Opportunistic osteoporosis screening using chest CT with artificial intelligence.

Osteoporosis has a high incidence and a low detection rate. If it is not detected in time, it will cause osteoporotic fracture and other serious consequences. This study showed that the attenuation values of vertebrae on chest CT could be used for opportunistic screening of osteoporosis. This will be beneficial to improve the detection rate of osteoporosis and reduce the incidence of adverse events caused by osteoporosis. INTRODUCTION: To explore the value of the attenuation values of all thoracic vertebrae and the first lumbar vertebra measured by artificial intelligence on non-enhanced chest CT to do osteoporosis screening. METHODS: On base of images of chest CT, using artificial intelligence (AI) to measure the attenuation values (HU) of all thoracic and the first vertebrae of patients who underwent CT examination for lung cancer screening and dual-energy X-ray absorptiometry (DXA) examination during the same period. The patients were divided into three groups: normal group, osteopenia group, and osteoporosis group according to the results of DXA. Clinical baseline data and attenuation values were compared among the three groups. The correlation between attenuation values and BMD values was analyzed, and the predictive ability and diagnostic efficacy of attenuation values of thoracic and first lumbar vertebrae on osteopenia or osteoporosis risk were further evaluated. RESULTS: CT values of each thoracic vertebrae and the first lumbar vertebrae decreased with age, especially in menopausal women and presented high predictive ability and diagnostic efficacy for osteopenia or osteoporosis. After clinical data correction, with every 10 HU increase of CT values, the risk of osteopenia or osteoporosis decreased by 32 ~ 44% and 61 ~ 80%, respectively. And the combined diagnostic efficacy of all thoracic vertebrae was higher than that of a single vertebra. The AUC of recognizing osteopenia or osteoporosis from normal group was 0.831and 0.972, respectively. CONCLUSIONS: The routine chest CT with AI is of great value in opportunistic screening for osteopenia or osteoporosis, which can quickly screen the population at high risk of osteoporosis without increasing radiation dose, thus reducing the incidence of osteoporotic fracture.

Automated total and vessel-specific coronary artery calcium (CAC) quantification on chest CT: direct comparison with CAC scoring on non-contrast cardiac CT.

BACKGROUND: This study aimed to evaluate the artificial intelligence (AI)-based coronary artery calcium (CAC) quantification and regional distribution of CAC on non-gated chest CT, using standard electrocardiograph (ECG)-gated CAC scoring as the reference. METHODS: In this retrospective study, a total of 405 patients underwent non-gated chest CT and standard ECG-gated cardiac CT. An AI-based algorithm was used for automated CAC scoring on chest CT, and Agatston score on cardiac CT was manually quantified. Bland-Altman plots were used to evaluate the agreement of absolute Agatston score between the two scans at the patient and vessel levels. Linearly weighted kappa (κ) was calculated to assess the reliability of AI-based CAC risk categorization and the number of involved vessels on chest CT. RESULTS: The AI-based algorithm showed moderate reliability for the number of involved vessels in comparison to measures on cardiac CT (κ = 0.75, 95% CI 0.70-0.79, P < 0.001) and an assignment agreement of 76%. Considerable coronary arteries with CAC were not identified with a per-vessel false-negative rate of 59.3%, 17.8%, 34.9%, and 34.7% for LM, LAD, CX, and RCA on chest CT. The leading causes for false negatives of LM were motion artifact (56.3%, 18/32) and segmentation error (43.8%, 14/32). The motion artifact was almost the only cause for false negatives of LAD (96.6%, 28/29), CX (96.7%, 29/30), and RCA (100%, 34/34). Absolute Agatston scores on chest CT were underestimated either for the patient and individual vessels except for LAD (median difference: - 12.5, - 11.3, - 5.6, - 18.6 for total, LM, CX, and RCA, all P < 0.01; - 2.5 for LAD, P = 0.18). AI-based total Agatston score yielded good reliability for risk categorization (weighted κ 0.86, P < 0.001) and an assignment agreement of 86.7% on chest CT, with a per-patient false-negative rate of 15.2% (28/184) and false-positive rate of 0.5% (1/221) respectively. CONCLUSIONS: AI-based per-patient CAC quantification on non-gated chest CT achieved a good agreement with dedicated ECG-gated CAC scoring overall and highly reliable CVD risk categorization, despite a slight but significant underestimation. However, it is challenging to evaluate the regional distribution of CAC without ECG-synchronization.

A Multifunctional Integrated Metal-Free MRI Agent for Early Diagnosis of Oxidative Stress in a Mouse Model of Diabetic Cardiomyopathy.

Reactive oxygen species (ROS) are closely associated with the progression of diabetic cardiomyopathy (DCM) and can be regarded as one of its early biomarkers. Magnetic resonance imaging (MRI) is emerging as a powerful tool for the detection of cardiac abnormalities, but the sensitive and direct ROS-response MRI probe remains to be developed. This restricts the early diagnosis of DCM and prevents timely clinical interventions, resulting in serious and irreversible pathophysiological abnormalities. Herein, a novel ROS-response contrast-enhanced MRI nanoprobe (RCMN) is developed by multi-functionalizing fluorinated carbon nanosheets (FCNs) with multi-hydroxyl and 2,2,6,6-tetramethylpiperidin-1-oxyl groups. RCMNs capture ROS and then gather in the heart provisionally, which triggers MRI signal changes to realize the in vivo detection of ROS. In contrast to the clinical MRI agents, the cardiac abnormalities of disease mice is detected 8 weeks in advance with the assistance of RCMNs, which greatly advances the diagnostic window of DCM. To the best of the knowledge, this is the first ROS-response metal-free T2 -weighted MRI probe for the early diagnosis of DCM mice model. Furthermore, RCMNs can timely scavenge excessively produced ROS to alleviate oxidative stress.

A Novel Subtraction Method to Reduce Metal Artifacts of Cerebral Aneurysm Embolism Coils.

OBJECTIVE: To investigate a novel subtraction method (S-MAR), combing metal artifact reduction (MAR), virtual monochromatic imaging (VMI), and subtraction CT angiography (CTA) to remove the metal artifacts of coils after endovascular embolotherapy of intracranial aneurysms. METHOD: In this retrospective study, 29 patients with 38 coils after endovascular embolotherapy of intracranial aneurysms who underwent cerebral CTA using a dual-layer detector spectral CT were included. Conventional CT images (CI), virtual non-enhanced (VNC) images and VMI ranging from 40 to 120 KeV in steps of 10 were reconstructed. These images were then postprocessed to CIMAR, VMIMAR and VNCMAR with MAR software (O-MAR; Philips Healthcare, Cleveland, OH, USA). The novel subtraction method (S-MAR) was derived from subtraction imaging between VNCMAR and the optimal VMIMAR. Contrast-to-noise (CNR) and Noise(Background) of CI, CIMAR, VMI, and VMIMAR were calculated quantitatively. Two Independent radiologists qualitatively assessed artifacts in all images using coil artifact score (CA score), a 5-point Likert scale. Besides, all coils were divided into two groups (group 1: diameter < 5.0 mm, group 2: diameter ≥ 5.0 mm). Differences between two groups were statistically analyzed. RESULTS: The optimal KeV was 40 KeV. Strong correlations between diameter of coils and the CA score of CI were found (rs = 0.652, P < 0.05). CNR, Noise and CA score were significantly improved by CIMAR and VMIMAR compared with CI (P < 0.05). The S­MAR showed significantly better performance compared with CI, CIMAR, VMI, and VMIMAR in reducing metal coil artifacts according to the CA score (P < 0.05), especially in group 2. CONCLUSION: The novel S­MAR proved to be a promising method to reduce coil metal artifacts and elevate the vessel visualization adjacent to coils. It could develop to be widely used in cerebral CTA after coiled aneurysms.

Asynchronous changes of normal lung lobes during respiration based on quantitative computed tomography (CT).

Background: This study aimed to explore the coordinated and independent actions of lung lobes during respiration using quantitative computed tomography (CT) in order to increase our in vivo understanding of pulmonary anatomy. Methods: Cases for whom test results showed normal pulmonary function tests (PFTs) results, and normal paired inspiratory-expiratory chest CT findings, as assessed by 2 radiologists, were retrospectively included in this study. From the chest CT results, we measured quantitative indices of lung volume (LV) and mean lung density (MLD) for the total lung (TL), left lung (LL), right lung (RL), and 5 lobes in inspiratory and expiratory phases. The differences of these measures between bilateral lungs and among the lobes were evaluated to study whether they were consistent or different during respiration. Results: A total of 70 cases were included {median age of 49.5 [interquartile range (IQR), 38.0 to 60.3] years; 32 males; 38 females}. Overall, the inspiratory and expiratory volumes of the LL were smaller than those of the RL (both P<0.001). For the ventilation workload (λ, which indicates the ratio of lobar volume to total LV), the end-expiratory volume ratio (λex ) of the LL was 0.44 (IQR, 0.43 to 0.46), while the end-inspiratory volume ratio (λin ) had risen to 0.46 (IQR, 0.45 to 0.47) (P<0.001). Comparing the 5 lobes, not all lobes shared the same LV. However, the left lower lobe (LLL) and right lower lobe (RLL) showed some similarities. The λin-LLL and λin-RLL was higher than λex-LLL and λex-RLL , respectively (both P<0.001), while the ratios of the other lobes reduced. The pairwise mean absolute difference (PMAD) on λin and λex of the bilateral lower lobes was low in inspiration (0.0288) and expiration (0.0346). The MLD of bilateral lower lobes showed consistency in inspiration or in expiration (inspiration: P>0.999; expiration: P=0.975). In addition, the PMADs between the right middle lobe (RML) and other lobes were significantly larger than the PMAD between other pairs of lobes in both inspiration and expiration. Beyond that, the expiratory MLD of RML [-789.6 (IQR, -814 to -762.05) HU] was the lowest among the 5 lobes. Conclusions: We found that the LL assumes a higher workload during ventilation than it does during respiration. The 5 normal lobes were non-synchronous during respiration and contributed differently to ventilation. The bilateral lower lobes showed similarities and had a high-ventilation function, while and the LV and MLD of the RML showed the least changes within a respiration cycle.

Facile access to chiral chromanone-2-carboxylic acids enabled by rhodium-catalyzed chemo- and enantioselective hydrogenation.

Rh-catalyzed highly chemo- and enantioselective hydrogenation of chromone-2-carboxylic acids was successfully established for the first time, providing a wide range of enantiopure chromanone-2-carboxylic acids with excellent results (up to 97% yield and 99% ee) and high efficiency (up to 10 000 TON). The carboxylic group in the substrate was demonstrated to play a vital role and an enantio-induction mode was elucidated by DFT calculation. This hydrogenation protocol provided straightforward access to various bioactive chromanoids.

Well-Aerated Lung and Mean Lung Density Quantified by CT at Discharge to Predict Pulmonary Diffusion Function 5 Months after COVID-19.

Background: The aim of this study was to explore the predictive values of quantitative CT indices of the total lung and lung lobe tissue at discharge for the pulmonary diffusion function of coronavirus disease 2019 (COVID-19) patients at 5 months after symptom onset. Methods: A total of 90 patients with moderate and severe COVID-19 underwent CT scans at discharge, and pulmonary function tests (PFTs) were performed 5 months after symptom onset. The differences in quantitative CT and PFT results between Group 1 (patients with abnormal diffusion function) and Group 2 (patients with normal diffusion function) were compared by the chi-square test, Fisher's exact test or Mann−Whitney U test. Univariate analysis, stepwise linear regression and logistic regression were used to determine the predictors of diffusion function in convalescent patients. Results: A total of 37.80% (34/90) of patients presented diffusion dysfunction at 5 months after symptom onset. The mean lung density (MLD) of the total lung tissue in Group 1 was higher than that in Group 2, and the percentage of the well-aerated lung (WAL) tissue volume (WAL%) of Group 1 was lower than that of Group 2 (all p < 0.05). Multiple stepwise linear regression identified only WAL and WAL% of the left upper lobe (LUL) as parameters that positively correlated with the percent of the predicted value of diffusion capacity of the lungs for carbon monoxide (WAL: p = 0.002; WAL%: p = 0.004), and multiple stepwise logistic regression identified MLD and MLDLUL as independent predictors of diffusion dysfunction (MLD: OR (95%CI): 1.011 (1.001, 1.02), p = 0.035; MLDLUL: OR (95%CI): 1.016 (1.004, 1.027), p = 0.008). Conclusion: At five months after symptom onset, more than one-third of moderate and severe COVID-19 patients presented with diffusion dysfunction. The well-aerated lung and mean lung density quantified by CT at discharge could be predictors of diffusion function in convalesce.

Artificial intelligence measuring the aortic diameter assist in identifying adverse blood pressure status including masked hypertension.

INTRODUCTION AND OBJECTIVES: Artificial intelligence (AI) made it achievable that aortic dilation could be measured in CT images indirectly, while aortic diameter (AD) has the certain relationship with blood pressure. It was potential that the blood pressure condition be determined by AD measurement using the data obtained from a CT scanning especially in identifying masked hypertension and predicting the risk of poor control of blood pressure (BP) which was easy to elude diagnosis in clinic. We aimed to evaluate the possibility of utilizing AD by AI for predicting the risk of adverse BP status (including masked hypertension or poor BP control) and the optimal thoracic aortic position in measurement as well as the cutoff value for predicting the risk. METHODS: Eight hundred and one patients were enrolled in our study. AI-Rad Companion Cardiovascular (K183268 FDA approved) was used to perform automatic aorta measurement in thoracic CT images at nine key positions based on AHA guidelines. Data was post processed by software from AI-Rad Companion undergone rigorous clinical validation by both FDA and CE as verification of its efficacy and usability. The AD's risk and diagnostic value was assessed in identifying hypertension in the general population, in identifying the poor BP controlled in the hypertension population, and in screening masked hypertension in the general population respectively by multiple regression analysis and receiver operating curve analysis. RESULTS: AD measured by AI was a risk factor for adverse BP status after clinical covariates adjustment (OR = 1.02 ~ 1.26). The AD at mid descending aorta was mostly affected by BP particularly, which is optimal indicator in identifying hypertension in the general population (AUC = 0.73) and for screening masked hypertension (AUC = 0.78). CONCLUSION: Using AI to measure the AD of the aorta, particularly at the position of mid descending aorta, is greatly valuable for identifying people with poor BP status. It will be possible to reveal more clinical information reflected by ordinary CT images and enrich the screening methods for hypertension, especially masked hypertension.PLAIN LANGUAGE SUMMARYHTN has a significant adverse effect on arterial deformation. BP and arterial dilation promote each other in a vicious circle. Arterial dilation may not be restricted by apparent fluctuations in BP and is objective evidence of an undesirable BP state. The accuracy of AD measurements by AI on chest CT images has been verified. There has not been the application of AD measurement by AI in the scene of poor BP status in clinical practice.In this study, we applied AI to measure the diameter of the aorta in nine consecutive positions. We explored the association between AD at various positions and BP levels and the possibility that AD in identifying poor BP status in different populations. We found that the AD at the MD is of great value in screening MH and evaluating the control state of BP in HTN. It will be possible to significantly expand the clinical information reflected by ordinary CT images and enrich the screening methods for HTN, especially MH.

CT-Based Radiomics Helps to Predict Residual Lung Lesions in COVID-19 Patients at Three Months after Discharge.

BACKGROUND: In this study, our focus was on pulmonary sequelae of coronavirus disease 2019 (COVID-19). We aimed to develop and validate CT-based radiomic models for predicting the presence of residual lung lesions in COVID-19 survivors at three months after discharge. METHODS: We retrospectively enrolled 162 COVID-19 confirmed patients in our hospital (84 patients with residual lung lesions and 78 patients without residual lung lesions, at three months after discharge). The patients were all randomly allocated to a training set (n = 114) or a test set (n = 48). Radiomic features were extracted from chest CT images in different regions (entire lung or lesion) and at different time points (at hospital admission or at discharge) to build different models, sequentially, or in combination, as follows: (1) Lesion_A model (based on the lesion region at admission CT); (2) Lesion_D model (based on the lesion region at discharge CT); (3) Δlesion model (based on the lesion region at admission CT and discharge CT); (4) Lung_A model (based on the lung region at admission CT); (5) Lung_D model (based on the lung region at discharge CT); (6) Δlung model (based on the lung region at admission CT and discharge CT). The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to evaluate the predictive performances of the radiomic models. RESULTS: Among the six models, the Lesion_D and the Δlesion models achieved better predictive efficacy, with AUCs of 0.907 and 0.927, sensitivity of 0.898 and 0.763, and specificity of 0.855 and 0.964 in the training set, and AUCs of 0.875 and 0.837, sensitivity of 0.920 and 0.680, and specificity of 0.826 and 0.913 in the test set, respectively. CONCLUSIONS: The CT-based radiomic models showed good predictive effects on the presence of residual lung lesions in COVID-19 survivors at three months after discharge, which may help doctors to plan follow-up work and to reduce the psychological burden of COVID-19 survivors.

Thoracic Aorta Diameter Calculation by Artificial Intelligence Can Predict the Degree of Arterial Stiffness.

Background: Arterial aging is characterized by decreased vascular function, caused by arterial stiffness (AS), and vascular morphological changes, caused by arterial dilatation. We analyzed the relationship of pre-AS and AS, as assessed by cardio ankle vascular index (CAVI), with arterial diameters (AD) at nine levels, from the aortic sinus to the abdominal aorta, as measured by artificial intelligence (AI) on non-enhanced chest computed tomography (CT) images. Methods: Overall, 801 patients who underwent both chest CT scan and arterial elasticity test were enrolled. Nine horizontal diameters of the thoracic aorta (from the aortic sinuses of Valsalva to the abdominal aorta at the celiac axis origin) were measured by AI using CT. Patients were divided into non-AS (mean value of the left and right CAVIs [M.CAVI] < 8), pre-AS (8 ≤ M.CAVI < 9), and AS (M.CAVI ≥ 9) groups. We compared AD differences among groups, analyzed the correlation of age, ADs, and M.CAVI or the mean pressure-independent CAVI (M.CAVI0), Furthermore, we evaluated the risk predictors and the diagnostic value of the nine ADs for pre-AS and AS. Results: The AD at mid descending aorta (MD) correlated strongest with CAVI (r = 0.46, p < 0.001) or M.CAVI0 (r = 0.42, p < 0.001). M.CAVI was most affected by the MD AD and by age. An increase in the MD AD independently predicted the occurrence of pre-AS or AS. For MD AD, every 4.37 mm increase caused a 14% increase in the pre-AS and AS risk and a 13% increase in the AS risk. With a cut-off value of 26.95 mm for the MD AD, the area under the curve (AUC) for identifying the risk of AS was 0.743. With a cut-off value of 25.15 mm, the AUC for identifying the risk of the stage after the prophase of AS is 0.739. Conclusions: Aging is associated with an increase in AD and a decrease in arterial elasticity. An increase in AD, particularly at the MD level is an independent predictor of AS development.

Pyrazolone structural motif in medicinal chemistry: Retrospect and prospect.

The pyrazolone structural motif is a critical element of drugs aimed at different biological end-points. Medicinal chemistry researches have synthesized drug-like pyrazolone candidates with several medicinal features including antimicrobial, antitumor, CNS (central nervous system) effect, anti-inflammatory activities and so on. Meanwhile, SAR (Structure-Activity Relationship) investigations have drawn attentions among medicinal chemists, along with a plenty of analogues have been derived for multiple targets. In this review, we comprehensively summarize the biological activity and SAR for pyrazolone analogues, wishing to give an overall retrospect and prospect on the pyrazolone derivatives.

Diagnostic Value of 128-slice Spiral CT Combined with Virtual Colonoscopy for Colorectal Cancer.

The objective of this study was to evaluate the diagnostic value of 128-slice spiral CT combined with virtual colonoscopy in diagnosis of colorectal cancer. We retrospectively analyzed 45 patients of colorectal diseases who underwent definition AS+128-slice spiral CT combined with virtual colonoscopy after bowel preparation and gas injection to evaluate the clinical diagnostic value of this technology. All the patients received electronic colonoscopy and were confirmed by pathology. In total, colorectal cancer was confirmed in 42 cases and inflammation in 3 cases. Diagnostic results shows: there were 17 cases of lump, 10 cases of infiltration, 6 cases of ulcer, 9 cases of mixed type, 4 cases of liver metastases, and 36 cases of lymph node metastasis. There was no significant difference between 128-slice spiral CT combined with virtual colonoscopy and electronic colonoscopy in detection, localization and characterization of colorectal tumors. CT virtual endoscopy has great advantages in observing the invasion around the lesion and the presence or absence of metastasis in distant organs and lymph node metastasis. It is also possible to understand the shape of the lesion in the intestinal lumen and the length of the lesion involving the lumen of the intestine.

Challenges Faced with Small Molecular Modulators of Potassium Current Channel Isoform Kv1.5.

The voltage-gated potassium channel Kv1.5, which mediates the cardiac ultra-rapid delayed-rectifier (IKur) current in human cells, has a crucial role in atrial fibrillation. Therefore, the design of selective Kv1.5 modulators is essential for the treatment of pathophysiological conditions involving Kv1.5 activity. This review summarizes the progress of molecular structures and the functionality of different types of Kv1.5 modulators, with a focus on clinical cardiovascular drugs and a number of active natural products, through a summarization of 96 compounds currently widely used. Furthermore, we also discuss the contributions of Kv1.5 and the regulation of the structure-activity relationship (SAR) of synthetic Kv1.5 inhibitors in human pathophysiology. SAR analysis is regarded as a useful strategy in structural elucidation, as it relates to the characteristics that improve compounds targeting Kv1.5. Herein, we present previous studies regarding the structural, pharmacological, and SAR information of the Kv1.5 modulator, through which we can assist in identifying and designing potent and specific Kv1.5 inhibitors in the treatment of diseases involving Kv1.5 activity.

Synthesis and in vitro evaluation of a hyaluronic acid-quantum dots-melphalan conjugate.

Polymer-drug conjugates have played an important role in improving tumor cell targeting and the selectivity of anticancer drugs. In this study, quantum dots and melphalan were attached to the backbone of hyaluronic acid to synthesize a polymer-drug conjugate. The physicochemical properties of the conjugate were characterized by FT-IR, XRD, (1)H NMR, UV-Vis spectra and DLS. The in vitro drug release profiles and cell evaluation were investigated. The results showed that the conjugate was synthesized and self-assembled into nanoparticles with a diameter of 115 ± 2.3 nm. The conjugate had a pH-sensitive drug controlled release property. It was an ideal receptor-mediated delivery system and can be internalized into the human breast cancer cell. It had a better inhibition effect on human breast cancer cell and a poorer inhibition effect on normal breast cell than melphalan. These results supported that the conjugate would be a promising candidate for cancer therapy.