Therapeutic surgery without a definitive diagnosis can be an option in selected patients with suspected lung cancer

The study of plain CT combined with contrast-enhanced CT-based models in predicting malignancy of solitary solid pulmonary nodules

To compare the diagnostic performance between plain CT-based model and plain plus contrast CT-based modelin the classification of malignancy for solitary solid pulmonary nodules. Between January 2012 and July 2021, 527 patients with pathologically confirmed solitary solid pulmonary nodules were collected at dual centers with similar CT examinations and scanning parameters. Before surgery, all patients underwent both plain and contrast-enhanced chest CT scans. Two clinical characteristics, fifteen plain CT characteristics, and four enhanced characteristics were used to develop two logistic regression models: model 1 (plain CT only) and model 2 (plain + contrast CT). The diagnostic performance of the two models was assessed separately in the development and external validation cohorts using the AUC. 392 patients from Center A were included in the training cohort (median size, 20.0 [IQR, 15.0-24.0] mm; mean age, 55.8 [SD, 9.9] years; male, 53.3%). 135 patients from Center B were included in the external validation cohort (median size, 20.0 [IQR, 16.0-24.0] mm; mean age, 56.4 [SD, 9.6] years; male, 51.9%). Preoperative patients with 201 malignant (adenocarcinoma, 148 [73.6%]; squamous cell carcinoma, 35 [17.4%]; large cell carcinoma,18 [9.0%]) and 326 benign (pulmonary hamartoma, 118 [36.2%]; sclerosing pneumocytoma, 35 [10.7%]; tuberculosis, 104 [31.9%]; inflammatory pseudonodule, 69 [21.2%]) solitary solid pulmonary nodules were gathered from two independent centers. The mean sensitivity, specificity, accuracy, PPV, NPV, and AUC (95%CI) of model 1 (Plain CT only) were 0.79, 0.78, 0.79, 0.67, 0.87, and 0.88 (95%CI, 0.82-0.93), the model 2 (Plain + Contrast CT) were 0.88, 0.91, 0.90, 0.84, 0.93, 0.93 (95%CI, 0.88-0.98) in external validation cohort, respectively. A logistic regression model based on plain and contrast-enhanced CT characteristics showed exceptional performance in the evaluation of malignancy for solitary solid lung nodules. Utilizing this contrast-enhanced CT model would provide recommendations concerning follow-up or surgical intervention for preoperative patients presenting with solid lung nodules.

Enhanced CT-Based Intratumoral and Peritumoral Radiomics Nomograms Predict High-Grade Patterns of Invasive Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

Extraction of intratumoral and peritumoral radiomics features combined with clinical factors to establish nomograms to predict high-grade patterns (micropapillary and solid) of invasive adenocarcinoma of the lung (IAC).

MATERIALS AND METHODS

A retrospective study was conducted on 463 patients with pathologically confirmed IAC. Patients were randomized in a 7:3 ratio into a training cohort (n = 324) and a testing cohort (n = 139). A total of 2154 CT-based radiomic features were extracted from each of the four regions: gross tumor volume (GTV) and gross peritumoral tumor volume (GPTV3, GPTV6, GPTV9) containing peri-tumor regions of 3 mm, 6 mm, and 9 mm. A radiomics nomogram was constructed based on the optimal radiomics model and clinically independent predictors.

RESULTS

The GPTV3 radiomics model showed better predictive performance in the testing group compared to the GTV (0.840), GPTV6 (0.843), and GPTV9 (0.734) models, with an AUC value of 0.889 in the testing group. In the clinical model, tumor density and the presence of a spiculation sign were identified as independent predictors. The nomogram, which combined these independent predictors with the GPTV3-Radscore, proved to be clinically useful.

CONCLUSION

The GPTV3 radiomics model was superior to the GTV, GPTV6, and GPTV9 radiomics models in predicting high-grade patterns (HGP) of IAC. In addition, nomograms based on GPTV3 radiomics features and clinically independent predictors can further improve the prediction efficiency.

Is histological confirmation necessary to avoid futile resections? Comparative of 4 university hospitals

OBJECTIVES

There is no consensus in the literature on preoperative histological analysis for lung cancer. The objective of this study was to assess 4 diagnostic models used in different hospitals with differing practices regarding preoperative histological diagnosis and the consequences in terms of unnecessary surgery and futile major resection.

METHODS

We carried out a retrospective observational study collected from 4 university hospitals in Spain over 3 years (January 2019 to December 2021). We included all patients with a confirmed diagnosis of primary lung cancer and any patients with suspected primary lung cancer who had undergone surgery. All patients underwent computed tomography and positron emission tomography/computed tomography scans. Each multidisciplinary committee was free to choose whether to perform flexible bronchoscopic or transthoracic lung biopsy. Decisions concerning whether to perform intraoperative sample analysis, the surgical approach and the type of resection were left to the surgical team.

RESULTS

We included a total of 1642 patients. The use of flexible endoscopy and its diagnostic performance varied substantially between hospitals (range: 23.8-79.3% and 25-60.7%, respectively); and the same was observed for transthoracic biopsy and its performance (range: 16.9-82.3% and 64.6-97%, respectively). Regarding major resection surgery (lobectomy or more extensive resection), the lowest rate was observed in hospital C (1%) and the highest in hospital B (2.8%), with between-hospital differences not reaching significance (P = 0.173).

CONCLUSIONS

The rate of histological sampling before lung cancer surgery still varies between hospitals. In spite of very diverse multidisciplinary management, the rate of futile lobectomy is not significantly higher in hospitals with lower rates of preoperative histological analysis.

Prediction of histologic types in solid lung lesions using preoperative contrast-enhanced CT

OBJECTIVES

This study aimed to develop and validate a predicting model for the histologic classification of solid lung lesions based on preoperative contrast-enhanced CT.

METHODS

A primary dataset of 1012 patients from Tianjin Medical University Cancer Institute and Hospital (TMUCIH) was randomly divided into a development cohort (708) and an internal validation cohort (304). Patients from the Second Hospital of Shanxi Medical University (SHSMU) were set as an external validation cohort (212). Two clinical factors (age, gender) and twenty-one characteristics on contrast-enhanced CT were used to construct a multinomial multivariable logistic regression model for the classification of seven common histologic types of solid lung lesions. The area under the receiver operating characteristic curve was used to assess the diagnostic performance of the model in the development and validation cohorts, separately.

RESULTS

Multivariable analysis showed that two clinical factors and twenty-one characteristics on contrast-enhanced CT were predictive in lung lesion histologic classification. The mean AUC of the proposed model for histologic classification was 0.95, 0.94, and 0.92 in the development, internal validation, and external validation cohort, respectively. When determining the malignancy of lung lesions based on histologic types, the mean AUC of the model was 0.88, 0.86, and 0.90 in three cohorts.

CONCLUSIONS

We demonstrated that by utilizing both clinical and CT characteristics on contrast-enhanced CT images, the proposed model could not only effectively stratify histologic types of solid lung lesions, but also enabled accurate assessment of lung lesion malignancy. Such a model has the potential to avoid unnecessary surgery for patients and to guide clinical decision-making for preoperative treatment.

KEY POINTS

• Clinical and CT characteristics on contrast-enhanced CT could be used to differentiate histologic types of solid lung lesions. • Predicting models using preoperative contrast-enhanced CT could accurately assessment of tumor malignancy based on predicted histologic types.

A novel nomogram model combining CT texture features and urine energy metabolism to differentiate single benign from malignant pulmonary nodule

Objective

To investigate a novel diagnostic model for benign and malignant pulmonary nodule diagnosis based on radiomic and clinical features, including urine energy metabolism index.

Methods

A total of 107 pulmonary nodules were prospectively recruited and pathologically confirmed as malignant in 86 cases and benign in 21 cases. A chest CT scan and urine energy metabolism test were performed in all cases. A nomogram model was established in combination with radiomic and clinical features, including urine energy metabolism levels. The nomogram model was compared with the radiomic model and the clinical feature model alone to test its diagnostic validity, and receiver operating characteristic (ROC) curves were plotted to assess diagnostic validity.

Results

The nomogram was established using a logistic regression algorithm to combine radiomic features and clinical characteristics including urine energy metabolism results. The predictive performance of the nomogram was evaluated using the area under the ROC and calibration curve, which showed the best performance, area under the curve (AUC) = 0.982, 95% CI = 0.940-1.000, compared to clinical and radiomic models in the testing cohort. The clinical benefit of the model was assessed using the decision curve analysis (DCA) and using the nomogram for benign and malignant pulmonary nodules, and preoperative prediction of benign and malignant pulmonary nodules using nomograms showed better clinical benefit.

Conclusion

This study shows that a coupled model combining CT imaging features and clinical features (including urine energy metabolism) in combination with the nomogram model has higher diagnostic performance than the radiomic and clinical models alone, suggesting that the combination of both methods is more advantageous in identifying benign and malignant pulmonary nodules.

Chest three-dimensional-computed tomography imaging data analysis for the variation of exercise capacity after lung lobectomy

BACKGROUND

Postoperative loss of exercise capacity and pulmonary function is a major concern among lung cancer patients. In this study, the time for a stair-climbing to 12-m height was used to investigate whether preoperative chest 3D-computed tomography (CT) could be a useful tool for predicting postoperative variations in exercise capacity and pulmonary function.

METHODS

Seventy-eight patients undergoing lobectomy for suspected stage I lung cancer were prospectively enrolled. Preoperatively, lobe volume and low attenuation volume (LAV) were evaluated using the SYNAPSE VINCENT system. Preoperative data on stair-climbing time, spirometry, and diffusing capacity of the lung for carbon monoxide (DL_CO ) at baseline and 6-month postoperative data were used to evaluate variations in exercise capacity and pulmonary function. Maximal oxygen uptake (VO₂ t) was evaluated based on the stair-climbing time.

RESULTS

Significant differences in the variation of exercise capacity at 6 months postoperatively were found between the groups categorized by target lobe volume and LAV status: The large volume/LAV (+) group had a greater decline in VO₂ t. Mean loss of VO₂ t was -6.2%, -1.4%, -1.6%, and -0.1% in the large volume/LAV (+), large volume/LAV (-), small volume/LAV (+), and small volume/LAV (-) groups, respectively. The large volume/LAV (-) group had a greater decline in forced expiratory volume in 1 s. The small volume/LAV (+) group showed a reduced decline in the DL_CO .

CONCLUSIONS

Analysis of chest 3D-CT scans is a potential tool for predicting the loss of exercise capacity and pulmonary function after lung lobectomy. This article is protected by copyright. All rights reserved.

Risk Assessment for Loss-of-Exercise Capacity After Lung Cancer Surgery: Current Advances in Surgery and Systemic Treatment

BACKGROUND

Considering advances in current post-recurrence treatment, we examined the prognostic significance of the number of risk factors for loss-of-exercise capacity (LEC) after lung cancer surgery, which were identified by our previous prospective observational study.

METHODS

Risk factors for LEC were defined as a short baseline 6-min walk distance (<400 m), older age (≥75 years), and low predicted postoperative diffusing capacity for carbon monoxide (<60%). Patients were classified as Risk 0/I/II/III according to the number of risk factors. The survival data were retrospectively analyzed.

RESULTS

Between 2014 and 2017, 564 patients (n = 307, 193, 57, 7; Risk 0/I/II/III) who underwent lung cancer surgery were included in the study. The number of risk factors was associated with smoking status, predicted postoperative forced expiratory volume in 1 s, histology, pathological stage, and adjuvant therapy. In a multivariate Cox regression analysis, compared to Risk 0, Risk I/II/III showed significant associations with overall survival (hazard ratios: 1.92, 3.35, 9.21; 95% confidence interval: 1.27-2.92, 2.01-5.58, 3.64-23.35; Risk I/II/III, respectively). In 141 patients with recurrence, molecular targeted therapies (MTTs) or immune checkpoint inhibitors (ICIs) were included in 58%, 47%, 32%, and 0% (Risk 0/I/II/III) during the course of treatment. In patients with MTT/ICI treatment, the estimated 1-year and 3-year post-recurrence survival rates were 88% and 58%, respectively.

CONCLUSIONS

Risk classification for LEC was associated with survival after lung cancer surgery, as well as post-recurrence treatment. The concept of physical performance-preserving surgery may contribute to improving the outcomes of current lung cancer treatment.

Surgery without preoperative histological confirmation of lung cancer: what is the current clinical practice?

BACKGROUND

There are discordances in the guidelines regarding the need to acquire histological diagnosis before surgical treatment of (presumed) lung cancer. Preoperative histological confirmation is always encouraged in this setting to prevent unnecessary surgery or when sublobar resection for small-sized tumors is considered. The aim of this retrospective cohort study was to assess the proportion of patients undergoing lung cancer resection in the Netherlands without preoperative pathological confirmation, based on the intraoperative pathological diagnosis (IOD) rate, and to determine characteristics that may influence IOD frequency.

METHODS

Data on 10,226 patients, who underwent surgical treatment for lung cancer from 2010 to 2015, were retrieved from the Netherlands National Cancer Registry. We registered an IOD when the date of diagnosis equaled the date of the first surgical intervention. Tabulations and multivariable logistic regression were used to identify predictive parameters for IOD.

RESULTS

36% of surgical procedures were classified as IOD, and decreased with increasing tumor size and extent of surgery (57% for segmentectomy, 39% for lobectomy and 11% for pneumonectomy). IOD was more frequently observed in adenocarcinoma (41%), varied between hospitals from 13% to 66% and was less common when patients were referred from a hospital where thoracic surgery was not performed. Previous history of cancer did not affect IOD.

CONCLUSIONS

More than one-third of patients with suspected lung cancer in the Netherlands was operated without preoperative histological confirmation. There was significant variation in IOD rates between different hospitals, which deserves further detailed analysis when striving for uniform surgical quality of care for patients with lung cancer.

A contrast-enhanced-CT-based classification tree model for classifying malignancy of solid lung tumors in a Chinese clinical population

Background

To develop and validate a contrast-enhanced CT based classification tree model for classifying solid lung tumors in clinical patients into malignant or benign.

Methods

Between January 2015 and October 2017, 827 pathologically confirmed solid lung tumors (487 malignant, 340 benign; median size, 27.0 mm, IQR 18.0–39.0 mm) from 827 patients from a dedicated Chinese cancer hospital were identified. Nodules were divided randomly into two groups, a training group (575 cases) and a testing group (252 cases). CT characteristics were collected by two radiologists, and analyzed using a classification and regression tree (CART) model. For validation, we used the decision analysis threshold to evaluate the classification performance of the CART model and radiologist’s diagnosis (benign; malignant) in the testing group.

Results

Three out of 19 characteristics [margin (smooth; slightly lobulated/lobulated/spiculated), and shape (round/oval; irregular), subjective enhancement (no/uniform enhancement; heterogeneous enhancement)] were automatically generated by the CART model for classifying solid lung tumors. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the CART model is 98.5%, 58.1%, 80.6%, 98.6%, 79.8%, and 90.4%, 54.7%, 82.4% 98.5%, 74.2% for the radiologist’s diagnosis by using three-threshold decision analysis.

Conclusions

Tumor margin and shape, and subjective tumor enhancement were the most important CT characteristics in the CART model for classifying solid lung tumors as malignant. The CART model had higher discriminatory power than radiologist’s diagnosis. The CART model could help radiologists making recommendations regarding follow-up or surgery in clinical patients with a solid lung tumor.

CT Texture Analysis for Differentiating Bronchiolar Adenoma, Adenocarcinoma In Situ, and Minimally Invasive Adenocarcinoma of the Lung

Purpose: This study aimed to investigate the potential of computed tomography (CT) imaging features and texture analysis to distinguish bronchiolar adenoma (BA) from adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA).

Materials and Methods: Fifteen patients with BA, 38 patients with AIS, and 36 patients with MIA were included in this study. Clinical data and CT imaging features of the three lesions were evaluated. Texture features were extracted from the thin-section unenhanced CT images using Artificial Intelligence Kit software. Then, multivariate logistic regression analysis based on selected texture features was employed to distinguish BA from AIS/MIA. Receiver operating characteristics curves were performed to determine the diagnostic performance of the features.

Results: By comparison with AIS/MIA, significantly different CT imaging features of BA included nodule type, tumor size, and pseudo-cavitation sign. Among them, pseudo-cavitation sign had a moderate diagnostic value for distinguishing BA and AIS/MIA (AUC: 0.741 and 0.708, respectively). Further, a total of 396 quantitative texture features were extracted. After comparation, the top six texture features showing the most significant difference between BA and AIS or MIA were chosen. The ROC results showed that these key texture features had a high diagnostic value for differentiating BA from AIS or MIA, among which the value of a comprehensive model with six selected texture features was the highest (AUC: 0.977 or 0.976, respectively) for BA and AIS or MIA. These results indicated that texture analyses can effectively improve the efficacy of thin-section unenhanced CT for discriminating BA from AIS/MIA.

Conclusion: CT texture analysis can effectively improve the efficacy of thin-section unenhanced CT for discriminating BA from AIS/MIA, which has a potential clinical value and helps pathologist and clinicians to make diagnostic and therapeutic strategies.

Definitive lobectomy without frozen section analysis is a treatment option for large or deep nodules selected carefully with clinical diagnosis of malignancy

Background

Tissue harvesting for patients with a lung nodule is sometimes unsuitable due to the size and location of the nodule. In such cases, it is unclear whether it is acceptable to proceed to definitive lobectomy without intraoperative frozen section analysis.

Methods

We retrospectively reviewed patients who underwent definitive lobectomy or wedge resection for frozen section analysis at our institution between 2014 and 2018. The sensitivity, specificity, and accuracies of the clinical and frozen section diagnoses were evaluated against the final pathological diagnosis.

Results

There were 141 patients in the definitive lobectomy group and 58 patients in the frozen section analysis group, with the latter having smaller and less deep nodules and a lower rate of malignancy on clinical and final pathological diagnoses. The sensitivity, specificity, and accuracy of the clinical diagnosis were 100%, 82%, and 95%, respectively, in the frozen section analysis group and 99%, 67%, and 97%, respectively, in the definitive lobectomy group; values of frozen section diagnosis were 98%, 82%, and 93%, respectively. On subgroup analysis, all ground‐glass nodules clinically diagnosed as malignant had a final pathological diagnosis of malignancy.

Conclusions

The accuracy of the clinical diagnosis was high and was not inferior to the frozen section diagnosis. These data suggest that definitive lobectomy is an acceptable treatment option for carefully selected patients with large or deep nodules and ground‐glass nodules clinically diagnosed as malignant. To avoid unnecessary lobectomy, frozen section diagnosis should be considered for nodules likely to be benign.

Key points

[Short-term results of video-assisted lung cancer surgery in octogenarians]

INTRODUCTION

Due to an increase in life expectancy, onco-pulmonologists and thoracic surgeons are more frequently faced with octogenarian patients with lung cancer. In this age group, treatment modalities may need to be revised because of the increasing presence of comorbidities. Surgery remains the reference treatment for early stage disease, but mortality rates and postoperative complications are higher in this group of patients. One of the solutions to reduce the operative risk would be to develop videoassisted thoracoscopic pulmonary resection surgery. The aim of this study was to evaluate the results of this form of lung cancer surgery in octogenarians.

METHODS

All patients 80 years old or more who underwent videoassisted lung cancer surgery from 2014 to 2018 at Lyon University Hospital were included. Wedge resections and diagnostic procedures were excluded.

RESULTS

Nineteen patients (13 men, 6 women) were included. The median age was 82 years old. All patients had undergone videoassisted lobectomy. Three patients required conversion to thoracotomy (15.8%). All patients underwent complete resection (R0). One patient had N1 lymph node involvement, all others were N0. The postoperative complication rate was 68.4%, the majority of which were grade II of the Clavien classification. Perioperative mortality was 5.3%.

CONCLUSIONS

Videoassisted lung cancer resection in a selected population of octogenarians is associated with satisfactory short-term results. It is reasonable to favour minimally invasive techniques in this population, even if the proof of their superiority has not yet been firmly established.

CT texture analysis of histologically proven benign and malignant lung lesions

The purpose of our study was to determine accuracy of CT texture analysis (CTTA) for differentiating benign from malignant pulmonary nodules, and well-differentiated from poorly differentiated lung cancers, with histology as the standard of reference.In this IRB-approved study, 175 adult patients (average age 66 ± 12 years; age range 27-89 years, male 82: female 93) who underwent a noncontrast chest CT examination prior to CT-guided biopsy of pulmonary nodules were included. There were 57 benign (24 tumors or tumor-like lesions; 33 inflammatory conditions) and 120 malignant (29 well-differentiated adenocarcinomas, 48 poorly differentiated adenocarcinomas, and 43 squamous cell carcinomas) diagnoses on pathology. CTTA was performed on the prebiopsy noncontrast CT images using a commercially available software (TexRAD limited, UK). The CTCA features analyzed included mean HU values, percent positive pixels (PPP), mean value of positive pixels (MPP), standard deviation (SD), normalized SD, skewness, kurtosis, and entropy.The ROC analyses showed that normalized SD [AUC: 0.63, (CI: 0.55-72), P = .003] had moderate accuracy for differentiating between benign and malignant lesions. For differentiating among well-differentiated and poorly differentiated tumors, the ROC analysis showed that except skewness all other parameters were statistically significant The AUC values of other CTTA parameters were: mean (AUC: 0.73-0.76, P = .001- < .0001).CT texture analyses can reliably predict well- and poorly differentiated lung malignancies. However, inflammatory lung lesions with tissue heterogeneity negatively affect the performance of CTTA when it comes to differentiation between benign and malignant pulmonary nodules.

FDG PET/CT Overcomes Discordance Between Clinical and Pathologic TNM Classification of Small-size Primary Lung Cancer: Influence on Postoperative Prognosis

INTRODUCTION

We aimed to determine the concordance between the clinical stage (c-stage) and pathologic stage (p-stage) for patients with small-size lung cancer. Additionally we searched for prognostic factors other than the TNM stage.

PATIENTS AND METHODS

We retrospectively reviewed the preoperative multidetector computed tomography (CT) and positron emission tomography/CT reports, surgical records, and pathologic reports of patients with primary lung cancer ≤ 3 cm. The Union for International Cancer Control TNM seventh edition classification of c-stage and p-stage were compared. The tumors were classified into multiple subgroups by concordance or discordance between the c-stage and p-stage. Disease-free survival (DFS) was assessed using survival analysis to assess the tumor characteristics that were predictive of prognosis.

RESULTS

A total of 289 surgically resected primary lung cancers were evaluated. The concordance between c-stage and p-stage was 65.4%, with moderate reproducibility (kappa coefficient, 0.467). The upstaging rate from c-stage I to p-stage II-IV was 9.4%, and these patients had significantly worse DFS than those with a concordant stage I classification (P < .001). The main reason for upstaging was an underestimation of metastases to the hilar lymph nodes (n = 7) or mediastinal lymph nodes (n = 11). A multivariate Cox proportional hazards model showed that the significant predictive factors for DFS were p-stage (hazard ratio, 1.342; P = .003) and maximum standardized uptake value on positron emission tomography/CT (hazard ratio, 12.162; P = .001).

CONCLUSION

The concordance rate between c-stage and p-stage for small primary lung cancers had moderate reproducibility. Discordance between c-stage I and p-stage II-IV significantly affected DFS. The maximum standardized uptake value of the primary lesion was an independent prognostic factor, and combining it with c-stage might improve the prediction of therapeutic outcomes.

Marginal pulmonary function is associated with poor short- and long-term outcomes in lung cancer surgery

We sought to determine the short- and long-term prognoses among ‘marginal-risk’ non-small cell lung cancer patients who have a predicted postoperative- (ppo) forced expiratory volume in the first second (FEV₁) of 30–60% and/or a ppo-diffusing capacity of the lung for carbon monoxide (DL_CO) of 30–60%. The present study included 73 ‘marginal-risk’ and 318 ‘normal-risk’ patients who underwent anatomical resection for clinical stage I lung cancer between 2008 and 2012. The rates of postoperative morbidity, prolonged hospital stay, and overall survival were assessed. Postoperative morbidity occurred in 35 (48%) ‘marginal-risk’ patients and 66 (21%) ‘normal-risk’ patients, and 17 (23%) ‘marginal-risk’ patients and 20 (6%) ‘normal-risk’ patients required a prolonged hospital stay. The three- and five-year survival rates were 79% and 64% in the ‘marginal-risk’ patients and 93% and 87% in the ‘normal-risk’ patients, respectively. A ‘marginal-risk’ status was a significant factor in the prediction of postoperative morbidity (odds ratio [OR] 2.97, p < 0.001), the rate of prolonged hospital stay (OR 3.83, p < 0.001), and overall survival (hazard ratio 2.07, p = 0.028). In conclusion, ‘Marginal-risk’ patients, who are assessed based on ppo-values, comprise a subgroup of patients with poorer short- and long-term postoperative outcomes.

Evaluation of locoregional invasiveness of small-sized non-small cell lung cancers by enhanced dual-energy computed tomography

Background

To investigate the correlation between iodine-related attenuation of dual-energy computed tomography (DE-CT) and the histopathological invasiveness of surgically resected primary non-small cell lung cancers (NSCLCs) ≤ 3 cm in diameter.

Methods

We selected 63 consecutive NSCLC lesions from 60 patients (32 males, 28 females; age range, 39–85 years; mean age, 68 years). After injection of iodinated contrast media, arterial phases were scanned using 140-kVp and 80-kVp tube voltages. Three-dimensional iodine-related attenuation (3D-IRA) of primary tumors at the arterial phase was computed using “lung nodule” application software. The corrected 3D-IRA normalized to the patient’s body weight and contrast medium concentration was then calculated. Single-factor analysis of variance (ANOVA) was used for comparison among tumor differentiation grade groups. Univariate and multivariate logistic regression analysis was used for the correlation between locoregional invasive tumor and clinical factors.

Results

Resected tumors were histopathologically classified into well-differentiated (G1; n = 24), moderately-differentiated (G2; n = 28), and poorly-differentiated (G3; n = 11) groups by degree of tumor differentiation. The mean ± standard deviation of the 3D-IRA was 56.1 ± 22.6 HU in G1 tumours, 48.5 ± 23.9 HU in G2 tumours, and 28.4 ± 15.8 HU in G3 tumours; significant differences were observed between groups by ANOVA. (p = 0.005). Univariate logistic analysis showed that the 3D-IRA and corrected 3D-IRAs were significantly correlated with locoregional invasive tumors (p = 0.002 and p < 0.001, respectively). Multivariate logistic analysis revealed that only the corrected 3D-IRA was significantly correlated with tumor invasiveness (p = 0.003), while gender, clinical size, and solid/subsolid type were not (p = 0.950, p = 0.057 and p = 0.456, respectively).

Conclusions

The 3D-IRA of small-sized NSCLCs was significantly associated with and invasiveness. Low 3D-IRA tumors tended to have greater invasiveness than high 3D-IRA tumors.

Correlation between FDG-PET/CT findings and solid type non-small cell cancer prognostic factors: are there differences between adenocarcinoma and squamous cell carcinoma?

OBJECTIVES

The maximum standardized uptake value (SUVmax) of FDG-PET/CT is commonly used as an indicator to evaluate the invasiveness and prognosis of non-small-cell lung cancers (NSCLC). We investigated the correlation between SUVmax and tumor invasiveness or postoperative recurrence of solid type NSCLC and compared squamous cell carcinoma (SCC)/adenosquamous carcinoma (ASC) to adenocarcinoma (AC).

METHODS

A retrospective review of preoperative PET/CT, thin-section CT, and postoperative pathological records obtained over a 5-year period was conducted. Solid type NSCLC tumors on thin-section CT with confirmed diagnosis from surgical resection (diameter ≤3 cm) were included. Multivariate logistic regression was used to evaluate the correlation between tumor characteristics and pathological prognostic factors or postoperative recurrence.

RESULTS

150 patients (111 males, 39 females; mean age 67 years; 106 cases of AC, 36 cases of SCC, and 8 cases of ASC) were included. SUVmax was significantly correlated with pleural involvement (p = 0.047), lymphatic permeation (p = 0.003), lymph node metastasis (p = 0.027), and tumor invasiveness (p < 0.001). Receiver operating characteristic analysis indicated an optimal SUVmax threshold of 5.0 for tumor invasiveness. Histopathological type was significantly correlated with pleural involvement (p = 0.042), but not with other types of invasiveness. Twenty-nine patients experienced postoperative recurrence. SUVmax was significantly correlated with tumor recurrence (p = 0.004), but size and histopathological type were not (p = 0.502 and p = 0.351, respectively).

CONCLUSION

SUVmax of the primary lesion in solid type NSCLC was significantly correlated with tumor invasiveness and postoperative recurrence. No differences in tumor invasiveness were observed between solid type AC and SCC/ASC. However, in solid type AC, SUVmax of the primary lesion was more significantly correlated with recurrence.