Lung Volume Calculation in Preclinical MicroCT: A Fast Geometrical Approach

Lung; Preclinical imaging; VolumePulmón; Imágenes preclínicas; VolumenPulmó; Imatges preclíniques; VolumIn this study, we present a time-efficient protocol for thoracic volume calculation as a proxy for total lung volume. We hypothesize that lung volume can be calculated indirectly from this thoracic volume. We compared the measured thoracic volume with manually segmented and automatically thresholded lung volumes, with manual segmentation as the gold standard. A linear regression formula was obtained and used for calculating the theoretical lung volume. This volume was compared with the gold standard volumes. In healthy animals, thoracic volume was 887.45 mm3, manually delineated lung volume 554.33 mm3 and thresholded aerated lung volume 495.38 mm3 on average. Theoretical lung volume was 554.30 mm3. Finally, the protocol was applied to three animal models of lung pathology (lung metastasis and transgenic primary lung tumor and fungal infection). In confirmed pathologic animals, thoracic volumes were: 893.20 mm3, 860.12 and 1027.28 mm3. Manually delineated volumes were 640.58, 503.91 and 882.42 mm3, respectively. Thresholded lung volumes were 315.92 mm3, 408.72 and 236 mm3, respectively. Theoretical lung volume resulted in 635.28, 524.30 and 863.10.42 mm3. No significant differences were observed between volumes. This confirmed the potential use of this protocol for lung volume calculation in pathologic models

Quantitative CT-based image registration metrics provide different ventilation and lung motion patterns in prone and supine positions in healthy subjects

Background Previous studies suggested that the prone position (PP) improves oxygenation and reduces mortality among patients with acute respiratory distress syndrome (ARDS). However, the mechanism of this clinical benefit of PP is not completely understood. The aim of the present study was to quantitatively compare regional characteristics of lung functions in the PP with those in the supine position (SP) using inspiratory and expiratory computed tomography (CT) scans. Methods Ninety subjects with normal pulmonary function and inspiration and expiration CT images were included in the study. Thirty-four subjects were scanned in PP, and 56 subjects were scanned in SP. Non-rigid image registration-based inspiratory-expiratory image matching assessment was used for regional lung function analysis. Tissue fractions (TF) were computed based on the CT density and compared on a lobar basis. Three registration-derived functional variables, relative regional air volume change (RRAVC), volumetric expansion ratio (J), and three-dimensional relative regional displacement (s*) were used to evaluate regional ventilation and deformation characteristics. Results J was greater in PP than in SP in the right middle lobe (P = 0 .025), and RRAVC was increased in the upper and right middle lobes (P < 0.001). The ratio of the TF on inspiratory and expiratory scans, J, and RRAVC at the upper lobes to those at the middle and lower lobes and that ratio at the upper and middle lobes to those at the lower lobes of were all near unity in PP, and significantly higher than those in SP (0.98–1.06 vs 0.61–0.94, P < 0.001). Conclusion We visually and quantitatively observed that PP not only induced more uniform contributions of regional lung ventilation along the ventral-dorsal axis but also minimized the lobar differences of lung functions in comparison with SP. This may help in the clinicians search for an understanding of the benefits of the application of PP to the patients with ARDS or other gravitationally dependent pathologic lung diseases. Trial registration Retrospectively registered.This research was supported by a Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1A1A09082160) and Korea Environment Industry & Technology Institute (KEITI) through Environmental Health Action Program, funded by Korea Ministry of Environment (MOE) (2018001360001)

Processamento e análise em tomografia computorizada pulmonar: pneumonia

Mestrado em Tecnologias da Imagem MédicaA Tomografia Computorizada (TC) representa a modalidade imagiológica mais eficiente no estudo das regiões pulmonares. Os métodos para a segmentação pulmonar são ferramentas essenciais para a análise de imagens de TC pulmonar, pois permitem a avaliação de parâmetros quantitativos, que podem ter grande interesse na avaliação de patologias pulmonares e impactos de intervenções terapêuticas, nomeadamente em pneumonia. As técnicas de fisioterapia respiratória têm sido exploradas como um complemento ao tratamento de pneumonia, no entanto é ainda um assunto bastante controverso e em investigação. De entre as inúmeras abordagens para a segmentação pulmonar existentes, a maioria não funciona adequadamente na presença de condição patológica moderada a severa. Assim, os principais objetivos deste projeto de investigação consistiram no desenvolvimento de uma rede de processamento e análise de imagem, utilizando a plataforma MeVisLab, para a segmentação automática da árvore brônquica (AB) e do parênquima pulmonar, em exames de TC pulmonar de pacientes com pneumonia. A rede foi utilizada para obter o volume e a densidade do parênquima pulmonar numa amostra de 33 pacientes com diagnóstico de pneumonia, com o objetivo de averiguar qual o impacto das técnicas de fisioterapia respiratória na condição clínica dos pacientes submetidos a esta abordagem terapêutica. Todos os pacientes realizaram duas TC pulmonares, uma de caráter urgente e outras após três semanas de tratamento, sendo que este consistiu numa terapêutica conservadora farmacológica (grupo de controlo) ou na conjugação desta última com fisioterapia respiratória (grupo experimental). A rede MeVisLab desenvolvida conjugou alguns métodos de segmentação pulmonar, nomeadamente o método de Region Growing 3D e o método baseado no registo, que foi utilizado na segmentação pulmonar de casos clínicos com achados imagiológicos severos, em que o método de Region Growing 3D se revelou ineficaz. Além disto, o método de segmentação baseado no registo foi validado numa amostra de 15 pacientes nos quais era possível aplicar os dois métodos de segmentação. Todos os dados recolhidos neste projeto foram analisados estatisticamente, sendo aplicado o teste da ANOVA de dois fatores mistos para avaliar os efeitos das intervenções terapêuticas na amostra em estudo e o teste t-Student para a validação do método baseado no registo. Os resultados obtidos sugerem que a fisioterapia respiratória é uma abordagem terapêutica eficiente e viável na gestão de pacientes com pneumonia, principalmente ao nível das caraterísticas imagiológicas da AB, e que o método baseado no registo permitiu a obtenção de resultados de segmentação tão fiáveis como os resultados de segmentação obtidos pelo método de Region Growing 3D.Computed Tomography (CT) represents the most efficient imaging modality in the study of pulmonary regions. Methods for the pulmonary segmentation are essential tolls for the analysis of pulmonary CT images because they allow the evaluation of quantitative parameters which can be extremely important in the evaluation of pulmonary diseases and therapeutic interventions, such as pneumonia. The respiratory physiotherapy techniques have been implemented as a complementary intervention in pneumonia, however this is controverse and is under and investigation. Among the many approaches to the lung segmentation, most of them don´t work correctly in the presence of a moderate to severe pathological condition. Thus, the main objectives of this project were the development of an image processing and an analysis network using the MeVisLab platform for the automatic segmentation of the bronchial tree and the pulmonary parenchyma, in pulmonary CT scans of patients with pneumonia. Then, the respective quantitative parameters were extracted (volume and density) to determinate the impact of respiratory physiotherapy on de clinical condition of patients submitted to this therapeutic approach. This project included 33 patients with suspected pneumonia, who performed two pulmonary CT, the first of the urgent character and the other three weeks after de treatment, which consisted in a conservative pharmacological therapy (control group) or a combination on this latter with the respiratory physiotherapy (experimental group). The MeVisLab network combined some methods for the lung segmentation, principally the Region Growing 3D and registration methods. The last method was used in the pulmonary segmentation of clinical cases with severe imaging findings, in which the Region Growing 3D was inefficient. In addition, these two methods were applied in a set of 15 patients in order to test the similarity between both. All the data of these project were statistically analyzed, being applied the ANOVA two way to evaluate the effects of the therapeutics interventions in the sample patients and the Student t-test for the validation of the method based on registration. The results obtained suggested that respiratory physiotherapy seems an efficient and viable therapeutic in the management of patients with pneumonia, mainly at the level of bronchial tree imaging features, and that the method based on registration allowed to obtain segmentation results as reliable as the segmentation results obtained with the standard method