Evaluation of multiple radiographic predictors of cartilage lesions in the hip joints of eight-month-old dogs

Rory J. Todhunter Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by Rory J. Todhunter in
Current site
Google Scholar
PubMed
Close
 BVSc, PhD
,
Yrjo T. Grohn Department of Population Medicine and Diagnostic Services, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by Yrjo T. Grohn in
Current site
Google Scholar
PubMed
Close
 DVM, MPVM, PhD
,
Stuart P. Bliss Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by Stuart P. Bliss in
Current site
Google Scholar
PubMed
Close
 DVM
,
Ashley Wilfand Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by Ashley Wilfand in
Current site
Google Scholar
PubMed
Close
 BS
,
Alma J. Williams James A. Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by Alma J. Williams in
Current site
Google Scholar
PubMed
Close
 MS
,
Margaret Vernier-Singer Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by Margaret Vernier-Singer in
Current site
Google Scholar
PubMed
Close
 BS
,
Nancy I. Burton-Wurster James A. Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by Nancy I. Burton-Wurster in
Current site
Google Scholar
PubMed
Close
 PhD
,
Nathan L. Dykes Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by Nathan L. Dykes in
Current site
Google Scholar
PubMed
Close
 DVM
,
Rongling Wu Department of Statistics, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32611.

Search for other papers by Rongling Wu in
Current site
Google Scholar
PubMed
Close
 PhD
,
George Casella Department of Statistics, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32611.

Search for other papers by George Casella in
Current site
Google Scholar
PubMed
Close
 PhD
,
Gregory M. Acland James A. Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by Gregory M. Acland in
Current site
Google Scholar
PubMed
Close
 BVSc
, and
George Lust James A. Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

Search for other papers by George Lust in
Current site
Google Scholar
PubMed
Close
 PhD

Click on author name to view affiliation information

Abstract

Objective—To determine the radiographic methods that best predict the development of osteoarthritis in the hip joints of a cohort of dogs with hip dysplasia and unaffected dogs.

Animals—205 Labrador Retrievers, Greyhounds, and Labrador Retriever-Greyhound crossbred dogs.

Procedure—Pelvic radiography was performed when the dogs were 8 months old. Ventrodorsal extendedhip, distraction, and dorsolateral subluxation (DLS) radiographs were obtained. An Orthopedic Foundation for Animals-like hip score, distraction index, dorsolateral subluxation score, and Norberg angle were derived from examination of radiographs. Osteoarthritis was diagnosed at the time of necropsy in dogs ≥ 8 months of age on the basis of detection of articular cartilage lesions. Multiple logistic regression was used to determine the radiographic technique or techniques that best predicted development of osteoarthritis.

Results—A combination of 2 radiographic methods was better than any single method in predicting a cartilage lesion or a normal joint, but adding a third radiographic method did not improve that prediction. A combination of the DLS score and Norberg angle best predicted osteoarthritis of the hip joint or an unaffected hip joint. All models that excluded the DLS score were inferior to those that included it.

Conclusions and Clinical Relevance—A combination of the DLS score and Norberg angle was the best predictor of radiographic measures in 8-month-old dogs to determine whether a dog would have normal or osteoarthritic hip joints. (Am J Vet Res 2003;64:1472–1478)

Abstract

Objective—To determine the radiographic methods that best predict the development of osteoarthritis in the hip joints of a cohort of dogs with hip dysplasia and unaffected dogs.

Animals—205 Labrador Retrievers, Greyhounds, and Labrador Retriever-Greyhound crossbred dogs.

Procedure—Pelvic radiography was performed when the dogs were 8 months old. Ventrodorsal extendedhip, distraction, and dorsolateral subluxation (DLS) radiographs were obtained. An Orthopedic Foundation for Animals-like hip score, distraction index, dorsolateral subluxation score, and Norberg angle were derived from examination of radiographs. Osteoarthritis was diagnosed at the time of necropsy in dogs ≥ 8 months of age on the basis of detection of articular cartilage lesions. Multiple logistic regression was used to determine the radiographic technique or techniques that best predicted development of osteoarthritis.

Results—A combination of 2 radiographic methods was better than any single method in predicting a cartilage lesion or a normal joint, but adding a third radiographic method did not improve that prediction. A combination of the DLS score and Norberg angle best predicted osteoarthritis of the hip joint or an unaffected hip joint. All models that excluded the DLS score were inferior to those that included it.

Conclusions and Clinical Relevance—A combination of the DLS score and Norberg angle was the best predictor of radiographic measures in 8-month-old dogs to determine whether a dog would have normal or osteoarthritic hip joints. (Am J Vet Res 2003;64:1472–1478)

All Time Past Year Past 30 Days
Abstract Views 55 0 0
Full Text Views 519 356 36
PDF Downloads 172 65 4
Advertisement