T.D. Turmezei

Focal osteoporosis defects play a key role in hip fracture.

Background Hip fractures are mainly caused by accidental falls and trips, which magnify forces in well-defined areas of the proximal femur. Unfortunately, the same areas are at risk of rapid bone loss with ageing, since they are relatively stress-shielded during walking and sitting. Focal osteoporosis in those areas may contribute to fracture, and targeted 3D measurements might enhance hip fracture prediction. In the FEMCO case-control clinical study, Cortical Bone Mapping (CBM) was applied to clinical computed tomography (CT) scans to define 3D cortical and trabecular bone defects in patients with acute hip fracture compared to controls. Direct measurements of trabecular bone volume were then made in biopsies of target regions removed at operation. Methods The sample consisted of CT scans from 313 female and 40 male volunteers (158 with proximal femoral fracture, 145 age-matched controls and 50 fallers without hip fracture). Detailed Cortical Bone Maps (c.5580 measurement points on the unfractured hip) were created before registering each hip to an average femur shape to facilitate statistical parametric mapping (SPM). Areas where cortical and trabecular bone differed from controls were visualised in 3D for location, magnitude and statistical significance. Measures from the novel regions created by the SPM process were then tested for their ability to classify fracture versus control by comparison with traditional CT measures of areal Bone Mineral Density (aBMD). In women we used the surgical classification of fracture location (‘femoral neck’ or ‘trochanteric’) to discover whether focal osteoporosis was specific to fracture type. To explore whether the focal areas were osteoporotic by histological criteria, we used micro CT to measure trabecular bone parameters in targeted biopsies taken from the femoral heads of 14 cases. Results Hip fracture patients had distinct patterns of focal osteoporosis that determined fracture type, and CBM measures classified fracture type better than aBMD parameters. CBM measures however improved only minimally on aBMD for predicting any hip fracture and depended on the inclusion of trabecular bone measures alongside cortical regions. Focal osteoporosis was confirmed on biopsy as reduced sub-cortical trabecular bone volume. Conclusion Using 3D imaging methods and targeted bone biopsy, we discovered focal osteoporosis affecting trabecular and cortical bone of the proximal femur, among men and women with hip fracture.

Cortical bone assessed with clinical computed tomography at the proximal femur.

Hip fractures are the most serious of all fragility fractures in older people of both sexes. Trips, stumbles, and falls result in fractures of the femoral neck or trochanter, and the incidence of these two common fractures is increasing worldwide as populations age. Although clinical risk factors and chance are important in causation, the ability of a femur to resist fracture also depends on the size and spatial distribution of the bone, its intrinsic material properties, and the loads applied. Over the past two decades, clinical quantitative computed tomography (QCT) studies of living volunteers have provided insight into how the femur changes with advancing age to leave older men and women at increased risk of hip fractures. In this review, we focus on patterns of cortical bone loss associated with hip fracture, age‐related changes in cortical bone, and the effects of drugs used to treat osteoporosis. There are several methodologies available to measure cortical bone in vivo using QCT. Most techniques quantify bone density (g/cm3), mass (g), and thickness (mm) in selected, predefined or “traditional” regions of interest such as the “femoral neck” or “total hip” region. A recent alternative approach termed “computational anatomy,” uses parametric methods to identify systematic differences, before displaying statistically significant regions as color‐scaled maps of density, mass, or thickness on or within a representative femur model. This review will highlight discoveries made using both traditional and computational anatomy methods, focusing on cortical bone of the proximal femur.

A new CT grading system for hip osteoarthritis

OBJECTIVES We have developed a new grading system for hip osteoarthritis using clinical computed tomography (CT). This technique was compared with Kellgren and Lawrence (K&L) grading and minimum joint space width (JSW) measurement in digitally reconstructed radiographs (DRRs) from the same CT data. In this paper we evaluate and compare the accuracy and reliability of these measures in the assessment of radiological disease. DESIGN CT imaging of hips from 30 female volunteers aged 66 ± 17 years were used in two reproducibility studies, one testing the reliability of the new system, the other testing K&L grading and minimum JSW measurement in DRRs. RESULTS Intra- and inter-observer reliability was substantial for CT grading according to weighted kappa (0.74 and 0.75 respectively), while intra- and inter-observer reliability was at worst moderate (0.57) and substantial (0.63) respectively for DRR K&L grading. Bland-Altman analysis showed a systematic difference in minimum JSW measurement of 0.82 mm between reviewers, with a least detectable difference of 1.06 mm. The area under the curve from ROC analysis was 0.91 for our CT composite score. CONCLUSIONS CT grading of hip osteoarthritis (categorised as none, developing and established) has substantial reliability. Sensitivity was increased when CT features of osteoarthritis were assigned a composite score (0 = none to 7 = severest) that also performed well as a diagnostic test, but at the cost of reliability. Having established feasibility and reliability for this new CT system, sensitivity testing and validation against clinical measures of hip osteoarthritis will now be performed.

Computed Tomography of Subchondral Bone and Osteophytes in Hip Osteoarthritis: the Shape of Things to Come?

Bone is a fundamental component of the disordered joint homeostasis seen in osteoarthritis, a disease that has been primarily characterized by the breakdown of articular cartilage accompanied by local bone changes and a limited degree of joint inflammation. In this review we consider the role of computed tomography imaging and computational analysis in osteoarthritis research, focusing on subchondral bone and osteophytes in the hip. We relate what is already known in this area to what could be explored through this approach in the future in relation to both clinical research trials and the underlying cellular and molecular science of osteoarthritis. We also consider how this area of research could impact on our understanding of the genetics of osteoarthritis.

Severity mapping of the proximal femur: a new method for assessing hip osteoarthritis with computed tomography

OBJECTIVE Plain radiography has been the mainstay of imaging assessment in osteoarthritis for over 50 years, but it does have limitations. Here we present the methodology and results of a new technique for identifying, grading, and mapping the severity and spatial distribution of osteoarthritic disease features at the hip in 3D with clinical computed tomography (CT). DESIGN CT imaging of 456 hips from 230 adult female volunteers (mean age 66 ± 17 years) was reviewed using 3D multiplanar reformatting to identify bone-related radiological features of osteoarthritis, namely osteophytes, subchondral cysts and joint space narrowing. Scoresheets dividing up the femoral head, head-neck region and the joint space were used to register the location and severity of each feature (scored from 0 to 3). Novel 3D cumulative feature severity maps were then created to display where the most severe disease features from each individual were anatomically located across the cohort. RESULTS Feature severity maps showed a propensity for osteophytes at the inferoposterior and superolateral femoral head-neck junction. Subchondral cysts were a less common and less localised phenomenon. Joint space narrowing <1.5 mm was recorded in at least one sector of 83% of hips, but most frequently in the posterolateral joint space. CONCLUSIONS This is the first description of hip osteoarthritis using unenhanced clinical CT in which we describe the co-localisation of posterior osteophytes and joint space narrowing for the first time. We believe this technique can perform several important roles in future osteoarthritis research, including phenotyping and sensitive disease assessment in 3D.

The linguistic roots of Modern English anatomical terminology.

Previous research focusing on Classical Latin and Greek roots has shown that understanding the etymology of English anatomical terms may be beneficial for students of human anatomy. However, not all anatomical terms are derived from Classical origins. This study aims to explore the linguistic roots of the Modern English terminology used in human gross anatomy. By reference to the Oxford English Dictionary, etymologies were determined for a lexicon of 798 Modern English gross anatomical terms from the 40th edition of Grays Anatomy. Earliest traceable language of origin was determined for all 798 terms; language of acquisition was determined for 747 terms. Earliest traceable languages of origin were: Classical Latin (62%), Classical Greek (24%), Old English (7%), Post‐Classical Latin (3%), and other (4%). Languages of acquisition were: Classical Latin (42%), Post‐Classical Latin (29%), Old English (8%), Modern French (6%), Classical Greek (5%), Middle English (3%), and other (7%). While the roots of Modern English anatomical terminology mostly lie in Classical languages (accounting for the origin of 86% of terms), the anatomical lexicon of Modern English is actually much more diverse. Interesting and perhaps less familiar examples from these languages and the methods by which such terms have been created and absorbed are discussed. The author suggests that awareness of anatomical etymologies may enhance the enjoyment and understanding of human anatomy for students and teachers alike. Clin. Anat. 25:1015–1022, 2012.

Joint space mapping validation and reproducibility data

These data files provide the framework, thickness and thickness error values for 3D joint space mapping validation and reproducibility experiments.

Three-dimensional measurement of the hip joint space from clinical CT for the assessment and prediction of osteoarthritis

Abstract Background Advances in our understanding of osteoarthritis have been hampered by an ongoing inability to detect relevant structural changes in vivo. Radiography, which remains the gold standard for disease assessment, is limited by its two-dimensional representation of the whole joint and the need for observer-generated grading or measurement of disease. The aim of this study was to develop and validate a novel algorithm for three-dimensional (3D) measurement of the hip joint space width (JSW) with clinical CT data. Methods Right hips were dissected from 20 female cadavers, all with ante-mortem informed consent for participation in post-mortem imaging research. Each hip was imaged with clinical CT (test set) and high resolution peripheral quantitative CT (validation set). An automated model-based deconvolution approach was then applied to measure JSW in 3D from clinical CT data. This study was approved by the Cambridge Human Biology Research Ethics Committee. Findings Each hip joint was processed with a pipeline of automatic sphere fitting to the femoral head, manual 3D segmentation of joint space limits on the surface of this sphere, and subsequent automatic JSW measurement with a technique called joint space mapping. With a model-based approach, JSW was measured as the distance between opposing subchondral bone edges after deconvolution of the clinical CT data. Measurement validation was performed after cross-registration with the corresponding high resolution data, using a thresholding technique to determine JSW in this data set. Joint space mapping of clinical CT data was both technically accurate and precise over a 95% range of high resolution JSW values, from 1·48 to 4·61 mm (mean bias +0·02 mm [SD 0·43]). Interpretation Joint space mapping is a new image analysis technique that can automatically measure hip joint space in 3D from clinical CT data with high accuracy and precision, subsequently building a 3D model of the joint itself. This technique could deliver a step-change both in research trials and in the clinical setting, where the ability to stratify individuals for therapy and then evaluate disease accordingly is essential for prognostication and monitoring treatment efficacy over time. Funding Wellcome Trust.