User-defined Region Of Interest Research Articles

ColocZStats: a z-stack signal colocalization extension tool for 3D slicer.

Confocal microscopy has evolved to be a widely adopted imaging technique in molecular biology and is frequently utilized to achieve accurate subcellular localization of proteins. Applying colocalization analysis on image z-stacks obtained from confocal fluorescence microscopes is a dependable method of revealing the relationship between different molecules. In addition, despite the established advantages and growing adoption of 3D visualization software in various microscopy research domains, there have been few systems that can support colocalization analysis within a user-specified region of interest (ROI). In this context, several broadly employed biological image visualization platforms are meticulously explored in this study to understand the current landscape. It has been observed that while these applications can generate three-dimensional (3D) reconstructions for z-stacks, and in some cases transfer them into an immersive virtual reality (VR) scene, there is still little support for performing quantitative colocalization analysis on such images based on a user-defined ROI and thresholding levels. To address these issues, an extension called ColocZStats (pronounced Coloc-Zee-Stats) has been developed for 3D Slicer, a widely used free and open-source software package for image analysis and scientific visualization. With a custom-designed user-friendly interface, ColocZStats allows investigators to conduct intensity thresholding and ROI selection on imported 3D image stacks. It can deliver several essential colocalization metrics for structures of interest and produce reports in the form of diagrams and spreadsheets.

Traffic Monitoring from the Perspective of an Unmanned Aerial Vehicle

The paper is focused on the development of the experimental web-based solution for image processing from the perspective of an Unmanned Aerial Vehicle (UAV). Specifically, the research is carried out as part of the broader study on drone utilization in traffic at the Technical University of Kosice. This contribution explores the possibility of using the UAV as a tool to detect the temporal state of the traffic in multiple locations. Road traffic analysis is enabled through the detection of vehicles from the user-defined region of interest (ROI). Its content then serves as the input for motion detection, followed by the detection of vehicles using the YOLOv4 model. Detection of other types of objects is possible, thus making the system more universal. The vehicle is tracked after recognition in two consecutive frames. The tracking algorithm is based on the calculation of the Euclidean distance and the intersection of the rectangles. The experimental verification yields lower hardware requirements for CPU and GPU by about two FPS when using optimization techniques, such as ROI or reference dimensions of objects. The accuracy of detection and the subsequent tracking of cars reaches almost 100% while providing accurate trajectory determination.

Spatial frequency analysis detects altered tissue organization following hamstring strain injury at time of injury but not return to sport

BackgroundHamstring strain injury (HSI) diagnosis is often corroborated using ultrasound. Spatial frequency analysis (SFA) is a quantitative ultrasound method that has proven useful in characterizing altered tissue organization. The purpose of this study was to determine changes in muscular tissue organization using SFA following HSI.MethodsUltrasound B-mode images were captured at time of injury (TOI) and return to sport (RTS) in collegiate athletes who sustained an HSI. Spatial frequency parameters extracted from two-dimensional Fourier Transforms in user-defined regions of interest (ROI) were analyzed. Separate ROIs encompassed injured and adjacent tissue within the same image of the injured limb and mirrored locations in the contralateral limb at TOI. The ROIs for RTS images were drawn to correspond to the injury-matched location determined from TOI imaging. Peak spatial frequency radius (PSFR) and the fascicular banded pattern relative to image background (Mmax%) were compared between injured and adjacent portions within the same image with separate paired t-tests. Within-image differences of SFA parameters in the injured limb were calculated and compared between TOI and RTS with Wilcoxon rank sum tests.ResultsWithin the injured limb at TOI, PSFR differences in injured and healthy regions did not strictly meet statistical significance (p = 0.06), while Mmax% was different between regions (p < 0.001). No differences were observed between regions in the contralateral limb at TOI (PSFR, p = 0.16; Mmax%, p = 0.30). Significant within-image differences in PSFR (p = 0.03) and Mmax% (p = 0.04) at RTS were detected relative to TOI.ConclusionsThese findings are a first step in determining the usefulness of SFA in muscle injury characterization and provide quantitative assessment of both fascicular disruption and edema presence in acute HSI.

Perspective registration and multi-frame super-resolution of license plates in surveillance videos

One task often encountered in surveillance videos is the recognition of a target—e.g. the license plate of a vehicle. Often, the quality of a single video frame does not permit a reliable recognition. If multiple frames are available, it is possible to combine them in order to generate a single image with lower noise (frame averaging) and/or higher resolution (super-resolution). In order for these techniques to work, it is necessary to accurately estimate the motion of the object of interest in the recorded footage.In this paper, we introduce a method capable of accurately computing the perspective transformation that describes the motion of a planar object. The method minimizes the squared distance between the transformed image and a reference, computed over a user-defined region of interest, and uses the partial derivatives in order to significantly speed up the computation. This approach is inspired by the well known Kanade–Lucas–Tomasi feature tracker.

Bitmap generation from computer-aided design for potential layer-quality evaluation in electron beam additive manufacturing

PurposeElectron beam additive manufacturing (EBAM) is a popular additive manufacturing (AM) technique used by many industrial sectors. In EBAM process monitoring, data analysis is focused on information extraction directly from the raw data collected in-process, i.e. thermal/optical/electronic images, and the comparison between the collected data and the computed tomography/microscopy images generated after the EBAM process. This paper aims to postulate that a stack of bitmaps could be generated from the computer-aided design (CAD) at a range of Z heights and user-defined region of interest during file preparation of the EBAM process, and serve as a reference image set.Design/methodology/approachComparison between that and the workpiece images collected during the EBAM process could then be used for quality assessment purposes. In spite of the extensive literature on CAD slicing and contour generation for AM process preparation, the method of bitmap generation from the CAD model at different field of views (FOVs) has not been disseminated in detail. This article presents a piece of custom CAD-bitmap generation software and an experiment demonstrating the application of the software alongside an electronic imaging system prototype.FindingsResults show that the software is capable of generating binary bitmaps with user-defined Z heights, image dimensions and image FOVs from the CAD model; and can generate reference bitmaps to work with workpiece electronic images for potential pixel-to-pixel image comparison.Originality/valueIt is envisaged that this CAD-bitmap image generation ability opens up new opportunities in quality assessment for the in-process monitoring of the EBAM process.

Deformable registration and region-of-interest image reconstruction in sparse repeat CT scanning.

Repeat CT scanning is ubiquitous in many clinical situations, e.g. to follow disease progression, to evaluate treatment efficacy, and to monitor interventional CT procedures. However, it incurs in cumulative radiation to the patient which can be significantly reduced by using a region of interest (ROI) and the existing baseline scan. To obtain a high-quality reconstruction of a ROI with a significantly reduced X-ray radiation dosage that accounts for deformations. We present a new method for deformable registration and image reconstruction inside an ROI in repeat CT scans with a highly reduced X-ray radiation dose based on sparse scanning. Our method uses the existing baseline scan data, a user-defined ROI, and a new sparse repeat scan to compute a high-quality repeat scan ROI image with a significantly reduced radiation dose. Our method first performs rigid registration between the densely scanned baseline and the sparsely scanned repeat CT scans followed by deformable registration with a low-order parametric model, both in 3D Radon space and without reconstructing the repeat scan image. It then reconstructs the repeat scan ROI without computing the entire repeat scan image. Our experimental results on clinical lung and liver CT scans yield a mean × 14 computation speedup and a × 7.6-12.5 radiation dose reduction, with a minor image quality loss of 0.0157 in the NRMSE metric. Our method is considerably faster than existing methods, thereby enabling intraoperative online repeat scanning that it is accurate and accounts for position, deformation, and structure changes at a fraction of the radiation dose required by existing methods.

GeoMx™ RNA Assay: High Multiplex, Digital, Spatial Analysis of RNA in FFPE Tissue.

RNA in situ hybridization (ISH) is a widely used technique for the localization of mRNA in tissues. Limitations to traditional ISH include the number of targets that can be analyzed concurrently and the ability for many of these assays to be used in formalin-fixed, paraffin-embedded tissues (FFPE). Here, we describe the GeoMx™ RNA assay that is capable of the highly multiplexed detection of mRNA targets in FFPE tissues. This assay utilizes ISH probes linked to indexing oligo barcodes via a photocleavable linker and the GeoMx Digital Spatial Profiler (DSP) Instrument to enable profiling of RNA targets in a region-of-interest-based method. In brief, 5μm FFPE sections are dewaxed, target retrieved, digested with proteinase K, post-fixed, and then incubated overnight with GeoMx RNA detection probes. Stringent washes are performed followed by the addition of fluorescently labeled antibodies for use as morphology markers. User-defined regions of interest are then profiled on the GeoMx DSP through region-specific cleaving and collecting the photocleaved indexing oligos. Cleaved indices are then quantified using NanoString nCounter® Technology generating digital quantification of RNA expression with spatial context.

Abstract B006: Gridded tissue profiling strategy with digital spatial profiling for unbiased tissue sampling

Abstract Characterization of the spatial distribution and abundance of protein and RNAs within a tissue enables deep understanding of biologic systems. The ability to interrogate multiple targets simultaneously from clinical samples enhances the potential for discovery, but has proven to be challenging for formalin fixed paraffin embedded (FFPE) tissue. NanoString Technologies® has developed the Digital Spatial Profiling (DSP) platform to enable highly multiplexed profiling of protein or RNA from FFPE tissue using a non-destructive protocol. This technology can be used to quantify the abundance of targets within user-defined regions of interest (ROI) using a variety of masking strategies to select and define those regions, including geometric, phenotypic, or automatically generated masks based on expression of certain markers within the tissue. The current technology is capable of profiling dozens of targets, and future iterations could enable hundreds or thousands of targets to be profiled simultaneously. Controlling ROI size, shape, and features defines the heterogeneity and granularity of the information generated. To date, studies on the DSP have largely focused on profiling regions of interest in a nonsystematic way. However, profiling a tissue in a gridded fashion enables a uniform sampling of protein expression either across a whole tissue section or within a smaller area of the tissue to enable nonbiased evaluation, which may aid in biomarker discovery. This study utilizes DSP and a gridded ROI selection strategy to profile protein distribution within normal and tumor tissue. FFPE tissue from tonsil or colorectal tumors are stained with a 44-plex cocktail of antibodies conjugated to unique DNA oligos via a photocleavable linker and up to 3 fluorescent antibodies. Visual images of the tissue are collected with the fluorescent antibodies, and selected regions of interest are subsequently illuminated with UV light to release the oligos for collection. ROIs are profiled serially and captured oligos are then quantitated in the standard NanoString assay. In this study, tonsil and colorectal cancer (CRC) tissue is profiled on the DSP platform using a gridded ROI selection strategy to collect protein profiles from an entire tissue section either via low-resolution sampling or from specific regions within the tissue via high-resolution sampling. Low-resolution sampling of the tissue provides an estimate of the protein distribution across a section of tonsil or CRC. It further enables identification of regions of interest within the tumor suitable for deeper profiling with the high-resolution approach. The higher resolution profiling enables reconstruction of the tissue morphology at the molecular level by looking solely at the distribution of proteins. A distinct protein profiles for the germinal centers and T-cell zones within lymph nodes. Furthermore, we see variations emerges of protein expression between different lymph nodes that may contribute to different biologic functionality. Similarly, in CRC tissue, we see protein profiles that distribute uniquely between the tumor and the tumor microenvironment. For example, there is highly localized expression of immune cell type markers in particular, discrete regions of the tissue rather than distributed throughout the tumor microenvironment, and strong expression of pathways know to be involved in tumor growth/progression distributed to tumor-rich region of the tissue. Furthermore, there appears to be expression of select immune checkpoint molecules (e.g., PD-L1 and TIM3) in regions of the tissue that are predominantly tumor. Whether this represents tumor infiltration by immune cells or aberrant expression of the checkpoint molecules remains to be determined. These results demonstrate the utility of a gridded ROI selection strategy for deep profiling of tissue in an unbiased way to interrogate the immune biology within FFPE tissue using the NanoString DSP platform. Citation Format: Sarah Church, Chris Merritt, Giang Ong, Andrew White, Kristi Zevin, Sarah Warren, Joseph M. Beechem. Gridded tissue profiling strategy with digital spatial profiling for unbiased tissue sampling [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B006.

Dosimetric Impact of MRI Distortions: A Study on Head and Neck Cancers

To evaluate the effect of magnetic resonance (MR) imaging (MRI) geometric distortions on head and neck radiation therapy treatment planning (RTP) for an MRI-only RTP. We also assessed the potential benefits of patient-specific shimming to reduce the magnitude of MR distortions for a 3-T scanner. Using an in-house Matlab algorithm, shimming within entire imaging volumes and user-defined regions of interest were simulated. We deformed 21 patient computed tomography (CT) images with MR distortion fields (gradient nonlinearity and patient-induced susceptibility effects) to create distorted CT (dCT) images using bandwidths of 122 and 488Hz/mm at 3T. Field parameters from volumetric modulated arc therapy plans initially optimized on dCT data sets were transferred to CT data to compute a new plan. Both plans were compared to determine the impact of distortions on dose distributions. Shimming across entire patient volumes decreased the percentage of voxels with distortions of more than 2mm from 15.4% to 2.0%. Using the user-defined region of interest (ROI) shimming strategy, (here the Planning target volume (PTV) was the chosen ROI volume) led to increased geometric for volumes outside the PTV, as such voxels within the spinal cord with geometric shifts above 2 mm increased from 11.5% to 32.3%. The worst phantom-measured residual system distortions after 3-dimensional gradient nonlinearity correction within a radial distance of 200mm from the isocenter was 2.17mm. For all patients, voxels with distortion shifts of more than 2mm resulting from patient-induced susceptibility effects were 15.4% and 0.0% using bandwidths of 122Hz/mm and 488Hz/mm at 3T. Dose differences between dCT and CT treatment plans in D50 at the planning target volume were 0.4%±0.6% and 0.3%±0.5% at 122 and 488Hz/mm, respectively. The overall effect of MRI geometric distortions on data used for RTP was minimal. Shimming over entire imaging volumes decreased distortions, but user-defined subvolume shimming introduced significant errors in nearby organs and should probably be avoided.

Pilot study on renal magnetic resonance diffusion tensor imaging: are quantitative diffusion tensor imaging values useful in the evaluation of children with ureteropelvic junction obstruction?

Ureteropelvic junction (UPJ) obstruction is a common cause of renal injury in children. Indications for surgery are still controversial. Currently, there is no threshold to differentiate patients with suspected UPJ obstruction requiring surgery from the ones that do not, or to predict renal outcome after surgery. Several studies have demonstrated that diffusion tensor imaging (DTI) results may correlate with microstructural changes in the kidneys. To evaluate the feasibility of using DTI to identify UPJ obstruction kidneys. We analyzed functional MR urography (fMRU) with renal DTI (b=0 and b=400, 20 directions, 1.5Tesla, no respiratory triggering) in 26 kidneys of 19 children (mean age: 6.15years) by comparing 13 kidneys with UPJ obstruction configuration that underwent pyeloplasty following the fMRU, and 13 anatomically normal age- and gender-matched kidneys. DTI tractography was reconstructed using a fractional anisotropy threshold of 0.10 and an angle threshold of 55°. User-defined regions of interest (ROIs) of the renal parenchyma (excluding collecting system) were drawn to quantify DTI parameters: fractional anisotropy, apparent diffusion coefficient (ADC), track length and track volume. The failure rate was evaluated. All DTI parameters changed with age; fractional anisotropy decreased (P<0.032). Track volume and track length increased (P<0.05). ADC increased with age in normal kidneys (P<0.001) but not in UPJ obstruction kidneys (P=0.11). After controlling for age, the fractional anisotropy (UPJ obstruction mean: 0.18, normal kidney mean: 0.21; P=0.001) and track length (UPJ obstruction mean: 11.9mm, normal kidney mean: 15.4mm; P<0.001) were lower in UPJ obstruction vs. normal kidneys. There was a trend toward a higher ADC in UPJ obstruction kidneys vs. normal kidneys (P=0.062). The failure rate in UPJ obstruction kidneys due to technical limitations of DTI was 13/26 (50%). We demonstrated that fractional anisotropy is lower in UPJ obstruction than in normal kidneys. It is necessary to improve this technique to increase the success rate and to perform more studies to evaluate if a decrease in fractional anisotropy can differentiate UPJ obstruction kidneys from hydronephrotic kidneys without UPJ obstruction.

Array Designer: automated optimized array design for functional near-infrared spectroscopy.

.The position of each source and detector “optode” on the scalp, and their relative separations, determines the sensitivity of each functional near-infrared spectroscopy (fNIRS) channel to the underlying cortex. As a result, selecting appropriate scalp locations for the available sources and detectors is critical to every fNIRS experiment. At present, it is standard practice for the user to undertake this task manually; to select what they believe are the best locations on the scalp to place their optodes so as to sample a given cortical region-of-interest (ROI). This process is difficult, time-consuming, and highly subjective. Here, we propose a tool, Array Designer, that is able to automatically design optimized fNIRS arrays given a user-defined ROI and certain features of the available fNIRS device. Critically, the Array Designer methodology is generalizable and will be applicable to almost any subject population or fNIRS device. We describe and validate the algorithmic methodology that underpins Array Designer by running multiple simulations of array design problems in a realistic anatomical model. We believe that Array Designer has the potential to end the need for manual array design, and in doing so save researchers time, improve fNIRS data quality, and promote standardization across the field.

Effect of two different therapeutic interventions: SRT in comparison to ERT on immune aspects and bone involvement in Gaucher disease

The flow-induced vibration of bluff bodies is an important problem of many marine, civil, or mechanical engineers. In the design phase of such structures, it is vital to obtain good predictions of the fluid forces acting on the structure. Current methods rely on computational fluid dynamic simulations (CFD), with a too high computational cost to be effectively used in the design phase or for control applications. Alternative methods use heuristic mathematical models of the fluid forces, but these lack the accuracy (they often assume the system to be linear) or flexibility to be useful over a wide operating range.In this work we show that it is possible to build an accurate, flexible and low-computational-cost mathematical model using nonlinear system identification techniques. This model is data driven: it is trained over a user-defined region of interest using data obtained from experiments or simulations, or both. Here we use a Van der Pol oscillator as well as CFD simulations of an oscillating circular cylinder to generate the training data. Then a discrete-time polynomial nonlinear state-space model is fit to the data. This model relates the oscillation of the cylinder to the force that the fluid exerts on the cylinder. The model is finally validated over a wide range of oscillation frequencies and amplitudes, both inside and outside the so-called lock-in region. We show that forces simulated by the model are in good agreement with the data obtained from CFD.

Abstract 3728: Imaging biomarkers of aromatase-inhibitor induced joint pain

Abstract Estrogen receptor positive (ER+) breast cancer patients undergoing treatment with aromatase inhibitors (AI) tend to discontinue the supplement when to painful side effects appear. It is believed that women with AI-induced musculoskeletal syndrome (AIMSS) have specific physiological conditions that differentiate them from women with normal aging-related inflammatory processes (e.g., rheumatoid arthritis or RA). Ultrasound shear wave elastography (USWE) provides a real-time, quantitative assessment of the elastic modulus of soft tissue, which is a potential biomarker that is altered in women with AIMSS. Because USWE is a completely noninvasive technique available on state-of-the-art clinical ultrasound scanners, it can be readily applied to study patients who undergo AI treatment and help predict adverse effects during therapy. A Siemens s3000 clinical scanner and 9 MHz linear probe were used for USWE of the hands and wrists in postmenopausal women on AI, postmenopausal women with RA and healthy postmenopausal women. The scans included an evaluation of major wrist tendons, nerve, and joints with shear wave velocities ranging from 0.5 to 15 m/s, which are directly related to the local shear modulus – an absolute measure of tissue stiffness. The ultrasound images and raw shear wave data were then analyzed in MATLAB-TM using a custom graphical user interface (GUI) to calculate the distribution of velocities (or shear moduli) in a user-defined region of interest (ROI). The results were exported to a spreadsheet in Excel for further analysis and comparison among the different groups. Initial results suggest the shear wave velocity and estimated Young’s modulus (λ) were significantly higher in AI patients (14.6 ± 0.2 m/s, λ=642 ± 17 kPa) compared to RA (6.84 ± 1.1 m/s, λ=143 ± 43 kPa) and healthy (7.58 ± 0.9 m/s, λ=174 ± 42 kPa) patients. These values suggest that the mechanical properties of tendons in the wrist may change during treatment with AI and contribute to joint pain in these subjects. It is critical that ER+ patients on AI complete their full treatment. As a potential biomarker of AIMSS and associated pain, USWE may help predict which patients are most susceptible to these side effects, promote early intervention to reduce or eliminate symptoms, and help increase adherence to AI therapy. Citation Format: Brian A. Goldstein, Mihra Taljanovic, Pavani Chalasani, C. Kent Kwoh, Amanda Hadden, Russell Witte, Jessica Martinez. Imaging biomarkers of aromatase-inhibitor induced joint pain [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3728. doi:10.1158/1538-7445.AM2017-3728

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales.

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales.

Anatomy-driven multiple trajectory planning (ADMTP) of intracranial electrodes for epilepsy surgery

PurposeEpilepsy is potentially curable with resective surgery if the epileptogenic zone (EZ) can be identified. If non-invasive imaging is unable to elucidate the EZ, intracranial electrodes may be implanted to identify the EZ as well as map cortical function. In current clinical practice, each electrode trajectory is determined by time-consuming manual inspection of preoperative imaging to find a path that avoids blood vessels while traversing appropriate deep and superficial regions of interest (ROIs). We present anatomy-driven multiple trajectory planning (ADMTP) to find safe trajectories from a list of user-defined ROIs within minutes rather than the hours required for manual planning.MethodsElectrode trajectories are automatically computed in three steps: (1) Target Point Selection to identify appropriate target points within each ROI; (2) Trajectory Risk Scoring to quantify the cumulative distance to critical structures (blood vessels) along each trajectory, defined as the skull entry point to target point. (3) Implantation Plan Computation: to determine a feasible combination of low-risk trajectories for all electrodes.ResultsADMTP was evaluated on 20 patients (190 electrodes). ADMTP lowered the quantitative risk score in 83% of electrodes. Qualitative results show ADMTP found suitable trajectories for 70% of electrodes; a similar portion of manual trajectories were considered suitable. Trajectory suitability for ADMTP was 95% if traversing sulci was not included in the safety criteria. ADMTP is computationally efficient, computing between 7 and 12 trajectories in 54.5 (17.3–191.9) s.ConclusionsADMTP efficiently compute safe and surgically feasible electrode trajectories.

Nonlinear state-space modelling of the kinematics of an oscillating circular cylinder in a fluid flow

The flow-induced vibration of bluff bodies is an important problem of many marine, civil, or mechanical engineers. In the design phase of such structures, it is vital to obtain good predictions of the fluid forces acting on the structure. Current methods rely on computational fluid dynamic simulations (CFD), with a too high computational cost to be effectively used in the design phase or for control applications. Alternative methods use heuristic mathematical models of the fluid forces, but these lack the accuracy (they often assume the system to be linear) or flexibility to be useful over a wide operating range. In this work we show that it is possible to build an accurate, flexible and low-computational-cost mathematical model using nonlinear system identification techniques. This model is data driven: it is trained over a user-defined region of interest using data obtained from experiments or simulations, or both. Here we use a Van der Pol oscillator as well as CFD simulations of an oscillating circular cylinder to generate the training data. Then a discrete-time polynomial nonlinear state-space model is fit to the data. This model relates the oscillation of the cylinder to the force that the fluid exerts on the cylinder. The model is finally validated over a wide range of oscillation frequencies and amplitudes, both inside and outside the so-called lock-in region. We show that forces simulated by the model are in good agreement with the data obtained from CFD.

Validation of a new multiscale finite element analysis approach at the distal radius

High-resolution peripheral computed tomography is commonly used to evaluate mechanical behavior of the distal radius microstructure using micro-finite element (FE) modeling. However, only a 9mm section is considered and boundary conditions (BCs) are usually simplified (platen-compression), and may not represent physiologic loading. Regardless, these methods are increasingly being used for clinical evaluations. Our goal was to develop and validate a novel multiscale solution that allows for physiologically relevant loading simulations (such as bracing during a fall), and show that mechanical behavior in the distal radius is different under platen BCs. Our approach incorporated bone microstructure together with organ-level radius geometry, by replacing matching continuum regions with micro-FE sections in user-defined regions of interest. Multiscale model predicted strains showed a strong correlation and a significant relationship with measured strains (r=0.836, p<0.001; slope=0.881, intercept=−12.17 µε, p<0.001). Interestingly, platen BC simulated strains were almost 50% lower than measured strains (r=0.835, p<0.001), and strain distributions were clearly different. Our multiscale method demonstrated excellent potential as a computationally efficient alternative for observing true mechanical environment within distal radius microstructure under physiologically accurate loading.

Semi-Quantitative Strain Ratio Determined Using Different Measurement Methods: Comparison of Strain Ratio Values and Diagnostic Performance Using One- versus Two-Region-of-Interest Measurement

We evaluated the agreement and diagnostic performance of strain ratio values using measurements made with one and two user-defined regions of interest (ROIs) on breast elastography. Two hundred forty-three breast masses of 226 women (mean age: 48.2 y) were included. Ultrasonography (US) and elastography images of the masses were recorded. Strain ratio was measured twice on the same elastography image; strain ratio 1, applying one ROI at the target mass for measurement, and strain ratio 2, applying one ROI at the target mass and another ROI as reference strain. The two strain ratio measurements were in substantial agreement, with an intra-class correlation coefficient of 0.655 (95% confidence interval: 0.577–0.722). Specificity, positive predictive value and accuracy (cutoffs: 2.66 and 2.35) were significantly improved for US combined with the two strain ratio measurements (all p values < 0.05). Strain ratios measured using one or two user-defined ROIs were in substantial agreement, both contributing to the improved diagnostic performance of breast US.

A robust method to extract the anterior pelvic plane from CT volume independent of pelvic pose

Purpose: The anterior pelvic plane (APP) is commonly used as a reference plane to assess acetabular orientation. However, conventional methods for determining the APP may not be accurate and are prone to user variability. To overcome these issues, we developed a robust method to accurately extract the APP independent of pelvic pose using three-dimensional pelvic computed tomography (CT).Materials and methods: Twenty-eight studies for suspected nonmusculoskeletal conditions were obtained. The APP was determined by four landmarks that were automatically extracted from user-defined regions of interest (ROIs) with compensation of pelvic pose. The APP defined from these landmarks was quantitatively compared to the APPs determined by an expert and an unskilled. Intraobserver reliability was measured to evaluate the time-interval variability. Finally, we evaluate the robustness of this method to patient posture using an arbitrarily rotated volume. The intraclass correlation coefficients (ICCs) were calculated to determine the interobserver and intraobserver reliabilities.Results: The ICC values for the four landmarks and the APP were similar between the semiautomated method and expert determination (ICC >0.937). The ICC values for intraobserver reliability over time for our method were all 1, demonstrating high reliability. Furthermore, agreement between the parameters determined from the original volume and the rotated volume was nearly perfect.Conclusions: Our method is a useful measurement tool for the APP as it is robust, and the results were similar to an experienced surgeon’s determination. Furthermore, it was independent to the direction of the CT slice and more robust than a measurement by an unskilled.

Metopic "ridge" vs. "craniosynostosis": Quantifying severity with 3D curvature analysis.

There has been an increased incidence of surgical treatment for metopic craniosynostosis (MCS) over the past decade. MCS presents as a wide spectrum, ranging from severe trigonocephaly on one end to an isolated metopic ridge on the other. Current surgical diagnosis relies upon subjective clinical assessment of patients' cranial shape, which is often combined with impressions from radiologic imaging. In our study, we have developed a semi-automated methodology using three-dimensional curvature analysis to rigorously separate the phenotypes along the spectrum. Three clinically distinct groups of patients with CT images were obtained: 1) Normal subjects without any deformity; 2) "Benign" metopic ridge (BMR) without classic trigonocephaly; 3) Severe trigonocephaly with MCS. CT scans were converted into three-dimensional skull surface images, and curvature analysis was performed using two user-defined regions of interest (mid-forehead and lateral orbit). Three-dimensional curvature analysis of mid-forehead strip, and right/left lateral orbital areas was performed in thirty patients. The difference in average mean curvature between true MCS and BMR was 10.5m(-1) and-18.6m(-1) for mid-forehead strip and right/left lateral orbital rim, respectively. The average mean curvatures of mid-forehead strip and right/left lateral orbit areas among the three groups were significantly different (p<0.0001). K-means clustering reliably classified patients into different severity groups based on average mean curvature of the two regions of interest. The described methods are effective in classifying severity of orbitofrontal deformity in the spectrum of MCS, which can aid providers in identifying an appropriate threshold for surgical treatments of MCS.