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Fibrotic scarring in idiopathic pulmonary fibrosis (IPF) typically develops first in the posterior-basal lung tissue before advancing to involve more of the lung. The complexity of lung shape in the costo-diaphragmatic region has been proposed as a potential factor in this regional development. Intrinsic and disease-related shape could therefore be important for understanding IPF risk and its staging. We hypothesized that lung and lobe shape in IPF would have important differences from controls. A principal component (PC) analysis was used to derive a statistical shape model (SSM) of the lung for a control cohort aged > 50 years (N = 39), using segmented lung and fissure surface data from CT imaging. Individual patient shape models derived for baseline (N = 18) and follow-up (N = 16) CT scans in patients with IPF were projected to the SSM to describe shape as the sum of the SSM average and weighted PC modes. Associations between the first four PC shape modes, lung function, percentage of fibrosis (fibrosis%) and pulmonary vessel-related structures (PVRS%), and other tissue metrics were assessed and compared between the two cohorts. Shape was different between IPF and controls (P < 0.05 for all shape modes), with IPF shape forming a distinct shape cluster. Shape had a negative relationship with age in controls (P = 0.013), but a positive relationship with age in IPF (P = 0.026). Some features of shape changed on follow-up. Shape in IPF was associated with fibrosis% (P < 0.05) and PVRS% (P < 0.05). Quantitative comparison of lung and lobe shape in IPF with controls of a similar age reveals shape differences that are strongly associated with age and percent fibrosis. The clustering of IPF cohort shape suggests that it could be an important feature to describe disease. [ABSTRACT FROM AUTHOR]

Summary: A multi-feature fusion DCNN model for automated evaluation of lumbar vertebrae L1 on chest combined with clinical information and radiomics permits estimation of volumetric bone mineral density for evaluation of osteoporosis. Purpose: To develop a multi-feature deep learning model based on chest CT, combined with clinical information and radiomics to explore the feasibility in screening for osteoporosis based on estimation of volumetric bone mineral density. Methods: The chest CT images of 1048 health check subjects were retrospectively collected as the master dataset, and the images of 637 subjects obtained from a different CT scanner were used for the external validation cohort. The subjects were divided into three categories according to the quantitative CT (QCT) examination, namely, normal group, osteopenia group, and osteoporosis group. Firstly, a deep learning–based segmentation model was constructed. Then, classification models were established and selected, and then, an optimal model to build bone density value prediction regression model was chosen. Results: The DSC value was 0.951 ± 0.030 in the testing dataset and 0.947 ± 0.060 in the external validation cohort. The multi-feature fusion model based on the lumbar 1 vertebra had the best performance in the diagnosis. The area under the curve (AUC) of diagnosing normal, osteopenia, and osteoporosis was 0.992, 0.973, and 0.989. The mean absolute errors (MAEs) of the bone density prediction regression model in the test set and external testing dataset are 8.20 mg/cm3 and 9.23 mg/cm3, respectively, and the root mean square errors (RMSEs) are 10.25 mg/cm3 and 11.91 mg/cm3, respectively. The R-squared values are 0.942 and 0.923, respectively. The Pearson correlation coefficients are 0.972 and 0.965. Conclusion: The multi-feature fusion DCNN model based on only the lumbar 1 vertebrae and clinical variables can perform bone density three-classification diagnosis and estimate volumetric bone mineral density. If confirmed in independent populations, this automated opportunistic chest CT evaluation can help clinical screening of large-sample populations to identify subjects at high risk of osteoporotic fracture. [ABSTRACT FROM AUTHOR]

Abstract Anecdotal evidence from preliminary observations has noted multiple instances where osteoporosis is present in elderly patients before the clinical detection of bowel disease, even in the absence of overt gastrointestinal symptoms. However, any potential association between these conditions remains to be further investigated. This computed tomography (CT) study investigates whether patients with gastrointestinal (GI) perforation have lower bone mineral density (BMD) than age and sex matched controls. BMD was measured by drawing 3D regions of interest in the bone marrow of the L1–L3 vertebral bodies on CT scans of each of 37 GI perforations and matched controls. Spectrometric calibration of Hounsfield units to the mineral scale was performed with density measurements in the paravertebral muscles (erector spinae) and subcutaneous adipose tissue. The mean BMD of patients with GI perforation (135.9 ± 24.3 mg/ml) was significantly lower than that of controls (96.9 ± 27.5 mg/ml, p

Abstract Background Idiopathic Pulmonary Fibrosis (IPF) is a progressive fibrotic lung disease. However, the field of quantitative CT scan analysis in conjunction with pulmonary function test for IPF patients remains relatively understudied. In this study, we evaluated the diagnostic value of features derived high-resolution computed tomography (HRCT) for patients with IPF and correlated them with pulmonary function tests. Methods We retrospectively analyzed the chest HRCT images and pulmonary function test results of 52 patients with IPF during the same period (1 week) and selected 52 healthy individuals, matched for sex, age, and body mass index (BMI) and with normal chest HRCT as controls. HRCT scans were performed using a Philips 256-row Brilliance iCT scanner with standardized parameters. Lung function tests were performed using a Jaeger volumetric tracer for forced vital capacity (FVC), total lung capacity (TLC), forced expiratory volume in first second (FEV1), FEV1/FVC, carbon monoxide diffusing capacity (DLCO), and maximum ventilation volume (MVV) metrics. CT quantitative analysis, including tissue segmentation and threshold-based quantification of lung abnormalities, was performed using 3D-Slicer software to calculate the percentage of normal lung areas (NL%), percentage of ground-glass opacity areas (GGO%), percentage of fibrotic area (F%) and abnormal lesion area percentage (AA%). Semi-quantitative analyses were performed by two experienced radiologists to assess disease progression. The aortic-to-sternal distance (ASD) was measured on axial images as a standardized parameter. Spearman or Pearson correlation analysis and multivariate stepwise linear regression were used to analyze the relationship between the data in each group, and the ROC curve was used to determine the optimal quantitative CT metrics for identifying IPF and controls. Results ROC curve analysis showed that F% distinguished the IPF patient group from the control group with the largest area under the curve (AUC) of 0.962 (95% confidence interval: 0.85–0.96). Additionally, with F% = 4.05% as the threshold, the Youden’s J statistic was 0.827, with a sensitivity of 92.3% and a specificity of 90.4%. The ASD was significantly lower in the late stage of progression than in the early stage (t = 5.691, P

Abstract Background Serum bone turnover markers offer limited insight into metabolic activity at the individual vertebra level in osteoporosis. This study introduces a novel image-derived bone turnover marker for individual vertebrae to address this limitation, utilizing volumetric density-adjusted quantitative bone single-photon emission computed tomography/computed tomography (SPECT/CT) with [99mTc]Tc-DPD. This retrospective study included 177 lumbar vertebrae from 55 postmenopausal South Korean women. The mean standardized uptake value (SUVmean, g/cm3) and volumetric bone mineral density (vBMD, mg/cm3) were determined within a 2-cm³ volume of interest in the trabecular portion of each vertebra using quantitative SPECT and CT. The density-adjusted mean standardized uptake value (dSUVmean) was calculated by dividing the SUVmean by the vBMD and multiplying by 1,000. Results SUVmean correlated positively with vBMD (r = 0.60, p

Automated mineralogy is a software addition usually seen on scanning electron microscopes designed to provide rapid insight into sample chemistry and texture in routine petrology workflows. The specific purpose of automated mineralogy is to provide mineral classifications to uniquely identified phases typically using energy dispersive spectroscopy, thus removing laborious and time‐consuming human input for routine tasks. These mineral classifications can then be applied to image data to quantify which mineral is associated with any particular texture. Automated mineralogy systems were primarily designed to generate quantitative textural analysis of particle samples to the mining industry and have remained a critical technique in this setting for the last several decades. Automated mineralogy has become more widely used in academia, and this has changed the focus of the technique, applying it to a broader range of workflows and applications. Here we show petrology examples focussing where combined geochemical and textural analysis are widely used. Critically, the use of quantitative geochemical data means that mineral classifications are based on their quantitatively measured chemistry. By making both the chemical and textural analysis quantitative, automated mineralogy can become highly flexible and provide a unique system for petrologists in both industry and academia. [ABSTRACT FROM AUTHOR]

Background: Idiopathic Pulmonary Fibrosis (IPF) is a progressive fibrotic lung disease. However, the field of quantitative CT scan analysis in conjunction with pulmonary function test for IPF patients remains relatively understudied. In this study, we evaluated the diagnostic value of features derived high-resolution computed tomography (HRCT) for patients with IPF and correlated them with pulmonary function tests. Methods: We retrospectively analyzed the chest HRCT images and pulmonary function test results of 52 patients with IPF during the same period (1 week) and selected 52 healthy individuals, matched for sex, age, and body mass index (BMI) and with normal chest HRCT as controls. HRCT scans were performed using a Philips 256-row Brilliance iCT scanner with standardized parameters. Lung function tests were performed using a Jaeger volumetric tracer for forced vital capacity (FVC), total lung capacity (TLC), forced expiratory volume in first second (FEV1), FEV1/FVC, carbon monoxide diffusing capacity (DLCO), and maximum ventilation volume (MVV) metrics. CT quantitative analysis, including tissue segmentation and threshold-based quantification of lung abnormalities, was performed using 3D-Slicer software to calculate the percentage of normal lung areas (NL%), percentage of ground-glass opacity areas (GGO%), percentage of fibrotic area (F%) and abnormal lesion area percentage (AA%). Semi-quantitative analyses were performed by two experienced radiologists to assess disease progression. The aortic-to-sternal distance (ASD) was measured on axial images as a standardized parameter. Spearman or Pearson correlation analysis and multivariate stepwise linear regression were used to analyze the relationship between the data in each group, and the ROC curve was used to determine the optimal quantitative CT metrics for identifying IPF and controls. Results: ROC curve analysis showed that F% distinguished the IPF patient group from the control group with the largest area under the curve (AUC) of 0.962 (95% confidence interval: 0.85–0.96). Additionally, with F% = 4.05% as the threshold, the Youden's J statistic was 0.827, with a sensitivity of 92.3% and a specificity of 90.4%. The ASD was significantly lower in the late stage of progression than in the early stage (t = 5.691, P < 0.001), with a mean reduction of 2.45% per month. Quantitative CT indices correlated with all pulmonary function parameters except FEV1/FVC, with the highest correlation coefficients observed for F% and TLC%, FEV1%, FVC%, MVV% (r = − 0.571, − 0.520, − 0.521, − 0.555, respectively, all P-values < 0.001), and GGO% was significantly correlated with DLCO% (r = − 0.600, P < 0.001). Multiple stepwise linear regression analysis showed that F% was the best predictor of TLC%, FEV1%, FVC%, and MVV% (R2 = 0.301, 0.301, 0.300, and 0.302, respectively, all P-values < 0.001), and GGO% was the best predictor of DLCO% (R2 = 0.360, P < 0.001). Conclusions: Quantitative CT analysis can be used to diagnose IPF and assess lung function impairment. A decrease in the ASD may indicate disease progression. [ABSTRACT FROM AUTHOR]

Background: Serum bone turnover markers offer limited insight into metabolic activity at the individual vertebra level in osteoporosis. This study introduces a novel image-derived bone turnover marker for individual vertebrae to address this limitation, utilizing volumetric density-adjusted quantitative bone single-photon emission computed tomography/computed tomography (SPECT/CT) with [99mTc]Tc-DPD. This retrospective study included 177 lumbar vertebrae from 55 postmenopausal South Korean women. The mean standardized uptake value (SUVmean, g/cm3) and volumetric bone mineral density (vBMD, mg/cm3) were determined within a 2-cm³ volume of interest in the trabecular portion of each vertebra using quantitative SPECT and CT. The density-adjusted mean standardized uptake value (dSUVmean) was calculated by dividing the SUVmean by the vBMD and multiplying by 1,000. Results: SUVmean correlated positively with vBMD (r = 0.60, p < 0.001). Conversely, dSUVmean correlated negatively with vBMD (ρ = −0.66, p < 0.001), highlighting the inverse relationship between bone mass and turnover after density adjustment of SUVmean. Patients with major osteoporotic fractures had lower vBMD (62.5 ± 29.4 vs. 92.3 ± 27.4 mg/cm³, p = 0.001) but higher dSUVmean (100.8 ± 60.7 vs. 62.6 ± 17.5, p = 0.001) compared to those without fractures, reinforcing the association between fracture prevalence, low bone mass, and high bone turnover. Conclusion: Volumetric density-adjusted quantitative bone SPECT/CT offers a novel image-derived bone turnover marker for assessing bone turnover in osteoporosis. This method provides a precise assessment of fragility at the individual vertebra level, which may enhance personalized osteoporosis management. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study was to apply quantitative computed tomography (QCT) for GOLD-grade specific disease characterization and phenotyping of air-trapping, emphysema, and airway abnormalities in patients with chronic obstructive pulmonary disease (COPD) from a nationwide cohort study. Methods: As part of the COSYCONET multicenter study, standardized CT in ex- and inspiration, lung function assessment (FEV1/FVC), and clinical scores (BODE index) were prospectively acquired in 525 patients (192 women, 327 men, aged 65.7 ± 8.5 years) at risk for COPD and at GOLD1–4. QCT parameters such as total lung volume (TLV), emphysema index (EI), parametric response mapping (PRM) for emphysema (PRMEmph) and functional small airway disease (PRMfSAD), total airway volume (TAV), wall percentage (WP), and total diameter (TD) were computed using automated software. Results: TLV, EI, PRMfSAD, and PRMEmph increased incrementally with each GOLD grade (p < 0.001). Aggregated WP5–10 of subsegmental airways was higher from GOLD1 to GOLD3 and lower again at GOLD4 (p < 0.001), whereas TD5–10 was significantly dilated only in GOLD4 (p < 0.001). Fifty-eight patients were phenotyped as “non-airway non-emphysema type,” 202 as “airway type,” 96 as “emphysema type,” and 169 as “mixed type.” FEV1/FVC was best in “non-airway non-emphysema type” compared to other phenotypes, while “mixed type” had worst FEV1/FVC (p < 0.001). BODE index was 0.56 ± 0.72 in the “non-airway non-emphysema type” and highest with 2.55 ± 1.77 in “mixed type” (p < 0.001). Conclusion: QCT demonstrates increasing hyperinflation and emphysema depending on the GOLD grade, while airway wall thickening increases until GOLD3 and airway dilatation occur in GOLD4. QCT identifies four disease phenotypes with implications for lung function and prognosis. [ABSTRACT FROM AUTHOR]

X-ray CT imaging is an important three-dimensional non-destructive testing technique, which has been widely applied in various fields. However, segmenting image voxels as discrete material compositions may lose information below the voxel size. In this study, six samples with known volume fractions of compositions were imaged using laboratory micro-CT. Optical microscopic images of the samples reveal numerous small particles of compositions smaller than the CT voxel size within the samples. By employing the equivalent energy method to determine the X-ray beam energy for sample imaging experiments, data-constrained modelling (DCM) was used to obtain the volume fractions of different compositions in the samples for each voxel. The results demonstrated that DCM effectively captured information about compositions occupying CT voxels partially. The computed volume fractions of compositions using DCM closely matched the known values. The results of DCM and four automatic threshold segmentation algorithms were compared and analyzed. The results showed that DCM has obvious advantages in processing those samples containing a large number of particles smaller than the CT voxel size. This work is the first quantitative evaluation of DCM for laboratory CT image processing, which provides a new idea for multi-scale structure characterization of materials based on laboratory CT. [ABSTRACT FROM AUTHOR]

For Caucasian women, the QCT (quantitative CT) lumbar spine (LS) bone mineral density (BMD) cutpoint value for classifying osteoporosis is 80 mg/ml. At the age of approximate 78 years, US Caucasian women QCT LS BMD population mean is 80 mg/ml, while that of Chinese women and Japanese women is around 50 mg/ml. Correlation analyses show, for Chinese women and Japanese women, QCT LS BMD of 45 mg/ml corresponds to the dual-energy X-ray absorptiometry cutpoint value for classifying osteoporosis. For Chinese and Japanese women, if QCT LS BMD 80 mg/ml is used as the threshold to classify osteoporosis, then the specificity of classifying subjects with vertebral fragility fracture into the osteoporotic group is low, whereas threshold of 45 mg/ml approximately achieve a similar separation for women with and without vertebral fragility fracture as the reports for Caucasian women. Moreover, by using 80mg/ml as the cutpoint value, LS QCT leads to excessively high prevalence of osteoporosis for Chinese women, with the discordance between hip dual-energy X-ray absorptiometry and LS QCT measures far exceeding expectation. Considering the different bone properties and the much lower prevalence of fragility fractures in the East Asian women compared with Caucasians, we argue that the QCT cutpoint value for classifying osteoporosis among older East Asian women will be close to and no more than 50 mg/ml LS BMD. We suggest that it is also imperative the QCT osteoporosis classification criterion for East Asian male LS, and male and female hips be re-examined. [ABSTRACT FROM AUTHOR]

Objective: To assess the impact of scatter radiation on quantitative performance of first and second‐generation dual‐layer spectral computed tomography (DLCT) systems. Method: A phantom with two iodine inserts (1 and 2 mg/mL) configured to intentionally introduce high scattering conditions was scanned with a first‐ and second‐generation DLCT. Collimation widths (maximum of 4 cm for first generation and 8 cm for second generation) and radiation dose levels were varied. To evaluate the performance of both systems, the mean CT numbers of virtual monoenergetic images (MonoEs) at different energies were calculated and compared to expected values. MonoEs at 50 versus 150 keV were plotted to assess material characterization of both DLCTs. Additionally, iodine concentrations were determined, plotted, and compared against expected values. For each experimental scenario, absolute errors were reported. Results: An experimental setup, including a phantom design, was successfully implemented to simulate high scatter radiation imaging conditions. Both CT scanners illustrated high spectral accuracy for small collimation widths (1 and 2 cm). With increased collimation (4 cm), the second‐generation DLCT outperformed the earlier DLCT system. Further, the spectral performance of the second‐generation DLCT at an 8 cm collimation width was comparable to a 4 cm collimation on the first‐generation DLCT. A comparison of the absolute errors between both systems at lower energy MonoEs illustrates that, for the same acquisition parameters, the second‐generation DLCT generated results with decreased errors. Similarly, the maximum error in iodine quantification was less with second‐generation DLCT (0.45 and 0.33 mg/mL for the first and second‐generation DLCT, respectively). Conclusion: The implementation of a two‐dimensional anti‐scatter grid in the second‐generation DLCT improves the spectral quantification performance. In the clinical routine, this improvement may enable additional clinical benefits, for example, in lung imaging. [ABSTRACT FROM AUTHOR]

Rationale: Rates of emphysema progression vary in chronic obstructive pulmonary disease (COPD), and the relationships with vascular and airway pathophysiology remain unclear. Objectives: We sought to determine if indices of peripheral (segmental and beyond) pulmonary arterial dilation measured on computed tomography (CT) are associated with a 1-year index of emphysema (EI; percentage of voxels <−950 Hounsfield units) progression. Methods: Five hundred ninety-nine former and never-smokers (Global Initiative for Chronic Obstructive Lung Disease stages 0–3) were evaluated from the SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) cohort: rapid emphysema progressors (RPs; n = 188, 1-year ΔEI > 1%), nonprogressors (n = 301, 1-year ΔEI ± 0.5%), and never-smokers (n = 110). Segmental pulmonary arterial cross-sectional areas were standardized to associated airway luminal areas (segmental pulmonary artery–to–airway ratio [PAARseg]). Full-inspiratory CT scan–derived total (arteries and veins) pulmonary vascular volume (TPVV) was compared with small vessel volume (radius smaller than 0.75 mm). Ratios of airway to lung volume (an index of dysanapsis and COPD risk) were compared with ratios of TPVV to lung volume. Results: Compared with nonprogressors, RPs exhibited significantly larger PAARseg (0.73 ± 0.29 vs. 0.67 ± 0.23; P = 0.001), lower ratios of TPVV to lung volume (3.21 ± 0.42% vs. 3.48 ± 0.38%; P = 5.0 × 10−12), lower ratios of airway to lung volume (0.031 ± 0.003 vs. 0.034 ± 0.004; P = 6.1 × 10−13), and larger ratios of small vessel volume to TPVV (37.91 ± 4.26% vs. 35.53 ± 4.89%; P = 1.9 × 10−7). In adjusted analyses, an increment of 1 standard deviation in PAARseg was associated with a 98.4% higher rate of severe exacerbations (95% confidence interval, 29–206%; P = 0.002) and 79.3% higher odds of being in the RP group (95% confidence interval, 24–157%; P = 0.001). At 2-year follow-up, the CT-defined RP group demonstrated a significant decline in postbronchodilator percentage predicted forced expiratory volume in 1 second. Conclusions: Rapid one-year progression of emphysema was associated with indices indicative of higher peripheral pulmonary vascular resistance and a possible role played by pulmonary vascular–airway dysanapsis. [ABSTRACT FROM AUTHOR]

Objective To compare the bone mineral density and age-related bone loss rate of thoracic and lumbar vertebrae using quantitative CT(QCT), and to explore the feasibility of measuring bone density and bone loss rate using thoracic QCT. Methods A total of 708 patients who underwent full abdominal CT scans due to trauma, acute abdominal disease, and health examination from March 2022 to March 2023 were selected. The average BMD of T10 to L3 vertebral bodies were measured using quantitative CT software. The subjects were divided into several age groups according to the age of every 10 years. The average bone density and the age-related annual rate of bone density loss of the thoracic and lumbar vertebrae for each group were computed, the correlation analysis between thoracic and lumbar BMD and age was conducted using Pearson correlation analysis. Results The peak BMD for both males and females was in the 20 to 29 years age group. After the age of 30, the bone density of the thoracic and lumbar vertebrae began to decrease to varying degrees. For females aged 80 to 89, the cumulative bone loss rate for the thoracic and lumbar vertebrae was 60.61% and 61.34%, respectively, while for males, it was 44.45% and 49.35%, respectively. The BMD of the thoracic and lumbar vertebrae in both males and females showed a negative correlation with age (P < 0.01). There was a significant positive correlation between the bone mineral density of the thoracic and lumbar vertebrae (for males, r = 0.96; for females, r = 0.98; P < 0.01). Conclusion Both thoracic and lumbar QCT accurately displayed BMD and bone loss in different age groups, and thoracic QCT could be used as a method for evaluating and monitoring bone loss. [ABSTRACT FROM AUTHOR]

BACKGROUND: There is no consensus on the optimal bone tunnel position in the lateral clavicle, which guides coracoclavicular ligament reconstruction. Postoperative complications such as enlargement of the lateral clavicle bone tunnel, bone osteolysis, clavicle fracture, and failure of internal fixation are likely to occur. Bone mass density plays an important role in the strength and stability of endophytic fixation. Regional differences in the bone mass density of the distal clavicle should not be overlooked in the repair and reconstruction of acromioclavicular dislocation. Currently, there are no quantitative clinical studies in humans regarding the bone mass density of the distal clavicle. OBJECTIVE: To measure the magnitude of bone mass density in different regions of the distal clavicle by quantitative CT to provide a reference for surgeons to repair and reconstruct the coracoclavicular ligament. METHODS: 101 patients undergoing quantitative CT checking in Fuyang People’s Hospital Affiliated to Anhui Medical University from October to December 2022 were enrolled, from which 1 616 samples of subdivisional bone mass density of the distal clavicle were measured. For each of the quantitative CT samples, firstly, the distal clavicle was divided medially to laterally into the following four regions: conical nodal region (region A), inter-nodal region (region B), oblique crest region (region C) and distal clavicular region (region D). Secondly, each region was divided into the first half and the second half to determine eight subdivisions, then setting semiautomatic region of interest (ROI) in each subdivision: (ROI A1, A2, B1, B2, C1, C2, D1, and D2). Thirdly, each quantitative CT scan was transferred to the quantitative CT pro analysis workstation, and cancellous bone mass density was measured in the distal clavicle ROI. Finally, the clavicular cortex was avoided when measuring. RESULTS AND CONCLUSION: (1) There was no statistically significant difference in bone mineral density on the different sides of the shoulder (P > 0.05). (2) The analysis of bone mineral density in eight sub-areas of the distal clavicle A1, A2, B1, B2, C1, C2, D1, and D2 showed statistically significant differences (P < 0.05). It could be considered that there were differences in bone mineral density in different areas of the distal clavicle. After pairwise comparison, there was no statistically significant difference in bone mineral density between A1 and A2, D1 and D2, A2 and B1 (P > 0.05), and there was a statistically significant difference in bone mineral density between the other sub-areas (P < 0.05). (3) The bone mineral density in the region A2 of the anatomical insertion of the conical ligament was significantly higher than that in the inter-nodular area (region B) (P < 0.05). The bone mineral density in the region A1 was higher than that in the region A2, but the difference was not statistically significant (P > 0.05). The bone mineral density in the region C1 of the anatomical insertion of the trapezium ligament was higher than that in regions C2, D1 and D2, and the bone mineral density in the inter-nodular area (region B) was significantly higher than that in regions C and D (P < 0.05). (4) These results have suggested that there are differences in bone mass density in different regions of the distal clavicle; regional differences in bone mass density in the distal clavicle during repair and reconstruction of acromioclavicular dislocation cannot be ignored. Consideration should be given not only to biomechanical factors but also to the placement of implants or bone tunnels in regions of higher bone mass density, which could improve the strength and stability of implant fixation and reduce the risk of complications such as bone tunnel enlargement, osteolysis, fracture and implant failure. [ABSTRACT FROM AUTHOR]

Bronchial thermoplasty (BT) is a treatment for patients with poorly controlled, severe asthma. However, predictors of treatment response to BT are defined poorly. Do baseline radiographic and clinical characteristics exist that predict response to BT? We conducted a longitudinal prospective cohort study of participants with severe asthma receiving BT across eight academic medical centers. Participants received three separate BT treatments and were monitored at 3-month intervals for 1 year after BT. Similar to prior studies, a positive response to BT was defined as either improvement in Asthma Control Test results of ≥ 3 or Asthma Quality of Life Questionnaire of ≥ 0.5. Regression analyses were used to evaluate the association between pretreatment clinical and quantitative CT scan measures with subsequent BT response. From 2006 through 2017, 88 participants received BT, with 70 participants (79.5%) identified as responders by Asthma Control Test or Asthma Quality of Life Questionnaire criteria. Responders were less likely to undergo an asthma-related ICU admission in the prior year (3% vs 25%; P =.01). On baseline quantitative CT imaging, BT responders showed less air trapping percentage (OR, 0.90; 95% CI, 0.82-0.99; P =.03), a greater Jacobian determinant (OR, 1.49; 95% CI, 1.05-2.11), greater SD of the Jacobian determinant (OR, 1.84; 95% CI, 1.04-3.26), and greater anisotropic deformation index (OR, 3.06; 95% CI, 1.06-8.86). To our knowledge, this is the largest study to evaluate baseline quantitative CT imaging and clinical characteristics associated with BT response. Our results show that preservation of normal lung expansion, indicated by less air trapping, a greater magnitude of isotropic expansion, and greater within-lung spatial variation on quantitative CT imaging, were predictors of future BT response. ClinicalTrials.gov; No.: NCT01185275; URL: www.clinicaltrials.gov [ABSTRACT FROM AUTHOR]

Idiopathic Pulmonary Fibrosis (IPF) is a progressive interstitial lung disease characterised by heterogeneously distributed fibrotic lesions. The inter- and intra-patient heterogeneity of the disease has meant that useful biomarkers of severity and progression have been elusive. Previous quantitative computed tomography (CT) based studies have focussed on characterising the pathological tissue. However, we hypothesised that the remaining lung tissue, which appears radiologically normal, may show important differences from controls in tissue characteristics. Quantitative metrics were derived from CT scans in IPF patients (N = 20) and healthy controls with a similar age (N = 59). An automated quantitative software (CALIPER, Computer-Aided Lung Informatics for Pathology Evaluation and Rating) was used to classify tissue as normal-appearing, fibrosis, or low attenuation area. Densitometry metrics were calculated for all lung tissue and for only the normal-appearing tissue. Heterogeneity of lung tissue density was quantified as coefficient of variation and by quadtree. Associations between measured lung function and quantitative metrics were assessed and compared between the two cohorts. All metrics were significantly different between controls and IPF (p < 0.05), including when only the normal tissue was evaluated (p < 0.04). Density in the normal tissue was 14% higher in the IPF participants than controls (p < 0.001). The normal-appearing tissue in IPF had heterogeneity metrics that exhibited significant positive relationships with the percent predicted diffusion capacity for carbon monoxide. We provide quantitative assessment of IPF lung tissue characteristics compared to a healthy control group of similar age. Tissue that appears visually normal in IPF exhibits subtle but quantifiable differences that are associated with lung function and gas exchange. [ABSTRACT FROM AUTHOR]

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Rationale and objectives: This study aims to evaluate the effectiveness of integrating clinical data and quantitative CT parameters with machine learning techniques in forecasting the short-term outcomes of severe COVID-19 in elderly patients. Materials and methods: In this retrospective study, we analyzed the clinical profiles and chest quantitative CT parameters of 239 elderly patients with severe COVID-19 admitted for treatment. The cohort included 61 deceased patients (death group) and 178 who recovered and were discharged (survival group). The participants were randomly assigned into a training group (n = 167) and a validation group (n = 72). Quantitative CT parameters were measured using the 3D-Slicer software. Univariate and multivariate logistic regression analyses identified independent risk factors for mortality. Predictive models were developed employing four machine learning algorithms: Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), and Support Vector Machine (SVM). Results: Both univariate and multivariate logistic regression analyses revealed age, hypersensitive C-reactive protein (hs-CRP), and solid organ volume percentage (SOV%) as independent predictors of mortality. The Area Under the Curve (AUC) values for the LR, RF, DT, and SVM models in the training group were 0.795, 0.726, 0.854, and 0.589, respectively; for the validation group, they were 0.817, 0.634, 0.869, and 0.754, respectively. The DT algorithm outperformed other models in both the training and validation groups, emerging as the most effective predictive model in this study. Conclusion: The combination of clinical data and quantitative CT parameters with machine learning approaches is highly valuable in predicting the short-term prognosis of severe COVID-19 in the elderly. Among the various models tested, the Decision Tree algorithm-based model proved to be the most accurate and reliable in this context.

Objective: To find the optimal quantitative index of emphysema by comparing and analyzing the quantitative indexes of emphysema in patients with mild to moderate chronic obstruction pulmonary disease (COPD) via registered biphasic quantitative computed tomography (QCT). Methods: We retrospectively collected 55 healthy controls, 21 Global Initiative for Chronic Obstructive Pulmonary Disease (GOLD) 1 case, and 31 GOLD 2 cases in our hospital. We imported the CT raw DICOM data into the "Digital Lung" analysis platform and measured the LAA-950% at the end of deep inspiration and the LAA-910% at the end of deep expiration. The expiratory and inspiratory CT images were registered. Then, the percentage of emphysema area (PRMEmph%), the percentage of functional small airway disease area (PRMfSAD%), and the percentage of the normal area (PRMNormal%) were calculated according to the threshold method. Pulmonary function indicators included FVC, FEV1%, and FEV1/FVC. Differences in general data, CT quantitative indexes, and pulmonary function between groups were assessed using the independent sample t-test, Mann–Whitney U test, or chi-square test, and the correlation was analyzed using Spearman correlation. The receiver operating characteristic (ROC) curve was drawn to analyze the diagnostic performance of CT quantitative parameters for emphysema in patients with mild to moderate COPD. Results: There were significant differences in sex, smoking index, FEV1%, FEV1/FVC, inspiratory phase LAA%-950, expiratory phase LAA%-910, PRMEmph%, PRMfSAD%, and PRMNormal% between the mild to moderate COPD patients and normal control groups. The inspiratory phase LAA%-950 was negatively correlated with FEV1/FVC, the expiratory phase LAA%-910 and PRMEmph% were negatively correlated with FVC, FEV1%, and FEV1/FVC. ROC curve analysis results showed that the areas under the curve of inspiration phase LAA%-950, expiratory phase LAA%-910, and PRMEmph% were 0.742, 0.861, and 0.876, respectively. Among them, the area under the curve of the PRMEmph% index was the largest, with a corresponding critical value of 9.84%, a sensitivity of 76.90%, and a specificity of 94.50%. Conclusion: Quantitative CT emphysema index LAA%-950 in the inspiratory phase, LAA%-910 in the expiratory phase, and PRMEmph% in biphasic can objectively evaluate emphysema in patients with mild to moderate COPD, among which PRMEmph% is the best evaluation index.

Abstract Objective To develop and evaluate a deep learning model based on chest CT that achieves favorable performance on opportunistic osteoporosis screening using the lumbar 1 + lumbar 2 vertebral bodies fusion feature images, and explore the feasibility and effectiveness of the model based on the lumbar 1 vertebral body alone. Materials and methods The chest CT images of 1048 health check subjects from January 2021 to June were retrospectively collected as the internal dataset (the segmentation model: 548 for training, 100 for tuning and 400 for test. The classification model: 530 for training, 100 for validation and 418 for test set). The subjects were divided into three categories according to the quantitative CT measurements, namely, normal, osteopenia and osteoporosis. First, a deep learning-based segmentation model was constructed, and the dice similarity coefficient(DSC) was used to compare the consistency between the model and manual labelling. Then, two classification models were established, namely, (i) model 1 (fusion feature construction of lumbar vertebral bodies 1 and 2) and (ii) model 2 (feature construction of lumbar 1 alone). Receiver operating characteristic curves were used to evaluate the diagnostic efficacy of the models, and the Delong test was used to compare the areas under the curve. Results When the number of images in the training set was 300, the DSC value was 0.951 ± 0.030 in the test set. The results showed that the model 1 diagnosing normal, osteopenia and osteoporosis achieved an AUC of 0.990, 0.952 and 0.980; the model 2 diagnosing normal, osteopenia and osteoporosis achieved an AUC of 0.983, 0.940 and 0.978. The Delong test showed that there was no significant difference in area under the curve (AUC) values between the osteopenia group and osteoporosis group (P = 0.210, 0.546), while the AUC value of normal model 2 was higher than that of model 1 (0.990 vs. 0.983, P = 0.033). Conclusion This study proposed a chest CT deep learning model that achieves favorable performance on opportunistic osteoporosis screening using the lumbar 1 + lumbar 2 vertebral bodies fusion feature images. We further constructed the comparable model based on the lumbar 1 vertebra alone which can shorten the scan length, reduce the radiation dose received by patients, and reduce the training cost of technologists.

Objective To investigate the correlation between bone mineral density (BMD) at different hip positions with muscle parameters and physical performance in middle-aged and elderly people in Kunming area. Methods 531 middle-aged and elderly volunteers were recruited from the Radiology Department of the First People's Hospital of Yunnan Province from May 2021 to April 2022. All study subjects completed the five-times-sitto-stand test (FTSST) and hip quantitative CT (QCT) examinations. Volunteers’ total hip (TH), femoral neck (FN), and intertrochanteric (IT) BMD were measured by using QCT PRO workstation and using OsiriX software to measure the area and density of their gluteus maximus muscle, gluteus medius, and minimus muscle and midthigh muscle. Divide male and female volunteers into positive and negative groups respectively based on FTSST time ≥ 12 seconds or < 12 seconds, and analyze the differences in hip BMD between the groups; Also divide male and female volunteers into three groups (50~59 years old, 60~69 years old, 70 years old and above) at the age of 10, and analyze the correlation between hip BMD and muscle parameters in different age and gender stratification. Control for age and BMI, and then perform partial correlation analysis on the above indicators. Results The BMD of the hip in the female FTSST positive group was lower than that in the negative group ( P < 0.001), while there was no statistically significant difference between the male groups (P > 0.05). After adjusting for age and BMI, among males, FN BMD was positively correlated with gluteus medius and minimus muscle density in the age groups of 50～59 and 60~69 ( P<0.05), while TH BMD, FN BMD, and IT BMD were strongly positively correlated with gluteus medius and minimus muscle density in the age group over 70 (P<0.05). For females, the correlation between hip BMD and muscle density in the age groups of 50～59 and 60～69 was weak, while BMD in all parts of the hip was not correlated with muscle density in the age group over 70 (P > 0.05). There was a negative correlation between TH BMD, FN BMD, and gluteus medius and minimus muscle area in the age group of 50～59 years old for males (P<0.05), while there was a significant negative correlation between TH BMD, IT BMD, and gluteus maximus area in the age group of 70 years old and above for females (P<0.05). Conclusion The BMD of various parts of the hip in the female FTSST positive group is lower than that in the negative group. The density of the gluteus medius and minimus muscle can to some extent serve as a predictive indicator of femoral neck bone strength in middle-aged and elderly men in Kunming area. [ABSTRACT FROM AUTHOR]

Aims: To investigate the characteristics and diagnostic performance of quantitative computed tomography (QCT) parameters in eosinophilic chronic obstructive pulmonary disease (COPD) patients. Methods: High‐resolution CT scans of COPD patients were retrospectively analyzed, and various emphysematous parenchyma measurements, including lung volume (LC), lung mean density (LMD), lung standard deviation (LSD), full‐width half maximum (FWHM), and lung relative voxel number (LRVN) were performed. The QCT parameters were compared between eosinophilic and noneosinophilic COPD patients, using a definition of eosinophilic COPD as blood eosinophil values ≥ 300 cells·µL−1 on at least three times. Receiver operating characteristic curves and area under the curve (ROC‐AUC) and python were used to evaluate discriminative efficacy of QCT. Results: Noneosinophilic COPD patients had a significantly lower TLMD (−846.3 ± 47.9 Hounsfield Unit [HU]) and TFWHM(162.5 ± 30.6 HU) compared to eosinophilic COPD patients (−817.8 ± 54.4, 177.3 ± 33.1 HU, respectively) (p = 0.018, 0.03, respectively). Moreover, the total LC (TLC) and TLSD were significantly lower in eosinophilic COPD group (3234.4 ± 1145.8, 183.8 ± 33.9 HU, respectively) than the noneosinophilic COPD group (5600.2 ± 1248.4, 203.5 ± 20.4 HU, respectively) (p = 0.009, 0.002, respectively). The ROC‐AUC values for TLC, TLMD, TLSD, and TFWHM were 0.91 (95% confidence interval [CI], 0.828–0.936), 0.66 (95% CI, 0.546–0.761), 0.64 (95% CI, 0.524–0.742), and 0.63 (95% CI, 0.511–0.731), respectively. When the TLC value was 4110 mL, the sensitivity was 90.7% (95% CI, 79.7–96.9), specificity was 77.8% (95% CI, 57.7–91.4) and accuracy was 86.4%. Notably, TLC demonstrated the highest discriminative efficiency with an F1 Score of 0.79, diagnostic Odds Ratio of 34.3 and Matthews Correlation Coefficient of 0.69, surpassing TLMD (0.55, 3.66, 0.25), TLSD (0.56, 3.95, 0.26), and TFWHM (0.56, 4.16, 0.33). Conclusion: Eosinophilic COPD patients exhibit lower levels of emphysema and a more uniform density distribution throughout the lungs compared to noneosinophilic COPD patients. Furthermore, TLC demonstrated the highest diagnostic efficiency and may serve as a valuable diagnostic marker for distinguishing between the two groups. [ABSTRACT FROM AUTHOR]

Copyright of Imaging Science & Photochemistry is the property of Imaging Science & Photochemistry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

X-ray CT imaging is an important three-dimensional non-destructive testing technique, which has been widely applied in various fields. However, segmenting image voxels as discrete material compositions may lose information below the voxel size. In this study, six samples with known volume fractions of compositions were imaged using laboratory micro-CT. Optical microscopic images of the samples reveal numerous small particles of compositions smaller than the CT voxel size within the samples. By employing the equivalent energy method to determine the X-ray beam energy for sample imaging experiments, data-constrained modelling (DCM) was used to obtain the volume fractions of different compositions in the samples for each voxel. The results demonstrated that DCM effectively captured information about compositions occupying CT voxels partially. The computed volume fractions of compositions using DCM closely matched the known values. The results of DCM and four automatic threshold segmentation algorithms were compared and analyzed. The results showed that DCM has obvious advantages in processing those samples containing a large number of particles smaller than the CT voxel size. This work is the first quantitative evaluation of DCM for laboratory CT image processing, which provides a new idea for multi-scale structure characterization of materials based on laboratory CT.

Objective: To quantitatively analyze and compare the chest computed tomography (CT) imaging features of patients infected with delta and omicron variants of COVID-19 using artificial intelligence (AI). Method: The clinical data of 294 patients infected with the novel coronavirus delta variant diagnosed at the Fourth Hospital of Inner Mongolia Autonomous Region from February 20, 2022 to April 19, 2022 and 222 patients infected with the omicron variant diagnosed at the People's Hospital of Inner Mongolia Autonomous Region from December 1, 2022 to December 30, 2022 were retrospectively analyzed. CT imaging data were analyzed and divided into delta and omicron groups. Quantitative calculation was performed using deductive predictive pulmonary infection auxiliary diagnostic software, and CT imaging signs and quantitative CT data between groups were compared and analyzed. Results: No statistical significance was noted between the delta and omicron groups in imaging signs, such as ground-glass opacity, ground-glass nodule, cord-like lesion, consolidation, paving stone sign, thickened interlobular septum, and thickened vessels in the lesion. The distribution of lesions along the bronchial vascular bundle was more likely in the omicron than in the delta group. The total lung lesion volume, volume proportion, right middle lobe lesion volume, volume proportion, right inferior lobe lesion volume, and volume proportion in the delta group were higher than those in the omicron group. The proportions of lesions in the delta group in −570 ~ −470 HU, −470 ~ −370 HU, −370 ~ −270 HU, and −270 ~ −170 HU volumes were higher than those in the omicron group. Conclusion: In the early stage of COVID-19, the volume of CT lesions in the patients infected with the delta variant was higher than that in the omicron group, and the distribution of lesions in the omicron group was more likely to have atypical distribution along the bronchial vascular bundle than that in the delta group. The volume and volume proportion of the pneumonia-infected area in patients with COVID-19 were quantitatively evaluated using the AI-assisted diagnosis system for COVID-19 to provide objective reference data for patients' condition assessment.

Purpose To assess normal CT scans with quantitative CT (QCT) analysis based on smoking habits and chronic obstructive pulmonary disease (COPD). Materials and Methods From January 2013 to December 2014, 90 male patients with normal chest CT and quantification analysis results were enrolled in our study [non-COPD never-smokers (n = 38) and smokers (n = 45), COPD smokers (n = 7)]. In addition, an age-matched cohort study was performed for seven smokers with COPD. The square root of the wall area of a hypothetical bronchus of internal perimeter 10 mm (Pi10), skewness, kurtosis, mean lung attenuation (MLA), and percentage of low attenuation area (%LAA) were evaluated. Results Among patients without COPD, the Pi10 of smokers (4.176 ± 0.282) was about 0.1 mm thicker than that of never-smokers (4.070 ± 0.191, p = 0.047), and skewness and kurtosis of smokers (2.628 ± 0.484 and 6.448 ± 3.427) were lower than never-smokers (2.884 ± 0.624, p = 0.038 and 8.594 ± 4.944, p = 0.02). The Pi10 of COPD smokers (4.429 ± 0.435, n = 7) was about 0.4 mm thicker than never-smokers without COPD (3.996 ± 0.115, n = 14, p = 0.005). There were no significant differences in MLA and %LAA between groups (p > 0.05). Conclusion Even on normal CT scans, QCT showed that the airway walls of smokers are thicker than never-smokers regardless of COPD and it preceded lung parenchymal changes.

Abstract Aims To investigate the characteristics and diagnostic performance of quantitative computed tomography (QCT) parameters in eosinophilic chronic obstructive pulmonary disease (COPD) patients. Methods High‐resolution CT scans of COPD patients were retrospectively analyzed, and various emphysematous parenchyma measurements, including lung volume (LC), lung mean density (LMD), lung standard deviation (LSD), full‐width half maximum (FWHM), and lung relative voxel number (LRVN) were performed. The QCT parameters were compared between eosinophilic and noneosinophilic COPD patients, using a definition of eosinophilic COPD as blood eosinophil values ≥ 300 cells·µL−1 on at least three times. Receiver operating characteristic curves and area under the curve (ROC‐AUC) and python were used to evaluate discriminative efficacy of QCT. Results Noneosinophilic COPD patients had a significantly lower TLMD (−846.3 ± 47.9 Hounsfield Unit [HU]) and TFWHM(162.5 ± 30.6 HU) compared to eosinophilic COPD patients (−817.8 ± 54.4, 177.3 ± 33.1 HU, respectively) (p = 0.018, 0.03, respectively). Moreover, the total LC (TLC) and TLSD were significantly lower in eosinophilic COPD group (3234.4 ± 1145.8, 183.8 ± 33.9 HU, respectively) than the noneosinophilic COPD group (5600.2 ± 1248.4, 203.5 ± 20.4 HU, respectively) (p = 0.009, 0.002, respectively). The ROC‐AUC values for TLC, TLMD, TLSD, and TFWHM were 0.91 (95% confidence interval [CI], 0.828–0.936), 0.66 (95% CI, 0.546–0.761), 0.64 (95% CI, 0.524–0.742), and 0.63 (95% CI, 0.511–0.731), respectively. When the TLC value was 4110 mL, the sensitivity was 90.7% (95% CI, 79.7–96.9), specificity was 77.8% (95% CI, 57.7–91.4) and accuracy was 86.4%. Notably, TLC demonstrated the highest discriminative efficiency with an F1 Score of 0.79, diagnostic Odds Ratio of 34.3 and Matthews Correlation Coefficient of 0.69, surpassing TLMD (0.55, 3.66, 0.25), TLSD (0.56, 3.95, 0.26), and TFWHM (0.56, 4.16, 0.33). Conclusion Eosinophilic COPD patients exhibit lower levels of emphysema and a more uniform density distribution throughout the lungs compared to noneosinophilic COPD patients. Furthermore, TLC demonstrated the highest diagnostic efficiency and may serve as a valuable diagnostic marker for distinguishing between the two groups.

BACKGROUND: Whether the huge difference in biomechanical properties between bone cement and osteoporotic vertebral body will increase the occurrence of refracture is still controversial. The extent to which cement implantation will affect the biomechanical parameters of unaugmented vertebrae remains unclear. OBJECTIVE: To analyze the influence range of vertebral augmentation on biomechanical parameters of the osteoporotic spine through the finite element model of long-segment osteoporotic vertebral compression fracture based on quantitative CT. METHODS: The osteoporotic compression fracture model of T12 vertebrae with a long segment of T4-L5 was constructed based on quantitative CT data. On the basis of 150 N vertical load, 1.5 N•m torsional torque was applied to the model in different directions to simulate flexion, extension, lateral flexion and rotation. The stress changes of the vertebral bodies, intervertebral disc and facet joint were compared before and after bone cement implantation. RESULTS AND CONCLUSION: (1) After implantation of model bone cement, the overall displacement amplitude of each movement state decreased by 16% on average. (2) The stress of the fifth vertebrae away from the treated vertebra at the cephalic side increased by approximately 20% on average; the stress of the first intervertebral disc at the cephalic side decreased by approximately 20%, and the stress of the second and third intervertebral discs increased by approximately 4% and 2%, respectively. The stress of the facet joints of the treated vertebrae and its caudal adjacent vertebrae decreased by approximately 6%, and the stress of the other caudal facet joints and the four cephalic adjacent facet joints increased to different degrees. In addition, the stress changes tended to be more significant the closer to the treated vertebra. (3) The results of this study show that the stress of multiple vertebral body, intervertebral discs and facets at the cephalic and caudal sides from the augmented vertebra will be significantly changed by cement implantation, and the closer to the treated vertebra, the more obvious the effect is. This stress change may be associated with the occurrence of new fractures after vertebral augmentation. [ABSTRACT FROM AUTHOR]

Background and Objective: There is increasing interest in the role of lipids in processes that modulate lung fibrosis with evidence of lipid deposition in idiopathic pulmonary fibrosis (IPF) histological specimens. The aim of this study was to identify measurable markers of pulmonary lipid that may have utility as IPF biomarkers. Study Design and Methods: IPF and control lung biopsy specimens were analysed using a unbiased lipidomic approach. Pulmonary fat attenuation volume (PFAV) was assessed on chest CT images (CTPFAV) with 3D semi‐automated lung density software. Aerated lung was semi‐automatically segmented and CTPFAV calculated using a Hounsfield‐unit (−40 to −200HU) threshold range expressed as a percentage of total lung volume. CTPFAV was compared to pulmonary function, serum lipids and qualitative CT fibrosis scores. Results: There was a significant increase in total lipid content on histological analysis of IPF lung tissue (23.16 nmol/mg) compared to controls (18.66 mol/mg, p = 0.0317). The median CTPFAV in IPF was higher than controls (1.34% vs. 0.72%, p < 0.001) and CTPFAV correlated significantly with DLCO% predicted (R2 = 0.356, p < 0.0001) and FVC% predicted (R2 = 0.407, p < 0.0001) in patients with IPF. CTPFAV correlated with CT features of fibrosis; higher CTPFAV was associated with >10% reticulation (1.6% vs. 0.94%, p = 0.0017) and >10% honeycombing (1.87% vs. 1.12%, p = 0.0003). CTPFAV showed no correlation with serum lipids. Conclusion: CTPFAV is an easily quantifiable non‐invasive measure of pulmonary lipids. In this pilot study, CTPFAV correlates with pulmonary function and radiological features of IPF and could function as a potential biomarker for IPF disease severity assessment. Aberrant cell lipid metabolism has been described in IPF but the underlying mechanisms are underexplored. In this study, chest CT is used to assess pulmonary fat attenuation volume (PFAV) in IPF. CTPFAV correlates with spirometry and IPF radiological markers. With further validation, CTPFAV could be used as a disease severity biomarker. [ABSTRACT FROM AUTHOR]

Introduction: The availability of highly effective triple cystic fibrosis transmembrane conductance regulator (CFTR) modulator combination therapy with elexacaftor--tezacaftor--ivacaftor (ETI) has improved pulmonary outcomes and quality of life of people with cystic fibrosis (pwCF). The aim of this study was to assess computed tomography (CT) changes under ETI visually with the Brody score and quantitatively with dedicated software, and to correlate CT measures with parameters of clinical response. Methods: Twenty two adult pwCF with two consecutive CT scans before and after ETI treatment initiation were retrospectively included. CT was assessed visually employing the Brody score and quantitatively by YACTA, a well-evaluated scientific software computing airway dimensions and lung parenchyma with wall percentage (WP), wall thickness (WT), lumen area (LA), bronchiectasis index (BI), lung volume and mean lung density (MLD) as parameters. Changes in CT metrics were evaluated and the visual and quantitative parameters were correlated with each other and with clinical changes in sweat chloride concentration, spirometry [percent predicted of forced expiratory volume in one second (ppFEV1)] and body mass index (BMI). Results: The mean (SD) Brody score improved with ETI [55 (12) vs. 38 (15); p < 0.001], incl. sub-scores for mucus plugging, peribronchial thickening, and parenchymal changes (all p < 0.001), but not for bronchiectasis (p = 0.281). Quantitatve WP (p < 0.001) and WT (p = 0.004) were reduced, conversely LA increased (p = 0.003), and BI improved (p = 0.012). Lung volume increased (p < 0.001), and MLD decreased (p < 0.001) through a reduction of ground glass opacity areas (p < 0.001). Changes of the Brody score correlated with those of quantitative parameters, exemplarily WT with the sub-score for mucus plugging (r = 0.730, p < 0.001) and peribronchial thickening (r = 0.552, p = 0.008). Changes of CT parameters correlated with those of clinical response parameters, in particular ppFEV1 with the Brody score (r = -0.606, p = 0.003) and with WT (r = -0.538, p = 0.010). Discussion: Morphological treatment response to ETI can be assessed using the Brody score as well as quantitative CT parameters. Changes in CT correlated with clinical improvements. The quantitative analysis with YACTA proved to be an objective, reproducible and simple method for monitoring lung disease, particularly with regard to future interventional clinical trials. [ABSTRACT FROM AUTHOR]

Objective To analyze the specificity and sensitivity of quantitative CT (QCT) in the diagnosis of rheumatoid arthritis (RA) complicated with osteoporosis (OP), as well as the influencing factors of bone loss in RA patients assessed by QCT, and to explore the value of QCT in the diagnosis and disease assessment of RA patients complicated with OP. Methods A total of 112 patients with confirmed rheumatoid arthritis were selected as research objects, including QCT group (56 cases) and dual-energy X-ray group (56 cases). Bone mineral density was measured by QCT and DXA respectively in the two groups. General information was collected, including age, sex, body mass index, disease duration (month), previous illness, and medication. Meanwhile, RA-related clinical manifestations, auxiliary examination and bone density examination results were collected. The receiver operating characteristic curve (ROC curve) was used to analyze the specificity and sensitivity of QCT for the diagnosis of OP, and multiple linear regression was used to analyze the correlation between bone loss in QCT group and the clinical manifestations and auxiliary examination of RA.Results 1. After comparison, there was no significant difference in general data between the two groups (P>0.05); The detection rate of osteoporosis in patients with rheumatoid arthritis was 44.6% by DXA and 51.9% by QCT. ROC curve analysis showed that the sensitivity and specificity of QCT for the diagnosis of RA combined with OP were 0.739 and 0.618.3. Bone loss in QCT group was not significantly correlated with clinical manifestations and disease activity indexes in RA patients (P>0.05), but was correlated with RA specific antibody anti-perinuclear factor antibody (APF). Conclusion The detection rate of RA combined OP by QCT is higher than that of DXA, and it has good sensitivity and specificity, which may be used as an important means for the diagnosis of RA combined with OP. [ABSTRACT FROM AUTHOR]

Although coronavirus disease 2019 (COVID-19) primarily affects the respiratory system, this disease can affect multiple systems, including the musculoskeletal system. However, studies regarding the effect of COVID-19 on musculoskeletal system are limited. This study analyzed the bone mineral density (BMD) and body composition of 33 patients with COVID-19 using their chest CT scans at admission, discharge, and one-year follow-up. Among the patients, 2 were asymptomatic, 8 had mild symptoms, 19 had ordinary symptoms, and 4 had severe symptoms, and no critical patients were included. The mean length of hospital stay was (29.5±9.6) days, and the mean duration to follow-up was (423.0±53.6) days. The study found no significant changes in BMD of segmental or total thoracic vertebrae at admission, discharge, and one-year follow-up. No significant changes were observed in the subcutaneous adipose tissue (SAT) area, visceral adipose tissue (VAT) area, and total adipose tissue (TAT) of the mid-slice of the T12~L1 intervertebral disc. However, the asymptomatic and mild group had a higher average BMD of the T1~T12 than that of the common and severe group at admission and one-year follow-up. The common and severe group had higher VAT and TAT area than those of the asymptomatic and mild group at admission and one-year follow-up. This study provides valuable insights into the effects of COVID-19 on the musculoskeletal system and suggests that COVID-19 does not significantly affect thoracic BMD and abdominal adipose tissue after one year of infection.

BackgroundWhether the airway is involved in the pathogenesis of interstitial lung abnormalities (ILA) is not well understood. Also the impact of ILA on lung function in COPD patients remains controversial. We aimed to assess the quantitative CT measurements of airway wall thickness (AWT) and lung function according to ILA status in COPD patients.Methods157 COPD patients discharged from our hospital from August 1, 2019 through August 31, 2022 who underwent chest CT imagings and pulmonary function tests were retrospectively enrolled. Linear regression analysis and multiple models were used to analyze associations between quantitative assessment of airway wall changes and the presence of ILA.ResultsIn 157 COPD patients, 23 patients (14.6%) had equivocal ILA, 42 patients (26.8%) had definite ILA. The definite ILA group had the highest measurements of Pi10 (square root of theoretical airway wall area with a lumen perimeter of 10 mm), segmental AWT and segmental WA% (percentage of wall area), whereas the no ILA group had the lowest measurements of Pi10, segmental AWT and segmental WA%. In the adjusted analyses (adjusted by age, sex, body mass index, smoking intensity, COPD GOLD stage, lung function, slice thickness and scanner type), compared to COPD patients without ILA, the measurements of Pi10, segmental AWT and segmental WA% were higher in definite ILA group with differences of 0.225 mm (p = 0.012), 0.152 mm (p

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Copyright of Chinese Medical Equipment Journal is the property of Chinese Medical Equipment Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study analyzes body composition information in patients on maintenance hemodialysis and explores the application value of QCT technology. Methods: A total of 62 patients on maintenance hemodialysis were selected and divided into three groups according to different dialysis durations. The bone density value, abdominal fat, and muscle content of patients were determined by quantitative CT technology and 62 cases of the health examination population matched by sex and age were selected for comparative analysis. Results: In the dialysis group, osteoporosis accounted for 17.70% (11 cases) and bone loss accounted for 30.60% (19 cases), while in the healthy control group, osteoporosis and bone loss accounted for 6.50% (4 cases) and 16.10% (10 cases), respectively. The difference between these two groups was statistically significant. Moreover, the intra-abdominal and subcutaneous fat content in the dialysis group were (113.70±63.29)cm² and (80.65±59.67)cm², respectively, which were lower than that of the healthy control group ((135.90±58.80)cm² and (122.26±54.94)cm², respectively). Additionally, the dialysis group had a significantly lower L3-SMA (107.00±30.70)cm² than the control group (121.37±32.87)cm², and the lumbar vertebral bone density value was significantly lower in male dialysis patients (156.11±51.94)mg/cm³ than in female dialysis patients (124.29±50.89)mg/cm³. Moreover, the subcutaneous fat content was significantly higher in females than in males; however, the difference in intraperitoneal fat content between males and females was not statistically significant. Additionally, the difference between bone density values and L3-SMA changes in the dialysis group and the length of dialysis time were not statistically significant. Conclusion: The incidence of osteoporosis is higher in patients on maintenance hemodialysis than in healthy people, and the amount of abdominal fat and muscle content are lower than that in healthy people. Moreover, quantitative CT body composition monitoring has high accuracy and sensitivity.

Copyright of CT Theory & Applications is the property of Editorial Department of CT Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective To investigate the changes of body composition and risk factors in patients with colorectal cancer（CRC） before and after treatment. Methods Data of 221 patients attacked by colorectal cancer who underwent radical surgery and postoperative intravenous chemotherapy in hospital from January 2018 to December 2021 were retrospectively analyzed. There were 124 males and 97 females. The CT images of the whole abdomen before and after treatment were analyzed. Quantitative CT（QCT） was used to measure lumbar bone mineral density（BMD）, abdominal subcutaneous fat area（SFA）, abdominal visceral fat area（VFA） and posterior vertebral muscle group muscle area（MA） before and after trement, and the abdominal total fat area（TFA） was calculated. Results The SFA after treatment was higher than that before treatment, and the BMD of the lumbar spine and the MA of the posterior vertebral muscle group were lower than before treatment（P＜0.05）. There was no statistical difference in TFA and VFA after treatment compared to before treatment（P＞0.05）. VFA and lumbar spine BMD were lower in patients ≥60 years of age after treatment than before treatment（P＜0.05）. There was no statistical difference in each body component before and after treatment in patients ＜60 years of age（P＞0.05）. Male patients had higher TFA and SFA after treatment than before treatment, and lower lumbar spine BMD and posterior vertebral muscle group MA than before treatment（P＜0.05）. In female patients, TFA and VFA were lower after treatment than before treatment（P＜0.05）. Male, laparotomy and colon cancer were independent risk factors for lumbar spine BMD decline（P＜0.05）. Male, rectal cancer, low lumbar spine BMD before treatment and high T-staging were independent risk factors for MA decline in posterior vertebral muscle group（P＜0.05）. Conclusion CRC patients undergoing radical surgery and postoperative chemotherapy will affect their body composition. Male, open surgery and colon cancer are independent risk factors for lumbar spine BMD decline. Male, rectal cancer, low lumbar spine BMD before treatment and high T-staging were independent risk factors for MA decline in posterior vertebral muscle group. [ABSTRACT FROM AUTHOR]

Introduction: The availability of highly effective triple cystic fibrosis transmembrane conductance regulator (CFTR) modulator combination therapy with elexacaftor–tezacaftor–ivacaftor (ETI) has improved pulmonary outcomes and quality of life of people with cystic fibrosis (pwCF). The aim of this study was to assess computed tomography (CT) changes under ETI visually with the Brody score and quantitatively with dedicated software, and to correlate CT measures with parameters of clinical response.Methods: Twenty two adult pwCF with two consecutive CT scans before and after ETI treatment initiation were retrospectively included. CT was assessed visually employing the Brody score and quantitatively by YACTA, a well-evaluated scientific software computing airway dimensions and lung parenchyma with wall percentage (WP), wall thickness (WT), lumen area (LA), bronchiectasis index (BI), lung volume and mean lung density (MLD) as parameters. Changes in CT metrics were evaluated and the visual and quantitative parameters were correlated with each other and with clinical changes in sweat chloride concentration, spirometry [percent predicted of forced expiratory volume in one second (ppFEV1)] and body mass index (BMI).Results: The mean (SD) Brody score improved with ETI [55 (12) vs. 38 (15); p < 0.001], incl. sub-scores for mucus plugging, peribronchial thickening, and parenchymal changes (all p < 0.001), but not for bronchiectasis (p = 0.281). Quantitatve WP (p < 0.001) and WT (p = 0.004) were reduced, conversely LA increased (p = 0.003), and BI improved (p = 0.012). Lung volume increased (p < 0.001), and MLD decreased (p < 0.001) through a reduction of ground glass opacity areas (p < 0.001). Changes of the Brody score correlated with those of quantitative parameters, exemplarily WT with the sub-score for mucus plugging (r = 0.730, p < 0.001) and peribronchial thickening (r = 0.552, p = 0.008). Changes of CT parameters correlated with those of clinical response parameters, in particular ppFEV1 with the Brody score (r = −0.606, p = 0.003) and with WT (r = −0.538, p = 0.010).Discussion: Morphological treatment response to ETI can be assessed using the Brody score as well as quantitative CT parameters. Changes in CT correlated with clinical improvements. The quantitative analysis with YACTA proved to be an objective, reproducible and simple method for monitoring lung disease, particularly with regard to future interventional clinical trials.

Objectives: Our goal was to compare the chest computed tomography (CT) imaging findings of COVID-19 in lung transplant recipients (LTR) and a group of non-transplanted controls (NTC). Methods: This retrospective study included 51 consecutive LTR hospitalized with COVID-19 from two centers. A total of 75 NTC were included for comparison. Images were classified regarding the standardized RSNA category, main pattern of lung attenuation, and longitudinal and axial distribution. Quantitative CT (QCT) analysis was performed to evaluate percentage of high attenuation areas (%HAA, threshold −250 to −700 HU). CT scoring was used to measure severity of parenchymal abnormalities. Results: The imaging findings of COVID-19 in LTR were significantly different from controls regarding the RSNA classification and pattern of lung attenuation. LTR had a significantly higher proportion of patients with an indeterminate pattern on CT (0.31 vs. 0.11, p = 0.014). The most frequent pattern of attenuation in LTR was predominantly consolidation (0.39 vs. 0.22, p = 0.144) followed by a mixed pattern of ground-glass opacities (GGO) and consolidation (0.37 vs. 0.20, adjusted p = 0.102). On the other hand, the most common pattern in NTC was GGO predominant (0.58 vs. 0.24 of LTR, p = 0.001). LTR had significantly more severe parenchymal disease measured by CT score and %HAA by QCT (0.372 ± 0.08 vs. 0.148 ± 0.06, p < 0.001). Conclusion: The most frequent finding of COVID-19 in LTR is a predominant pattern of consolidation. Compared to NTC, LTR more frequently demonstrated an indeterminate pattern according to the RSNA classification and more extensive lung abnormalities on QCT and semi-quantitative scoring. Key Points: • The most common CT finding of COVID-19 in LTR is a predominant pattern of consolidation followed by a mixed pattern of GGO and consolidation, while controls more often have a predominant pattern of GGO. • LTR more often presents with an indeterminate pattern of COVID-19 by RSNA classification than controls; therefore, molecular testing for COVID-19 is essential for LTR presenting with lower airway infection independently of imaging findings. • LTR had more extensive disease by semi-quantitative CT score and increased percentage areas of high attenuation on QCT. [ABSTRACT FROM AUTHOR]

Copyright of CT Theory & Applications is the property of Editorial Department of CT Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: The patient's position may affect the bone mineral density (BMD) measurements; however, the extent of this effect is undefined. This CT image-based simulation study quantified changes in BMD induced by hip flexion, adduction, and rotations to recommend appropriate patient positioning when acquiring dual-energy x-ray absorptiometry images. Purpose: Several studies have analyzed the effect of hip rotation on the measurement of bone mineral density (BMD) of the proximal femur by dual-energy x-ray absorptiometry (DXA). However, as the effects of hip flexion and abduction on BMD measurements remain uncertain, a computational simulation study using CT images was performed in this study. Methods: Hip CT images of 120 patients (33 men and 87 women; mean age, 82.1 ± 9.4 years) were used for analysis. Digitally reconstructed radiographs of the proximal femur region were generated from CT images to calculate the BMD of the proximal femur region. BMD at the neutral position was quantified, and the percent changes in BMD when hip internal rotation was altered from −30° to 15°, when hip flexion was altered from 0° to 30°, and when hip abduction was altered from –15° to 30° were quantified. Analyses were automatically performed with a 1° increment in each direction using computer programming. Results: The alteration of hip angles in each direction affected BMD measurements, with the largest changes found for hip flexion (maximum change of 17.7% at 30° flexion) and the smallest changes found for hip rotation (maximum change of 2.2% at 15° internal rotation). The BMD measurements increased by 0.34% for each 1° of hip abduction, and the maximum change was 12.3% at 30° abduction. Conclusion: This simulation study quantified the amount of BMD change induced by altering the hip position. Based on these results, we recommend that patients be positioned carefully when acquiring DXA images. [ABSTRACT FROM AUTHOR]

Abstract: Objective To investigate the effect of different amounts of abdominal adipose on the accuracy of low-mA quantitative computed tomography ( QCT) measurements of bone mineral density (BMD) in a spine phantom model. Methods Fresh porcine fat of different areas were wrapped around the European Spine Phantom ( ESP) to simulate different contents of total adipose tissue ( TAT) in human abdomen, which were divided into four groups according to TAT area; TAT = 0 cm², 200 cm², 320 cm², and 420 cm². The BMD values of the 1,1.3 vertebrae were measured using routine QCT and low-mA QCT with 10 repeated scans for each group of body models. A one-sample t-test was used to analyze the differences between the measurements obtained from low-mA QCT and the true values of the ESP. One-way ANOVA Tukey test was used to compare within-group differences in low-mA QCT measurements under different TAT conditions. The paired-sample t-test was used to compare the differences in BMD measurements for each vertebra between routine QCT and low-mA QCT. The root-mean-square errors (RMSEs) of the BMD measurements were calculated and compared; the correlation between RMSE and TAT was observed by Pearson correlation analysis. Results When TAT = 0 cm², 200 cm² and 320 cm², there were no statistically differences between routine QCT and low-mA QCT measurements ( P>0. 05), while TAT = 420 cm², significant differences were shown (P<0. 05) . TAT = 420 cm² group, the RMSEs using routine QCT were smaller than those using low-mA QCT. The RMSE of low-mA QCT was positively correlated with TAT; RMSEs of L1 vertebrae were constantly larger than those of L2 and L3 vertebrae under different TAT conditions. Conclusion Low-mA QCT is a reliable method to measure lumbar BMD as accurately as routine QCT for the general population and has a great advantage in radiation dose, while for the overweight/obese people, routine QCT is more accurate. [ABSTRACT FROM AUTHOR]

Characterizing changes in sacral bone density could help us to inform instrumentation choices for procedures involving the sacrum. The aim of this study is to provide detailed maps of changes in sacral bone density across a series of patients using opportunistic quantitative computed tomography (QCT). We hypothesized that there would be significant differences in local cortical and trabecular bone density associated with age and sex. Fifty‐four three‐dimensional sacral models were segmented from routine clinical computed tomography scans, and detailed bone density estimates were derived for each bone using a calibrated opportunistic QCT approach. The effects of age and sex on cortical and trabecular bone density were determined across the sample. Overall cortical bone loss averaged 2.1 and 0.9 mg/cc per year, and trabecular bone loss was 1.6 and 0.7 mg/cc for female and males, respectively. Several regions had loss rates several times greater. Areas that were significantly affected by age included the vertebral bodies, bilateral ala, apex, and areas adjacent to both the anterior and posterior sacral foramina. Areas that were significantly affected by sex were the anterior sacral promontory, aspects of the ala. Bone density distribution across the sacrum changes nonuniformly due to factors including sex and age. Despite these overall trends, there remains significant variability between individuals. Clinical significance: This study provides detailed bone density information for both cortical and trabecular bone that could assist orthopaedic surgeons in planning surgical approaches to sacral fracture fixation. [ABSTRACT FROM AUTHOR]

(1) Background: Quantitative CT analysis (QCT) has demonstrated promising results in the prognosis prediction of patients affected by COVID-19. We implemented QCT not only at diagnosis but also at short-term follow-up, pairing it with a clinical examination in search of a correlation between residual respiratory symptoms and abnormal QCT results. (2) Methods: In this prospective monocentric trial performed during the “first wave” of the Italian pandemic, i.e., from March to May 2020, we aimed to test the relationship between %deltaCL (variation of %CL-compromised lung volume) and variations of symptoms-dyspnea, cough and chest pain-at follow-up clinical assessment after hospitalization. (3) Results: 282 patients (95 females, 34%) with a median age of 60 years (IQR, 51–69) were included. We reported a correlation between changing lung abnormalities measured by QCT, and residual symptoms at short-term follow up after COVID-19 pneumonia. Independently from age, a low percentage of surviving patients (1–4%) may present residual respiratory symptoms at approximately two months after discharge. QCT was able to quantify the extent of residual lung damage underlying such symptoms, as the reduction of both %PAL (poorly aerated lung) and %CL volumes was correlated to their disappearance. (4) Conclusions QCT may be used as an objective metric for the measurement of COVID-19 sequelae.