Correlation between whole tumor size and solid component size on high-resolution computed tomography in the prediction of the degree of pathologic malignancy and the prognostic outcome in primary lung adenocarcinoma

Radiomics Analysis for the Identification of Invasive Pulmonary Subsolid Nodules From Longitudinal Presurgical CT Scans

PURPOSE

Effective identification of malignant part-solid lung nodules is crucial to eliminate risks due to therapeutic intervention or lack thereof. We aimed to develop delta radiomics and volumetric signatures, characterize changes in nodule properties over three presurgical time points, and assess the accuracy of nodule invasiveness identification when combined with immediate presurgical time point radiomics signature and clinical biomarkers.

MATERIALS AND METHODS

Cohort included 156 part-solid lung nodules with immediate presurgical CT scans and a subset of 122 nodules with scans at 3 presurgical time points. Region of interest segmentation was performed using ITK-SNAP, and feature extraction using CaPTk. Image parameter heterogeneity was mitigated at each time point using nested ComBat harmonization. For 122 nodules, delta radiomics features (ΔR AB = (R B -R A )/R A ) and delta volumes (ΔV AB = (V B -V A )/V A ) were computed between the time points. Principal Component Analysis was performed to construct immediate presurgical radiomics (Rs 1 ) and delta radiomics signatures (ΔRs 31 + ΔRs 21 + ΔRs 32 ). Identification of nodule pathology was performed using logistic regression on delta radiomics and immediate presurgical time point signatures, delta volumes (ΔV 31 + ΔV 21 + ΔV 32 ), and clinical variable (smoking status, BMI) models (train test split (2:1)).

RESULTS

In delta radiomics analysis (n= 122 nodules), the best-performing model combined immediate pre-surgical time point and delta radiomics signatures, delta volumes, and clinical factors (classification accuracy [AUC]): (77.5% [0.73]) (train); (71.6% [0.69]) (test).

CONCLUSIONS

Delta radiomics and volumes can detect changes in nodule properties over time, which are predictive of nodule invasiveness. These tools could improve conventional radiologic assessment, allow for earlier intervention for aggressive nodules, and decrease unnecessary intervention-related morbidity.

AI-driven Characterization of Solid Pulmonary Nodules on CT Imaging for Enhanced Malignancy Prediction in Small-sized Lung Adenocarcinoma

OBJECTIVES

Distinguishing solid nodules from nodules with ground-glass lesions in lung cancer is a critical diagnostic challenge, especially for tumors ≤2 cm. Human assessment of these nodules is associated with high inter-observer variability, which is why an objective and reliable diagnostic tool is necessary. This study focuses on artificial intelligence (AI) to automatically analyze such tumors and to develop prospective AI systems that can independently differentiate highly malignant nodules.

MATERIALS AND METHODS

Our retrospective study analyzed 246 patients who were diagnosed with negative clinical lymph node metastases (cN0) using positron emission tomography-computed tomography (PET/CT) imaging and underwent surgical resection for lung adenocarcinoma. AI detected tumor sizes ≤2 cm in these patients. By utilizing AI to classify these nodules as solid (AI_solid) or non-solid (non-AI_solid) based on confidence scores, we aim to correlate AI determinations with pathological findings, thereby advancing the precision of preoperative assessments.

RESULTS

Solid nodules identified by AI with a confidence score ≥0.87 showed significantly higher solid component volumes and proportions in patients with AI_solid than in those with non-AI_solid, with no differences in overall diameter or total volume of the tumors. Among patients with AI_solid, 16% demonstrated lymph node metastasis, and a significant 94% harbored invasive adenocarcinoma. Additionally, 44% were upstaging postoperatively. These AI_solid nodules represented high-grade malignancies.

CONCLUSION

In small-sized lung cancer diagnosed as cN0, AI automatically identifies tumors as solid nodules ≤2 cm and evaluates their malignancy preoperatively. The AI classification can inform lymph node assessment necessity in sublobar resections, reflecting metastatic potential.

Clinical and radiomic factors for predicting invasiveness in pulmonary ground‑glass opacity

Patients with preinvasive or invasive pulmonary ground-glass opacity (GGO) often face different clinical treatments and prognoses. The present study aimed to identify the invasiveness of pulmonary GGO by analysing clinical and radiomic features. Patients with pulmonary GGOs who were treated between January 2014 and February 2019 were included. Clinical features were collected, while radiomic features were extracted from computed tomography records using the three-dimensional Slicer software. Predictors of GGO invasiveness were selected by least absolute shrinkage and selection operator logistic regression analysis, and receiver operating characteristic (ROC) curves were drawn for each prediction model. A total of 194 patients with pulmonary GGOs were included in the present study. The maximum diameter of the solid component, waveletHLL_ngtdm_Coarseness (P=0.03), waveletLHH_firstorder_Maximum (P<0.01) and waveletLLH_glrlm_LongRunEmphasis (P<0.01) were significant predictors of invasive lung GGOs. The area under the ROC curve (AUC) for the prediction models of clinical features and radiomic features was 0.755 and 0.719, respectively, whereas the AUC for the combined prediction model was 0.864 (95% CI, 0.802-0.926). Finally, a nomogram was established for individualized prediction of invasiveness. The combination of radiomic and clinical features can enable the differentiation between preinvasive and invasive GGOs. The present results can provide some basis for the best choice of treatment in patients with lung GGOs.

A radiomics nomogram for invasiveness prediction in lung adenocarcinoma manifesting as part-solid nodules with solid components smaller than 6 mm

Objective

To investigate whether radiomics can help radiologists and thoracic surgeons accurately predict invasive adenocarcinoma (IAC) manifesting as part-solid nodules (PSNs) with solid components <6 mm and provide a basis for rational clinical decision-making.

Materials and Methods

In total, 1,210 patients (mean age ± standard deviation: 54.28 ± 11.38 years, 374 men and 836 women) from our hospital and another hospital with 1,248 PSNs pathologically diagnosed with adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or IAC were enrolled in this study. Among them, 1,050 cases from our hospital were randomly divided into a derivation set (n = 735) and an internal validation set (n = 315), 198 cases from another hospital were used for external validation. Each labeled nodule was segmented, and 105 radiomics features were extracted. Least absolute shrinkage and selection operator (LASSO) was used to calculate Rad-score and build the radiomics model. Multivariable logistic regression was conducted to identify the clinicoradiological predictors and establish the clinical-radiographic model. The combined model and predictive nomogram were developed based on identified clinicoradiological independent predictors and Rad-score using multivariable logistic regression analysis. The predictive performances of the three models were compared via receiver operating characteristic (ROC) curve analysis. Decision curve analysis (DCA) was performed on both the internal and external validation sets to evaluate the clinical utility of the nomogram.

Results

The radiomics model showed superior predictive performance than the clinical-radiographic model in both internal and external validation sets (Az values, 0.884 vs. 0.810, p = 0.001; 0.924 vs. 0.855, p < 0.001, respectively). The combined model showed comparable predictive performance to the radiomics model (Az values, 0.887 vs. 0.884, p = 0.398; 0.917 vs. 0.924, p = 0.271, respectively). The clinical application value of the nomogram developed based on the Rad-score, maximum diameter, and lesion shape was confirmed, and DCA demonstrated that application of the Rad-score would be beneficial for radiologists predicting invasive lesions.

Conclusions

Radiomics has the potential as an independent diagnostic tool to predict the invasiveness of PSNs with solid components <6 mm.

Development and validation of a nomogram to assess postoperative venous thromboembolism risk in patients with stage IA non-small cell lung cancer

BACKGROUND

Venous thromboembolism (VTE) is a common postoperative complication in patients with lung cancer that seriously affects prognosis and quality of life. At present, the detection rate of patients with early-stage lung cancer is increasing, but there are few studies on the risk factors for postoperative venous thromboembolism (VTE) in patients with stage IA non-small cell lung cancer (NSCLC). This study aimed to establish a nomogram for predicting the probability of postoperative VTE risk in patients with stage IA NSCLC.

METHODS

The clinical data of 452 patients with stage IA NSCLC from January 2017 to January 2022 in our center were retrospectively analyzed and randomly divided into a training set and a validation set at a ratio of 7:3. Independent risk factors were identified by univariate and multivariate logistic regression analyses, and a nomogram was established based on the results and internally validated. The predictive power of the nomogram was evaluated by receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

RESULTS

The nomogram prediction model included three risk factors: age, preoperative D-dimer, and intermuscular vein dilatation. The areas under the ROC curve of this predictive model were 0.832 (95% CI: 0.732-0.924) and 0.791 (95% CI: 0.668-0.930) in the training and validation sets, respectively, showing good discriminative power. In addition, the probability of postoperative VTE occurrence predicted by the nomogram was consistent with the actual occurrence probability. In the decision curve, the nomogram model had a better net clinical benefit at a threshold probability of 5%-90%.

CONCLUSION

This study is the first to develop a nomogram for predicting the risk of postoperative VTE in patients with stage IA NSCLC; this nomogram can accurately and intuitively evaluate the probability of VTE in these patients and help clinicians make decisions on prevention and treatment.

A Novel Radiopathological Grading System to Tailor Recurrence Risk for Pathologic Stage IA Lung Adenocarcinoma

To validate the efficiency of pathologic grading system in pathologic stage IA lung adenocarcinoma (LUAD), and explore whether integrating preoperative radiological features would enhance the performance of recurrence discrimination. We retrospectively collected 510 patients with resected stage IA LUAD between January 2012 and December 2019 from Guangdong Provincial People's Hospital (GDPH). Pathologic grade classification of each case was based on the International Association for the Study of Lung Cancer (IASLC) pathologic staging system. Kaplan-Meier curves was used to assess the power of recurrence stratification. Concordance index (C-Index) and receiver operating characteristic curves (ROC) were used for evaluating the clinical utility of different grading systems for recurrence discrimination. Patients of lower IASLC grade showed improved recurrence-free survival (RFS) (P < 0.0001) where numerically difference was found between grade II and grade III (P = 0.119). By integrating the IASLC grading system and radiological feature, we found the RFS rate decreased as the novel radiopathological (RP) grading system increased (P < 0.0001). The difference of RFS curves between any 2 groups as per the RP grading system was statisticallysignificant (RP grade I vs RP grade II, p = 0.007; RP grade I vs RP grade III, P < 0.0001; RP grade II vs RP grade III, P = 0.0003). Compared with the IASLC grading system, the RP grading system remarkably improved recurrence survival discrimination (C-index: 0.822; area under the curve, 0.845). Integrating imaging features into pathologic grading system enhanced the efficiency of recurrence discrimination for resected stage IA LUAD and might help conduct subsequent management.

Detection and treatment of lung adenocarcinoma at pre-/minimally invasive stage: is it lead-time bias?

OBJECTIVES

This study investigates whether lead-time bias contributes to the excellent survival of AIS and MIA.

METHODS

We enrolled patients with resected adenocarcinoma from 2008 to 2012. Age, sex, smoke history, surgical approach, radiological features, invasive stage and postoperative follow-up data were documented. 1:1 PSM was performed to balance the influence of sex and smoking status on survival. After matching, the average age of the two groups was compared to calculate the lead time of diagnosis. The gain in life years for adenocarcinoma diagnosed at pre-/minimally invasive stage was estimated by subtracting the "lead time" and "median survival year of IAC" from "the life expectancy of AIS/MIA patients" referring to the Centre for Health and Information.

RESULTS

There were 124 AIS/MIA patients and 1148 IAC patients. The frequency of female and never-smoking patients in AIS/MIA group was much higher than that in IAC group. PSM analysis identified 124 patient pairs. No cancer-related death and recurrence were observed among AIS/MIA patients 5 years after surgery. For IAC patients, the 5-year disease-specific survival rate was 73.5% and the median survival is 13.5 years. The average age of AIS/MIA group and IAC group are 53.6 years and 58.2 years, respectively. The lead time between diagnosis of AIS/MIA and IAC is 4.6 years. Referring to the Centre for Health and Information, the life expectancy of patients with AIS/MIA diagnosed at 53.6 years old is 28.9 years. With adjustment for the lead time, the gain in life years for adenocarcinoma diagnosed at pre-/minimally invasive stage is 10.8 years.

CONCLUSIONS

With adjustment for the lead time between diagnosis of AIS/MIA and IAC, resecting lung adenocarcinoma at pre-/minimally invasive stage can improve life expectancy. The excellent survival of AIS/MIA is not lead-time bias.

Latest Clinical Evidence and Operative Strategy for Small-Sized Lung Cancers

Many thoracic surgeons revealed that consolidation tumor ratio or solid component size on thin-section computed tomography has been considered more prognostic than maximum tumor size in non-small cell lung cancer (NCSLC). According to the results, the 8th TNM classification drastically changed the staging system, i.e., clinical T category was determined based on the invasive or solid component size excluding a ground-glass opacity (GGO). However, several debates are arising over the application of radiological solid size for the clinical T staging. Meanwhile, recent several institutional reports have noticed a significantly simple fact that the presence of a GGO denotes an influence on the favorable prognosis of NSCLC. More important, radiologic pure-solid lung cancers without a GGO exhibit more malignant behaviors with regard to both the clinical and pathological aspects, and show several histologic types that have a poorer prognosis than radiologic part-solid lung cancer. In contrast, favorable prognostic impact of the presence of a GGO component was demonstrated, which was irrespective of the solid component size in cases in which the tumor showed a GGO component. Recently, this concept has been gradually noticed on a nationwide level. Obvious distinctions regarding the several baseline characteristics between the tumor with/without GGO component is a fundamental biological feature of early-stage lung cancer, which would result in a big difference in prognosis, modes of recurrence, overall behavior, and appropriate operative strategies. As a future perspective, the presence or absence of a GGO should be considered as an important parameter in the next clinical T classification.

Predictors of upstage and treatment strategies for stage IA lung cancers after sublobar resection for adenocarcinoma in situ and minimally invasive adenocarcinoma

Background

Invasive adenocarcinoma intraoperatively underestimated as adenocarcinoma in situ (AIS) or minimally invasive adenocarcinoma (MIA) based on frozen section (FS) is more likely to undergo insufficient resection. We aimed to investigate the predictors of upstage and treatment strategies for stage IA invasive adenocarcinoma after sublobar resection for AIS and MIA.

Methods

We identified 2,006 patients from January 2012 to December 2016 with early-stage lung adenocarcinoma who underwent sublobar resection based on FS diagnosis to guide surgical decision-making. All FS were categorized into three groups in real-time: (I) atypical adenomatous hyperplasia (AAH), (II) AIS, and (III) MIA.

Results

A total of 272 (13.5%, 272/2,006) cases were upstaged in the final pathology (FP) diagnosis (82 AAH to AIS, 127 AIS to MIA, and nine AIS and 54 MIA to invasive adenocarcinoma), and most upstage cases (64.3%, 175/272) were attributed to sampling error. Multivariate logistic regression showed that tumor size ≥1 cm was the only independent predictor of upstage. The upstage of 209 cases to AIS or MIA had no influence on the therapy because the extent of their resection was enough. Of the 63 cases upstaged to invasive adenocarcinoma, only 13 cases agreed to receive complementary treatment: five patients underwent complementary lobectomy, and seven patients received chemotherapy. Two invasive adenocarcinoma cases without complementary treatment experienced a local recurrence after surgery. No recurrence was observed in AAH, AIS and MIA. No patient died until December 01, 2019.

Conclusions

Timely complementary treatment is encouraged in AIS/MIA upstaged to invasive adenocarcinoma based on the FP after sublobar resection to avoid local recurrence. Pathologists should be more cautious about AIS and MIA with tumor size ≥1 cm to avoid underestimation and potentially insufficient resection.

Optimization of CT windowing for diagnosing invasiveness of adenocarcinoma presenting as sub-solid nodules

PURPOSE

To evaluate the optimal window setting to diagnose the invasiveness of lung adenocarcinoma in sub-solid nodules (SSNs).

METHODS

We retrospectively included 437 SSNs and randomly divided them 3:1 into a training group (327) and a testing group (110). The presence of a solid component was regarded as indicator of invasiveness. At fixed window level (WL) of 35 Hounsfield Units (HU), two readers adjusted the window width (WW) in the training group and recorded once a solid component appeared or disappeared on CT images acquired at 120 kVp. The optimal WW cut-off value to differentiate between invasive and pre-invasive lesions, based on the receiver operating characteristic (ROC) curve, was defined as "core" WW. The diagnostic performances of the mediastinal window setting (WW/WL, 350/35 HU) and core window setting were then compared in the testing group.

RESULTS

Of the 437 SSNs, 88 were pre-invasive [17 atypical adenomatous hyperplasia (AAH) and 71 adenocarcinoma in situ (AIS)], 349 were invasive [233 minimally invasive adenocarcinoma (MIA), 116 invasive adenocarcinoma (IA)]. In training group, the core WW of 1175 HU was the optimal cut-off to detect solid components of SSNs (AUC:0.79). In testing group, the sensitivity, specificity, positive, negative predictive value, and diagnostic accuracy for SSN invasiveness were 49.4%, 90.5%, 95.7%, 29.7%, and 57.3% for mediastinal window setting, and 87.6%, 76.2%, 91.6%, 76.2%, and 85.5% for core window setting.

CONCLUSION

At 120 kVp, core window setting (WW/WL, 1175/35 HU) outperformed the traditional mediastinal window setting to diagnose the invasiveness of SSNs.

Tumor Atelectasis Gives Rise to a Solid Appearance in Pulmonary Adenocarcinomas on High-Resolution Computed Tomography

Introduction

Ground-glass opacities in a high-resolution computed tomography (HR-CT) scan correlate, if malignant, with adenocarcinoma in situ. The solid appearance in the HR-CT is often considered indicative of an invasive component. This study aims to compare the radiologic features revealed in the HR-CT and the histologic features of primary adenocarcinomas in resection specimens to find the presence of tumor atelectasis in ground-glass nodules (GGNs) and part-solid and solid nodules.

Methods

HR-CT imaging was evaluated, and lung nodules were classified as GGNs, part-solid nodules, and solid nodules, whereas adenocarcinomas were classified according to WHO classification. Lepidic growth pattern with collapse was considered if there was reduction of air in the histologic section with maintained pulmonary architecture (without signs of pleural or vascular invasion).

Results

Radiologic and histologic features were compared in 47 lesions of 41 patients. The number of GGN, part-solid, and solid nodules were two, eight, and 37, respectively. Lepidic growth pattern with collapse was observed in both GGN, seven of the eight part-solid (88%) and 24 of the 37 solid (65%) lesions. Remarkably, more than 50% of the adenocarcinomas with a solid appearance in HR-CT imaging had a preexisting pulmonary architecture with adenocarcinoma with a predominant lepidic growth pattern. In these cases, the solid component can be explained by tumor-related collapse in vivo (tumor atelectasis on radiologic examination).

Conclusions

Tumor atelectasis is a frequent finding in pulmonary adenocarcinomas and may beside a ground glass opacity also result in a solid appearance in HR-CT imaging. A solid appearance on HR-CT cannot be attributed to invasion alone, as has been the assumption until now.

The Prognostic Significance of Pure Ground Glass Opacities in Lung Cancer Computed Tomographic Images

Objective: Pure ground-glass opacity (GGO) nodules have been detected with increasing frequency using computed tomography (CT). We performed a retrospective study to clarify whether lung cancer patient prognoses correlated with pure GGO nodules. We also analyzed the clinical characters of patients with pure GGO nodules to provide diagnostic guidance on lung cancer identification and treatment of patients in clinical practice.

Methods: We enrolled 39 of 1422 patients with pure GGO nodules who accepted surgical treatment of the lung cancer nodules, and reviewed materials from 404 patients to verify our conclusions. To discover which factors were prognostically significant, we used the Kaplan-Meier method to estimate the overall survival (OS) and progression-free survival (PFS) curves. Age, gender, smoking history, histology, tumor size, and stage were the factors examined in our study. We also performed subgroup and matching group analyses to clarify the correlation between the presence of pure GGO nodules and prognoses.

Results: Pure GGO nodules were associated with non-smoking females that had adenocarcinoma. The prognoses of patients in the pure GGO nodule group was better than those in the non-pure GGO nodule group (p = 0.046). Age, grade, and stage (including tumor size and lymph node metastases) were had prognostic significance. In the matching group stage assessments, although patient prognoses were not significantly different among patients of the GGO group compared with thoses of the other group in long-term, while in the short term, patients with pure GGO nodules had longer PFS. Non-smoking female patients with lung cancer were more likely to have adenocarcinoma.

Conclusions: As a subgroup of GGO nodules, pure GGO nodules predict a better prognosis in all lung cancer patients. Wheras our study showed that lung patients with pure GGO nodules in similar stages were not significantly different in long-term prognoses, in the short term; patients with pure GGO nodules had longer PFS.

Propensity-Matched Analysis Comparing Survival After Sublobar Resection and Lobectomy for cT1N0 Lung Adenocarcinoma

BACKGROUND

The optimal surgical method for cT1N0 lung adenocarcinoma remains controversial.

OBJECTIVE

The aim of this study was to evaluate the differences in clinical outcomes of sublobar resection and lobectomy for cT1N0 lung adenocarcinoma patients.

METHODS

We included 1035 consecutive patients with cT1N0 lung adenocarcinoma who underwent surgery at our institute from January 2011 to December 2016. The surgical approach, either sublobar resection or lobectomy, was determined at the discretion of each surgeon. A propensity-matched analysis incorporating total tumor diameter, solid component diameter, consolidation-to-tumor (C/T) ratio, and performance status was used to compare the clinical outcomes of the sublobar resection and lobectomy groups.

RESULTS

Sublobar resection and lobectomy were performed for 604 (58.4%; wedge resection/segmentectomy: 470/134) and 431 (41.6%) patients, respectively. Patients in the sublobar resection group had smaller total tumor diameters, smaller solid component diameters, lower C/T ratios, and better performance status. More lymph nodes were dissected in the lobectomy group. Patients in the sublobar resection group had better perioperative outcomes. A multivariable analysis revealed that the solid component diameter and serum carcinoembryonic antigen level are independent risk factors for tumor recurrence. After propensity matching, 284 paired patients in each group were included. No differences in overall survival (OS; p = 0.424) or disease-free survival (DFS; p = 0.296) were noted between the two matched groups.

CONCLUSIONS

Sublobar resection is not inferior to lobectomy regarding both DFS and OS for cT1N0 lung adenocarcinoma patients. Sublobar resection may be a feasible surgical method for cT1N0 lung adenocarcinoma.

Invasiveness and surgical timing evaluation by clinical features of ground-glass opacity nodules in lung cancers

Background

The early stages of lung cancer with ground‐glass opacity (GGO) pattern are detectable. However, it remains a challenge for physicians how best to treat GGO nodules as invasive tumors are occasionally found, even in pure GGO nodules. This study identified the invasiveness by the clinical features of the GGO nodules.

Methods

A retrospective review of patients with resected GGO nodules from August 2015 to February 2019 was performed. A total of 92 patients were enrolled and gender, age, tumor location, operation times, tumor size, histopathologic and radiological findings were analyzed.

Results

In this study, the sequential of GGO nodules invasiveness was significantly related to the tumor size and solid component. After regrouping the population into preinvasive and invasive groups, the invasiveness was significantly related to tumor size, solid component, tumor volume and maximal computed tomography (CT) value.

Conclusions

The invasiveness is difficult to evaluate according to the CT features only when the GGO nodules are less than 2 cm and consolidation/tumor ratio (C/T ratio) are less than 0.25. Tumor size and solid component are significant factors for predicting invasiveness. Part‐solid GGO nodules with a diameter greater than 1 cm require surgical consideration due to their high risk of invasiveness.

Radiomic signature: a non-invasive biomarker for discriminating invasive and non-invasive cases of lung adenocarcinoma

Purpose

We aimed to assess the classification performance of a computed tomography (CT)-based radiomic signature for discriminating invasive and non-invasive lung adenocarcinoma.

Patients and Methods

A total of 192 patients (training cohort, n=116; validation cohort, n=76) with pathologically confirmed lung adenocarcinoma were retrospectively enrolled in the present study. Radiomic features were extracted from preoperative unenhanced chest CT images to build a radiomic signature. Predictive performance of the radiomic signature were evaluated using an intra-cross validation cohort. Diagnostic performance of the radiomic signature was assessed via receiver operating characteristic (ROC) analysis.

Results

The radiomic signature consisted of 14 selected features and demonstrated good discrimination performance between invasive and non-invasive adenocarcinoma. The area under the ROC curve (AUC) for the training cohort was 0.83 (sensitivity, 0.84 ; specificity, 0.78; accuracy, 0.82), while that for the validation cohort was 0.77 (sensitivity, 0.94; specificity, 0.52 ; accuracy, 0.82).

Conclusion

The CT-based radiomic signature exhibited good classification performance for discriminating invasive and non-invasive lung adenocarcinoma, and may represent a valuable biomarker for determining therapeutic strategies in this patient population.

Multi-window CT based Radiomic signatures in differentiating indolent versus aggressive lung cancers in the National Lung Screening Trial: a retrospective study

Background

We retrospectively evaluated the capability of radiomic features to predict tumor growth in lung cancer screening and compared the performance of multi-window radiomic features and single window radiomic features.

Methods

One hundred fifty lung nodules among 114 screen-detected, incident lung cancer patients from the National Lung Screening Trial (NLST) were investigated. Volume double time (VDT) was calculated as the difference between continuous two scans and used to define indolent and aggressive lung cancers. Lung nodules were semi-automatically segmented using lung and mediastinal windows separately, and subtracting the mediastinal window region from the lung window region generated the difference region. 364 radiomic features were separately exacted from nodules using the lung window, the mediastinal window and the difference region. Multivariable models were conducted to identify the most predictive features in predicting tumor growth. Clinical information was also obtained from the database.

Results

Based on our definition, 26% of the cases were indolent lung cancer. The tumor growth pattern could be predicted by radiomic models constructed using features obtained in the lung window, the difference region, and by combining features obtained in both the lung window and difference regions with areas under the receiver operator characteristic (AUROCs) of 0.799, 0.819, and 0.846, respectively. The multi-window feature model showed better performance compared to single window features (P < 0.001). Incorporating clinical factors into the multi-window feature models showed improvement, yielding an accuracy of 84.67% and AUROC of 0.855 for distinguishing indolent from aggressive disease.

Conclusions

Multi-window CT based radiomics features are valuable predictors of indolent lung cancers and out performed single CT window setting. Combining clinical information improved predicting performance.

Electronic supplementary material

The online version of this article (10.1186/s40644-019-0232-6) contains supplementary material, which is available to authorized users.

Assessment of Image Quality and Dosimetric Performance of CT Simulators

BACKGROUND

CT simulator for radiation therapy aims to produce high-quality images for dose calculation and delineation of target and organs at risk in the process of treatment planning. Selection of CT imaging protocols that achieve a desired image quality while minimizing patient dose depends on technical CT parameters and their relationship with image quality and radiation dose. For similar imaging protocols using comparable technical CT parameters, there are also variations in image quality metrics between different CT simulator models. Understanding the relationship and variation is important for selecting appropriate imaging protocol and standardizing QC process. Here, we proposed an automated method to determine the relationship between image quality and radiation dose for various CT technical parameters.

MATERIAL AND METHOD

The impact of scan parameters on various aspects of image quality and volumetric CT dose index for a Philips Brilliance Big Bore and a Toshiba Aquilion One CT scanners were determined by using commercial phantom and automated image quality analysis software and cylindrical radiation dose phantom.

RESULTS AND DISCUSSION

Both scanners had very similar and satisfactory performance based on the diagnostic acceptance criteria recommended by ACR, International Atomic Energy Agency, and American Association of Physicists in Medicine. However, our results showed a compromise between different image quality components such as low-contrast and spatial resolution with the change of scanning parameters and revealed variations between the two scanners on their image quality performance. Measurement using a generic phantom and analysis by automated software was unbiased and efficient.

CONCLUSION

This method provides information that can be used as a baseline for CT scanner image quality and dosimetric QC for different CT scanner models in a given institution or across sites.

Incidental pulmonary nodules: characterization and management

This update covers the management of solitary or multiple pulmonary nodules detected incidentally in imaging studies done for other reasons. It describes the most appropriate computed tomography technique for the evaluation of these nodules, how they are classified, and how the different types of nodules are measured. It also reviews the patient-related and nodule-related criteria for determining the risk of malignancy. It discusses the recommendations in the guidelines recently published by the Fleischner Society for the management and follow-up of each type of nodules according to its size and risk of malignancy.

A Prediction Rule for Overall Survival in Non-Small-Cell Lung Cancer Patients with a Pathological Tumor Size Less Than 30 mm

We sought to develop and validate a clinical nomogram model for predicting overall survival (OS) in non-small-cell lung cancer (NSCLC) patients with resected tumors that were 30 mm or smaller, using clinical data and molecular marker findings. We retrospectively analyzed 786 NSCLC patients with a pathological tumor size less than 30 mm who underwent surgery between 2007 and 2017 at our institution. We identified and integrated significant prognostic factors to build the nomogram model using the training set, which was subjected to the internal data validation. The prognostic performance was calibrated and evaluated by the concordance index (C-index) and risk group stratification. Multivariable analysis identified the pathological tumor size, lymph node metastasis, and Ki-67 expression as independent prognostic factors, which were entered into the nomogram model. The nomogram-predicted probabilities of OS at 1 year, 3 years, and 5 years posttreatment represented optimal concordance with the actual observations. Harrell's C-index of the constructed nomogram with the training set was 0.856 (95% CI: 0.804-0.908), whereas TNM staging was 0.814 (95% CI: 0.742-0.886, P = 5.280221e − 13). Survival analysis demonstrated that NSCLC subgroups showed significant differences in the training and validation sets (P < 0.001). A nomogram model was established for predicting survival in NSCLC patients with a pathological tumor size less than 30 mm, which would be further validated using demographic and clinicopathological data. In the future, this prognostic model may assist clinicians during treatment planning and clinical studies.

Can Quantitative Volumetric Analysis Predict Tumor Recurrence in the Patients with Mucinous Adenocarcinoma of the Lung After Surgical Resection?

RATIONALE AND OBJECTIVES

Mucinous adenocarcinoma (MAC) is a distinct histologic variant subtype of lung adenocarcinomas. However, detailed radiologic findings and prognostic factors are still poorly understood. Thus, this study aimed to investigate the prognostic value of quantitative volumetric analysis of the computed tomography images of patients with MAC after. surgical resection.

MATERIALS AND METHODS

Semiautomatic segmentation from computed tomography images of 60 patients with pathologically confirmed MAC was performed and retrospectively reviewed. The main cutoff value in Hounsfield Units (HU) to predict tumor recurrence was defined by receiver-operating curve analysis. Solid volume of mass (SVM) was defined as the volume of HU greater than this cutoff, and solid ratio (Sratio) was defined as SVM divided by total volume. Each parameter was compared to clinicopathologic characteristics and maximum standardized uptake value. Disease-free survival (DFS) was assessed and was compared among patients. Univariate and multivariate Cox regression was performed to predict DFS of MAC.

RESULTS

The cutoff value of HU as determined by ROC analysis was 20 HU. SVM and Sratio were positively correlated with the maximum standardized uptake and pathologic invasion size, respectively (p < 0.001). SVM and Sratio were significantly higher in the recurrence group than in the no-recurrence group (p < 0.001). Multivariate Cox proportional hazards regression analysis revealed that the SVM (Hazard Ratio 1.016; 95% Confidence Interval 1.000-1.032; p = 0.048) and Sratio (Hazard Ratio 29.136; 95% Confidence Interval 1.419-598.191; p = 0.029) were independent significant predictors of DFS.

CONCLUSION

Quantitative volumetric parameters can predict the prognosis of patients with MAC after surgical resection.

Clinicopathological characteristics and treatment strategies for young lung cancer patients

Background

The reported age-specific survival rates of lung cancer patients have been largely inconsistent. Management strategies for younger patients and treatment outcomes are not well characterized.

Methods

Out of the 4,697 lung cancer patients with treatment history at Tokyo Medical University Hospital between January 2000 and December 2014, 266 patients were <49 years of age. Patient characteristics were investigated, and the association of overall survival (OS) with age, sex, stage, and histological type were investigated.

Results

The 1-, 3-, and 5-year survival rates in the ≤49 years age group were 82.9%, 64.6%, and 57.0%. Among surgical cases, the survival rate of patients in the ≤49 years age group was significantly better than that in the 50-69 and ≥70 years age groups (P=0.29 and P<0.0001, respectively). In comparison with the OS rate with clinical stages, I, II, and III (but not with clinical stage IV) in the older than 50 years age group, the rates in the ≤49 years age group were better. The 1-, 3-, and 5-year OS rates of females were higher than those of their males. The 1-, 3-, and 5-year OS rates for lung adenocarcinoma patients were higher than that of lung non-adenocarcinoma patients.

Conclusions

Despite the higher proportion of advanced disease, the postoperative survival rate of the younger was higher than that of the older. Aggressive multimodality treatments, including surgery, are more feasible and effective for younger patients as compared with that in older patients.

Lung Adenocarcinomas Manifesting as Radiological Part-Solid Nodules Define a Special Clinical Subtype

INTRODUCTION

The clinicopathologic features and prognostic predictors of radiological part-solid lung adenocarcinomas were unclear.

METHODS

We retrospectively compared the clinicopathologic features and survival times of part-solid tumors with those of pure ground glass nodules (pGGNs) and pure solid tumors treated with surgery at Fudan University Shanghai Cancer Center and evaluated the prognostic implications of consolidation-to-tumor ratio (CTR), solid component size, and tumor size for part-solid lung adenocarcinomas.

RESULTS

A total of 911 patients and 988 pulmonary nodules (including 329 part-solid nodules [PSNs], 501 pGGNs, and 158 pure solid nodules) were analyzed. More female patients (p = 0.015) and nonsmokers (p = 0.003) were seen with PSNs than with pure solid nodules. The prevalence of lymphatic metastasis was lower in patients with PSNs than in those with pure solid tumors (2.2% versus 27% [p < 0.001]). The 5-year lung cancer-specific (LCS) recurrence-free survival and LCS overall survival of patients with PSNs were worse than those of patients with pGGNs (p < 0.001 and p = .042, respectively) but better than those of patients with pure solid tumors ([p < 0.001 and p < 0.0001, respectively]). CTR (OR = 12.90; 95% confidence interval [CI]: 1.85-90.04), solid component size (OR = 1.45; 95% CI: 1.28-1.64), and tumor size (OR = 1.23; 95% CI: 1.15-1.31) could predict pathologic invasive adenocarcinoma for patients with PSNs. None of them could predict the prognosis. Patients receiving sublobar resection had prognoses comparable to those of patients receiving lobectomy (p = .178 for 5-year LCS recurrence-free survival and p = .319 for 5-year LCS overall survival). The prognostic differences between patients with systemic lymph node dissection and those without systemic lymph node dissection were statistically insignificant.

CONCLUSIONS

Part-solid lung adenocarcinoma showed clinicopathologic features different from those of pure solid tumor. CTR, solid component size, and tumor size could not predict the prognosis. Part-solid lung adenocarcinomas define one special clinical subtype.

Lung nodules: A comprehensive review on current approach and management

In daily clinical practice, radiologists and pulmonologists are faced with incidental radiographic findings of pulmonary nodules. Deciding how to manage these findings is very important as many of them may be benign and require no further action, but others may represent early disease and importantly early-stage lung cancer and require prompt diagnosis and definitive treatment. As the diagnosis of pulmonary nodules includes invasive procedures which can be relatively minimal, such as bronchoscopy or transthoracic aspiration or biopsy, but also more invasive procedures such as thoracic surgical biopsies, and as these procedures are linked to anxiety and to cost, it is important to have clearly defined algorithms for the description, management, and follow-up of these nodules. Clear algorithms for the imaging protocols and the management of positive findings should also exist in lung cancer screening programs, which are already established in the USA and which will hopefully be established worldwide. This article reviews current knowledge on nodule definition, diagnostic evaluation, and management based on literature data and mainly recent guidelines.

Predictive factors for invasive adenocarcinoma in patients with clinical non-invasive or minimally invasive lung cancer

Background

Pure ground glass opacity (GGO) or part-solid GGO with small solid component (≤5 mm) are likely to be non-invasive or minimally invasive lung cancer. However, those lesions sometimes are diagnosed as invasive adenocarcinoma postoperatively. The aim of this study was to determine the predictors of invasive adenocarcinoma in clinical non- or minimally invasive lung cancer.

Methods

From January 2010 to December 2017, 203 patients were diagnosed as clinical adenocarcinoma in situ (AIS) or minimally invasive adenocarcinoma (MIA) identified on chest computed tomography (CT) and they underwent surgical resection. A retrospective study was performed to analyze the prediction of invasive adenocarcinoma in clinical non- or minimally invasive lung cancer.

Results

Of all clinical AIS or MIA patients, invasive adenocarcinoma was diagnosed in 55 patients (27.1%). In clinical AIS, invasive adenocarcinoma was diagnosed in 19 patients (17.9%) and 36 patients (37.1%) were diagnosed as invasive adenocarcinoma in clinical MIA (P=0.002). Tumor diameter and the presence of solid component were confirmed to be significant predictive factors for invasive adenocarcinoma in a multivariate analysis [hazard ratio (HR) 1.071, P=0.037; HR 2.573, P=0.005; respectively].

Conclusions

Large tumor size and the presence of solid component in clinical AIS or MIA are predictive factors for invasive adenocarcinoma. Therefore, early surgical intervention is recommended for those lesions.

Preoperative Watchful-Waiting Time and Surgical Outcome of Patients with Non-small Cell Lung Cancer Found by Chest Low-Dose CT Screening

BACKGROUNDS

Chest low-dose CT screening (LDCTS) has been finding unprecedented numbers of peripheral non-small cell lung cancers (NSCLC) at an early stage and increased the number of patients with surgical indication. It is important to explore the influence of preoperative watchful-waiting time (WWT) on surgical outcomes. Objective is to clarify relationship between WWT and surgical outcomes of LDCTS-finding NSCLC from the view point of treatment delay.

METHODS

Total 283 cases of NSCLC, found by LDCTS and consecutively resected, were surveyed for preoperative WWT and surgical outcomes. Validity of the present guideline for management of pulmonary nodules detected by LDCTS was verified whether WWT before surgery was suitable for eradication of NSCLC.

RESULTS

The median value of WWT was 4.0 months in total, and the distribution of WWT exhibited long-tail-type pattern. That was 5.0 months in the group of pure ground-glass nodule (pGGN), 4.0 months in the group of part-solid nodule (PSN), and 1.7 months in the group of solid nodule (SON). During long-term postoperative observation time (median 79 months), 10-year progression-free survival rates were 100% in pGGN, 96% in PSN, and 72% in SON (P < .0001). They decreased significantly depending on enlargement of size: 91% or higher in size of 2 cm or smaller, and 71% or lower in size of larger than 2 cm (P < .0001).

CONCLUSIONS

Limited to LDCTS-finding nodules, surgical outcome will depend mainly on some malignant potential of NSCLC per se, rather than on duration of WWT or treatment delay.

Predictors of Pathologic Tumor Invasion and Prognosis for Ground Glass Opacity Featured Lung Adenocarcinoma

BACKGROUND

We make surgical strategies for ground glass opacity (GGO) nodules currently based on thin-section (TS) computed tomography (CT) findings. Whether radiologic measurements could precisely predict tumor invasion and prognosis of GGO-featured lung adenocarcinoma is uncertain.

METHODS

We retrospectively evaluated medical records of patients with radiologic GGO nodules undergoing a surgical procedure at Fudan University Shanghai Cancer Center. The study endpoints were the predictive value and prognostic significance of radiologic measurements (consolidation-to-tumor ratio value, consolidation size, and tumor size) for pathologic lung adenocarcinoma.

RESULTS

In this study 736 patients and 841 GGO nodules were included. Five-year lung cancer-specific regression-free survival (LCS-RFS) rate was 95.76% (95% confidence interval [CI], 93.01% to 97.44%). The 5-year LCS overall survival (OS) rate was 98.99% (95% CI, 97.69% to 99.57%). Multivariable analysis showed that tumor invasion (invasive adenocarcinoma [IAD] vs adenocarcinoma in situ [AIS]/minimally invasive adenocarcinoma [MIA], p = 0.020) was the only independent predictor for 5-year LCS-RFS. IAD (hazard ratio, 15.98; 95% CI, 1.55 to 164.35) was correlated with a higher risk of recurrence. Kaplan-Meier analysis showed that only tumor invasion status (IAD vs AIS/MIA, p = 0.003) could predict 5-year lung cancer-specific overall survival (LCS-OS), and IAD had a worse LCS-OS than AIS and MIA. A part-solid component (odds ratio [OR], 9.09; 95% CI, 2.71 to 30.47; p = 0.000), large consolidation size (OR, 3.11; 95% CI, 1.03 to 9.40; p = 0.045), and large tumor size (OR, 5.48; 95% CI, 2.68 to 11.19; p = 0.000) were associated with pathologic IAD. For IAD ≤ 20 mm, segmentectomy and lobectomy had better 5-year LCS-RFS than wedge resection, although the difference was statistically insignificant (p = 0.367). The three types of surgeries provided the similar 5-year LCS-OS (p = 0.834).

CONCLUSIONS

Radiologic measurements could not precisely predict tumor invasion and prognosis. Making treatment strategies solely according to TS-CT findings for GGO tumor is inappropriate.

Effect of CT window settings on size measurements of the solid component in subsolid nodules: evaluation of prediction efficacy of the degree of pathological malignancy in lung adenocarcinoma

OBJECTIVE

To investigate the predictive value of size measurements of the solid components in pulmonary subsolid nodules with different CT window settings and to evaluate the degree of pathological malignancy in lung adenocarcinoma.  Methods: The preoperative chest CT images and pathological data of 125 patients were retrospectively evaluated. The analysis included 127 surgically resected lung adenocarcinomas that manifested as subsolid nodules. All subsolid nodules were divided into two groups: 69 in group A, including 22 adenocarcinomas in situ (AIS) and 47 minimally invasive adenocarcinomas (MIA); 58 in group B that included invasive pulmonary adenocarcinomas (IPA). The size of the solid component in the pulmonary subsolid nodules were calculated in one dimensional, two dimensional and three dimensional views using lung and mediastinal windows that were recorded as 1D-SCLW, 2D-SCLW, 3D-SCLW, 1D-SCMW, 2D-SCMW and 3D-SCMW, respectively. Furthermore, the volume of solid component with a threshold of -300HU was measured using lung window (3D-SCT). All the quantitative features were evaluated by the Mann-Whitney U test. Multivariate analysis was used to identify the significant predictor of the degree of pathological malignancy.  Results: The 1D-SCLW, 2D-SCLW, 3D-SCLW, 1D-SCMW, 2D-SCMW, 3D-SCMW and 3D-SCT views of group B were significantly larger than those of group A (p < 0.001). The multivariate logistic regression analysis indicated that 3D-SCT (OR = 1.018, 95%CI: 1.005 ~ 1.03, p <0.05＝was the independent predictive factor. The larger SCT was significantly associated with IPAs.  Conclusion: 3D-SCT of subsolid nodules during preoperative CT can be used to predict the degree of pathological malignancy in lung adenocarcinoma, which may provide a more objective and convenient selection criterion for clinical application.  Advances in knowledge:  Applying threshold of -300 HU with lung window setting would be better than other window setting for the evaluation of solid component in subsolid nodules. Computer-aided volumetry of the solid component in subsolid nodules can more accurately predict the degree of pathological malignancy than the other dimensional measurements.

Planning and marking for thoracoscopic anatomical segmentectomies

Although sublobar resection (SLR) for treating non-small cell lung carcinoma (NSCLC) is still controversial, thoracoscopic segmentectomy is rising. Performing it by closed chest surgery is complex as it means confirming the location of the lesion, identifying vascular and bronchial structures, preserving venous drainage of adjacent segments, severing the intersegmental plane and ensuring an oncological safety margin with no manual palpation and different landmarks. Accurate planning is mandatory. We discuss in this article the interest of 3D reconstruction and mapping technics to enhance safety and reliability of these procedures.

Subsolid Lung Nodule Classification: A CT Criterion for Improving Interobserver Agreement

Purpose To evaluate an objective computed tomographic (CT) criterion for distinguishing between part-solid (PS) and nonsolid (NS) lung nodules. Materials and Methods This study received institutional review board approval, and patients gave informed consent. Preoperative CT studies in all patients who underwent surgery for subsolid nodules between 2008 and 2015 were first reviewed by two senior radiologists, who subjectively classified the nodules as PS or NS. A second reading performed 1 month later used predefined classification criteria and involved a third senior radiologist as well as three junior radiologists. Subsolid nodules were classified as PS if a solid portion was detectable in the mediastinal window setting (nonmeasurable, < 50%, or > 50% of the entire nodule) and were otherwise classified as NS (subclassified as pure or heterogeneous). Interreader agreement was assessed with κ statistics and the intraclass correlation coefficient (ICC). Results A total of 99 nodules measuring a median of 20 mm (range, 5-47 mm) in lung window CT images were analyzed. Senior radiologist agreement on the PS/NS distinction increased from moderate (κ = 0.54; 95% confidence interval [CI]: 0.37, 0.71) to excellent (κ = 0.89; 95% CI: 0.80, 0.98) between the first and second readings. At the second readings, agreement among senior and junior radiologists was excellent for PS/NS distinction (ICC = 0.87; 95% CI: 0.83, 0.90) and for subcategorization (ICC = 0.82; 95% CI: 0.77, 0.87). When a solid portion was measurable in the mediastinal window, the specificity for adenocarcinoma invasiveness ranged from 86% to 96%. Conclusion Detection of a solid portion in the mediastinal window setting allows subsolid nodules to be classified as PS with excellent interreader agreement. If the solid portion is measurable, the specificity for adenocarcinoma invasiveness is high. ^© RSNA, 2017 Online supplemental material is available for this article.

Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017

The Fleischner Society Guidelines for management of solid nodules were published in 2005, and separate guidelines for subsolid nodules were issued in 2013. Since then, new information has become available; therefore, the guidelines have been revised to reflect current thinking on nodule management. The revised guidelines incorporate several substantive changes that reflect current thinking on the management of small nodules. The minimum threshold size for routine follow-up has been increased, and recommended follow-up intervals are now given as a range rather than as a precise time period to give radiologists, clinicians, and patients greater discretion to accommodate individual risk factors and preferences. The guidelines for solid and subsolid nodules have been combined in one simplified table, and specific recommendations have been included for multiple nodules. These guidelines represent the consensus of the Fleischner Society, and as such, they incorporate the opinions of a multidisciplinary international group of thoracic radiologists, pulmonologists, surgeons, pathologists, and other specialists. Changes from the previous guidelines issued by the Fleischner Society are based on new data and accumulated experience. ^© RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on March 13, 2017.

Value of window technique in diagnosis of the ground glass opacities in patients with non-small cell pulmonary cancer

The aim of the present study was to examine the value of window technique in qualitative diagnosis of the ground glass opacities (GGO) in patients with non-small cell pulmonary cancer. A total of 124 clinically suspected pulmonary cancer patients were analyzed retrospectively. The lesions were affirmed by puncture biopsy, and were GGO on pulmonary window while were invisible on mediastinal window. Sixty-four multi-detector spiral computed tomography with the window width and window level of 1,500 Hounsfield units (HU) and −450 HU on pulmonary window, while the window width and window level of 400 and 40 HU on mediastinal window, was used in the study. The window adjustment technique was used to analyze the window width and window level of lesion on pulmonary window and mediastinal window, for searching invisible threshold on 3-megapixel medical displays. The diagnostic accuracy and the cut-off value were compared on receiver operating characteristic (ROC) curve. The results showed that the window width and window level on pulmonary window and mediastinal window of malignant lesions were significantly less than those of benign ones (P<0.05). The cut-off value on pulmonary window was the window width and window level of 1,300 and −220 HU, the area under the ROC was 0.830 [sensitivity was 72.5%, specificity was 84.3%; 95% confidence interval (CI), 0.712–0.945]. The cut-off value on mediastinal window was the window width and window level of 360 and 30 HU, and the area under the ROC was 0.623 (was 62.0%, specificity was 55.7%; 95% CI, 0.541–0.745). In conclusion, the window technique has high sensitivity and accuracy in qualitative diagnosis of the GGO.