From pixels to prognosis: Imaging biomarkers for discrimination and outcome prediction of pulmonary embolism : Original Research Article.

PURPOSE: Recent advancements in medical imaging have transformed diagnostic assessments, offering exciting possibilities for extracting biomarker-based information. This study aims to investigate the capabilities of a machine learning classifier that incorporates dual-energy computed tomography (DECT) radiomics. The primary focus is on discerning and predicting outcomes related to pulmonary embolism (PE). METHODS: The study included 131 participants who underwent pulmonary artery DECT angiography between January 2015 and March 2022. Among them, 104 patients received the final diagnosis of PE and 27 patients served as a control group. A total of 107 radiomic features were extracted for every case based on DECT imaging. The dataset was divided into training and test sets for model development and validation. Stepwise feature reduction identified the most relevant features, which were used to train a gradient-boosted tree model. Receiver operating characteristics analysis and Cox regression tests assessed the association of texture features with overall survival. RESULTS: The trained machine learning classifier achieved a classification accuracy of 0.94 for identifying patients with acute PE with an area under the receiver operating characteristic curve of 0.91. Radiomics features could be valuable for predicting outcomes in patients with PE, demonstrating strong prognostic capabilities in survival prediction (c-index, 0.991 [0.979-1.00], p = 0.0001) with a median follow-up of 130 days (IQR, 38-720). Notably, the inclusion of clinical or DECT parameters did not enhance predictive performance. CONCLUSION: In conclusion, our study underscores the promising potential of leveraging radiomics on DECT imaging for the identification of patients with acute PE and predicting their outcomes. This approach has the potential to improve clinical decision-making and patient management, offering efficiencies in time and resources by utilizing existing DECT imaging without the need for an additional scoring system.

Indicators for Hospitalization in Acute Pulmonary Embolism: Uncover the Association Between D-dimer Levels, Thrombus Volume and Radiomics.

BACKGROUND: The advent of advanced computed tomography (CT) technology and the field of radiomics has opened up new avenues in diagnostic assessments. Increasingly, there is substantial evidence advocating for the incorporation of quantitative imaging biomarkers in the clinical decision-making process. This study aimed to examine the correlation between D-dimer levels and thrombus size in acute pulmonary embolism (PE) combining dual-energy CT (DECT) and radiomics and to investigate the diagnostic utility of a machine learning classifier based on dual-energy computed tomography (DECT) radiomics for identifying patients with a complicated course, defined as at least hospitalization at IMC. METHODS: The study was conducted including 136 participants who underwent pulmonary artery CT angiography from January 2015 to March 2022. Based on DECT imaging, 107 radiomic features were extracted for each patient using standardized image processing. After dividing the dataset into training and test sets, stepwise feature reduction based on reproducibility, variable importance and correlation analyses were performed to select the most relevant features; these were used to train and validate the gradient-boosted tree models.Receiver operating characteristics (ROC) analysis was utilized to evaluate the association between volumetric, laboratory data and adverse outcomes. RESULTS: In the central PE group, we observed a significant correlation between thrombus volumetrics and D-dimer levels (p = 0.0037), as well as between thrombus volumetrics and hospitalization at the Intermediate Care Unit (IMC) (p = 0.0001). In contrast, no statistically significant differences were identified in thrombus sizes between patients who experienced complications and those who had a favorable course (p = 0.3162). The trained machine learning classifier achieved an accuracy of 61% and 55% in identifying patients with a complicated course, as indicated by an area under the ROC curve of 0.63 and 0.58. CONCLUSION: In conclusion, our findings indicate a positive correlation between D-dimer levels and central PE's pulmonary embolic burden. Thrombus volumetrics may serve as an indicator for complications and outcomes in acute PE patients. Thus, thrombus volumetrics, as opposed to D-dimers, could be an additional marker for evaluating embolic disease severity. Moreover, DECT-derived radiomic feature models show promise in identifying patients with a complicated course, such as hospitalization at IMC.

New Perspectives for Mucolytic, Anti-inflammatory and Adjunctive Therapy with 1,8-Cineole in COPD and Asthma: Review on the New Therapeutic Approach.

The mucolytic monoterpene 1,8-cineole (eucalyptol), the major constituent of eucalyptus species, is well known for its anti-inflammatory, antioxidant, bronchodilatory, antiviral and antimicrobial effects. The main protective antiviral, anti-inflammatory and mucolytic mechanisms of 1,8-cineole are the induction of interferon regulatory factor 3 (IRF3), the control of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) along with decreasing mucin genes (MUC2, MUC19). In normal human monocytes direct inhibition was shown of reactive oxygen species (ROS)-mediated mucus hypersecretion and of steroid resistence inducing superoxides (O2·-) and pro-inflammatory hydrogen peroxides (H2O2) with partial control of superoxide dismutase (SOD), which enzymatically metabolizes O2·- into H2O2. By inhibition of NF-κB, 1,8-cineole, at relevant plasma concentrations (1.5 µg/ml), strongly and significantly inhibited in normal human monocyte lipopolysaccharide (LPS)-stimulated cytokines relevant for exacerbation (tumour necrosis factor alpha (TNFα), interleukin (IL)-1ß and systemic inflammation (IL-6, IL-8). Infectious agents and environmental noxa have access via TNFα and IL-1ß to the immune system with induction of bronchitis complaints and exacerbations of chronic obstructive pulmonary disease (COPD), asthma and asthma-COPD overlap. In lymphocytes from healthy human donors 1,8-cineole inhibited TNFα, IL-1ß, IL-4 and IL-5 and demonstrated for the first time control of Th1/2-type inflammation. 1,8-Cineole at relevant plasma levels increased additively in vitro the efficacy of inhaled guideline medications of budesonide (BUD) and budesonide + formoterol ,and preliminary data also showed increased efficacy of long-acting muscarinic receptor antagonist (LAMA)-mediated cytokine inhibition in vitro. On the basis of the preclinical data, earlier randomised controlled studies with adjunctive therapy of 1,8-cineole (3 × 200 mg/day) for 6 months showed improvement of uncontrolled asthma by significant improvement of lung function, nocturnal asthma and quality of life scores and in COPD decrease of exacerbations (- 38.5%) (during wintertime). This review reports an update with reference to the literature of 1,8-cineole, also as adjunctive therapy, as a therapeutic agent for the protection and control of inflammatory airway diseases.