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The severity of developmental dysplasia of the hip does not correlate with the abnormality in pelvic incidence.

ABSTRACT: BACKGROUND:The purpose of this study was to investigate the association between the severity of Developmental dysplasia of the hip (DDH) and the abnormality in pelvic incidence (PI). METHODS:This was a retrospective study analyzing 53 DDH patients and 53 non-DDH age-matched controls. Computed tomography images were used to construct three-dimensional pelvic model. The Crowe classification was used to classify the severity of DDH. The midpoint of the femoral head centers and sacral endplates were projected to the sagittal plane of the pelvis. The PI was defined as the angle between a line perpendicular to the sacral plate at its midpoint and a line connecting this point to the axis of the femoral heads. Independent sample t-tests were used to compare the differences between the PI of DDH group and the non-DDH controls group. Kendall's coefficient of concordance was used to determine the correlation between the severity of DDH and PI. RESULTS:Patients with DDH had a significantly (p?=?0.041) higher PI than the non-DDH controls (DDH 47.6?±?8.2°, normal 44.2?±?8.8°). Crowe type I patients had a significantly (p?=?0.038) higher PI (48.2?±?7.6°) than the non-DDH controls. No significant difference between the PI in Crowe type II or III patients and the PI in non-DDH controls were found (Crowe type II, 50.2?±?9.6°, p?=?0.073; Crowe type III, 43.8?±?7.2°, p?=?0.930). No correlation was found between the severity of DDH and the PI (r?=?0.091, p?=?0.222). CONCLUSIONS:No correlation was found between the severity of DDH and the PI. The study confirmed that the PI in DDH (Crowe type I) group was higher than that of the non-DDH control group, while the PI does not correlate with the severity of DDH.

SUBMITTER: Cheng R

PROVIDER: S-EPMC7507613 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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The severity of developmental dysplasia of the hip does not correlate with the abnormality in pelvic incidence.

Cheng Rongshan R Huang Muyin M Kernkamp Willem Alexander WA Li Huiwu H Zhu Zhenan Z Wang Liao L Tsai Tsung-Yuan TY

BMC musculoskeletal disorders 20200921 1

<h4>Background</h4>The purpose of this study was to investigate the association between the severity of Developmental dysplasia of the hip (DDH) and the abnormality in pelvic incidence (PI).<h4>Methods</h4>This was a retrospective study analyzing 53 DDH patients and 53 non-DDH age-matched controls. Computed tomography images were used to construct three-dimensional pelvic model. The Crowe classification was used to classify the severity of DDH. The midpoint of the femoral head centers and sacral ...[more]

PMID: 32957942

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Project description:Developmental dysplasia of the hip (DDH) is common, and features a widened Sharp's angle as observed on pelvic x-ray images. Determination of Sharp's angle, essential for clinical decisions, can overwhelm the workload of orthopedic surgeons. To aid diagnosis of DDH and reduce false negative diagnoses, a simple and cost-effective tool is proposed. The model was designed using artificial intelligence (AI), and evaluated for its ability to screen anteroposterior pelvic radiographs automatically, accurately, and efficiently.Orthotopic anterior pelvic x-ray images were retrospectively collected (n = 11574) from the PACS (Picture Archiving and Communication System) database at Second Hospital of Jilin University. The Mask regional convolutional neural network (R-CNN) model was utilized and finely modified to detect 4 key points that delineate Sharp's angle. Of these images, 11,473 were randomly selected, labeled, and used to train and validate the modified Mask R-CNN model. A test dataset comprised the remaining 101 images. Python-based utility software was applied to draw and calculate Sharp's angle automatically. The diagnoses of DDH obtained via the model or the traditional manual drawings of 3 orthopedic surgeons were compared, each based on the degree of Sharp's angle, and these were then evaluated relative to the final clinical diagnoses (based on medical history, symptoms, signs, x-ray films, and computed tomography images).Sharp's angles on the left and right measured via the AI model (40.07° ± 4.09° and 40.65° ± 4.21°), were statistically similar to that of the surgeons' (39.35° ± 6.74° and 39.82° ± 6.99°). The measurement time required by the AI model (1.11 ± 0.00 s) was significantly less than that of the doctors (86.72 ± 1.10, 93.26 ± 1.12, and 87.34 ± 0.80 s). The diagnostic sensitivity, specificity, and accuracy of the AI method for diagnosis of DDH were similar to that of the orthopedic surgeons; the diagnoses of both were moderately consistent with the final clinical diagnosis.The proposed AI model can automatically measure Sharp's angle with a performance similar to that of orthopedic surgeons, but requires far less time. The AI model may be a viable auxiliary to clinical diagnosis of DDH.

Dataset Information

The severity of developmental dysplasia of the hip does not correlate with the abnormality in pelvic incidence.

Publications

The severity of developmental dysplasia of the hip does not correlate with the abnormality in pelvic incidence.

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