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COVID-19 pneumonia: microvascular disease revealed on pulmonary dual-energy computed tomography angiography.
Grillet, Franck; Busse-Coté, Andreas; Calame, Paul; Behr, Julien; Delabrousse, Eric; Aubry, Sébastien.
  • Grillet F; Department of Radiology, Centre Hospitalier Universitaire de Besancon, Besancon, France.
  • Busse-Coté A; Department of Radiology, Centre Hospitalier Universitaire de Besancon, Besancon, France.
  • Calame P; Department of Radiology, Centre Hospitalier Universitaire de Besancon, Besancon, France.
  • Behr J; Department of Radiology, Centre Hospitalier Universitaire de Besancon, Besancon, France.
  • Delabrousse E; Department of Radiology, Centre Hospitalier Universitaire de Besancon, Besancon, France.
  • Aubry S; Nanomedecine Laboratory EA4662, University of Franche-Comte, Besancon, France.
Quant Imaging Med Surg ; 10(9): 1852-1862, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-745372
Semantic information from SemMedBD (by NLM)
1. Acute pulmonary embolism COEXISTS_WITH COVID-19
Subject
Acute pulmonary embolism
Predicate
COEXISTS_WITH
Object
COVID-19
2. Lung LOCATION_OF Computed Tomography Angiography
Subject
Lung
Predicate
LOCATION_OF
Object
Computed Tomography Angiography
3. Lung LOCATION_OF Dual energy computed tomography
Subject
Lung
Predicate
LOCATION_OF
Object
Dual energy computed tomography
4. COVID-19 PROCESS_OF Patients
Subject
COVID-19
Predicate
PROCESS_OF
Object
Patients
5. Lung diseases PROCESS_OF Patients
Subject
Lung diseases
Predicate
PROCESS_OF
Object
Patients
6. Pulmonary angiogram ADMINISTERED_TO Patients
Subject
Pulmonary angiogram
Predicate
ADMINISTERED_TO
Object
Patients
7. Reverse Transcriptase Polymerase Chain Reaction DIAGNOSES 2019 novel coronavirus
Subject
Reverse Transcriptase Polymerase Chain Reaction
Predicate
DIAGNOSES
Object
2019 novel coronavirus
8. Symptom severe PROCESS_OF Patients
Subject
Symptom severe
Predicate
PROCESS_OF
Object
Patients
9. Parenchyma LOCATION_OF Ischemia
Subject
Parenchyma
Predicate
LOCATION_OF
Object
Ischemia
10. Pulmonary artery thrombosis COEXISTS_WITH Ischemia
Subject
Pulmonary artery thrombosis
Predicate
COEXISTS_WITH
Object
Ischemia
11. Parenchyma PART_OF Lung
Subject
Parenchyma
Predicate
PART_OF
Object
Lung
12. Pulmonary artery thrombosis PROCESS_OF Patients
Subject
Pulmonary artery thrombosis
Predicate
PROCESS_OF
Object
Patients
13. Ischemia PROCESS_OF Patients
Subject
Ischemia
Predicate
PROCESS_OF
Object
Patients
14. Ischemia COEXISTS_WITH Pulmonary artery thrombosis
Subject
Ischemia
Predicate
COEXISTS_WITH
Object
Pulmonary artery thrombosis
15. Patients LOCATION_OF Iodides
Subject
Patients
Predicate
LOCATION_OF
Object
Iodides
16. Pneumonia COEXISTS_WITH Microthrombosis
Subject
Pneumonia
Predicate
COEXISTS_WITH
Object
Microthrombosis
17. Acute pulmonary embolism COEXISTS_WITH COVID-19
Subject
Acute pulmonary embolism
Predicate
COEXISTS_WITH
Object
COVID-19
18. Lung LOCATION_OF Computed Tomography Angiography
Subject
Lung
Predicate
LOCATION_OF
Object
Computed Tomography Angiography
19. Lung LOCATION_OF Dual energy computed tomography
Subject
Lung
Predicate
LOCATION_OF
Object
Dual energy computed tomography
20. COVID-19 PROCESS_OF Patients
Subject
COVID-19
Predicate
PROCESS_OF
Object
Patients
21. Lung diseases PROCESS_OF Patients
Subject
Lung diseases
Predicate
PROCESS_OF
Object
Patients
22. Pulmonary angiogram ADMINISTERED_TO Patients
Subject
Pulmonary angiogram
Predicate
ADMINISTERED_TO
Object
Patients
23. Reverse Transcriptase Polymerase Chain Reaction DIAGNOSES 2019 novel coronavirus
Subject
Reverse Transcriptase Polymerase Chain Reaction
Predicate
DIAGNOSES
Object
2019 novel coronavirus
24. Symptom severe PROCESS_OF Patients
Subject
Symptom severe
Predicate
PROCESS_OF
Object
Patients
25. Parenchyma LOCATION_OF Ischemia
Subject
Parenchyma
Predicate
LOCATION_OF
Object
Ischemia
26. Pulmonary artery thrombosis COEXISTS_WITH Ischemia
Subject
Pulmonary artery thrombosis
Predicate
COEXISTS_WITH
Object
Ischemia
27. Parenchyma PART_OF Lung
Subject
Parenchyma
Predicate
PART_OF
Object
Lung
28. Pulmonary artery thrombosis PROCESS_OF Patients
Subject
Pulmonary artery thrombosis
Predicate
PROCESS_OF
Object
Patients
29. Ischemia PROCESS_OF Patients
Subject
Ischemia
Predicate
PROCESS_OF
Object
Patients
30. Ischemia COEXISTS_WITH Pulmonary artery thrombosis
Subject
Ischemia
Predicate
COEXISTS_WITH
Object
Pulmonary artery thrombosis
31. Patients LOCATION_OF Iodides
Subject
Patients
Predicate
LOCATION_OF
Object
Iodides
32. Pneumonia COEXISTS_WITH Microthrombosis
Subject
Pneumonia
Predicate
COEXISTS_WITH
Object
Microthrombosis
ABSTRACT

BACKGROUND:

Increased prevalence of acute pulmonary embolism in COVID-19 has been reported in few recent studies. Some works have highlighted pathological changes on lung microvasculature with local pulmonary intravascular coagulopathy that may explain pulmonary artery thrombosis found on pulmonary computed tomography (CT) angiography. The objective of our study was to describe lung perfusion disorders assessed by pulmonary dual-energy CT (DECT) angiography in severe COVID-19 patients.

METHODS:

This single center retrospective study included 85 consecutive patients with a reverse transcriptase-polymerase chain reaction diagnosis of SARS-CoV-2 who underwent a pulmonary DECT angiography between March 16th 2020 and April 22th 2020. Pulmonary DECT angiography was performed when the patient had severe clinical symptoms or suffered from active neoplasia or immunosuppression. Two chest radiologists performed pulmonary angiography analysis in search of pulmonary artery thrombosis and a blinded semi quantitative analysis of iodine color maps focusing on the presence of parenchymal ischemia. The lung parenchyma was divided into volumes based on HU values. DECT analysis included lung segmentation, total lungs volume and distribution of lung perfusion assessment.

RESULTS:

Twenty-nine patients (34%) were diagnosed with pulmonary artery thrombosis, mainly segmental (83%). Semi-quantitative analysis revealed parenchymal ischemia in 68% patients of the overall population, with no significant difference regarding absence or presence of pulmonary artery thrombosis (23 vs. 35, P=0.144). Inter-reader agreement of parenchymal ischemia between reader 1 and 2 was substantial [0.74; interquartile range (IQR) 0.59-0.89]. Volume of ischemia was significantly higher in patients with pulmonary artery thrombosis [29 (IQR, 8-100) vs. 8 (IQR, 0-45) cm3, P=0.041]. Lung parenchyma was divided between normal parenchyma (59%, of which 34% was hypoperfused), ground glass opacities (10%, of which 20% was hypoperfused) and consolidation (31%, of which 10% was hypoperfused).

CONCLUSIONS:

Pulmonary perfusion evaluated by iodine concentration maps shows extreme heterogeneity in COVID-19 patients and lower iodine levels in normal parenchyma. Pulmonary ischemic areas were more frequent and larger in patients with pulmonary artery thrombosis. Pulmonary DECT angiography revealed a significant number of pulmonary ischemic areas even in the absence of visible pulmonary arterial thrombosis. This may reflect microthrombosis associated with COVID-19 pneumonia.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Risk factors Language: English Journal: Quant Imaging Med Surg Year: 2020 Document Type: Article Affiliation country: Qims-20-708

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Risk factors Language: English Journal: Quant Imaging Med Surg Year: 2020 Document Type: Article Affiliation country: Qims-20-708