Cortical and Trabecular Bone Deficit in Middle-Aged Men Living with HIV

A significant increase in the risk of hip fracture was observed in middle-aged men living with human immunodeficiency virus (MLWH), almost a decade earlier than those without infection. Data regarding cortical and trabecular bone deficit of hip, an important determinant of bone strength, in MLWH are limited. Quantitative CT was performed in consecutive MLWH aged ≥30 years between November 2017 and October 2018 at Severance Hospital, Seoul, Korea. Volumetric bone mineral density (vBMD) and cortical bone mapping parameters of hip (cortical thickness [CTh], cortical bone vBMD [CBMD], cortical mass surface density [CMSD], endocortical trabecular density [ECTD]) were compared to age-matched and body mass index (BMI)-matched controls (1:2) using a community-based healthy adults cohort. Among 83 MLWH and 166 controls (mean age: 47.2 years; BMI: 23.6 kg/m2 ), MLWH had lower total hip vBMD (280 ± 41 versus 296 ± 41 mg/cm3 ), CMSD (155 versus 160 mg/cm2 ), and ECTD (158 versus 175 mg/cm3 ) than controls that remained robust after adjustment for covariates (adjusted β: total hip vBMD, -18.8; CMSD, -7.3; ECTD, -18.0; p < 0.05 for all). Cortical bone mapping revealed localized deficit of CTh, CBMD, and CMSD in the anterolateral trochanteric region and femoral neck in MLWH compared to controls, with a more extensive ECTD deficit. In MLWH, lower CD4 T-cell count (/100 cells/mm3 decrement) and protease inhibitor (PI)-based regimen (versus non-PI regimen) at the time of antiretroviral treatment initiation were associated with lower total hip vBMD (adjusted β -7.5 for lower CD4 count; -28.3 for PI-based regimen) and CMSD (adjusted β -2.6 for lower CD4 count; -12.7 for PI-based regimen; p < 0.05 for all) after adjustment for covariates including age, BMI, smoking, alcohol use, hepatitis C virus co-infection, tenofovir exposure, and CT scanner types. MLWH had lower hip bone density with cortical and trabecular bone deficit compared to community-dwelling controls. © 2023 American Society for Bone and Mineral Research (ASBMR).

Real Image Denoising With a Locally-Adaptive Bitonic Filter

Image noise removal is a common problem with many proposed solutions. The current standard is set by learning-based approaches, however these are not appropriate in all scenarios, perhaps due to lack of training data or the need for predictability in novel circumstances. The bitonic filter is a non-learning-based filter for removing noise from signals, with a mathematical morphology (ranking) framework in which the signal is postulated to be locally bitonic (having only one minimum or maximum) over some domain of finite extent. A novel version of this filter is developed in this paper, with a domain that is locally-adaptive to the signal, and other adjustments to allow application to real image sensor noise. These lead to significant improvements in noise reduction performance at no cost to processing times. The new bitonic filter performs better than the block-matching 3D filter for high levels of additive white Gaussian noise. It also surpasses this and other more recent non-learning-based filters for two public data sets containing real image noise at various levels. This is despite an additional adjustment to the block-matching filter, which leads to significantly better performance than has previously been cited on these data sets. The new bitonic filter has a signal-to-noise ratio 2.4dB lower than the best learning-based techniques when they are optimally trained. However, the performance gap is closed completely when these techniques are trained on data sets not directly related to the benchmark data. This demonstrates what can be achieved with a predictable, explainable, entirely local technique, which makes no assumptions of repeating patterns either within an image or across images, and hence creates residual images which are well behaved even in very high noise. Since the filter does not require training, it can still be used in situations where training is either difficult or inappropriate.

Protective effect of bisphosphonate on the cortical bone at key locations of the femur in aromatase inhibitor-associated bone loss: A three-dimensional cortical bone mapping study

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Aromatase inhibitor use was associated with cortical bone loss in the hip.

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Bisphosphonate protected hip cortical bone against aromatase inhibitor use.

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The effect was prominent at the superior femoral neck and greater trochanter.

Aromatase inhibitor treatment in breast cancer is associated with accelerated bone loss and an increased risk of fracture. Bisphosphonates (BPs) are the mainstay treatment of aromatase inhibitor-associated bone loss (AIBL), which might improve femoral bone at key locations prone to fracture. To test this hypothesis, we performed three-dimensional cortical bone mapping based on quantitative computed tomography (QCT) scans in postmenopausal women with early breast cancer who were receiving aromatase inhibitors. Data of subjects who had both baseline and at least one follow-up QCT at Severance Hospital (South Korea) between 2005 and 2015 were analyzed (BP users, n = 93; BP non-users, n = 203). After exclusion of BP users with low medication persistence (proportion of days covered: <50%), BP users and non-users were 1:1 matched (n = 54 for each group) in terms of age, lumbar spine volumetric bone mineral density (LSvBMD), femoral neck areal BMD (FNaBMD), and total hip areal BMD (THaBMD). During a median follow-up of 2.1 years, BP use attenuated bone loss in LSvBMD (+7.2% vs. −3.8%, p < 0.001), FNaBMD (+1.3% vs. −2.7%, p < 0.001), and THaBMD (-0.3% vs. −2.5%, p = 0.024). BP had a protective effect on cortical parameters of femoral bone: estimated cortical thickness (CTh) (+3.3% vs. + 0.1%, p = 0.007) and cortical mass surface density (CMSD, cortical mass per unit surface area was calculated by multiplying cortical BMD with CTh) (+3.4% vs. −0.3%, p < 0.001). CMSD increased by up to 15% at key locations such as the superior part of the femoral neck and greater trochanter. BP prevented the thinning of average CTh of the femoral neck (-1.4% vs. −6.1%, p < 0.001), particularly at the superior anterior quadrant of femoral neck (absolute difference: +12.8% point vs. non-users). Compared to BP non-users, BP users had improved cross-sectional moment of inertia (+4.4% vs. −0.7%, p = 0.001) and less increase in buckling ratio (+1.3% vs. + 7.5%, p < 0.001). In summary, BP use prevented cortical bone deficits observed in AIBL at key locations of the proximal femur.

Morphology-based Noise Reduction: Structural Variation and Thresholding in the Bitonic Filter

The bitonic filter was recently developed to embody the novel concept of signal bitonicity (one local extremum within a set range) to differentiate from noise, by use of data ranking and linear operators. For processing images, the spatial extent was locally constrained to a fixed circular mask. Since structure in natural images varies, a novel structurally varying bitonic filter is presented, which locally adapts the mask, without following patterns in the noise. This new filter includes novel robust structurally varying morphological operations, with efficient implementations, and a novel formulation of non-iterative directional Gaussian filtering. Data thresholds are also integrated with the morphological operations, increasing noise reduction for low noise, and enabling a multi-resolution framework for high noise levels. The structurally varying bitonic filter is presented without presuming prior knowledge of morphological filtering, and compared to high-performance linear noise-reduction filters, to set this novel concept in context. These are tested over a wide range of noise levels, on a fairly broad set of images. The new filter is a considerable improvement on the fixed-mask bitonic, outperforms anisotropic diffusion and image-guided filtering in all but extremely low noise, non-local means at all noise levels, but not the block-matching 3D filter, though results are promising for very high noise. The structurally varying bitonic tends to have less characteristic residual noise in regions of smooth signal, and very good preservation of signal edges, though with some loss of small scale detail when compared to the block-matching 3D filter. The efficient implementation means that processing time, though slower than the fixed-mask bitonic filter, remains competitive.

Cortical Bone Mapping: Measurement and Statistical Analysis of Localised Skeletal Changes

PURPOSE OF REVIEW

Cortical bone mapping (CBM) is a technique for measuring localised skeletal changes from computed tomography (CT) images. It can provide measurements with accuracy surpassing the underlying imaging resolution. CBM can detect changes in several properties of the cortex, with no prior assumptions about the likely location of said changes. This paper summarises the theory behind CBM, discusses its strengths and limitations, and reviews some studies in which it has been applied.

RECENT FINDINGS

CBM has revealed associations between fracture risk and cortical properties in specific regions of the proximal femur which present feasible therapeutic targets. Analyses of several pharmaceutical and exercise interventions quantify effects that are distinct both in location and in the nature of the micro-architectural changes. CBM has illuminated age-related changes in the proximal femur and has recently been applied to other bones, as well as to the assessment of cartilage. The CBM processing pipeline is designed primarily for large cohort studies. Its main impact thus far has not been in the realm of clinical practice, but rather to improve our fundamental understanding of localised bone structure and changes.

The Bitonic Filter: Linear Filtering in an Edge-Preserving Morphological Framework

A new filter is presented which has better edge and detail preserving properties than a median, noise reduction capability similar to a Gaussian, and is applicable to many signal and noise types. It is built on a definition of signal as bitonic, i.e., containing only one local maxima or minima within the filter range. This definition is based on data ranking rather than value; hence, the bitonic filter comprises a combination of non-linear morphological and linear operators. It has no data-level-sensitive parameters and can locally adapt to the signal and noise levels in an image, precisely preserving both smooth and discontinuous signals of any level when there is no noise, but also reducing noise in other areas without creating additional artifactual noise. Both the basis and the performance of the filter are examined in detail, and it is shown to be a significant improvement on the Gaussian and median. It is also compared over various noisy images to the image-guided filter, anisotropic diffusion, non-local means, the grain filter, and self-dual forms of leveling and rank filters. In terms of signal-to-noise, the bitonic filter outperforms all these except non-local means, and sometimes anisotropic diffusion. However, it gives good visual results in all circumstances, with characteristics which make it appropriate particularly for signals or images with varying noise, or features at varying levels. The bitonic has very few parameters, does not require optimization nor prior knowledge of noise levels, does not have any problems with stability, and is reasonably fast to implement. Despite its non-linearity, it hence represents a very practical operation with general applicability.

A clinical system for three-dimensional extended-field-of-view ultrasound

OBJECTIVE

This work is concerned with the creation of three-dimensional (3D) extended-field-of-view ultrasound from a set of volumes acquired using a mechanically swept 3D probe. 3D volumes of ultrasound data can be registered by attaching a position sensor to the probe; this can be an inconvenience in a clinical setting. A position sensor can also cause some misalignment due to patient movement and respiratory motion. We propose a combination of three-degrees-of-freedom image registration and an unobtrusively integrated inertial sensor for measuring orientation. The aim of this research is to produce a reliable and portable ultrasound system that is able to register 3D volumes quickly, making it suitable for clinical use.

METHOD

As part of a feasibility study we recruited 28 pregnant females attending for routine obstetric scans to undergo 3D extended-field-of-view ultrasound. A total of 49 data sets were recorded. Each registered data set was assessed for correct alignment of each volume by two independent observers.

RESULTS

In 77-83% of the data sets more than four consecutive volumes registered. The successful registration relies on good overlap between volumes and is adversely affected by advancing gestational age and foetal movement.

CONCLUSION

The development of reliable 3D extended-field-of-view ultrasound may help ultrasound practitioners to demonstrate the anatomical relation of pathology and provide a convenient way to store data.

Real-time quasi-static ultrasound elastography

Ultrasound elastography is a technique used for clinical imaging of tissue stiffness with a conventional ultrasound machine. It was first proposed two decades ago, but active research continues in this area to the present day. Numerous clinical applications have been investigated, mostly related to cancer imaging, and though these have yet to prove conclusive, the technique has seen increasing commercial and clinical interest. This paper presents a review of the most widely adopted, non-quantitative, techniques focusing on technical innovations rather than clinical applications. The review is not intended to be exhaustive, concentrating instead on placing the various techniques in context according to the authors' perspective of the field.

Efficient implementation of spatially-varying 3-D ultrasound deconvolution

There are sometimes occasions when ultrasound beamforming is performed with only a subset of the total data that will eventually be available. The most obvious example is a mechanically-swept (wobbler) probe in which the three-dimensional data block is formed from a set of individual B-scans. In these circumstances, non-blind deconvolution can be used to improve the resolution of the data. Unfortunately, most of these situations involve large blocks of three-dimensional data. Furthermore, the ultrasound blur function varies spatially with distance from the transducer. These two facts make the deconvolution process time-consuming to implement. This paper is about ways to address this problem and produce spatially-varying deconvolution of large blocks of three-dimensional data in a matter of seconds. We present two approaches, one based on hardware and the other based on software. We compare the time they each take to achieve similar results and discuss the computational resources and form of blur model that each requires.

Estimation of speed of sound in dual-layered media using medical ultrasound image deconvolution

The speed of sound in soft tissues is usually assumed to be 1540 m/s in medical pulse-echo ultrasound imaging systems. When the true speed is different, the mismatch can lead to distortions in the acquired images, and so reduce their clinical value. Previously we reported a new method of sound-speed estimation in the context of image deconvolution. Unlike most other sound-speed estimation methods, this enables the use of unmodified ultrasound machines and a normal scanning pattern. Our approach was validated for largely homogeneous media with single sound speeds. In this article, we demonstrate that sound speeds of dual-layered media can also be estimated through image deconvolution. An ultrasound simulator has been developed for layered media assuming that, for moderate speed differences, the reflection at the interface may be neglected. We have applied our dual-layer algorithm to simulations and in vitro phantoms. The speed of the top layer is estimated by our aforesaid method for homogeneous media. Then, when the layer boundary position is known, a series of deconvolutions are carried out with dual-layered point-spread functions having different lower-layer speeds. The best restoration is selected using a correlation metric. The error level (e.g., a mean error of -9 m/s with a standard deviation of 16 m/s) for in vitro phantoms is found to be not as good as that of our single-speed algorithm, but is comparable to other local speed estimation methods where the data acquisition may not be as simple as in our proposed method.

A hybrid displacement estimation method for ultrasonic elasticity imaging

Axial displacement estimation is fundamental to many freehand quasistatic ultrasonic strain imaging systems. In this paper, we present a novel estimation method that combines the strengths of quality-guided tracking, multi-level correlation, and phase-zero search to achieve high levels of accuracy and robustness. The paper includes a full description of the hybrid method, in vivo examples to illustrate the method's clinical relevance, and finite element simulations to assess its accuracy. Quantitative and qualitative comparisons are made with leading single- and multi-level alternatives. In the in vivo examples, the hybrid method produces fewer obvious peak-hopping errors, and in simulation, the hybrid method is found to reduce displacement estimation errors by 5 to 50%. With typical clinical data, the hybrid method can generate more than 25 strain images per second on commercial hardware; this is comparable with the alternative approaches considered in this paper.

Estimation of average speed of sound using deconvolution of medical ultrasound data

In diagnostic ultrasound imaging the speed of sound is assumed to be 1540 m/s in soft tissues. When the actual speed is different, the mismatch can lead to distortions in the acquired images and so reduce their clinical value. Therefore, the estimation of the true speed has been pursued not only because it enables image correction but also as a way of tissue characterisation. In this article, we present a novel way to measure the average speed of sound concurrently with performing image enhancement by deconvolution. This simultaneous capability, based on a single acquisition of ultrasound data, has not been reported in previous publications. Our algorithm works by conducting non-blind deconvolution of the reflection data with point-spread functions based on different speeds of sound. Using a search strategy, we select the speed that produces the best-possible restoration. The deconvolution operates on the beamformed uncompressed radio-frequency data, without any need to modify the hardware of the ultrasound machine. A conventional handling of the transducer array is all that is required in the data acquisition part of our proposed method: the data can be collected freehand, unlike most other estimation methods. We have tested our algorithm with simulations, in vitro phantoms with known and unknown speeds and in vivo scans. The estimation error was found to be +0.19 +/- 8.90 m/s (mean +/- standard deviation) for in vitro in-house phantoms whose speeds were also measured independently. In addition to the speed estimation, our method has also proved to be capable of simultaneously producing a better restoration of ultrasound images than deconvolution by an assumed speed of 1540 m/s, when this assumption is incorrect.

Sensitivity to point-spread function parameters in medical ultrasound image deconvolution

Clinical ultrasound images are often perceived as difficult to interpret due to image blurring and speckle inherent in the ultrasound imaging. But the image quality can be improved by deconvolution using an estimate of the point-spread function. However, it is difficult to obtain a sufficiently accurate estimate of the point-spread function in vivo because of the unknown properties of the soft tissue in clinical applications. Local variations in the speed of sound and attenuation change the pulse and beam shape. These in turn affect the point-spread function. The purpose and novelty of this paper is therefore to explore the sensitivity of a state-of-the-art deconvolution algorithm to uncertainty in the point-spread function. The point-spread function in our restoration algorithm is made shift invariant in the lateral dimension but shift dependent in the axial direction, and is modelled to match a 128-element 1D linear array often found in clinical use. We present simulated and in vitro sensitivity analyses of two-dimensional deconvolution while varying six parameters on which the point-spread function depends. Uncertainty in the ultrasound machine is analysed by varying the axial depths of lateral and elevational foci alongside height and width of transducer elements. Sensitivity to tissue influence is investigated by varying the speed of sound and frequency-dependent attenuation of the electro-mechanical impulse response. The results are analysed both quantitatively and in terms of the perceived image quality. First, the assessment of deconvolution using the logarithmic image amplitude is found to be a better indicator of the perceived improvement in the restoration. Secondly, the two most critical parameters for two-dimensional deconvolution are discovered to be the lateral focus and the speed of sound, because the success of deconvolution is perceived primarily in terms of deblurring. We also observed similar patterns for the simulation and in vitro experiment. Finally, we show that it is possible to restore in vivo ultrasound images using an assumed point-spread function and hence conclude that an exact point-spread function is not necessary for enhancing ultrasound image quality by deconvolution.

Stable, intelligible ultrasonic strain imaging

BACKGROUND: Freehand quasistatic strain imaging can reveal qualitative information about tissue stiffness with good spatial accuracy. Clinical trials, however, repeatedly cite instability and variable signal-to-noise ratio as significant drawbacks. METHODS: This study investigates three post-processing strategies for quasistatic strain imaging. Normalisation divides the strain by an estimate of the stress field, the intention being to reduce sensitivity to variable applied stress. Persistence aims to improve the signal-to-noise ratio by time-averaging multiple frames. The persistence scheme presented in this article operates at the pixel level, weighting each frame's contribution by an estimate of the strain precision. Precision-based display presents the clinician with an image in which regions of indeterminate strain are obscured behind a colour wash. This is achieved using estimates of strain precision that are faithfully propagated through the various stages of signal processing. RESULTS AND DISCUSSION: The post-processing strategy is evaluated qualitatively on scans of a breast biopsy phantom and in vivo head and neck examinations. Strain images processed in this manner are observed to benefit from improved stability and signal-to-noise ratio. There are, however, limitations. In unusual though conceivable circumstances, the normalisation procedure might suppress genuine stiffness variations evident in the unprocessed strain images. In different circumstances, the raw strain images might fail to capture significant stiffness variations, a situation that no amount of post-processing can improve. CONCLUSION: The clinical utility of freehand quasistatic strain imaging can be improved by normalisation, precision-weighted pixel-level persistence and precision-based display. The resulting images are stable and generally exhibit a better signal-to-noise ratio than any of the original, unprocessed strain images.

Wavelet restoration of medical pulse-echo ultrasound images in an EM framework

The clinical utility of pulse-echo ultrasound images is severely limited by inherent poor resolution that impacts negatively on their diagnostic potential. Research into the enhancement of image quality has mostly been concentrated in the areas of blind image restoration and speckle removal, with little regard for accurate modeling of the underlying tissue reflectivity that is imaged. The acoustic response of soft biological tissues has statistics that differ substantially from the natural images considered in mainstream image processing: although, on a macroscopic scale, the overall tissue echogenicity does behave some-what like a natural image and varies piecewise-smoothly, on a microscopic scale, the tissue reflectivity exhibits a pseudo-random texture (manifested in the amplitude image as speckle) due to the dense concentrations of small, weakly scattering particles. Recognizing that this pseudorandom texture is diagnostically important for tissue identification, we propose modeling tissue reflectivity as the product of a piecewise-smooth echogenicity map and a field of uncorrelated, identically distributed random variables. We demonstrate how this model of tissue reflectivity can be exploited in an expectation-maximization (EM) algorithm that simultaneously solves the image restoration problem and the speckle removal problem by iteratively alternating between Wiener filtering (to solve for the tissue reflectivity) and wavelet-based denoising (to solve for the echogenicity map). Our simulation and in vitro results indicate that our EM algorithm is capable of producing restored images that have better image quality and greater fidelity to the true tissue reflectivity than other restoration techniques based on simpler regularizing constraints.

Modeling ultrasound imaging as a linear, shift-variant system

We solve the equation that governs acoustic wave propagation in an inhomogeneous medium to show that the radio-frequency (RF) ultrasound signal can be expressed as the result of filtering the scatterer field with a point-spread function. We extend the analysis to make the link between the RF ultrasound signal and the representation of ultrasound scatterers as vectors with small magnitude and random phase in the complex plane. Others have previously performed parts of this analysis. The contribution of the present paper is to provide a single, coherent treatment emphasizing the assumptions that have to be made and the physical consequences of the models derived. This leads to insights into the interaction of monopole and dipole scattering, useful techniques for simulating and analyzing speckle statistics in the complex plane and a new expression for the normalized covariance of the analytic RF ultrasound signal in terms of the complex envelope of the point-spread function.

Ultrasound attenuation measurement in the presence of scatterer variation for reduction of shadowing and enhancement

Pulse-echo ultrasound display relies on many assumptions that are known to be incorrect. Departure from these makes interpretation of conventional ultrasound images difficult, and three-dimensional (3-D) visualizations harder still. For instance, shadowing and enhancement are the result of an incorrect assumption that sound attenuation is a function only of depth. Attempts to reduce such artefacts by estimating attenuation locally have been frustrated by large statistical variations and the influence of scatterer type. We address the latter by examining the influence of scatterer type on two existing attenuation estimation algorithms. This analysis is novel for one of the algorithms, and contains a correction to previously published work for the other. We then propose a novel algorithm that is less sensitive to scatterer variation. We also present a novel technique for handling large statistical variations based on combined assumptions of monotonicity and smoothness. We then assess the performance of each algorithm for correcting shadowing and enhancement in in vitro data, using a real time 3-D radio frequency (RF) ultrasound acquisition system developed for this purpose. The results show visible differences in attenuation estimates from each technique, which are supported by the theoretical analysis. The novel attenuation estimation algorithm does show less sensitivity to scatterer variation, though it results in a more noisy estimate. Nevertheless, the novel technique for reducing statistical variations is sufficient to allow some degree of correction of shadowing and enhancement in each case.

Processing and visualizing three-dimensional ultrasound data

This paper describes techniques for the visualization and processing of three-dimensional (3D) ultrasound data. The nature of such data demands specialized algorithms, which differ from those employed for other medical imaging modalities. In this paper, the emphasis is placed on generic processing techniques, which are relevant across a wide range of 3D ultrasound application domains.

Freehand 3D ultrasound without voxels: volume measurement and visualisation using the Stradx system

This paper describes recent developments in the Stradx freehand 3D ultrasound system. Unlike other systems, Stradx works directly from the raw B-scans and their relative positions, without first resampling this unstructured data onto a regular voxel array. The paper discusses the many advantages of this unique approach, and presents new developments in the visualisation and quantitative analysis of freehand 3D ultrasound data, including novel volume rendering schemes and a robust method to compensate for the effects of varying probe pressure.

3D ultrasound measurement of large organ volume

Freehand 3D ultrasound is particularly appropriate for the measurement of organ volumes. For small organs, which can be fully examined with a single sweep of the ultrasound probe, the results are known to be much more accurate than those using conventional 2D ultrasound. However, large or complex shaped organs are difficult to quantify in this manner because multiple sweeps are required to cover the entire organ. Typically, there are significant registration errors between the various sweeps, which generate artifacts in an interpolated voxel array, making segmentation of the organ very difficult. This paper describes how sequential freehand 3D ultrasound, which does not employ an interpolated voxel array, can be used to measure the volume of large organs. Partial organ cross-sections can be segmented in the original B-scans, and then combined, without the need for image-based registration, to give the organ volume. The inherent accuracy (not including position sensor and segmentation errors) is demonstrated in simulation to be within +/- 2%. The in vivo precision of the complete system is demonstrated (by repeated observations of a human liver) to be +/- 5%.