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Tarsal and Metatarsal Bone Mineral Density Measurement Using Volumetric Quantitative Computed Tomography

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Abstract

A new method for measuring bone mineral density (BMD) of the tarsal and metatarsals is described using volumetric quantitative computed tomography (VQCT) in subjects with diabetes mellitus and peripheral neuropathy. VQCT images of a single foot were acquired twice from eight subjects (mean age 51 [11 SD], seven males, one female). The cortical shells of the seven tarsal and five metatarsal bones were identified and semiautomatically segmented from adjacent bones. Volume and BMD of each bone were measured separately from the two acquired scans for each subject. Whole-bone semiautomatic segmentation measurement errors were determined as the root mean square coefficient of variation for the volume and BMD of 0.8% and 0.9%, respectively. In addition to the whole-bone segmentation methods, we performed atlas-based partitioning of subregions within the second metatarsal for all subjects, from which the volumes and BMDs were obtained for each subregion. The subregion measurement BMD errors (root mean square coefficient of variation) within the shaft, proximal end, and distal end were shown to vary by approximately 1% between the two scans of each subject. The new methods demonstrated large variations in BMDs between the 12 bones of the foot within a subject and between subjects, and between subregions within the second metatarsal. These methods can provide an important outcome measure for clinical research trials investigating the effects of interventions, aging, or disease progression on bone loss, or gain, in individual foot bones.

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References

  1. http://www.fda.gov/oc/initiatives/criticalpath/whitepaper.html. U.S. Food and Drug Administration. Accessed 18 February 2008

  2. Biomarkers definitions working group: Commentary: Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 69(3):89–95, 2001

    Article  Google Scholar 

  3. Prior F, Commean PK, Ju T, Hastings MK, Hildebolt CF, Sinacore DR: Developing a biomarker for neuropathic arthropathy in diabetic patients. 2007 IEEE/NIH Life Science Systems and Applications Workshop (LISSA 2007)

  4. Bonnick SL: Bone Densitometry in Clinical Practice, Totowa, NJ: Humana Press, 2004

    Google Scholar 

  5. Genant HK, Engelke K, Fuerst T, et al: Noninvasive assessment of bone mineral and structure: state of the art. J Bone Miner Res 11:707–730, 1996

    PubMed  CAS  Google Scholar 

  6. Njeh CF, Genant HK: Bone loss: quantitative imaging techniques for assessing bone mass in rheumatoid arthritis. Arthritis Res 2(6):446–450, 2000

    Article  PubMed  CAS  Google Scholar 

  7. Jergas M, Breitenseher M, Gluer CC, Yu W, Genant HK: Estimates of volumetric bone density from projectional measurements improve the discriminatory capability of dual X-ray absorptiometry. J Bone Miner Res 10:1101–1110, 1995

    PubMed  CAS  Google Scholar 

  8. Lang TF, Li J, Harris ST, Genant HK: Assessment of vertebral bone mineral density using volumetric quantitative CT. J Comput Assist Tomogr 23(1):130–7, 1999

    Article  PubMed  CAS  Google Scholar 

  9. Mastmeyer A, Engelke K, Fuchs C, Kalender WA: A hierarchical 3D segmentation method and the definition of vertebral body coordinate systems for QCT of the lumbar spine. Med Image Anal 10(4):560–77, 2006

    Article  PubMed  Google Scholar 

  10. Kang Y, Engelke K, Fuchs C, Kalender WA: An anatomic coordinate system of the femoral neck for highly reproducible BMD measurements using 3D QCT. Comput Med Imaging Graph 29(7):533–41, 2005

    Article  PubMed  Google Scholar 

  11. Ju T, Warren J, Eichele G, Thaller C, Chiu W, Carson J: A geometry database for gene expression data. In: Proceedings of Eurographics Symposium on Geometry Processing, pages 166–176, 2003

  12. Fabrin J, Larsen K, Hostein PE: Long-term follow-up in diabetic Charcot feet with spontaneous onset. Diabetes Care 23(6):796–800, 2000

    Article  PubMed  CAS  Google Scholar 

  13. Diamond JE, Mueller MJ, Delitto A, Sinacore DR: Reliability of a diabetic foot evaluation. Phys Ther 69:797–802, 1989

    PubMed  CAS  Google Scholar 

  14. Lott DJ, Hastings MK, Commean PK, Smith KE, Mueller MJ: Effect of footwear and orthotic devices on stress reduction and soft tissue strain of the neuropathic foot. Clin Biomech 22(3):352–359, 2007

    Article  Google Scholar 

  15. Commean PK, Mueller MJ, Smith KE, et al: Reliability and validity of combined imaging and pressures assessment methods for diabetic feet. Arch Phys Med Rehabil 83:497–505, 2002

    Article  PubMed  Google Scholar 

  16. Mueller MJ, Smith KE, Commean PK, Robertson DD, Johnson JE: Use of computed tomography and plantar pressure measurement for management of neuropathic ulcers in patients with diabetes. Phys Ther 79:296–307, 1999

    PubMed  CAS  Google Scholar 

  17. Robb RA, Hanson DP, Karwoski RA, Larson AG, Workman EL, Stacy MC: Analyze: a comprehensive, operator-interactive software package for multidimensional medical image display and analysis. Comput Med Imaging Graph 13:433–454, 1989

    Article  PubMed  CAS  Google Scholar 

  18. Robb RA: Three Dimensional Biomedical Imaging: Principles and Practice, New York: VCH Publishers, 1995

    Google Scholar 

  19. Fu KS, Mui JK: A survey on image segmentation. Pattern Recogn 13:3–16, 1981

    Article  Google Scholar 

  20. Zijdenbos AP, Dawant BM: Brain segmentation and white matter lesion detection in MR images. Crit Rev Biomed Eng 22:401–465, 1994

    PubMed  CAS  Google Scholar 

  21. Sonka M, Fitzpatrick JM: Handbook of Medical Imaging: Medical Image Processing and Analysis. In (vol 2). Bellingham, WA: SPIE (The International Society for Optical Engineering), 2000

  22. Russ JC: The Image Processing Handbook, 2nd Edition, Boca Raton, FL: CRC Press, 1995

    Google Scholar 

  23. Girish V, Vijayalakshmi A: (http://rsb.info.nih.gov/ij/) Affordable image analysis using NIH Image/ImageJ. Indian J Cancer 41(1):47, 2004

    PubMed  CAS  Google Scholar 

  24. Hohne KH, Hanson WA: Interactive 3D segmentation of MRI and CT volumes using morphological operations. J Comput Assist Tomogr 16:285–294, 1992

    Article  PubMed  CAS  Google Scholar 

  25. Kalender WA, Klotz E, Suss C: Vertebral bone mineral analysis: an integrated approach with CT. Radiology 164:19–23, 1987

    Google Scholar 

  26. Burroughs KE, Reimer CD, Fields KB: Lisfranc injury of the foot: a commonly missed diagnosis. Am Fam Physician 58:118–24, 1998

    PubMed  CAS  Google Scholar 

  27. Robertson DD, Mueller MJ, Smith KE, Commean PK, Pilgram T, Johnson J: Forefoot structural change in individuals with diabetes and prior plantar ulcer. J Bone Jt Surg Am vol. (ed), 84–A(8):1395–1404, 2002

    Google Scholar 

  28. Schaefer S, Hakenberg J, Warren J: Smooth subdivision of tetrahedral meshes. In Proceedings of Eurographics Symposium on Geometry Processing, 2004, pages 151–158

  29. Garland M, Heckbert P: Surface Simplification Using Quadric Error Metrics. Proceedings of SIGGRAPH 97, 1997, pp. 209–216

  30. Shewchuk JR: Tetrahedral mesh generation by Delaunay refinement. In SCG’98: Proceedings of the fourteenth annual symposium on Computational geometry. ACM Press, New York, NY, USA, 1998, pages 86–95

  31. Gluer CC, Blake G, Lu Y, Blunt BA, Jergas M, Genant HK: Accurate assessment of precision errors: how to measure the reproducibility of bone densitometry techniques. Osteoporos Int 5(4):262–270, 1995

    Article  PubMed  CAS  Google Scholar 

  32. Armstrong DG, Todd WF, Lavery LA, et al: The natural history of acute Charcot’s arthropathy in a diabetic foot specialty clinic. J Am Podiatr Med Assoc 87(6):272–278, 1997

    PubMed  CAS  Google Scholar 

  33. Schartz AV, Sellmeyer DE, Ensrud KE, et al: Older women with diabetes have an increased risk of fracture: a prospective study. J Clin Endocrinol Metab 86(1):32–38, 2001

    Article  Google Scholar 

  34. Hasselman CT, Vogt MT, Stone KL, Cauley JA, Conti SF: Foot and ankle fractures in elderly white women: Incidence and risk factors. J Bone Jt Surg 85:820–824, 2003

    Google Scholar 

  35. Rosenthal DI, Ganott MA, Wyshak G, Slovik DM, Doppelt SH, Neer RM: Quantitative computed tomography for spinal density measurement. Factors affecting precision. Invest Radiol 20:306–310, 1985

    Article  PubMed  CAS  Google Scholar 

  36. Graves VB, Wimmer R: Long-term reproducibility of quantitative computed tomography vertebral mineral measurements. J Comput Tomogr 9:73–76, 1985

    Article  PubMed  CAS  Google Scholar 

  37. Pouilles JM, Tremollieres F, Todorovsky N, Ribot C: Precision and sensitivity of dual-energy x-ray absorptiometry in spinal osteoporosis. J Bone Miner Res 6:997–1002, 1991

    Article  PubMed  CAS  Google Scholar 

  38. Lees B, Stevenson JC: An evaluation of dual-energy X-ray absorptiometry and comparison with dual-photon absorptiometry. Osteoporos Int 2:146–152, 1992

    Article  PubMed  CAS  Google Scholar 

  39. Cann CE: Quantitative CT for determination of bone mineral density: a review. Radiology 166:509–522, 1988

    PubMed  CAS  Google Scholar 

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Acknowledgments

We would like to thank Dr. Fred W. Prior for his collaborative support of this project. We would also like to thank Ryan Goldberg for his repeated measurements of the eight subjects with diabetes and peripheral neuropathy. Funding was provided by the National Institutes of Health, National Center of Medical Rehabilitation and Research (RO1 HD36895) and National Institute of Diabetes and Digestive and Kidney Diseases (R21 DK079457). The authors acknowledge the Prevention and Control Research Core of the Washington University Diabetes Research and Training Center (P60 DK20579) for their assistance in subject recruitment. We thank Richard Robb and his associates of the Mayo Biomedical Imaging Resource, Rochester, MN, for providing the Analyze software.

This study was supported by the National Center for Medical Rehabilitation Research and National Institute of Diabetes and Digestive and Kidney Diseases and the National Institutes of Health Grants.

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Authors and Affiliations

  1. Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue., Campus Box 8131, St. Louis, MO, 63110, USA

    Paul K. Commean

  2. Department of Computer Science and Engineering, Washington University, One Brookings Drive, St. Louis, MO, 63130, USA

    Tao Ju & Lu Liu

  3. Program in Physical Therapy, Washington University School of Medicine, Campus Box 8502, 4444 Forest Park Blvd., St. Louis, MO, 63108-2212, USA

    David R. Sinacore, Mary K. Hastings & Michael J. Mueller

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  1. Paul K. Commean
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  2. Tao Ju
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  4. David R. Sinacore
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  5. Mary K. Hastings
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  6. Michael J. Mueller
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Correspondence to Paul K. Commean.

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Commean, P.K., Ju, T., Liu, L. et al. Tarsal and Metatarsal Bone Mineral Density Measurement Using Volumetric Quantitative Computed Tomography. J Digit Imaging 22, 492–502 (2009). https://doi.org/10.1007/s10278-008-9118-z

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  • DOI: https://doi.org/10.1007/s10278-008-9118-z

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