Lung ventilation and the physiology of breathing

Barrow, Anna; Pandit, J. J.

doi:10.1016/j.mpsur.2017.02.004

Cited by 4 publications

(6 citation statements)

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“…In contrast, expiration is a passive process that is largely driven by the elastic recoil of lung tissue and the thoracic wall. 17 Considering the distribution of the critical time points (T max , T min ), only 26.2% of lung voxels (2.59 × 10 6 in 9.89 × 10 6 voxels) exhibited the same expansion/contraction pattern as global lung. This further demonstrates that there are limitations in the conventional 2-phase 4DCT-based ventilation imaging metrics that the utilization of only EE and EI phase pairs actually ignores the temporal heterogeneity of ventilation process.…”

Section: Discussionmentioning

confidence: 95%

“…During quiet breathing (different from forced breathing), inspiration process is primarily driven by the contraction of respiratory muscles, including the diaphragm and intercostal muscles. In contrast, expiration is a passive process that is largely driven by the elastic recoil of lung tissue and the thoracic wall 17 . Considering the distribution of the critical time points

( {{T_{max}},\;{T_{min}}} )

, only 26.2% of lung voxels (2.59 × 10 6 in 9.89 × 10 6 voxels) exhibited the same expansion/contraction pattern as global lung.…”

Section: Discussionmentioning

confidence: 99%

“…Affected by physiological and pathological factors, the spatiotemporal heterogeneities of ventilation generally exist during normal breathing. 17,18 Dynamic consideration of the evolution of the ventilation process throughout respiration is helpful to more clearly spare lung tissues with different levels of function and to provide time-resolved functional information for the potential four-dimensional FLART planning. However, most of the standard NM modalities are prone to acquire time-averaged signal magnitude of inhaled agent in the respiratory cycle instead of time-resolved images.…”

Section: Introductionmentioning

confidence: 99%

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Volumetric multiphase ventilation imaging based on four‐dimensional computed tomography for functional lung avoidance radiotherapy

et al. 2022

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Purpose Current computed tomography (CT)‐based lung ventilation imaging (CTVI) techniques derive a static ventilation image without temporal information. This research aims to develop a four‐dimensional CT (4DCT)‐based multiphase dynamic ventilation imaging framework capable of recovering the entire ventilation process throughout the breathing cycle for functional lung avoidance radiotherapy (FLART). Methods A total of 15 free‐breathing thoracic 4DCT scans of lung or esophageal cancer patients were collected from the public datasets. The lung region of each phase image was first delineated, and then the mask‐free isotropic total variation image registration algorithm was used to derive the deformation vector fields between the end‐expiration (EE) phase and other phases. As a surrogate of ventilation, the voxel‐wise local expansion ratio of each phase relative to the EE phase was estimated using the parameterized Integrated Jacobian Formulation method in the EE phase coordinate. Lastly, the dynamic ventilation images were generated by warping these phase‐specific local expansion distributions with a same geometry into their respective breathing phases. Quantitative analysis, including interphase Spearman correlation coefficients, voxel‐wise, and regional‐wise expansion/contraction tracking, were performed to indirectly validate the proposed method. Results The proposed method maintains the physiological meaning of ventilation on each phase and enables to recover the dynamic lung ventilation process. The mean interphase Spearman correlations ranged between 0.23 ± 0.20 and 0.93 ± 0.04 and decreased near the EE phase. Only 26.2% (2.59E + 6 out of 9.89E + 6) of lung voxels exhibited the same expansion/contraction pattern as the global lung. Qualitative and quantitative evaluations of the interphase ventilation distribution difference show that ventilation spatiotemporal heterogeneities generally exist during respiration. Conclusions In contrast to conventional CTVI metrics, our method enables to extract additional phase‐resolved respiration‐correlated information and reflects the generally existed ventilation spatiotemporal heterogeneities. Subsequent studies with quantitative phase‐by‐phase cross‐modality evaluations will further explore its potential to deepen our understanding of lung function and respiration mechanics and also to facilitate more accurate implementation of FLART.

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Section: Discussionmentioning

confidence: 95%

( {{T_{max}},\;{T_{min}}} )

, only 26.2% of lung voxels (2.59 × 10 6 in 9.89 × 10 6 voxels) exhibited the same expansion/contraction pattern as global lung.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Volumetric multiphase ventilation imaging based on four‐dimensional computed tomography for functional lung avoidance radiotherapy

et al. 2022

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“…Key Words: computed tomography, ventilation, lung cancer, functional imaging, radiomics (J Thorac Imaging 2023;38:286-296) S patial variability in the distribution of lung function, of which ventilation (V) and perfusion (Q) are fundamental components, is commonly affected by a mixture of physiological and pathological factors, both internal and external. [1][2][3] Visual inspection and quantitative assessment of the lung function distribution have unique applications for interpreting respiratory mechanisms, diagnosing thoracic diseases, and personalized planning of lung toxicity optimization in lung cancer radiotherapy (RT) planning (eg, functional lung avoidance RT). 4,5 At present, the mainstream methods for lung function imaging depend on contrast agent-based direct mapping or algorithm-aided indirect mapping.…”

Section: Discussionmentioning

confidence: 99%

“…Spatial variability in the distribution of lung function, of which ventilation (V) and perfusion (Q) are fundamental components, is commonly affected by a mixture of physiological and pathological factors, both internal and external 1–3 . Visual inspection and quantitative assessment of the lung function distribution have unique applications for interpreting respiratory mechanisms, diagnosing thoracic diseases, and personalized planning of lung toxicity optimization in lung cancer radiotherapy (RT) planning (eg, functional lung avoidance RT) 4,5 …”

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confidence: 99%

Respiratory Invariant Textures From Static Computed Tomography Scans for Explainable Lung Function Characterization

Huang

Teng

Zhang

et al. 2023

Journal of Thoracic Imaging

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Purpose: The inherent characteristics of lung tissue independent of breathing maneuvers may provide fundamental information for function assessment. This paper attempted to correlate textural signatures from computed tomography (CT) with pulmonary function measurements. Materials and Methods: Twenty-one lung cancer patients with thoracic 4-dimensional CT, DTPA-single-photon emission CT ventilation (V NM) scans, and available spirometry measurements (forced expiratory volume in 1 s, FEV1; forced vital capacity, FVC; and FEV1/FVC) were collected. In subregional feature discovery, function-correlated candidates were identified from 79 radiomic features based on the statistical strength to differentiate defected/nondefected lung regions. Feature maps (FMs) of selected candidates were generated on 4-dimensional CT phases for a voxel-wise feature distribution study. Quantitative metrics were applied for validations, including the Spearman correlation coefficient (SCC) and the Dice similarity coefficient for FM-V NM spatial agreement assessments, intraclass correlation coefficient for FM interphase robustness evaluations, and FM-spirometry comparisons. Results: At the subregion level, 8 function-correlated features were identified (effect size>0.330). The FMs of candidates yielded moderate-to-strong voxel-wise correlations with the reference V NM. The FMs of gray level dependence matrix dependence nonuniformity showed the highest robust (intraclass correlation coefficient=0.96 and P<0.0001) spatial correlation, with median SCCs ranging from 0.54 to 0.59 throughout the 10 breathing phases. Its phase-averaged FM achieved a median SCC of 0.60, a median Dice similarity coefficient of 0.60 (0.65) for high (low) functional lung volumes, and a correlation of 0.565 (0.646) between the spatially averaged feature values and FEV1 (FEV1/FVC). Conclusions: The results provide further insight into the underlying association of specific pulmonary textures with both local (V NM) and global (FEV1/FVC, FEV1) functions. Further validations of the FM generalizability and the standardization of implementation protocols are warranted before clinically relevant investigations.

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Diaphragmatic electromyography in infants: an overview of possible clinical applications

Scholten,

van Leuteren,

de Waal

et al. 2023

Pediatr Res

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Lung ventilation and the physiology of breathing

Cited by 4 publications

References 0 publications

Volumetric multiphase ventilation imaging based on four‐dimensional computed tomography for functional lung avoidance radiotherapy

Volumetric multiphase ventilation imaging based on four‐dimensional computed tomography for functional lung avoidance radiotherapy

Respiratory Invariant Textures From Static Computed Tomography Scans for Explainable Lung Function Characterization

Diaphragmatic electromyography in infants: an overview of possible clinical applications

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