Search Results (278)

Background: Restrictive lung disease (RLD) is a potential complication in type 2 diabetes (T2D), but its relationship with insulin resistance and liver-related metabolic dysfunction remains unclear. This study evaluated the association between lung function and metabolic markers in T2D and retrospectively assessed whether metabolic improvements from dietary intervention were accompanied by changes in lung function. Methods: This cross-sectional analysis included 184 individuals (101 with T2D, 33 with prediabetes, and 50 glucose-tolerant individuals). Lung function parameters—vital capacity (VC), total lung capacity by plethysmography (TLC-B), and diffusion capacity for carbon monoxide (TL_CO)—were assessed alongside metabolic markers including HOMA2-IR, fatty liver index (FLI), NAFLD score, and Fibrosis-4 index (FIB-4). In a subset of 54 T2D participants, lung function was reassessed after six months following either a fasting-mimicking diet (FMD, n = 14), Mediterranean diet (n = 13), or no dietary intervention (n = 27). Results: T2D participants had significantly lower VC and TLC-B compared to glucose-tolerant and prediabetic individuals, with 18–21% falling below clinical thresholds for RLD. Lung volumes were negatively correlated with HOMA2-IR, FLI, NAFLD score, and FIB-4 across the cohort and within the T2D group. Although the FMD intervention led to significant improvements in HOMA2-IR and FLI, no corresponding changes in lung function were observed over the six-month period. Conclusions: Restrictive lung impairment in T2D is associated with insulin resistance and markers of liver steatosis and fibrosis. While short-term dietary interventions can improve metabolic parameters, their effect on lung function may require a longer duration or additional interventions and targeted follow-up. These findings highlight the relevance of pulmonary assessment in individuals with metabolic dysfunction. Full article

Introduction: Radiomics is the extraction of non-invasive and reproducible quantitative imaging features, which may yield mineable information for clinical practice implementation. Quantification of lung function through radiomics could play a role in the management of patients with pulmonary lesions. The aim of this study is to test the capability of radiomic features to predict pulmonary function parameters, focusing on the diffusing capacity of lungs to carbon monoxide (DL_CO). Methods: Retrospective data were retrieved from electronical medical records of patients treated with Stereotactic Body Radiation Therapy (SBRT) at a single institution. Inclusion criteria were as follows: (1) SBRT treatment performed for primary early-stage non-small cell lung cancer (ES-NSCLC) or oligometastatic lung nodules, (2) availability of simulation four-dimensional computed tomography (4DCT) scan, (3) baseline spirometry data availability, (4) availability of baseline clinical data, and (5) written informed consent for the anonymized use of data. The gross tumor volume (GTV) was segmented on 4DCT reconstructed phases representing the moment of maximum inhalation and maximum exhalation (Phase 0 and Phase 50, respectively), and radiomic features were extracted from the lung parenchyma subtracting the lesion/s. An iterative algorithm was clustered based on correlation, while keeping only those most associated with baseline and post-treatment DL_CO. Three models were built to predict DL_CO abnormality: the clinical model—containing clinical information; the radiomic model—containing the radiomic score; the clinical-radiomic model—containing clinical information and the radiomic score. For the models just described, the following were constructed: Model 1 based on the features in Phase 0; Model 2 based on the features in Phase 50; Model 3 based on the difference between the two phases. The AUC was used to compare their performances. Results: A total of 98 patients met the inclusion criteria. The Charlson Comorbidity Index (CCI) scored as the clinical variable most associated with baseline DL_CO (p = 0.014), while the most associated features were mainly texture features and similar among the two phases. Clinical-radiomic models were the best at predicting both baseline and post-treatment abnormal DL_CO. In particular, the performances for the three clinical-radiomic models at predicting baseline abnormal DL_CO were AUC₁ = 0.72, AUC₂ = 0.72, and AUC₃ = 0.75, for Model 1, Model 2, and Model 3, respectively. Regarding the prediction of post-treatment abnormal DL_CO, the performances of the three clinical-radiomic models were AUC₁ = 0.91, AUC₂ = 0.91, and AUC₃ = 0.95, for Model 1, Model 2, and Model 3, respectively. Conclusions: This study demonstrates that radiomic features extracted from healthy lung parenchyma on a 4DCT scan are associated with baseline pulmonary function parameters, showing that radiomics can add a layer of information in surrogate models for lung function assessment. Preliminary results suggest the potential applicability of these models for predicting post-SBRT lung function, warranting validation in larger, prospective cohorts. Full article

Background: Patients with mild coronavirus disease 2019 (COVID-19) are usually managed in an outpatient setting. Pulmonary functions in this setting have not been explored. This study aimed to determine abnormal lung functions in COVID-19 patients under a home isolation program. Methods: A prospective study was conducted in asymptomatic or mild COVID-19 patients with normal chest radiographs at two medical centers in Thailand. Spirometry data, including forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), peak expiratory flow (PEF), forced expiratory flow at 25–75% of FVC (FEF25–75), and bronchodilator responsiveness (BDR), were collected. Spirometry was performed after disease resolution at baseline and 3-month follow-up. Abnormal lung functions were classified into airway obstruction, restrictive defect, mixed defect, small airway disease, and BDR. Results: A total of 250 patients (58% female) were included. The mean age was 37.4 ± 15.2 years. Asymptomatic patients accounted for 7.6%. Common symptoms included fever (55.6%) and cough (60.0%). Abnormal lung functions were observed in 28.4% of patients, with a restrictive lung pattern (14.4%), airway obstruction (4.8%), mixed defect (0.4%), small airway disease (8.4%), and BDR (2.8%). Significant changes from baseline were noted in FVC (1.21%), FEV₁/FVC (−1.51%predicted), PEF (0.06%), and FEF_25–75 (−2.76%). Logistic regression analysis indicated that a higher body mass index was associated with a lower risk of abnormal lung function. Conclusions: Ventilatory defects were observed in one-third of patients with mild COVID-19 who did not require hospitalization, mainly presenting as restrictive patterns and small airway disease. Even mild cases may have residual pulmonary impairment, warranting further long-term studies. Full article

Introduction: Computed tomography-guided biopsies (CTGB) are essential in diagnosing various conditions, particularly in respiratory medicine, with lung cancer being a primary focus. A significant complication associated with CTGB is pneumothorax, which can occur in up to 26% of cases. At Northumbria Healthcare NHS Foundation Trust, a large interventional service collaborates closely with radiologists and respiratory physicians. This study aims to evaluate the incidence of pneumothorax following CTGB. Methods: A retrospective service review was conducted on all lung parenchymal CTGBs performed between April 2011 and July 2023, with approval from the local information governance. Demographic data and clinical outcomes were analyzed using descriptive statistics. Continuous variables are presented as medians with interquartile ranges (IQR), while categorical variables are reported as frequencies and percentages. Results: A total of 1492 CT-guided lung biopsies were analyzed. The median age of patients was 72 years (IQR 10.5), and 50.9% were male. Pneumothorax occurred in 23.8% (n = 355) of cases. Of these, 159 (44.8%) were detected on post-biopsy CT scans. The average number of pleural passes was 1.8 (range 1–4). Among those with pneumothorax, 53.6% had radiologically evident emphysema. The median forced expiratory volume in 1 s (FEV1) was 1.97 L (IQR 1.04). Sixty-seven percent (n = 234) of patients had no pleural contact, and the median lesion size was 26 mm (IQR 24). Seventy-two percent (n = 255) of lesions with pneumothoraces were less than 3 cm deep. Forty-four percent of biopsies were performed using 18 French gauge tru-cut needles. Of the 355 pneumothoraces, 89% (n = 315) were managed conservatively, with 42 requiring pleural intervention (41 small-bore 12 Fr intercostal chest drains and one pleural vent). Symptoms were initially present in 40 cases, and two cases developed symptoms up to 7 days post-procedure. Conclusions: The incidence of pneumothorax is consistent with expected rates, with more occurrences observed in biopsies of smaller lesions lacking pleural contact, lesions with surrounding emphysema, and cases requiring multiple pleural passes. FEV1 does not appear to influence the risk of pneumothorax. Conservative management is generally effective, without significant complications. Full article

Objectives: Deep learning-based artificial intelligence (AI) tools have been gradually used to detect and segment pulmonary nodules in clinical practice. This study aimed to assess the diagnostic performance of quantitative measures derived from a commercially available AI software for predicting the invasiveness of pulmonary adenocarcinomas that manifested as pure ground-glass nodules (pGGNs) on low-dose CT (LDCT) in lung cancer screening. Methods: A total of 388 pGGNs were consecutively enrolled and divided into a training cohort (198 from center 1 between February 2019 and April 2022), testing cohort (99 from center 1 between April 2022 and March 2023), and external validation cohort (91 from centers 2 and 3 between January 2021 and August 2023). The automatically extracted quantitative measures included diameter, volume, attenuation, and mass. The diameter was also manually measured by radiologists. The agreement of diameter between AI and radiologists was evaluated by intra-class correlation coefficient (ICC) and Bland–Altman method. The diagnostic performance was evaluated by the area under curve (AUC) of receiver operating characteristic curve. Results: The ICCs of diameter between AI and radiologists were from 0.972 to 0.981 and Bland–Altman biases were from −1.9% to −2.3%. The mass showed the highest AUCs of 0.915 (0.867–0.950), 0.913 (0.840–0.960), and 0.893 (0.810–0.948) in the training, testing, and external validation cohorts, which were higher than those of diameters of radiologists and AI, volume, and attenuation (all p < 0.05). Conclusions: The automated measurement of pGGNs diameter using the AI software demonstrated comparable accuracy to that of radiologists on LDCT images. Among the quantitative measures of diameter, volume, attenuation, and mass, mass was the most optimal predictor of invasiveness in pulmonary adenocarcinomas on LDCT, which might be used to assist clinical decision of pGGNs during lung cancer screening. Full article

Background/Objectives: Spread through air spaces (STAS) is defined as the spread of tumor cells into the parenchymal alveolar space beyond the margins of the main tumor, and it is associated with worse clinical outcomes in resected lung adenocarcinoma. This study aimed to evaluate the preoperative computed tomography (CT) findings of primary lung adenocarcinoma in surgically resected T1 cases and to compare CT findings with and without STAS. Methods: A total of 145 patients were included in this study. The following factors were evaluated on CT images: nodule type (pure ground-glass nodule [GGN], part-solid nodule, or solid nodule), margin (smooth or irregular), the presence of lobulation, spicula, cavity, calcification, central low attenuation, peripheral opacity (well-defined or ill-defined), air bronchogram, satellite lesions, pleural retraction, pulmonary emphysema, and interstitial pneumonia; CT values (maximum, minimum, and mean); volume (tumor and solid component); and diameter (tumor and solid component). CT criteria were compared between the presence and absence of STAS. Results: Lobulation and central low attenuation were significantly more frequent in patients with STAS (p < 0.05). The mean CT value, and the volume, rate, and diameter of the solid component were significantly larger in cases with STAS (p < 0.05). A multiple logistic regression analysis identified central low attenuation as an indicator of the presence of STAS (p < 0.001; odds ratio, 3.993; 95% confidence interval, 1.993–8.001). Conclusions: Quantitative and qualitative analyses are useful for differentiating between the presence and absence of STAS. Full article

Background: Post-COVID syndrome is characterized by persistent symptoms such as dyspnea, fatigue, and reduced exercise tolerance, which can significantly impair pulmonary function and quality of life. Pulmonary rehabilitation has been proposed as a potential intervention to address these challenges. This study aimed to evaluate the effects of a pulmonary rehabilitation program on pulmonary function, inflammatory markers, and quality of life in patients with post-COVID syndrome. Methods: A prospective, interventional, non-randomized clinical trial was conducted involving 77 participants (mean age 59.4 ± 11.6 years; 39% female) who attended a post-COVID care clinic in Rzeszów, Poland. The intervention included supervised respiratory and aerobic exercises, muscle strengthening, and body balance therapy, alongside motivational breathing therapy. Pulmonary function (spirometry, plethysmography, gasometry), inflammatory markers (CRP, WBC, D-dimer), and quality of life (WHOQOL-BREF) were assessed pre- and post-intervention. Results: Significant improvements were observed in pulmonary function parameters post-rehabilitation, including increases in forced vital capacity (FVC, 75% to 78.4%, p < 0.001), forced expiratory volume in one second (FEV1, 78.2% to 80.5%, p < 0.001), and total lung capacity (TLC, 67.3% to 71%, p < 0.001). The diffusing capacity for carbon monoxide (DLCO) improved by 6.2% (p < 0.001). Arterial oxygen pressure (PaO₂) increased by 7.6 mmHg (p < 0.001). Markers of inflammation, including CRP (8.9 to 1.3 mg/dL, p < 0.001) and d-dimer (1722.2 to 203.4 ng/mL, p < 0.001), showed significant reductions. Quality of life improved across physical, psychological, and environmental domains. Sex, BMI, and baseline inflammatory markers were significant determinants of rehabilitation outcomes. Conclusions: A pulmonary rehabilitation program significantly improved pulmonary function, reduced systemic inflammation, and enhanced quality of life in individuals with post-COVID syndrome. The findings highlight the importance of tailored rehabilitation in mitigating long-term post-COVID sequelae. Future research should explore the long-term effects of rehabilitation and its applicability in diverse populations. Full article

Pre-metastatic niche (PMN) formation is a critical step in metastatic progression. However, the biological effects of subtherapeutic doses of ionizing radiation (SDIRs) following radiotherapy on this process remain unclear. Using a 4T1 breast cancer mouse model, we investigated the effects of SDIRs (3 × 0.3 Gy) on lung PMN development and metastasis upon SDIR exposure on days 8–10 post-tumor injection, followed by mastectomy and analyzed on day 24. SDIRs significantly increased the total metastatic volume (TMV) in lungs, suggesting an accelerated PMN formation. Mechanistically, the SDIR acted as an early catalyst for niche priming, upregulating Bv8 expression, enhancing neutrophil recruitment, and increasing MMP9, S100A8, and Il6 production in the PMN by day 11. Moreover, SDIR drives metastasis through distinct mechanisms. Proteomic analysis revealed SDIR-driven metabolic reprogramming, with a shift away from fatty acid metabolism toward glycolysis and lipid accumulation within the PMN. This shift contributes to extracellular matrix (ECM) remodeling, immune modulation, and the upregulation of adhesion-related pathways, shaping a microenvironment that accelerates metastatic outgrowth. By reprogramming the pre-metastatic lung, the SDIR highlights the need to integrate organ-specific radiation exposure into metastasis models. Metabolic and immune-stromal pathways emerge as potential therapeutic targets, underscoring the importance of refining radiotherapy strategies to mitigate unintended pro-metastatic effects. Full article

Background: The associations between physical activity (PA) and all-cause mortality remain under-investigated among individuals with impaired lung function. Methods: With 201,596 participants from the UK Biobank cohort, baseline pre-bronchodilation lung function tests and a modified International Physical Activity Questionnaire were used to assess lung function status (normal, restricted, obstructed) and PA attributes (volume, intensity, duration). All-cause mortality was determined through linkage to the National Health Services Register. Cox proportional hazard regression was applied to characterize the associations between PA metrics and all-cause mortality among people with different lung function statuses. Dose–response relationships between PA metrics and all-cause mortality risks were examined using restricted cubic splines (number of knots = 4). Results: Over a 11.81-year median follow-up, 5.24% of participants died. All-cause mortality risk declined with increasing total PA volume, plateauing at 1800 MET-min/week without further reduction in individuals with and without impaired lung function. Similar trends were observed for PA intensity and duration, with both factors demonstrating reduced mortality risk that plateaued after reaching a specific threshold. Notably, 24.1% (95% CI: 16.7%, 30.8%) and 43.1% (95% CI: 36.1%, 49.7%) lower mortality risk was observed among individuals with and without impaired lung function for PA with 1201–1800 MET-min/wk. Conclusions: PA was associated with a decreased risk of all-cause mortality among individuals with and without impaired lung function, suggesting that those with impaired lung function might also benefit from PA. Full article

Background/Objectives: Lung cancer is the leading cause of cancer-related mortality worldwide. Accurate radiotherapy (RT) planning alongside chemotherapy and immunotherapy is critical for improving treatment outcomes for inoperable non-metastatic cases. Conventional computed tomography (CT)-based planning may be inadequate for accurately identifying tumor margins and the location of nodal disease. We investigated whether ¹⁸F-labeled fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET-CT) imaging can assist in target volume delineation for primary, nodal, and metastatic disease in the RT planning and overall therapeutic planning of patients. Methods: In this single-center, prospective study, we recruited 34 patients with histologically confirmed locally advanced non-small-cell lung carcinoma (NSCLC). All patients underwent ¹⁸F-FDG PET-CT-based RT simulation. Two sequential RT plans were created by the same radiation oncologist: one based on CT alone and the other PET-CT. Planning target volumes (PTVs) and PET-CT-guided adjustments were analyzed to assess their impact. Standardized protocols for immobilization, imaging, target delineation, and dose prescription were applied. Results: A total of 34 patients (31 males and 3 females) were recruited in the study. ¹⁸F-FDG PET-CT detected distant metastases in 7/34 (20.6%) patients, altering the overall therapeutic plan in 4/34 (11.8%) and allowing radical RT in 3 of them who had oligometastatic disease (8.8%). It modified RT planning in 26/34 (76.5%) patients and clarified malignancy in atelectatic areas. Nodal involvement was identified in 3/34 patients (8.8%) and excluded in 3/34 cases, avoiding unnecessary nodal irradiation. Additional involved nodes were revealed in 12/34 (35.3%) patients, requiring dose escalation. Overall, changes to the tumor PTV were made in 23/30 (76.6%) and to the nodal PTV in 19/30 (63.3%) cases (p < 0.0001). Primary tumor and nodal PTVs increased in 20/34 (66.7%) and 13/34 (43.3%), respectively. Conclusions: ¹⁸F-FDG PET-CT significantly improves RT planning by more precisely defining tumor and nodal volumes, identifying undetected lesions, and guiding dose adaptation. Larger long-term studies are required to confirm potential locoregional control and survival improvements. Full article

Background/Objectives: This study aims to distinguish radiological differences between primary idiopathic Usual Interstitial Pneumonia (UIP) and secondary UIP patterns Methods: This retrospective study included patients with HRCT findings consistent with a UIP pattern. Final diagnoses were established via multidisciplinary discussion and classified as primary UIP/IPF or secondary UIP, following the 2022 ATS/ERS/JRS/ALAT guidelines. An expert thoracic radiologist (>10 years of experience), blinded to clinical data, reviewed the earliest available HRCT assessing key imaging features: honeycombing (micro-, macro- or exuberant), fibrosis distribution (symmetry, anterior-upper lobe sign, etc.), ground-glass opacities (GGO), dilatation of esophagus. Additionally, AI software AVIEW Build 1.1.46.28-win Coreline (©Coreline Soft Co., Ltd. All Rights Reserved). performed lung texture analysis, quantifying total lung volume and radiological patterns. Statistical analysis was performed to reveal results. Results: Among 53 cases, 31 were classified as IPF and 22 as secondary UIP cases. The expert radiologist achieved a diagnostic sensitivity of 82.9%, specificity of 889%, with a positive predictive value of 93.5%—in distinguishing between primary and secondary UIP. Primary UIP cases exhibited typical hallmark radiological features, including uniform honeycombing with cranio-caudal distribution (90.3%). Reticulations contributed significantly to the fibrotic texture, maintaining a consistent cranio-caudal gradient and axial symmetry (84.8%). Secondary UIP displayed more significant radiological heterogeneity, including patchy fibrosis with irregular GGO distribution (84.5% versus 53.33%); other findings—such as exuberant honeycombing, four corner sign and wedge-shaped fibrosis—were mainly observed in secondary pattern with respective percentages of 31.8%, 9% and 49%. Conclusions: Experienced thoracic radiologists, leveraging hallmark imaging features, play a critical role in improving diagnostic accuracy between primary and secondary UIP patterns. Full article

Background/Objectives: Background: COVID-19 pneumonia leads to alveolar collapse and parenchymal infiltration, contributing to lung volume loss and respiratory failure. Objectives: To quantify lung volume loss and recovery in moderate and severe cases, explore mechanisms of respiratory failure, and correlate imaging findings with histopathological changes. Methods: We retrospectively analyzed 43 patients with moderate/severe COVID-19. CT scans from the acute phase and at 3–12 months follow-ups were processed using 3D Slicer. Infiltrated (−650 to −200 HU) and collapsed (−200 to 0 HU) lung regions were quantified and summed to define the affected lung volume. CT severity scores and total affected percentage were compared with lung volume loss. Histopathological analysis of three autopsy cases was used to support imaging findings. Results: Median acute phase lung volume loss was 30.6%. Patients with <25%, 25–50%, and >50% affected lung had median losses of 6.5%, 35.7%, and 39.8%, respectively. Volume loss strongly correlated with affected lung percentage (r = 0.72, p < 0.000001) and moderately with CT severity score (r = 0.52, p < 0.01). Histology confirmed alveolar area reductions over 65% in infiltrated regions. Conclusions: Lung volume loss reflects both imaging severity and histopathological damage, offering insights into the mechanisms of COVID-19 respiratory failure. CT volumetry is a valuable tool for assessing parenchymal injury and monitoring recovery, and 3D Slicer provides an accessible platform for implementing this approach. Full article

Background/Objectives: Lung-protective ventilation (LPV) reduces postoperative pulmonary complications (PPCs) in obese patients. While the roles of low tidal volume and positive end-expiratory pressure (PEEP) in LPV have been established in patients with healthy lungs, the protective effect of alveolar recruitment strategies (ARSs) remains a subject of debate. This study aims to evaluate the benefit of ARSs in patients with low-to-moderate risk according to the Assess Respiratory Risk in Surgical Patients in Catalonia (ARISCAT) score undergoing gynecologic cancer surgery with LPV and low tidal volume intraoperatively. Methods: A total of 88 obese patients were evaluated in this study. They were divided into two groups as the non-ARS group (non-ARS) and the ARS group (ARS). Intraoperative hemodynamics, blood gas analyses, respiratory mechanics, mechanical ventilator parameters, and postoperative outcomes were compared in these obese patients. Results: A total of 40 obese patients undergoing major gynecological cancer surgery were included in this study. Although the non-ARS group presented with higher weight (p < 0.05), body mass indexes were similar to the ARS group. Intraoperative blood gas analysis revealed higher end-tidal carbon dioxide (etCO₂) levels in the non-ARS group during the T2 and T3 time intervals (p < 0.05). In the ARS group, peak inspiratory pressure (PIP) at T3 was lower, while drive pressures at T1 and T2 and dynamic compliance at T3 were higher (p < 0.05). Radiologic atelectasis scores were higher in the non-ARS group, indicating more atelectatic lung images (p < 0.05). PPC rates were similar across both groups. Conclusions: Although the ARS demonstrated positive effects on lung mechanics and radiologic atelectasis scores in major open gynecologic cancer surgeries, it did not effectively reduce postoperative pulmonary complications. Full article

Background/Objectives: The accurate diagnosis and classification of brain tumors are critical for appropriate treatment planning and patient management. We evaluated the effectiveness of perfusion in differentiating glial tumors from metastases using dynamic susceptibility-weighted contrast enhanced perfusion MRI (DSC-MRI) Methods: A total of 95 consecutive patients with pathological diagnoses of brain tumors who underwent perfusion MRI between July 2021 and March 2023 were retrospectively recruited. Conventional and perfusion MRI were evaluated, and tumoral and peritumoral relative cerebral blood volume (rCBV) values were measured. Mann–Whitney U and Kruskal–Wallis tests were performed for non-parametric comparisons of continuous data. The optimal cut-off value of rCBV in differentiating tumor types was evaluated with the receiver operating characteristic (ROC) curve analysis. Results: Tumoral rCBV (p < 0.001) and peritumoral rCBV values (p = 0.001) were significantly higher in glial tumors than metastases. Further subgroup analyses showed that tumoral and peritumoral rCBV values of glial tumors were higher than those of non-small-cell lung cancers (p < 0.001 and p = 0.003, respectively) and those of breast cancer (p = 0.311 and p = 0.053, respectively) in discriminating high-grade glial tumors and metastases. ROC analyses showed that area under the curve values for tumoral and peritumoral rCBV were 0.816 and 0.725, respectively, for the optimal cut-off points 1.339 and 1.238 (87.5% and 58.33% sensitivity; 73.85% and 90.77% specificity, respectively). Multivariate analysis showed that increased tumoral rCBV and peritumoral rCBV values were independent risk factors for glial tumor occurrence. Conclusions: DSC-MRI is an effective method to differentiate glial tumors and metastases. Higher rCBV values may serve as a determinant for the diagnosis of glial tumors and metastatic brain tumors. Full article

Objective: The air content within the lungs directly influences the dielectric properties of lung tissue; however, previous studies were conducted under ex vivo conditions and without quantitatively controlling air volume. This study aims to develop an improved model using in vivo measurements to accurately characterize the dielectric properties of rabbit lung tissue across various tidal volumes. Methods: In this study, six sets of different tidal volumes (30, 40, 50, 60, 70, 80 mL) were set in the frequency band of 100 MHz~1 GHz to analyze the trend of the dielectric properties, and the dielectric parameters were systematically constructed under the conditions of different tidal volumes. Results: It was found that the conductivity and permittivity of rabbit lung tissue showed a decreasing trend with increasing tidal volume in the measuring frequency band. The traditional Cole–Cole model has limitations in simulating the dielectric properties of in vivo lung tissues. Therefore, by refining and optimizing the model, this study successfully reduced the average error between the measured data and the model fitting to less than 5%. Conclusions: This study lays the groundwork for investigating the relationship between total air volume within the lungs and their dielectric properties in vivo. Full article