3-D lung deformation and function from respiratory-gated 4-D x-ray CT images : application to radiation treatment planning.

Many lung diseases or injuries can cause biomechanical or material property changes that can alter lung function. While the mechanical changes associated with the change of the material properties originate at a regional level, they remain largely asymptomatic and are invisible to global measures of lung function until they have advanced significantly and have aggregated. In the realm of external beam radiation therapy of patients suffering from lung cancer, determination of patterns of pre- and post-treatment motion, and measures of regional and global lung elasticity and function are clinically relevant. In this dissertation, we demonstrate that 4-D CT derived ventilation images, including mechanical strain, provide an accurate and physiologically relevant assessment of regional pulmonary function which may be incorporated into the treatment planning process. Our contributions are as follows: (i) A new volumetric deformable image registration technique based on 3-D optical flow (MOFID) has been designed and implemented which permits the possibility of enforcing physical constraints on the numerical solutions for computing motion field from respiratory-gated 4-D CT thoracic images. The proposed optical flow framework is an accurate motion model for the thoracic CT registration problem. (ii) A large displacement landmark-base elastic registration method has been devised for thoracic CT volumetric image sets containing large deformations or changes, as encountered for example in registration of pre-treatment and post-treatment images or multi-modality registration. (iii) Based on deformation maps from MOFIO, a novel framework for regional quantification of mechanical strain as an index of lung functionality has been formulated for measurement of regional pulmonary function. (iv) In a cohort consisting of seven patients with non-small cell lung cancer, validation of physiologic accuracy of the 4-0 CT derived quantitative images including Jacobian metric of ventilation, Vjac, and principal strains, (V?1, V?2, V?3, has been performed through correlation of the derived measures with SPECT ventilation and perfusion scans. The statistical correlations with SPECT have shown that the maximum principal strain pulmonary function map derived from MOFIO, outperforms all previously established ventilation metrics from 40-CT. It is hypothesized that use of CT -derived ventilation images in the treatment planning process will help predict and prevent pulmonary toxicity due to radiation treatment. It is also hypothesized that measures of regional and global lung elasticity and function obtained during the course of treatment may be used to adapt radiation treatment. Having objective methods with which to assess pre-treatment global and regional lung function and biomechanical properties, the radiation treatment dose can potentially be escalated to improve tumor response and local control

Predicting Outcomes in Long COVID Patients with Spatiotemporal Attention

Long COVID is a general term of post-acute sequelae of COVID-19. Patients with long COVID can endure long-lasting symptoms including fatigue, headache, dyspnea and anosmia, etc. Identifying the cohorts with severe long-term complications in COVID-19 could benefit the treatment planning and resource arrangement. However, due to the heterogeneous phenotype presented in long COVID patients, it is difficult to predict their outcomes from their longitudinal data. In this study, we proposed a spatiotemporal attention mechanism to weigh feature importance jointly from the temporal dimension and feature space. Considering that medical examinations can have interchangeable orders in adjacent time points, we restricted the learning of short-term dependency with a Local-LSTM and the learning of long-term dependency with the joint spatiotemporal attention. We also compared the proposed method with several state-of-the-art methods and a method in clinical practice. The methods are evaluated on a hard-to-acquire clinical dataset of patients with long COVID. Experimental results show the Local-LSTM with joint spatiotemporal attention outperformed related methods in outcome prediction. The proposed method provides a clinical tool for the severity assessment of long COVID

CT ventilation functional image-based IMRT treatment plans are comparable to SPECT ventilation functional image-based plans.

PurposeTo investigate the hypothesis that CT ventilation functional image-based IMRT plans designed to avoid irradiating highly-functional lung regions are comparable to single-photon emission CT (SPECT) ventilation functional image-based plans.Methods and materialsThree IMRT plans were created for eight thoracic cancer patients using: (1) CT ventilation functional images, (2) SPECT ventilation functional images, and (3) anatomic images (no functional images). CT ventilation images were created by deformable image registration of 4D-CT image data sets and quantitative analysis. The resulting plans were analyzed for the relationship between the deviations of CT-functional plan metrics from anatomic plan metrics (ΔCT-anatomic) and those of SPECT-functional plans (ΔSPECT-anatomic), and moreover for agreements of various metrics between the CT-functional and SPECT-functional plans.ResultsThe relationship between ΔCT-anatomic and ΔSPECT-anatomic was strong (e.g., R=0.94; linear regression slope 0.71). The average differences and 95% limits of agreement between the CT-functional and SPECT-functional plan metrics (except for monitor units) for various structures were mostly less than 1% and 2%, respectively.ConclusionsThis study demonstrated a reasonable agreement between the CT ventilation functional image-based IMRT plans and SPECT-functional plans, suggesting the potential for CT ventilation imaging to serve as a surrogate for SPECT ventilation in functional image-guided radiotherapy

CT ventilation functional image-based IMRT treatment plans are comparable to SPECT ventilation functional image-based plans.

PurposeTo investigate the hypothesis that CT ventilation functional image-based IMRT plans designed to avoid irradiating highly-functional lung regions are comparable to single-photon emission CT (SPECT) ventilation functional image-based plans.Methods and materialsThree IMRT plans were created for eight thoracic cancer patients using: (1) CT ventilation functional images, (2) SPECT ventilation functional images, and (3) anatomic images (no functional images). CT ventilation images were created by deformable image registration of 4D-CT image data sets and quantitative analysis. The resulting plans were analyzed for the relationship between the deviations of CT-functional plan metrics from anatomic plan metrics (ΔCT-anatomic) and those of SPECT-functional plans (ΔSPECT-anatomic), and moreover for agreements of various metrics between the CT-functional and SPECT-functional plans.ResultsThe relationship between ΔCT-anatomic and ΔSPECT-anatomic was strong (e.g., R=0.94; linear regression slope 0.71). The average differences and 95% limits of agreement between the CT-functional and SPECT-functional plan metrics (except for monitor units) for various structures were mostly less than 1% and 2%, respectively.ConclusionsThis study demonstrated a reasonable agreement between the CT ventilation functional image-based IMRT plans and SPECT-functional plans, suggesting the potential for CT ventilation imaging to serve as a surrogate for SPECT ventilation in functional image-guided radiotherapy

Weak to no correlation between quantitative high-resolution computed tomography metrics and lung function change in fibrotic diseases

Background Identifying systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) patients at risk of more rapid forced vital capacity (FVC) decline could improve trial design. The purpose of the present study was to explore the prognostic value of quantitative high-resolution computed tomography (HRCT) metrics derived by Imbio lung texture analysis (LTA) tool in predicting FVC slope. Methods This retrospective study used data from patients who were not treated with investigational drugs with and without background antifibrotic therapies in tocilizumab phase 3 SSc, lebrikizumab phase 2 IPF, and zinpentraxin alfa phase 2 IPF studies conducted from 2015 to 2021. Controlled HRCT axial volumetric multidetector computed tomography scans were evaluated using the Imbio LTA tool. Associations between HRCT metrics and FVC slope were assessed through the Spearman correlation coefficient and adjusted R2 in a linear regression model adjusted by demographics and baseline clinical characteristics. Results A total of 271 SSc and IPF patients were analysed. Correlation coefficients of highest magnitude were observed in the SSc study between the extent of ground glass, normal volume, quantification of interstitial lung disease, reticular pattern, and FVC slope (−0.25, 0.28, −0.28, and −0.33, respectively), while the correlation coefficients observed in IPF studies were in general <0.2. The incremental prognostic value of the baseline HRCT metrics was marginal after adjusting baseline characteristics and was inconsistent across study arms. Conclusion Data from the SSc and IPF studies suggested weak to no and inconsistent correlation between quantitative HRCT metrics derived by the Imbio LTA tool and FVC slope in the studied SSc and IPF population

Dynamic CT imaging of volumetric changes in pulmonary nodules correlates with physical measurements of stiffness.

Background and purposeA major challenge in CT screening for lung cancer is limited specificity when distinguishing between malignant and non-malignant pulmonary nodules (PN). Malignant nodules have different mechanical properties and tissue characteristics ('stiffness') from non-malignant nodules. This study seeks to improve CT specificity by demonstrating in rats that measurements of volumetric ratios in PNs with varying composition can be determined by respiratory-gated dynamic CT imaging and that these ratios correlate with direct physical measurements of PN stiffness.Methods and materialsRespiratory-gated MicroCT images acquired at extreme tidal volumes of 9 rats with PNs from talc, matrigel and A549 human lung carcinoma were analyzed and their volumetric ratios (δ) derived. PN stiffness was determined by measuring the Young's modulus using atomic force microscopy (AFM) for each nodule excised immediately after MicroCT imaging.ResultsThere was significant correlation (p=0.0002) between PN volumetric ratios determined by respiratory-gated CT imaging and the physical stiffness of the PNs determined from AFM measurements.ConclusionWe demonstrated proof of concept that PN volume changes measured non-invasively correlate with direct physical measurements of stiffness. These results may translate clinically into a means of improving the specificity of CT screening for lung cancer and/or improving individual prognostic assessments based on lung tumor stiffness

Dynamic CT imaging of volumetric changes in pulmonary nodules correlates with physical measurements of stiffness.

Background and purposeA major challenge in CT screening for lung cancer is limited specificity when distinguishing between malignant and non-malignant pulmonary nodules (PN). Malignant nodules have different mechanical properties and tissue characteristics ('stiffness') from non-malignant nodules. This study seeks to improve CT specificity by demonstrating in rats that measurements of volumetric ratios in PNs with varying composition can be determined by respiratory-gated dynamic CT imaging and that these ratios correlate with direct physical measurements of PN stiffness.Methods and materialsRespiratory-gated MicroCT images acquired at extreme tidal volumes of 9 rats with PNs from talc, matrigel and A549 human lung carcinoma were analyzed and their volumetric ratios (δ) derived. PN stiffness was determined by measuring the Young's modulus using atomic force microscopy (AFM) for each nodule excised immediately after MicroCT imaging.ResultsThere was significant correlation (p=0.0002) between PN volumetric ratios determined by respiratory-gated CT imaging and the physical stiffness of the PNs determined from AFM measurements.ConclusionWe demonstrated proof of concept that PN volume changes measured non-invasively correlate with direct physical measurements of stiffness. These results may translate clinically into a means of improving the specificity of CT screening for lung cancer and/or improving individual prognostic assessments based on lung tumor stiffness