FACTS: Fully Automatic CT Segmentation of a Hip Joint

Extraction of surface models of a hip joint from CT data is a pre-requisite step for computer assisted diagnosis and planning (CADP) of periacetabular osteotomy (PAO). Most of existing CADP systems are based on manual segmentation, which is time-consuming and hard to achieve reproducible results. In this paper, we present a Fully Automatic CT Segmentation (FACTS) approach to simultaneously extract both pelvic and femoral models. Our approach works by combining fast random forest (RF) regression based landmark detection, multi-atlas based segmentation, with articulated statistical shape model (aSSM) based fitting. The two fundamental contributions of our approach are: (1) an improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the multi-atlas based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 6-fold cross validation. When the present approach was compared to manual segmentation, a mean segmentation accuracy of 0.40, 0.36, and 0.36 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. When the models derived from both segmentations were used to compute the PAO diagnosis parameters, a difference of 2.0 ± 1.5°, 2.1 ± 1.6°, and 3.5 ± 2.3% were found for anteversion, inclination, and acetabular coverage, respectively. The achieved accuracy is regarded as clinically accurate enough for our target applications.

Which Radiographic Hip Parameters Do Not Have to Be Corrected for Pelvic Rotation and Tilt?

Background Acetabular anatomy on AP pelvic radiographsdepends on pelvic orientation during radiograph acquisition. However, not all parameters may change to a clinically relevant degree with differences in pelvic orientation. This issue may influence the diagnosis of acetabular pathologies and planning of corrective acetabular surgery (reorientation or rim trimming). However, to this point, it has not been well characterized. Questions/purposes We asked (1) which radiographic parameters change in a clinical setting when normalized to neutral pelvic orientation; (2) which parameters do not change in an experimental setting when the pelvis is experimentally rotated/tilted; and (3) which of these changes are ‘‘ultimately’’ relevant based on a prespecified definition of relevance. Methods In a clinical setup, 11 hip parameters were evaluated in 101 patients (126 hips) by two observers and the interobserver difference was calculated. All parameters were normalized to an anatomically defined neutral pelvic orientation with the help of a lateral pelvic radiograph and specific software. Differences between nonnormalized and normalized values were calculated (effect of normalization). In an experimental setup involving 20 cadaver pelves (40 hips), the maximum range for each parameter was computed with the pelvis rotated (range, −12° to 12°) and tilted (range, −24° to 24°). ‘‘Ultimately’’ relevant changes existed if the effect of normalization exceeded the interobserver difference (eg, 37% versus 6% for prevalence of a positive crossover sign) and/or the maximum experimental range exceeded 1 SD of interobserver difference (eg, 27% versus 6% for anterior acetabular coverage). Results In the clinical setup, all parameters except the ACM angle and craniocaudal acetabular coverage changed when being normalized, eg, effect of normalization for lateral center-edge angle, acetabular index, and sharp angle ranged from −5° to 4° (p values < 0.029). In the experimental setup, five parameters showed no major changes, whereas six parameters did change (all p values < 0.001). Ultimately relevant changes were found for anteroposterior acetabular coverage, retroversion index, and prevalence of a positive crossover or posterior wall sign. Conclusions Lateral center-edge angle, ACM angle, Sharp angle, acetabular and extrusion index, and craniocaudal acetabular coverage showed no relevant changes with varying pelvic orientation and can therefore be acquired independent from individual pelvic tilt and rotation in clinical practice. In contrast, anteroposterior acetabular coverage, crossover and posterior wall sign, and retroversion index call for specific efforts that address individual pelvic orientation such as computer-assisted evaluation of radiographs. Level of Evidence Level III, diagnostic study. See the Guidelines for Authors for a complete description of levels of evidence.

A complete-pelvis segmentation framework for image-free total hip arthroplasty (THA): methodology and clinical study

Background Complete-pelvis segmentation in antero-posterior pelvic radiographs is required to create a patient-specific three-dimensional pelvis model for surgical planning and postoperative assessment in image-free navigation of total hip arthroplasty. Methods A fast and robust framework for accurately segmenting the complete pelvis is presented, consisting of two consecutive modules. In the first module, a three-stage method was developed to delineate the left hemipelvis based on statistical appearance and shape models. To handle complex pelvic structures, anatomy-specific information processing techniques were employed. As the input to the second module, the delineated left hemi-pelvis was then reflected about an estimated symmetry line of the radiograph to initialize the right hemi-pelvis segmentation. The right hemi-pelvis was segmented by the same three-stage method, Results Two experiments conducted on respectively 143 and 40 AP radiographs demonstrated a mean segmentation accuracy of 1.61±0.68 mm. A clinical study to investigate the postoperative assessment of acetabular cup orientations based on the proposed framework revealed an average accuracy of 1.2°±0.9° and 1.6°±1.4° for anteversion and inclination, respectively. Delineation of each radiograph costs less than one minute. Conclusions Despite further validation needed, the preliminary results implied the underlying clinical applicability of the proposed framework for image-free THA.

Preoperative Planning of Periacetabular Osteotomy (PAO)

Pelvic osteotomies improve containment of the femoral head in cases of developmental dysplasia of the hip or in femoroacetabular impingement due to acetabular retroversion. In the evolution of osteotomies, the Ganz Periacetabular Osteotomy (PAO) is among the complex reorientation osteotomies and allows for complete mobilization of the acetabulum without compromising the integrity of the pelvic ring. For the complex reorientation osteotomies, preoperative planning of the required acetabular correction is an important step, due to the need to comprehend the three-dimensional (3D) relationship between acetabulum and femur. Traditionally, planning was performed using conventional radiographs in different projections, reducing the 3D problem to a two-dimensional one. Known disturbance variables, mainly tilt and rotation of the pelvis make assessment by these means approximate at the most. The advent of modern enhanced computation skills and new imaging techniques gave room for more sophisticated means of preoperative planning. Apart from analysis of acetabular geometry on conventional x-rays by sophisticated software applications, more accurate assessment of coverage and congruency and thus amount of correction necessary can be performed on multiplanar CT images. With further evolution of computer-assisted orthopaedic surgery, especially the ability to generate 3D models from the CT data, examiners were enabled to simulate the in vivo situation in a virtual in vitro setting. Based on this ability, different techniques have been described. They basically all employ virtual definition of an acetabular fragment. Subsequently reorientation can be simulated using either 3D calculation of standard parameters of femoroacetabular morphology, or joint contact pressures, or a combination of both. Other techniques employ patient specific implants, templates or cutting guides to achieve the goal of safe periacetabular osteotomies. This chapter will give an overview of the available techniques for planning of periacetabular osteotomy.

2D-3D Reconstruction-Based Planning of Total Hip Arthroplasty

This chapter proposed a personalized X-ray reconstruction-based planning and post-operative treatment evaluation framework called iJoint for advancing modern Total Hip Arthroplasty (THA). Based on a mobile X-ray image calibration phantom and a unique 2D-3D reconstruction technique, iJoint can generate patient-specific models of hip joint by non-rigidly matching statistical shape models to the X-ray radiographs. Such a reconstruction enables a true 3D planning and treatment evaluation of hip arthroplasty from just 2D X-ray radiographs whose acquisition is part of the standard diagnostic and treatment loop. As part of the system, a 3D model-based planning environment provides surgeons with hip arthroplasty related parameters such as implant type, size, position, offset and leg length equalization. With this newly developed system, we are able to provide true 3D solutions for computer assisted planning of THA using only 2D X-ray radiographs, which is not only innovative but also cost-effective.

Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.