Development of a fully automatic shape model matching (FASMM) system to derive statistical shape models from radiographs: application to the accurate capture and global representation of proximal femur shape
To evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal femur from non-standardised anteroposterior (AP) pelvic radiographs. AP pelvic radiographs obtained with informed consent and appropriate ethica...
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Published in | Osteoarthritis and cartilage Vol. 21; no. 10; pp. 1537 - 1544 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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England
Elsevier Ltd
01.10.2013
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Abstract | To evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal femur from non-standardised anteroposterior (AP) pelvic radiographs.
AP pelvic radiographs obtained with informed consent and appropriate ethical approval were available for 1105 subjects with unilateral hip osteoarthritis (OA) who had been recruited previously for The arcOGEN Study. The FASMM system was applied to capture the shape of the unaffected (i.e., without signs of radiographic OA) proximal femur from these radiographs. The accuracy and sensitivity of the FASMM system in calculating geometric measurements of the proximal femur and in shape representation were evaluated relative to validated manual methods.
De novo application of the FASMM system had a mean point-to-curve error of less than 0.9 mm in 99% of images (n = 266). Geometric measurements generated by the FASMM system were as accurate as those obtained manually. The analysis of the SSMs generated by the FASMM system for male and female subject groups identified more significant differences (in five of 17 SSM modes after Bonferroni adjustment) in their global proximal femur shape than those obtained from the analysis of conventional geometric measurements. Multivariate gender-classification accuracy was higher when using SSM mode values (76.3%) than when using conventional hip geometric measurements (71.8%).
The FASMM system rapidly and accurately generates a global SSM of the proximal femur from radiographs of varying quality and resolution. This system will facilitate complex morphometric analysis of global shape variation across large datasets. The FASMM system could be adapted to generate SSMs from the radiographs of other skeletal structures such as the hand, knee or pelvis. |
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AbstractList | To evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal femur from non-standardised anteroposterior (AP) pelvic radiographs.
AP pelvic radiographs obtained with informed consent and appropriate ethical approval were available for 1105 subjects with unilateral hip osteoarthritis (OA) who had been recruited previously for The arcOGEN Study. The FASMM system was applied to capture the shape of the unaffected (i.e., without signs of radiographic OA) proximal femur from these radiographs. The accuracy and sensitivity of the FASMM system in calculating geometric measurements of the proximal femur and in shape representation were evaluated relative to validated manual methods.
De novo application of the FASMM system had a mean point-to-curve error of less than 0.9 mm in 99% of images (n = 266). Geometric measurements generated by the FASMM system were as accurate as those obtained manually. The analysis of the SSMs generated by the FASMM system for male and female subject groups identified more significant differences (in five of 17 SSM modes after Bonferroni adjustment) in their global proximal femur shape than those obtained from the analysis of conventional geometric measurements. Multivariate gender-classification accuracy was higher when using SSM mode values (76.3%) than when using conventional hip geometric measurements (71.8%).
The FASMM system rapidly and accurately generates a global SSM of the proximal femur from radiographs of varying quality and resolution. This system will facilitate complex morphometric analysis of global shape variation across large datasets. The FASMM system could be adapted to generate SSMs from the radiographs of other skeletal structures such as the hand, knee or pelvis. To evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal femur from non-standardised anteroposterior (AP) pelvic radiographs.OBJECTIVETo evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal femur from non-standardised anteroposterior (AP) pelvic radiographs.AP pelvic radiographs obtained with informed consent and appropriate ethical approval were available for 1105 subjects with unilateral hip osteoarthritis (OA) who had been recruited previously for The arcOGEN Study. The FASMM system was applied to capture the shape of the unaffected (i.e., without signs of radiographic OA) proximal femur from these radiographs. The accuracy and sensitivity of the FASMM system in calculating geometric measurements of the proximal femur and in shape representation were evaluated relative to validated manual methods.DESIGNAP pelvic radiographs obtained with informed consent and appropriate ethical approval were available for 1105 subjects with unilateral hip osteoarthritis (OA) who had been recruited previously for The arcOGEN Study. The FASMM system was applied to capture the shape of the unaffected (i.e., without signs of radiographic OA) proximal femur from these radiographs. The accuracy and sensitivity of the FASMM system in calculating geometric measurements of the proximal femur and in shape representation were evaluated relative to validated manual methods.De novo application of the FASMM system had a mean point-to-curve error of less than 0.9 mm in 99% of images (n = 266). Geometric measurements generated by the FASMM system were as accurate as those obtained manually. The analysis of the SSMs generated by the FASMM system for male and female subject groups identified more significant differences (in five of 17 SSM modes after Bonferroni adjustment) in their global proximal femur shape than those obtained from the analysis of conventional geometric measurements. Multivariate gender-classification accuracy was higher when using SSM mode values (76.3%) than when using conventional hip geometric measurements (71.8%).RESULTSDe novo application of the FASMM system had a mean point-to-curve error of less than 0.9 mm in 99% of images (n = 266). Geometric measurements generated by the FASMM system were as accurate as those obtained manually. The analysis of the SSMs generated by the FASMM system for male and female subject groups identified more significant differences (in five of 17 SSM modes after Bonferroni adjustment) in their global proximal femur shape than those obtained from the analysis of conventional geometric measurements. Multivariate gender-classification accuracy was higher when using SSM mode values (76.3%) than when using conventional hip geometric measurements (71.8%).The FASMM system rapidly and accurately generates a global SSM of the proximal femur from radiographs of varying quality and resolution. This system will facilitate complex morphometric analysis of global shape variation across large datasets. The FASMM system could be adapted to generate SSMs from the radiographs of other skeletal structures such as the hand, knee or pelvis.CONCLUSIONSThe FASMM system rapidly and accurately generates a global SSM of the proximal femur from radiographs of varying quality and resolution. This system will facilitate complex morphometric analysis of global shape variation across large datasets. The FASMM system could be adapted to generate SSMs from the radiographs of other skeletal structures such as the hand, knee or pelvis. Summary Objective To evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal femur from non-standardised anteroposterior (AP) pelvic radiographs. Design AP pelvic radiographs obtained with informed consent and appropriate ethical approval were available for 1105 subjects with unilateral hip osteoarthritis (OA) who had been recruited previously for The arcOGEN Study. The FASMM system was applied to capture the shape of the unaffected (i.e., without signs of radiographic OA) proximal femur from these radiographs. The accuracy and sensitivity of the FASMM system in calculating geometric measurements of the proximal femur and in shape representation were evaluated relative to validated manual methods. Results De novo application of the FASMM system had a mean point-to-curve error of less than 0.9 mm in 99% of images ( n = 266). Geometric measurements generated by the FASMM system were as accurate as those obtained manually. The analysis of the SSMs generated by the FASMM system for male and female subject groups identified more significant differences (in five of 17 SSM modes after Bonferroni adjustment) in their global proximal femur shape than those obtained from the analysis of conventional geometric measurements. Multivariate gender-classification accuracy was higher when using SSM mode values (76.3%) than when using conventional hip geometric measurements (71.8%). Conclusions The FASMM system rapidly and accurately generates a global SSM of the proximal femur from radiographs of varying quality and resolution. This system will facilitate complex morphometric analysis of global shape variation across large datasets. The FASMM system could be adapted to generate SSMs from the radiographs of other skeletal structures such as the hand, knee or pelvis. |
Author | Cootes, T.F. Thiagarajah, S. Lindner, C. Wilkinson, J.M. Wallis, G.A. |
Author_xml | – sequence: 1 givenname: C. surname: Lindner fullname: Lindner, C. email: claudia.lindner@postgrad.manchester.ac.uk organization: Imaging Sciences, The University of Manchester, Manchester, UK – sequence: 2 givenname: S. surname: Thiagarajah fullname: Thiagarajah, S. organization: Department of Human Metabolism, The University of Sheffield, Sheffield, UK – sequence: 3 givenname: J.M. surname: Wilkinson fullname: Wilkinson, J.M. organization: Department of Human Metabolism, The University of Sheffield, Sheffield, UK – sequence: 4 givenname: G.A. surname: Wallis fullname: Wallis, G.A. organization: Wellcome Trust Centre for Cell Matrix Research, The University of Manchester, Manchester, UK – sequence: 5 givenname: T.F. surname: Cootes fullname: Cootes, T.F. organization: Imaging Sciences, The University of Manchester, Manchester, UK |
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CitedBy_id | crossref_primary_10_1016_j_bone_2021_116146 crossref_primary_10_3389_fbioe_2024_1250095 crossref_primary_10_1016_j_joca_2020_12_003 crossref_primary_10_11124_JBIES_22_00175 crossref_primary_10_1002_jor_25761 crossref_primary_10_1111_joa_12900 crossref_primary_10_1016_j_bone_2014_01_003 crossref_primary_10_1002_art_39186 crossref_primary_10_1007_s40674_018_0096_0 crossref_primary_10_1002_mrm_25598 crossref_primary_10_1186_s12891_022_05603_3 crossref_primary_10_12688_wellcomeopenres_16656_1 crossref_primary_10_1148_radiol_211057 crossref_primary_10_12688_wellcomeopenres_16656_2 crossref_primary_10_1016_j_ocarto_2022_100275 crossref_primary_10_1080_17453674_2020_1779516 crossref_primary_10_1093_rheumatology_kev232 crossref_primary_10_1007_s11914_014_0206_3 crossref_primary_10_1007_s10278_023_00953_3 crossref_primary_10_1016_j_joca_2015_11_013 crossref_primary_10_1016_j_jbiomech_2014_06_027 crossref_primary_10_1109_JPROC_2019_2943836 crossref_primary_10_1002_jbmr_4649 crossref_primary_10_1016_j_bone_2013_12_006 crossref_primary_10_1016_j_jbiomech_2014_12_018 crossref_primary_10_1007_s00223_020_00702_6 crossref_primary_10_1016_j_joca_2017_09_006 crossref_primary_10_1016_j_joca_2014_04_030 crossref_primary_10_1016_j_artmed_2021_102057 crossref_primary_10_1016_j_joca_2019_09_005 |
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Copyright | 2013 Osteoarthritis Research Society International Osteoarthritis Research Society International Copyright © 2013 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved. |
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Keywords | Hip morphology Shape analysis Proximal femur Osteoarthritis Statistical shape models |
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Snippet | To evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal... Summary Objective To evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs)... |
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SubjectTerms | Female Femur - diagnostic imaging Femur - pathology Femur Head - diagnostic imaging Femur Head - pathology Femur Neck - diagnostic imaging Femur Neck - pathology Hip morphology Humans Male Models, Anatomic Models, Statistical Observer Variation Osteoarthritis Osteoarthritis, Hip - diagnostic imaging Osteoarthritis, Hip - pathology Pelvic Bones - diagnostic imaging Proximal femur Radiographic Image Interpretation, Computer-Assisted - methods Rheumatology Sex Characteristics Shape analysis Statistical shape models |
Title | Development of a fully automatic shape model matching (FASMM) system to derive statistical shape models from radiographs: application to the accurate capture and global representation of proximal femur shape |
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