Quantifying avian inertial properties using calibrated computed tomography.
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ABSTRACT:
SUBMITTER: Durston NE
PROVIDER: S-EPMC8778804 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeComputed tomography (CT)-derived ventilation methods compute respiratory induced volume changes as a surrogate for pulmonary ventilation. Currently, there are no known methods to derive perfusion information from noncontrast CT. We introduce a novel CT-Perfusion (CT-P) method for computing the magnitude mass changes apparent on dynamic noncontrast CT as a surrogate for pulmonary perfusion.MethodsCT-Perfusion is based on a mass conservation model which describes the unknown mass change as a linear combination of spatially corresponding inhale and exhale HU estimated voxel densities. CT-P requires a deformable image registration (DIR) between the inhale/exhale lung CT pair, a preprocessing lung volume segmentation, and an estimate for the Jacobian of the DIR transformation. Given this information, the CT-P image, which provides the magnitude mass change for each voxel within the lung volume, is formulated as the solution to a constrained linear least squares problem defined by a series of subregional mean magnitude mass change measurements. Similar to previous robust CT-ventilation methods, the amount of uncertainty in a subregional sample mean measurement is related to measurement resolution and can be characterized with respect to a tolerance parameter τ . Spatial Spearman correlation between single photon emission CT perfusion (SPECT-P) and the proposed CT-P method was assessed in two patient cohorts via a parameter sweep of τ . The first cohort was comprised of 15 patients diagnosed with pulmonary embolism (PE) who had SPECT-P and 4DCT imaging acquired within 24 h of PE diagnosis. The second cohort was comprised of 15 nonsmall cell lung cancer patients who had SPECT-P and 4DCT images acquired prior to radiotherapy. For each test case, CT-P images were computed for 30 different uncertainty parameter values, uniformly sampled from the range [0.01, 0.125], and the Spearman correlation between the SPECT-P and the resulting CT-P images were computed.ResultsThe median correlations between CT-P and SPECT-P taken over all 30 test cases ranged between 0.49 and 0.57 across the parameter sweep. For the optimal tolerance τ = 0.0385, the CT-P and SPECT-P correlations across all 30 test cases ranged between 0.02 and 0.82. A one-sample sign test was applied separately to the PE and lung cancer cohorts. A low Spearmen correlation of 15% was set as the null median value and two-sided alternative was tested. The PE patients showed a median correlation of 0.57 (IQR = 0.305). One-sample sign test was statistically significant with 96.5 % confidence interval: 0.20-0.63, P < 0.00001. Lung cancer patients had a median correlation of 0.57(IQR = 0.230). Again, a one-sample sign test for median was statistically significant with 96.5 percent confidence interval: 0.45-0.71, P < 0.00001.ConclusionCT-Perfusion is the first mechanistic model designed to quantify magnitude blood mass changes on noncontrast dynamic CT as a surrogate for pulmonary perfusion. While the reported correlations with SPECT-P are promising, further investigation is required to determine the optimal CT acquisition protocol and numerical method implementation for CT-P imaging.
| S-EPMC8252085 | biostudies-literature
Project description:ObjectiveWe aimed to establish a quantitative description of motion patterns and establish test-retest reliability of the four-dimensional CT when quantifying in vivo kinematics of the scaphoid, lunate, and capitate.Materials and methodsWe assessed in vivo kinematics of both wrists of 20 healthy volunteers (11 men and 9 women) between the ages of 20 and 40 years. All volunteers performed active flexion-extension and radial-ulnar deviation with both wrists. To test for reliability, one motion cycle was rescanned for both wrists approximately 15 min after the first scan. The coefficient of multiple correlation was used to analyze reliability. When two motion patterns are similar, the coefficient of multiple correlation tends towards 1, whereas in dissimilar motion patterns, it tends towards 0. The root mean square deviation was used to analyze the total motion patterns variability between the two scans.ResultsOverall, mean or median coefficient of multiple correlations were higher than 0.86. The root mean square deviations were low and ranged from 1.17° to 4.29°.ConclusionThis innovative non-invasive imaging technique can reliably describe in vivo carpal kinematics of uninjured wrists in healthy individuals. It provides us with a better understanding and reference values of carpal kinematics of the scaphoid, lunate, and capitate.
| S-EPMC7736028 | biostudies-literature
Project description:Angiogenesis is a critical process essential for optimal bone healing. Several in vitro and in vivo systems have been previously used to elucidate some of the mechanisms involved in the process of angiogenesis, and at the same time, to test potential therapeutic agents and bioactive factors that play important roles in neovascularization. Computed tomography (CT) is a noninvasive imaging technique that has recently allowed investigators to obtain a diverse range of high-resolution, three-dimensional characterization of structures, such as bone formation within bony defects. Unfortunately, to date, angiogenesis evaluation relies primarily on histology, or ex vivo imaging and few studies have utilized CT to qualitatively and quantitatively study the vascular response during bone repair. In the current study a clinical CT-based technique was used to evaluate the effects of rhBMP-2 eluting graft treatment on soft tissue vascular architecture surrounding a large segmental bone defect model in the minipig mandible. The objective of this study was to demonstrate the efficacy of contrast-enhanced, clinical 64-slice CT technology in extracting quantitative metrics of vascular architecture over a 12-week period. The results of this study show that the presence of rhBMP-2 had a positive effect on vessel volume from 4 to 12 weeks, which was explained by a concurrent increase in vessel number, which was also significantly higher at 4 weeks for the rhBMP-2 treatment. More importantly, analysis of vessel architecture showed no changes throughout the duration of the study, indicating therapeutic safety. This study validates CT analysis as a relevant imaging method for quantitative and qualitative analysis of morphological characteristics of vascular tissue around a bone healing site. Also important, the study shows that CT technology can be used in large animal models and potentially be translated into clinical models for the development of improved methods to evaluate tissue healing and vascular adaptation processes over the course of therapy. This methodology has demonstrated sensitivity to tracking spatial and temporal changes in vascularization and has the potential to be applied to studying changes in other high-contrast tissues as well. Impact Statement Tissue engineering solutions depend on the surrounding tissue response to support regeneration. The inflammatory environment and surrounding vascular supply are critical to determining if therapies will survive, engraftment occurs, and native physiology is restored. This study for the first time evaluates the blood vessel network changes in surrounding soft tissue to a bone defect site in a large animal model, using clinically available computed tomography tools and model changes in vessel number, size, and architecture. While this study focuses on rhBMP2 delivery impacting surrounding vasculature, this validated method can be extended to studying the vascular network changes in other tissues as well.
| S-EPMC7058991 | biostudies-literature
Project description:The aim of this study was to quantify sub-resolution trabecular bone morphometrics, which are also related to osteoarthritis (OA), from clinical resolution cone beam computed tomography (CBCT). Samples (n = 53) were harvested from human tibiae (N = 4) and femora (N = 7). Grey-level co-occurrence matrix (GLCM) texture and histogram-based parameters were calculated from CBCT imaged trabecular bone data, and compared with the morphometric parameters quantified from micro-computed tomography. As a reference for OA severity, histological sections were subjected to OARSI histopathological grading. GLCM and histogram parameters were correlated to bone morphometrics and OARSI individually. Furthermore, a statistical model of combined GLCM/histogram parameters was generated to estimate the bone morphometrics. Several individual histogram and GLCM parameters had strong associations with various bone morphometrics (|r| > 0.7). The most prominent correlation was observed between the histogram mean and bone volume fraction (r = 0.907). The statistical model combining GLCM and histogram-parameters resulted in even better association with bone volume fraction determined from CBCT data (adjusted R2 change = 0.047). Histopathology showed mainly moderate associations with bone morphometrics (|r| > 0.4). In conclusion, we demonstrated that GLCM- and histogram-based parameters from CBCT imaged trabecular bone (ex vivo) are associated with sub-resolution morphometrics. Our results suggest that sub-resolution morphometrics can be estimated from clinical CBCT images, associations becoming even stronger when combining histogram and GLCM-based parameters.
| S-EPMC6949315 | biostudies-literature
Project description:Mechanical ventilation strategies that reduce the heterogeneity of regional lung stress and strain may reduce the risk of ventilator-induced lung injury (VILI). In this study, we used registration of four-dimensional computed tomographic (4DCT) images to assess regional lung aeration and deformation in 10 pigs under baseline conditions and following acute lung injury induced with oleic acid. CT images were obtained via dynamic axial imaging (Siemens SOMATOM Force) during conventional pressure-controlled mechanical ventilation (CMV), as well as high-frequency and multi-frequency oscillatory ventilation modalities (HFOV and MFOV, respectively). Our results demonstrate that oscillatory modalities reduce intratidal strain throughout the lung in comparison to conventional ventilation, as well as the spatial gradients of dynamic strain along the dorsal-ventral axis. Harmonic distortion of parenchymal deformation was observed during HFOV with a single discrete sinusoid delivered at the airway opening, suggesting inherent mechanical nonlinearity of the lung tissues. MFOV may therefore provide improved lung-protective ventilation by reducing strain magnitudes and spatial gradients of strain compared to either CMV or HFOV.
| S-EPMC7044245 | biostudies-literature
Project description:To derive the reperfusion index best predicting clinical outcome of ischemic stroke patients, we retrospectively analysed the acute and 24-h computed tomography perfusion data of 116 patients, collected from two centres equipped with whole-brain computed tomography perfusion. Reperfusion index was defined by the percentage of the ischemic region reperfused from acute to 24-h computed tomography perfusion. Recanalization was graded by arterial occlusive lesion system. Receiver operator characteristic analysis was performed to assess the prognostic value of reperfusion and recanalization in predicting good clinical outcome, defined as modified Rankin Score of 0-2 at 90 days. Among previous reported reperfusion measurements, reperfusion of the Tmax>6 s region resulted in higher prognostic value than recanalization at predicting good clinical outcome (area under the curve = 0.88 and 0.74, respectively, p = 0.002). Successful reperfusion of the Tmax>6 s region (≥60%) had 89% sensitivity and 78% specificity in predicting good clinical outcome. A reperfusion index defined by Tmax>2 s or by mean transit time>145% had much lower area under the curve in comparison to Tmax>6 s measurement (p < 0.001 and p = 0.003, respectively), and had no significant difference to recanalization at predicting clinical outcome (p = 0.58 and 0.63, respectively). In conclusion, reperfusion index calculated by Tmax>6 s is a stronger predictor of clinical outcome than recanalization or other reperfusion measures.
| S-EPMC5464706 | biostudies-literature
Project description:The potential increased frequency and severity of drought associated with environmental change represents a significant obstacle to efforts aimed at enhancing food security due to its impact on crop development, and ultimately, yield. Our understanding of the impact of drought on crop growth in terms of plant aerial tissues is much more advanced than knowledge of the below-ground impacts. We undertook an experiment using X-ray Computed Tomography that aimed to support measurements of infrared gas exchange from plant shoots with quantification of 3D root architecture traits and the associated soil structural characteristics. Winter wheat (cv. Zebedee) was assessed at two early growth stages (14 and 21 days) under four water treatments (100, 75, 50 and 25 % of a notional field capacity (FC) and across two soil types (sandy loam and clay loam)). Plants generally grew better (to a larger size) in sandy loam soil as opposed to clay loam soil, most likely due to the soil structure and the associated pore network. All plants grew poorly under extreme water stress and displayed optimal growth at 75 % of FC, as opposed to 100 %, as the latter was most likely too wet. The optimal matric potential for root and shoot growth, inferred from the water release curve for each soil type, was higher than that for photosynthesis, stomatal conductance and transpiration suggesting root and shoot growth was more affected by soil water content than photosynthesis-related characteristics under water deficit conditions. With incidences of drought likely to increase, identification of wheat cultivars that are more tolerant of these conditions is important. Studies that consider the impact of water stress on both plant shoots and roots, and the role of the soil pore system such as this offer considerable potential in supporting these efforts.
| S-EPMC7469715 | biostudies-literature
Project description:Current implant materials and designs used in spinal fusion show high rates of subsidence. There is currently a need for a method to predict the mechanical properties of the endplate using clinically available tools. The purpose of this study was to develop a predictive model of the mechanical properties of the vertebral endplate at a scale relevant to the evaluation of current medical implant designs and materials. Twenty vertebrae (10 L1 and 10 L2) from 10 cadavers were studied using dual-energy X-ray absorptiometry to define bone status (normal, osteopenic, or osteoporotic) and computed tomography (CT) to study endplate thickness (?m), density (mg/mm3), and mineral density of underlying trabecular bone (mg/mm3) at discrete sites. Apparent Oliver-Pharr modulus, stiffness, maximum tolerable pressure (MTP), and Brinell hardness were measured at each site using a 3?mm spherical indenter. Predictive models were built for each measured property using various measures obtained from CT and demographic data. Stiffness showed a strong correlation between the predictive model and experimental values (r?=?0.85), a polynomial model for Brinell hardness had a stronger predictive ability compared to the linear model (r?=?0.82), and the modulus model showed weak predictive ability (r?=?0.44), likely due the low indentation depth and the inability to image the endplate at that depth (?0.15 mm). Osteoporosis and osteopenia were found to be the largest confounders of the measured properties, decreasing them by approximately 50%. It was confirmed that vertebral endplate mechanical properties could be predicted using CT and demographic indices.
| S-EPMC6056182 | biostudies-literature
Project description:BackgroundIn bioenergy/forage sorghum, morpho-anatomical stem properties are major components affecting standability and juice yield. However, phenotyping these traits is low-throughput, and has been restricted by the lack of a high-throughput phenotyping platforms that can collect both morphological and anatomical stem properties. X-ray computed tomography (CT) offers a potential solution, but studies using this technology in plants have evaluated limited numbers of genotypes with limited throughput. Here we suggest that using a medical CT might overcome sample size limitations when higher resolution is not needed. Thus, the aim of this study was to develop a practical high-throughput phenotyping and image data processing pipeline that extracts stem morpho-anatomical traits faster, more efficiently and on a larger number of samples.ResultsA medical CT was used to image morpho-anatomical stem properties in sorghum. The platform and image analysis pipeline revealed extensive phenotypic variation for important morpho-anatomical traits in well-characterized sorghum genotypes at suitable repeatability rates. CT estimates were highly predictive of morphological traits and moderately predictive of anatomical traits. The image analysis pipeline also identified genotypes with superior morpho-anatomical traits that were consistent with ground-truth based classification in previous studies. In addition, stem cross section intensity measured by the CT was highly correlated with stem dry-weight density, and can potentially serve as a high-throughput approach to measure stem density in grass stems.ConclusionsThe use of CT on a diverse set of sorghum genotypes with a defined platform and image analysis pipeline was effective at predicting traits such as stem length, diameter, and pithiness ratio at the internode level. High-throughput phenotyping of stem traits using CT appears to be useful and feasible for use in an applied breeding program.
| S-EPMC6043981 | biostudies-literature
Project description:Unlike the majority of cancers, survival for lung cancer has not shown much improvement since the early 1970s and survival rates remain low. Genetically engineered mice tumor models are of high translational relevance as we can generate tissue specific mutations which are observed in lung cancer patients. Since these tumors cannot be detected and quantified by traditional methods, we use micro-computed tomography imaging for longitudinal evaluation and to measure response to therapy. Conventionally, we analyze microCT images of lung cancer via a manual segmentation. Manual segmentation is time-consuming and sensitive to intra- and inter-analyst variation. To overcome the limitations of manual segmentation, we set out to develop a fully-automated alternative, the Mouse Lung Automated Segmentation Tool (MLAST). MLAST locates the thoracic region of interest, thresholds and categorizes the lung field into three tissue categories: soft tissue, intermediate, and lung. An increase in the tumor burden was measured by a decrease in lung volume with a simultaneous increase in soft and intermediate tissue quantities. MLAST segmentation was validated against three methods: manual scoring, manual segmentation, and histology. MLAST was applied in an efficacy trial using a Kras/Lkb1 non-small cell lung cancer model and demonstrated adequate precision and sensitivity in quantifying tumor growth inhibition after drug treatment. Implementation of MLAST has considerably accelerated the microCT data analysis, allowing for larger study sizes and mid-study readouts. This study illustrates how automated image analysis tools for large datasets can be used in preclinical imaging to deliver high throughput and quantitative results.
| S-EPMC8211241 | biostudies-literature