Internal growth of nonsolid lung nodules: radiologic-pathologic correlation

Prospective Radiologic-Pathologic Correlation of Macroscopic Volume and Microscopic Extension of Nonsolid Lung Nodules on Thin-section CT Images for Sublobar Resection and Stereotactic Radiotherapy Planning

INTRODUCTION

The objective of this study was to determine whether computed tomography (CT) could be a useful tool for nonsolid lung nodule (NSN) treatment planning, surgery or stereotactic body radiation therapy (SBRT), by assessing the macroscopic and microscopic extension of these nodules.

METHODS

The study prospectively included 23 patients undergoing anatomic resection at the Foch Hospital in 2020/2021 for NSN with a ground-glass component of more than 50%. Firstly, for each patient, both the macroscopic dimensions of the NSN were assessed on CT and during pathologic analysis. Secondly, the microscopic extension was assessed during pathologic examination. Wilcoxon sign rank tests were used to compare these dimensions. Spearman correlation test and Bland-Altman analysis were used to evaluate the agreement between radiological and pathologic measurements.

RESULTS

On CT, the median largest diameter and volume of NSN were 21 mm and 3780 cc, while on pathologic analysis, they were 15 mm and 1800 cc, respectively. Therefore, the largest diameter and volume of the NSN were significantly higher on CT than on pathological analysis. For microscopic extension, the median largest diameter and volume of NSN were 17 mm and 2040 cc, respectively. No significant difference was observed between the macroscopic size and the microscopic extension assessed during pathologic analysis. Moreover, correlation analysis and Bland-Altman plots showed that radiological and pathologic measurements could provide equivalent precision.

CONCLUSION

Our study showed that CT did not underestimate the macroscopic size and microscopic extension of NSN and confirmed that CT can be used for NSN treatment planning.

Qualitative (and Quantitative) Values of the Lung-RADS and Computed Tomography in Diagnosing Solitary Pulmonary Nodules

Background: Lung-RADS classification and CT signs can both help in the differential diagnosis of SPNs. The purpose of this study was to investigate the diagnostic value of these two methods and the combination of the two methods for solitary pulmonary nodules (SPNs). Methods: A total of 296 cases of SPNs were retrospectively analyzed. All the SPNs were classified according to the Lung-RADS grading version 1.1. The scores of each lesion were calculated according to their CT signs. Imaging features, such as the size and margin of the lesions, pleural traction, spiculation, lobulation, bronchial cutoff, air bronchogram, vacuoles, tumor vasculature, and cavity signs, were analyzed. The imaging results were compared with the pathology examination findings. Receiver operating characteristic (ROC) curves were applied to compare the values of the different methods in differentially diagnosing benign and malignant SPNs. Results: The sensitivity, specificity, and accuracy of Lung-RADS grading for diagnosing SPNs were 34.0%, 94.4%, and 47.6%, respectively. The area under the ROC curve (AUC) was 0.600 (p < 0.001). The sensitivity, specificity, and accuracy of the CT sign scores were 56.3%, 70.0%, and 60.5%, respectively, and the AUC was 0.657 (p < 0.001). The sensitivity, specificity, and accuracy of the combination of the two methods for diagnosing SPNs were 93.2%, 61.1%, and 83.5%, and the AUC was 0.777 (p < 0.001). Conclusion: The combination of Lung-RADS classification and CT signs significantly improved the differential diagnosis of SPNs.

Precise characterization of a solitary pulmonary nodule using tumor shadow disappearance rate-corrected F-18 FDG PET and enhanced CT

We aimed to characterize solitary pulmonary nodule (SPN) using imaging parameters for F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) or enhanced CT corrected by tumor shadow disappearance rate (TDR) to reflect the tissue density.We enrolled 51 patients with an SPN who underwent PET/CT and chest CT with enhancement. The FDG uptake of SPN was evaluated using maximum standardized uptake value (SUVmax) on PET/CT. The mean Hounsfield unit (HU) for each SPN was evaluated over the region of interest on nonenhanced and enhanced CT images. The change in mean HU (HUpeak-pre) was quantified by subtracting the mean HU of the preenhanced CT from that of the post-enhanced CT. TDR was defined as the ratio of the tumor area, which disappears at a mediastinal window, to the tumor area of the lung window. We investigated which parameters (SUVmax or HUpeak-pre) could contribute to the characterization of SPN classified by TDR value and whether diagnostic performance could be improved using TDR-corrected imaging parameters.For SPN with higher tissue density (TDR <42%, n = 22), high value of SUVmax (≥3.1) was a significant factor to predict malignancy (P = .006). High value of HUpeak-pre (≥38) was a significant factor to characterize SPN (P = .002) with lower tissue density (TDR ≥42%, n = 29). The combined approach using TDR-corrected parameters had better predictive performance to characterize SPN than SUVmax only (P = .031).Applying imaging parameters such as SUVmax or HUpeak-pre in consideration of tissue density calculated with TDR could contribute to accurate characterization of SPN.

Predicting the histological invasiveness of pulmonary adenocarcinoma manifesting as persistent pure ground-glass nodules by ultra-high-resolution CT target scanning in the lateral or oblique body position

Background

Ultra-high-resolution computed tomography (U-HRCT) has improved image quality for displaying the detailed characteristics of disease states and lung anatomy. The purpose of this study was to retrospectively examine whether U-HRCT target scanning in the lateral or oblique body position (protocol G scan) could predict histological invasiveness of pulmonary adenocarcinoma manifesting as pure ground-glass nodules (pGGNs).

Methods

From January 2015 to December 2016, 260 patients with 306 pathologically confirmed pGGNs who underwent preoperative protocol G scans were retrospectively reviewed and analyzed. The U-HRCT findings of preinvasive lesions [atypical adenomatous hyperplasias (AAH) and adenocarcinomas in situ (AIS)] and invasive pulmonary adenocarcinomas [minimally invasive adenocarcinomas (MIA) and invasive adenocarcinomas (IAC)] were manually compared and analyzed using orthogonal multiplanar reformation (MPR) images. The logistic regression model was established to determine variables that could predict the invasiveness of pGGNs. Receiver operating characteristic (ROC) curve analysis was performed to evaluate their diagnostic performance.

Results

There were 213 preinvasive lesions (59 AAHs and 154 AISs) and 93 invasive pulmonary adenocarcinomas (53 MIAs and 40 IACs). Compared with the preinvasive lesions, invasive adenocarcinomas exhibited a larger diameter (13.5 vs. 9.3 mm, P=0.000), higher mean attenuation (-571 vs. -613 HU, P=0.002), higher representative attenuation (-475 vs. -547 HU, P=0.000), lower relative attenuation (-339 vs. -292 HU, P=0.000) and greater frequencies of heterogeneity (P=0.001), air bronchogram (P=0.000), bubble lucency (P=0.000), and pleural indentation (P=0.000). Multiple logistic analysis revealed that larger diameter [odds ratio (OR), 1.328; 95% CI: 1.208-1.461; P=0.000] and higher representative attenuation (OR, 1.005; 95% CI: 1.003-1.007; P=0.000) were significant predictive factors of invasive pulmonary adenocarcinomas from preinvasive lesions. The optimal cut-off value of the maximum diameter for invasive pulmonary adenocarcinomas was larger than 10 mm (sensitivity, 66.7%; specificity, 72.8%).

Conclusions

The imaging features based on protocol G scanning can effectively help predict the histological invasiveness of pGGNs. The maximum diameter and representative attenuation are important parameters for predicting invasiveness.

Prediction of the Growth Rate of Early-Stage Lung Adenocarcinoma by Radiomics

Objectives

To investigate the value of imaging in predicting the growth rate of early lung adenocarcinoma.

Methods

From January 2012 to June 2018, 402 patients with pathology-confirmed lung adenocarcinoma who had two or more thin-layer CT follow-up images were retrospectively analyzed, involving 407 nodules. Two complete preoperative CT images and complete clinical data were evaluated. Training and validation sets were randomly assigned according to an 8:2 ratio. All cases were divided into fast-growing and slow-growing groups. Researchers extracted 1218 radiomics features from each volumetric region of interest (VOI). Then, radiomics features were selected by repeatability analysis and Analysis of Variance (ANOVA); Based on the Univariate and multivariate analyses, the significant radiographic features is selected in training set. A decision tree algorithm was conducted to establish the radiographic model, radiomics model and the combined radiographic-radiomics model. Model performance was assessed by the area under the curve (AUC) obtained by receiver operating characteristic (ROC) analysis.

Results

Sixty-two radiomics features and one radiographic features were selected for predicting the growth rate of pulmonary nodules. The combined radiographic-radiomics model (AUC 0.78) performed better than the radiographic model (0.727) and the radiomics model (0.710) in the validation set.

Conclusions

The model has good clinical application value and development prospects to predict the growth rate of early lung adenocarcinoma through the combined radiographic-radiomics model.

A comparison of ultra-high-resolution CT target scan versus conventional CT target reconstruction in the evaluation of ground-glass-nodule-like lung adenocarcinoma

Background

The aim of this study was to determine whether the clinical value of scanned computed tomography (CT) images is higher when using ultra-high-resolution CT (U-HRCT) target scanning than conventional CT target reconstruction scanning in the evaluation of ground-glass-nodule (GGN)-like lung adenocarcinoma.

Methods

A total of 91 consecutive patients with isolated GGN-like lung adenocarcinoma were included in this study from April 2017 to June 2018. U-HRCT and conventional CT scans were conducted in all enrolled patients. Two experienced thoracic radiologists independently assessed image quality and made diagnoses. Based on the pathological results, the accuracies of U-HRCT target scanning and conventional CT target reconstruction for detecting morphological features on CT, including spiculation of GGNs, bronchial vascular bundles, solid components in the nodules, burr, vacuole, air bronchial signs, and fissure distortion, were calculated. All statistical analyses were performed using SPSS 17.0 software. Enumeration data were tested using the Chi-square test. A P value of <0.05 was considered statistically significant.

Results

When both techniques were compared with the pathological findings, the detection rate for CT images obtained using U-HRCT target scanning and conventional CT target reconstruction with regard to the spiculation of GGNs, bronchial vascular bundles, and solid components in the nodules were 78% vs. 61.5%, 72.5% vs. 54.9%, 65.9% vs. 49.5%, respectively. The presence of the spiculation of GGNs, bronchial vascular bundles, and solid components in the nodules in U-HRCT target scanning was significantly higher than that in conventional CT target reconstruction (all P<0.05). However, no significant difference was observed between the two techniques with regard to the burr, vacuole, air bronchial signs, and fissure distortion (all P>0.05).

Conclusions

When viewing GGNs, the detection rate was higher for U-HRCT target scanning than for conventional CT target reconstruction, and this improvement significantly enhanced the diagnostic accuracy of early lung adenocarcinoma.

Modified Quality Threshold Clustering for Temporal Analysis and Classification of Lung Lesions

Lung cancer is the type of cancer that most often kills after the initial diagnosis. To aid the specialist in its diagnosis, temporal evaluation is a potential tool for analyzing indeterminate lesions, which may be benign or malignant, during treatment. With this goal in mind, a methodology is herein proposed for the analysis, quantification, and visualization of changes in lung lesions. This methodology uses a modified version of the quality threshold clustering algorithm to associate each voxel of the lesion to a cluster, and changes in the lesion over time are defined in terms of voxel moves to another cluster. In addition, statistical features are extracted for classification of the lesion as benign or malignant. To develop the proposed methodology, two databases of pulmonary lesions were used, one for malignant lesions in treatment (public) and the other for indeterminate cases (private). We determined that the density change percentage varied from 6.22% to 36.93% of lesion volume in the public database of malignant lesions under treatment and from 19.98% to 38.81% in the private database of lung nodules. Additionally, other inter-cluster density change measures were obtained. These measures indicate the degree of change in the clusters and how each of them is abundant in relation to volume. From the statistical analysis of regions in which the density changes occurred, we were able to discriminate lung lesions with an accuracy of 98.41%, demonstrating that these changes can indicate the true nature of the lesion. In addition to visualizing the density changes occurring in lesions over time, we quantified these changes and analyzed the entire set through volumetry, which is the technique most commonly used to analyze changes in pulmonary lesions.

Updating the role of FDG PET/CT for evaluation of lung cancer manifesting in nonsolid nodules

PURPOSE

To assess the feasibility of using CT to correct specific uptake values (SUVs) for fluorodeoxyglucose (FDG) in patients with nonsolid nodules.

METHODS

Patients with FDG-PET/CT and thin-section CT were included in this pilot study. Thirty-five adenocarcinomas manifesting as nonsolid nodules were classified into two groups; 90-100% and 1-89% lepidic component. SUVmax was corrected based on the CT determination of the proportion of soft tissue component within the cancer (SUVatt).

RESULTS

Both SUVmax and SUVatt increased as the percentage of the lepidic component decreased. SUVmax and SUVatt were significantly different between the groups.

CONCLUSION

Extent of invasiveness of nonsolid cancers (as a marker of aggressiveness) can potentially be quantified by PET/CT using a correction method that accounts for the proportion of soft tissue within the tumor.

Comprehensive Computed Tomography Radiomics Analysis of Lung Adenocarcinoma for Prognostication

BACKGROUND

In this era of personalized medicine, there is an expanded demand for advanced imaging biomarkers that reflect the biology of the whole tumor. Therefore, we investigated a large number of computed tomography-derived radiomics features along with demographics and pathology-related variables in patients with lung adenocarcinoma, correlating them with overall survival.

MATERIALS AND METHODS

Three hundred thirty-nine patients who underwent operation for lung adenocarcinoma were included. Analysis was performed using 161 radiomics features, demographic, and pathologic variables and correlated each with patient survival. Prognostic performance for survival was compared among three models: (a) using only clinicopathological data; (b) using only selected radiomics features; and (c) using both clinicopathological data and selected radiomics features.

RESULTS

At multivariate analysis, age, pN, tumor size, type of operation, histologic grade, maximum value of the outer 1/3 of the tumor, and size zone variance were statistically significant variables. In particular, maximum value of outer 1/3 of the tumor reflected tumor microenvironment, and size zone variance represented intratumor heterogeneity. Integration of 31 selected radiomics features with clinicopathological variables led to better discrimination performance.

CONCLUSION

Radiomics approach in lung adenocarcinoma enables utilization of the full potential of medical imaging and has potential to improve prognosis assessment in clinical oncology.

IMPLICATIONS FOR PRACTICE

Two radiomics features were prognostic for lung cancer survival at multivariate analysis: (a) maximum value of the outer one third of the tumor reflects the tumor microenvironment and (b) size zone variance represents the intratumor heterogeneity. Therefore, a radiomics approach in lung adenocarcinoma enables utilization of the full potential of medical imaging and could play a larger role in clinical oncology.

Statistical tools for the temporal analysis and classification of lung lesions

BACKGROUND AND OBJECTIVE

Lung cancer remains one of the most common cancers globally. Temporal evaluation is an important tool for analyzing the malignant behavior of lesions during treatment, or of indeterminate lesions that may be benign. This work proposes a methodology for the analysis, quantification, and visualization of small (local) and large (global) changes in lung lesions. In addition, we extract textural features for the classification of lesions as benign or malignant.

METHODS

We employ the statistical concept of uncertainty to associate each voxel of a lesion to a probability that changes occur in the lesion over time. We employ the Jensen divergence and hypothesis test locally to verify voxel-to-voxel changes, and globally to capture changes in lesion volumes.

RESULTS

For the local hypothesis test, we determine that the change in density varies by between 3.84 and 40.01% of the lesion volume in a public database of malignant lesions under treatment, and by between 5.76 and 35.43% in a private database of benign lung nodules. From the texture analysis of regions in which the density changes occur, we are able to discriminate lung lesions with an accuracy of 98.41%, which shows that these changes can indicate the true nature of the lesion.

CONCLUSION

In addition to the visual aspects of the density changes occurring in the lesions over time, we quantify these changes and analyze the entire set using volumetry. In the case of malignant lesions, large b-divergence values are associated with major changes in lesion volume. In addition, this occurs when the change in volume is small but is associated with significant changes in density, as indicated by the histogram divergence. For benign lesions, the methodology shows that even in cases where the change in volume is small, a change of density occurs. This proves that even in lesions that appear stable, a change in density occurs.

X-ray Dark-field Radiography - In-Vivo Diagnosis of Lung Cancer in Mice

Accounting for about 1.5 million deaths annually, lung cancer is the prevailing cause of cancer deaths worldwide, mostly associated with long-term smoking effects. Numerous small-animal studies are performed currently in order to better understand the pathogenesis of the disease and to develop treatment strategies. Within this letter, we propose to exploit X-ray dark-field imaging as a novel diagnostic tool for the detection of lung cancer on projection radiographs. Here, we demonstrate in living mice bearing lung tumors, that X-ray dark-field radiography provides significantly improved lung tumor detection rates without increasing the number of false-positives, especially in the case of small and superimposed nodules, when compared to conventional absorption-based imaging. While this method still needs to be adapted to larger mammals and finally humans, the technique presented here can already serve as a valuable tool in evaluating novel lung cancer therapies, tested in mice and other small animal models.

Improved image quality and diagnostic potential using ultra-high-resolution computed tomography of the lung with small scan FOV: A prospective study

The aim of this study was to assess whether CT imaging using an ultra-high-resolution CT (UHRCT) scan with a small scan field of view (FOV) provides higher image quality and helps to reduce the follow-up period compared with a conventional high-resolution CT (CHRCT) scan. We identified patients with at least one pulmonary nodule at our hospital from July 2015 to November 2015. CHRCT and UHRCT scans were conducted in all enrolled patients. Three experienced radiologists evaluated the image quality using a 5-point score and made diagnoses. The paired images were displayed side by side in a random manner and annotations of scan information were removed. The following parameters including image quality, diagnostic confidence of radiologists, follow-up recommendations and diagnostic accuracy were assessed. A total of 52 patients (62 nodules) were included in this study. UHRCT scan provides a better image quality regarding the margin of nodules and solid internal component compared to that of CHRCT (P < 0.05). Readers have higher diagnostic confidence based on the UHRCT images than of CHRCT images (P<0.05). The follow-up recommendations were significantly different between UHRCT and CHRCT images (P<0.05). Compared with the surgical pathological findings, UHRCT had a relative higher diagnostic accuracy than CHRCT (P > 0.05). These findings suggest that the UHRCT prototype scanner provides a better image quality of subsolid nodules compared to CHRCT and contributes significantly to reduce the patients' follow-up period.

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.

Volumes Learned: It Takes More Than Size to "Size Up" Pulmonary Lesions

RATIONALE AND OBJECTIVES

This study aimed to review the current understanding and capabilities regarding use of imaging for noninvasive lesion characterization and its relationship to lung cancer screening and treatment.

MATERIALS AND METHODS

Our review of the state of the art was broken down into questions about the different lung cancer image phenotypes being characterized, the role of imaging and requirements for increasing its value with respect to increasing diagnostic confidence and quantitative assessment, and a review of the current capabilities with respect to those needs.

RESULTS

The preponderance of the literature has so far been focused on the measurement of lesion size, with increasing contributions being made to determine the formal performance of scanners, measurement tools, and human operators in terms of bias and variability. Concurrently, an increasing number of investigators are reporting utility and predictive value of measures other than size, and sensitivity and specificity is being reported. Relatively little has been documented on quantitative measurement of non-size features with corresponding estimation of measurement performance and reproducibility.

CONCLUSIONS

The weight of the evidence suggests characterization of pulmonary lesions built on quantitative measures adds value to the screening for, and treatment of, lung cancer. Advanced image analysis techniques may identify patterns or biomarkers not readily assessed by eye and may also facilitate management of multidimensional imaging data in such a way as to efficiently integrate it into the clinical workflow.

Quantitative CT Scanning Analysis of Pure Ground-Glass Opacity Nodules Predicts Further CT Scanning Change

BACKGROUND

We sought to determine whether quantitative analysis of lung adenocarcinoma manifesting as a ground-glass opacity (GGO) nodule (GGN) on initial CT scans can predict further CT scanning change or rate of growth.

METHODS

This retrospective study included patients with lung adenocarcinoma manifesting as pure GGN on initial CT scans who were followed up with interval CT scanning until resection. All pure GGNs were classified based on CT scanning interval change in three subgroups as follows: group A (development of solid component), group B (growth of GGO component), and group C (no change in size). Nodule size, volume, density, mass, and CT scanning attenuation values were assessed from initial CT data sets.

RESULTS

Fifty-four pure GGNs were enrolled and classified into group A (n = 9), group B (n = 25), and group C (n = 20). Nodule size, volume, mass, and density of the GGNs in each subgroup were not significantly different. The 97.5th percentile CT scanning attenuation value and slope of CT scanning attenuation values from the 2.5th to the 97.5th percentile were significantly different among the three subgroups (P = .02, P < .00). Three of nine (33%) pure GGNs showing a new solid component developed a solid component within 6 months.

CONCLUSIONS

The 97.5th percentile CT scanning attenuation value and slope of CT scanning attenuation values from the 2.5th to the 97.5th percentile could be helpful in predicting future CT scanning change and growth rate of pure GGNs. Pure GGNs showing higher 97.5th percentile CT scanning attenuation values and steeper slopes of CT scanning attenuation values may require more frequent follow-up than the usual interval of 6 months.

[Three-dimensional Mass Measurement of Subsolid Pulmonary Nodules on Chest CT: Intra and Inter-observer Variability]

背景与目的

肺内亚实性结节（包括磨玻璃密度结节和部分实性结节）体积增长常较缓慢，但恶性概率比实性结节大，常需随访确定其生长特性。恶性亚实性结节的生长性不仅可以表现为体积的增长，也可以表现为密度的增加或新出现实性成分。计算机断层扫描（computed tomography, CT）质量（Mass）测量能综合评估其体积及密度的变化，在结节随访中量化反映其生长特性。本研究目的是评估亚实性结节质量测量的重复性，并与体积测量重复性比较。

方法

两名医生盲法应用结节分析软件对44例患者共80个亚实性结节的CT影像资料进行三维体积及质量重复测量，对自动分割效果不佳的结节采用手动调整。应用Bland-Altman法评估质量测量及体积测量的观察者内及观察者间差异，组内相关及Wilcoxon检验评估质量测量与体积测量观察者内、间测量变异度的差异。

结果

74个（92.5%）亚实性结节分割效果满意纳入研究。结节直径（7.2±2.5）mm（3.2 mm-16.4 mm）。质量测量的观察者内、观察者间95%一致性区间分别为-11.5%-10.4%、-17.4%-19.3%，体积测量的观察者内、观察者间95%一致性区间分别为-8.4%-8.8%、-17.9%-19.4%，观察者内、间质量测量与体积测量变异度的组内相关系数分别为0.95、0.93（P均 < 0.001），二者之间无统计学差异（P值分别为0.78、0.09）。手动调整结节分割对测量的重复性有一定影响。

结论

亚实性肺结节的质量测量重复性较好，可作为随访定量评估方法。

CT Screening for Lung Cancer: Nonsolid Nodules in Baseline and Annual Repeat Rounds

PURPOSE

To address the frequency of identifying nonsolid nodules, diagnosing lung cancer manifesting as such nodules, and the long-term outcome after treatment in a prospective cohort, the International Early Lung Cancer Action Program.

MATERIALS AND METHODS

A total of 57,496 participants underwent baseline and subsequent annual repeat computed tomographic (CT) screenings according to an institutional review board, HIPAA-compliant protocol. Informed consent was obtained. The frequency of participants with nonsolid nodules, the course of the nodule at follow-up, and the resulting diagnoses of lung cancer, treatment, and outcome are given separately for baseline and annual repeat rounds of screening. The χ(2) statistic was used to compare percentages.

RESULTS

A nonsolid nodule was identified in 2392 (4.2%) of 57,496 baseline screenings, and pathologic pursuit led to the diagnosis of 73 cases of adenocarcinoma. A new nonsolid nodule was identified in 485 (0.7%) of 64,677 annual repeat screenings, and 11 had a diagnosis of stage I adenocarcinoma; none were in nodules 15 mm or larger in diameter. Nonsolid nodules resolved or decreased more frequently in annual repeat than in baseline rounds (322 [66%] of 485 vs 628 [26%] of 2392, P < .0001). Treatment of the cases of lung cancer was with lobectomy in 55, bilobectomy in two, sublobar resection in 26, and radiation therapy in one. Median time to treatment was 19 months (interquartile range [IQR], 6-41 months). A solid component had developed in 22 cases prior to treatment (median transition time from nonsolid to part-solid, 25 months). The lung cancer-survival rate was 100% with median follow-up since diagnosis of 78 months (IQR, 45-122 months).

CONCLUSION

Nonsolid nodules of any size can be safely followed with CT at 12-month intervals to assess transition to part-solid. Surgery was 100% curative in all cases, regardless of the time to treatment.

Using the CT features to differentiate invasive pulmonary adenocarcinoma from pre-invasive lesion appearing as pure or mixed ground-glass nodules

OBJECTIVE

To differentiate pre-invasive lesion from invasive pulmonary adenocarcinoma (IPA) appearing as ground-glass nodules (GGNs) using CT features.

METHODS

149 GGNs were enrolled in this study, with 74 pure GGNs (p-GGNs) and 75 mixed GGNs (m-GGNs). Firstly, univariate analysis was used to analyse the difference of CT features between pre-invasive lesion and IPA. Then, multivariate analysis was conducted to identify variables that could independently differentiate pre-invasive lesion from IPA. Receiver operating characteristic curve analysis was performed to evaluate the differentiating value of identified variables.

RESULTS

In the p-GGNs, multivariate analysis showed that the amount of blood vessels was an independent risk factor. Using the amount of blood vessels "≥1" as the diagnostic criterion, we could diagnose IPA with a sensitivity of 100%. Using the amount of blood vessels "=0" as the diagnostic criterion, we could diagnose pre-invasive lesions with a specificity of 100%. In the m-GGNs, multivariate analysis showed that the volume of solid portion (VSolid) and pleural indentation were two independent risk factors. One further model was constructed using these two variables: model = 2.508 × (VSolid + 1.407) × (pleural indentation - 1.016). Using the new model, improved diagnostic ability was achieved compared with using VSolid or pleural indentation alone.

CONCLUSION

The amount of blood vessels through the p-GGNs would be an important criterion during clinical management, while VSolid and pleural indentation seemed important for m-GGNs. Moreover, the new model could further improve the differentiating value for m-GGNs.

ADVANCES IN KNOWLEDGE

CT features are useful in differentiating pre-invasive lesion from IPA appearing as GGNs.

Pulmonary subsolid nodules: what radiologists need to know about the imaging features and management strategy

Pulmonary subsolid nodules (SSNs) refer to pulmonary nodules with pure ground-glass nodules and part-solid ground-glass nodules. SSNs are frequently encountered in the clinical setting, such as screening chest computed tomography (CT). The main concern regarding pulmonary SSNs, particularly when they are persistent, has been lung adenocarcinoma and its precursors. The CT manifestations of SSNs help radiologists and clinicians manage these lesions. However, the management plan for SSNs has not previously been standardized. Recently, the Fleischner Society published recommendations for the management of incidentally detected SSNs. The guidelines reflect the new lung adenocarcinoma classification system proposed by the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society (IASLC/ATS/ERS) and include six specific recommendations according to the nodule size, solid portion and multiplicity. This review aims to increase the understanding of SSNs and the imaging features of SSNs according to their histology, natural course, possible radiologic interventions, such as biopsy, localization prior to surgery, and current management.

Evidence based imaging strategies for solitary pulmonary nodule

Solitary pulmonary nodule (SPN) is defined as a rounded opacity ≤3 cm in diameter surrounded by lung parenchyma. The majority of smokers who undergo thin-section CT have SPNs, most of which are smaller than 7 mm. In the past, multiple follow-up examinations over a two-year period, including CT follow-up at 3, 6, 12, 18, and 24 months, were recommended when such nodules are detected incidentally. This policy increases radiation burden for the affected population. Nodule features such as shape, edge characteristics, cavitation, and location have not yet been found to be accurate for distinguishing benign from malignant nodules. When SPN is considered to be indeterminate in the initial exam, the risk factor of the patients should be evaluated, which includes patients' age and smoking history. The 2005 Fleischner Society guideline stated that at least 99% of all nodules 4 mm or smaller are benign; when nodule is 5-9 mm in diameter, the best strategy is surveillance. The timing of these control examinations varies according to the nodule size (4-6, or 6-8 mm) and the type of patients, specifically at low or high risk of malignancy concerned. Noncalcified nodules larger than 8 mm diameter bear a substantial risk of malignancy, additional options such as contrast material-enhanced CT, positron emission tomography (PET), percutaneous needle biopsy, and thoracoscopic resection or videoassisted thoracoscopic resection should be considered.

[Management of subsolid pulmonary nodules]

The finding of subsolid pulmonary nodules poses a frequent problem in the daily routine of the radiologist. The biological behavior of such subsolid lesions differs significantly from solid nodules. The risk of malignancy is significantly higher in subsolid nodules as compared to solid or purely ground glass opacities or nodules. The recommendations regarding the diagnostic management of subsolid nodules have been adapted according to the tendency of growth and the risk of malignancy. A benign etiology is also seen quite often in subsolid lesions and in this case they will show a reduction of size or disappear completely by the follow-up examination. Therefore, in many cases a short-term follow-up examination is primarily recommended. As the findings will often show no changes for a long period of time, further annual follow-up examinations over a longer, not yet specified period of time are recommended. Subsolid lesions that grow in size and/or show an increase in density or develop a solid part within a ground glass lesion should remain as suspected malignancies until proven otherwise.

Persistent pure ground-glass opacity lung nodules ≥ 10 mm in diameter at CT scan: histopathologic comparisons and prognostic implications

BACKGROUND

Little is known about the histopathology and prognosis of persistent pure ground-glass opacity nodules (GGNs) of ≥ 10 mm in diameter. We aimed to compare the morphologic features of persistent pure GGNs of ≥ 10 mm in diameter at thin-section CT (TSCT) scan with histopathology and patient prognosis.

METHODS

A total of 46 resected GGNs that were evaluated with TSCT scan and followed up for ≥ 3 years were included in this study. Correlations between histopathology (adenocarcinoma in situ [AIS], minimally invasive adenocarcinoma [MIA], and invasive adenocarcinoma) and CT scan characteristics were examined. CT scan and clinicodemographic data were investigated by univariate and multivariate analyses to identify features that helped distinguish invasive adenocarcinoma from AIS or MIA. Disease recurrence was also evaluated.

RESULTS

The nodules included 19 AISs (41%), nine MIAs (20%), and 18 invasive adenocarcinomas (39%). On univariate analysis, the presence of air bronchogram (P = .012), size of nodule (P = .032, cutoff = 16.4 mm in diameter), and mass of nodule (P = .040, cutoff = 0.472 g) were significant factors that differentiated invasive adenocarcinoma from AIS or MIA. On multivariate analysis, size (P = .010) and mass of nodule (P = .016) were significant determinants for invasive adenocarcinoma. There were no cases of recurrence during a follow-up period of ≥ 3 years after surgical resection.

CONCLUSIONS

In persistent pure GGNs of ≥ 10 mm in diameter, the size and mass of the nodule are determinants of invasive adenocarcinoma, for which surgical resection leads to excellent prognosis.

Nodule characterization: subsolid nodules

In this review, we focus on the radiologic, clinical, and pathologic aspects primarily of solitary subsolid pulmonary nodules. Particular emphasis will be placed on the pathologic classification and correlative computed tomography (CT) features of adenocarcinoma of the lung. The capabilities of fluorodeoxyglucose positron emission tomography-CT and histologic sampling techniques, including CT-guided biopsy, endoscopic-guided biopsy, and surgical resection, are discussed. Finally, recently proposed management guidelines by the Fleischner Society and the American College of Chest Physicians are reviewed.

Computed tomography quantitative analysis of components: a new method monitoring the growth of pulmonary nodule

BACKGROUND

The estimation of the growth of solitary pulmonary nodules by using non-invasive methods is increasingly gaining clinical importance for performing the timely adequate treatment of these nodules.

PURPOSE

To evaluate the application value of computed tomography (CT) quantitative analysis of components for dynamic assessment of the growth of solitary pulmonary nodules, and compare this approach with three-dimensional (3D) volumetric measurement of pulmonary nodules.

MATERIAL AND METHODS

The imaging data of 21 patients who had undergone multiple follow-up CT scans for solitary pulmonary nodules were retrospectively analyzed, and the total volume of pulmonary nodules and the percentage change in the total volume of pulmonary nodules after multiple follow-up CT scans were measured using 3D volume measurement software. The volume of solid components in pulmonary nodules was measured using CT quantitative analysis; the percentage change in the volume of solid components across examinations was calculated; and the percentage change in the total volume of pulmonary nodules was compared and contrasted with the percentage change in the volume of solid components in the pulmonary nodules.

RESULTS

All 21 cases were malignant adenocarcinomas. In the 21 cases of malignant nodules, the 3D volumes of the nodules and solid components were both increased, with the percentage change in the volume of the solid components (115.78-418.91%, 130.45 ± 119.48) significantly different from the percentage change in the total volume of the nodules (78.56-105.73% , 42.34 ± 32.17) (P = 0.02).

CONCLUSION

By measuring volume changes in solid components in the nodules, CT quantitative analysis offers more sensitive and earlier evaluation of the dynamic growth of the nodules than measurement of volume changes in the nodules alone.

Pathologic classification of adenocarcinoma of lung

Recently, the 1999/2004 World Health Organization (WHO) classification of adenocarcinoma became less useful from a clinical standpoint as most adenocarcinomas belonged to the mixed subtype and the term bronchioloalveolar carcinoma (BAC) gave rise to much confusion among clinicians. For these reasons a new adenocarcinoma classification was introduced in 2011 by a joint working group of the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS). This represents an international, multidisciplinary effort joining pathologists, molecular biologists, pulmonary physicians, thoracic oncologists, radiologists, and thoracic surgeons. Currently, a distinction is made between pre-invasive lesions, minimally invasive and invasive lesions. The confusing term BAC is not used anymore and new subcategories include adenocarcinoma in situ and minimally invasive adenocarcinoma. Several aspects of this classification are discussed with main emphasis on its correlation with imaging techniques and its impact on diagnosis, treatment and prognosis. On chest computed tomography (CT) a distinction is made between solid and subsolid nodules, the latter comprising ground glass opacities (GGO), and partly solid lesions. Several studies incorporating CT and positron emission tomographic (PET) data show a good imaging-pathologic correlation. With the implementation of screening programs early lung cancer has become a hotly debated topic and sublobar resection is currently reconsidered for early lesions without lymph node involvement. This new classification will also have an impact on the TNM classification. Thoracic surgeons will continue to play a major role in the application, evaluation and further refinement of this new adenocarcinoma classification.

Radiologic implications of the 2011 classification of adenocarcinoma of the lung

Now the leading subtype of lung cancer, adenocarcinoma received a new classification in 2011. For tumors categorized previously as bronchioloalveolar carcinoma (BAC), criteria and terminology had not been uniform, so the 2011 classification provided four new terms: (a) adenocarcinoma in situ (AIS), representing histopathologically a small (≤3-cm), noninvasive lepidic growth, which at computed tomography (CT) is usually nonsolid; (b) minimally invasive adenocarcinoma, representing histopathologically a small (≤3-cm) and predominantly lepidic growth that has 5-mm or smaller invasion, which at CT is mainly nonsolid but may have a central solid component of up to approximately 5 mm; (c) lepidic predominant nonmucinous adenocarcinoma, representing histopathologically invasive adenocarcinoma that shows predominantly lepidic nonmucinous growth, which at CT is usually part solid but may be nonsolid or occasionally have cystic components; and (d) invasive mucinous adenocarcinoma, histopathologically showing lepidic growth as its predominant component, which at CT varies widely from solid to mostly solid to part solid to nonsolid and may be single or multiple (when multifocal, it was formerly called multicentric BAC). In addition, new histopathologic subcategories of acinar, papillary, micropapillary, and solid predominant adenocarcinoma are now described, all as nonmucinous, predominantly invasive, may include a small lepidic component, and at CT are usually solid but may include a small nonsolid component. The micropapillary subtype has a poorer prognosis than the other subtypes. In addition, molecular genetic correlations for the subcategories of adenocarcinoma of the lung are now a topic of increasing interest. As the new classification enters common use, further descriptions of related correlations can be anticipated.