Accurate Density Measurements Research Articles

A machine learning method for precise detection of spine bone mineral density

Osteoporosis is prevalent among the elderly and requires precise diagnostic approaches for effective treatment and prevention. This work introduces a machine learning-based method for the accurate grading of osteoporosis via the analysis of high-resolution computed tomography (HRCT) images of the spine. This approach allows for the precise extraction of the trabecular component of vertebral bodies, thereby enabling accurate measurement of bone density. Evaluated in 183 individuals, our method demonstrated enhanced stability in bone density prediction and reduced bias when juxtaposed with traditional random sampling techniques. Despite the inherent risk of overestimation, the machine learning model more accurately approximates the actual bone quality compared to conventional clinical methods, which typically involve the random extraction of 3–4 trabecular bone slices from the spine. These findings offer a novel approach to the clinical assessment of osteoporosis, underscoring the significant potential of integrating machine learning into existing medical image analysis workflows.

Progress of CO2 Dispersion Interferometer on EAST

A CO2 Dispersion Interferometer (DI) system on the Experimental Advanced Superconducting Tokamak (EAST) was successfully operated, providing plasma electron density measurements. The DI system utilizes a continuous-wave 9.3 μm CO2 laser source to measure line-averaged electron densities. This offers significant advantages, including the ability to minimize fringe jumps and insensitivity to mechanical vibrations. These characteristics are well-suited for future high-density, long-pulse plasma discharges. The DI system provides a real-time density feedback signal to the plasma control system for routine density control during long-pulse operation. Experiments with EAST demonstrated good agreement between the density obtained by the DI system and the preset densities. The DI system also exhibited stability during long-pulse discharge. Moreover, the DI system was stable during rapid density changes and high-density pellet injections. In shot No. 120594, the DI system exhibited stable density feedback during continuous projectile injection lasting over 50 seconds; the line-averaged electron density is approximately 4×1019 m-3. In contrast to the long-wavelength source interferometer, which may deflect light from the detector owing to excessive refraction angles in larger density-gradient discharges, the DI ensured accurate density measurements. The DI system on EAST is dependable for accurately measuring the electron density.

Annotated dataset for training deep learning models to detect astrocytes in human brain tissue

Astrocytes, a type of glial cell, significantly influence neuronal function, with variations in morphology and density linked to neurological disorders. Traditional methods for their accurate detection and density measurement are laborious and unsuited for large-scale operations. We introduce a dataset from human brain tissues stained with aldehyde dehydrogenase 1 family member L1 (ALDH1L1) and glial fibrillary acidic protein (GFAP). The digital whole slide images of these tissues were partitioned into 8730 patches of 500 × 500 pixels, comprising 2323 ALDH1L1 and 4714 GFAP patches at a pixel size of 0.5019/pixel, furthermore 1382 ADHD1L1 and 311 GFAP patches at 0.3557/pixel. Sourced from 16 slides and 8 patients our dataset promotes the development of tools for glial cell detection and quantification, offering insights into their density distribution in various brain areas, thereby broadening neuropathological study horizons. These samples hold value for automating detection methods, including deep learning. Derived from human samples, our dataset provides a platform for exploring astrocyte functionality, potentially guiding new diagnostic and treatment strategies for neurological disorders.

Real-Time Unmanned Aerial Vehicle-Based Traffic State Estimation for Multi-Regional Traffic Networks

Traffic state estimation is a challenging task because of the collection of sparse and noisy measurements from fixed points in the traffic network. Induction loops, as they are non-intrusive, can observe any area of the traffic network on demand and provide accurate traffic density and speed measurements. Our main contribution is the development of an optimization framework where small parts of the traffic network are monitored by Unmanned Aerial Vehicles (UAVs) and accurate estimates of traffic density and mean speeds for every region in the traffic network are returned in real-time. Assuming regional-based traffic dynamics, a cyclical UAV flight path is defined for each region. One UAV is assigned to each flight path and monitors a small area of the region below. The UAV-based traffic measurements are expressed as moving averages to smooth out fluctuations in traffic density and mean speed. A moving horizon optimization problem is formulated, which minimizes the estimation and process errors over a moving time window. The problem is non-convex and challenging to solve, because of the presence of nonlinear traffic dynamics. By considering free-flow conditions, the optimization problem is recast to a quadratic program that returns density estimations for each region of the traffic network in real-time. Simulation results compare our UAV framework to an alternative, where the whole traffic network is monitored by UAVs. Both frameworks obtain similar results, despite the alternative framework using more UAVs than our framework.

Density measurement and uncertainty evaluation of elemental and alloy liquids using electrostatic levitation

Liquid density is a crucial parameter in physical models, numerical simulations, and a key thermophysical property essential for understanding various physical phenomena. Although density measurements of liquid metals have been carried out with various methods, it is still hard to give consistent and precise results, particularly at high temperatures. In this study, we systematically perform the precise density measurements for 34 elemental and alloy liquids using electrostatic levitation (ESL). Through a comprehensive review of density data in the literature, we propose recommended density values for fourteen transition metal liquids. Notably, we observe significant discrepancies in density measurements between ESL and electromagnetic levitation (EML). After conducting careful uncertainty evaluation and error analysis, the discrepancies are attributed to the shape deformation of the liquids, which seriously influences the density and its temperature coefficient measurements. The present work not only provides high-quality density data but also helps to develop standards for archiving density datasets and improve the density measurements of high-temperature molten melts.

The effect of forearm rotation on the bone mineral density measurements of the distal radius.

Forearm dual-energy X-ray absorptiometry (DXA) is often performed in clinics where central DXA is unavailable. Accurate bone mineral density (BMD) measurement is crucial for clinical assessment. Forearm rotation can affect BMD measurements, but this effect remains uncertain. Thus, we aimed to conduct a simulation study using CT images to clarify the effect of forearm rotation on BMD measurements. Forearm CT images of 60 women were analyzed. BMD was measured at the total, ultra-distal (UD), mid-distal (MD), and distal 33% radius regions with the radius located at the neutral position using digitally reconstructed radiographs generated from CT images. Then, the rotation was altered from - 30° to 30° (supination set as positive) with a one-degree increment, and the percent BMD changes from the neutral position were quantified for all regions at each angle for each patient. The maximum mean BMD changes were 5.8%, 7.0%, 6.2%, and 7.2% for the total, UD, MD, and distal 33% radius regions, respectively. The analysis of the absolute values of the percent BMD changes from the neutral position showed that BMD changes of all patients remained within 2% when the rotation was between - 5° and 7° for the total region, between - 3° and 2° for the UD region, between - 4° and 3° for the MD region, and between - 3° and 1° for the distal 33% radius region. Subtle rotational changes affected the BMD measurement of each region. The results showed the importance of forearm positioning when measuring the distal radius BMD.

Design of a Tree Micro Drill Instrument to Improve the Accuracy of Wood Density Estimation

To improve the estimation accuracy of wood density and study the linear correlation between drill feed resistance and wood density, a new micro drill instrument prototype that can simultaneously measure the rotation resistance and feed resistance of the drill needle was designed. The test tree species included hard and soft broad-leaved trees and coniferous trees, and the absolute dry density of each wood sample was measured. The drill resistance data were tested by our newly proposed prototype and a Resistograph 650-SC, and four linear models were established to define the relation between drill resistance and the absolute dry density of the wood. The results showed that (1) the statistical indicators of each model for our proposed prototype were better than the corresponding indicators of the Resistograph 650-SC for three of the four species tested; (2) the coefficient of determination of the linear regression model between the feed resistance of our proposed prototype and the absolute dry density of wood was 0.946; and (3) the statistical indicators of the model that included rotation resistance and feed resistance were better than those of the model that only including rotation resistance. Although the proposed prototype produced a competitive level of accuracy and explicitly demonstrated that including feed resistance improved wood density measurement accuracy, the prototype should be considered a first iteration as further hardware design changes and in-forest performance assessments across wider diverse set of test species are required before a conclusive evaluation can be rendered.

Density and surface tension measurements of molten Al–Si based alloys

AbstractThis study is part of a series of studies aimed at measuring the thermophysical properties of molten phase change material-type metallic thermal energy storage materials near 873 K (600°C). The target material is Al–Si based alloys. First, as a feasibility study, density measurements of the molten state of three Al–Si binary alloys (Al–12.2Si, Al–50Si and Al–90Si in atomic%) were performed. A highly accurate non-contact density measurement method based on the static magnetic field superposition electromagnetic levitation (EML) method was employed as the density measurement method. The validity of this experimental method was confirmed, and density of molten Al–Si base alloys (ADC12 and Al–5.9mass%Si–1.6mass%Fe) were measured as a function of temperature with an expanded uncertainty of 1.2%. In addition, the surface tension of the alloys was measured by the droplet oscillation method using the EML technique. The surface tension was successfully obtained as a function of temperature with expanded uncertainty of 2.3%.

Review of SIRIO interferometer experimental results

The SIRIO (Scanning InfraRed Interferometer) interferometer [1], recently disassembled together with the FTU (Frascati Tokamak Upgrade) experiment [2], worked continuously from 2004 to 2019.An extremely important contribution was made in all the experiments conducted on this tokamak. By virtue of its characteristics, in terms of spatial (1 cm) and temporal resolution (density profiles every 62 μs), combined with its capability to scan the entire plasma column. This interferometer produced all the density feedbacks for operations. Above all, it collected accurate density measurements in plasma physics, among the best data of all tokamak interferometers.In this review, it is reported the highly valuable experimental work of this powerful diagnostics. Indeed, high density observations were analyzed, as well as fast variations were measured; some examples: the detection of plasma instabilities (MARFE), the trace and the speed of the pellets, the measurement of the particle transport efficiencies in important transients etc.In order to improve the knowledge for future interferometry in plasma density measurements projects, some topics related to data analysis are also exposed, as well as local density reconstruction methods.

Accurate measurement of effective atomic number and electron density with X-ray attenuation coefficient spectrum

Energy spectra of X-ray attenuation coefficients, μ(E)s, are measured using a system comprising a laboratory X-ray source and a photon-counting-type detector with an accuracy of 3% or less. We propose a method to derive the electron density (ρe) and effective atomic number (Zeff) of an object from measured μ(E) values. The method is based on a simple approximation in which an atomic cross-section of attenuation is expressed by a linear equation of Z4 and experimental calibration using standard materials. The μ(E) values of aqueous ethanol and acetic acid aqueous solutions are measured to get the ρes and Zeffs. The proposed method yielded a ρe value with an accuracy of 1.4% despite the use of standard materials, whereas it yielded a Zeff value with an accuracy of 1.1% for standard materials whose values of Z are similar to that of the sample.

Design and realization of a femtosecond-laser-inscribed fiber Bragg grating for accurate measurement of liquid level and liquid density

An exceptionally sensitive liquid level and density sensor system using Femtosecond-Laser-Inscribed Fiber Bragg Gratings is designed and demonstrated utilizing the basic Archimedes’ Law of Buoyancy. The sensor works based on principles of Archimedes’ law of buoyancy and basic strain sensitivity of Fiber Bragg Grating (FBG). A cylindrical mass of 22.5 cm long is suspended from one end of the FBG and whereas the other end of the fiber is fixed. The mass is partially immersed into the liquid under consideration to measure the liquid level as well as liquid density. Following Archimedes’ law of buoyancy, the relative weight of the suspended mass gets reduced and the corresponding shift in Bragg wavelength is measured using an interrogator connected at the fixed end of the sensor lead fiber. The relative weight of the immersed mass also depends on the liquid density. Therefore, a change in liquid density also is reflected by the shift in Bragg wavelength. The system can be calibrated to measure the accurate liquid level and liquid density. A liquid (water) level measurement sensitivity of 5.47 to 5.60 pm/mm is achieved using the system under three times of consecutive experiments which is very close to the simulated value (5.9 pm/mm). A density measurement sensitivity of ∼ 0.71 nm/(gm/cm3) is calculated in this system and experimentally achieved sensitivity is ∼ 0.7 nm/(gm/cm3). The LOD (limit of detection) was also found to be 1.008 gm/cc for the density measurement and the average error during the measurement was 0.0021 nm/(gm/cm3).It is also shown that the density measurement sensitivity is highly dependent on the amount of immersed portion of the suspended mass and more amount of immersed mass is desirable for better sensitivity.

High power density battery chargers with fast-charging utilizing heat storage

While wide bandgap semiconductor technology, such as gallium nitride, has considerably enhanced power density in mobile battery charger applications, the development of smaller, cost- and resource-effective systems is hindered by thermal constraints arising from miniaturized components and compact housings. This work proposes a transient thermal management system that dynamically adjusts converter output power according to thermal boundaries, utilizing latent and sensible heat storage to enable an initial boosted performance. An analytical and numerical sensitivity analysis of power density limits was conducted to evaluate the impact of thermal and electrical boundary conditions. A 40W hardware prototype of a quasi-resonant flyback converter with transient thermal management was realized using epoxy resin and phase change material filling. The findings show a 40% higher effective power density when charging a conventional 50Wh laptop battery, all within the same thermal boundaries as common operation at constant output power, with a power density measurement accuracy of 5.2%. The system was implemented using PI controller for inner component and surface temperature control. This novel approach to fast-charging highlights the optimization potential of current systems through converter heat storage utilization and provides valuable insights, including analytical and numerical models, for developing chargers capable of overcoming thermal barriers.

Investigation of Microstructure and Density of Atmospheric Ice Formed by High-Wind-Speed In-Cloud Icing

In-cloud icing occurred on cables, wind turbines, and aircraft wings and may cause power transmission paralysis, energy dissipation, and unsafe flight. The study of atmospheric ice is crucial to facilitate the development of in-cloud icing prediction/detection and anti-/de-icing systems. Herein, atmospheric ice formed by high-wind-speed, in-cloud icing was obtained and reserved during icing tests in the 3 m × 2 m icing wind tunnel located at CARDC. Microstructures of atmospheric ice formed by high-wind-speed, in-cloud icing were observed and analysed using the microscopic observation method. A better description was established to explore the influence of the icing environment on ice microstructures, such as the size and shape of air bubbles and the boundaries of ice grains. Furthermore, an accurate density measurement was developed to allow a better practical density expression to consider the characteristics of the impacted surface and the effect of the flow field.

A novel constraint-based method for density measurement in cased hole

In recent years, thru-casing measurement has shown high application values in controlling risk and improving production efficiency. However, in cased-hole applications, the investigation depth of gamma density logging is significantly confined due to the impacts of casing and cement, resulting in decreased accuracy of density measurement. Furthermore, the common uncertainty associated with cement bonding quality increases the difficulty of quantitative density evaluation. In order to overcome these challenges, a new thru-casing density measurement method is proposed. The method consists of three aspects: 1) casing correction; 2) simultaneous formation and cement density calculation based on cement constraint characterization; 3) cement thickness correction. The key to the method is step 2), where cement is defined by a set of physical constraints. e.g., volumetric fractions of contaminants such as water, mud, gas. The identification of constraints enables efficient sampling in the constrained phase space and provides the optimal solution to both formation density and cement density. To obtain precise and scenario-based cement constraints, Naive Bayes classifier combined with sliding window technique is used to provide prior information on cement quality. Geant4 is employed to simulate gamma density tools and obtain their responses in various formations, casings, and cements. These models are capable of meeting statistical error requirements. Since the simulation parameters are well-defined, it is useful for validating the proposed method using Monte Carlo simulation data under varying casing, cement, and formation conditions. The method can effectively obtain formation and cement density, as indicated by the calculation error of less than 0.02 g/cm³ and 0.025 g/cm³, respectively. The method is then applied to a well in the Bohai oilfield, and the measured data is processed using the proposed method. A comparison of open-hole and cased-hole density in a 48-m well interval shows that the error of each section increases as the well condition deteriorates. The maximum RMSE is 0.027 g/cm³ in the unstable borehole section (>13.6), while minimum RMSE is 0.016 g/cm³ in the section with good cementing quality and stable borehole. The mean relative error of the entire section is 0.91% and the RMSE of cased-hole density measurement is 0.0245 g/cm³. These results demonstrate the feasibility of the proposed method in the field by effectively correcting casing and cement impacts.

Characterization of higher-order resonant cantilevers for density determination in different flowing liquids

This study investigates the sensing characteristics of micromachined electromagnetic cantilevers vibrating at different resonance orders and under static or flowing liquid immersions. The cantilever is designed with a wide-plate structure, which contributes to the modal optimization for basic and higher-order torsions. The fluid-structure interaction is used to analyze the parameterized expressions of the density and its changing sensitivity based on the cantilever’s flexural and torsional vibrations. They have successfully clarified the comprehensive factors that influence the density measurement performance. The study shows that the analytical predictions for the density changing sensitivity agree well with the experimental results. The experiments prove that the cantilever under flowing immersion appears significantly degraded in its density measurement accuracy. Higher mode and shorter length enable the cantilever to respond better density sensing behaviors under flowing immersion. These results here can be further generalized to guide the optimal design of cantilever-based resonators in flowing liquid monitoring.

Restoring morphology of light sheet microscopy data based on magnetic resonance histology.

The combination of cellular-resolution whole brain light sheet microscopy (LSM) images with an annotated atlas enables quantitation of cellular features in specific brain regions. However, most existing methods register LSM data with existing canonical atlases, e.g., The Allen Brain Atlas (ABA), which have been generated from tissue that has been distorted by removal from the skull, fixation and physical handling. This limits the accuracy of the regional morphologic measurement. Here, we present a method to combine LSM data with magnetic resonance histology (MRH) of the same specimen to restore the morphology of the LSM images to the in-skull geometry. Our registration pipeline which maps 3D LSM big data (terabyte per dataset) to MRH of the same mouse brain provides registration with low displacement error in ∼10 h with limited manual input. The registration pipeline is optimized using multiple stages of transformation at multiple resolution scales. A three-step procedure including pointset initialization, automated ANTs registration with multiple optimized transformation stages, and finalized application of the transforms on high-resolution LSM data has been integrated into a simple, structured, and robust workflow. Excellent agreement has been seen between registered LSM data and reference MRH data both locally and globally. This workflow has been applied to a collection of datasets with varied combinations of MRH contrasts from diffusion tensor images and LSM with varied immunohistochemistry, providing a routine method for streamlined registration of LSM images to MRH. Lastly, the method maps a reduced set of the common coordinate framework (CCFv3) labels from the Allen Brain Atlas onto the geometrically corrected full resolution LSM data. The pipeline maintains the individual brain morphology and allows more accurate regional annotations and measurements of volumes and cell density.

Assessing breast density using the chemical-shift encoding-based proton density fat fraction in 3-T MRI

ObjectivesThere is a clinical need for a non-ionizing, quantitative assessment of breast density, as one of the strongest independent risk factors for breast cancer. This study aims to establish proton density fat fraction (PDFF) as a quantitative biomarker for fat tissue concentration in breast MRI and correlate mean breast PDFF to mammography.MethodsIn this retrospective study, 193 women were routinely subjected to 3-T MRI using a six-echo chemical shift encoding-based water-fat sequence. Water-fat separation was based on a signal model accounting for a single T2* decay and a pre-calibrated 7-peak fat spectrum resulting in volumetric fat-only, water-only images, PDFF- and T2*-values. After semi-automated breast segmentation, PDFF and T2* values were determined for the entire breast and fibroglandular tissue. The mammographic and MRI-based breast density was classified by visual estimation using the American College of Radiology Breast Imaging Reporting and Data System categories (ACR A-D).ResultsThe PDFF negatively correlated with mammographic and MRI breast density measurements (Spearman rho: −0.74, p < .001) and revealed a significant distinction between all four ACR categories. Mean T2* of the fibroglandular tissue correlated with increasing ACR categories (Spearman rho: 0.34, p < .001). The PDFF of the fibroglandular tissue showed a correlation with age (Pearson rho: 0.56, p = .03).ConclusionThe proposed breast PDFF as an automated tissue fat concentration measurement is comparable with mammographic breast density estimations. Therefore, it is a promising approach to an accurate, user-independent, and non-ionizing breast density assessment that could be easily incorporated into clinical routine breast MRI exams.Key Points• The proposed PDFF strongly negatively correlates with visually determined mammographic and MRI-based breast density estimations and therefore allows for an accurate, non-ionizing, and user-independent breast density measurement.• In combination with T2*, the PDFF can be used to track structural alterations in the composition of breast tissue for an individualized risk assessment for breast cancer.

Re-IMAGinING the Pathway for Clinical Decision Making in Rare Lung Diseases: Moving Towards a United Vision

This industry-supported symposium was held during the European Respiratory Society (ERS) International Congress and included presentations from several internationally renowned experts in rare lung diseases. The panel discussed the need to improve clinical decision making to expedite disease recognition, prognostic prediction, and early treatment in interstitial lung disease (ILD) and alpha 1 antitrypsin (AAT) deficiency-related chronic obstructive pulmonary disease (COPD). Daiana Stolz, Clinic for Pneumology, University Hospital Freiburg, Switzerland, and Marlies S. Wijsenbeek, Erasmus University Medical Centre, Rotterdam, the Netherlands, explained that although high-resolution CT (HRCT) scans may appear similar, ILD from different causes results in significantly different patient outcomes. Therefore, image analysis and the identification of sensitive and specific biomarkers are critical to improving diagnosis and monitoring treatment response and disease progression in ILD. Charlie Strange, Medical University of South Carolina, Charleston, USA, and Gerry McElvaney, Irish Centre for Genetic Lung Disease, Dublin, Ireland, described the variability in CT-based lung density measurements used to assess the progression of emphysema in patients with AAT deficiency. Clinical trial data indicate that accurate CT lung density measurements are superior to lung function measurements and other endpoints to detect disease progression. However, Strange presented data that showed the considerable impact of acute exacerbations of COPD on CT imaging measurements. One organisation working to improve the accuracy and value of imaging data in lung diseases is the Open Source Imaging Consortium (OSIC), Saugatuck, Michigan, USA. Elizabeth Estes, who works for OSIC, explained that OSIC aims to build a large, global database of anonymised patient data and CT images in ILD, with plans for future expansion into other rare lung diseases. The ultimate goals of this effort are to encourage collaboration, and to develop machine learning algorithms to improve clinical decision making in rare lung diseases.

Deep-learning image reconstruction for image quality evaluation and accurate bone mineral density measurement on quantitative CT: A phantom-patient study.

Background and purposeTo investigate the image quality and accurate bone mineral density (BMD) on quantitative CT (QCT) for osteoporosis screening by deep-learning image reconstruction (DLIR) based on a multi-phantom and patient study.Materials and methodsHigh-contrast spatial resolution, low-contrast detectability, modulation function test (MTF), noise power spectrum (NPS), and image noise were evaluated for physical image quality on Caphan 500 phantom. Three calcium hydroxyapatite (HA) inserts were used for accurate BMD measurement on European Spine Phantom (ESP). CT images were reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction-veo 50% (ASiR-V50%), and three levels of DLIR(L/M/H). Subjective evaluation of the image high-contrast spatial resolution and low-contrast detectability were compared visually by qualified radiologists, whilst the statistical difference in the objective evaluation of the image high-contrast spatial resolution and low-contrast detectability, image noise, and relative measurement error were compared using one-way analysis of variance (ANOVA). Cohen’s kappa coefficient (k) was performed to determine the interobserver agreement in qualitative evaluation between two radiologists.ResultsOverall, for three levels of DLIR, 50% MTF was about 4.50 (lp/cm), better than FBP (4.12 lp/cm) and ASiR-V50% (4.00 lp/cm); the 2 mm low-contrast object was clearly resolved at a 0.5% contrast level, while 3mm at FBP and ASiR-V50%. As the strength level decreased and radiation dose increased, DLIR at three levels showed a higher NPS peak frequency and lower noise level, leading to leftward and rightward shifts, respectively. Measured L1, L2, and L3 were slightly lower than that of nominal HA inserts (44.8, 95.9, 194.9 versus 50.2, 100.6, 199.2mg/cm3) with a relative measurement error of 9.84%, 4.08%, and 2.60%. Coefficients of variance for the L1, L2, and L3 HA inserts were 1.51%, 1.41%, and 1.18%. DLIR-M and DLIR-H scored significantly better than ASiR-V50% in image noise (4.83 ± 0.34, 4.50 ± 0.50 versus 4.17 ± 0.37), image contrast (4.67 ± 0.73, 4.50 ± 0.70 versus 3.80 ± 0.99), small structure visibility (4.83 ± 0.70, 4.17 ± 0.73 versus 3.83 ± 1.05), image sharpness (3.83 ± 1.12, 3.53 ± 0.90 versus 3.27 ± 1.16), and artifacts (3.83 ± 0.90, 3.42 ± 0.37 versus 3.10 ± 0.83). The CT value, image noise, contrast noise ratio, and image artifacts in DLIR-M and DLIR-H outperformed ASiR-V50% and FBP (P<0.001), whilst it showed no statistically significant between DLIR-L and ASiR-V50% (P>0.05). The prevalence of osteoporosis was 74 (24.67%) in women and 49 (11.79%) in men, whilst the osteoporotic vertebral fracture rate was 26 (8.67%) in women and (5.29%) in men.ConclusionImage quality with DLIR was high-qualified without affecting the accuracy of BMD measurement. It has a potential clinical utility in osteoporosis screening.

The Effect of Region of Interest on Measurement of Bone Mineral Density of the Proximal Femur: Simulation Analysis Using CT Images.

While accurate measurement of bone mineral density (BMD) is essential in the diagnosis of osteoporosis and in evaluating the treatment of osteoporosis, it is unclear how region of interest (ROI) settings affect measurement of BMD at the total proximal femur region. In this study, we performed a simulation analysis to clarify the effect on BMD measurement of changing the ROI using hip computed tomography (CT) images of 75 females (mean age, 62.4years). Digitally reconstructed radiographs of the proximal femur region were generated from CT images to calculate the change in BMD when the proximal boundary of the ROI was altered by 0-10mm, and when the distal boundary of the ROI was altered by 0-30mm. Further, changes in BMD were compared across BMD classification groups. A mean BMD increase of 0.62% was found for each 1-mm extension of the distal boundary. A mean BMD decrease of 0.18% was found for each 1-mm alteration of the proximal boundary. Comparing BMD classification groups, patients with osteoporosis and osteopenia demonstrated greater BMD changes than patients with normal BMD for the distal boundary (0.68%, 0.64%, and 0.54%, respectively) and patients with osteoporosis demonstrated greater BMD changes than patients with osteoporosis and normal BMD for the proximal boundary (0.37%, 0.13%, and 0.03%, respectively). In conclusion, our study found that a consistent ROI setting, especially on the distal boundary, is necessary for the accurate measurement of total proximal femur BMD. Based on the findings, we recommend confirming that the ROI setting shown on the BMD result form is consistent with changes in serial BMD.