Quantitative Evaluation of Lobar Pulmonary Function of Emphysema Patients with Endobronchial Coils

Comparison of lung volumes measured with computed tomography and whole-body plethysmography - a systematic review

Introduction

Whole-body plethysmography is the preferred method for measuring the static lung volumes: total lung capacity (TLC), functional residual capacity (FRC) and residual volume (RV), as it also incorporates trapped gas - a common finding in chronic obstructive pulmonary disease (COPD). Quantitative computed tomography (CT) is a promising alternative to plethysmography, which can be challenging to perform for patients with severely impaired lung function. The present systematic review explores the agreement between lung volumes measured by plethysmography and CT, as well as the attempts being made to optimize alignment between these two methods.

Methods

A literature search was performed on the PubMed database using the block search strategy. Articles were included if they provided both CT based and plethysmography based TLC. Risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) checklist.

Results

22 articles were included. On average, CT-derived TLC (CT-TLC) was 709 mL lower compared to plethysmography TLC (p-TLC) with a 12.1% deviation from the reference standard, p-TLC. This discrepancy (ΔTLC) appeared slightly larger in obstructive patients (obstructive: 781 mL, non-obstructive: 609 mL), whereas percent deviation was slightly smaller (obstructive: 11.4%, non-obstructive: 13.5%). CT-based RV analyses primarily based on COPD patients measured 603 mL higher than plethysmography (p-RV) with 17.8% deviation from p-RV. Studies utilizing spirometry-gating for CT acquisition reported good agreement between modalities (ΔTLC: 70-280 mL), and one study demonstrated noticeable improvements compared to conventional breath-hold instructions in an otherwise identical study setting.

Conclusion

CT quantifications routinely underestimate TLC and overestimate RV in comparison to plethysmography. Spirometry gating reduces the level of disagreement and can be of assistance when patients are already undergoing CT. However, further studies are needed to confirm these results.

Reproducibility of a semiautomatic lobar lung tissue assignment technique on noncontrast CT scans: a study on swine animal model

BACKGROUND

To evaluate the reproducibility of a vessel-specific minimum cost path (MCP) technique used for lobar segmentation on noncontrast computed tomography (CT).

METHODS

Sixteen Yorkshire swine (49.9 ± 4.7 kg, mean ± standard deviation) underwent a total of 46 noncontrast helical CT scans from November 2020 to May 2022 using a 320-slice scanner. A semiautomatic algorithm was employed by three readers to segment the lung tissue and pulmonary arterial tree. The centerline of the arterial tree was extracted and partitioned into six subtrees for lobar assignment. The MCP technique was implemented to assign lobar territories by assigning lung tissue voxels to the nearest arterial tree segment. MCP-derived lobar mass and volume were then compared between two acquisitions, using linear regression, root mean square error (RMSE), and paired sample t-tests. An interobserver and intraobserver analysis of the lobar measurements was also performed.

RESULTS

The average whole lung mass and volume was 663.7 ± 103.7 g and 1,444.22 ± 309.1 mL, respectively. The lobar mass measurements from the initial (MLobe1) and subsequent (MLobe2) acquisitions were correlated by MLobe1 = 0.99 MLobe2 + 1.76 (r = 0.99, p = 0.120, RMSE = 7.99 g). The lobar volume measurements from the initial (VLobe1) and subsequent (VLobe2) acquisitions were correlated by VLobe1 = 0.98VLobe2 + 2.66 (r = 0.99, p = 0.160, RSME = 15.26 mL).

CONCLUSIONS

The lobar mass and volume measurements showed excellent reproducibility through a vessel-specific assignment technique. This technique may serve for automated lung lobar segmentation, facilitating clinical regional pulmonary analysis.

RELEVANCE STATEMENT

Assessment of lobar mass or volume in the lung lobes using noncontrast CT may allow for efficient region-specific treatment strategies for diseases such as pulmonary embolism and chronic thromboembolic pulmonary hypertension.

KEY POINTS

• Lobar segmentation is essential for precise disease assessment and treatment planning. • Current methods for segmentation using fissure lines are problematic. • The minimum-cost-path technique here is proposed and a swine model showed excellent reproducibility for lobar mass measurements. • Interobserver agreement was excellent, with intraclass correlation coefficients greater than 0.90.

Application of 3D computed tomography in emphysematous parenchyma patients scheduled for bronchoscopic lung volume reduction

Bronchoscopic lung volume reduction (BLVR) is a feasible, safe, effective and minimally invasive technique to significantly improve the quality of life of advanced severe chronic obstructive pulmonary disease (COPD). In this study, three-dimensional computed tomography (3D-CT) automatic analysis software combined with pulmonary function test (PFT) was used to retrospectively evaluate the postoperative efficacy of BLVR patients. The purpose is to evaluate the improvement of lung function of local lung tissue after operation, maximize the benefits of patients, and facilitate BLVR in the treatment of patients with advanced COPD. All the reported cases of advanced COPD patients treated with BLVR with one-way valve were collected and analysed from 2017 to 2020. Three-dimensional-CT image analysis software system was used to analyse the distribution of low-density areas <950 Hounsfield units in both lungs pre- and post- BLVR. Meanwhile, all patients performed standard PFT pre- and post-operation for retrospective analysis. We reported six patients that underwent unilateral BLVR with 1 to 3 valves according to the range of emphysema. All patients showed a median increase in forced expiratory volume in 1 second (FEV1) of 34%, compared with baseline values. Hyperinflation was reduced by 16.6% (range, 4.9%-47.2%). The volumetric measurements showed a significant reduction in the treated lobe volume among these patients. Meanwhile, the targeted lobe volume changes were inversely correlated with change in FEV1/FEV1% in patients with heterogeneous emphysematous. We confirm that 3D-CT analysis can quantify the changes of lung volume, ventilation and perfusion, to accurately evaluate the distribution and improvement of emphysema and rely less on the observer.

Predicted versus CT-derived total lung volume in a general population: The ImaLife study

Predicted lung volumes based on the Global Lung Function Initiative (GLI) model are used in pulmonary disease detection and monitoring. It is unknown how well the predicted lung volume corresponds with computed tomography (CT) derived total lung volume (TLV). The aim of this study was to compare the GLI-2021 model predictions of total lung capacity (TLC) with CT-derived TLV. 151 female and 139 male healthy participants (age 45-65 years) were consecutively selected from a Dutch general population cohort, the Imaging in Lifelines (ImaLife) cohort. In ImaLife, all participants underwent low-dose, inspiratory chest CT. TLV was measured by an automated analysis, and compared to predicted TLC based on the GLI-2021 model. Bland-Altman analysis was performed for analysis of systematic bias and range between limits of agreement. To further mimic the GLI-cohort all analyses were repeated in a subset of never-smokers (51% of the cohort). Mean±SD of TLV was 4.7±0.9 L in women and 6.2±1.2 L in men. TLC overestimated TLV, with systematic bias of 1.0 L in women and 1.6 L in men. Range between limits of agreement was 3.2 L for women and 4.2 L for men, indicating high variability. Performing the analysis with never-smokers yielded similar results. In conclusion, in a healthy cohort, predicted TLC substantially overestimates CT-derived TLV, with low precision and accuracy. In a clinical context where an accurate or precise lung volume is required, measurement of lung volume should be considered.

Evaluation of spirometry-gated computed tomography to measure lung volumes in emphysema patients

Introduction

In emphysema patient being evaluated for bronchoscopic lung volume reduction (BLVR), accurate measurement of lung volumes is important. Total lung capacity (TLC) and residual volume (RV) are commonly measured by body plethysmography but can also be derived from chest computed tomography (CT). Spirometry-gated CT scanning potentially improves the agreement of CT and body plethysmography. The aim of this study was to compare lung volumes derived from spirometry-gated CT and “breath-hold-coached” CT to the reference standard: body plethysmography.

Methods

In this single-centre retrospective cohort study, emphysema patients being evaluated for BLVR underwent body plethysmography, inspiration (TLC) and expiration (RV) CT scan with spirometer guidance (“gated group”) or with breath-hold-coaching (“non-gated group”). Quantitative analysis was used to calculate lung volumes from the CT.

Results

200 patients were included in the study (mean±sd age 62±8 years, forced expiratory flow in 1 s 29.2±8.7%, TLC 7.50±1.46 L, RV 4.54±1.07 L). The mean±sd CT-derived TLC was 280±340 mL lower compared to body plethysmography in the gated group (n=100), and 590±430 mL lower for the non-gated group (n=100) (both p<0.001). The mean±sd CT-derived RV was 300±470 mL higher in the gated group and 700±720 mL higher in the non-gated group (both p<0.001). Pearson correlation factors were 0.947 for TLC gated, 0.917 for TLC non-gated, 0.823 for RV gated, 0.693 for RV non-gated, 0.539 for %RV/TLC gated and 0.204 for %RV/TLC non-gated. The differences between the gated and non-gated CT results for TLC and RV were significant for all measurements (p<0.001).

Conclusion

In severe COPD patients with emphysema, CT-derived lung volumes are strongly correlated to body plethysmography lung volumes, and especially for RV, more accurate when using spirometry gating.

Measuring pulmonary function in COPD using quantitative chest computed tomography analysis

COPD is diagnosed and evaluated by pulmonary function testing (PFT). Chest computed tomography (CT) primarily serves a descriptive role for diagnosis and severity evaluation. CT densitometry-based emphysema quantification and lobar fissure integrity assessment are most commonly used, mainly for lung volume reduction purposes and scientific efforts.

A shift towards a more quantitative role for CT to assess pulmonary function is a logical next step, since more, currently underutilised, information is present in CT images. For instance, lung volumes such as residual volume and total lung capacity can be extracted from CT; these are strongly correlated to lung volumes measured by PFT.

This review assesses the current evidence for use of quantitative CT as a proxy for PFT in COPD and discusses challenges in the movement towards CT as a more quantitative modality in COPD diagnosis and evaluation. To better understand the relevance of the traditional PFT measurements and the role CT might play in the replacement of these parameters, COPD pathology and traditional PFT measurements are discussed.

CT may be used as a proxy for lung function in COPD diagnosis and evaluation, particularly for the hyperinflation markershttps://bit.ly/2RrGAZf

Challenges of evaluating lung function as part of cancer care during the COVID-19 pandemic

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a newly identified agent foisted upon humanity and responsible for the contagious affliction, coronavirus disease 2019 (COVID-19) [1] that has rapidly evolved into a pandemic testing to the limits, and sometimes beyond, the capacity to respond of healthcare systems across the world [2]. Management is purely supportive and social isolation crucial to containment [3]. Enforced reallocation of hospital resources and personnel to cope with the increasing numbers requiring hospital admission and intensive care [4] in the most trying of conditions has been at the expense of many hospital departments, among them those offering diagnostic and support services for lung cancer [5–7].

The COVID-19 pandemic and the necessity for social isolation are ushering in a new era of remote clinical evaluation. Modifications of CT imaging and processing in chest medicine yield both anatomical and functional information in a safe environment. https://bit.ly/2Np3Dyz

Inter- and intra-software reproducibility of computed tomography lung density measurements

PURPOSE

Multiple commercial, open-source, and academic software tools exist for objective quantification of lung density in computed tomography (CT) images. The purpose of this study was to evaluate the intersoftware reproducibility of CT lung density measurements.

METHODS

Computed tomography images from 50 participants from the COPDGene^TM cohort study were randomly selected for analysis; n = 10 participants across each global initiative for chronic obstructive lung disease (GOLD) grade (GOLD 0-IV). Academic-based groups (n = 4) and commercial vendors (n = 4) participated anonymously to generate CT lung density measurements using their software tools. Computed tomography total lung volume (TLV), percentage of the low attenuation areas in the lung with Hounsfield unit (HU) values below -950HU (LAA₉₅₀ ), and the HU value corresponding to the 15th percentile on the parenchymal density histogram (Perc15) were included in the analysis. The intersoftware bias and reproducibility coefficient (RDC) was generated with and without quality assurance (QA) for manual correction of the lung segmentation; intrasoftware bias and RDC was also generated by repeated measurements on the same images.

RESULTS

Intersoftware mean bias was within ±0.22 mL, ±0.46%, and ±0.97 HU for TLV, LAA₉₅₀ and Perc15, respectively. The RDC was 0.35 L, 1.2% and 1.8 HU for TLV, LAA₉₅₀ and Perc15, respectively. Intersoftware RDC remained unchanged following QA: 0.35 L, 1.2% and 1.8 HU for TLV, LAA₉₅₀ and Perc15, respectively. All software investigated had an intrasoftware RDC of 0. The RDC was comparable for TLV, LAA₉₅₀ and Perc15 measurements, respectively, for academic-based groups/commercial vendor-based software tools: 0.39 L/0.32 L, 1.2%/1.2%, and 1.7 HU/1.6 HU. Multivariable regression analysis showed that academic-based software tools had greater within-subject standard deviation of TLV than commercial vendors, but no significant differences between academic and commercial groups were found for LAA₉₅₀ or Perc15 measurements.

CONCLUSIONS

Computed tomography total lung volume and lung density measurement bias and reproducibility was reported across eight different software tools. Bias was negligible across vendors, reproducibility was comparable for software tools generated by academic-based groups and commercial vendors, and segmentation QA had negligible impact on measurement variability between software tools. In summary, results from this study report the amount of additional measurement variability that should be accounted for when using different software tools to measure lung density longitudinally with well-standardized image acquisition protocols. However, intrasoftware reproducibility was deterministic for all cases so use of the same software tool to reduce variability for serial studies is highly recommended.