Advanced Quantitative Spine Imaging

Abstract

Although advanced quantitative imaging may not be currently used to any degree in the routine reporting of spinal examinations, this situation will change in the not too distant future. Advanced quantitative imaging has already allowed us to understand a great deal more regarding spinal development, marrow physiology, and disease pathogenesis. Radiologists are ideally suited to drive this research forward. To speed up this process and optimize the impact of studies reporting spine quantitative data, we should work toward universal standards on the acquisition of spine data that will allow quantitative studies to be more easily compared, contrasted, and amalgamated.

Keywords

spine - imaging - quantification

Publikationsverlauf

Artikel online veröffentlicht:
29. September 2020

• References

• 1 Weaver O, Leung JWT. Biomarkers and imaging of breast cancer. AJR Am J Roentgenol 2018; 210 (02) 271-278
• 2 Whyte MB, Kelly P. The normal range: it is not normal and it is not a range. Postgrad Med J 2018; 94 (1117): 613-616
• 3 Flechtner-Mors M, Schwab KO, Fröhlich-Reiterer EE. , et al. Overweight and obesity based on four reference systems in 18,382 paediatric patients with type 1 diabetes from Germany and Austria. J Diabetes Res 2015; 2015: 370753
• 4 Ulbrich EJ, Schraner C, Boesch C. , et al. Normative MR cervical spinal canal dimensions. Radiology 2014; 271 (01) 172-182
• 5 Kato F, Yukawa Y, Suda K, Yamagata M, Ueta T. Normal morphology, age-related changes and abnormal findings of the cervical spine. Part II: Magnetic resonance imaging of over 1,200 asymptomatic subjects. Eur Spine J 2012; 21 (08) 1499-1507
• 6 Fradet L, Arnoux PJ, Ranjeva JP, Petit Y, Callot V. Morphometrics of the entire human spinal cord and spinal canal measured from in vivo high-resolution anatomical magnetic resonance imaging. Spine 2014; 39 (04) E262-E269
• 7 Matsuura P, Waters RL, Adkins RH, Rothman S, Gurbani N, Sie I. Comparison of computerized tomography parameters of the cervical spine in normal control subjects and spinal cord-injured patients. J Bone Joint Surg Am 1989; 71 (02) 183-188
• 8 American College of Radiology. Practice parameter for the performance of quantitative computed tomography (QCT) bone densitometry. Available at: https://www.acr.org/Quality-Safety/Standards-Guidelines/Practice-Guidelines-by-Modality/CT . Accessed April 12, 2020
• 9 Zhang JT, Wang LF, Liu YJ. , et al. Relationship between developmental canal stenosis and surgical results of anterior decompression and fusion in patients with cervical spondylotic myelopathy. BMC Musculoskelet Disord 2015; 16: 267
• 10 Kadoya S, Nakamura T, Kwak R, Hirose G. Anterior osteophytectomy for cervical spondylotic myelopathy in developmentally narrow canal. J Neurosurg 1985; 63 (06) 845-850
• 11 Nouri A, Martin AR, Nater A. , et al. Influence of magnetic resonance imaging features on surgical decision-making in degenerative cervical myelopathy: results from a global survey of AOSpine international members. World Neurosurg 2017; 105: 864-874
• 12 Morishita Y, Naito M, Hymanson H, Miyazaki M, Wu G, Wang JC. The relationship between the cervical spinal canal diameter and the pathological changes in the cervical spine. Eur Spine J 2009; 18 (06) 877-883
• 13 Nagata K, Yoshimura N, Hashizume H. , et al. The prevalence of cervical myelopathy among subjects with narrow cervical spinal canal in a population-based magnetic resonance imaging study: the Wakayama Spine Study. Spine J 2014; 14 (12) 2811-2817
• 14 Blackley HR, Plank LD, Robertson PA. Determining the sagittal dimensions of the canal of the cervical spine. The reliability of ratios of anatomical measurements. J Bone Joint Surg Br 1999; 81 (01) 110-112
• 15 Herzog RJ, Wiens JJ, Dillingham MF, Sontag MJ. Normal cervical spine morphometry and cervical spinal stenosis in asymptomatic professional football players. Plain film radiography, multiplanar computed tomography, and magnetic resonance imaging. Spine 1991; 16 (06) S178-S186
• 16 Prasad SS, O'Malley M, Caplan M, Shackleford IM, Pydisetty RK. MRI measurements of the cervical spine and their correlation to Pavlov's ratio. Spine 2003; 28 (12) 1263-1268
• 17 Nakashima H, Yukawa Y, Suda K, Yamagata M, Ueta T, Kato F. Narrow cervical canal in 1211 asymptomatic healthy subjects: the relationship with spinal cord compression on MRI. Eur Spine J 2016; 25 (07) 2149-2154
• 18 Hayashi H, Okada K, Hamada M, Tada K, Ueno R. Etiologic factors of myelopathy. A radiographic evaluation of the aging changes in the cervical spine. Clin Orthop Relat Res 1987; (214) 200-209
• 19 Inoue H, Ohmori K, Takatsu T, Teramoto T, Ishida Y, Suzuki K. Morphological analysis of the cervical spinal canal, dural tube and spinal cord in normal individuals using CT myelography. Neuroradiology 1996; 38 (02) 148-151
• 20 Kasai Y, Akeda K, Uchida A. Physical characteristics of patients with developmental cervical spinal canal stenosis. Eur Spine J 2007; 16 (07) 901-903
• 21 Kim G, Khalid F, Oommen VV. , et al. T1- vs. T2-based MRI measures of spinal cord volume in healthy subjects and patients with multiple sclerosis. BMC Neurol 2015; 15: 124
• 22 Ishikawa M, Matsumoto M, Fujimura Y, Chiba K, Toyama Y. Changes of cervical spinal cord and cervical spinal canal with age in asymptomatic subjects. Spinal Cord 2003; 41 (03) 159-163
• 23 Kameyama T, Hashizume Y, Ando T, Takahashi A. Morphometry of the normal cadaveric cervical spinal cord. Spine 1994; 19 (18) 2077-2081
• 24 Lee MJ, Cassinelli EH, Riew KD. Prevalence of cervical spine stenosis. Anatomic study in cadavers. J Bone Joint Surg Am 2007; 89 (02) 376-380
• 25 Yanase M, Matsuyama Y, Hirose K. , et al. Measurement of the cervical spinal cord volume on MRI. J Spinal Disord Tech 2006; 19 (02) 125-129
• 26 Sayıt E, Aghdasi B, Daubs MD, Wang JC. The occupancy of the components in the cervical spine and their changes with extension and flexion. Global Spine J 2015; 5 (05) 396-405
• 27 Rüegg TB, Wicki AG, Aebli N, Wisianowsky C, Krebs J. The diagnostic value of magnetic resonance imaging measurements for assessing cervical spinal canal stenosis. J Neurosurg Spine 2015; 22 (03) 230-236
• 28 Nouri A, Montejo J, Sun X. , et al. Cervical cord-canal mismatch: a new method for identifying predisposition to spinal cord injury. World Neurosurg 2017; 108: 112-117
• 29 Countee RW, Vijayanathan T. Congenital stenosis of the cervical spine: diagnosis and management. J Natl Med Assoc 1979; 71 (03) 257-264
• 30 Nouri A, Martin AR, Tetreault L. , et al. MRI analysis of the combined prospectively collected AOSpine North America and international data: the prevalence and spectrum of pathologies in a global cohort of patients with degenerative cervical myelopathy. Spine 2017; 42 (14) 1058-1067
• 31 Nouri A, Tetreault L, Nori S, Martin AR, Nater A, Fehlings MG. Congenital cervical spine stenosis in a multicenter global cohort of patients with degenerative cervical myelopathy: an ambispective report based on a magnetic resonance imaging diagnostic criterion. Neurosurgery 2018; 83 (03) 521-528
• 32 Presciutti SM, DeLuca P, Marchetto P, Wilsey JT, Shaffrey C, Vaccaro AR. Mean subaxial space available for the cord index as a novel method of measuring cervical spine geometry to predict the chronic stinger syndrome in American football players. J Neurosurg Spine 2009; 11 (03) 264-271
• 33 Tierney RT, Maldjian C, Mattacola CG, Straub SJ, Sitler MR. Cervical spine stenosis measures in normal subjects. J Athl Train 2002; 37 (02) 190-193
• 34 Ezra D, Masharawi Y, Salame K, Slon V, Alperovitch-Najenson D, Hershkovitz I. Demographic aspects in cervical vertebral bodies' size and shape (C3-C7): a skeletal study. Spine J 2017; 17 (01) 135-142
• 35 Stemper BD, Yoganandan N, Pintar FA. , et al. Anatomical gender differences in cervical vertebrae of size-matched volunteers. Spine 2008; 33 (02) E44-E49
• 36 Pashkova IG, Kosourov AK. Age dependent changes in cervical region of the spine according to data of nuclear magnetic tomography [in Russian]. Morfologiia 2004; 125 (01) 80-82
• 37 Boyle JW, Nikitov SA, Boardman AD, Booth JG, Booth K. Nonlinear self-channeling and beam shaping of magnetostatic waves in ferromagnetic films. Phys Rev B Condens Matter 1996; 53 (18) 12173-12181
• 38 Papp T, Porter RW, Craig CE, Aspden RM, Campbell DM. Significant antenatal factors in the development of lumbar spinal stenosis. Spine 1997; 22 (16) 1805-1810
• 39 Schizas C, Schmit A, Schizas A, Becce F, Kulik G, Pierzchała K. Secular changes of spinal canal dimensions in western Switzerland: a narrowing epidemic?. Spine 2014; 39 (17) 1339-1344
• 40 Griffith JF, Huang J, Law SW. , et al. Population reference range for developmental lumbar spinal canal size. Quant Imaging Med Surg 2016; 6 (06) 671-679
• 41 Wiley MR, Hee Jo C, Khaleel MA, McIntosh AL. Size matters: which adolescent patients are most likely to require surgical decompression for lumbar disk herniations?. J Pediatr Orthop 2019; 39 (10) e791-e795
• 42 Steurer J, Roner S, Gnannt R, Hodler J. LumbSten Research Collaboration. Quantitative radiologic criteria for the diagnosis of lumbar spinal stenosis: a systematic literature review. BMC Musculoskelet Disord 2011; 12: 175
• 43 Limthongkul W, Karaikovic EE, Savage JW, Markovic A. Volumetric analysis of thoracic and lumbar vertebral bodies. Spine J 2010; 10 (02) 153-158
• 44 Wilms GE, Willems E, Demaerel P, De Keyzer F. CT volumetry of lumbar vertebral bodies in patients with hypoplasia L5 and bilateral spondylolysis and in normal controls. Neuroradiology 2012; 54 (08) 839-843
• 45 Caula A, Metmer G, Havet E. Anthropometric approach to lumbar vertebral body volumes. Surg Radiol Anat 2016; 38 (03) 303-308
• 46 Griffith JF, Engelke K, Genant HK. Looking beyond bone mineral density : Imaging assessment of bone quality. Ann N Y Acad Sci 2010; 1192: 45-56
• 47 Löffler MT, Sollmann N, Mei K. , et al. X-ray-based quantitative osteoporosis imaging at the spine. Osteoporos Int 2020; 31 (02) 233-250
• 48 Adams JE. Quantitative computed tomography. Eur J Radiol 2009; 71 (03) 415-424
• 49 Roski F, Hammel J, Mei K. , et al. Bone mineral density measurements derived from dual-layer spectral CT enable opportunistic screening for osteoporosis. Eur Radiol 2019; 29 (11) 6355-6363
• 50 Sfeir JG, Drake MT, Atkinson EJ. , et al. Evaluation of cross-sectional and longitudinal changes in volumetric bone mineral density in postmenopausal women using single- versus dual-energy quantitative computed tomography. Bone 2018; 112: 145-152
• 51 Cheng X, Li K, Zhang Y. , et al. The accurate relationship between spine bone density and bone marrow in humans. Bone 2020; 134: 115312
• 52 Bredella MA, Daley SM, Kalra MK, Brown JK, Miller KK, Torriani M. Marrow adipose tissue quantification of the lumbar spine by using dual-energy CT and single-voxel (1)H MR spectroscopy: a feasibility study. Radiology 2015; 277 (01) 230-235
• 53 Ulano A, Bredella MA, Burke P. , et al. Distinguishing untreated osteoblastic metastases from enostoses using CT attenuation measurements. AJR Am J Roentgenol 2016; 207 (02) 362-368
• 54 Sala F, Dapoto A, Morzenti C. , et al. Bone islands incidentally detected on computed tomography: frequency of enostosis and differentiation from untreated osteoblastic metastases based on CT attenuation value. Br J Radiol 2019; 92 (1103): 20190249
• 55 Dieckmeyer M, Ruschke S, Cordes C. , et al. The need for T₂ correction on MRS-based vertebral bone marrow fat quantification: implications for bone marrow fat fraction age dependence. NMR Biomed 2015; 28 (04) 432-439
• 56 Kühn JP, Hernando D, Meffert PJ. , et al. Proton-density fat fraction and simultaneous R2* estimation as an MRI tool for assessment of osteoporosis. Eur Radiol 2013; 23 (12) 3432-3439
• 57 Zhang Y, Zhou Z, Wang C. , et al. Reliability of measuring the fat content of the lumbar vertebral marrow and paraspinal muscles using MRI mDIXON-Quant sequence. Diagn Interv Radiol 2018; 24 (05) 302-307
• 58 Karampinos DC, Baum T, Nardo L. , et al. Characterization of the regional distribution of skeletal muscle adipose tissue in type 2 diabetes using chemical shift-based water/fat separation. J Magn Reson Imaging 2012; 35 (04) 899-907
• 59 Bernard CP, Liney GP, Manton DJ, Turnbull LW, Langton CM. Comparison of fat quantification methods: a phantom study at 3.0T. J Magn Reson Imaging 2008; 27 (01) 192-197
• 60 Griffith JF, Yeung DK, Chow SK, Leung JC, Leung PC. Reproducibility of MR perfusion and (1)H spectroscopy of bone marrow. J Magn Reson Imaging 2009; 29 (06) 1438-1442
• 61 Baum T, Yap SP, Dieckmeyer M. , et al. Assessment of whole spine vertebral bone marrow fat using chemical shift-encoding based water-fat MRI. J Magn Reson Imaging 2015; 42 (04) 1018-1023
• 62 Sieron D, Drakopoulos D, Loebelenz LI. , et al. Correlation between fat signal ratio on T1-weighted MRI in the lower vertebral bodies and age, comparing 1.5-T and 3-T scanners. Acta Radiol Open 2020; 9 (01) 2058460120901517
• 63 Belavy DL, Quittner MJ, Ridgers ND, Shiekh A, Rantalainen T, Trudel G. Specific modulation of vertebral marrow adipose tissue by physical activity. J Bone Miner Res 2018; 33 (04) 651-657
• 64 Kugel H, Jung C, Schulte O, Heindel W. Age- and sex-specific differences in the 1H-spectrum of vertebral bone marrow. J Magn Reson Imaging 2001; 13 (02) 263-268
• 65 Duda SH, Laniado M, Schick F, Strayle M, Claussen CD. Normal bone marrow in the sacrum of young adults: differences between the sexes seen on chemical-shift MR imaging. AJR Am J Roentgenol 1995; 164 (04) 935-940
• 66 Griffith JF, Yeung DKW, Ma HT, Leung JC, Kwok TCY, Leung PC. Bone marrow fat content in the elderly: a reversal of sex difference seen in younger subjects. J Magn Reson Imaging 2012; 36 (01) 225-230
• 67 Griffith JF, Wang YX, Zhou H. , et al. Reduced bone perfusion in osteoporosis: likely causes in an ovariectomy rat model. Radiology 2010; 254 (03) 739-746
• 68 Griffith JF, Yeung DK, Ahuja AT. , et al. A study of bone marrow and subcutaneous fatty acid composition in subjects of varying bone mineral density. Bone 2009; 44 (06) 1092-1096
• 69 Griffith JF. Age-related changes in the bone marrow. Curr Radiol Rep 2017; 5: 24
• 70 Dunnill MS, Anderson JA, Whitehead R. Quantitative histological studies on age changes in bone. J Pathol Bacteriol 1967; 94 (02) 275-291
• 71 Griffith JF, Yeung DK, Antonio GE. , et al. Vertebral bone mineral density, marrow perfusion, and fat content in healthy men and men with osteoporosis: dynamic contrast-enhanced MR imaging and MR spectroscopy. Radiology 2005; 236 (03) 945-951
• 72 Griffith JF, Yeung DK, Antonio GE. , et al. Vertebral marrow fat content and diffusion and perfusion indexes in women with varying bone density: MR evaluation. Radiology 2006; 241 (03) 831-838
• 73 Li X, Shet K, Xu K, Rodríguez JP, Pino AM, Kurhanewicz J, Schwartz A, Rosen CJ. Unsaturation level decreased in bone marrow fat of postmenopausal women with low bone density using high resolution magic angle spinning (HRMAS) 1H NMR spectroscopy. Bone 2017; 105: 87-92
• 74 Griffith JF, Yeung DK, Leung JC, Kwok TC, Leung PC. Prediction of bone loss in elderly female subjects by MR perfusion imaging and spectroscopy. Eur Radiol 2011; 21 (06) 1160-1169
• 75 Woods GN, Ewing SK, Sigurdsson S. , et al. Greater bone marrow adiposity predicts bone loss in older women. J Bone Miner Res 2020; 35 (02) 326-332
• 76 Wehrli FW, Hopkins JA, Hwang SN, Song HK, Snyder PJ, Haddad JG. Cross-sectional study of osteopenia with quantitative MR imaging and bone densitometry. Radiology 2000; 217 (02) 527-538
• 77 Griffith JF. Identifying osteoporotic vertebral fracture. Quant Imaging Med Surg 2015; 5 (04) 592-602
• 78 Schmeel FC, Luetkens JA, Feißt A. , et al. Quantitative evaluation of T2* relaxation times for the differentiation of acute benign and malignant vertebral body fractures. Eur J Radiol 2018; 108: 59-65
• 79 Suh CH, Yun SJ, Jin W, Park SY, Ryu CW, Lee SH. Diagnostic performance of in-phase and opposed-phase chemical-shift imaging for differentiating benign and malignant vertebral marrow lesions: a meta-analysis. AJR Am J Roentgenol 2018; 211 (04) W188-W197
• 80 Yeung DK, Griffith JF, Antonio GE, Lee FK, Woo J, Leung PC. Osteoporosis is associated with increased marrow fat content and decreased marrow fat unsaturation: a proton MR spectroscopy study. J Magn Reson Imaging 2005; 22 (02) 279-285
• 81 Patsch JM, Li X, Baum T. , et al. Bone marrow fat composition as a novel imaging biomarker in postmenopausal women with prevalent fragility fractures. J Bone Miner Res 2013; 28 (08) 1721-1728
• 82 Chen WT, Ting-Fang Shih T, Hu CJ, Chen RC, Tu HY. Relationship between vertebral bone marrow blood perfusion and common carotid intima-media thickness in aging adults. J Magn Reson Imaging 2004; 20 (05) 811-816
• 83 Chen WT, Shih TT, Chen RC. , et al. Vertebral bone marrow perfusion evaluated with dynamic contrast-enhanced MR imaging: significance of aging and sex. Radiology 2001; 220 (01) 213-218
• 84 Montazel JL, Divine M, Lepage E, Kobeiter H, Breil S, Rahmouni A. Normal spinal bone marrow in adults: dynamic gadolinium-enhanced MR imaging. Radiology 2003; 229 (03) 703-709
• 85 Savvopoulou V, Maris TG, Vlahos L, Moulopoulos LA. Differences in perfusion parameters between upper and lower lumbar vertebral segments with dynamic contrast-enhanced MRI (DCE MRI). Eur Radiol 2008; 18 (09) 1876-1883
• 86 Hillengass J, Stieltjes B, Bäuerle T. , et al. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging of bone marrow in healthy individuals. Acta Radiol 2011; 52 (03) 324-330
• 87 Baur A, Stäbler A, Bartl R, Lamerz R, Scheidler J, Reiser M. MRI gadolinium enhancement of bone marrow: age-related changes in normals and in diffuse neoplastic infiltration. Skeletal Radiol 1997; 26 (07) 414-418
• 88 Griffith JF, Yeung DK, Tsang PH. , et al. Compromised bone marrow perfusion in osteoporosis. J Bone Miner Res 2008; 23 (07) 1068-1075
• 89 Wang YX, Griffith JF, Kwok AW. , et al. Reduced bone perfusion in proximal femur of subjects with decreased bone mineral density preferentially affects the femoral neck. Bone 2009; 45 (04) 711-715
• 90 Biffar A, Dietrich O, Sourbron S, Duerr HR, Reiser MF, Baur-Melnyk A. Diffusion and perfusion imaging of bone marrow. Eur J Radiol 2010; 76 (03) 323-328
• 91 Ward R, Caruthers S, Yablon C, Blake M, DiMasi M, Eustace S. Analysis of diffusion changes in posttraumatic bone marrow using navigator-corrected diffusion gradients. AJR Am J Roentgenol 2000; 174 (03) 731-734
• 92 Li X, Schwartz AV. MRI assessment of bone marrow composition in osteoporosis. Curr Osteoporos Rep 2020; 18 (01) 57-66
• 93 Jie H, Hao F, Na LX. Vertebral bone marrow diffusivity in healthy adults at 3T diffusion-weighted imaging. Acta Radiol 2016; 57 (10) 1238-1243
• 94 Herrmann J, Krstin N, Schoennagel BP. , et al. Age-related distribution of vertebral bone-marrow diffusivity. Eur J Radiol 2012; 81 (12) 4046-4049
• 95 Yeung DK, Wong SY, Griffith JF, Lau EM. Bone marrow diffusion in osteoporosis: evaluation with quantitative MR diffusion imaging. J Magn Reson Imaging 2004; 19 (02) 222-228
• 96 Nonomura Y, Yasumoto M, Yoshimura R. , et al. Relationship between bone marrow cellularity and apparent diffusion coefficient. J Magn Reson Imaging 2001; 13 (05) 757-760
• 97 Lasbleiz J, Le Ster C, Guillin R, Saint-Jalmes H, Gambarota G. Measurements of diffusion and perfusion in vertebral bone marrow using intravoxel incoherent motion (IVIM) with multishot, readout-segmented (RESOLVE) echo-planar imaging. J Magn Reson Imaging 2019; 49 (03) 768-776
• 98 Hatipoglu HG, Selvi A, Ciliz D, Yuksel E. Quantitative and diffusion MR imaging as a new method to assess osteoporosis. AJNR Am J Neuroradiol 2007; 28 (10) 1934-1937
• 99 Tang GY, Lv ZW, Tang RB. , et al. Evaluation of MR spectroscopy and diffusion-weighted MRI in detecting bone marrow changes in postmenopausal women with osteoporosis. Clin Radiol 2010; 65 (05) 377-381
• 100 Shih TT, Liu HC, Chang CJ, Wei SY, Shen LC, Yang PC. Correlation of MR lumbar spine bone marrow perfusion with bone mineral density in female subjects. Radiology 2004; 233 (01) 121-128
• 101 Blebea JS, Houseni M, Torigian DA. , et al. Structural and functional imaging of normal bone marrow and evaluation of its age-related changes. Semin Nucl Med 2007; 37 (03) 185-194
• 102 Basu S, Houseni M, Bural G. , et al. Magnetic resonance imaging based bone marrow segmentation for quantitative calculation of pure red marrow metabolism using 2-deoxy-2-[F-18]fluoro-D-glucose-positron emission tomography: a novel application with significant implications for combined structure-function approach. Mol Imaging Biol 2007; 9 (06) 361-365
• 103 Fan C, Hernandez-Pampaloni M, Houseni M. , et al. Age-related changes in the metabolic activity and distribution of the red marrow as demonstrated by 2-deoxy-2-[F-18]fluoro-D-glucose-positron emission tomography. Mol Imaging Biol 2007; 9 (05) 300-307
• 104 Derlin T, Janssen T, Salamon J. , et al. Age-related differences in the activity of arterial mineral deposition and regional bone metabolism: a 18F-sodium fluoride positron emission tomography study. Osteoporos Int 2015; 26 (01) 199-207
• 105 Kurata S, Shizukuishi K, Tateishi U. , et al. Age-related changes in pre- and postmenopausal women investigated with 18F-fluoride PET—a preliminary study. Skeletal Radiol 2012; 41 (08) 947-953
• 106 Griffith JF, Kumta SM, Huang Y. Hard arteries, weak bones. Skeletal Radiol 2011; 40 (05) 517-521
• 107 Sudhir G, Vignesh Jayabalan S, Gadde S, Venkatesh Kumar G, Karthik Kailash K. Analysis of factors influencing ligamentum flavum thickness in lumbar spine: a radiological study of 1070 disc levels in 214 patients. Clin Neurol Neurosurg 2019; 182: 19-24
• 108 Kwok AW, Wang YX, Griffith JF. , et al. Morphological changes of lumbar vertebral bodies and intervertebral discs associated with decrease in bone mineral density of the spine: a cross-sectional study in elderly subjects. Spine 2012; 37 (23) E1415-E1421
• 109 Tertti M, Paajanen H, Laato M, Aho H, Komu M, Kormano M. Disc degeneration in magnetic resonance imaging. A comparative biochemical, histologic, and radiologic study in cadaver spines. Spine 1991; 16 (06) 629-634
• 110 Marinelli NL, Haughton VM, Muñoz A, Anderson PA. T2 relaxation times of intervertebral disc tissue correlated with water content and proteoglycan content. Spine 2009; 34 (05) 520-524
• 111 Kerttula L, Kurunlahti M, Jauhiainen J, Koivula A, Oikarinen J, Tervonen O. Apparent diffusion coefficients and T2 relaxation time measurements to evaluate disc degeneration. A quantitative MR study of young patients with previous vertebral fracture. Acta Radiol 2001; 42 (06) 585-591
• 112 Boos N, Wallin A, Gbedegbegnon T, Aebi M, Boesch C. Quantitative MR imaging of lumbar intervertebral disks and vertebral bodies: influence of diurnal water content variations. Radiology 1993; 188 (02) 351-354
• 113 Marinelli NL, Haughton VM, Anderson PA. T2 relaxation times correlated with stage of lumbar intervertebral disk degeneration and patient age. AJNR Am J Neuroradiol 2010; 31 (07) 1278-1282
• 114 Ogon I, Takebayashi T, Takashima H. , et al. Analysis of chronic low back pain with magnetic resonance imaging T2 mapping of lumbar intervertebral disc. J Orthop Sci 2015; 20 (02) 295-301
• 115 Mok GSP, Zhang D, Chen SZ, Yuan J, Griffith JF, Wang YXJ. Comparison of three approaches for defining nucleus pulposus and annulus fibrosus on sagittal magnetic resonance images of the lumbar spine. J Orthop Translat 2016; 6: 34-41
• 116 Wáng YX. Towards consistency for magnetic resonance (MR) relaxometry of lumbar intervertebral discs. Quant Imaging Med Surg 2016; 6 (04) 474-477
• 117 Altinkaya N, Yildirim T, Demir S, Alkan O, Sarica FB. Factors associated with the thickness of the ligamentum flavum: is ligamentum flavum thickening due to hypertrophy or buckling?. Spine 2011; 36 (16) E1093-E1097
• 118 Rahmani MS, Terai H, Akhgar J. , et al. Anatomical analysis of human ligamentum flavum in the cervical spine: Special consideration to the attachments, coverage, and lateral extent. J Orthop Sci 2017; 22 (06) 994-1000
• 119 Chelladurai A, Balasubramaniam S, Anbazhagan SP, Gnanasihamani S, Ramaswami S. Dorsal spinal ligamentum flavum thickening: a magnetic resonance imaging study. Asian Spine J 2018; 12 (01) 47-51
• 120 Munns JJ, Lee JY, Espinoza Orías AA. , et al. Ligamentum flavum hypertrophy in asymptomatic and chronic low back pain subjects. PLOS One 2015; 10 (05) e0128321
• 121 Kolte VS, Khambatta S, Ambiye MV. Thickness of the ligamentum flavum: correlation with age and its asymmetry—an magnetic resonance imaging study. Asian Spine J 2015; 9 (02) 245-253
• 122 Morimoto M, Higashino K, Manabe H. , et al. Age-related changes in axial and sagittal orientation of the facet joints: Comparison with changes in degenerative spondylolisthesis. J Orthop Sci 2019; 24 (01) 50-56