Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning.

Journal: Bone
PMID: 36958542

Abstract

BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent of bone mineral density (BMD). Ultrashort echo time (UTE) MRI techniques of measuring cortical bone porosity and geometry have been extensively validated in preclinical studies and have recently been shown to detect impaired bone quality in vivo in patients with osteoporosis. However, these techniques rely on laborious image segmentation, which is clinically impractical. Additionally, UTE MRI porosity techniques typically require long scan times or external calibration samples and elaborate physics processing, which limit their translatability. To this end, the UTE MRI-derived Suppression Ratio has been proposed as a simple-to-calculate, reference-free biomarker of porosity which can be acquired in clinically feasible acquisition times.

Authors

  • Brandon C Jones
    Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.
  • Felix W Wehrli
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Founders Building, 3400 Spruce St, Philadelphia, PA 19104, United States of America. Electronic address: felix.wehrli@pennmedicine.upenn.edu.
  • Nada Kamona
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Founders Building, 3400 Spruce St, Philadelphia, PA 19104, United States of America; Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, 210 South 33(rd) St, Philadelphia, PA 19104, United States of America. Electronic address: nkamona@seas.upenn.edu.
  • Rajiv S Deshpande
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Founders Building, 3400 Spruce St, Philadelphia, PA 19104, United States of America; Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, 210 South 33(rd) St, Philadelphia, PA 19104, United States of America. Electronic address: rajiv.deshpande@pennmedicine.upenn.edu.
  • Brian-Tinh Duc Vu
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Founders Building, 3400 Spruce St, Philadelphia, PA 19104, United States of America; Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, 210 South 33(rd) St, Philadelphia, PA 19104, United States of America. Electronic address: brian-tinh.vu@pennmedicine.upenn.edu.
  • Hee Kwon Song
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
  • Hyunyeol Lee
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Founders Building, 3400 Spruce St, Philadelphia, PA 19104, United States of America; School of Electronics Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 41566, Republic of Korea. Electronic address: hyunyeollee@knu.ac.kr.
  • Rasleen Kaur Grewal
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Founders Building, 3400 Spruce St, Philadelphia, PA 19104, United States of America. Electronic address: rasleen.grewal@pennmedicine.upenn.edu.
  • Trevor Jackson Chan
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Founders Building, 3400 Spruce St, Philadelphia, PA 19104, United States of America; Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, 210 South 33(rd) St, Philadelphia, PA 19104, United States of America. Electronic address: trevor.chan@pennmedicine.upenn.edu.
  • Walter R Witschey
    Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, USA.
  • Matthew T MacLean
    Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
  • Nicholas J Josselyn
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Founders Building, 3400 Spruce St, Philadelphia, PA 19104, United States of America; Department of Data Science, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, United States of America. Electronic address: njjosselyn@wpi.edu.
  • Srikant Kamesh Iyer
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Founders Building, 3400 Spruce St, Philadelphia, PA 19104, United States of America.
  • Mona Al Mukaddam
    Department of Medicine, Division of Endocrinology, Perelman School of Medicine, University of Pennsylvania, Perelman Center for Advanced Medicine, 3400 Civic Center Boulevard, Philadelphia, PA 19104, United States of America. Electronic address: mona.almukaddam@pennmedicine.upenn.edu.
  • Peter J Snyder
    Department of Medicine, Division of Endocrinology, Perelman School of Medicine, University of Pennsylvania, Perelman Center for Advanced Medicine, 3400 Civic Center Boulevard, Philadelphia, PA 19104, United States of America. Electronic address: pjs@pennmedicine.upenn.edu.
  • Chamith S Rajapakse
    University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA.

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