Dataset Information

Anatomical analysis of the pelvis to identify any predisposing anatomical factors for ischiofemoral space pathology: a retrospective study.

ABSTRACT:

Objective

Anatomical analysis of the hips and pelvis was performed using MRI to evaluate morphological characteristics and associations between them. We identified correlations between the ischiofemoral space (IFS), quadratus femoris space (QFS), femoral version angle (FVA) and cervicodiaphyseal angle (CDA).

Methods

This study involved a retrospective search of a database of consecutive reports of adult hip MRI examinations carried out between January and September 2016. Patients with a medical history likely to affect pelvic and hip morphometry were excluded.

Results

A total of 137 adult patients were enrolled in the study (45.3% males and 54.7% females), with a mean age of 50.16 ± 13.87 years. The mean IFS was 20.88 ± 5.96?mm, mean QFS was 15.2 ± 6.18?mm, mean FVA was 12.43 ± 6.98, and mean CDA was 121.27 ± 4.6°. The IFS measurements were significantly correlated with femoral measurements (p = 0.025). These visible differences showed a slight negative relationship (-0.191), and females had a smaller distance between these anatomical structures than males (p < 0.001). Females had a significantly smaller QFS than males (12.42 ± 5.94 vs 18.73 ± 4.48?mm, p = 0.000). There was a small but significant positive relationship between CDA and FVA (p = 0.022), with a correlation coefficient of 0.195.

Conclusion

A higher FVA was correlated with a smaller IFS. Furthermore, an increase in the CDA appeared in tandem with an increase in the FVA.

Advances in knowledge

A single conventional MRI sequence can alert us to how anatomical factors could predispose individuals to a decrease in IFS.

SUBMITTER: Lopez-Royo MP

PROVIDER: S-EPMC7362912 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Anatomical analysis of the pelvis to identify any predisposing anatomical factors for ischiofemoral space pathology: a retrospective study.

López-Royo Maria Pilar MP Valero-Tena Esther E Roca Mercedes M

The British journal of radiology 20200129 1108

<h4>Objective</h4>Anatomical analysis of the hips and pelvis was performed using MRI to evaluate morphological characteristics and associations between them. We identified correlations between the ischiofemoral space (IFS), quadratus femoris space (QFS), femoral version angle (FVA) and cervicodiaphyseal angle (CDA).<h4>Methods</h4>This study involved a retrospective search of a database of consecutive reports of adult hip MRI examinations carried out between January and September 2016. Patients ...[more]

PMID: 31977237

Similar Datasets

Project description:Increased information on the encoded mammalian genome is expected to facilitate an integrated understanding of complex anatomical structure and function based on the knowledge of gene products. Determination of gene expression-anatomy associations is crucial for this understanding. To elicit the association in the three-dimensional (3D) space, we introduce a novel technique for comprehensive mapping of endogenous gene expression into a web-accessible standard space: Transcriptome Tomography. The technique is based on conjugation of sequential tissue-block sectioning, all fractions of which are used for molecular measurements of gene expression densities, and the block- face imaging, which are used for 3D reconstruction of the fractions. To generate a 3D map, tissues are serially sectioned in each of three orthogonal planes and the expression density data are mapped using a tomographic technique. This rapid and unbiased mapping technique using a relatively small number of original data points allows researchers to create their own expression maps in the broad anatomical context of the space. In the first instance we generated a dataset of 36,000 maps, reconstructed from data of 61 fractions measured with microarray, covering the whole mouse brain (ViBrism: http://vibrism.riken.jp/3dviewer/ex/index.html) in one month. After computational estimation of the mapping accuracy we validated the dataset against existing data with respect to the expression location and density. To demonstrate the relevance of the framework, we showed disease related expression of Huntington's disease gene and Bdnf. Our tomographic approach is applicable to analysis of any biological molecules derived from frozen tissues, organs and whole embryos, and the maps are spatially isotropic and well suited to the analysis in the standard space (e.g. Waxholm Space for brain-atlas databases). This will facilitate research creating and using open-standards for a molecular-based understanding of complex structures; and will contribute to new insights into a broad range of biological and medical questions.

Project description:PurposeMinimally invasive alternatives are now available for many complex surgeries. These approaches are enabled by the increasing availability of intra-operative image guidance. Yet, fluoroscopic X-rays suffer from projective transformation and thus cannot provide direct views onto anatomy. Surgeons could highly benefit from additional information, such as the anatomical landmark locations in the projections, to support intra-operative decision making. However, detecting landmarks is challenging since the viewing direction changes substantially between views leading to varying appearance of the same landmark. Therefore, and to the best of our knowledge, view-independent anatomical landmark detection has not been investigated yet.MethodsIn this work, we propose a novel approach to detect multiple anatomical landmarks in X-ray images from arbitrary viewing directions. To this end, a sequential prediction framework based on convolutional neural networks is employed to simultaneously regress all landmark locations. For training, synthetic X-rays are generated with a physically accurate forward model that allows direct application of the trained model to real X-ray images of the pelvis. View invariance is achieved via data augmentation by sampling viewing angles on a spherical segment of [Formula: see text].ResultsOn synthetic data, a mean prediction error of 5.6 ± 4.5 mm is achieved. Further, we demonstrate that the trained model can be directly applied to real X-rays and show that these detections define correspondences to a respective CT volume, which allows for analytic estimation of the 11 degree of freedom projective mapping.ConclusionWe present the first tool to detect anatomical landmarks in X-ray images independent of their viewing direction. Access to this information during surgery may benefit decision making and constitutes a first step toward global initialization of 2D/3D registration without the need of calibration. As such, the proposed concept has a strong prospect to facilitate and enhance applications and methods in the realm of image-guided surgery.

Dataset Information

Anatomical analysis of the pelvis to identify any predisposing anatomical factors for ischiofemoral space pathology: a retrospective study.

Objective

Methods

Results

Conclusion

Advances in knowledge

Publications

Anatomical analysis of the pelvis to identify any predisposing anatomical factors for ischiofemoral space pathology: a retrospective study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets