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Titolo:
A software tool for automatic image-based ventilation analysis using dynamic chest CT-scanning in healthy and in ARDS lungs.
Autore:
Markstaller, K; Arnold, M; Dobrich, M; Heitmann, K; Karmrodt, J; Weiler, N; Uthmann, T; Eberle, B; Thelen, M; Kauczor, HU;
Indirizzi:
Univ Mainz, Klin & Poliklin Radiol, Anasthesiol Klin, D-55131 Mainz, Germany Univ Mainz Mainz Germany D-55131 nasthesiol Klin, D-55131 Mainz, Germany Univ Mainz, Inst Informat, D-6500 Mainz, Germany Univ Mainz Mainz Germany D-6500 nz, Inst Informat, D-6500 Mainz, Germany
Titolo Testata:
ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN
fascicolo: 9, volume: 173, anno: 2001,
pagine: 830 - 835
SICI:
1438-9029(200109)173:9<830:ASTFAI>2.0.ZU;2-2
Fonte:
ISI
Lingua:
GER
Soggetto:
RESPIRATORY-DISTRESS SYNDROME; MULTIPLE NEURAL NETWORKS; GROUND-GLASS OPACITIES; RECRUITMENT; DIAGNOSIS; COLLAPSE; LAVAGE; INJURY; MODEL;
Keywords:
software; computed tomography (CT); quantitative; lung, ventilation; lung, density; Adult Respiratory Distress Syndrome (ARDS);
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Citazioni:
16
Recensione:
Indirizzi per estratti:
Indirizzo: Markstaller, K Univ Mainz, Klin & Poliklin Radiol, Anasthesiol Klin, Langenbeckstr 1, D-55131 Mainz, Germany Univ Mainz Langenbeckstr 1 Mainz Germany D-55131 , Germany
Citazione:
K. Markstaller et al., "A software tool for automatic image-based ventilation analysis using dynamic chest CT-scanning in healthy and in ARDS lungs.", ROFO-F RONT, 173(9), 2001, pp. 830-835

Abstract

Purpose: Density measurements in dynamic CT image series of the lungs allow one to quantify ventilated, hyperinflated, and atelectatic pulmonary compartments with high temporal resolution. Fast automatic segmentation of lungparenchyma and a subsequent evaluation of it's respective density values are a prerequisite for any clinical application of this technique. Material and Methods: For automatic lung segmentation in thoracic CT scans, an algorithm was developed which uses (a) different density masks, and (b) anatomicknowledge to differentiate heart, diaphragm and chest wall from ventilatedand atelectatic lung parenchyma. With Animal Care Committee approval, the automated technique was tested in 8 anaesthetized ventilated pigs undergoing dynamic CT before and after induction of lavage-ARDS. Images were acquired in one supradiaphragmatic, cross-sectional slice (temporal resolution of 100 ms; slice thickness of 1 mm, high resolution reconstruction algorithm). In 120 CT images the total pixel number and the calculated MLD from the automatically segmentated lung were compared to the values obtained from an interactive lung segmentation. Results: The software tool was able to read all image series (DICOM standard). Automatic and interactive segmentation were in high agreement (R-2 = 0.99 for the total number of pixels and the MILD). Originally, the most frequent error was misclassification of atelectasis as extrapulmonary solid tissue. Conclusion: An automatic software tool ispresented for lung segmentation in healthy lungs and in ARDS. Aerated lungand atelectasis were identified with high accuracy. This post-processing tool allows for a quantitative, CT based assessment of ventilation and recruitment processes in the lung. Thus, it may help to optimize ventilation patterns in patients with ARDS.

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Documento generato il 09/04/20 alle ore 00:15:19