Cardiovascular and Thoracic Imaging: Trends, Perspectives and Prospects

Radiology is evolving at a fast pace, and the specific field of cardiovascular and thoracic imaging is no stranger to that trend. While it could, at first, seem unusual to gather these two specialties in a common Issue, the very fact that many of us are trained and exercise in both is more than a hint to the common grounds these fields are sharing. From the ever-increasing role of artificial intelligence in the reconstruction, segmentation, and analysis of images to the quest of functionality derived from anatomy, their interplay is big, and one innovation developed with the former in mind could prove useful for the latter. If the coronavirus disease 2019 (COVID-19) pandemic has shed light on the decisive diagnostic role of chest CT and, to a lesser extent, cardiac MR, one must not forget the major advances and extensive researches made possible in other areas by these techniques in the past years. With this Issue, we aim at encouraging and wish to bring to light state-of-the-art reviews, novel original researches, and ongoing discussions on the multiple aspects of cardiovascular and chest imaging

Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks

Fast diagnostic methods can control and prevent the spread of pandemic diseases like coronavirus disease 2019 (COVID-19) and assist physicians to better manage patients in high workload conditions. Although a laboratory test is the current routine diagnostic tool, it is time-consuming, imposing a high cost and requiring a well-equipped laboratory for analysis. Computed tomography (CT) has thus far become a fast method to diagnose patients with COVID-19. However, the performance of radiologists in diagnosis of COVID-19 was moderate. Accordingly, additional investigations are needed to improve the performance in diagnosing COVID-19. In this study is suggested a rapid and valid method for COVID-19 diagnosis using an artificial intelligence technique based. 1020 CT slices from 108 patients with laboratory proven COVID-19 (the COVID-19 group) and 86 patients with other atypical and viral pneumonia diseases (the non-COVID-19 group) were included. Ten well-known convolutional neural networks were used to distinguish infection of COVID-19 from non-COVID-19 groups: AlexNet, VGG-16, VGG-19, SqueezeNet, GoogleNet, MobileNet-V2, ResNet-18, ResNet-50, ResNet-101, and Xception. Among all networks, the best performance was achieved by ResNet-101 and Xception. ResNet-101 could distinguish COVID-19 from non-COVID-19 cases with an AUC of 0.994 (sensitivity, 100; specificity, 99.02; accuracy, 99.51). Xception achieved an AUC of 0.994 (sensitivity, 98.04; specificity, 100; accuracy, 99.02). However, the performance of the radiologist was moderate with an AUC of 0.873 (sensitivity, 89.21; specificity, 83.33; accuracy, 86.27). ResNet-101 can be considered as a high sensitivity model to characterize and diagnose COVID-19 infections, and can be used as an adjuvant tool in radiology departments. © 2020 Elsevier Lt

Occupational exposure to diacetyl and 2,3-pentanedione

This criteria document is derived from the NIOSH evaluation of critical health effects studies of occupational exposure to diacetyl and 2,3-pentanedione. It provides recommendations for controlling workplace exposures including recommended exposure limits derived by using current quantitative risk assessment methodology on human and animal health effects data. Using cross-sectional pulmonary function data from diacetyl-exposed employees, NIOSH conducted assessments to determine the exposure-response relationship and to identify risk of pulmonary function decrease at various levels of diacetyl exposure. NIOSH found that a relationship exists between diacetyl exposures and lower pulmonary function. Utilizing this analysis, NIOSH recommends keeping exposure to diacetyl below a concentration of 5 parts per billion as a time-weighted average during a 40-hour work week. To further protect against effects of short-term exposures, NIOSH recommends a short-term exposure limit for diacetyl of 25 parts per billion for a 15-minute time period. In many operations, 2,3-pentanedione is being used to substitute for diacetyl. Published toxicological studies indicate that 2,3-pentanedione exposure can cause damage similar to that caused by diacetyl in laboratory studies. Therefore, NIOSH recommends keeping occupational exposure to 2,3-pentanedione below a level comparable to the level recommended for diacetyl. However, the recommended sampling and analytical method can only reliably quantify it to 9.3 parts per billion in an 8-hour sample. NIOSH also recommends a short-term exposure limit for 2,3-pentanedione of 31 parts per billion during a 15-minute period. Engineering and work practices are available to control diacetyl and 2,3-pentanedione exposures below the recommended exposure limits. A hierarchy of controls including elimination, substitution, engineering controls, administrative controls, and the use of personal protective equipment should be followed to control workplace exposures. NIOSH urges employers to disseminate this information to employees and customers. NIOSH also requests that professional and trade associations and labor organizations inform their members about the hazards of occupational exposure to these flavoring compounds. NIOSH appreciates the time and effort of the expert peer, stakeholder, and public reviewers whose comments and input strengthened this document.Suggested citation: NIOSH [2016]. Criteria for a recommended standard: occupational exposure to diacetyl and 2,3-pentanedione. By McKernan LT, Niemeier RT, Kreiss K, Hubbs A, Park R, Dankovic D, Dunn KH, Parker J, Fedan K, Streicher R, Fedan J, Garcia A, Whittaker C, Gilbert S, Nourian F, Galloway E, Smith R, Lentz TJ, Hirst D, Topmiller J, Curwin B. Cincinnati, OH: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, DHHS (NIOSH) Publication No. 2016-111.NIOSH No 200488541. Introduction -- 2. Assessing Occupational Exposure in Employees -- 3. Effects of Exposure in Employees -- 4. Toxicology of Diacetyl and 2,3-Pentanedione -- 5. Quantitative Risk Assessment Based on Employee Data -- 6. Quantitative Risk Assessment Based on Animal Data -- 7. Basis of the Recommended Standards for Diacetyl and 2,3-Pentanedione -- 8. Hazard Prevention and Control of Exposures to Diacetyl and 2,3-Pentanedione -- 9. Medical Monitoring and Surveillance of Exposed Employees -- 10. Exposure Monitoring in Occupational Safety and Health Programs -- 11. Research Needs -- Appendix A. OSHA PV2118 (Diacetyl) -- Appendix B. OSHA 1012 (Acetoin and Diacetyl) -- Appendix C. Acetoin Diacetyl 1013 -- Appendix D. 2, 3-Pentanedione -- Appendix E. Volatile Organic Compounds (Screening) 2549 [NIOSH Manual of Analytical Methods (NMAM), Fourth Edition, 5/15/96] -- Appendix F. Correcting Diacetyl Concentrations from Air Samples Collected with NIOSH Method 2557 [J Occup Environ Hyg. 2011 Feb;8(2):59-70. doi: 10.1080/15459624.2011.540168.] -- Appendix G. JEM Tables for Four Plants -- Appendix H. Development of a Job Exposure Matrix for Company G -- Appendix I. Typical Protocol for Collecting Air Samples for Diacetyl and 2, 3-Pentanedione

Texture Analysis and Machine Learning to Predict Pulmonary Ventilation from Thoracic Computed Tomography

Chronic obstructive pulmonary disease (COPD) leads to persistent airflow limitation, causing a large burden to patients and the health care system. Thoracic CT provides an opportunity to observe the structural pathophysiology of COPD, whereas hyperpolarized gas MRI provides images of the consequential ventilation heterogeneity. However, hyperpolarized gas MRI is currently limited to research centres, due to the high cost of gas and polarization equipment. Therefore, I developed a pipeline using texture analysis and machine learning methods to create predicted ventilation maps based on non-contrast enhanced, single-volume thoracic CT. In a COPD cohort, predicted ventilation maps were qualitatively and quantitatively related to ground-truth MRI ventilation, and both maps were related to important patient lung function and quality-of-life measures. This study is the first to demonstrate the feasibility of predicting hyperpolarized MRI-based ventilation from single-volume, breath-hold thoracic CT, which has potential to translate pulmonary ventilation information to widely available thoracic CT imaging

Coupled Shape Models for the Diagnosis of Organ Motion Restriction

Annähernd 30% der weltweiten Todesfälle sind auf Erkrankungen des Herzens und der Lunge zurückzuführen, wobei die meisten dieser Erkrankungen während ihres Verlaufs die Mobilität des betroffenen Organs verändern. Viele dieser To-desfälle könnten durch eine frühzeitige Erkennung und Behandlung der Erkran-kung vermieden werden. Deshalb wurden im Zuge dieser Arbeit Methoden ent-wickelt, um aus Segmentierungen von dynamischen Magnetresonanztomogra-phie-Daten quantitative Kennzahlen für die funktionale Analyse der Herz- und Lungenbewegung zu generieren. Ein automatisiertes Segmentierungsverfahren basierend auf gekoppelten Formmodellen wurde entwickelt, welches wechsel-seitige Informationen der Form und Geometrie mehrerer korrelierter Objekte mit einbezieht, und somit 40% bessere Ergebnisse im Vergleich zur Verwendung einzelner Modelle erzielte. Im Fall des Herzens wurde ein Volumenberechnungs-fehler von unter 13% erreicht, was in der Größenordnung der Interobserver-Variabilität liegt. Für die Lunge konnte ein Volumenfehler von unter 70ml gezeigt werden. Aus den Segmentierungsergebnissen wurden funktionale Parameter der lokalen Organdynamik abgeleitet und visualisiert, die gegen konventionelle Diag-nosemethoden evaluiert wurden und dabei gute Übereinstimmung zeigen, dar-über hinaus jedoch eine lokal und regionale Mobilitätscharakterisierung erlau-ben

Pulmonary fibrosis: one manifestation, various diseases

This research topic collection entitled “Pulmonary Fibrosis: one manifestation, various diseases”, involving authors from different countries, confirms that this disease is a hot topic (Confalonieri P et al.,2022, Orlandi M et al., 2022). There are over 200 different types of pulmonary fibrosis (PF), the most common is the idiopathic pulmonary fbrosis (IPF), called idiopathic because it has no known cause. Another rare form is familial PF, for which several studies reported correlation with few genes. An important group of PF are due to other diseases, for example, autoimmune diseases such as rheumatoid arthritis, systemic sclerosis or Sjogren’s syndrome (Ruaro et al., 2022, Trombetta AC et al., 2017, Bernero Eet al., 2013). PF could correlate to viral infections (e.g. COVID-19), gastroesophageal reflux disease (GERD) (Baratella E et al, 2021, Ruaro et al., 2018), and the exposure to various materials (including naturally occurring such as bird or animal droppings, and occupational such as asbestos or silica). Furthermore, smoking, radiation treatments, and certain drugs can increase risk of developing PF. In the first article (Saketkoo et al.) of the collection, the authors evaluate the use of International Classification of Functioning, Disability, and Health (ICF) approved by World Health Organization (WHO) in patients affected by interstitial lung diseases (ILD)

Smoking and Second Hand Smoking in Adolescents with Chronic Kidney Disease: A Report from the Chronic Kidney Disease in Children (CKiD) Cohort Study

The goal of this study was to determine the prevalence of smoking and second hand smoking [SHS] in adolescents with CKD and their relationship to baseline parameters at enrollment in the CKiD, observational cohort study of 600 children (aged 1-16 yrs) with Schwartz estimated GFR of 30-90 ml/min/1.73m2. 239 adolescents had self-report survey data on smoking and SHS exposure: 21 [9%] subjects had “ever” smoked a cigarette. Among them, 4 were current and 17 were former smokers. Hypertension was more prevalent in those that had “ever” smoked a cigarette (42%) compared to non-smokers (9%), p\u3c0.01. Among 218 non-smokers, 130 (59%) were male, 142 (65%) were Caucasian; 60 (28%) reported SHS exposure compared to 158 (72%) with no exposure. Non-smoker adolescents with SHS exposure were compared to those without SHS exposure. There was no racial, age, or gender differences between both groups. Baseline creatinine, diastolic hypertension, C reactive protein, lipid profile, GFR and hemoglobin were not statistically different. Significantly higher protein to creatinine ratio (0.90 vs. 0.53, p\u3c0.01) was observed in those exposed to SHS compared to those not exposed. Exposed adolescents were heavier than non-exposed adolescents (85th percentile vs. 55th percentile for BMI, p\u3c 0.01). Uncontrolled casual systolic hypertension was twice as prevalent among those exposed to SHS (16%) compared to those not exposed to SHS (7%), though the difference was not statistically significant (p= 0.07). Adjusted multivariate regression analysis [OR (95% CI)] showed that increased protein to creatinine ratio [1.34 (1.03, 1.75)] and higher BMI [1.14 (1.02, 1.29)] were independently associated with exposure to SHS among non-smoker adolescents. These results reveal that among adolescents with CKD, cigarette use is low and SHS is highly prevalent. The association of smoking with hypertension and SHS with increased proteinuria suggests a possible role of these factors in CKD progression and cardiovascular outcomes