Department of Neurologic Surgery, Mayo Clinic;
  • 5 Division of Endocrinology, Department of Medicine, Mayo Clinic; and
  • 6 Department of Biomedical Engineering, Mayo Clinic, Rochester, Minnesota
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OBJECTIVE

The goal of this study was to compare different recognized definitions of osteoporosis in patients with degenerative lumbar spine pathology undergoing elective spinal fusion surgery to determine which patient population should be considered for preoperative optimization.

METHODS

A retrospective review of patients in whom lumbar spine surgery was planned at 2 academic medical centers was performed, and the rate of osteoporosis was compared based on different recognized definitions. Assessments were made based on dual-energy x-ray absorptiometry (DXA), CT Hounsfield units (HU), trabecular bone score (TBS), and fracture risk assessment tool (FRAX). The rate of osteoporosis was compared based on different definitions: 1) the WHO definition (T-score ≤ −2.5) at total hip or spine; 2) CT HU of < 110; 3) National Bone Health Alliance (NBHA) guidelines; and 4) “expanded spine” criteria, which includes patients meeting NBHA criteria and/or HU < 110, and/or “degraded” TBS in the setting of an osteopenic T-score. Inclusion criteria were adult patients with a DXA scan of the total hip and/or spine performed within 1 year and a lumbar spine CT scan within 6 months of the physician visit.

RESULTS

Two hundred forty-four patients were included. The mean age was 68.3 years, with 70.5% female, 96.7% Caucasian, and the mean BMI was 28.8. Fracture history was reported in 53.8% of patients. The proportion of patients identified with osteoporosis on DXA, HUs, NBHA guidelines, and the authors’ proposed “expanded spine” criteria was 25.4%, 36.5%, 75%, and 81.9%, respectively. Of the patients not identified with osteoporosis on DXA, 31.3% had osteoporosis based on HU, 55.1% had osteoporosis with NBHA, and 70.4% had osteoporosis with expanded spine criteria (p < 0.05), with poor correlations among the different assessment tools.

CONCLUSIONS

Limitations in the use of DXA T-scores alone to diagnose osteoporosis in patients with lumbar spondylosis has prompted interest in additional methods of evaluating bone health in the spine, such as CT HU, TBS, and FRAX, to inform guidelines that aim to reduce fracture risk. However, no current osteoporosis assessment was developed with a focus on improving outcomes in spinal surgery. Therefore, the authors propose an expanded spine definition for osteoporosis to identify a more comprehensive cohort of patients with potential poor bone health who could be considered for preoperative optimization, although further study is needed to validate these results in terms of clinical outcomes.

ABBREVIATIONS BMD = bone mineral density; DXA = dual-energy x-ray absorptiometry; FRAX = Fracture Risk Assessment Tool; HU = Hounsfield unit; LL = lumbar lordosis; MOF = major osteoporotic fracture; NBHA = National Bone Health Alliance; PI = pelvic incidence; TBS = trabecular bone score.

OBJECTIVE

The goal of this study was to compare different recognized definitions of osteoporosis in patients with degenerative lumbar spine pathology undergoing elective spinal fusion surgery to determine which patient population should be considered for preoperative optimization.

METHODS

A retrospective review of patients in whom lumbar spine surgery was planned at 2 academic medical centers was performed, and the rate of osteoporosis was compared based on different recognized definitions. Assessments were made based on dual-energy x-ray absorptiometry (DXA), CT Hounsfield units (HU), trabecular bone score (TBS), and fracture risk assessment tool (FRAX). The rate of osteoporosis was compared based on different definitions: 1) the WHO definition (T-score ≤ −2.5) at total hip or spine; 2) CT HU of < 110; 3) National Bone Health Alliance (NBHA) guidelines; and 4) “expanded spine” criteria, which includes patients meeting NBHA criteria and/or HU < 110, and/or “degraded” TBS in the setting of an osteopenic T-score. Inclusion criteria were adult patients with a DXA scan of the total hip and/or spine performed within 1 year and a lumbar spine CT scan within 6 months of the physician visit.

RESULTS

Two hundred forty-four patients were included. The mean age was 68.3 years, with 70.5% female, 96.7% Caucasian, and the mean BMI was 28.8. Fracture history was reported in 53.8% of patients. The proportion of patients identified with osteoporosis on DXA, HUs, NBHA guidelines, and the authors’ proposed “expanded spine” criteria was 25.4%, 36.5%, 75%, and 81.9%, respectively. Of the patients not identified with osteoporosis on DXA, 31.3% had osteoporosis based on HU, 55.1% had osteoporosis with NBHA, and 70.4% had osteoporosis with expanded spine criteria (p < 0.05), with poor correlations among the different assessment tools.

CONCLUSIONS

Limitations in the use of DXA T-scores alone to diagnose osteoporosis in patients with lumbar spondylosis has prompted interest in additional methods of evaluating bone health in the spine, such as CT HU, TBS, and FRAX, to inform guidelines that aim to reduce fracture risk. However, no current osteoporosis assessment was developed with a focus on improving outcomes in spinal surgery. Therefore, the authors propose an expanded spine definition for osteoporosis to identify a more comprehensive cohort of patients with potential poor bone health who could be considered for preoperative optimization, although further study is needed to validate these results in terms of clinical outcomes.

ABBREVIATIONS BMD = bone mineral density; DXA = dual-energy x-ray absorptiometry; FRAX = Fracture Risk Assessment Tool; HU = Hounsfield unit; LL = lumbar lordosis; MOF = major osteoporotic fracture; NBHA = National Bone Health Alliance; PI = pelvic incidence; TBS = trabecular bone score.

Osteoporosis is characterized by low bone mass and poor bone quality leading to fragility fractures and is the most common metabolic bone disease.1–3 In the absence of fragility fractures after the age of 50 years, osteoporosis is classically defined by low bone mineral density (BMD) based on dual-energy x-ray absorptiometry (DXA). The WHO classifies bone health in adults age > 50 years by using the lowest spine or total hip BMD compared to a reference standard taken from young white women. Osteoporosis is defined as a T-score ≤ −2.5, osteopenia defined with a T-score between −1.0 and −2.4, and normal bone density with a T-score > −1.0.4 Despite the important role that DXA has played in fracture risk assessment, many individuals with incident fragility fractures have BMD values in the osteopenic range.5 Bone quality reflects the collagen structure, mineralization, turnover, and microarchitecture. Bone microarchitecture refers to the shape, orientation, and interconnectedness of trabeculae, and the width, distribution, and porosity of bone, and is more difficult to measure.

The trabecular bone score (TBS) was developed to describe bone microarchitecture of the vertebral body from lumbar spine DXA images. It does this by measuring gray-level texture variations from one pixel to the next across 2D images. This is not a direct measurement of bone microarchitecture but gives TBS the potential to discern differences in 3D microarchitecture between 2D DXA measurements that have similar BMD levels.1–3 Higher values of TBS are obtained in more homogeneously textured bone, whereas heterogeneously textured bone, with higher porosity and/or fatty infiltration, results in lower TBS values. This texture parameter obtained from a TBS provides additional skeletal information that is not captured from the standard BMD measurement, which makes TBS independent of and additive to fracture risk prediction by BMD.1–3,6 TBS is typically obtained from reanalysis of anterior-posterior lumbar spine DXA images. Lumbar TBSs are an age-dependent variable with little change observed between the ages of 30 and 45 years. Studies have shown that a progressive decrease which is more marked in women than in men, is observed with advancing age.1,8 Given the importance of bone microarchitecture in the evaluation of risk for fragility fractures with advancing age, TBS complements BMD assessment by DXA scan to inform clinical decision-making.7

Another method to estimate BMD is the use of Hounsfield unit (HU) measurements from CT.9–12 HUs are a dimensionless unit calculated based on the radiodensity of tissue, with increasingly positive values reflecting more dense tissue. Because lumbar CT is a routine preoperative examination for patients being evaluated for spinal surgery, the additional determination of HUs is essentially an opportunistic and costless augmentation to the information routinely obtained from CT scans obtained for any reason. An HU < 110 of the L1 vertebral body has been proposed as a diagnostic threshold for osteoporosis.12 Additionally, HUs may be particularly useful in patients with degenerative changes in the spine, because cortical sclerosis may increase the measured BMD on DXA,9 and has recently been shown to be useful to monitor improvement in lumbar BMD following teriparatide treatment.13

Recognizing the limitations in sensitivity of any single diagnostic test for defining osteoporosis, imaging modalities have been combined with clinical risk factors to improve diagnostic sensitivity. These assessments are particularly important for spine surgeons, because DXA has been demonstrated to be an inadequate predictor of osteoporosis-related complications following elective spinal fusion surgery.14,15 The most commonly used combined modality is the Fracture Risk Assessment Tool (FRAX), which estimates the 10-year probability of hip fracture and major osteoporotic fractures (MOFs) based on the individual’s risk factors profile.3,16 FRAX may be determined with or without BMD data and can be used to identify patients who need formal DXA screening and to aid treatment decisions. More recently, TBS has been used to further refine the FRAX predictive capabilities.1

With the development of multiple assessment tools for bone health, various definitions of osteoporosis have been established. In addition to the WHO criteria, the National Bone Health Alliance (NBHA) defined osteoporosis based on the presence of any of the following 3 criteria: “T-score ≤ −2.5 at the hip or spine, history of low energy hip fracture, clinical (i.e. diagnosed, not incidentally identified on imaging), vertebral, proximal humerus, pelvis, or some distal forearm fractures, or FRAX scores with ≥3% (hip) or ≥20% (major) 10-year fracture risk.”17 Using the expanded NBHA definition, compared to the WHO definition, would increase the prevalence of osteoporosis in the United States population ≥ 50 years old, to 30% of women and 16% of men.18 Thus, as with all disease, the method used to define it determines its prevalence and management.

We hypothesized that there is substantial variability in bone health characterization in patients with degenerative lumbar spine pathology based on different methods for diagnosing osteoporosis. Therefore, the objectives of this study were as follows: 1) to compare the performance of indicators of bone health developed for fracture risk assessment in patients with degenerative spinal disorders indicated for elective surgical intervention, and 2) to propose criteria for diagnosing osteoporosis in this patient population to identify those who should be considered for preoperative bone health optimization, to minimize the risk of surgical complications.

Methods

Following institutional review board approval, a retrospective review of patients from 2 independent academic centers was performed. All patients were evaluated for and/or underwent elective surgical treatment of lumbar degenerative pathology between 2007 and 2018. The additional inclusion criteria were patients with a DXA scan of the hips and/or spine performed within 1 year and CT scans within 6 months of the surgeon’s evaluation. Patients were excluded if they were younger than 18 years or had a concurrent infection, trauma, malignancy, skeletal dysplasia, neuromuscular disorders, or concomitant or staged anterior-posterior procedure.

Baseline characteristics, medical comorbidities, and surgical data were obtained from the electronic medical record. Patients were classified as having a fracture if there was a documented history of a fragility fracture. Prior CT scans obtained during patient workup were used to calculate the HU of a defined region of interest in the first lumbar vertebral body, as previously described.13 There were multiple CT scanners, with a 120-kV tube voltage. HU measurements were excluded from analysis if there was prior instrumentation at L1. All measurements were made using the institutions’ standard Picture Archiving and Communication Software (PACS). BMD by DXA was determined by using the lowest available T-scores of the total hip and lumbar spine. The FRAX 10-year MOF and hip fracture risk incorporating DXA BMD were documented from the medical record or calculated using the FRAX risk assessment calculator.19 The mean TBSs of L1–4 were calculated using TBS iNsight (TBS iNsight (Osteo), version 3.0.2.0; Medimaps Group). TBS ≤ 1.2 was considered degraded microarchitecture, TBS between 1.2 and 1.35 was partially degraded microarchitecture, and TBS ≥ 1.35 was normal.20,21

We then independently applied the following 4 diagnostic criteria to the entire study cohort to determine the prevalence of osteoporosis based on each definition (Table 1). Group 1) WHO—lowest total hip or spine T-score ≤ −2.5. Group 2) L1 vertebral body HU < 110. Group 3) NBHA—at least 1 of the following 3 criteria met: a) T-score ≤ −2.5 at the hip or spine; or b) history of low-energy hip fracture, clinical vertebral (i.e., diagnosed, not incidentally identified on imaging), proximal humerus, pelvis, or some distal forearm fractures; or c) FRAX (calculated with BMD) indicating a ≥ 3% (hip) or ≥ 20% (MOF) 10-year fracture risk. Group 4) Proposed “expanded spine” criteria—at least 1 of the 3 criteria met: a) NBHA definition; or b) HU < 110; or c) osteopenia (lowest T-score between −1.0 and −2.4) as well as “degraded” TBS (< 1.2).

TABLE 1.

Osteoporosis cohort and group definition

GroupDefinition
1WHO classic definition, lowest total hip or spine T-score ≤ −2.5
2L1 vertebral body HU < 110
3NBHA definition (at least 1 of the following 3 criteria met):
 a) T-score ≤ −2.5 at the hip or spine, or;
 b) history of low-energy hip fracture, clinical vertebral (i.e., diagnosed, not incidentally identified on imaging), proximal humerus, pelvis, or some distal forearm fractures, or;
 c) FRAX (calculated with BMD) indicating a ≥3% (hip) or ≥20% (MOF) 10-yr fracture risk
4Proposed “expanded spine” definition (at least 1 of the 3 criteria met):
 a) NBHA definition, or;
 b) HU < 110, or;
 c) osteopenia (lowest T-score between −1.0 and −2.4) as well as “degraded” TBS (<1.2)

Statistical Analysis

Standard descriptive summary statistics (e.g., means and SDs for continuous variables and percentage for categorical variables) were used to summarize demographic variables. Comparisons of categorical variables between subgroups were made using the chi-square test or the Fisher exact test, depending on the normality of the sample. Comparisons of continuous variables were completed using independent t-tests or simple linear regression. Alpha was set at a significance level of p < 0.05. Statistical analysis was performed using JMP software (version 14.1.0., 1989–2019; SAS Institute, Inc.).

Results

For the 244 patients included in the study, the mean age was 68.3 years, 70.5% were female, and 96.7% were white, with a mean BMI of 28.8 (Table 2). More than 53.8% reported a history of fracture, with 24% occurring after the age of 50 years.

TABLE 2.

Baseline demographic data in 244 patients with osteoporosis who underwent spine surgery

CharacteristicValue (%)
Mean age in yrs, ± SD68.3 ± 9.2
Age group, no. (%)
 <60 yrs38 (15.6)
 60–70 yrs103 (42.2)
 >70 yrs103 (42.2)
Sex, no. (%)
 Female172 (70.5)
Ethnicity, no. (%)
 Asian2 (0.8)
 Latino2 (0.8)
 Native American1 (0.4)
 Unknown3 (1.2)
 White236 (96.7)
BMI, mean ± SD28.8 ± 5.9
Fracture history, no. (%)
 None48 (46.2)
 <50 yrs old19 (18.3)
 ≥50 yrs old25 (24.0)
 Both12 (11.5)

Overall Densitometric Characteristics

Based on the lowest BMD of hip or spine, the overall mean (SD) DXA T-score was −1.72 (1.11). Based on WHO criteria there were 62 (25.4%) patients with osteoporosis, 132 (54.1%) patients with osteopenia, and 50 (20.5%) patients with normal BMD (Table 3). The mean FRAX 10-year risk of MOF was 17.9% (9.7%) and the mean hip fracture risk was 5.4% (5.4%) (Table 3). The mean TBS was 1.31 (0.12). There were 33 (22.3%) patients with normal TBS, 79 (53.4%) with partially degraded, and 36 (24.3%) with degraded TBS. The mean L1 HU was 131.7 (44.7). There were 53 (36.5%) of patients with HU < 110, and 38 (26.2%) of patients with HU ≥ 160.

TABLE 3.

Overall distribution of bone health measurements in 244 patients with osteoporosis who underwent spine surgery

MeasurementValue (%)
DXA T-score, no. (%)*
 Normal50 (20.5)
 Osteopenia132 (54.1)
 Osteoporosis62 (25.4)
 Mean T-score, ± SD−1.72 ± 1.11
HU, no. (%)
 <11053 (36.5)
 ≥11092 (63.5)
 <160107 (73.8)
 ≥16038 (26.2)
 Mean HU, ± SD131.7 ± 44.7
TBS, no. (%)
 Intact33 (22.3)
 Partially degraded79 (53.4)
 Degraded36 (24.3)
 Mean TBS, ± SD1.31 ± 0.12
Mean % w/ FRAX MOF, ± SD17.9 ± 9.7
Mean % w/ FRAX hip fracture, ± SD5.4 ± 5.4

Based on lowest T-score on DXA measurements of hip or spine.

10-year fracture risk.

Comparisons of Densitometric Characteristics

The proportion of patients identified with osteoporosis on WHO criteria, HU, NBHA, and expanded spine criteria was 25.4%, 36.5%, 75%, and 81.9%, respectively (p < 0.0001) (Table 4). In patients without WHO classification of osteoporosis based on T-score ≤ −2.5, 31.3% had osteoporosis based on HU, 55.1% using NBHA criteria, and 70.4% had osteoporosis with expanded spine criteria (Table 4).

TABLE 4.

Comparison of distribution of bone quality measurements grouped by T-score

HU, No. (%)NBHA, No. (%)Expanded Spine, No. (%)
DXA T-Score*Non-OPSOPSp ValueNon-OPSOPSp ValueNon-OPSOPSp Value
Normal38 (90.5)4 (9.5)<0.000116 (88.9)2 (11.1)<0.000114 (70)6 (30.0)<0.0001
Osteopenia50 (58.1)36 (41.9)19 (31.7)41 (68.3)15 (19.2)63 (80.8)
Osteoporosis4 (23.5)13 (76.5)0 (0)62 (100)0 (0)62 (100)
Total92 (63.5)53 (36.5)35 (25)105 (75)29 (18.1)131 (81.9)

OPS = osteoporosis.

Boxed values—patients without OPS based on T-score: 31.3% had OPS on HU, 55.1% had OPS with NBHA, and 70.4% had OPS with expanded spine criteria. Significant results (p < 0.05) are written in boldface type.

Lowest T-score based on DXA measurements.

To examine the influence of age and sex, the groups were further stratified. Among women less than 60 and women 60–70 years old, the rates of osteoporosis diagnosis using DXA, HU, and NBHA definitions were comparable (Fig. 1). However, there was an increase in osteopenia diagnosis using the HU definition for women greater than 70 years old (63% vs 36% for both DXA and NBHA definitions). Notably, the diagnosis of osteoporosis among men less than 60 years old was higher among the DXA- and NBHA-defined groups (29%) versus the HU-defined group (17%), whereas the diagnosis of osteoporosis in men greater than 70 years old was higher among the HU group (46%) than either the DXA or NBHA groups (6%).

FIG. 1.
FIG. 1.

Age-specific and sex-specific proportion of patients with osteoporosis, based on the different definitions of osteoporosis.

The association between DXA, HUs, and TBS was evaluated with simple linear regression (Fig. 2). The association between T-score and CT HU was weak, with R2 = 0.22 (p < 0.0001), and, as expected, TBS and T-score were weakly correlated consistent with each being independent indicators of bone strength, with R2 = 0.10 (p = 0.0001). There were also weak correlations between osteoporosis based on WHO class definition and osteoporosis based on the other 3 definitions that were examined (Table 5).

FIG. 2.
FIG. 2.

Scatterplots demonstrating poor correlation between (A) HUs and T-score, (B) TBS and HUs, and (C) TBS and T-score.

TABLE 5.

Group comparison using the Pearson chi-square test

ComparisonR2Chi-Square Testp Value
WHO by HU0.00010.0280.8678
WHO by NBHA0.433287.520<0.0001
WHO by expanded spine0.288651.544<0.0001

Significant results (p < 0.05) are written in boldface type.

Representative Case

A 65-year-old woman with a history of a prior L4–5 instrumented posterolateral fusion 4 years prior was referred with increasing back pain and progressive forward-leaning posture. She had a grade II spondylolisthesis and clear pseudarthrosis with loosening of the pedicle screws at L4 and L5. On standing radiographs (EOS Imaging), she had a sagittal vertical axis of 16 cm, pelvic incidence (PI) 70°, pelvic tilt 29°, and lumbar lordosis (LL) 35°, with only 12° of lordosis from L4 to S1 (Fig. 3A) and PI–LL mismatch of 35°. Her preoperative DXA demonstrated a T-score −0.4 at the total hip, nondiagnostic spine, and TBS 1.43. She underwent removal of posterior hardware at L4–5, and then received L4–5 and L5–S1 anterior lumbar interbody fusions, followed by posterior instrumented fusion for L2–sacrum with S2–alar–iliac supplemental fixation, resulting in 61° of lumbar lordosis, and 40° of lumbar lordosis from L4 to S1 (Fig. 3B). However, several weeks postoperatively she developed mechanical back pain and a progressive forward-leaning posture, with difficulty ambulating due to intractable pain. She was found to have proximal junctional failure with a fracture through the bilateral L2 pedicles (Fig. 3C and D). She then required extension of her construct to T10 (Fig. 3E). In retrospect, the HU measurement at the level of the L2 pedicles was 68 (Fig. 3F), which is suggestive of severe osteoporosis despite a normal total hip T-score and normal vertebral body TBS.

FIG. 3.
FIG. 3.

Representative case demonstrating utility of broader bone health screening. (A) Standing lateral radiograph demonstrating sagittal vertical axis 16 cm and 35° PI–LL mismatch. (B) Postoperative lateral lumbar spine radiograph demonstrating L2–S1 construct with pelvic supplemental fixation and restoration of lumbar lordosis. Sagittal CT demonstrating (C) right and (D) left pedicles with fracture extending through both pedicles and superior vertebral body. (E) Postoperative lateral standing scoliosis radiograph obtained following revision with extension up to T10. (F) HU measurement of 68 in the L2 vertebral body at the level of the pedicles.

Discussion

Osteoporosis as classically defined by T-score and/or low-energy fracture after the age of 50 years has been associated with adverse outcomes in spine surgery including screw loosening, pseudarthrosis, proximal and distal junctional fracture, or kyphosis.22–24 Osteoanabolic medications used both before and after surgery have been shown to improve outcomes of spine surgery in osteoporotic patients. Thus, the importance of preoperative evaluation of bone health is clear, although the optimal method to identify patients at risk of poor surgical outcomes is not known.23

The overall rate of osteoporosis regardless of definition was high in our patients being evaluated for possible spine surgery. The average T-score in our sample was −1.72, and 25.4% of patients were identified with osteoporosis based on DXA alone. However, each of the additional criteria identified a greater proportion of patients who may be considered as having poor bone health. We found that based on HU, NBHA guidelines, and our proposed expanded spine criteria, 36.5%, 75%, and 81.9% of patients, respectively, had poor bone health. Importantly, this means that based on these additional assessments or criteria, significantly more patients were identified with poor bone health if surgical outcomes rather than fracture risk was the basis for diagnosis, despite a T-score that would otherwise have not indicated osteoporosis.

Although we identified a greater proportion of patients with potential poor bone health, these results mirror a prior study on patients undergoing primary lumbar fusion surgery, in which 10% were diagnosed with osteoporosis and 59% were diagnosed with osteopenia. However, there was still a 33% risk of osteoporosis-related complications in the osteopenia group, whereas the osteoporotic group had a 50% risk.25 In a separate study on postmenopausal women undergoing spinal fusion surgery, CT postprocessing techniques were used to calculate vertebral trabecular BMD, and finite-element analysis was used to predict fracture and fragile bone strength. Whereas only 14% of the cohort had osteoporosis based on BMD alone, 27% had fragile bone strength, and 29% had poor bone quality based on finite-element analysis, suggesting that additional parameters outside of BMD result in poor bone health.26

Although DXA T-scores have been the gold standard for assessing bone health,27 this method may overestimate spine BMD in the setting of changes related to lumbar spondylosis thereby limiting their utility in this region of interest.9,28 This has led to growing interest in alternative or supplemental methods of assessing bone quality,9,11,28 especially in the setting of hyperparathyroidism, morbid obesity, single vertebral reading, or anatomical variation.29 Additionally, Z-scores rather than T-scores are used when assessing BMD in children, men younger than age 50 years, and premenopausal women.29 These types of limitations have led to methods that may be less affected by degenerative changes in the spine caused by comorbidities.9,30

Opportunistic use of screening CT scans by measuring HU isolates regions of interest to the vertebral body (or even pedicle screw tracts), thus potentially being useful in place of DXA in degenerative and deformity lumbar spine cases.9,10,13 In the lumbar spine, HU < 110 has been the identified as a cutoff or threshold for the diagnosis of osteoporosis.30,31 Although 25.4% of patients had osteoporosis based on DXA alone, applying the HU threshold of < 110 identified that 36.5% of patients had osteoporosis. Because many spine patients have significant degenerative changes or spinal deformity with invalid lumbar BMD measurements on DXA,32 HU measurements are a valuable tool in the lumbar spine, and may provide a superior assessment of risk for vertebral fracture.33 For instance, HU measurements ≤ 90 at L1 resulted in a significantly increased risk of fracture.34

TBS informs fracture prediction and is less affected by degenerative changes than is BMD. Because TBS is independent of BMD,28 the addition of TBS analysis aids in stratifying fracture risk, even in the presence of normal DXA T-scores. For instance, in a cadaveric study, there was a significant correlation between TBS and trabecular bone volume, but no correlation between TBS and BMD.35 We found that 24.3% of patients had “degraded” bone microarchitecture on TBS, including 17.1% of patients without osteoporosis based on DXA T-scores alone, thus identifying additional patients who may be at risk of osteoporosis-related complications postoperatively. We similarly found that BMD based on DXA was poorly correlated with the other assessment definitions as well as TBS. This was also consistent with prior findings that BMD measures bone quantity, whereas TBS may be more reflective of bone porosity and/or fatty infiltration.7 Patients with type 2 diabetes often do not have diminished BMD but have elevated fracture risk associated with low TBS.7 The TBS can also be used as an input to FRAX and aid identification of high fracture risk. However, whereas TBS has been found to be associated with an overall increased fracture risk,28,36,37 its clinical performance in predicting complications following spine surgery in the setting of degenerative changes, prior surgery, or spinal deformity has yet to be fully determined.

Based on our data, there was a high rate of poor bone health in patients undergoing elective lumbar spine surgery, with 25.4% of patients diagnosed by T-score alone, and 81.9% with osteoporosis if defined by our proposed expanded spine criteria. Because there is an elevated risk of postoperative complications in both osteoporotic and osteopenic patients (as defined by T-score) undergoing elective lumbar spine surgery,38 we recommend that preoperative testing with DXA be supplemented by opportunistic CT imaging for HU measurements. We also propose using the expanded spine criteria to identify the broadest cohort of patients who should be considered for medical optimization of bone health prior to surgery, although further clinical outcome studies are required to validate the use of our proposed criteria.

There are limitations to this study, such as its retrospective nature and moderate sample size. For instance, there was incomplete fracture history data on some of the patients, so it was not possible to correlate fracture risk with the different osteoporosis definitions, and further assessment of future fracture risk would allow us to establish the sensitivity and specificity of each definition. There was potential selection bias in who underwent DXA because the use was not universally applied. Additionally, because clinical outcome endpoints such as fusion rate or hardware failure were not assessed, it is not possible to validate our proposed expanded spine criteria to stratify postoperative risk. Also, there may be variability in the HU assessments based on differences in CT machines and distance in collimator from the patient. Last, we used T-scores for all patients in this study, although Z-scores would be the more appropriate measure in patients < 50 years of age. Although the expanded spine criteria is complicated, and may be challenging to implement in everyday use, the model was designed to be comprehensive. Further studies could examine a “modified spine criteria” by using DXA with HU and FRAX as a screening method. This would provide a simpler model that could readily be used by most spine surgeons, and would be likely to identify a majority of patients with osteoporosis.

Conclusions

Although DXA has been the historical gold standard in assessing bone health, it has significant limitations in patients with lumbar spondylosis, which has prompted spine surgeons to seek additional methods of evaluating bone health in the spine, such as CT HU, TBS, and FRAX. Even newer diagnostic criteria for osteoporosis, such as the NBHA guidelines, remain focused on predicting fracture risk. Therefore, we propose expanded spine criteria to identify patients at risk of poor surgical outcomes due to poor bone health or “surgical osteoporosis” despite “nonosteoporotic” T-scores. These criteria identified that 81.9% of our patients had poor bone health, including 70.4% of patients with a T-score > −2.5. The expanded spine criteria could aid in the identification of patients with poor health to facilitate bone health optimization prior to spine surgical intervention, although further study is needed to validate these results with clinical outcomes.

Disclosures

Dr. Currier reports receiving royalties for a chapter in UpToDate from Wolters Kluwer, for design work from DePuy Synthes and Zimmer Biomet, institutional fellowship support from AO Spine North America, and direct stock ownership in Tenex and Spinology. Dr. Fogelson reports being a consultant for Medtronic. Dr. Nassr reports receiving AO Spine North America research funding, Pfizer research funding, and Premia Spine research funding. Dr. Anderson is a consultant for Amgen, Radius Medical, and Medtronic; owns stock in Titan Spine; and receives royalties from Regeneration Technologies, Inc.

Author Contributions

Conception and design: Elder. Acquisition of data: St. Jeor. Analysis and interpretation of data: St. Jeor, Jackson, Xiong. Drafting the article: St. Jeor, Jackson, Xiong. Critically revising the article: Elder, St. Jeor, Kadri, Freedman, Sebastian, Currier, Nassr, Fogelson, Kennel, Anderson. Statistical analysis: Jackson.

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    • Export Citation
  • 7

    Krohn K, Schwartz EN, Chung YS, Lewiecki EM. Dual-energy X-ray absorptiometry monitoring with trabecular bone score: 2019 ISCD Official Position. J Clin Densitom. 2019;22(4):501505.

    • Search Google Scholar
    • Export Citation
  • 8

    Simonelli C, Leib E, Mossman N, Creation of an age-adjusted, dual-energy x-ray absorptiometry-derived trabecular bone score curve for the lumbar spine in non-Hispanic US White women. J Clin Densitom. 2014;17(2):314319.

    • Search Google Scholar
    • Export Citation
  • 9

    Zou D, Li W, Deng C, The use of CT Hounsfield unit values to identify the undiagnosed spinal osteoporosis in patients with lumbar degenerative diseases. Eur Spine J. 2019;28(8):17581766.

    • Search Google Scholar
    • Export Citation
  • 10

    Anderson PA, Morgan SL, Krueger D, Use of bone health evaluation in orthopedic surgery: 2019 ISCD Official Position. J Clin Densitom. 2019;22(4):517543.

    • Search Google Scholar
    • Export Citation
  • 11

    Schreiber JJ, Anderson PA, Rosas HG, Hounsfield units for assessing bone mineral density and strength: a tool for osteoporosis management. J Bone Joint Surg Am. 2011;93(11):10571063.

    • Search Google Scholar
    • Export Citation
  • 12

    Schreiber JJ, Anderson PA, Hsu WK. Use of computed tomography for assessing bone mineral density. Neurosurg Focus. 2014;37(1):E4.

  • 13

    Mikula AL, Puffer RC, Jeor JDS, Teriparatide treatment increases Hounsfield units in the lumbar spine out of proportion to DEXA changes. J Neurosurg Spine. 2020;32(1):5055.

    • Search Google Scholar
    • Export Citation
  • 14

    Kanis JA, Hans D, Cooper C, Interpretation and use of FRAX in clinical practice. Osteoporos Int. 2011;22(9):23952411.

  • 15

    Kanis JA, McCloskey EV, Johansson H, Development and use of FRAX in osteoporosis. Osteoporos Int. 2010;21(suppl 2):S407S413.

  • 16

    Kanis JA, Johnell O, Oden A, FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int. 2008;19(4):385397.

    • Search Google Scholar
    • Export Citation
  • 17

    Siris ES, Adler R, Bilezikian J, The clinical diagnosis of osteoporosis: a position statement from the National Bone Health Alliance Working Group. Osteoporos Int. 2014;25(5):14391443.

    • Search Google Scholar
    • Export Citation
  • 18

    Wright NC, Saag KG, Dawson-Hughes B, The impact of the new National Bone Health Alliance (NBHA) diagnostic criteria on the prevalence of osteoporosis in the USA. Osteoporos Int. 2017;28(4):12251232.

    • Search Google Scholar
    • Export Citation
  • 19

    International Society for Clinical Densitometry. 2010 Official Positions of the ISCD/IOF Interpretation and Use of FRAX in Clinical Practice. June 28, 2019. Accessed June 16, 2020. https://www.iscd.org/official-positions/2010-official-positions-iscd-iof-frax/

    • Export Citation
  • 20

    Hans D, Šteňová E, Lamy O. The trabecular bone score (TBS) complements DXA and the FRAX as a fracture risk assessment tool in routine clinical practice. Curr Osteoporos Rep. 2017;15(6):521531.

    • Search Google Scholar
    • Export Citation
  • 21

    White R, Binkley N, Krueger D. Effect of vertebral exclusion on TBS and FRAX calculations. Arch Osteoporos. 2018;13(1):87.

  • 22

    Bokov A, Bulkin A, Aleynik A, Pedicle screws loosening in patients with degenerative diseases of the lumbar spine: potential risk factors and relative contribution. Global Spine J. 2019;9(1):5561.

    • Search Google Scholar
    • Export Citation
  • 23

    Kadri A, Binkley N, Hare KJ, Anderson PA. Bone health optimization in orthopaedic surgery. J Bone Joint Surg Am. 2020;102(7):574581.

  • 24

    Ullrich BW, Schenk P, Spiegl UJ, Hounsfield units as predictor for cage subsidence and loss of reduction: following posterior-anterior stabilization in thoracolumbar spine fractures. Eur Spine J. 2018;27(12):30343042.

    • Search Google Scholar
    • Export Citation
  • 25

    Chin DK, Park JY, Yoon YS, Prevalence of osteoporosis in patients requiring spine surgery: incidence and significance of osteoporosis in spine disease. Osteoporos Int. 2007;18(9):12191224.

    • Search Google Scholar
    • Export Citation
  • 26

    Burch S, Feldstein M, Hoffmann PF, Keaveny TM. Prevalence of poor bone quality in women undergoing spinal fusion using biomechanical-CT analysis. Spine (Phila Pa 1976). 2016;41(3):246252.

    • Search Google Scholar
    • Export Citation
  • 27

    Black DM, Rosen CJ. Clinical practice. Postmenopausal osteoporosis. N Engl J Med. 2016;374(3):254262.

  • 28

    Silva BC, Leslie WD, Resch H, Trabecular bone score: a noninvasive analytical method based upon the DXA image. J Bone Miner Res. 2014;29(3):518530.

    • Search Google Scholar
    • Export Citation
  • 29

    International Society for Clinical Densitometry. 2015 ISCD Official Positions—Adult. June 16, 2015. Accessed June 16, 2020. https://www.iscd.org/official-positions/2015-iscd-official-positions-adult/

    • Search Google Scholar
    • Export Citation
  • 30

    Anderson KB, Holloway-Kew KL, Mohebbi M, Is trabecular bone score less affected by degenerative-changes at the spine than lumbar spine BMD? Arch Osteoporos. 2018;13(1):127.

    • Search Google Scholar
    • Export Citation
  • 31

    Lee SJ, Binkley N, Lubner MG, Opportunistic screening for osteoporosis using the sagittal reconstruction from routine abdominal CT for combined assessment of vertebral fractures and density. Osteoporos Int. 2016;27(3):11311136.

    • Search Google Scholar
    • Export Citation
  • 32

    Lewiecki EM, Binkley N, Morgan SL, Best practices for dual-energy X-ray absorptiometry measurement and reporting: International Society for Clinical Densitometry Guidance. J Clin Densitom. 2016;19(2):127140.

    • Search Google Scholar
    • Export Citation
  • 33

    Engelke K, Adams JE, Armbrecht G, Clinical use of quantitative computed tomography and peripheral quantitative computed tomography in the management of osteoporosis in adults: the 2007 ISCD Official Positions. J Clin Densitom. 2008;11(1):123162.

    • Search Google Scholar
    • Export Citation
  • 34

    Lee SJ, Graffy PM, Zea RD, Future osteoporotic fracture risk related to lumbar vertebral trabecular attenuation measured at routine body CT. J Bone Miner Res. 2018;33(5):860867.

    • Search Google Scholar
    • Export Citation
  • 35

    Roux JP, Wegrzyn J, Boutroy S, The predictive value of trabecular bone score (TBS) on whole lumbar vertebrae mechanics: an ex vivo study. Osteoporos Int. 2013;24(9):24552460.

    • Search Google Scholar
    • Export Citation
  • 36

    Pothuaud L, Barthe N, Krieg MA, Evaluation of the potential use of trabecular bone score to complement bone mineral density in the diagnosis of osteoporosis: a preliminary spine BMD-matched, case-control study. J Clin Densitom. 2009;12(2):170176.

    • Search Google Scholar
    • Export Citation
  • 37

    Winzenrieth R, Dufour R, Pothuaud L, Hans D. A retrospective case-control study assessing the role of trabecular bone score in postmenopausal Caucasian women with osteopenia: analyzing the odds of vertebral fracture. Calcif Tissue Int. 2010;86(2):104109.

    • Search Google Scholar
    • Export Citation
  • 38

    Bjerke BT, Zarrabian M, Aleem IS, Incidence of osteoporosis-related complications following posterior lumbar fusion. Global Spine J. 2018;8(6):563569.

    • Search Google Scholar
    • Export Citation

If the inline PDF is not rendering correctly, you can download the PDF file here.

Contributor Notes

Correspondence Benjamin D. Elder: Mayo Clinic, Rochester, MN. elder.benjamin@mayo.edu.

INCLUDE WHEN CITING DOI: 10.3171/2020.5.FOCUS20277.

Disclosures Dr. Currier reports receiving royalties for a chapter in UpToDate from Wolters Kluwer, for design work from DePuy Synthes and Zimmer Biomet, institutional fellowship support from AO Spine North America, and direct stock ownership in Tenex and Spinology. Dr. Fogelson reports being a consultant for Medtronic. Dr. Nassr reports receiving AO Spine North America research funding, Pfizer research funding, and Premia Spine research funding. Dr. Anderson is a consultant for Amgen, Radius Medical, and Medtronic; owns stock in Titan Spine; and receives royalties from Regeneration Technologies, Inc.

  • View in gallery

    Age-specific and sex-specific proportion of patients with osteoporosis, based on the different definitions of osteoporosis.

  • View in gallery

    Scatterplots demonstrating poor correlation between (A) HUs and T-score, (B) TBS and HUs, and (C) TBS and T-score.

  • View in gallery

    Representative case demonstrating utility of broader bone health screening. (A) Standing lateral radiograph demonstrating sagittal vertical axis 16 cm and 35° PI–LL mismatch. (B) Postoperative lateral lumbar spine radiograph demonstrating L2–S1 construct with pelvic supplemental fixation and restoration of lumbar lordosis. Sagittal CT demonstrating (C) right and (D) left pedicles with fracture extending through both pedicles and superior vertebral body. (E) Postoperative lateral standing scoliosis radiograph obtained following revision with extension up to T10. (F) HU measurement of 68 in the L2 vertebral body at the level of the pedicles.

  • 1

    Harvey NC, Glüer CC, Binkley N, Trabecular bone score (TBS) as a new complementary approach for osteoporosis evaluation in clinical practice. Bone. 2015;78:216224.

    • Search Google Scholar
    • Export Citation
  • 2

    Mirzaei A, Jahed SA, Nojomi M, A study of the value of trabecular bone score in fracture risk assessment of postmenopausal women. Taiwan J Obstet Gynecol. 2018;57(3):389393.

    • Search Google Scholar
    • Export Citation
  • 3

    Shevroja E, Lamy O, Kohlmeier L, Use of trabecular bone score (TBS) as a complementary approach to dual-energy X-ray absorptiometry (DXA) for fracture risk assessment in clinical practice. J Clin Densitom. 2017;20(3):334345.

    • Search Google Scholar
    • Export Citation
  • 4

    World Health Organization. WHO Scientific Group on the Assessment of Osteoporosis at Primary Health Care Level. Summary Meeting Report. Published 2007. Accessed June 16, 2020. https://www.who.int/chp/topics/Osteoporosis.pdf

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  • 5

    Siris ES, Brenneman SK, Barrett-Connor E, The effect of age and bone mineral density on the absolute, excess, and relative risk of fracture in postmenopausal women aged 50-99: results from the National Osteoporosis Risk Assessment (NORA). Osteoporos Int. 2006;17(4):565574.

    • Search Google Scholar
    • Export Citation
  • 6

    Martineau P, Leslie WD. The utility and limitations of using trabecular bone score with FRAX. Curr Opin Rheumatol. 2018;30(4):412419.

    • Search Google Scholar
    • Export Citation
  • 7

    Krohn K, Schwartz EN, Chung YS, Lewiecki EM. Dual-energy X-ray absorptiometry monitoring with trabecular bone score: 2019 ISCD Official Position. J Clin Densitom. 2019;22(4):501505.

    • Search Google Scholar
    • Export Citation
  • 8

    Simonelli C, Leib E, Mossman N, Creation of an age-adjusted, dual-energy x-ray absorptiometry-derived trabecular bone score curve for the lumbar spine in non-Hispanic US White women. J Clin Densitom. 2014;17(2):314319.

    • Search Google Scholar
    • Export Citation
  • 9

    Zou D, Li W, Deng C, The use of CT Hounsfield unit values to identify the undiagnosed spinal osteoporosis in patients with lumbar degenerative diseases. Eur Spine J. 2019;28(8):17581766.

    • Search Google Scholar
    • Export Citation
  • 10

    Anderson PA, Morgan SL, Krueger D, Use of bone health evaluation in orthopedic surgery: 2019 ISCD Official Position. J Clin Densitom. 2019;22(4):517543.

    • Search Google Scholar
    • Export Citation
  • 11

    Schreiber JJ, Anderson PA, Rosas HG, Hounsfield units for assessing bone mineral density and strength: a tool for osteoporosis management. J Bone Joint Surg Am. 2011;93(11):10571063.

    • Search Google Scholar
    • Export Citation
  • 12

    Schreiber JJ, Anderson PA, Hsu WK. Use of computed tomography for assessing bone mineral density. Neurosurg Focus. 2014;37(1):E4.

  • 13

    Mikula AL, Puffer RC, Jeor JDS, Teriparatide treatment increases Hounsfield units in the lumbar spine out of proportion to DEXA changes. J Neurosurg Spine. 2020;32(1):5055.

    • Search Google Scholar
    • Export Citation
  • 14

    Kanis JA, Hans D, Cooper C, Interpretation and use of FRAX in clinical practice. Osteoporos Int. 2011;22(9):23952411.

  • 15

    Kanis JA, McCloskey EV, Johansson H, Development and use of FRAX in osteoporosis. Osteoporos Int. 2010;21(suppl 2):S407S413.

  • 16

    Kanis JA, Johnell O, Oden A, FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int. 2008;19(4):385397.

    • Search Google Scholar
    • Export Citation
  • 17

    Siris ES, Adler R, Bilezikian J, The clinical diagnosis of osteoporosis: a position statement from the National Bone Health Alliance Working Group. Osteoporos Int. 2014;25(5):14391443.

    • Search Google Scholar
    • Export Citation
  • 18

    Wright NC, Saag KG, Dawson-Hughes B, The impact of the new National Bone Health Alliance (NBHA) diagnostic criteria on the prevalence of osteoporosis in the USA. Osteoporos Int. 2017;28(4):12251232.

    • Search Google Scholar
    • Export Citation
  • 19

    International Society for Clinical Densitometry. 2010 Official Positions of the ISCD/IOF Interpretation and Use of FRAX in Clinical Practice. June 28, 2019. Accessed June 16, 2020. https://www.iscd.org/official-positions/2010-official-positions-iscd-iof-frax/

    • Export Citation
  • 20

    Hans D, Šteňová E, Lamy O. The trabecular bone score (TBS) complements DXA and the FRAX as a fracture risk assessment tool in routine clinical practice. Curr Osteoporos Rep. 2017;15(6):521531.

    • Search Google Scholar
    • Export Citation
  • 21

    White R, Binkley N, Krueger D. Effect of vertebral exclusion on TBS and FRAX calculations. Arch Osteoporos. 2018;13(1):87.

  • 22

    Bokov A, Bulkin A, Aleynik A, Pedicle screws loosening in patients with degenerative diseases of the lumbar spine: potential risk factors and relative contribution. Global Spine J. 2019;9(1):5561.

    • Search Google Scholar
    • Export Citation
  • 23

    Kadri A, Binkley N, Hare KJ, Anderson PA. Bone health optimization in orthopaedic surgery. J Bone Joint Surg Am. 2020;102(7):574581.

  • 24

    Ullrich BW, Schenk P, Spiegl UJ, Hounsfield units as predictor for cage subsidence and loss of reduction: following posterior-anterior stabilization in thoracolumbar spine fractures. Eur Spine J. 2018;27(12):30343042.

    • Search Google Scholar
    • Export Citation
  • 25

    Chin DK, Park JY, Yoon YS, Prevalence of osteoporosis in patients requiring spine surgery: incidence and significance of osteoporosis in spine disease. Osteoporos Int. 2007;18(9):12191224.

    • Search Google Scholar
    • Export Citation
  • 26

    Burch S, Feldstein M, Hoffmann PF, Keaveny TM. Prevalence of poor bone quality in women undergoing spinal fusion using biomechanical-CT analysis. Spine (Phila Pa 1976). 2016;41(3):246252.

    • Search Google Scholar
    • Export Citation
  • 27

    Black DM, Rosen CJ. Clinical practice. Postmenopausal osteoporosis. N Engl J Med. 2016;374(3):254262.

  • 28

    Silva BC, Leslie WD, Resch H, Trabecular bone score: a noninvasive analytical method based upon the DXA image. J Bone Miner Res. 2014;29(3):518530.

    • Search Google Scholar
    • Export Citation
  • 29

    International Society for Clinical Densitometry. 2015 ISCD Official Positions—Adult. June 16, 2015. Accessed June 16, 2020. https://www.iscd.org/official-positions/2015-iscd-official-positions-adult/

    • Search Google Scholar
    • Export Citation
  • 30

    Anderson KB, Holloway-Kew KL, Mohebbi M, Is trabecular bone score less affected by degenerative-changes at the spine than lumbar spine BMD? Arch Osteoporos. 2018;13(1):127.

    • Search Google Scholar
    • Export Citation
  • 31

    Lee SJ, Binkley N, Lubner MG, Opportunistic screening for osteoporosis using the sagittal reconstruction from routine abdominal CT for combined assessment of vertebral fractures and density. Osteoporos Int. 2016;27(3):11311136.

    • Search Google Scholar
    • Export Citation
  • 32

    Lewiecki EM, Binkley N, Morgan SL, Best practices for dual-energy X-ray absorptiometry measurement and reporting: International Society for Clinical Densitometry Guidance. J Clin Densitom. 2016;19(2):127140.

    • Search Google Scholar
    • Export Citation
  • 33

    Engelke K, Adams JE, Armbrecht G, Clinical use of quantitative computed tomography and peripheral quantitative computed tomography in the management of osteoporosis in adults: the 2007 ISCD Official Positions. J Clin Densitom. 2008;11(1):123162.

    • Search Google Scholar
    • Export Citation
  • 34

    Lee SJ, Graffy PM, Zea RD, Future osteoporotic fracture risk related to lumbar vertebral trabecular attenuation measured at routine body CT. J Bone Miner Res. 2018;33(5):860867.

    • Search Google Scholar
    • Export Citation
  • 35

    Roux JP, Wegrzyn J, Boutroy S, The predictive value of trabecular bone score (TBS) on whole lumbar vertebrae mechanics: an ex vivo study. Osteoporos Int. 2013;24(9):24552460.

    • Search Google Scholar
    • Export Citation
  • 36

    Pothuaud L, Barthe N, Krieg MA, Evaluation of the potential use of trabecular bone score to complement bone mineral density in the diagnosis of osteoporosis: a preliminary spine BMD-matched, case-control study. J Clin Densitom. 2009;12(2):170176.

    • Search Google Scholar
    • Export Citation
  • 37

    Winzenrieth R, Dufour R, Pothuaud L, Hans D. A retrospective case-control study assessing the role of trabecular bone score in postmenopausal Caucasian women with osteopenia: analyzing the odds of vertebral fracture. Calcif Tissue Int. 2010;86(2):104109.

    • Search Google Scholar
    • Export Citation
  • 38

    Bjerke BT, Zarrabian M, Aleem IS, Incidence of osteoporosis-related complications following posterior lumbar fusion. Global Spine J. 2018;8(6):563569.

    • Search Google Scholar
    • Export Citation

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