Volume 75, Issue 1 pp. 403-413
Full Paper

Automated analysis of hip joint cartilage combining MR T2 and three-dimensional fast-spin-echo images

Shekhar S. Chandra

Corresponding Author

Shekhar S. Chandra

School of Information Technology and Electrical Engineering, University of Queensland, Australia

Correspondence to: Shekhar S. Chandra, B.Sc (Hons), Ph.D, School of Information Technology and Electrical Engineering at the University of Queensland, St. Lucia, Queensland 4072, Australia. E-mail: [email protected], Twitter handle: @shakes76Search for more papers by this author
Rachel Surowiec

Rachel Surowiec

Steadman Philippon Research Institute (SPRI), Colorado, USA

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Charles Ho

Charles Ho

Steadman Philippon Research Institute (SPRI), Colorado, USA

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Ying Xia

Ying Xia

School of Information Technology and Electrical Engineering, University of Queensland, Australia

Australian e-Health Research Centre, CSIRO Computational Informatics, Australia

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Craig Engstrom

Craig Engstrom

School of Human Movement Studies, University of Queensland, Australia

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Stuart Crozier

Stuart Crozier

School of Information Technology and Electrical Engineering, University of Queensland, Australia

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Jurgen Fripp

Jurgen Fripp

Australian e-Health Research Centre, CSIRO Computational Informatics, Australia

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First published: 30 January 2015
Citations: 13

Correction added after online publication 13 April 2015. The authors have updated Figure 1 to correct the anterior/posterior labeling for the femur and acetabulum.

Abstract

Purpose

To validate a fully automated scheme to extract biochemical information from the hip joint cartilages using MR T2 mapping images incorporating segmentation of co-registered three-dimensional Fast-Spin-Echo (3D-SPACE) images.

Methods

Manual analyses of unilateral hip (3 Tesla) MR images of 24 asymptomatic volunteers were used to validate a 3D deformable model method for automated cartilage segmentation of SPACE scans, partitioning of the individual femoral and acetabular cartilage plates into clinically defined sub-regions and propagating these results to T2 maps to calculate region-wise T2 value statistics. Analyses were completed on a desktop computer (∼10 min per case).

Results

The mean voxel overlap between automated A and manual M segmentations of the cartilage volumes in the (clinically based) SPACE images was 73% urn:x-wiley:07403194:media:mrm25598:mrm25598-math-0001. The automated and manual analyses demonstrated a relative difference error <10% in the median “T2 average signal” for each cartilage plate. The automated and manual analyses showed consistent patterns between significant differences in T2 data across the hip cartilage sub-regions.

Conclusion

The good agreement between the manual and automatic analyses of T2 values indicates the use of structural 3D-SPACE MR images with the proposed method provides a promising approach for automated quantitative T2 assessment of hip joint cartilages. Magn Reson Med 75:403–413, 2016. © 2015 Wiley Periodicals, Inc.

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