Shekhar S Chandra1, Rachel Surowiec2, Charles Ho2, Ying Xia1,3, Craig Engstrom4, Stuart Crozier1, Jurgen Fripp3. 1. School of Information Technology and Electrical Engineering, University of Queensland, Australia. 2. Steadman Philippon Research Institute (SPRI), Colorado, USA. 3. Australian e-Health Research Centre, CSIRO Computational Informatics, Australia. 4. School of Human Movement Studies, University of Queensland, Australia.
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% (100 × 2|A∩M|/[|A|+|M|]). 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.
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% (100 × 2|A∩M|/[|A|+|M|]). 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.
Authors: Leon Lenchik; Laura Heacock; Ashley A Weaver; Robert D Boutin; Tessa S Cook; Jason Itri; Christopher G Filippi; Rao P Gullapalli; James Lee; Marianna Zagurovskaya; Tara Retson; Kendra Godwin; Joey Nicholson; Ponnada A Narayana Journal: Acad Radiol Date: 2019-08-10 Impact factor: 3.173
Authors: Florian Schmaranzer; Ronja Helfenstein; Guodong Zeng; Till D Lerch; Eduardo N Novais; James D Wylie; Young-Jo Kim; Klaus A Siebenrock; Moritz Tannast; Guoyan Zheng Journal: Clin Orthop Relat Res Date: 2019-05 Impact factor: 4.176
Authors: Adrian C Ruckli; Florian Schmaranzer; Malin K Meier; Till D Lerch; Simon D Steppacher; Moritz Tannast; Guodong Zeng; Jürgen Burger; Klaus A Siebenrock; Nicolas Gerber; Kate Gerber Journal: Int J Comput Assist Radiol Surg Date: 2022-08-17 Impact factor: 3.421