Predicting Postoperative Lung Function Following Lung Cancer Resection: A Systematic Review and Meta-analysis

Clinical Factors Affecting Discrepancy Between Predicted and Long-term Actual Lung Function Following Surgery

PURPOSE

Lung cancer surgery outcomes depend heavily on preoperative pulmonary reserve, with forced expiratory volume in 1 second (FEV1) being a critical preoperative evaluation factor. Our study investigates the discrepancies between predicted and long-term actual postoperative lung function, focusing on clinical factors affecting these outcomes.

METHODS

This retrospective observational study encompassed lung cancer patients who underwent preoperative lung perfusion SPECT/CT between 2015 and 2021. We evaluated preoperative and postoperative pulmonary function tests, considering factors such as surgery type, resected volume, and patient history including tuberculosis. Predicted postoperative lung function was calculated using SPECT/CT imaging.

RESULTS

From 216 patients (men:women, 150:66; age, 67.9 ± 8.7 years), predicted postoperative FEV1% (ppoFEV1%) showed significant correlation with actual postoperative FEV1% (r = 0.667; P < 0.001). Paired t test revealed that ppoFEV1% was significantly lower compared with actual postoperative FEV1% (P < 0.001). The study identified video-assisted thoracic surgery (VATS) (odds ratio [OR], 3.90; 95% confidence interval [CI], 1.98-7.69; P < 0.001) and higher percentage of resected volume (OR per 1% increase, 1.05; 95% CI, 1.01-1.09; P = 0.014) as significant predictors of postsurgical lung function improvement. Conversely, for the decline in lung function postsurgery, significant predictors included lower percentage of resected lung volume (OR per 1% increase, 0.92; 95% CI, 0.86-0.98; P = 0.011), higher preoperative FEV1% (OR, 1.03; 95% CI, 1.01-1.07; P = 0.009), and the presence of tuberculosis (OR, 5.19; 95% CI, 1.48-18.15; P = 0.010). Additionally, in a subgroup of patients with borderline lung function, VATS was related with improvement.

CONCLUSIONS

Our findings demonstrate that in more than half of the patients, actual postsurgical lung function exceeded predicted values, particularly following VATS and with higher volume of lung resection. It also identifies lower resected lung volume, higher preoperative FEV1%, and tuberculosis as factors associated with a postsurgical decline in lung function. The study underscores the need for precise preoperative lung function assessment and tailored postoperative management, with particular attention to patients with relevant clinical factors. Future research should focus on validation of clinical factors and exploring tailored approaches to lung cancer surgery and recovery.

Predicting Postoperative Lung Function in Patients with Lung Cancer Using Imaging Biomarkers

There have been previous studies conducted to predict postoperative lung function with pulmonary function tests (PFTs). Computing tomography (CT) can quantitatively measure small airway walls' thickness, lung volume, pulmonary vessel volume, and emphysema area, which reflect the severity of respiratory diseases. These measurements are considered imaging biomarkers. This study aimed to predict postoperative lung function with imaging biomarkers. A retrospective analysis of 79 patients with lung cancer who had undergone lung surgery was completed. Postoperative lung function measured by forced expiratory volume in one second (FEV1) was defined as an outcome. Preoperative clinico-pathological parameters and imaging biomarkers representing airway walls' thickness, severity of emphysema, total lung volume, and pulmonary vessel volume were measured quantitatively in chest CT by an automated segmentation software, AVIEW COPD. Pi1 was defined as the first percentile along the histogram of lung attenuation that represents the degree of emphysema. Wafw was defined as the airway thickness, which was calculated by the full-width at half-maximum method. Logistic and linear regressions were used to assess these variables. If the actual postoperative FEV1 was higher than the postoperative FEV1 projected by a formula, the group was considered to be preserved. Among the 79 patients, 16 of the patients were grouped as a non-preserved group, and 63 of them were grouped as a preserved group. The patients in the preserved FEV1 group had a higher vessel volume than the non-preserved group. Pi1 and Wafw were independent predictors of postoperative lung function. Imaging biomarkers can be considered significant variables in predicting postoperative lung function in patients with lung cancer.

Predicting postoperative lung function using ventilation SPECT/CT in patients with lung cancer

Background

Single-photon emission computed tomography/computed tomography (SPECT/CT) has the advantage of assessing regional lung function. We aimed to investigate the potential of ventilation (SPECT/CT) for predicting postoperative lung function in patients with lung cancer.

Methods

This retrospective study included consecutive patients with lung cancer who underwent lobectomy, preoperative ventilation, and perfusion SPECT/CT between January 2020 and December 2021. The percentage of predicted postoperative forced expiratory volume in 1 s (ppoFEV1%) and the percentage of predicted postoperative diffusion capacity of the lung for carbon monoxide (ppoDLCO%) were calculated from the % counts of each scan based on anatomical segments for lobar function. Correlation tests were performed between the predicted lung function values and actual ppoFEV1% and ppoDLCO%.

Results

Among the 47 patients, 29 men and 18 women aged 67.5±9.6 years were included. Moreover, 46 ventilation and 41 perfusion SPECT/CT scans were obtained. The pulmonary function on ventilation SPECT/CT strongly correlated with perfusion SPECT/CT (correlation coefficient r=0.939 for ppoFEV1%, P<0.001; r=0.938 for ppoDLCO%, P<0.001). Both ppoFEV1% and ppoDLCO% values obtained from the ventilation and perfusion scans strongly correlated with postoperative FEV1% and DLCO% (correlation coefficient, r=0.774 and r=0.768 for ventilation; r=0.795 and r=0.751 for perfusion, each P<0.001).

Conclusions

Ventilation SPECT/CT was comparable to perfusion SPECT/CT in predicting postoperative lung function.

Cohort study investigating evolution and factors associated with dyspnoea after anatomic lung resection

Background

Dyspnoea is common following surgical resection for non-small cell lung cancer (NSCLC). The effects range from reduced quality of life to impact on adjuvant therapy outcomes. Currently, dyspnoea beyond the immediate postoperative phase and risk factors are not well characterised. We hope to assess the evolution of patient-reported dyspnoea after anatomic lung resection and associated factors.

Methods

Single-centre cohort study with analysis on data collected longitudinally of 131 patients undergoing anatomic lung resections for NSCLC between September 2014 and December 2018. The European Organization for Research and Treatment Lung Cancer-specific Quality of Life Questionnaire Dyspnoea Scale was used to measure dyspnoea before and after surgery. Multivariable regression analysis was used to identify factors associated with clinically meaningful perioperative changes in dyspnoea at 6-12 months.

Results

Mean Dyspnoea Scale scores preoperatively and 6-12 months after resection were 12.6 (standard deviation 17.4) and 17.9 (standard deviation 20.5), respectively. Of all patients 31% experienced a clinically meaningful increase in dyspnoea, defined as >10 points between Dyspnoea Scale scores preoperatively and at 6-12 months. Comparatively, 71% of patients without preoperative symptoms of dyspnoea developed a clinically meaningful increase of dyspnoea postoperatively. After adjusting the analysis for baseline factors and preoperative Dyspnoea Scale score, female sex remained the only patient factor associated with increased postoperative dyspnoea at 6-12 months after surgery (P=0.046). A total of 34% of patients reported increased dyspnoea after lobectomies and 9% after segmentectomies (P=0.014). Segmentectomy (as opposed to larger resections) was the only surgical factor associated with lower risk of increased dyspnoea (P=0.057).

Conclusions

A clinically meaningful increase in dyspnoea is frequent after lung resection. Postoperative evolution of dyspnoea is non-predictable using objective baseline factors highlighting the importance of patient reported symptoms and involvement in clinical consultation.

The role of the diaphragm in prediction of respiratory function in the immediate postoperative period in lung cancer patients using a machine learning model

BACKGROUND

The prediction of postoperative respiratory function is necessary in identifying patients that are at greater risk of complications. There are not enough studies on the effect of the diaphragm on postoperative respiratory function prediction in lung cancer surgical patients. The objective of this study is to estimate the precision of machine learning methods in the prediction of respiratory function in the immediate postoperative period and how diaphragm function contributes to that prediction.

MATERIALS AND METHODS

Our prospective study included 79 patients who underwent lung cancer surgery. Diaphragm function was estimated by its mobility measured both ultrasonographically and radiographically and by noninvasive muscle strength tests. We present a new machine learning multilayer regression metamodel, which predicts FEV1 for each patient based on preoperative measurements.

RESULTS

The proposed regression models are specifically trained to predict FEV1 in the immediate postoperative period and were proved to be highly accurate (mean absolute error in the range from 8 to 11%). Predictive models based on resected segments give two to three times less precise results. Measured FEV1 was 44.68% ± 14.07%, 50.95% ± 15.80%, and 58.0%1 ± 14.78%, and predicted postoperative (ppo) FEV1 was 43.85% ± 8.80%, 50.62% ± 9.28%, and 57.85% ± 10.58% on the first, fourth, and seventh day, respectively. By interpreting the obtained model, the diaphragm contributes to ppoFEV1 13.62% on the first day, 10.52% on the fourth, and 9.06% on the seventh day.

CONCLUSION

The machine learning metamodel gives more accurate predictions of postoperative lung function than traditional calculations. The diaphragm plays a notable role in the postoperative FEV1 prediction.

Systematic metareview of prediction studies demonstrates stable trends in bias and low PROBAST inter-rater agreement

OBJECTIVES

To (1) explore trends of risk of bias (ROB) in prediction research over time following key methodological publications, using the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and (2) assess the inter-rater agreement of the PROBAST.

STUDY DESIGN AND SETTING

PubMed and Web of Science were searched for reviews with extractable PROBAST scores on domain and signaling question (SQ) level. ROB trends were visually correlated with yearly citations of key publications. Inter-rater agreement was assessed using Cohen's Kappa.

RESULTS

One hundred and thirty nine systematic reviews were included, of which 85 reviews (containing 2,477 single studies) on domain level and 54 reviews (containing 2,458 single studies) on SQ level. High ROB was prevalent, especially in the Analysis domain, and overall trends of ROB remained relatively stable over time. The inter-rater agreement was low, both on domain (Kappa 0.04-0.26) and SQ level (Kappa -0.14 to 0.49).

CONCLUSION

Prediction model studies are at high ROB and time trends in ROB as assessed with the PROBAST remain relatively stable. These results might be explained by key publications having no influence on ROB or recency of key publications. Moreover, the trend may suffer from the low inter-rater agreement and ceiling effect of the PROBAST. The inter-rater agreement could potentially be improved by altering the PROBAST or providing training on how to apply the PROBAST.

Outcomes and pulmonary function after sleeve lobectomy compared with pneumonectomy in patients with non-small cell lung cancer

BACKGROUND

Sleeve lobectomy is recommended to avoid pneumonectomy and preserve pulmonary function in patients with central lung cancer. However, the relationship between postoperative pulmonary functional loss and resected lung parenchyma volume has not been fully characterized. The aim of this study was to evaluate the relationship between pulmonary function and lung volume in patients undergoing sleeve lobectomy or pneumonectomy.

METHODS

A total of 61 lung cancer patients who had undergone pneumonectomy or sleeve lobectomy were analyzed retrospectively. Among them, 20 patients performed pulmonary function tests, including vital capacity (VC) and forced expiratory volume in 1 s (FEV1) tests, preoperatively and then about 6 months after surgery. VC and FEV1 ratios were calculated (measured postoperative respiratory function/predicted postoperative respiratory function) as the standardized pulmonary functional loss ratio.

RESULTS

Thirty-day operation-related mortality was significantly lower after sleeve lobectomy (3.2%) than pneumonectomy (9.6%). The 5-year relapse-free survival rate was 46.67% versus 29.03%, and the 5-year overall survival rate was 63.33% versus 38.71% in patients receiving sleeve lobectomy versus pneumonectomy. The VC ratio in the pneumonectomy group was better than in the sleeve lobectomy group (1.003 ± 0.117 vs. 0.779 ± 0.12; p = 0.0008), as was the FEV1 ratio (1.132 ± 0.226 vs. 0.851 ± 0.063; p = 0.0038).

CONCLUSIONS

Both short-term and long-term outcomes were better with sleeve lobectomy than pneumonectomy. However, actual postoperative pulmonary function after pneumonectomy may be better than clinicians expect, and pneumonectomy should still be considered a treatment option for patients with sufficient pulmonary reserve and in whom sleeve lobectomy is less likely to be curative.

A Comprehensive Survey on the Progress, Process, and Challenges of Lung Cancer Detection and Classification

Lung cancer is the primary reason of cancer deaths worldwide, and the percentage of death rate is increasing step by step. There are chances of recovering from lung cancer by detecting it early. In any case, because the number of radiologists is limited and they have been working overtime, the increase in image data makes it hard for them to evaluate the images accurately. As a result, many researchers have come up with automated ways to predict the growth of cancer cells using medical imaging methods in a quick and accurate way. Previously, a lot of work was done on computer-aided detection (CADe) and computer-aided diagnosis (CADx) in computed tomography (CT) scan, magnetic resonance imaging (MRI), and X-ray with the goal of effective detection and segmentation of pulmonary nodule, as well as classifying nodules as malignant or benign. But still, no complete comprehensive review that includes all aspects of lung cancer has been done. In this paper, every aspect of lung cancer is discussed in detail, including datasets, image preprocessing, segmentation methods, optimal feature extraction and selection methods, evaluation measurement matrices, and classifiers. Finally, the study looks into several lung cancer-related issues with possible solutions.

Assessment and Rehabilitation of the Compromised Patient Prior to Thoracotomy

Patients for whom pulmonary resection is anticipated often have compromised pulmonary function and decreased exercise tolerance. To avoid major morbidity and reduce mortality, identification of the high-risk patient becomes extremely important. The means of identification include rather simple testing modalities as well as those that are more complex, which report specific physiologic data. This article develops a schematic for a logical progression through the assessment of prethoracotomy patients in order that those facing a significant surgical risk might undergo pulmonary rehabilitation to improve exercise performance followed by reassessment prior to surgery.

A preliminary study identifies early postoperative lung volume changes in patients with non-small cell lung cancer following video-assisted thoracic surgery using CT volumetry

The present study aimed to investigate the changes in early postoperative lung volume in patients with non-small cell lung cancer (NSCLC) following video-assisted thoracic surgery (VATS) and to analyze the effects of the clinical characteristics on the lung volume of the patients. Therefore, 38 patients with NSCLC, who planned to undergo VATS at the Department of Thoracic Surgery, The Affiliated Hospital of Guizhou Medical University in June 2019, were enrolled into the present study. The clinical and computed tomography (CT) scan data from the patients was prospectively collected within 1 week preoperatively, and at 1, 3 and 6 months following surgery, then subsequently analyzed. A total of 34 patients successfully completed follow-up and were included in the datasets. The results showed that the volume of the right lung was larger compared with that in the left one, at each observational time point. The whole, right and left lung held the same trendline of volume changes, which was sharply decreased during the first postoperative month, increased quickly over the next 3 months, and slowly increased from months 3 to 6. There were 7 patients, whose whole lung volume was increased at 6 months following surgery compared with that preoperatively. In addition, significant differences were observed between males and females in the whole, right and left lung volume. However, the differences on the postoperative net expansion volume of the whole lung were not significant among sex, age, body mass index (BMI), smoking status and surgical side subgroups. The early changes of the postoperative lung volume were not linear, since the lung volume was significantly reduced during the first postoperative month, quickly increased in the next 3 months, and slowly increased from months 3 to 6. Sex, age, BMI, smoking status and surgical sides was not found to affect the postoperative volume and net expansion of the whole lung following VATS lobectomy.

Dynamic perfusion digital radiography for predicting pulmonary function after lung cancer resection

Background

Accurate prediction of postoperative pulmonary function is important for ensuring the safety of patients undergoing radical resection for lung cancer. Dynamic perfusion digital radiography is an excellent and easy imaging method for detecting blood flow in the lung compared with the less-convenient conventional lung perfusion scintigraphy. As such, the present study aimed to confirm whether dynamic perfusion digital radiography can be evaluated in comparison with pulmonary perfusion scintigraphy in predicting early postoperative pulmonary function and complications.

Methods

Dynamic perfusion digital radiography and spirometry were performed before and 1 and 3 months after radical resection for lung cancer. Correlation coefficients between blood flow ratios calculated using dynamic perfusion digital radiography and pulmonary perfusion scintigraphy were then confirmed in the same cases. In all patients who underwent dynamic perfusion digital radiography, the correlation predicted values calculated from the blood flow ratio, and measured values were examined. Furthermore, ppo%FEV1 or ppo%DLco values, which indicated the risk for perioperative complications, were examined.

Results

A total of 52 participants who satisfied the inclusion criteria were analyzed. Blood flow ratios measured using pulmonary perfusion scintigraphy and dynamic perfusion digital radiography showed excellent correlation and acceptable predictive accuracy. Correlation coefficients between predicted FEV1 values obtained from dynamic perfusion digital radiography or pulmonary perfusion scintigraphy and actual measured values were similar. All patients who underwent dynamic perfusion digital radiography showed excellent correlation between predicted values and those measured using spirometry. A significant difference in ppo%DLco was observed for respiratory complications but not cardiovascular complications.

Conclusions

Our study demonstrated that dynamic perfusion digital radiography can be a suitable alternative to pulmonary perfusion scintigraphy given its ability for predicting postoperative values and the risk for postoperative respiratory complications. Furthermore, it seemed to be an excellent modality because of its advantages, such as simplicity, low cost, and ease in obtaining in-depth respiratory functional information.

Trial registration

Registered at UMIN on October 25, 2017. https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_his_list.cgi?recptno=R000033957

Registration number: UMIN000029716

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02158-w.

The Year in Thoracic Anesthesia: Selected Highlights from 2019

THIS special article is the 4th in an annual series for the Journal of Cardiothoracic and Vascular Anesthesia. The authors thank the editor-in-chief, Dr. Kaplan; the associate editor-in-chief, Dr. Augoustides; and the editorial board for the opportunity to expand this series, the research highlights of the year that specifically pertain to the specialty of thoracic anesthesia. The major themes selected for 2019 are outlined in this introduction, and each highlight is reviewed in detail in the main body of the article. The literature highlights in this specialty for 2019 include updates in the preoperative assessment and optimization of patients undergoing lung resection and esophagectomy, updates in one lung ventilation (OLV) and protective ventilation during OLV, a review of recent meta-analyses comparing truncal blocks with paravertebral catheters and the introduction of a new truncal block, meta-analyses comparing nonintubated video-assisted thoracoscopic surgery (VATS) with those performed using endotracheal intubation, a review of the Society of Thoracic Surgeons (STS) recent composite score rating for pulmonary resection of lung cancer, and an update of the Enhanced Recovery After Surgery (ERAS) guidelines for both lung and esophageal surgery.