The distribution of cortical bone in the proximal femur is believed to be a critical component in determining fracture resistance. Current CT technology is limited in its ability to measure cortical thickness, especially in the sub-millimetre range which lies within the point spread function of today’s clinical scanners. In this paper, we present a novel technique that is capable of producing unbiased thickness estimates down to 0.3 mm. The technique relies on a mathematical model of the anatomy and the imaging system, which is fitted to the data at a large number of sites around the proximal femur, producing around 17,000 independent thickness estimates per specimen. In a series of experiments on 16 cadaveric femurs, estimation errors were measured as −0.01 ± 0.58 mm (mean ± 1 std.dev.) for cortical thicknesses in the range 0.3–4 mm. This compares with 0.25 ± 0.69 mm for simple thresholding and 0.90 ± 0.92 mm for a variant of the 50% relative threshold method. In the clinically relevant sub-millimetre range, thresholding increasingly fails to detect the cortex at all, whereas the new technique continues to perform well. The many cortical thickness estimates can be displayed as a colour map painted onto the femoral surface. Computation of the surfaces and colour maps is largely automatic, requiring around 15 min on a modest laptop computer.

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Highlights► Focal thinning of cortical bone in the proximal femur predisposes a hip to fracture. ► Thinning is difficult to detect in CT since the cortex may be narrower than the PSF. ► We present a model-fitting technique to estimate cortical thickness, density and mass. ► Evaluation on cadaveric femurs confirms accurate measurement of mass and peak density. ► Thickness errors do not exceed 20% and are confined to regions of thin cortex.

BackgroundIndividuals with osteoporosis are predisposed to hip fracture during trips, stumbles or falls, but half of all hip fractures occur in those without generalised osteoporosis. By analysing ordinary clinical CT scans using a novel cortical thickness mapping technique, we discovered patches of markedly thinner bone at fracture-prone regions in the femurs of women with acute hip fracture compared with controls.MethodsWe analysed CT scans from 75 female volunteers with acute fracture and 75 age- and sex-matched controls. We classified the fracture location as femoral neck or trochanteric before creating bone thickness maps of the outer ‘cortical’ shell of the intact contra-lateral hip. After registration of each bone to an average femur shape and statistical parametric mapping, we were able to visualise and quantify statistically significant foci of thinner cortical bone associated with each fracture type, assuming good symmetry of bone structure between the intact and fractured hip. The technique allowed us to pinpoint systematic differences and display the results on a 3D average femur shape model.FindingsThe cortex was generally thinner in femoral neck fracture cases than controls. More striking were several discrete patches of statistically significant thinner bone of up to 30%, which coincided with common sites of fracture initiation (femoral neck or trochanteric).InterpretationFemoral neck fracture patients had a thumbnail-sized patch of focal osteoporosis at the upper head-neck junction. This region coincided with a weak part of the femur, prone to both spontaneous ‘tensile’ fractures of the femoral neck, and as a site of crack initiation when falling sideways. Current hip fracture prevention strategies are based on case finding: they involve clinical risk factor estimation to determine the need for single-plane bone density measurement within a standard region of interest (ROI) of the femoral neck. The precise sites of focal osteoporosis that we have identified are overlooked by current 2D bone densitometry methods.

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The local structure of the proximal femoral cortex is of interest since both fracture risk, and the effects of various interventions aimed at reducing that risk, are associated with cortical properties focused in particular regions rather than dispersed over the whole bone. Much of the femoral cortex is less than 3mm thick, appearing so blurred in clinical CT that its actual density is not apparent in the data, and neither thresholding nor full-width half-maximum techniques are capable of determining its width. Our previous work on cortical bone mapping showed how to produce more accurate estimates of cortical thickness by assuming a fixed value of the cortical density for each hip. However, although cortical density varies much less over the proximal femur than thickness, what little variation there is leads to errors in thickness measurement. In this paper, we develop the cortical bone mapping technique by exploiting local estimates of imaging blur to correct the global density estimate, thus providing a local density estimate as well as more accurate estimates of thickness. We also consider measurement of cortical mass surface density and the density of trabecular bone immediately adjacent to the cortex. Performance is assessed with ex vivo clinical QCT scans of proximal femurs, with true values derived from high resolution HRpQCT scans of the same bones. We demonstrate superior estimation of thickness than is possible with alternative techniques (accuracy 0.12 ± 0.39 mm for cortices in the range 1-3mm), and that local cortical density estimation is feasible for densities >800 mg/cm(3).

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This review is about the development of three-dimensional (3D) ultrasonic medical imaging, how it works, and where its future lies. It assumes knowledge of two-dimensional (2D) ultrasound, which is covered elsewhere in this issue. The three main ways in which 3D ultrasound may be acquired are described: the mechanically swept 3D probe, the 2D transducer array that can acquire intrinsically 3D data, and the freehand 3D ultrasound. This provides an appreciation of the constraints implicit in each of these approaches together with their strengths and weaknesses. Then some of the techniques that are used for processing the 3D data and the way this can lead to information of clinical value are discussed. A table is provided to show the range of clinical applications reported in the literature. Finally, the discussion relating to the technology and its clinical applications to explain why 3D ultrasound has been relatively slow to be adopted in routine clinics is drawn together and the issues that will govern its development in the future explored.