CT Volumetry and Pulmonary Function After Lung Resection

CT Volumetric Analysis as a Predictor: Multiple studies have examined computed tomography (CT) lung volumetry as a tool to predict pulmonary function after lung resection. CT volumetry involves measuring lung or lobar volumes from imaging (often via semi-automated software) and using those volumes to estimate post-operative pulmonary function test (PFT) values. In general, CT-based predictions correlate well with actual PFT outcomes. For example, Bolliger et al. (2002) showed that quantitative CT was more accurate than simple anatomical segment counts in predicting post-lobectomy FEV₁ and DLCO (Computed tomography volumetric analysis for predicting postoperative lung function for segmentectomy - PMC) More recent work by Bae et al. (2022) in 175 segmentectomy patients found that CT volumetry and traditional segment-count methods produced nearly identical predicted post-op values, both closely matching observed PFTs (Computed tomography volumetric analysis for predicting postoperative lung function for segmentectomy - PMC) This suggests modern CT volumetry can reliably estimate functional loss. Moreover, advanced quantitative CT measures can track post-surgery compensation: one study found that increases in CT-defined functional lung volume after lobectomy correlated significantly with improvements in postoperative FEV₁ (R ≈ 0.6) (Computed tomography-defined functional lung volume after segmentectomy versus lobectomy | European Journal of Cardio-Thoracic Surgery | Oxford Academic) In a 2024 analysis, Liu et al. noted that quantitative CT provided “significant value in predicting postoperative pulmonary function preservation and compensatory changes” up to 2 years after surgery (Quantitative computed tomography assessment of pulmonary function and compensation after lobectomy and segmentectomy in lung cancer patients - PMC) Overall, current literature supports CT volumetric analysis as a useful predictor of post-lung resection function, often comparable or superior to older methods (e.g. segment counting) (Computed tomography volumetric analysis for predicting postoperative lung function for segmentectomy - PMC) (Computed tomography volumetric analysis for predicting postoperative lung function for segmentectomy - PMC)

Lobar Segmentation Tools: The accuracy of CT predictions has been enhanced by semi-automated lobe segmentation software (e.g. Coreline Aview or similar). Such tools can separate each lung lobe and calculate volumes rapidly, with manual adjustment as needed for precision. These platforms also quantify parenchymal characteristics (like emphysema burden) that pure anatomy-based methods overlook. Automated CT lung volume measurements show excellent correlation with lung capacity measured on PFTs – even in diseased lungs. For instance, in patients with pulmonary fibrosis, an automated CT-derived total lung volume correlated r ≈ 0.92 with total lung capacity from PFTs (Visual and Automated CT Measurements of Lung Volume Loss in Idiopathic Pulmonary Fibrosis - PubMed) underscoring the reliability of software-based volumetry. Research teams in Korea and elsewhere have incorporated semi-automated 3D CT segmentation into pre-surgical planning; one study calculated low-attenuation volume (LAV) percentages on CT to assess emphysema in lobectomy candidates, recognizing that emphysematous changes could influence a patient’s functional recovery (Postoperative pulmonary function changes according to the resected lobe: a 1-year follow-up study of lobectomized patients - PMC) In practice, tools like Aview allow radiologists to obtain lobar volumes (and even emphysema index by measuring the percent of lung below -950 HU ( Quantitative computed tomography assessment of pulmonary function and compensation after lobectomy and segmentectomy in lung cancer patients - PMC) pre- and post-operatively, facilitating detailed comparison with pulmonary function. These technologies have made it easier to study how anatomical volume changes translate to physiological changes.

Factors Leading to Discrepancies Between CT Volume and PFT

Despite generally good correlation, certain factors can cause CT-measured lung volumes to diverge from PFT results in post-surgery patients. Key contributors to such inconsistencies include underlying emphysema, post-operative scarring/fibrosis, and uneven functional distribution of the lung:

• Emphysema and COPD: Patients with significant emphysema (often due to smoking/COPD) may have a larger anatomical lung volume on CT that does not equate to functional capacity. Emphysematous lung tissue is hyper-inflated but offers poor gas exchange and airflow. Therefore, removing a diseased portion of lung (lobectomy) in these patients can yield less functional loss than volume loss – or even a paradoxical improvement in FEV₁. This phenomenon is often called the “volume reduction effect,” analogous to lung volume reduction surgery. Ueda et al. reported that “lung lobectomy sometimes results in an unexpected improvement of the remaining lung function in some patients with moderate-to-severe emphysema” (Assessment of volume reduction effect after lung lobectomy for cancer ) By resecting a poorly functioning, hyperinflated lobe, the remaining lung can expand and work more efficiently (relieving airflow obstruction and dead-space ventilation (Assessment of volume reduction effect after lung lobectomy for cancer ) . Indeed, multiple studies have observed minimal loss – or even improvement – of FEV₁ after lobectomy in COPD patients (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) For example, Matsumoto et al. found that patients with mild-to-severe COPD had better preserved FEV₁ one year after lobectomy than patients with normal lungs, often exceeding the predicted values (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) In essence, heavy emphysema skews the volume–function relationship: CT might show a large resected volume, but function drops proportionally less because that volume was low-quality lung.

• Post-Operative Scarring and Fibrosis: Fibrotic changes after surgery can also create discrepancies. Scar tissue (from the surgical resection line, radiation therapy, or post-op complications) can stiffen lung tissue or pleura, reducing compliance and functional capacity more than would be expected from volume metrics alone. For instance, if the remaining lung develops fibrosis or extensive pleural adhesions, the CT-measured volume might appear relatively preserved while the patient’s vital capacity and diffusion capacity decline due to restricted expansion. Over years, gradual fibrotic remodeling at the surgical margin or in surrounding parenchyma could limit inflation of the residual lobes. (Notably, in contrast to emphysema, fibrosis tends to decrease both CT volume and PFT measures together. One imaging study in idiopathic pulmonary fibrosis showed CT lung volume and FVC were closely linked despite fibrosis (Visual and Automated CT Measurements of Lung Volume Loss in Idiopathic Pulmonary Fibrosis - PubMed) This suggests that when scarring significantly reduces volume, CT and PFT will both reflect the loss. The more subtle issue is when moderate scarring impairs mechanics without large volume loss.) In summary, post-lobectomy fibrosis or pleural thickening may lead to a greater-than-expected drop in functional metrics or slower recovery of function, creating a volume-function mismatch.

• Uneven Regional Function (Ventilation/Perfusion Mismatch): CT volumetry is an anatomic measurement and assumes each unit of lung volume contributes equally to function. In reality, the functional contribution of a given lobe can vary. If a resected lobe was poorly ventilated or perfused preoperatively (due to tumor obstruction or disease), then its removal will have less impact on PFT than its volume share implies. Conversely, if the remaining lung has areas of low perfusion or chronic disease, the actual post-op function may underperform relative to the volume of lung left. Some authors have noted that changes in the ventilation–perfusion relationship after surgery modulate functional outcomes (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) For example, resection might improve overall V/Q matching by eliminating a high-dead-space region, boosting efficiency more than volume alone would predict. On the other hand, if part of the residual lung has radiotherapy changes or chronic bronchitis, it might not fully utilize its volume. These functional nuances (which CT densitometry or perfusion scans can sometimes identify) help explain cases where volumetric predictions and spirometric results diverge.

In clinical research, factors like the ones above are examined to refine predictive models. Many groups incorporate emphysema indexes from CT or perfusion scintigraphy alongside volume measurements to improve PFT predictions (Assessment of volume reduction effect after lung lobectomy for cancer ) (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) Ultimately, understanding why a given patient’s CT volume and actual lung function don’t align can help personalize their post-op management or prognosis.

Impact of Smoking History and COPD on Recovery

Smoking history and pre-existing chronic obstructive pulmonary disease (COPD) are critical modifiers of post-lung resection outcomes. Prior COPD often indicates the presence of emphysema and small airway disease, which, as noted, can lead to smaller-than-expected losses in function after resection. Several studies have demonstrated that patients with COPD experience better preservation of lung function post-lobectomy than non-COPD patients (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) Baldi et al. (cited by Matsumoto) reported that even moderate COPD patients had higher long-term FEV₁ retention after lobectomy compared to those without COPD (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) The beneficial effect is attributed to the volume reduction phenomenon – essentially, the surgery removes the worst-functioning parts of the lung, allowing healthier portions to compensate.

However, there are two sides to smoking’s impact. While smokers with severe COPD may paradoxically fare well in terms of relative FEV₁ loss, smoking also predisposes patients to complications and may limit recovery in other ways. For instance, smokers are at higher risk of post-op atelectasis, bronchial healing issues, and pneumonia, which can temporarily worsen PFTs. Continued smoking after surgery is associated with slower recovery of lung function and can accelerate the decline of the remaining lung. In most studies, patients are strongly advised to quit smoking before surgery; in one lobectomy series, all current smokers stopped at least 4 weeks pre-op and remained abstinent post-op (Postoperative pulmonary function changes according to the resected lobe: a 1-year follow-up study of lobectomized patients - PMC) underlining how smoking can confound PFT results if not ceased. Over the long term, the natural progression of COPD in smokers is an important confounder. Matsumoto et al. observed that beyond one year after lobectomy, any gradual decline in lung function could be partly due to aging and ongoing COPD progression rather than the surgery itself (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease)

In summary, a history of heavy smoking/COPD often means: (1) the immediate post-surgical functional loss may be less than expected (or even an improvement) because the resected lung was not contributing effectively (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) and (2) these patients still require close monitoring, as their long-term recovery can be affected by their limited pulmonary reserve and any continued tobacco exposure. When comparing CT volume predictions to PFT outcomes, smoking/COPD is a key variable to account for, as it skews the volume-function relationship significantly.

Longitudinal Outcomes Over 5 Years

Most pulmonary function recovery after lobectomy or segmentectomy occurs within the first 6–12 months, but how do lung function and CT metrics hold up in the long term (5 years)? Longitudinal studies are somewhat scarce (due to patient follow-up challenges), but available data indicate a gradual decline in function over years that mirrors normal aging or disease progression.

A large 5-year follow-up study by Kobayashi et al. (2017) looked at lung cancer surgery survivors beyond 5 years, comparing lobectomy, segmentectomy, and wedge resections (Long-term pulmonary function after surgery for lung cancer - PubMed) (Long-term pulmonary function after surgery for lung cancer - PubMed) They found that at 1 year post-op, lobectomy patients on average had FEV₁ about 91% of their preoperative value, whereas segmentectomy patients were ~94% and wedge (partial) resection ~98% (Long-term pulmonary function after surgery for lung cancer - PubMed) This confirms that initial loss of function is highest for lobectomy. By 5 years post-op, lobectomy patients’ FEV₁ further declined to ~86% of baseline, segmentectomy to ~91%, and wedge to ~94% (Long-term pulmonary function after surgery for lung cancer - PubMed) Notably, the additional decline from year 1 to year 5 was not significantly different among the groups (Long-term pulmonary function after surgery for lung cancer - PubMed) – roughly a 5% drop in FEV₁ for each, which is similar to age-related decline or mild COPD progression. In other words, after the first-year recovery/compensation, all patients tended to experience a slow decline in lung function at a comparable rate. Lobectomy still had a greater net loss at 5 years (about 14% decline from pre-op) versus sublobar resections (~6–9% decline), but that gap was established early on (Long-term pulmonary function after surgery for lung cancer - PubMed) (Long-term pulmonary function after surgery for lung cancer - PubMed)

From a CT volumetry standpoint, long-term changes include compensatory hypertrophy of remaining lung and possible development of fibrosis or emphysema in the interim. One study noted that compensatory expansion of residual lung can continue and even involve growth of new alveolar septa in the first year or two post-lobectomy (Computed tomography-defined functional lung volume after segmentectomy versus lobectomy | European Journal of Cardio-Thoracic Surgery | Oxford Academic) (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) After that, any deterioration in CT-measured volume or density is likely due to other factors (new lung disease, smoking damage, or aging). Five-year serial CT data are limited, but it’s reasonable to expect that if a patient’s lung function declines between year 1 and 5, a corresponding decrease in well-aerated lung volume or increase in fibrotic changes might be seen on CT.

In summary, at 5 years after lung resection, most patients maintain the majority of their preoperative lung function (often 85–95% of baseline, depending on resection extent) (Long-term pulmonary function after surgery for lung cancer - PubMed) (Long-term pulmonary function after surgery for lung cancer - PubMed) Lobectomy patients have a larger initial drop but then plateau, and their subsequent rate of decline parallels that of other patients (implying the surgery itself doesn’t cause ongoing deterioration after the initial period). This long-term perspective is reassuring, but it also highlights the importance of monitoring – especially in smokers or those with COPD, whose underlying disease may progress during those years.

Proposed Research Plan: Retrospective CT Volumetry vs PFT Study

Study Objective: To retrospectively evaluate the correlation between CT volumetric measurements of lung lobes and postoperative pulmonary function in patients who underwent anatomical lung resection (lobectomy or segmentectomy). The study will identify factors (emphysema, scarring, etc.) that explain any discrepancies between CT-predicted lung function and actual PFT results after surgery.

Design: Retrospective cohort study at a single tertiary center. We will include adult patients who had lobectomy or segmentectomy for lung cancer (primary or metastatic) between Year X and Year Y, with preoperative CT scans and postoperative PFTs available. Wedge resections will be excluded to focus on anatomical resections. All patients should have baseline (pre-op) PFTs and a follow-up PFT approximately 6–12 months after surgery (once recovery has plateaued). This timeframe captures the post-op functional outcome while minimizing influence of cancer recurrence or adjuvant therapies.

CT Volumetric Data Collection: Preoperative chest CT scans will be retrieved. Each scan will be processed using Coreline Aview (a semi-automated lung analytics software) to perform lobe segmentation. The software will calculate volumes of each lung lobe. Trained analysts (e.g. radiologists) will review and manually adjust the lobe segmentations for accuracy, especially in areas where tumors or atelectasis might affect automatic borders. Key CT-derived variables will include: total lung volume, volume of the resected lobe/segment (from the pre-op scan), volume of the remaining lung (all other lobes), and an emphysema index (percentage of low-attenuation lung, to quantify COPD severity) (Quantitative computed tomography assessment of pulmonary function and compensation after lobectomy and segmentectomy in lung cancer patients - PMC) If postoperative CT scans (e.g. 6-month or 1-year follow-up CTs) are available for some patients, we will also segment those to observe how the remaining lung has expanded or changed, though the primary analysis will use preoperative volumes for predicting post-op function.

Pulmonary Function Data: From pulmonary function lab records, we will collect the relevant PFT results: forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV₁) – both preoperative and postoperative. DLCO (diffusion capacity) will also be noted if available, as it is an important metric for gas exchange. The primary functional outcome will be the postoperative FEV₁ (absolute value and % of the patient’s preoperative value). We will calculate the predicted postoperative FEV₁ for each patient using CT volumetry: for example, Predicted FEV₁ = Pre-op FEV₁ × (Volume of remaining lung / Total lung volume) (Computed tomography-defined functional lung volume after segmentectomy versus lobectomy | European Journal of Cardio-Thoracic Surgery | Oxford Academic) (Computed tomography-defined functional lung volume after segmentectomy versus lobectomy | European Journal of Cardio-Thoracic Surgery | Oxford Academic) This essentially assumes loss of function proportional to volume resected, adjusted for any emphysema if we choose (we might refine the formula by subtracting emphysematous volume). We will then compare this CT-based prediction to the actual measured post-op FEV₁.

Methodology & Analysis Plan:

• Descriptive Analysis: Summarize patient characteristics (age, sex, smoking history in pack-years, diagnosis), surgical details (lobectomy vs segmentectomy, which lobe resected, VATS vs open), and baseline lung status (pre-op FEV₁%, presence of COPD defined by GOLD criteria, etc.). We will stratify patients by groups (lobectomy vs segmentectomy, COPD vs non-COPD) for preliminary comparisons.

• Agreement Between CT Prediction and Actual PFT: Use scatter plots and correlation coefficients (Pearson’s r) to assess the relationship between CT-predicted FEV₁ and observed FEV₁. Ideally, compute Lin’s concordance correlation coefficient (CCC) or intraclass correlation (ICC) to evaluate how well the two methods agree (Robust imaging approach for precise prediction of postoperative lung function in lung cancer patients prior to curative operation - PMC) We will also generate a Bland-Altman plot to visualize bias (the mean difference between predicted and actual FEV₁) and limits of agreement. A small mean difference would indicate no systematic over- or underestimation. For instance, if we find that CT prediction tends to overestimate FEV₁ in certain patients, we’ll investigate why.

• Error Analysis: Calculate the prediction error for each patient (e.g. ΔFEV₁ = Actual post-op FEV₁ – CT predicted FEV₁ or as a percentage of predicted). This will be the key outcome to correlate with potential factors. We expect some patients to have positive ΔFEV₁ (actual higher than predicted, possibly those with emphysema/air-trapping in resected lobe) and others negative (actual lower than predicted, possibly those who developed complications or have less compensatory reserve).

• Statistical Comparison: Use a paired t-test (or Wilcoxon signed-rank if non-normal) to see if the mean predicted FEV₁ differs significantly from mean actual FEV₁. We anticipate overall no huge bias (as prior studies showed CT volumetry is fairly accurate on average (Computed tomography volumetric analysis for predicting postoperative lung function for segmentectomy - PMC) , but this confirms the model’s baseline performance.

• Multivariable Analysis: Perform regression to identify predictors of discrepancy between CT volume and PFT. For example, we can use multiple linear regression with dependent variable = Actual FEV₁ / Predicted FEV₁ (or the ΔFEV₁) for each patient. Independent variables (covariates) will include:

  • Smoking history: pack-years (continuous) or ever-vs-never smoker.
  • Presence of COPD: a binary variable (yes if diagnosed or if pre-op FEV₁/FVC <70%). We expect COPD to be associated with higher actual/predicted ratio (due to volume reduction effect) (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease)
  • Emphysema on CT: quantitative % low attenuation (LAV% < -950 HU) (Postoperative pulmonary function changes according to the resected lobe: a 1-year follow-up study of lobectomized patients - PMC) This gives a continuous measure of emphysema severity. We hypothesize higher emphysema % will predict actual FEV₁ being better than volumetric prediction (since diseased lung contributed less than its volume).
  • Resection type: lobectomy vs segmentectomy (and possibly which lobe was removed). Different lobes contribute different fractions of function; e.g., losing a lower lobe might have a different impact than an upper lobe. We’ll include indicator variables for lobectomy (yes/no) and maybe for specific lobes (to catch any outliers like right middle lobe, which is small).
  • Age and Sex: older age might limit compensatory hyperinflation, and females vs males might have differences in lung size vs function ratios.
  • Time since surgery: if postoperative PFT timing varies (say 3 months vs 12 months), include the interval as a covariate – lung function could improve between early and later follow-ups.
  • Post-op therapy or complications: e.g., an indicator if patient had postoperative pulmonary complications (pneumonia, prolonged air leak) or required adjuvant radiation (which could scar the lung). These factors could cause actual function to be worse than predicted. We will include any major complication as a binary covariate.

  Using this model, we aim to see which factors significantly influence the ratio of actual to predicted function. For instance, we might find that emphysema index is an independent predictor of a higher actual FEV₁ than predicted (consistent with the idea that CT volumetry overestimates loss in emphysema patients) (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) Or we might find that patients with no COPD but who had post-op scarring have actual/predicted <1.0, indicating underperformance.

• Subgroup Analyses: We will consider stratifying the analysis by surgical extent. For lobectomy patients, does the model behave differently than for segmentectomy patients? Prior research suggests segmentectomy spares a bit more function, but also has less room for a volume reduction effect since less lung is removed (Computed tomography-defined functional lung volume after segmentectomy versus lobectomy | European Journal of Cardio-Thoracic Surgery | Oxford Academic) (Computed tomography-defined functional lung volume after segmentectomy versus lobectomy | European Journal of Cardio-Thoracic Surgery | Oxford Academic) We’ll check if our findings (e.g., the impact of emphysema) hold in both groups. Another subgroup of interest is heavy smokers (COPD GOLD II+) vs non-smokers – comparing their Bland-Altman bias could vividly show the systematic difference in prediction accuracy between these groups.

• Pulmonary Diffusion: If DLCO data is available, we will do a parallel analysis for DLCO (predicted vs actual). CT volumetry per se doesn’t predict gas exchange well, but emphysema or interstitial changes would affect DLCO. We might find, for example, that patients with high emphysema have improved FEV₁ (due to volume reduction) but still a DLCO decline consistent with loss of alveolar surface – highlighting that volume reduction surgery helps airflow more than diffusion.

Anticipated Outcomes: We expect to confirm that CT volumetric predictions correlate strongly with actual postoperative PFT (with an overall correlation coefficient perhaps >0.8 and no significant bias, in line with prior studies (Computed tomography volumetric analysis for predicting postoperative lung function for segmentectomy - PMC) . Importantly, we anticipate systematic deviations in certain subgroups:

• In patients with significant emphysema (high LAV% or clinical COPD), the CT-based method will tend to under-predict actual FEV₁ (i.e., these patients do better than anatomic volume alone would suggest) (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) We’ll quantify how emphysema severity correlates with this “functional gain” beyond predicted.
• Patients with little emphysema but who had other issues (fibrosis, complications) may show over-prediction by CT (actual function worse than expected from volume). For instance, extensive scarring could be flagged if many outliers are found in patients who had postoperative radiation.
• We also expect differences by lobe resected. If sample size allows, we might observe that, say, right lower lobectomy patients have a slightly different pattern than right upper, due to different compensatory expansion of remaining lobes (Thieme E-Books & E-Journals -) (Thieme E-Books & E-Journals -) Previous data suggests lower lobectomy might cause more initial loss but also more compensatory diaphragm elevation, etc., equalizing by 1 year (Thieme E-Books & E-Journals -) (Thieme E-Books & E-Journals -)

Significance: This study will contribute a nuanced understanding of why CT volumetric and PFT assessments might diverge in post-lung resection patients. By leveraging automated lobe segmentation (with manual refinement) and detailed patient data, we can identify confounding factors – like smoking history, COPD, and post-op changes – that should be accounted for when using CT for functional prediction. The findings could help refine predictive models (e.g. adding an “emphysema correction” to CT volumetry) and inform surgeons and pulmonologists in preoperative risk assessments. Ultimately, this research can improve personalized prognostication: for example, flagging a COPD patient who might tolerate lobectomy better than expected, or conversely a low-emphysema patient who might need closer follow-up due to risk of functional loss from scarring.

Potential Limitations: Being retrospective, the study depends on available data – PFT timing and CT quality may vary. We will mitigate this by standardized timing as much as possible and excluding suboptimal CT scans. Another challenge is that post-op CT scans are not routine; our primary analysis uses pre-op CT to predict PFT, but lacking post-op imaging for all means we infer compensation rather than directly observe it. Nonetheless, by focusing on the delta between predicted and actual PFT, we capture the net effect of all compensation or loss. We will also be cautious interpreting causal relationships given this is an observational study; identified associations (e.g. smoking history and better FEV₁ preservation) will be hypothesis-generating.

In conclusion, the study will retrospectively marry imaging and physiology data to explore their relationship in lung resection patients. By addressing key confounders like emphysema and scarring, it aims to explain inconsistencies between CT volumes and pulmonary function and improve the accuracy of outcome predictions (Assessment of volume reduction effect after lung lobectomy for cancer ) (Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy - Matsumoto - Journal of Thoracic Disease) The knowledge gained could be validated in future prospective trials and eventually guide more tailored surgical decisions and postoperative care for patients with compromised lungs.