Ms. Marjorie Latrasse Profile

Marjorie Latrasse

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Proceedings Article | 15 February 2021 Presentation + Paper

Traction bronchiectasis identification and quantitative biomarkers for follow-up in nonspecific interstitial pneumonia

Marjorie Latrasse, Simon Rennotte, Pierre-Yves Brillet, Sylvain Marchand-Adam, Catalin Fetita

Proceedings Volume 11597, 115970T (2021) https://doi.org/10.1117/12.2580657

KEYWORDS: Lung, Pulmonary function tests, Inflammation, Databases, Convolutional neural networks

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As a subclass of interstitial lung diseases, nonspecific interstitial pneumonia (NSIP), defined by an association of inflammation and fibrotic lung lesions, leads to progressive loss of pulmonary function and premature mortality. Among fibrosis manifestations, traction bronchiectasis (TB) is one of the most critical, its presence being associated to poor prognosis. Accurate follow up is crucial to treatment decision and adaptation. In this paper we propose quantitative biomarkers for TB, associating spatial localization and severity measures. Bronchial tree segmentation and TB identification first exploited a semi-automatic approach for the definition of the ground truth, then used an automatic method involving a convolutional neural network. The CNN training/testing database included 73/18 patients respectively, with both baseline and follow up exams at one year; the detection performance was assessed in terms of precision, recall and F1-score. For both ground truth and CNN-segmented data, the following TB biomarkers were derived: TB ratio over total airway, airway volume, normalized tree length, and airway caliber (absolute and relative) deviation from the normal 2-power decrease law. A correlation study between the TB biomarkers and the initial and follow up pulmonary function tests was conducted. Among ground truth-based TB biomarkers, airway volume, normalized tree length, absolute caliber deviation and TB ratio over total airway showed significant negative correlation with both initial and follow-up pulmonary function parameters, manifesting as potential prognosis biomarkers. Among CNN-based TB biomarkers, airway volume, normalized tree length, relative and absolute caliber deviation showed significant negative correlation with follow-up pulmonary function parameters confirming their predictive potential.

Proceedings Article | 15 February 2021 Presentation + Paper

Transferring CT image biomarkers from fibrosing idiopathic interstitial pneumonia to COVID-19 analysis

Catalin Fetita, Simon Rennotte, Marjorie Latrasse, Ruxandra Tapu, Mathilde Maury, Bogdan Mocanu, Hilario Nunes, Pierre-Yves Brillet

Proceedings Volume 11597, 1159708 (2021) https://doi.org/10.1117/12.2580658

KEYWORDS: Computed tomography, Lung, Biological research, Image analysis, Pathology, Opacity, Image registration, Image classification, Glasses

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Fibrosing idiopathic interstitial pneumonia (fIIP) is a subclass of interstitial lung diseases, which leads to fibrosis in a continuous and irreversible process of lung function decay. Patients with fIIP require regular quantitative follow-up with CT and several image biomarkers have already been proposed to grade the pathology severity and try to predict the evolution. Among them, we cite the spatial extent of the diseased lung parenchyma and airway and vascular remodeling markers. COVID-19 (Cov-19) presents several similarities with fIIP and this condition is moreover suspected to evolve to fIIP in 10-30% of severe cases. Note also that the main difference between Cov-19 and fIIP is the presence of peripheral ground glass opacities and less or no amount of fibrosis in the lung, as well as the absence of airway remodeling. This paper proposes a preliminary study to investigate how existing image markers for fIIP may apply to Cov-19 phenotyping, namely texture classification and vascular remodeling. In addition, since for some patients, the fIIP/Cov-19 follow-up protocol imposes CT acquisitions at both full inspiration and full expiration, this information could also be exploited to extract additional knowledge for each individual case. We hypothesize that taking into account the two respiratory phases to analyze breathing parameters through interpolation and registration might contribute to a better phenotyping of the pathology. This preliminary study, conducted on a reduced number of patients (eight Cov-19 of different severity degrees, two fIIP patients and one control), shows a great potential of the selected CT image markers.

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