Literature DB >> 8628883

Articular cartilage volume in the knee: semiautomated determination from three-dimensional reformations of MR images.

M A Piplani1, D G Disler, T R McCauley, T J Holmes, J P Cousins.   

Abstract

PURPOSE: To determine the accuracy of semiautomated quantification of articular cartilage volume from three-dimensional (3D) reformations of magnetic resonance (MR) images.
MATERIALS AND METHODS: Sagittal, fat-suppressed, 3D, spoiled gradient-recalled-echo MR imaging of two bovine and two human cadaver knees was performed. Articular cartilage volume was calculated from 3D reformations of the MR images by using a semiautomated program written at the authors' institution. Calculated volumes were compared with directly measured volumes of the surgically removed articular cartilage.
RESULTS: The percentage of error of the MR imaging-determined volumes was 6.53% +/- 4.75 (mean +/- standard deviation). A strong correlation between the two sets of observations was shown (r=.997). Linear regression showed the calculated volumes to be highly accurate (slope=1.002, P>.25). Repeated reformations yielded volumes that were reproducible (mean absolute error, 0.013 mL +/- 0.019) and not significantly different from the measured volume (P>.10).
CONCLUSION: Semiautomated quantification of knee articular cartilage from MR images yields highly accurate cartilage volumes.

Entities:  

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Year:  1996        PMID: 8628883     DOI: 10.1148/radiology.198.3.8628883

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  14 in total

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2.  Intra- and inter-observer reproducibility of volume measurement of knee cartilage segmented from the OAI MR image set using a novel semi-automated segmentation method.

Authors:  K T Bae; H Shim; C Tao; S Chang; J H Wang; R Boudreau; C K Kwoh
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5.  Diseased Region Detection of Longitudinal Knee Magnetic Resonance Imaging Data.

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8.  Quantitative cartilage volume measurement using MRI: comparison of different evaluation techniques.

Authors:  Adel Maataoui; Heiko Graichen; Nasreddin D Abolmaali; Mohammad F Khan; Jessen Gurung; Ralf Straub; Jun Qian; Stefan Hinterwimmer; Hanns Ackermann; Thomas J Vogl
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9.  Automated image processing and analysis of cartilage MRI: enabling technology for data mining applied to osteoarthritis.

Authors:  Hussain Z Tameem; Usha S Sinha
Journal:  AIP Conf Proc       Date:  2007

10.  Deep learning-based fully automatic segmentation of wrist cartilage in MR images.

Authors:  Ekaterina Brui; Aleksandr Y Efimtcev; Vladimir A Fokin; Remi Fernandez; Anatoliy G Levchuk; Augustin C Ogier; Alexey A Samsonov; Jean P Mattei; Irina V Melchakova; David Bendahan; Anna Andreychenko
Journal:  NMR Biomed       Date:  2020-05-11       Impact factor: 4.044

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