Quantitative Computed Tomography Research Articles

Effect of adipose tissue deposition on insulin resistance in middle-aged and elderly women: Based on QCT and MRI mDIXON-Quant.

To explore the relationship between adipose tissue deposition and triglyceride-glucose (TyG) index, an indicator clinically used to assess insulin resistance (IR), in middle-aged and elderly women using quantitative computed tomography (QCT) and MRI mDIXON-Quant sequence. All participants underwent quantitative computed tomography (QCT) and MRI mDIXON-Quant examination and calculated the TyG index based on the fasting blood glucose and triacylglycerol. Bounded by the median TyG index, all participants were divided into low TyG group and high TyG group. Visceral fat mass (VFM) and subcutaneous fat mass (SFM) were measured on QCT images. Hepatic proton density fat fraction (H-PDFF), pancreatic proton density fat fraction (P-PDFF), and lumbar bone marrow fat fraction (L-BMFF) were measured on MRI mDIXON-Quant images. Adjusting for age and body mass index (BMI), TyG was moderately positively correlated with H-PDFF, and r/P was 0.416/<0.001, TyG index was weakly positively correlated with VFM and P-PDFF, and r/P were 0.385/<0.001 and 0.221/0.030. There was a difference of VFM, H-PDFF, and P-PDFF between low TyG group and high TyG group (P < 0.05). Adjusting for age and BMI, VFM, and H-PDFF were the risk factors of high TyG, and H-PDFF was the independent risk factor of high TyG. VFM and H-PDFF were the risk factors of IR, and H-PDFF was the independent risk factor. Early identification and active treatment of adipose tissue deposition, especially hepatic fat deposition, may reserve and delay the progression of IR and even metabolic syndrome.

Abstract 4135636: Age- and Sex-Related Coronary Atherosclerosis by Artificial Intelligence Quantitative Coronary CT Angiography from the INVICTUS Registry

Background: Coronary plaque analysis using artificial intelligence quantitative coronary CT (AI-QCT) is a promising tool to identify coronary atherosclerosis. However, there is insufficient data on coronary atherosclerosis volume and morphology using AI-QCT in patients who are at high risk of atherosclerosis. The purpose of this study is to clarify the differences in the volume and phenotypes of coronary atherosclerosis by age and gender using AI-QCT. Methods: The INVICTUS Registry is a multi-center registry enrolling patients who clinically underwent coronary CT angiography and invasive coronary angiography with invasive imaging modalities in Japan. Patients with a history of percutaneous coronary intervention or coronary artery bypass graft were excluded in this study. Using AI-QCT, the volume, and phenotypes (calcified, non-calcified, low-density non-calcified plaque [LD-NCP]) of coronary atherosclerosis were analyzed and assessed by age (&lt;55, 55-64, 65-74, and 75 and older) and gender. Results: A total of 982 patients were enrolled in the study. The mean age was 70.3 ± 10.8 years, 71.9% were male. Approximately two-thirds of patients had hypertension (73.3%) and dyslipidemia (71.5%), and 36.7% had diabetes. Mean total plaque volume (PV), calcified PV, non-calcified PV, and low-density PV were 745.5±529.8 mm 3 , 248.3±302.0 mm 3 , 482.2±340.6 mm 3 , and 15.0±29.4 mm 3 , respectively. The results of plaque volume and phenotypes by age are shown in the figure. Compared to those under 55 years of age, total PV increased gradually and significantly by about 10% for every 10 years of age (p=0.022). Though no significant difference was observed in non-calcified PV between the age groups (p=0.379), calcified PV progressively and significantly increases approximately 70% for every 10 years of age (p&lt;0.001). In contrast, the low-density plaque volume showed a trend toward a significant decrease with increasing age (p=0.073). These trends did not differ by gender. Conclusion: In a large cohort of patients at high risk for atherosclerosis analyzed by AI-QCT, total coronary PV increased with age, primarily calcified PV. While no change in non-calcified PV between the age groups, LD-NCPV was likely to decrease with increasing age. These findings may contribute to the guidance for the prevention of coronary artery diseases based on coronary atherosclerosis phenotype by age and gender.

Abstract 4144554: Revascularization of Patients with Low-Density Non-Calcified Plaque was Associated with Lower Occurrence of Acute Coronary Syndrome

INTRODUCTION: Coronary CT angiography (CCTA) is a powerful noninvasive tool for identifying high-risk plaque, such as low-density non-calcified plaque (LD-NCP). Though, the optimal treatment of patients with LD-NCP remains unclear. This study explored the association of revascularization in the setting of LD-NCP with the occurrence of acute coronary syndrome (ACS). Methods: This was a post-hoc analysis of the ICONIC study. A subset of 234 patients that underwent CCTA with subsequent ACS were matched to 234 control patients who also underwent CCTA but did not have ACS during follow-up. Patients were also followed for occurrence of revascularization, either coronary artery bypass graft or percutaneous coronary intervention. Atherosclerosis imaging-enabled quantitative CT (AI-QCT) was used to measure diameter stenosis, and LD-NCP, non-calcified plaque, and calcified plaque volumes from each CCTA. LD-NCP was defined as plaque with -190 to 30 Hounsfield Units. Patients were stratified based on the presence of LD-NCP. Subgroup analysis was conducted to compare the occurrence of ACS with the rate of revascularization. Kaplan-Meier survival curves and extended Cox regression analysis were used to evaluate the effect size of revascularization and LD-NCP on occurrence of ACS. Results: AI-QCT was completed in 448/468 subjects (follow-up time [MEAN±SD] 2.44±2.48 years). The median of LD-NCP was 1.2 mm 3 for patients with &gt;0 mm 3 LD-NCP. There were 85 patients with LD-NCP &gt;1.2 mm 3 and 363 patients with LD-NCP ≤1.2 mm 3 . In patients with LD-NCP &gt;1.2 mm 3 , the rate of revascularization in patients with and without ACS was 3/52 (5.8%) versus 14/33 (42.4%) (p&lt;0.001). In patients with LD-NCP ≤1.2 mm 3 , the rate of revascularization in patients with and without ACS was 36/170 (21.2%) versus 39/193 (20.2%) (p=0.897). In comparison to patients without revascularization and LD-NCP ≤1.2 mm 3 , patients with LD-NCP &gt;1.2 mm 3 and revascularization were less likely to have ACS during follow-up (adjusted HR: 0.20 [0.07, 0.61]; p=0.005). Additionally, patients with LD-NCP &gt;1.2 mm 3 who did not undergo revascularization were more likely to have ACS (adjusted HR: 1.47 [1.03, 2.12]; p=0.036). Hazard ratios were adjusted for diameter stenosis, and non-calcified and calcified plaque volume. Time-dependent coefficients were included for diameter stenosis. Conclusion: Revascularization of patients with LD-NCP &gt;1.2 mm 3 identified on CCTA with AI-QCT was associated with less risk for ACS.

Prediction of bone mineral density based on computer tomography images using deep learning model.

Introduction The problem of population aging is intensifying worldwide. Osteoporosis has become an important cause affecting the health status of older populations. However, the diagnosis of osteoporosis and people's understanding of it are seriously insufficient. We aim to develop a deep learning model to automatically measure bone mineral density (BMD) and improve the diagnostic rate of osteoporosis. Methods The images of 801 subjects with 2080 vertebral bodies who underwent abdominal paired computer tomography (CT) and quantitative computer tomography (QCT) scanning was retrived from June 2020 to January 2022. The BMD of T11-L4 vertebral bodies was measured by QCT. Developing a multi-stage deep learning-based model to simulate the segmentation of the vertebral body and predict BMD. The subjects were randomly divided into training dataset, validation dataset and test dataset. Analyze the fitting effect between the BMD measured by the model and the standard BMD by QCT. Accuracy, precision, recall and f1- score were used to analyze the diagnostic performance according to categorization criterion measured by QCT. Results 410 males (51.2%) and 391 females (48.8%) were included in this study. Among them, there were 154 (19.2%) males and 118 (14.7%) females aged 23-44; 182 (22.7%) males and 205 (25.6%) females aged 45-64; 74 (9.2%) males and 68 (8.5%) females aged 65-84. The number of vertebral bodies in the training dataset, the validation dataset, and the test dataset was 1433, 243, 404, respectively. In each dataset, the BMD of males and females decreases with age. There was a significant correlation between the BMD measured by the model and QCT, with the coefficient of determination (r2) 0.95-0.97. The diagnostic accuracy based on the model in the three datasets was 0.88, 0.91, and 0.91, respectively. Conclusion The proposed multi-stage deep learning-based model can achieve automatic measurement of vertebral BMD and performed well in the prediction of osteoporosis.

Quantifying Lower Extremity Blood Flow using Low-Dose CT Perfusion: Validation in a swine model

Abstract Background Quantitative assessment of blood flow in peripheral extremities in conjunction with simultaneous CT angiography measurements can improve risk assessment and provide a critical decision-making tool for patients across a wide spectrum of vascular disease severity. Purpose This study assessed the reproducibility and accuracy of lower extremity blood flow measurements with a low-dose first-pass analysis CT perfusion technique. Materials and Methods This prospective study utilized 16 Yorkshire Swine to obtain lower extremity blood flow CT measurements at baseline and under induced femoral stenosis using a vascular occluder. Thirty-three pairs of CT measurements evaluated reproducibility, and 43 CT measurements assessed accuracy against ultrasound flow probe references. Contrast agent and saline chaser were both injected peripherally at a rate of 5 mL/s. Bolus tracking was used, and a pre-contrast and post-contrast helical scan were acquired at the base and approximately the peak of the femoral enhancement (CT angiogram), respectively. The acquired data were then used as analytical inputs into a first-pass analysis model to derive perfusion in mL/min/g. The reproducibility and accuracy of lower extremity perfusion measurements were assessed via Mixed model regression and Bland-Altman analysis. Results Calculated CT perfusion measurements derived from first-pass analysis technique (PCT), and the reference standard ultrasound perfusion measurements (Pref) were related by PCT = 1.06 Pref + 0.00 (r2= 0.90, Root-Mean-Square Error = 0.01 mL/min/g). The first (P1) and second (P2) CT perfusion measurements were related by P2 = 0.98 P1 + 0.02 (r = 0.97, Root-Mean-Square Error = 0.11 mL/min/g). The average effective dose of perfusion measurement using first-pass analysis technique was calculated to be only 2.13 mSv. Conclusion The low-dose quantitative CT perfusion technique can accurately measure lower extremity perfusion (mL/min/g) using only two helical scans. The CT angiogram and perfusion measurements can be used as a comprehensive technique for morphological and physiological assessment of limb ischemia.

Utilizing artificial intelligence to determine bone mineral density using dual-layer spectral detector CT

BackgroundDual-energy computed tomography (DECT) has demonstrated the feasibility of using HAP-water to respond to BMD changes without requiring dedicated software or calibration. Artificial intelligence (AI) has been utilized for the diagnosis of osteoporosis in routine CT scans but has rarely been used in DECT. This study investigated the diagnostic performance of an AI system for osteoporosis screening using DECT images with reference quantitative CT (QCT) images. MethodsThis prospective study included 120 patients who underwent DECT and QCT scans from August to December 2023. Two convolutional neural networks, 3D RetinaNet, and 3D U-Net, were employed for automated vertebral body segmentation. The accuracy of the BMD measurements was assessed with relative measurement error (RME%). Linear regression and Bland–Altman analyses were performed to compare the BMD values between the AI and manual systems with those of the QCT. The diagnostic performance of the AI and manual systems for osteoporosis and low BMD was evaluated using receiver operating characteristic (ROC) curve analysis. ResultsThe overall mean RMEs for the AI and manual systems were − 15.93 ± 12.05 % and − 25.47 ± 14.83 %, respectively. BMD measurements using the AI system achieved greater agreement with the QCT results than those using the manual system (R2 = 0.946, 0.898, p < 0.001; mean bias, 23.27, 35.71 mg/cm3; 95 % LoA, −9.72 to 56.26, −11.45 to 82.87 mg/cm3). The areas under the curve for the AI and manual systems were 0.933–0.979 for detecting osteoporosis and 0.980–0.991 for low BMD. ConclusionThis AI system could achieve relatively high accuracy for automated BMD measurement on DECT scans, providing great potential for the follow-up of BMD in osteoporosis screening.

Endobronchial valve treatment improves chest-CT diaphragm configuration in COPD

This study investigated the impact of bronchoscopic lung volume reduction treatment using endobronchial valves (EBV) on diaphragm configuration. We successfully analyzed the diaphragm index using a newly developed quantitative computed tomography (QCT) tool before and after EBV treatment in forty patients with severe emphysema. We evaluated whether changes in the diaphragm index were associated with improvements in forced expiratory volume in 1 s (FEV1), residual volume (RV), Saint Georges Respiratory Questionnaire (SGRQ), and 6-min walking distance (6MWD) using Spearman's rho. The EBV treatment influenced the diaphragm configuration only on the treated side, resulting in an increased diaphragm curvature. There were significant associations of relative diaphragm index changes on the treated lung side or the entire diaphragm with improvements in FEV1 and 6MWD. These findings provide valuable insights into how EBV treatment affects the diaphragm in COPD patients.

Computed tomography coronary angiography assessment of left main coronary artery stenosis severity

BackgroundAngiographic assessment of left main coronary artery (LMCA) stenosis severity can be unreliable. In cases of ambiguity, intravascular ultrasound (IVUS) can be utilised with a minimal lumen area (MLA) of ≥6 ​mm2 an accepted threshold for safe deferral of revascularization. We sought to assess whether quantitative computer tomography coronary angiography (CTCA) measures could assist clinicians making LMCA revascularization decisions when compared with IVUS as gold standard. MethodsConsecutive patients undergoing IVUS assessment of angiographically intermediate LMCA stenosis were included. All patients had undergone 320-slice CTCA <90 days prior to IVUS imaging. Offline quantitative assessment of IVUS- and CT-derived measures were undertaken with the cohort divided into those with significant (s-LMCA) versus non-significant (ns-LMCA) disease using the accepted IVUS threshold. ResultsFifty-eight patients were included, with no difference in mean age (61.5 ​± ​12.2 vs. 59.7 ​± ​11.9 years, p ​= ​0.57), diabetic status (24.2% vs 16.0%, p ​= ​0.44) or other baseline demographics between groups. Patients with ns-LMCA had larger CT luminal area (8.64 ​± ​3.91 vs. 5.41 ​± ​1.54 ​mm2, p ​< ​0.001), larger minimal lumen diameter (MLD) (3.25 ​± ​0.74 vs. 2.56 ​± ​0.38 ​mm, p ​< ​0.001) and lower area stenosis (45.74 ​± ​18.10 vs. 60.93 ​± ​14.68%, p ​= ​0.001). There was a significant positive correlation between CTCA and IVUS MLA (r ​= ​0.68, p ​< ​0.001) and MLD (r ​= ​0.67, p ​< ​0.001). ROC analysis demonstrated CTCA MLA cut-off <8.29 ​mm2 provides the greatest negative predictive value and sensitivity in predicting the presence of significant LMCA disease. ConclusionCTCA derived MLA and MLD have a strong correlation with IVUS. A CTCA derived MLA cut-off <8.29 ​mm2 showed greatest clinical utility for predicting the need for further assessment, based on IVUS gold standard.

Gel dosimetry: An overview of dosimetry systems and read out methods

Gel dosimetry has emerged over the past three decades in response to a growing need in high-precision radiotherapy to assess, in three dimensions, the absorbed radiation dose, as would be administered in cancer patients.Radiation-induced reaction mechanisms are dependent on the class of gel dosimeter, with four classes emerging as primary dosimeters for use in radiation therapy dose verification: (i) Fricke gel dosimeters contain a Fricke solution consisting of ammonium iron (II) sulfate in an acidic solution of sulfuric acid. In Fricke systems an oxidation of ferrous ions results in a change in the nuclear magnetic resonance (NMR) relaxation rate, which enables reading out Fricke gel dosimeters by use of MRI. The radiation-induced oxidation in Fricke gel dosimeters can also be visualized by adding a redox indicator. (ii) Polymer gel dosimeters exploit the radiation induced polymerization reaction of vinyl monomers and are predominantly read out by quantitative MRI or X-ray CT. (iii) Radiochromic dosimeters do not demonstrate a significant radiation-induced change in NMR properties but can be scanned by use of optical scanners (optical CT). In contrast to Fricke gel dosimeters, radiochromic gel dosimeters do not rely on the oxidation of a metal ion but exhibit a color change upon radiation. (iv) Radiofluorogenic dosimeters become fluorescent when exposed to ionizing radiation and can be read out with a planar scanning light beam.Likewise, the imaging modality used to extract quantitative dose information depends on the class of dosimeter being used, and three primary imaging modalities have emerged in this context: quantitative MRI, x-ray CT, and optical CT imaging. The accuracy and precision of the dose information extracted from gel dosimetry systems depends on both the dosimetric properties of the gel dosimeters and the readout technique, and the optimal readout method depends on the gel dosimeter response.Despite remaining an active field of research and illustrations of the application of gel dosimetry for the validation of clinical dose distributions, the utilization of gel dosimetry as a routine clinical dosimeter has been rather limited. However, with the introduction of new radiotherapy techniques that focus on organ motion compensation, new fractionation schemes, and extreme dose rates, the need for 3D radiation dosimetry is apparent. Even with the need for 3D dosimetry being apparent, gel dosimetry faces continued challenges in areas regarding the extraction of reproducible, accurate, and precise dose information.This review paper focuses on an introduction to gel dosimeter classes; a detailed examination of the three readout techniques with emphasis on the achievable accuracy, precision, and optimization of readout parameters; an outlook on future applications in emerging new radiotherapy techniques. We note that the introduction of theragnostic hybrid MRI-Linacs that combine an MRI-scanner and a clinical linear accelerator create new opportunities for inline polymer gel dosimetry. Likewise, the use of cone beam CT on linear accelerators opens up the possibility to read out gel dosimeters on the linac. Multiple optical CT designs have shown that optical CT gel dosimetry is eminently capable of providing high quality dosimetric information from clinically relevant treatment regimes. As a result, gel dosimetry provides exciting opportunities for 3D radiation dosimetry that were not available even a few years ago. The unique feature set of a properly executed gel dosimetry workflow allows for the extraction of dosimetric information, in 3D, that is not possible with any other dosimetry system and hence gel dosimetry provides exciting opportunities for clinical and research work in the area of radiation dose measurement.

Quantitative texture analysis using machine learning for predicting interpretable pulmonary perfusion from non-contrast computed tomography in pulmonary embolism patients

BackgroundPulmonary embolism (PE) is life-threatening and requires timely and accurate diagnosis, yet current imaging methods, like computed tomography pulmonary angiography, present limitations, particularly for patients with contraindications to iodinated contrast agents. We aimed to develop a quantitative texture analysis pipeline using machine learning (ML) based on non-contrast thoracic computed tomography (CT) scans to discover intensity and textural features correlated with regional lung perfusion (Q) physiology and pathology and synthesize voxel-wise Q surrogates to assist in PE diagnosis.MethodsWe retrospectively collected 99mTc-labeled macroaggregated albumin Q-SPECT/CT scans from patients suspected of PE, including an internal dataset of 76 patients (64 for training, 12 for testing) and an external testing dataset of 49 patients. Quantitative CT features were extracted from segmented lung subregions and underwent a two-stage feature selection pipeline. The prior-knowledge-driven preselection stage screened for robust and non-redundant perfusion-correlated features, while the data-driven selection stage further filtered features by fitting ML models for classification. The final classification model, trained with the highest-performing PE-associated feature combination, was evaluated in the testing cohorts based on the Area Under the Curve (AUC) for subregion-level predictability. The voxel-wise Q surrogate was then synthesized using the final selected feature maps (FMs) and model score maps (MSMs) to investigate spatial distributions. The Spearman correlation coefficient (SCC) and Dice similarity coefficient (DSC) were used to assess the spatial consistency between FMs or MSMs and Q-SPECT scans.ResultsThe optimal model performance achieved an AUC of 0.863 during internal testing and 0.828 on the external testing cohort. The model identified a combination containing 14 intensity and textural features that were non-redundant, robust, and capable of distinguishing between high- and low-functional lung regions. Spatial consistency assessment in the internal testing cohort showed moderate-to-high agreement between MSMs and reference Q-SPECT scans, with median SCC of 0.66, median DSCs of 0.86 and 0.64 for high- and low-functional regions, respectively.ConclusionsThis study validated the feasibility of using quantitative texture analysis and a data-driven ML pipeline to generate voxel-wise lung perfusion surrogates, providing a radiation-free, widely accessible alternative to functional lung imaging in managing pulmonary vascular diseases.Clinical trial numberNot applicable.

Quantitative myocardial blood flow distribution derived from CCTA and determination of myocardium at risk in the FAST TRACK CABG trial

Abstract Background In the anatomic SYNTAX score derived from invasive coronary angiography, the ischemic impact of each stenotic coronary segment is weighed with a fixed score based on the severity of luminal diameter narrowing and the theoretical amount of blood flow supplied to the myocardium(1). This method neither accounts for individual variation nor reflects the true extent of myocardium ischemia. Purpose We aim to provide a quantitative CT SYNTAX score derived from coronary computed tomography angiography (CCTA) with customized percent blood flow distribution to the myocardium supplied by each stenotic coronary segment to determine the myocardium at risk of ischemia. Methods Patients with 3VD and/or left main coronary artery disease (CAD) were included in the first-in-human FAST TRACK CABG trial and received surgical revascularization guided solely by CCTA and fractional flow reserve derived from CCTA (FFRCT). The recently reported anatomic CT-SYNTAX score was calculated for all cases. The FFRCT value and percent myocardial blood flow distribution(%MBF) were computed for all 16 SYNTAX score segments using the validated method of Keulards et al(2). On the pre-CABG CCTA, the segments located distal to the site where the FFRCT value dropped below 0.80 were considered at risk of ischemia, and the individual weight point per segment was calculated as 6×%MBF for each segment. The SYNTAX score derived from %MBF is compared to the anatomic and functional CT-SYNTAX score. Results Out of 114 patients enrolled, FFRCT and %MBF were analyzable in 106 patients. After excluding vessels with total occlusion, the coronary flow distribution between the right and left coronary systems was 20.5% vs 79.5%, respectively, similar to the 1:5 ratio in the anatomic SYNTAX score. The anatomic and functional CT-SYNTAX scores were 43.6 and 41.1, respectively. The average total %MBF per patient was 72.0(19.1)%, and the average SYNTAX score derived from %MBF was 38.0. There is a strong correlation between functional SYNTAX score and SYNTAX score derived from %MBF (Peason’s R=0.93). Passing-Bablock regression trends showed that the functional SYNTAX score slightly overestimated the SYNTAX score derived from %MBF (Figure 1). The coronary segment weight varied significantly per individual, especially in the presence of total occlusion. Overall, the fixed weight of the anatomic SYNTAX score is a good surrogate for the individualized weighing based on %MBF (Figure 2). Conclusion CCTA-derived %MBF enabled clinicians to quantify the individualized myocardium at risk of ischemia or injury in patients with severe CAD. Retrospectively, the fixed weight score used in the anatomical SYNTAX score appeared to be a robust surrogate for myocardial blood flow distribution.Figure 1Figure 2

Impact of HHIP gene polymorphisms on phenotypes, serum IL-17 and IL-18 in COPD patients of the Chinese Han population

BackgroundGenetic factors, including the Hedgehog Interacting Protein (HHIP) gene, play a crucial role in Chronic Obstructive Pulmonary Disease (COPD) susceptibility. This study examines the association between HHIP gene polymorphisms and COPD susceptibility, phenotypes, and serum IL-17 and IL-18 levels in a Han Chinese population.MethodsA case-control study was conducted with 300 COPD patients and 300 healthy controls in Chinese Han population. Participants underwent genotyping for HHIP gene polymorphisms, pulmonary function tests, and quantitative CT scans. DNA samples were sequenced using a custom chip targeting the HHIP gene. Serum IL-17 and IL-18 levels were measured by enzyme-linked immunosorbent assay. Associations between SNPs, COPD susceptibility, and phenotypes were analyzed using logistic and multiple linear regression models, adjusting for confounders.ResultsOur study identified the rs11100865 polymorphism in the HHIP gene as significantly associated with COPD susceptibility (OR 2.479, 95% CI 1.527–4.024, P = 2.39E-04) after screening 114 SNPs through rigorous quality control. Stratified analyses further indicated this association was particularly in individuals aged 60 or older. Serum levels of IL-17 and IL-18 were significantly elevated in COPD patients compared to controls, with rs11100865 showing a notable association with IL-18 levels (B = 49.654, SE = 19.627, P = 0.012). However, no significant associations were observed between rs11100865 and serum IL-17 levels, COPD-related imaging parameters, or clinical phenotypes.ConclusionThis study identified a significant association between HHIP gene polymorphisms and COPD susceptibility in a Han Chinese population, with connections to inflammation, but found no significant associations between this SNP and COPD-related imaging or clinical phenotypes.Trial registrationwww.chictr.org.cn ID: ChiCTR2300071579 2023-05-18.

Pathophysiological Markers of Acute Respiratory Distress Syndrome Severity Are Correlated With Ventilation-Perfusion Mismatch Measured by Electrical Impedance Tomography.

Pulmonary ventilation/perfusion (V/Q) mismatch measured by electrical impedance tomography (EIT) is associated with the outcome of patients with the acute respiratory distress syndrome (ARDS), but the underlying pathophysiological mechanisms have not been fully elucidated. The present study aimed to verify the correlation between relevant pathophysiological markers of ARDS severity and V/Q mismatch. Prospective observational study. General ICU of a university-affiliated hospital. Deeply sedated intubated adult patients with ARDS under controlled mechanical ventilation. Measures of V/Q mismatch by EIT, respiratory mechanics, gas exchange, lung imaging, and plasma biomarkers. Unmatched V/Q units were assessed by EIT as the fraction of ventilated nonperfused plus perfused nonventilated lung units. At the same time, plasma biomarkers with proven prognostic and mechanistic significance for ARDS (carbonic anhydrase 9 [CA9], hypoxia-inducible factor 1 [HIF1], receptor for advanced glycation endproducts [RAGE], angiopoietin 2 [ANG2], gas exchange, respiratory mechanics, and quantitative chest CT scans were measured. Twenty-five intubated ARDS patients were included with median unmatched V/Q units of 37.1% (29.2-49.2%). Unmatched V/Q units were correlated with plasma levels of CA9 (rho = 0.47; p = 0.01), HIF1 (rho = 0.40; p = 0.05), RAGE (rho = 0.46; p = 0.02), and ANG2 (rho = 0.42; p = 0.03). Additionally, unmatched V/Q units correlated with plateau pressure (r = 0.38; p = 0.05) and with the number of quadrants involved on chest radiograph (r = 0.73; p < 0.01). Regional unmatched V/Q units were correlated with the corresponding fraction of poorly aerated lung tissue (r = 0.62; p = 0.01) and of lung tissue weight (rho: 0.51; p = 0.04) measured by CT scan. In ARDS patients, unmatched V/Q units are correlated with pathophysiological markers of lung epithelial and endothelial dysfunction, increased lung stress, and lung edema. Unmatched V/Q units could represent a comprehensive marker of ARDS severity, reflecting the complex organ pathophysiology and reinforcing their prognostic significance.

Characterization of bone lesions and bone mineral density of roadkilled wild animals in the Brazilian semi-arid

Highways are one of the anthropogenic factors that have the greatest impact on terrestrial biodiversity. Barriers, depletion effects, and roads are the most common locations of wild animal roadkill, leading to biodiversity loss in wild vertebrates. However, the corpses of these animals can be used as opportunistic samples, an excellent source of information on topics such as population dynamics, which is one of the aims of road ecology. Nonetheless, there are only a few studies on injuries in roadkilled wild animals. Between 2018 and 2021, road monitoring was performed around three Federal Conservation Units in Brazil. Twenty-four animals, including birds, reptiles, and mammals, were collected. This study aims to characterize the lesions in wild animals that were roadkilled on roads in the Brazilian semi-arid region using necropsy and quantitative computed tomography (QCT). Also, the bone mineral density was measured using QCT and compared with the number of lesions and body condition score. Four types of bone lesions were found in 13 different bones, with an average of 3.25 lesions per bird and 3.75 lesions per reptile and mammal, with no statistical difference between the means (p &amp;gt; 0.05). Providing a database on the main injuries found in wild animals that are frequently roadkilled serves as an aid to wildlife rescue and rehabilitation professionals who contribute to the conservation of species. In addition, the data on road ecology serves as a basis for the implementation of mitigation measures against wildlife roadkills, also contributing to the conservation of species.

Lung ultrasound score for the assessment of lung aeration in ARDS patients: comparison of two approaches.

Purpose A 4-step lung ultrasound (LUS) score has been previously used to quantify lung density. We compared 2 versions of this scoring system for distinguishing severe from moderate loss of aeration in ARDS: coalescence-based score (cLUS) vs. quantitative-based score (qLUS - >50% pleura occupied by artefacts). Materials and Methods We compared qLUS and cLUS to lung density measured by quantitative CT scan in 12 standard thoracic regions. A simplified approach (1 scan per region) was compared to an extensive one (regional score computed as the mean of all relevant intercostal space scores). Results We examined 13 conditions in 7 ARDS patients (7 at PEEP 5, 6 at PEEP 15 cmH2O-156 regions, 398 clips). Switching from cLUS to qLUS resulted in a change in interpretation in 117 clips (29.4%, 1-point reduction) and in 41.7% of the regions (64 decreases (range 0.2-1), 1 increase (0.2 points)). Regional qLUS showed very strong correlation with lung density (rs=0.85), higher than cLUS (rs=0.79; p=0.010). The agreement with CT classification in well aerated, poorly aerated, and not aerated tissue was moderate for cLUS (agreement 65.4%; Cohen's K coefficient 0.475 (95%CI 0.391-0.547); p<0.0001) and substantial for qLUS (agreement 81.4%; Cohen's K coefficient 0.701 (95%CI 0.653-0.765), p<0.0001). The agreement between single spot and extensive approaches was almost perfect (cLUS: agreement 89.1%, Cohen's kappa coefficient 0.840 (95%CI 0.811-0.911), p<0.0001; qLUS: agreement 86.5%, Cohen's kappa coefficient 0.819 (95%CI 0.761-0.848), p<0.0001). Conclusion A LUS score based on the percentage of occupied pleura performs better than a coalescence-based approach for quantifying lung density. A simplified approach performs as well as an extensive one.

Using QCT for the prediction of spontaneous age- and gender-specific thoracolumbar vertebral fractures and accompanying distant vertebral fractures.

To investigate the value and age- and gender-specific threshold values of bone mineral density (BMD) by quantitative computed tomography (QCT) for the prediction of spontaneous thoracolumbar vertebral fractures and thoracolumbar junction fractures accompanying distant vertebral fractures. Among the 556 patients included, 68 patients had thoracolumbar vertebral fractures (12 patients with distant vertebral fractures, 56 patients without distant vertebral fractures) and 488 patients had no vertebral fractures. All patients were grouped by gender and age. According to the principle of Youden index, the threshold values were calculated from receiver operating characteristic (ROC) curves. The threshold values for predicting thoracolumbar vertebral fractures were 89.8mg/cm3 for all subjects, 90.1mg/cm3 for men, and 88.6mg/cm3 for women. The threshold values for men aged < 60years old and ≥ 60years old were 117.4mg/cm3 and 87.5mg/cm3, respectively. The threshold values for women aged < 60years old and ≥ 60years old were 88.6 and 68.4mg/cm3, respectively. The threshold value for predicting spontaneous thoracolumbar junction fractures with distant vertebral fractures was 62.7mg/cm3. QCT provides a good ability to predict age- and gender-specific spontaneous thoracolumbar vertebral fractures, and to further predict spontaneous thoracolumbar junction fractures with distant vertebral fractures.

Feasibility study of opportunistic osteoporosis screening on chest CT using a multi-feature fusion DCNN model

SummaryA 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.PurposeTo 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.MethodsThe 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.ResultsThe 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.ConclusionThe 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.

Long-Term Reproducibility of BMD-Measurements with Clinical QCT Using Simultaneous and Asynchronous Calibration Methods and Different Measurement and Reconstruction Protocols.

Osteoporosis is underdiagnosed and undertreated. To improve timely fracture risk assessment optimized densitometry methods are required such as opportunistic spinal quantitative computed tomography (QCT). However, it is unclear how to best calibrate these scans and correct for potential scanner drift of QCT when used for monitoring bone mineral density (BMD) changes. We compared gold standard simultaneous calibration with asynchronous calibration methods, assessing mid-term (12weeks) and long-term (1.5years) reproducibility of BMD measurements. Cortical and trabecular compartments of the European Spine Phantom were studied with ten different protocols including low dose and high resolution (HR)-modes. Based on weekly phantom data, we compared simultaneous calibration to asynchronous single (termed global) or monthly calibration. The accuracy was better for trabecular measurements than for cortical measurements for all calibration methods. Reproducibility was excellent for all methods and slightly better for asynchronous than for simultaneous calibration both for trabecular and cortical bone. For HR protocols, reproducibility was better than for low dose measurements. In trabecular compartments averaged HR-BMD remained stable for global (- 0.1%/year, ns) but not for simultaneous calibration (- 1.5%/year, p < 0.001). No significant drifts could be detected for averaged low dose BMD (- 0.9 to + 0.8%/year) for either calibration method. Our data suggest that with regard to precision and accuracy measurements with asynchronous calibration are suitable for vertebral BMD assessment (no contrast agents) in clinical practice. Regular (e.g., monthly) stability tests using a calibration phantom could assure long term stability of at least 1year.

Quantitative CT imaging and radiation-absorbed dose estimations of 166Ho microspheres: paving the way for clinical application

BackgroundMicrobrachytherapy enables high local tumor doses sparing surrounding tissues by intratumoral injection of radioactive holmium-166 microspheres (166Ho-MS). Magnetic resonance imaging (MRI) cannot properly detect high local Ho-MS concentrations and single-photon emission computed tomography has insufficient resolution. Computed tomography (CT) is quicker and cheaper with high resolution and previously enabled Ho quantification. We aimed to optimize Ho quantification on CT and to implement corresponding dosimetry.MethodsTwo scanners were calibrated for Ho detection using phantoms and multiple settings. Quantification was evaluated in five phantoms and seven canine patients using subtraction and thresholding including influences of the target tissue, injected amounts, acquisition parameters, and quantification volumes. Radiation-absorbed dose estimation was implemented using a three-dimensional 166Ho specific dose point kernel generated with Monte Carlo simulations.ResultsCT calibration showed a near-perfect linear relation between radiodensity (HU) and Ho concentrations for all conditions, with differences between scanners. Ho detection during calibration was higher using lower tube voltages, soft-tissue kernels, and without a scanner detection limit. The most accurate Ho recovery in phantoms was 102 ± 11% using a threshold of mean tissue HU + (2 × standard deviation) and in patients 98 ± 31% using a 100 HU threshold. Thresholding allowed better recovery with less variation and dependency on the volume of interest compared to the subtraction of a single HU reference value. Corresponding doses and histograms were successfully generated.ConclusionCT quantification and dosimetry of 166Ho should be considered for further clinical application with on-site validation using radioactive measurements and intra-operative Ho-MS and dose visualizations.Relevance statementImage-guided holmium-166 microbrachytherapy currently lacks reliable quantification and dosimetry on CT to ensure treatment safety and efficacy, while it is the only imaging modality capable of quantifying high in vivo holmium concentrations.Key PointsLocal injection of 166Ho-MS enables high local tumor doses while sparing surrounding tissue.CT enables imaging-based quantification and radiation-absorbed dose estimation of concentrated Ho in vivo, essential for treatment safety and efficacy.Two different CT scanners and multiple acquisition and reconstruction parameters showed near-perfect linearity between radiodensity and Ho concentration.The most accurate Ho recoveries on CT were 102 ± 11% in five phantoms and 98 ± 31% in seven canine patients using thresholding methods.Dose estimations and volume histograms were successfully implemented for clinical application using a dose point kernel based on Monte Carlo simulations.Graphical

Advances in Research on Application of Quantitative CT in Clinical Diagnosis and Treatment of Osteoporosis.

Quantitative CT (QCT) is a method of measuring bone mineral density (BMD) of human based on a CT machine,calibrated by QCT body model and analyzed by professional software.Compared with dual-energy X-ray absorptiometry,QCT can not only assess the cortical and cancellous BMD but also exclude the influences of osteophytes and aortic/vascular calcification,thus being capable of accurately reflecting patients' bone mass.In recent years,increasing studies on QCT and osteoporosis (OP) have been carried out,and the application of QCT in the diagnosis of OP,evaluation of vertebral bone conditions,prediction of fracture risks,and assessment of anti-OP treatment is garnering increasing attention from researchers at home and abroad.This article reviews the research progress in this field,aiming to provide a reference for the research on QCT in the diagnosis and treatment of OP.