Complementary assessment of cardiopulmonary morphometric changes in COPD using 3D multidetector computed tomography: relationship with functional indices

Abstract

Background

This study aimed to quantitatively evaluate the structural remodeling of cardiopulmonary tissues in Chronic Obstructive Pulmonary Disease (COPD) using three-dimensional multidetector computed tomography (3D-MDCT) and to investigate the relationship between these morphometric changes and functional disease severity across genders.

Methods

A retrospective analysis was performed on 114 participants (58 stable COPD patients and 56 age-matched controls). Pulmonary function tests (PFT), Global Initiative for Chronic Obstructive Lung Disease (GOLD) staging, and clinical scores (CAT, mMRC) were recorded. Right/left lung volumes (RLV, LLV) and heart ventricular volumes (RV, LV) were measured via 3D-Slicer software. Major vascular diameters (VCS, VCI, PA) were assessed on axial CT sections.

Results

Distinct gender-related structural patterns were identified. Male COPD patients exhibited significantly higher right lung volumes compared to controls (p < 0.01), which showed a strong negative correlation with the Forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) ratio, indicating hyperinflation-driven remodeling. Conversely, male patients demonstrated significantly lower right heart ventricular volumes (RV) (p < 0.05), supporting the “pseudomicrocardia” effect where hyperinflation mechanically restricts cardiac filling. In female COPD patients, pulmonary artery (PA) diameters were higher than in controls, showing a borderline significant trend (p = 0.050), while total lung volume negatively correlated with Vena Cava Superior (VCS) diameter (p < 0.05). Across both genders, smoking pack-years were identified as a significant independent predictor of increased total lung volume (p < 0.05). Although morphometric parameters did not differ significantly across GOLD stages, RV volume was notably increased in the GOLD E subgroup, reflecting higher symptom burden.

Conclusions

3D-MDCT provides a quantitative and objective assessment of secondary cardiopulmonary structural changes that may accompany COPD. The study suggests a potential gender dimorphism in structural remodeling; while hyperinflation-related cardiac compression (pseudomicrocardia) appears more notable in males, vascular alteration trends seem more prominent in females. These morphometric insights may serve as a valuable complementary tool to spirometry, especially in monitoring disease progression and evaluating systemic structural effects in clinical practice.

Background

Chronic Obstructive Pulmonary Disease (COPD) is a severe disease that causes permanent damage to the lungs as a result of smoking and exposure to harmful gases. Narrowing of the small airways and lung tissue damage are the disease’s leading causes. Although COPD is a preventable disease, it causes serious health problems and deaths [1]. According to the World Health Organization (WHO), COPD, frequently seen among lung diseases, is estimated to be the world’s third leading cause of death in 2030. Other diseases accompanying COPD negatively affect the patient’s life expectancy. These include cardiovascular diseases, osteoporosis, muscle weakness, hormonal and metabolic disorders, anxiety, depression, and cancer. Physical inactivity, malnutrition, and oxygen deficiency can also worsen the course of the disease [2]. Although COPD is characterized by persistent respiratory symptoms and limited airflow, it is a treatable and preventable disease [3].

The diagnosis of COPD is usually made by spirometry. This test evaluates forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC). FEV1 is the main criterion for diagnosing COPD and is a dynamic parameter indicating airflow limitation. It reflects decreased expiratory airflow with decreased elastic retraction and increased airway resistance. Total lung capacity (TLC) and residual volume are the volumes that determine the amount of lung over-expansion and air trapping. The residual volume/TLC ratio is associated with mortality. In COPD, gas exchange is impaired due to decreased diffusion capacity and ventilation/perfusion imbalance¹. The severity of COPD disease is determined by the staging system in the GOLD (Global Initiative for Chronic Obstructive Lung Disease) guidelines. According to the GOLD 2017 guidelines, disease severity is assessed in four stages: Mild (GOLD 1) if the FEV1 value is 80% or higher than predicted; moderate (GOLD 2) if between 50% and 80%; severe (GOLD 3) if between 30% and 50%, and very severe (GOLD 4) if below 30%. This system is based on the American Thoracic Society (ATS) and European Respiratory Society (ERS) standards [4].

COPD is a known risk factor for right and left ventricular dysfunction, and overinflation of the lungs is considered a significant factor contributing to right and left ventricular diastolic dysfunction in patients [5]. The increase in pulmonary artery (PA) pressure creates additional load on the right heart ventricular volumes (RV) [6]. This additional load may lead to ventricular volume enlargement, contractile function impairment, and progressive RV failure. Increased RV volume causes muscle hypertrophy and dilatation. As a result of these changes, the RV becomes more spherical, the cross-sectional area widens, and the interventricular septum flattens. This leads to diastolic dysfunction in the Left heart ventricular volumes (LV). Previous studies found that RV volume was approximately 10% larger in GOLD 4 patients than in GOLD 1 patients according to the GOLD 2017 classification in patients with COPD and that for every 10 ml decrease in distal pulmonary artery blood volume, there was a 1 ml increase in RV volume [7]. Furthermore, distal arterial vascular volume loss and enlarged RV have been associated with an increased risk of death. In patients with COPD, it has been observed that subclinical systolic dysfunction in the LV may occur before the development of significant RV and LV failure, which is associated with the severity of the disease. In patients with COPD, LV systolic dysfunction can be present even in those with FEV1 values above 50%, and these findings suggest that the effects of COPD on cardiac function may be observed in the early period and may be directly related to the severity of the disease [8].

The effect of respiration on VCS flow rate is based on changes in pleural and right atrial pressure. In COPD patients, the VCS restricts the filling of the right atrium, resulting in a sustained elevation of right atrial pressure throughout the respiratory cycle. This reduces respiratory-related variability in VCS flow rate in patients with COPD [9]. Backflow across the VCS and Vena cava inferior (VCI), particularly at the tip of the VCS, may be associated with pulmonary vascular injury and dysfunction. This may occur due to increased pulmonary vascular resistance [10]. In the literature, studies examine VCS mean diameter values by transesophageal echocardiography and CT angiography [11, 12]. In addition, the mean diameter values of the VCS and VCI show significant differences between the sexes [12, 13].

Pulmonary hypertension (PH) becomes more pronounced in patients with COPD when airflow limitation is severe. This leads to the narrowing of the small pulmonary arteries due to hypoxia. Right heart catheterization is the most reliable method for diagnosing pulmonary vascular disease. Noninvasive methods bund as Doppler echocardiography can measure PA systolic pressure but often do not give precise results in patients with COPD due to overinflation of the lungs and imaging difficulties. Computed tomography (CT) scans are important for assessing the mean PA diameter, cross-sectional area of small pulmonary vessels, and PA ratio [14]. The CT study indicated that increased PA diameter may be associated with severe hypoxemia, inflammation, vascular resistance, and thromboembolic events [15].

Spirometry is the gold standard for diagnosing and staging the severity of COPD; however, as an effort-dependent test, its results can be influenced by the patient’s cooperation and the technician’s performance. Recently, the role of CT has been expanded both in clinical practice and in research to provide complementary structural information [3]. Lung volume measured by CT provides an objective volumetric assessment. Pulmonary function tests (PFT) include gas in the upper airways, whereas CT measurement can focus specifically on the lung parenchyma, potentially offering a different perspective on lung volumes. CT can accurately measure both overall and locally unilateral or bilateral lung volumes. Furthermore, CT is a reliable method for evaluating patients who may have difficulty cooperating with flow-based lung function tests [16]. 3D MDCT is a standard method for lung imaging and provides high spatial and temporal resolution, excellent contrast resolution for pulmonary structures, and the ability to acquire the complete three-dimensional (3D) volume of the thorax in a single breath-hold [17].

In health board procedures, the rate of disability is primarily determined according to spirometry. However, clinical evaluation can sometimes be challenging due to factors such as low compliance with the test. In this study, we aim to explore the following questions rather than proposing a replacement for the current gold standard:

• Is there a significant correlation between 3D-MDCT derived lung volumes and airflow limitation that could assist in the structural characterization of COPD?

• Can 3D-MDCT provide objective structural parameters that correlate with the GOLD severity groups, potentially serving as a supportive tool in clinical assessment?

• What are the results of measuring lung volume, left and right ventricular volume, pulmonary artery diameter, and vena cava diameters on 3D MDCT images in patients with COPD compared with pulmonary function tests, while specifically accounting for age and gender parameters? Based on these morphometric parameters, can specific structural changes be identified that correlate with disease progression?

Methods

Patient selection and study population

This retrospective cross-sectional study was conducted using the digital archive of Yalova State Hospital following approval from the Yalova University Ethics Committee (Protocol no: 2024/223). A total of 114 participants were included in the study. The COPD Group consisted of 58 patients (21 women and 37 men) diagnosed with stable Chronic Obstructive Pulmonary Disease according to the GOLD (2024) criteria. To prevent selection bias, all patients who applied to the chest diseases outpatient clinic during the study period and met the inclusion criteria were screened and included in the analysis. The Control Group consisted of 56 individuals (29 women and 27 men) with no known history of lung disease. Individuals in the control group were selected from those who did not have space-occupying pulmonary lesions such as pneumonia or lung cancer, and whose CT scans were performed for non-pulmonary medical reasons such as nodule screening, occupational health examinations, or differential diagnosis in the emergency department for non-respiratory complaints.

Evaluation of data and inclusion criteria

In the COPD group, to ensure clinical and functional correlation between the spirometric data and radiological morphometric findings, only patients who had undergone both thoracic MDCT imaging and PFT within a maximum interval of three months were included. For the COPD patients, demographic and clinical data including GOLD staging, FEV1, FVC, FEV1/FVC ratios, and COPD Assessment Test (CAT) and Modified Medical Research Council Dyspnea Scale (mMRC) scores were recorded. Exclusion criteria for both groups included the presence of active malignancy, a history of thoracic or upper abdominal surgery within the last three months, pregnancy, age under 18 years, and CT images that were technically inadequate (with significant artifacts) for analysis.

CT acquisition and standardization

All images were obtained using a 128-slice Multidetector CT scanner (GE Healthcare, United States). Due to the high sensitivity of volumetric measurements to the respiratory phase, all scans were performed under a standardized full inspiratory breath-hold protocol. The scan parameters were kept constant for all participants: slice thickness of 0.625 mm; field of view (FOV) of 220 mm; 120 kV, 74 mA, and 60 mAs; and a rotation time of 0.28 s. Images were reconstructed in DICOM format to ensure morphometric consistency across the sagittal, coronal, and axial planes.

Morphometric measurements and reproducibility

The DICOM data were uploaded to the 3D-Slicer (v5.6.2) platform. Right and left lung volumes (RLV, LLV) and heart ventricular volumes (RV, LV) were obtained through automatic segmentation using the “MONAIAuto3DSeg” module and verified using the “Segment Editor”. Vascular diameter measurements, including the Vena cava superior (VCS), Vena cava inferior (VCI) anteroposterior and transverse diameters at the renal vein level, and the Pulmonary Artery (PA) diameter at the level of the bifurcation, were performed on axial sections. To ensure measurement reliability (inter-observer variability), all segmentations and measurements were performed independently by two anatomists and subsequently confirmed by an experienced pulmonologist. Inter-observer consistency was verified using the Intraclass Correlation Coefficient (ICC), and a high level of agreement (ICC > 0.90) was ensured for all parameters.

RLV, LLV, and right heart ventricular volume (RV) and left heart ventricular volume (LV) were obtained by automatic segmentation with “MONAIAuto3DSeg” in the “Segmentation” module of the 3D-Slicer program, and the volumes of the three-dimensional images were statistically calculated with the help of the “Segment editor” and “Segment Quantification” module (Figs. 1 and 2).

Fig. 1.

Frontal view of lung segmentation. RLV volume (red), LLV volume (yellow)

Fig. 2.

Ventricular segmentation of the heart in the frontal view. A Frontal view of the surface model of the epicardial (myocardium and chamber) RV volume (green) and epicardial (myocardium and chamber) LV volume (blue), B Frontal view of RLV volume (red), LLV volume (yellow), epicardial (myocardium and chamber) RV volume (green), and epicardial (myocardium and chamber) LV volume (blue)

Morphometric evaluation was performed in accordance with the studies in the literatüre [12, 15, 18]; VCS diameter; its width at the point of junction with the vena azygos on the axial CT section (Fig. 3). VCI diameter; maximal anteroposterior and transverse diameters of the vena cava inferior at the level of the vena renalis on the axial CT section (Fig. 4). PA diameter; the diameter of the pulmonary artery at the level of the bifurcatio on the axial CT section (Fig. 5), and the evaluation of the values according to gender and age were planned.

Fig. 3.

The width at the point where the VCS joins with the azygos vein on the axial CT

Fig. 4.

A The maximal anteroposterior and B transverse diameters of VCI at the renal vein level on the axial CT image

Fig. 5.

The diameter of PA at the bifurcation level on the axial CT image

Sample size and power analysis

The required sample size was determined using G*Power software (v3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Germany). Based on an effect size of 0.60, a Type-I error rate of 0.05 (α), and a statistical power of 0.90 (1-β), a minimum total sample size of 98 participants was required to achieve statistical significance. This calculation ensures that the study is sufficiently powered to detect clinically meaningful differences between the study groups.

Statistical analysis

Statistical analyses were performed using SPSS software, version 20.0 (IBM Corp., Armonk, NY, USA). The distributional characteristics of continuous variables were evaluated using descriptive statistics and confirmed for normality through visual (histograms) and analytical methods.

Group comparisons

Continuous variables between the control and COPD groups were compared using the Independent Samples t-test. Variance homogeneity was assessed via Levene’s test; in cases where the homogeneity assumption was violated, the “equal variances not assumed” (Welch’s t-test) approach was adopted. Categorical variables were analyzed using the Pearson Chi-square test.

Subgroup analyses

To compare clinical measurements across COPD severity levels according to the GOLD classification, One-Way Analysis of Variance (ANOVA) was employed.

Correlation and regression

Linear relationships between quantitative measurements were evaluated using Pearson correlation analysis, with the correlation coefficient (r) used to interpret the direction and strength of the associations. Multiple Linear Regression Analysis was conducted to identify independent predictors (age, body mass index [BMI], and smoking history [pack-years]) impacting PA diameter and total lung volume. Model fit and explanatory power were assessed using the F-test and the coefficient of determination (R²), respectively.

For all analyses, a p-value < 0.05 was considered statistically significant, and findings were reported within 95% confidence intervals (CIs).

Results

Demographic Characteristics

A total of 114 participants were included (Control: n = 56; COPD: n = 58). There was no statistically significant difference between the groups in terms of age (Control: 58.34 ± 9.40 years; COPD: 59.81 ± 6.65 years; p = 0.336). Sex distribution did not differ significantly between groups (p = 0.068). The control group consisted of 58.0% women and 42.2% men, whereas the COPD group included 42.0% women and 57.8% men (Table 1).

Table 1.

Demographic characteristics of the study population

Variable	Control	COPD	Total	p-value
Age (mean)	58.34 ± 9.40	59.81 ± 6.6		0.336
Male. n (%)	27 (42%)	37 (57.8%)	64	0.068
Female. n (%)	29 (58%)	21 (42.2%)	50	0.068
Total	56 (49.1)	58 (50.9)

COPD Chronic Obstructive Pulmonary Disease

Comparison of thoracic CT measurements of control and COPD groups

Female participants

When thoracic CT measurements of control and COPD groups in females were compared. no statistically significant difference was found in terms of RV. LV. LLV. RLV. VCS. VCI transverse. and VCI AP (p > 0.05). PA diameter was found to be lower in the control group. and the difference was borderline significant (p = 0.050; Table 2).

Table 2.

Comparison of thoracic ct measurements by gender and group

		Group				p-value
		Control		COPD
		Mean	Std. Deviation	Mean	Std. Deviation
Female	RV(cm3)	124.194	27.798	125.470	29.014	0.876
	LV (cm3)	92.36	18.83	90.14	22.00	0.703
	LLV (cm3)	1882.58	601.50	1983.71	440.44	0.517
	RLV (cm3)	2190.589	668.698	2339.857	476.893	0.387
	VCS (mm)	11.248	2.108	12.799	4.101	0.087
	VCITRANSVERS (mm)	23.83	3.84	25.47	5.05	0.197
	VCIAP (mm)	11.28	3.93	12.59	3.55	0.231
	PA (mm)	21.25	3.76	23.59	4.41	0.050
Male	RV (cm3)	153.259	28.253	135.844	33.217	0.031
	LV (cm3)	118.42	28.06	105.85	29.08	0.088
	LLV (cm3)	2623.15	672.46	2926.62	577.27	0.057
	RLV (cm3)	2923.141	632.985	3355.838	563.349	0.005
	VCSmm	13.240	4.395	12.200	3.470	0.295
	VCITRANSVERS (mm)	24.96	4.93	25.89	5.81	0.502
	VCIAP (mm)	13.86	4.19	13.48	4.07	0.720
	PA (mm)	22.35	3.45	21.29	2.91	0.185

COPD Chronic Obstructive Pulmonary Disease, RLV Right lung volume, LLV Left lung volume, RV Right heart ventricular volume, LV Left heart ventricular volume, VCS Vena cava superior, VCI Vena cava inferior, VCIAP The maximal anteroposterior diameter of vena cava inferior, VCITRANSVERS The transvers diameter of vena cava inferior, PA Pulmonary artery, TLC Total lung capacity

**statistically significant p value (p < 0.001)

Table 2. Significant Structural Differences Between Control and COPD Groups by Sex.

Male participants

In males. the RV value was found to be significantly higher in the control group compared to the COPD group (p = 0.031).Right lung volume (RLV) was found to be significantly higher in the COPD group (p = 0.005). No significant difference was found in other parameters (p > 0.05; Table 2).

Correlation analyses

Female participants

Strong positive correlations were determined between pulmonary function tests (p < 0.01). Significant negative relationships were found between FEV1 and MMRC and CAT scores (p < 0.01). Very strong positive relationships exist between lung volumes (p < 0.01). A negative correlation was found between total lung volume and VCS (p < 0.05; Table 3).

Table 3.

Correlation analysis between pulmonary function tests. clinical scores. and thoracic ct measurements in female participants

Female		RV (cm3)	LV (cm3)	LLV (cm3)	RLV (cm3)	Total Lung	VCS (mm)	VCI TRANSVERS (mm)	VCIAP (mm)	FEV1	FEV1LT	FVC	FVCLT	FEV1FVC	FEF2575	MMRC	CAT
RV (cm3)	r	1	,824**	-,066	,085	-,377	,421**	,240	,127	-,101	-,111	-,136	-,105	-,116	-,071	,441*	,307
	p		,000	,650	,559	,092	,002	,093	,378	,664	,631	,558	,651	,615	,759	,045	,176
LV (cm3)	r	,824**	1	-,089	,078	-,308	,338*	,165	,023	-,049	-,108	-,057	-,113	-,031	-,055	,369	,206
	p	,000		,539	,589	,174	,016	,253	,876	,832	,641	,806	,625	,893	,814	,099	,369
LLV (cm3)	r	-,066	-,089	1	,947**	,966**	-,337*	,020	,212	-,137	-,144	-,179	-,203	-,026	-,118	-,210	,012
	p	,650	,539		,000	,000	,017	,891	,140	,555	,533	,437	,377	,912	,611	,361	,957
RLV (cm3)	r	,085	,078	,947**	1	,971**	-,195	,081	,201	-,146	-,162	-,160	-,172	-,159	-,196	-,118	,198
	p	,559	,589	,000		,000	,176	,578	,161	,528	,482	,490	,456	,491	,394	,612	,389
Total Lung	r	-,377	-,308	,966**	,971**	1	-,528*	-,289	-,110	-,146	-,159	-,175	-,193	-,098	-,164	-,167	,113
	p	,092	,174	,000	,000		,014	,204	,634	,528	,492	,449	,402	,672	,478	,469	,627
VCS (mm)	r	,421**	,338*	-,337*	-,195	-,528*	1	,388**	-,200	,325	,228	,338	,185	,180	,232	,085	,103
	p	,002	,016	,017	,176	,014		,005	,163	,151	,320	,134	,422	,434	,311	,715	,656
VCI TRANSVERS (MM)mm	r	,240	,165	,020	,081	-,289	,388**	1	,507**	,381	,147	,309	,007	,279	,238	-,166	-,370
	p	,093	,253	,891	,578	,204	,005		,000	,089	,524	,174	,977	,221	,299	,471	,098
VCIAP (mm)	r	,127	,023	,212	,201	-,110	-,200	,507**	1	,017	-,081	-,037	-,079	,009	-,103	,184	-,053
	p	,378	,876	,140	,161	,634	,163	,000		,940	,727	,874	,734	,970	,658	,425	,818
FEV1	r	-,101	-,049	-,137	-,146	-,146	,325	,381	,017	1	,834**	,925**	,579**	,860**	,886**	-,645**	-,571**
	p	,664	,832	,555	,528	,528	,151	,089	,940		,000	,000	,006	,000	,000	,002	,007
FEV1LT	r	-,111	-,108	-,144	-,162	-,159	,228	,147	-,081	,834**	1	,863**	,902**	,672**	,791**	-,453*	-,380
	p	,631	,641	,533	,482	,492	,320	,524	,727	,000		,000	,000	,001	,000	,039	,090
FVC	r	-,136	-,057	-,179	-,160	-,175	,338	,309	-,037	,925**	,863**	1	,732**	,664**	,739**	-,583**	-,461*
	p	,558	,806	,437	,490	,449	,134	,174	,874	,000	,000		,000	,001	,000	,005	,035
FVCLT	r	-,105	-,113	-,203	-,172	-,193	,185	,007	-,079	,579**	,902**	,732**	1	,340	,502*	-,247	-,121
	p	,651	,625	,377	,456	,402	,422	,977	,734	,006	,000	,000		,132	,020	,281	,601
FEV1FVC	r	-,116	-,031	-,026	-,159	-,098	,180	,279	,009	,860**	,672**	,664**	,340	1	,902**	-,506*	-,584**
	p	,615	,893	,912	,491	,672	,434	,221	,970	,000	,001	,001	,132		,000	,019	,005
FEF2575	r	-,071	-,055	-,118	-,196	-,164	,232	,238	-,103	,886**	,791**	,739**	,502*	,902**	1	-,606**	-,598**
	p	,759	,814	,611	,394	,478	,311	,299	,658	,000	,000	,000	,020	,000		,004	,004
MMRC	r	,441*	,369	-,210	-,118	-,167	,085	-,166	,184	-,645**	-,453*	-,583**	-,247	-,506*	-,606**	1	,667**
	p	,045	,099	,361	,612	,469	,715	,471	,425	,002	,039	,005	,281	,019	,004		,001
CAT	r	,307	,206	,012	,198	,113	,103	-,370	-,053	-,571**	-,380	-,461*	-,121	-,584**	-,598**	,667**	1
	p	,176	,369	,957	,389	,627	,656	,098	,818	,007	,090	,035	,601	,005	,004	,001

RLV Right lung volume, LLV- Left lung volume, RV Right heart ventricular volume, LV Left heart ventricular volume, VCS Vena cava superior, VCI Vena cava inferior, VCIAP the maximal anteroposterior diameter of vena cava inferior, VCITRANSVERS the transvers diameter of vena cava inferior, PA Pulmonary artery, TLC Total lung capacity, FEV1 Forced Expiratory volume in 1 s, FEV1LT Forced expiratory volume in 1 s (liters), FVC Forced vital capacity, FVCLT Forced vital capacity (liters), FEV1/FVC ratio of forced expiratory volume in 1 s to forced vital capacity, FEF25-75 Forced expiratory flow at 25–75% of FVC, CAT Copd assessment test

* Correlation is significant at the 0.05 level (2-tailed),  ** Correlation is significant at the 0.01 level (2-tailed)

*statistically significant p value (p < 0.05))

Male Participants

Significant negative relationships were found between the FEV1/FVC ratio and LLV, RLV and Total Lung volume (p < 0.05). A negative relationship was determined between total lung volume and VCS (p < 0.05; Table 4).

Table 4.

Correlation Analysis Between Pulmonary Function Tests. Clinical Scores. and Thoracic CT Measurements in Male Participants

Male		RV (cm3)	LV (cm3)	LLV (cm3)	RLV (cm3)	Total Lung	VCS (mm)	VCI TRANSVERS (mm)	VCIAP (mm)	FEV1	FEV1LT	FVC	FVCLT	FEV1FVC	FEF2575	mMRC	CAT
RV (cm3)	r	1	,643**	-,050	-,096	,095	,182	,143	-,035	,119	,176	,098	,156	,079	,131	-,047	-,054
	p		,000	,696	,452	,576	,151	,261	,783	,483	,296	,564	,355	,644	,439	,783	,749
LV (cm3)	r	,643**	1	-,011	-,070	-,017	,102	,230	-,118	,200	,242	,157	,200	,221	,201	-,167	,015
	p	,000		,930	,581	,918	,421	,068	,353	,236	,148	,355	,236	,189	,233	,323	,928
LLV (cm3)	r	-,050	-,011	1	,814**	,910**	-,181	,225	,438**	,159	,166	,294	,298	-,344*	,114	,191	,065
	p	,696	,930		,000	,000	,152	,074	,000	,347	,327	,078	,073	,037	,502	,258	,702
RLV (cm3)	r	-,096	-,070	,814**	1	,905**	-,207	,040	,252*	-,036	-,006	,064	,111	-,348*	-,034	,294	,189
	p	,452	,581	,000		,000	,100	,754	,045	,833	,971	,705	,513	,035	,841	,077	,262
Total Lung	r	,095	-,017	,910**	,905**	1	-,417*	,059	,173	,069	,089	,199	,226	-,381*	,045	,266	,139
	p	,576	,918	,000	,000		,010	,729	,305	,684	,601	,238	,178	,020	,792	,111	,411
VCS (mm)	r	,182	,102	-,181	-,207	-,417*	1	-,064	-,125	-,035	-,134	-,027	-,142	-,048	-,158	-,248	-,248
	p	,151	,421	,152	,100	,010		,616	,323	,838	,430	,875	,403	,779	,351	,138	,138
VCI TRANSVERS (MM)mm	r	,143	,230	,225	,040	,059	-,064	1	,358**	,187	,248	,248	,318	-,002	,075	,022	,012
	p	,261	,068	,074	,754	,729	,616		,004	,268	,139	,139	,056	,991	,661	,897	,942
VCIAP (mm)	r	-,035	-,118	,438**	,252*	,173	-,125	,358**	1	,141	,170	,196	,223	-,100	,143	,004	-,282
	p	,783	,353	,000	,045	,305	,323	,004		,406	,315	,244	,185	,557	,399	,983	,091
FEV1	r	,119	,200	,159	-,036	,069	-,035	,187	,141	1	,913**	,912**	,806**	,539**	,890**	-,445**	-,419**
	p	,483	,236	,347	,833	,684	,838	,268	,406		,000	,000	,000	,001	,000	,006	,010
FEV1LT	r	,176	,242	,166	-,006	,089	-,134	,248	,170	,913**	1	,842**	,929**	,514**	,862**	-,318	-,377*
	p	,296	,148	,327	,971	,601	,430	,139	,315	,000		,000	,000	,001	,000	,055	,021
FVC	r	,098	,157	,294	,064	,199	-,027	,248	,196	,912**	,842**	1	,880**	,217	,711**	-,411*	-,461**
	p	,564	,355	,078	,705	,238	,875	,139	,244	,000	,000		,000	,198	,000	,011	,004
FVCLT	r	,156	,200	,298	,111	,226	-,142	,318	,223	,806**	,929**	,880**	1	,203	,709**	-,284	-,426**
	p	,355	,236	,073	,513	,178	,403	,056	,185	,000	,000	,000		,228	,000	,088	,009
FEV1FVC	r	,079	,221	-,344*	-,348*	-,381*	-,048	-,002	-,100	,539**	,514**	,217	,203	1	,612**	-,285	-,060
	p	,644	,189	,037	,035	,020	,779	,991	,557	,001	,001	,198	,228		,000	,087	,723
FEF2575	r	,131	,201	,114	-,034	,045	-,158	,075	,143	,890**	,862**	,711**	,709**	,612**	1	-,320	-,307
	p	,439	,233	,502	,841	,792	,351	,661	,399	,000	,000	,000	,000	,000		,053	,065
mMRC	r	-,047	-,167	,191	,294	,266	-,248	,022	,004	-,445**	-,318	-,411*	-,284	-,285	-,320	1	,758**
	p	,783	,323	,258	,077	,111	,138	,897	,983	,006	,055	,011	,088	,087	,053		,000
CAT	r	-,054	,015	,065	,189	,139	-,248	,012	-,282	-,419**	-,377*	-,461**	-,426**	-,060	-,307	,758**	1
	p	,749	,928	,702	,262	,411	,138	,942	,091	,010	,021	,004	,009	,723	,065	,000

RLV Right lung volume, LLV Left lung volume, RV Right heart ventricular volume, LV Left heart ventricular volume, VCS Vena cava superior, VCI Vena cava inferior, VCIAP the maximal anteroposterior diameter of vena cava inferior, VCITRANSVERS the transvers diameter of vena cava inferior, PA Pulmonary artery, TLC Total lung capacity, FEV1 Forced Expiratory volume in 1s, FEV1LT Forced expiratory volume in 1 s (liters), FVC Forced vital capacity, FVCLT Forced vital capacity (liters), FEV1/FVC  ratio of forced expiratory volume in 1 s to forced vital capacity, FEF25-75 Forced expiratory flow at 25–75% of FVC, CAT Copd assessment test, mMRC Modified Medical Research Council Dyspnea Scalem

* Correlation is significant at the 0.05 level (2-tailed), ** Correlation is significant at the 0.01 level (2-tailed)

 *statistically significant p value (p < 0.05))

Analysis according to GOLD classification

Thoracic CT measurements in females and males did not show a significant difference according to GOLD stages (p > 0.05).

Multiple regression analyses

Regression analysis was conducted to determine the effect of BMI and smoking pack-years on PA. and the models established for both females and males were not found to be significant (p > 0.05). Regression analysis was conducted to determine the effect of BMI and smoking pack-years on Total Lung; while the regression model established for females was found to be significant. the model for males was non-significant. When the significance levels of the variables in the model for females were examined. it was observed that smoking pack-years significantly and positively affected total lung levels (p < 0.05; Table 5).

Table 5.

Multiple Regression Analysis Results for PA and Total Lung Volume

			Unstandardized Coefficients		Standardized Coefficients	t	p
			B	Std. Error	Beta
Female	Total Lung F = 4.410 p = 0.018 R2 = 0.418	Constant	4214.712	1483.042		2.842	0.011
		Age	8.856	19.852	0.084	0.446	0.661
		BMI	-56.488	36.619	-0.294	-1.543	0.141
		Smoking (pack)	26.824	10.212	0.509	2.627	0.018
Male	Total Lung F = 1.934 p = 0.143 R2 = 0.150	Constant	6234.875	1888.899		3.301	0.002
		Age	-3.337	32.489	-0.018	-0.103	0.919
		BMI	-15.096	33.216	-0.076	-0.454	0.652
		Smoking (pack)	15.046	6.989	0.371	2.153	0.039

BMI Body mass index

Discussion

In this study, we used three-dimensional multi-detector computed tomography (3D-MDCT) to quantitatively assess cardiopulmonary structural characteristics in COPD patients and to investigate their relationship with functional disease severity, comparing the results with control group data. The main finding of this study was that lung volume parameters, particularly right lung volume, were significantly increased in male COPD patients compared to the control group and showed a significant correlation with airflow limitation. Specifically, the FEV₁/FVC ratio showed significant negative correlations with right lung volume, left lung volume, and total lung volume, indicating that progressive airflow obstruction is associated with structural lung enlargement consistent with hyperinflation.

Hyperinflation is one of the most important pathophysiological features of COPD and develops as a result of air trapping, loss of elastic recoil, and impaired lung mechanics. Inadequate lung emptying during expiration leads to an increase in end-expiratory lung volume and thoracic expansion. CT-based studies have demonstrated that increased lung volume is associated with decreased FEV₁ and FEV₁/FVC ratio and reflects disease severity [19, 20]. Our findings also support this mechanism and show that CT-based volumetric measurements reflect structural remodelling in COPD.

Multiple cytokines play a role in chronic airway inflammatory diseases such as COPD. Cytokines play a key role in the pathogenesis of COPD patients who smoke and do not have airflow limitation. Exposure to cigarette smoke causes loss of lung elasticity and air trapping through chronic inflammation, protease activation, and alveolar destruction. This process results in increased lung volume and hyperinflation [21, 22]. Our study also demonstrated that smoking exposure is a significant determinant of total lung volume. The significant relationship between pack-years and lung volume indicates that smoking is one of the fundamental determinants of structural changes in COPD.

Another effect of hyperinflation is that the lungs occupy more space in the thoracic cavity, mechanically restricting the heart’s diastolic filling and potentially causing volumetric reduction in the cardiac chambers. Barr and colleagues demonstrated that hyperinflation in COPD patients can cause a significant reduction in heart size. This mechanism, defined in the literature as “pseudomicrocardia” [23, 24], was found to be consistent with an important finding of our study, namely that the right ventricular volume (RV) was significantly lower in male COPD patients compared to the control group, supporting the effect of hyperinflation on cardiac morphology.

An increase in COPD severity has been associated with a reduction in cardiac dimensions. In this mechanism, hyperinflation plays a role, leading to cardiac size reduction and cardiac dysfunction [25]. Hyperinflation may also cause compression of mediastinal vascular structures by increasing intrathoracic pressure. This situation may reduce venous return and lead to a decrease in vascular calibre [26]. Similarly, in our study, the negative correlation found between total lung volume and superior vena cava calibre may be an indicator of mediastinal compression. Our morphometric findings support this physiological mechanism at a structural level.

It is known that obesity causes increased circulating volume and cardiac workload, resulting in adaptive enlargement of the cardiac chambers [27]. Similarly, cardiac magnetic resonance imaging study of 33.801 individuals of European descent found that genetic predisposition to higher BMI was significantly associated with larger RV end-diastolic [28]. Our study also found a positive correlation between BMI and ventricular volumes. This indicates that cardiopulmonary interaction in COPD is not solely dependent on lung pathology but is also influenced by systemic factors. The fact that BMI and PA diameter were also found to be higher in female COPD patients supports this interaction.

Some evidence indicates that low exercise capacity and muscle weakness in lean individuals. along with oxidative stress and systemic inflammation in obese individuals. May contribute to lung dysfunction [29–31].

The gold standard diagnostic tool for COPD is spirometry [32]. Medical board assessments (e.g., disability or impairment ratings) are generally based on spirometry results. When the spirometry test is not performed appropriately for evaluation, lung volume measurements can be used as a complementary method in cases of technician and patient incompatibility or when the patient is unable to perform the test.

The GOLD classification is primarily based on symptom burden and risk of exacerbation [19]. The positive correlation between GOLD stages and CAT and mMRC supports its consistency with clinical staging. As it is a clinical classification, it may not directly reflect structural changes. In our study, no significant differences were found in morphometric parameters according to GOLD stages. The fact that structural changes do not progress in direct parallel with disease stages may also explain this situation.

Although regional parameters such as emphysema and airway wall thickness were not evaluated in our study, global lung volume measurements are a comprehensive indicator of structural remodelling in COPD [20]. When spirometry testing is not performed appropriately for evaluation, volumetric measurements obtained with 3D-MDCT can be used as a complementary method to spirometry in cases of technician-patient incompatibility or when the patient is unable to perform the test.

One of the most important strengths of this study is that the structural features of the thorax in individuals with COPD were analysed in detail on high-resolution 3D-MDCT images using 3D Slicer software. which is open source and allows objective measurements. Unlike GOLD-based classifications in the literature. which generally focus on functional assessments. this study brings a quantitative approach to the morphometric dimension of the disease and reveals the relationship between structural data and pulmonary function tests. In addition. The fact that measurements were performed by a multidisciplinary team consisting of pulmonologists and anatomists increased the reliability of the data in terms of anatomical accuracy and clinical validity.

Limitations

Retrospective design, single-centre structure, and the lack of emphysema analysis are among the limitations of the study. Finally, although CT imaging was performed using a standard inspiratory protocol, individual differences in inspiratory effort may have affected volumetric measurements.

Despite these limitations, the strengths of the study include the use of an age-matched control group, the provision of objective evidence that volumetric analysis obtained from 3D-MDCT reflects structural cardiopulmonary remodelling associated with COPD, and the support for the role of 3D-MDCT as a complementary imaging tool in the structural assessment of this disease.

Conclusions

This study demonstrates that CT-based lung volumetric measurements are associated with airflow limitation in COPD and reflect cardiopulmonary structural changes. These findings support the notion that 3D-MDCT can be used as a complementary method for structural assessment in COPD. Although spirometry is the primary method for diagnosing COPD, it has limitations such as patient non-compliance, exercise dependence, and the inability to perform it during disease periods when the risk of respiratory transmission increases, such as during the Coronavirus-19 pandemic. Therefore, CT-based volumetric measurements can provide significant contributions as a complementary method, particularly in the objective assessment of structural changes and the demonstration of cardiopulmonary interactions.

In conclusion, this study demonstrates that lung volume increase in COPD is associated with airway obstruction, that smoking exposure is an important determinant of these structural changes, and that hyperinflation can exert mechanical effects on cardiac and vascular structures. These findings support the notion that 3D-MDCT may be a clinically useful and objective imaging method for evaluating structural remodelling in COPD.

Abbreviations

BMI

Body mass index

CAT

COPD Assessment Test

COPD

Chronic Obstructive Pulmonary Disease

GOLD

Global Initiative for Chronic Obstructive Lung Disease

FEV1

forced expiratory volume in 1 s

FEV1/FVC

Ratio of forced expiratory volume in 1 s to forced vital capacity

FEF25-75

Forced expiratory flow at 25–75% of FVC

FVC

expiratory vital capacity

ICS

inhaled corticosteroid

LABA

long-acting beta-agonist

LAMA

long-acting muscarinic antagonist

LLV

Left lung volume

LV

Left heart ventricular volume

3D MDCT

Three-dimensional multidetector computed tomography

mMRC

Modified Medical Research Council

PA

Pulmonary artery

RLV

Right lung volume

RV

Right heart ventricular volumes

TLC

Total lung capacity

VCS

vena cava superior. VCI: vena cava inferior

VCIAP

The maximal anteroposterior diameter of vena cava inferior

VCITRANSVERS

The transvers diameter of vena cava inferior

Authors’ contributions

NKK: Protocol/project development. NKK GB: Data collection data analysis. NKK EE GB: Manuscript writing/editing. EE GB: Figures and tables preparation. All authors: Approval of the final version of the manuscript.

Funding

No funds. grants. or other support were received.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The ethics review board approved from The Ethıcs Commıttee Of Yalova Unıversıty with the protocol number 2024/223. Our study adhered to the Declaration of Helsinki. Informed consent was obtained from all patients for being included in the study.

Consent for publication

All participants gave permission for publication.

Competing interests

The authors declare no competing interests.