High-resolution Computed Tomography Images Research Articles

Imaging analysis of dural exposure in cholesteatomas with a skull base defect.

Dural exposure during cholesteatoma surgery can pose a risk of cerebrospinal fluid leakage or residual disease. Therefore, delicate handling of the area surrounding the bone defect in the cranial fossa is required. However, in small-sized defects, preoperative prediction of dural exposure can be challenging. This study aimed to evaluate the diagnostic value of computed tomography (CT) for preoperative prediction of cholesteatoma-related dural exposure in bone discontinuities in the skull base. We evaluated serial high-resolution CT images showing bone density discontinuities in the middle cranial fossa (MCF) requiring mastoidectomy for cholesteatoma. The CT and intraoperative findings were analyzed retrospectively. We evaluated the length between the superior margins of the bone density discontinuities using coronal CT planes. Receiveroperatingcharacteristic (ROC) curves were constructed to determine the optimal cut-off values. We extracted data from 107 bone density discontinuities, among which 54 (50.5%) showed dural exposure intraoperatively. Discontinuities with dural exposure (n = 54) had significantly greater lengths than did those without (n = 53) (p < 0.001, Wilcoxon rank-sum test). The area under the curve was 0.9780 according to the ROC analysis, and the optimal cut-off value was determined to be 2.99mm (sensitivity 92.59%; specificity 94.34%). A bone density discontinuity length of > 2.99mm in the MCF on coronal CT plane is a reliable diagnostic marker for cholesteatoma-related dural exposure. Thus, preoperative high-resolution CT analysis can inform optimal surgical preparation and planning before manipulating the area surrounding the osteolytic lesion in the MCF.

Quantitative Evaluation of Chronic Obstructive Pulmonary Disease and Risk Prediction of Acute Exacerbation by High-Resolution Computed Tomography.

Objective It is imperative to popularize the tertiary prevention of chronic obstructive pulmonary disease (COPD) and to improve the diagnosis and treatment. Methods COPD patients were divided into mild (n = 18), moderate (n = 20), severe (n = 24), and extremely severe (n = 22) groups for performing high-resolution computed tomography (HRCT) and pulmonary function test. Serum procalcitonin (PCT) and high-sensitivity C-reactive protein (hs-CRP) were detected, and the occurrence rate of acute exacerbation COPD (AECOPD) was recorded during a 12-months follow-up period. Results With an increase in the severity grade, the HRCT indexes, including emphysema index (EI), 1st and 15th percentile of inspiratory attenuation distribution (Perc1 and Perc15), ratio of expiratory/inspiratory mean lung density (MLDex/in) and lung volume (LVex/in), and ratio of the wall thickness to the outer diameter of the lumen (TDR), as well as percentage of the wall area to the total cross-sectional area (WA%) were increased with a decreased change in relative lung volume with attenuation values between −860 and −950 HU (RVC−860to −950) and lumen area (Ai). These were correlated with the ratio of forced expiratory volume in 1 sec (FEV1) over forced vital capacity (FVC) (FEV1/FVC), the percentage of FEV1 the predicted value (FEV1%), and ratio of residual volume to total lung volume (RV/TLC). Body mass index, MLDex/in, FEV1%, FEV1/FVC, and PCT had a predictive value to AECOPD, with the combined AUC of 0.812. Conclusions HRCT imaging effectively classifies the severity of COPD, which combined with BMI, PFT, and serum PCT can predict the risk of AECOPD.

Performance demonstration of a novel photon-counting CT for preclinical application

Photon-counting computed tomography (PC-CT) has attracted attention over the last few years as the next-generation CT technique that solves the problems encountered in clinical CT. In PC-CT, dark current and electronic noise can be reduced by setting the energy threshold to exceed the noise level, which leads to a low-dose scan. Furthermore, multiple energy thresholds realize multicolor CT imaging, which is not possible with clinical CT. Recently, we proposed a novel PC-CT system consisting of a multipixel photon counter (MPPC) coupled with a high-speed scintillator, performing simultaneous imaging of multiple contrast agents and estimate concentration. However, the PC-CT images obtained by our PC-CT system faces some limitations, such as degradation of image quality due to the lack of photon statistics and/or image resolution loss due to the pixel size of the detectors. In this study, the signal-to-noise ratio (SNR) of the PC-CT images was improved by applying machine-learning models, that is, U-Net and Noise2Noise, to the PC-CT images. In addition, a new imaging method was developed to acquire the high-resolution CT images required for clinical use. As a result, the resolution of the CT images improved from 1.04 mm to 0.77 mm. Finally, the visualization of contrast agents in plants was set as a challenge for the next step towards the clinical application of MPPC-based PC-CT. The results demonstrate that our PC-CT system can provide color imaging not only in phantom-based experiments, but also in plants close to an organism.

Ontogenetic Patterning of Human Subchondral Bone Microarchitecture in the Proximal Tibia.

Simple SummaryThe objective of this study is to explain the subchondral trabecular and the cortical ontogenetic changes that occur in the proximal tibia in both the medial and lateral condylar regions due to differential loadings associated with changing knee joint kinetics and body mass. The differential response of subchondral bone to changing mechanical loads during growth and development serves as a powerful tool to evaluate the significance of mechanical loading on subchondral bone morphology and joint development, and can offer insight into adult morphological variation for joint health.High-resolution computed tomography images were acquired for 31 proximal human tibiae, age 8 to 37.5 years, from Norris Farms #36 cemetery site (A.D. 1300). Morphometric analysis of subchondral cortical and trabecular bone architecture was performed between and within the tibial condyles. Kruskal–Wallis and Wilcoxon signed-rank tests were used to examine the association between region, age, body mass, and each morphometric parameter. The findings indicate that age-related changes in mechanical loading have varied effects on subchondral bone morphology. With age, trabecular microstructure increased in bone volume fraction (p = 0.033) and degree of anisotropy (p = 0.012), and decreased in connectivity density (p = 0.001). In the subchondral cortical plate, there was an increase in thickness (p < 0.001). When comparing condylar regions, only degree of anisotropy differed (p = 0.004) between the medial and lateral condyles. Trabeculae in the medial condyle were more anisotropic than in the lateral region. This research represents an innovative approach to quantifying both cortical and trabecular subchondral bone microarchitecture in archaeological remains.

Unsupervised domain selective graph convolutional network for preoperative prediction of lymph node metastasis in gastric cancer.

Preoperative prediction of lymph node (LN) metastasis based on computed tomography (CT) scans is an important task in gastric cancer, but few machine learning-based techniques have been proposed. While multi-center datasets increase sample size and representation ability, they suffer from inter-center heterogeneity. To tackle the above issue, we propose a novel multi-source domain adaptation framework for this diagnosis task, which not only considers domain-invariant and domain-specific features, but also achieves the imbalanced knowledge transfer and class-aware feature alignment across domains. First, we develop a 3D improved feature pyramidal network (i.e., 3D IFPN) to extract common multi-level features from the high-resolution 3D CT images, where a feature dynamic transfer (FDT) module can promote the network's ability to recognize the small target (i.e., LN). Then, we design an unsupervised domain selective graph convolutional network (i.e., UDS-GCN), which mainly includes three types of components: domain-specific feature extractor, domain selector and class-aware GCN classifier. Specifically, multiple domain-specific feature extractors are employed for learning domain-specific features from the common multi-level features generated by the 3D IFPN. A domain selector via the optimal transport (OT) theory is designed for controlling the amount of knowledge transferred from source domains to the target domain. A class-aware GCN classifier is developed to explicitly enhance/weaken the intra-class/inter-class similarity of all sample pairs across domains. To optimize UDS-GCN, the domain selector and the class-aware GCN classifier provide reliable target pseudo-labels to each other in the iterative process by collaborative learning. The extensive experiments are conducted on an in-house CT image dataset collected from four medical centers to demonstrate the efficacy of our proposed method. Experimental results verify that the proposed method boosts LN metastasis diagnosis performance and outperforms state-of-the-art methods. Our code is publically available at https://github.com/infinite-tao/LN_MSDA.

Serum Derivatives of Reactive Oxygen Metabolites are Associated with Severity of Chronic Obstructive Pulmonary Disease and Affected by a p53 Gene Polymorphism.

PurposeOxidative stress is known to activate tumor suppressor p53, which inhibits cell cycle progression and induces apoptosis. Levels of p53 in lung tissues from patients with chronic obstructive pulmonary disease (COPD) are increased compared with levels in nonsmokers or smokers without emphysema. A polymorphism in p53 codon 72 (rs1042522) is associated with emphysematous changes in patients with COPD. However, whether oxidative stress in the serum is associated with the p53 polymorphism and disease severity in COPD patients is unclear.Patients and MethodsA total of 251 patients with a history of smoking more than 10 pack-years were enrolled in this study, and serum levels of derivatives of reactive oxygen metabolites (d-ROMs), biological antioxidant potential (BAP), and d-ROMs/BAP ratio (oxidative stress index; OSI) were measured. The percent low-attenuation area (LAA%) and cross-sectional area of the erector spinae muscles (ESMCSA) at the Th12 level were calculated from chest high-resolution computed tomography images. p53 codon 72 C/G genotyping was performed using polymerase chain reaction–restriction fragment length polymorphism analysis.ResultsIn patients carrying the p53 GG genotype, LAA% was significantly higher than in those carrying the CC genotype. d-ROM levels and OSI were associated with COPD severity and correlated with airflow limitation and markers of muscle atrophy (ESMCSA and creatinine/cystatin C ratio). Associations between markers of oxidative stress and COPD severity were observed primarily in patients carrying the p53 codon 72 GG genotype.ConclusionSusceptibility to pulmonary emphysema and responses to oxidative stress may be affected by the p53 gene polymorphism.

Comparison of two ancient Egyptian Middle Kingdom statuettes from the Museo Egizio of Torino through computed tomographic measurements

X-ray Computed Tomography (CT) has a significant role as investigation tool not only in medical and industrial applications, but also in cultural heritage studies. One of the main reasons for such broad adoption of this method is its non-destructive capability to investigate the inner structure of precious and unique artefacts that would instead be damaged by traditional sampling procedures. Ordinary X-ray radiography is limited and gives only 2D images, while high-resolution X-ray CT imaging gives non-invasive access to three-dimensional (3D) information. This article focuses on the comparison of micro-CT results obtained from the analysis of two ancient Egyptian wooden statuettes representing offering bearers. The artefacts belong to the collection of the Museo Egizio of Torino as part of the funerary assemblage of Minhotep, discovered in the Asyut necropolis. For the analysis, an upgraded version of the X-ray imaging apparatus located in the Centro Conservazione e Restauro “La Venaria Reale” (CCR) was used, in order to reach a higher final resolution than the one already present and used at CCR. Thanks to this investigation, much information on the artistic technique was obtained and it was possible to highlight differences and similarities in the technical features of the two statuettes, acquiring elements to understand the specific contribution of micro-tomography in studying the finds and hypothesizing a common production method.

Prognostic impact of artificial intelligence-based volumetric quantification of the solid part of the tumor in clinical stage 0-I adenocarcinoma

IntroductionThe size of the solid part of a tumor, as measured using thin-section computed tomography, can help predict disease prognosis in patients with early-stage lung cancer. Although three-dimensional volumetric analysis may be more useful than two-dimensional evaluation, measuring the solid part of some lesions is difficult using this methods. We developed an artificial intelligence-based analysis software that can distinguish the solid and non-solid parts (ground-grass opacity). This software calculates the solid part volume in a totally automated and reproducible manner. The predictive performance of the artificial intelligence software was evaluated in terms of survival or recurrence-free survival. MethodsWe analyzed the high-resolution computed tomography images of the primary lesion in 772 consecutive patients with clinical stage 0-I adenocarcinoma. We performed automated measurement of the solid part volume using an artificial intelligence-based algorithm in collaboration with FUJIFILM Corporation. The solid part size, the solid part volume based on traditional three-dimensional volumetric analysis, and the solid part volume based on artificial intelligence were compared. ResultsHigher areas under the curve related to the solid part volume were provided by the artificial intelligence-based method (0.752) than by the solid part size (0.722) and traditional three-dimensional volumetric analysis-based method (0.723). Multivariate analysis demonstrated that the solid part volume based on artificial intelligence was independently correlated with overall survival (P = 0.019) and recurrence-free survival (P < 0.001). ConclusionThe solid part volume measured by artificial intelligence was superior to conventional methods in predicting the prognosis of clinical stage 0-I adenocarcinoma.

Comparison of the Utility of High-Resolution CT-DWI and T2WI-DWI Fusion Images for the Localization of Cholesteatoma.

Cholesteatoma is an aggressive disease that may lead to hearing impairment. This study aimed to compare the utility of high-resolution CT and TSE-DWI fusion images with that of T2WI and TSE-DWI fusion images in the localization of middle ear cholesteatoma. Seventy-one patients with middle ear cholesteatoma were retrospectively recruited. High-resolution CT, T2WI with fat suppression, and TSE-DWI scans were obtained, and image fusion was performed using a 3D reconstruction postprocessing workstation to form CT-DWI and T2WI-DWI fusion images. The quality of the 2 fused images was subjectively evaluated using a 5-point Likert scale with the horizontal semicircular canal transverse position as the reference. Receiver operating characteristic analysis was performed, and the diagnostic efficacies of CT-DWI and T2WI-DWI fusion images in localizing middle ear cholesteatoma were calculated. The overall quality of T2WI-DWI fusion images was slightly higher than that of CT-DWI fusion images (P < .001), and the semicircular canal was slightly less clear on T2WI-DWI than on CT-DWI (P < .001). No statistical difference was found in the diagnostic confidence between them. In the localization of middle ear cholesteatoma, the accuracy, sensitivity, and specificity of T2WI-DWI fusion images and CT-DWI fusion images were equivalent for involvement of the attic, tympanic cavity, mastoid antrum, and mastoid process, with no statistically significant differences. T2WI-DWI fusion images could replace CT-DWI in the preoperative selection of surgical options for middle ear cholesteatoma.

Humain Lens: The Disruptive Impact of AI and Precision Lung Data on Respiratory Trials

Humain Lens: The Disruptive Impact of AI and Precision Lung Data on Respiratory Trials

The Efficacy and Safety of Pirfenidone Combined With Immunosuppressant Therapy in Connective Tissue Disease-Associated Interstitial Lung Disease: A 24-Week Prospective Controlled Cohort Study.

ObjectiveInterstitial lung disease (ILD) is a common manifestation of connective tissue disease (CTD) that manifests as several subtypes with significant differences in prognosis. It is necessary to evaluate the efficacy and safety of pirfenidone (PFD) combined with immunosuppressant (IS) in the treatment of CTD-ILD.MethodsA total of 111 patients with CTD-ILD were enrolled, including those with systemic sclerosis (SSc), inflammatory myopathy (IIM), rheumatoid arthritis (RA), and other CTDs (such as systemic lupus erythematosus, primary Sjogren's syndrome, and undifferentiated CTD). After evaluation of the high-resolution computed tomography (HRCT), pulmonary function (PF), and basic disease activity, patients either were or were not prescribed PFD and were followed up regularly for 24 weeks.ResultsAfter 24 weeks of treatment, predicted forced vital capacity (FVC%) in the SSc-PFD group had improved by 6.60%, whereas this value was 0.55% in patients with SSc-no-PFD. The elevation in FVC% was also significant in IIM-PFD over the IIM-no-PFD controls (7.50 vs. 1.00%). The predicted diffusing capacity for carbon monoxide (DLCo%) of RA-PFD was enhanced by 7.40%, whereas that of RA-no-PFD decreased by 5.50%. When performing a subtype analysis of HRCT images, the change in FVC% among patients with SSc with a tendency toward usual interstitial pneumonia (UIP) was higher in those given PFD (SSc-PFD-UIP) than the no-PFD group (8.05 vs. −3.20%). However, in IIM patients with a non-UIP tendency, PFD displayed better therapeutic effects than the control (10.50 vs. 1.00%). DLCo% improved significantly in patients with the PFD-treated RA-non-UIP subtype compared with the patients with no-PFD (10.40 vs. −4.45%). Dichotomizing the patients around a baseline FVC% or DLCo% value of 70%, the PFD arm had a more improved FVC% than the no-PFD arm within the high-baseline-FVC% subgroups of patients with SSc and IIM (6.60 vs. 0.10%, 6.30 vs. 1.10%). In patients with RA-PFD, DLCo% showed a significant increase in the subgroup with low baseline DLCo% compared to that in patients with RA-no-PFD (7.40 vs. −6.60%).ConclusionThe response of PF to PFD varied between CTD-ILD subsets. Patients with SSc and IIM showed obvious improvements in FVC%, especially patients with SSc-UIP and IIM-non-UIP. In RA, the subsets of patients with non-UIP and a lower baseline DLCo% most benefited from PFD.

Natural History of Contralateral Bullae/Blebs After Ipsilateral Video-Assisted Thoracoscopic Surgery for Primary Spontaneous Pneumothorax: A Retrospective Cohort Study

Contralateral bullae/blebs are frequently found in patients who are scheduled to undergo ipsilateral video-assisted thoracoscopic surgery (VATS) for primary spontaneous pneumothorax (PSP). Should visible contralateral bullae/blebs be simultaneously resected when ipsilateral VATS bullectomy is performed? In this single-center, retrospective cohort study, we included patients aged≤ 30 years who underwent ipsilateral VATS for PSP from April 2009 to December 2019. Electronic medical records, radiograph images, and preoperative high-resolution CT images were reviewed. The primary end point was recurrence-free survival (no contralateral pneumothorax) after discharge of ipsilateral VATS for PSP, determined via Kaplan-Meier analysis. Recurrence was compared between the group with and that without contralateral bullae/blebs by using the log-rank test. A multivariable Cox proportional hazards model was constructed to investigate risk factors for contralateral pneumothorax. Among 567 patients, contralateral pneumothorax occurred in 86 of them after ipsilateral VATS (15.2%) during a median follow-up period of 51.3 (interquartile range, 67.2) months. The 1-, 5-, and 10-year recurrence-free survival rates were 92.2%, 83.7%, and 79.9%, respectively. Contralateral recurrence was higher in the group with (82/455, 18.0%) than in that without (4/112, 3.6%) contralateral bullae/blebs (P< .001). Age (hazard ratio [HR], 0.701; 95%CI, 0.629-0.780; P< .001), current smoking (HR, 2.106; 95%CI, 1.158-3.831; P= .015), and the presence of bullae/blebs (increasing with size, HR, 4.818-8.980; all P< .05) were independent risk factors for contralateral pneumothorax. The annual rates of contralateral pneumothorax in the group with (4.0%) and in that without (0.7%) contralateral bullae/blebs declined over time. Although contralateral bullae/blebs were common in patients who underwent ipsilateral VATS for PSP and were statistically significantly associated with future pneumothorax, the annual rate of pneumothorax was 4.0%in such patients, and it decreased over time. Therefore, a conservative approach on unruptured contralateral bullae/blebs is recommended.

Characterizing the Correlation Between Angiogenesis and Osteogenesis In Vivo Using Multicontrast Functional Imaging in a Calvarial Defect Model

Angiogenesis is a key factor in bone healing that allows the delivery of oxygen, nutrients, inflammatory and bone precursor cells to the defect site. It induces dramatic structural and functional remodeling of the vasculature during the first 4 weeks of bone healing. Although recent advances in optical imaging have elucidated the in vivo relationship between angiogenesis and osteogenesis in a calvarial defect model, these efforts were mostly limited to structural imaging of the vasculature and bone. Therefore, to better characterize changes in vascular function (i.e. blood flow, oxygenation, etc.) during the bone healing cascade we developed a multicontrast optical imaging framework to assess in vivo changes in microvascular architecture using intrinsic optical signal (IOS) imaging; changes in blood flow with laser speckle contrast (LSC) imaging; and bone formation with bright‐field imaging at high spatial (5 µm) and temporal (200 ms) resolutions. With this system we acquired multicontrast images from 10 animals with calvarial defects every 2 days, over 4 weeks (Fig. 1a, d). The bone and vasculature were then digitally segmented from the bright‐field and IOS images for quantitative analysis (Fig. 1b, c). We also euthanized an animal each week for assessing 3D changes in bone volume and vascular architecture using an ex vivo, high‐resolution (10 µm) CT imaging workflow we recently developed called VascuViz (Fig. 2a, b, d). Using this framework, we demonstrated that angiogenic remodeling within the bone defect microenvironment was most robust from post injury day (D) 4 to D10, during which blood vessel length, volume and density all showed significant increase (Fig. 2c). The blood flow exhibited a sudden increase at D6 when angiogenesis started, and the angiogenic vessels were most perfused at D12 (Fig. 1d). These vascular changes peaked by the end of week 2 and plateaued during the next 2 weeks which were correlated with a large increase in bone volume during the first 2 weeks and smaller increase during the last 2 weeks (Fig. 2e). These results indicate that both structural and functional changes of the microvascular system strongly correlate with bone growth during the early stages of bone healing.Next, we plan to include additional indices of vascular function such as vessel maturity and intravascular oxygenation, as well as image‐based hemodynamic models to further characterize the role of the vascular microenvironment during osteogenesis. We believe that this novel imaging framework for characterizing the defect microenvironment can be utilized to inform the design of novel tissue engineering (TE) constructs for craniofacial bone regeneration. Collectively, these advances herald a new era of “image‐based TE”.

Cerebral Vascular Density and Its Possible Correlation with Alzheimer Disease Progression in Elderly Individuals with Rheumatoid Arthritis

BackgroundRheumatoid Arthritis (RA) is characterized by chronic systemic inflammation, primarily affecting the joints. In RA patients, high concentrations of inflammatory cytokines are found within the synovial fluid and serum (PMID: 1700672). These cytokines reduce the blood brain barrier (BBB) integrity by decreasing the expression of tight junction proteins (PMID: 29910805). In a RA animal model such decreased BBB integrity has been shown to affect the transport of amyloid beta peptide (Aβ) between the peripheral circulation and the brain, thereby promoting accumulation of Aβ within the cerebral vasculature followed by the endothelial cell degeneration (PMID: 22029666). In humans, a similar pathologic process is a major risk factor for Alzheimer’s Disease (AD) which accelerates neuronal loss and cognitive impairment associated with AD (PMID: 29377008). Assessment of cerebral vascular density is an emerging modality for detection and monitoring the progression of cerebrovascular disease (CVD) (PMID: 15564412). Advancements in computed tomography (CT) imaging technology and the development of novel contrast agents should provide more accurate assessment for CVD in humans.The main objective of this study was to test high‐resolution CT imaging using a recently developed BriteVu contrast agent in conjunction with conventional histological techniques for postmortem assessment of CVD and pathology in the cerebral cortex and hippocampus of two male cadavers. The first, 74‐year‐old (D1) was diagnosed with RA and AD, while the second, 90‐year‐old (D2) had RA.ResultsThe D1 and D2 cadavers were fixed and perfused with BriteVu contrast agent. Heads were removed and scanned with a VimagoGT30 CT scanner at 300 µm. The images were subjected to volumetric analysis using Radiant software. The results showed that scans of the cerebral cortex from D2, specifically the middle frontal, inferior parietal, and superior temporal gyri, had significantly lower mean Hounsfield unit densities (MHUD) than those from the same regions of D1. The MHUD from the hippocampal scans revealed no significant difference. The lower MHUD count in the D2 cortex in comparison to D1 most likely reflects a lower vascular density in the respective brain region. The AD related pathology in both donors was assessed by histochemical and immunohistochemical techniques. To that end, the brains were extracted and fixed in formalin solution for 12‐16 weeks. The brain hippocampal and cortical sections were paraffin processed followed by H&amp;E and immunohistochemical staining for Aβ 1‐42, phospho‐tau, and phospho‐TDP‐43. Analysis of the data confirmed the AD diagnosis in D1 and demonstrated distinct AD pathology in D2. The AD staging could be characterized as mild in D1 and intermediate in D2.Conclusionsi) The vascular density within the cerebral cortex of elderly individuals with RA could correlate with the AD progression. ii) The adaptation of the reported CT imaging technique for its use in live individuals could provide more sensitive and accurate method for assessing AD in RA patients at the early AD stage(s).

Quantitative imaging analysis detects subtle airway abnormalities in symptomatic military deployers

BackgroundExposure to inhalational hazards during post-9/11 deployment to Southwest Asia and Afghanistan puts military personnel at risk for respiratory symptoms and disease. Pulmonary function and qualitative chest high resolution computed tomography (HRCT) are often normal in “deployers” with persistent respiratory symptoms. We explored the utility of quantitative HRCT imaging markers of large and small airways abnormalities, including airway wall thickness, emphysema, and air trapping, in symptomatic deployers with clinically-confirmed lung disease compared to controls.MethodsChest HRCT images from 45 healthy controls and 82 symptomatic deployers with asthma, distal lung disease or both were analyzed using Thirona Lung quantification software to calculate airway wall thickness (by Pi10), emphysema (by percentage of lung volume with attenuation < -950 Hounsfield units [LAA%-950]), and three parameters of air trapping (expiratory/inspiratory total lung volume and mean lung density ratios, and LAA%-856). SAS v.9.4 was used to compare demographic and clinical characteristics between deployers and controls using Chi-Square, Fisher Exact or t-tests. Linear regression was used to assess relationships between pulmonary function and quantitative imaging findings.ResultsGender and smoking status were not statistically significantly different between groups, but deployers were significantly younger than controls (42 vs 58 years, p < 0.0001), had higher body mass index (31 vs 28 kg/m2, p = 0.01), and had fewer total smoking pack-years (8 vs. 26, p = 0.007). Spirometric measures were not statistically significantly different between groups. Pi10 and LAA%-950 were significantly elevated in deployers compared to controls in unadjusted analyses, with the emphysema measure remaining significantly higher in deployers after adjustment for age, sex, smoking, BMI, and expiratory total lung volume. Air trapping parameters were more common in control images, likely due to differences in age and smoking between groups. Among deployers, LAA%-950 and Pi10 were significantly correlated with spirometric markers of obstruction based on ratio of forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) and/or percent predicted FEV1.ConclusionsQuantitative chest HRCT imaging analysis identifies emphysema in deployers with asthma and distal lung disease, and may be useful in detecting and monitoring deployment-related lung disease in a population where spirometry is typically normal.

High-Resolution Computer Tomography Image Features of Lungs for Patients with Type 2 Diabetes under the Faster-Region Recurrent Convolutional Neural Network Algorithm.

The objective of this study was to adopt the high-resolution computed tomography (HRCT) technology based on the faster-region recurrent convolutional neural network (Faster-RCNN) algorithm to evaluate the lung infection in patients with type 2 diabetes, so as to analyze the application value of imaging features in the assessment of pulmonary disease in type 2 diabetes. In this study, 176 patients with type 2 diabetes were selected as the research objects, and they were divided into different groups based on gender, course of disease, age, glycosylated hemoglobin level (HbA1c), 2 h C peptide (2 h C-P) after meal, fasting C peptide (FC-P), and complications. The research objects were performed with HRCT scan, and the Faster-RCNN algorithm model was built to obtain the imaging features. The relationships between HRCT imaging features and 2 h C-P, FC-P, HbA1c, gender, course of disease, age, and complications were analyzed comprehensively. The results showed that there were no significant differences in HRCT scores between male and female patients, patients of various ages, and patients with different HbA1c contents (P > 0.05). As the course of disease and complications increased, HRCT scores of patients increased obviously (P < 0.05). The HRCT score decreased dramatically with the increase in the contents of 2 h C-P and FC-P after the meal (P < 0.05). In addition, the results of the Spearman rank correlation analysis showed that the course of disease and complications were positively correlated with the HRCT scores, while the 2 h C-P and FC-P levels after meal were negatively correlated with the HRCT scores. The receiver operating curve (ROC) showed that the accuracy, specificity, and sensitivity of HRCT imaging based on Faster-RCNN algorithm were 90.12%, 90.43%, and 83.64%, respectively, in diagnosing lung infection of patients with type 2 diabetes. In summary, the HRCT imaging features based on the Faster-RCNN algorithm can provide effective reference information for the diagnosis and condition assessment of lung infection in patients with type 2 diabetes.

Radiomics for the Prediction of Response to Antifibrotic Treatment in Patients with Idiopathic Pulmonary Fibrosis: A Pilot Study.

Antifibrotic therapy has changed the treatment paradigm for idiopathic pulmonary fibrosis (IPF); however, a subset of patients still experienced rapid disease progression despite treatment. This study aimed to determine whether CT-based radiomic features can predict therapeutic response to antifibrotic agents. In this retrospective study, 35 patients with IPF on antifibrotic treatment enrolled from two centers were divided into training (n = 26) and external validation (n = 9) sets. Clinical and pulmonary function data were collected. The patients were categorized into stable disease (SD) and progressive disease (PD) groups based on functional or radiologic criteria. From pretreatment non-enhanced high-resolution CT (HRCT) images, twenty-six radiomic features were extracted through whole-lung texture analysis, and six parenchymal patterns were quantified using dedicated imaging platforms. The predictive factors for PD were determined via univariate and multivariate logistic regression analyses. In the training set (SD/PD: 12/14), univariate analysis identified eight radiomic features and ground-glass opacity percentage (GGO%) as potential predicators of PD. However, multivariate analysis found that the single independent predictor was the sum entropy (accuracy, 80.77%; AUC, 0.75). The combined sum entropy-GGO% model improved the predictive performance in the training set (accuracy, 88.46%; AUC, 0.77). The overall accuracy of the combined model in the validation set (SD/PD: 7/2) was 66.67%. Our preliminary results demonstrated that radiomic features based on pretreatment HRCT could predict the response of patients with IPF to antifibrotic treatment.

Breaking strength and bone microarchitecture in osteoporosis: a biomechanical approximation based on load tests in 104 human vertebrae from the cervical, thoracic, and lumbar spines of 13 body donors

BackgroundThe purpose of the study was to investigate associations between biomechanical resilience (failure load, failure strength) and the microarchitecture of cancellous bone in the vertebrae of human cadavers with low bone density with or without vertebral fractures (VFx).MethodsSpines were removed from 13 body donors (approval no. A 2017-0072) and analyzed in regard to bone mineral density (BMD), Hounsfield units (HU), and fracture count (Fx) with the aid of high-resolution CT images. This was followed by the puncture of cancellous bone in the vertebral bodies of C2 to L5 using a Jamshidi™ needle. The following parameters were determined on the micro-CT images: bone volume fraction (BVF), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp), degree of anisotropy (DA), trabecular number (Tb.N), trabecular pattern factor (Tb.Pf), and connectivity density (Conn.D). The axial load behavior of 104 vertebral specimens (C5, C6, T7, T8, T9, T12, L1, L3) was investigated with a servohydraulic testing machine.ResultsIndividuals with more than 2 fractures had a significantly lower trabecular pattern factor (Tb.Pf), which also proved to be an important factor for a reduced failure load in the regression analysis with differences between the parts of the spine. The failure load (FL) and endplate sizes of normal vertebrae increased with progression in the craniocaudal direction, while the HU was reduced. Failure strength (FS) was significantly greater in the cervical spine than in the thoracic or lumbar spine (p < 0.001), independent of sex. BVF, Tb.Th, Tb.N, and Conn.D were significantly higher in the cervical spine than in the other spinal segments. In contrast, Tb.Sp and Tb.Pf were lowest in the cervical spine. BVF was correlated with FL (r = 0.600, p = 0.030) and FS (r = 0.763, p = 0.002). Microarchitectural changes were also detectable in the cervical spine at lower densities.ConclusionsDue to the unique microarchitecture of the cervical vertebrae, fractures occur much later in this region than they do in the thoracic or lumbar spine.Trial registrationApproval no. A 2017-0072.

The Octopus Sign-A New HRCT Sign in Pulmonary Langerhans Cell Histiocytosis.

Background: Fibrosis in pulmonary Langerhans cell histiocytosis (PLCH) histologically comprises a central scar with septal strands and associated airspace enlargement that produce an octopus-like appearance. The purpose of this study was to identify the octopus sign on high-resolution computed tomography (HRCT) images to determine its frequency and distribution across stages of the disease. Methods: Fifty-seven patients with confirmed PLCH were included. Two experienced chest radiologists assessed disease stages as early, intermediate, or late, as well as the lung parenchyma for nodular, cystic, or fibrotic changes and for the presence of the octopus sign. Statistical analysis included Cohen’s kappa for interrater agreement and Fisher’s exact test for the frequency of the octopus sign. Results: Interobserver agreement was substantial for the octopus sign (kappa = 0.747). Significant differences in distribution of the octopus sign between stages 2 and 3 were found with more frequent octopus signs in stage 2 and fewer in stage 3. In addition, we only found the octopus sign in cases of nodular und cystic lung disease. Conclusions: The octopus sign in PLCH can be identified not only on histological images, but also on HRCT images. Its radiological presence seems to depend on the stage of PLCH.

CT image quality enhancement via a dual-channel neural network with jointing denoising and super-resolution

In recent years, computed tomography (CT) has been widely used in various clinical diagnosis. Given potential health risks bring by the X-ray radiation, the major objective of the current research is to achieve high-quality CT imaging while reducing X-ray radiation. However, most existing studies on low-dose CT image super-resolution reconstruction do not focus on the interaction between the denoising task and the super-resolution task. In this paper, we propose a dual-channel joint learning framework to accurately reconstruct high-resolution CT images from low-resolution CT images. Unlike the previous cascaded models which directly combine the denoising network and the super-resolution network, our method can process the denoising reconstruction and the super-resolution reconstruction in parallel. Additionally, we design a filter gate module that can filter features from the denoising branch and highlight important features which can benefit the super-resolution task. We evaluate the performance of our method in medical image enhancement by testing on the 2016 Low-Dose CT Grand Challenge dataset and the piglet dataset. The experimental results show that the proposed network is superior to other state-of-the-art methods in terms of both peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). We also demonstrate that our method can better remove noise and recover details. Furthermore, the method achieves competitive results not only for super-resolution reconstruction of low-dose CT, but also for super-resolution reconstruction of sparse-view CT.