Management of screening-detected ground glass nodules: a narrative review

Wide-scale application of low-dose computed tomography (LDCT) in lung cancer screening has led to an increased detection of ground glass nodule (GGN) lesions. However, there is still no clear management plan for these lesions after detection. Clinicians are usually faced with a dilemma in choosing the best initial management approach that not only limits overtreatment but also avoids the possibility of lesions growing into invasive carcinoma. Most current and past guidelines favor surveillance with computed tomography (CT) as the initial management approach based on the notion that the majority of GGN lesions are indolent tumors. Immediate surgery is generally considered overtreatment and is usually only recommended when the lesion grows in size, persists, or increases its solid component during follow-up CT surveillance. However, due to evolution of surgery to minimal invasive procedures, such as uniportal video-assisted thoracic surgery, and the development of enhanced recovery after thoracic surgery protocols, modern surgery is now safer and associated with less postoperative mortality. Additionally, intraoperative frozen sections can be used to guide resection, making initial management via surgery more attractive than before. Based on these developments, this review recommends that immediate surgery should be considered at the same level as follow-up CT surveillance when making multidisciplinary team decisions for screening-detected GGNs, as it provides both a diagnostic and treatment role.

Clinical and non-contrast computed tomography characteristics and disease development in patients with benign pulmonary subsolid nodules with a solid component ≤ 5 mm

OBJECTIVES

To evaluate the clinical and non-contrast computed tomography (CT) features of patients with benign pulmonary subsolid nodules (SSNs) with a solid component ≤ 5 mm and their development trends via follow-up CT.

METHODS

We retrospectively collected 436 data from patients who had SSNs with a solid component ≤ 5 mm, including 69 with absorbable benign SSNs (AB-SSNs), 70 with nonabsorbable benign SSNs (NB-SSNs), and 297 with malignant SSNs (M-SSNs). Models 1, 2, and 3 for distinguishing the different types of SSNs were then developed and validated.

RESULTS

Patients with AB-SSNs were younger and exhibited respiratory symptoms more frequently than those with M-SSNs. The frequency of nodules detected during follow-up CT was in the following order: AB-SSNs > NB-SSNs > M-SSNs. NB-SSNs were smaller than M-SSNs, and ill-defined margins were more frequent in AB-SSNs than in NB-SSNs and M-SSNs. Benign SSNs exhibited irregular shape, target sign, and lower CT values more frequently compared to M-SSNs, whereas the latter demonstrated bubble lucency more commonly compared to the former. Furthermore, AB-SSNs showed more thickened interlobular septa and satellite lesions than M-SSNs and M-SSNs had more pleural retraction than AB-SSNs (all p < 0.017). The three models had AUCs ranging 0.748-0.920 and 0.790-0.912 in the training and external validation cohorts, respectively. A follow-up CT showed nodule progression in four benign SSNs.

CONCLUSIONS

The three SSN types have different clinical and imaging characteristics, with some benign SSNs progressing to resemble malignancy.

CRITICAL RELEVANCE STATEMENT

A good understanding of the imaging features and development trends of benign SSNs may help reduce unnecessary follow-up or interventions. This retrospective study explores the CT characteristics of benign SSNs with a solid component ≤ 5 mm by comparing AB-SSNs, NB-SSNs, and M-SSNs and delineates their development trends via follow-up CT.

KEY POINTS

1. Different subsolid nodule types exhibit distinct clinical and imaging features. 2. A miniscule number of benign subsolid nodules can progress to resemble malignancy. 3. Knowing the clinical and imaging features and development trends of benign subsolid nodules can improve management.

Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma

BACKGROUND

The nature of the solid component of subsolid nodules (SSNs) can indicate tumor pathological invasiveness. However, preoperative solid component assessment still lacks a reference standard.

METHODS

In this retrospective study, an AI algorithm was proposed for measuring the solid components ratio in SSNs, which was used to assess the diameter ratio (1D), area ratio (2D), and volume ratio (3D). The radiologist measured each SSN's consolidation to tumor ratio (CTR) twice, four weeks apart. The area under the receiver-operating characteristic (ROC) curve (AUC) was calculated for each method used to discriminate an Invasive Adenocarcinoma (IA) from a non-IA. The AUC and the time cost of each measurement were compared. Furthermore, we examined the consistency of measurements made by the radiologist on two separate occasions.

RESULTS

A total of 379 patients (the primary dataset n = 278, the validation dataset n = 101) were included. In the primary dataset, compared to the manual approach (AUC: 0.697), the AI algorithm (AUC: 0.811) had better predictive performance (P =.0027) in measuring solid components ratio in 3D. Algorithm measurement in 3D had an AUC no inferior to 1D (AUC: 0.806) and 2D (AUC: 0.796). In the validation dataset, the AI 3D method also achieved superior diagnostic performance compared to the radiologist (AUC: 0.803 vs 0.682, P =.046). The two measurements of the CTR in the primary dataset, taken 4 weeks apart, have 7.9 % cases in poor consistency. The measurement time cost by the radiologist is about 60 times that of the AI algorithm (P <.001).

CONCLUSION

The 3D measurement of solid components using AI, is an effective and objective approach to predict the pathological invasiveness of SSNs. It can be a preoperative interpretable indicator of pathological invasiveness in patients with lung adenocarcinoma.

Preoperative radio-guided localization of lung nodules with I-125 seeds: experience with 32 patients at a single institution

OBJECTIVES

Videothoracoscopic visualization and/or palpation of pulmonary nodules may be difficult due to their location, small size or limited solid component. The purpose of this study is to present our experience with computed tomography (CT)-guided preoperative localization of pulmonary nodules by percutaneous marking with radio-labelled iodine-125 seeds.

METHODS

A total of 34 pulmonary nodules were marked under CT with the placement of 33 radio-labelled iodine-125 seeds in 32 consecutive patients.

RESULTS

All patients underwent biportal video-assisted thoracic surgery (VATS) and in no case was conversion to thoracotomy necessary. A total of 88.2% of the lung nodules were successfully resected. In the remaining 11.8%, migration of the seed to the pleural cavity occurred, although these nodules were still resected during VATS. Of all the patients with pneumothorax after the marking procedure, only one required chest tube placement (3.1%). No major postoperative complications were observed.

CONCLUSIONS

Preoperative marking of pulmonary nodules with I-125 seeds under CT guidance is a feasible and safe technique that allows their intraoperative identification and resection.

Subsolid Lung Adenocarcinomas: Radiological, Clinical and Pathological Features and Outcomes

Lung adenocarcinomas manifesting as subsolid nodules usually have a favorable prognosis. This study aimed to have a comprehensive investigation of the radiological and clinicopathologic features and oncological outcomes of subsolid nodules. Between March 2010 and December 2015, 865 patients with surgically resected clinical IA subsolid lung adenocarcinoma were retrospectively reviewed. Patients were classified into the pure ground-glass nodules (GGN) (pGGN [n = 358], without solid component on lung and mediastinal windows), heterogeneous GGN (hGGN [n = 65], only with solid components on lung window), and real part-solid nodule (rPSN [n = 442], with solid component on both lung and mediastinal windows) groups. The clinicopathological features and survival time of the three groups were compared between groups. There was a significant increase in median tumor size (P < 0.001), solid component size measured at lung window (LW-SCS) (P < 0.001), and the proportion of invasive adenocarcinoma subtypes (P < 0.001) from pGGNs to hGGNs to rPSNs. After adjustment for LW-SCS, adenocarcinomas with predominant lepidic patterns were still more common in hGGNs than in rPSNs (P = 0.009). Patients with rPSNs had a significantly worse recurrence-free survival (RFS) than those with pGGNs and hGGNs (5-year: 91.9% versus 100% versus 100%, P < 0.001). Multivariate Cox analyses revealed that gender (both P < 0.05) and clinical T category (based on lung window [LW-cT] [P = 0.002] or mediastinal window [MW-cT] [P < 0.001]) were independent prognostic factors of RFS in the rPSN group. HGGNs represented as an intermediate subtype between pGGNs and rPSNs. Both pGGNs and hGGNs had excellent outcomes, while rPSNs exhibited a worse prognosis than them. Clinical T category and gender had prognostic implications for rPSNs.

Distinct tumor bacterial microbiome in lung adenocarcinomas manifested as radiological subsolid nodules

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Subsolid nodules have higher microbiome diversity compared with solid nodules

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Microbiome composition of Subsolid nodules is distinct from that of solid nodules

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Microbial signatures show robust performance to predict lung adenocarcinoma or subsolid nodules

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Some lung microbial species are associated with clinical characteristics

Objectives

Increasing evidence indicates that microbiota dysbiosis in the human body may play vital roles in carcinogenesis. However, the relationship between microbiome and lung cancer remains unclear. In this study, we aimed to characterize the microbiome in early stage of lung adenocarcinoma (LUAD), which presented as subsolid nodules (SSN) or solid nodules (SN).

Materials and Methods

We performed 16S rRNA sequencing of 35 pairs (10 SSN and 25 SN) of LUAD tumor tissues and paired adjacent normal tissues. Machine learning was used to identify microbial signatures and construct predictive models.

Results

SSN has higher microbiome richness and diversity compared with SN (richness p = 0.017, Shannon index p = 0.17), and the microbiome composition of SSN is distinct from that of SN (Bray-Curtis p = 0.013, unweighted unifrac p = 0.001). Phylum Chloroflexi (p = 0.009), Gemmatimonadetes (p = 0.018) and genus including Cloacibacterium (p = 0.003), Subdoligranulum (p = 0.002), and Mycobacterium (p = 0.034) were significantly increased in SSN. Tumor and normal tissues had similar richness and diversity, as well as overall microbiome composition. Probiotics with anti-cancer potential, like Lactobacillus, showed elevated levels in normal tissues (p = 0.018). A random forest model with 20 genera-based biomarkers achieved high accuracy for LUAD prediction (area under curve, AUC = 0.879). Meanwhile, a five genera-based signature can accurately discriminate SSN between SN (AUC = 0.950). Cross-validation of these two models also showed high predictive performance (LUAD AUC = 0.813, SSN AUC = 0.933).

Conclusions

This study demonstrates, for the first time, the tumor bacterial microbiome composition of LUAD manifested as SSN is distinct from that presented as SN, which adds new knowledge to SSN in the perspective of microbiome. Furthermore, microbiome signatures showed good performance to predict LUAD or SSN.

Adenocarcinoma of the lung: from BAC to the future

Adenocarcinoma in situ, minimally invasive adenocarcinoma, lepidic predominant adenocarcinoma and invasive mucinous adenocarcinoma are relatively new classification entities which replace the now retired term, bronchoalveolar carcinoma (BAC). The radiographic appearance of these lesions ranges from pure, ground glass nodules to large, solid masses. A thorough understanding of the new classification is essential to radiologists who work with MDT colleagues to provide accurate staging and treatment. A 2-year review was performed of all surgically resected cases of adenocarcinoma in situ, minimally invasive adenocarcinoma and lepidic predominant adenocarcinoma in our institution. Cases are broken down by age, gender, tumour type and tumour location. A pictorial review is presented to illustrate the radiologic and pathologic features of each entity.

Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?

Background

To assess if radiomics can differentiate benign and malignant subsolid lung nodules (SSNs) on baseline or follow up chest CT examinations. If radiomics can differentiate between benign and malignant subsolid lung nodules, the clinical implications are shorter follow up CT imaging and early recognition of lung adenocarcinoma on imaging.

Materials and methods

The IRB approved retrospective study included 36 patients (mean age 69 ± 8 years; 5 males, 31 females) with 108 SSNs (31benign, 77 malignant) who underwent follow up chest CT for evaluation of indeterminate SSN. All SSNs were identified on both baseline and follow up chest CT. DICOM CT images were deidentified and exported into the open access 3D Slicer software (version 4.7) to obtain radiomic features. Logistic regression analyses and receiver operating characteristic (ROC) curves for various quantitative parameters were generated with SPSS statistical software.

Results

Only 2/92 radiomic features (cluster shade and surface volume ratio) enabled differentiation between malignant and benign SSN on baseline chest CT (P = 0.01 and 0.03) with moderate accuracy [AUC 0.624 (0.505–0.743)]. On follow-up CT, 52/92 radiomic features were significantly different between benign and malignant SSN (P: 0.04 - < 0.0001) with improved accuracy [AUC: 0.708 (0.605–0.811), P = 0.04 - < 0.0001]. Radiomics of benign SSN were stable over time, whereas 63/92 radiomic features of malignant SSNs changed significantly between the baseline and follow up chest CT (P: 0.04 - < 0.0001).

Conclusions

Temporal changes in radiomic features of subsolid lung nodules favor malignant etiology over benign. The change in radiomics features of subsolid lung nodules can allow shorter follow up CT imaging and early recognition of lung adenocarcinoma on imaging. Radiomic features have limited application in differentiating benign and early malignant SSN on baseline chest CT.

Long-Term Active Surveillance of Screening Detected Subsolid Nodules is a Safe Strategy to Reduce Overtreatment

INTRODUCTION

Lung cancer presenting as subsolid nodule (SSN) can show slow growth, hence treating SSN is controversial. Our aim was to determine the long-term outcome of subjects with unresected SSNs in lung cancer screening.

METHODS

Since 2005, the Multicenter Italian Lung Detection (MILD) screening trial implemented active surveillance for persistent SSN, as opposed to early resection. Presence of SSNs was related to diagnosis of cancer at the site of SSN, elsewhere in the lung, or in the body. The risk of overall mortality and lung cancer mortality was tested by Cox proportional hazards model.

RESULTS

SSNs were found in 16.9% (389 of 2303) of screenees. During 9.3 ± 1.2 years of follow-up, the hazard ratio of lung cancer diagnosis in subjects with SSN was 6.77 (95% confidence interval: 3.39-13.54), with 73% (22 of 30) of cancers not arising from SSN (median time to diagnosis 52 months from SSN). Lung cancer-specific mortality in subjects with SSN was significantly increased (hazard ratio = 3.80; 95% confidence interval: 1.24-11.65) compared to subjects without lung nodules. Lung cancer arising from SSN did not lead to death within the follow-up period.

CONCLUSIONS

Subjects with SSN in the MILD cohort showed a high risk of developing lung cancer elsewhere in the lung, with only a minority of cases arising from SSN, and never representing the cause of death. These results show the safety of active surveillance for conservative management of SSN until signs of solid component growth and the need for prolonged follow-up because of high risk of other cancers.

[Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma]

背景与目的

亚实性肺结节为肺原发腺癌的常见计算机体层成像（computed tomography, CT）表现，依据其CT影像特征预测病理分型对确定临床治疗策略具有临床价值。本研究根据病理分类，回顾性分析良性、不典型腺瘤样增生（atypical adenomatous hyperplasia, AAH）/原位腺癌（adenocarcinoma in situ, AIS）/微侵袭性腺癌（minimally invasive adenocarcinoma, MIA）、侵袭性腺癌三组亚实性肺结节的CT征象，评估其在良恶性鉴别及恶性侵袭程度判别中的价值。

方法

回顾性分析106例经手术切除亚实性结节的CT征象。依据手术病理分为良性和恶性组，恶性组根据侵袭程度分为无/微侵袭组（AAH/AIS/MIA）、侵袭性腺癌组，测量结节大小、实性成分比例、瘤肺界面、形状、边缘、胸膜牵拉征、空气支气管征、结节内血管异常等CT征象。根据单因素分析（χ²检验、非参数检验Mann-Whitney U检验）结果筛选有统计学差异的变量，纳入Logistic回归多因素分析。

结果

Logistic回归分析显示清晰的瘤肺界面、空气支气管征以及结节内血管异常是恶性结节的重要预测指标，风险比分别为38.1（95%CI: 5.0-287.7; P < 0.01）、7.9（95%CI: 1.3-49.3; P=0.03）、7.2（95%CI: 1.4-37.0; P=0.02）。更大的实性成分所占比例是侵袭性腺癌与AAH/AIS/MIA组鉴别的重要指标，其风险比分别为1.04（95%CI: 1.01-1.06, P=0.01）。

结论

亚实性结节中出现清晰的瘤肺界面、空气支气管征、结节内血管异常提示其恶性概率增加。恶性结节中实性成分所占比例越大预示着侵袭性更高。

Controversies on lung cancers manifesting as part-solid nodules

PURPOSE

Summarise survival of patients with resected lung cancers manifesting as part-solid nodules (PSNs).

METHODS

PubMed/MEDLINE and EMBASE databases were searched for all studies/clinical trials on CT-detected lung cancer in English before 21 December 2015 to identify surgically resected lung cancers manifesting as PSNs. Outcome measures were lung cancer-specific survival (LCS), overall survival (OS), or disease-free survival (DFS). All PSNs were classified by the percentage of solid component to the entire nodule diameter into category PSNs <80% or category PSNs ≥80%.

RESULTS

Twenty studies reported on PSNs <80%: 7 reported DFS and 2 OS of 100%, 6 DFS 96.3-98.7%, and 11 OS 94.7-98.9% (median DFS 100% and OS 97.5%). Twenty-seven studies reported on PSNs ≥80%: 1 DFS and 2 OS of 100%, 19 DFS 48.0%-98.0% (median 82.6%), and 16 reported OS 43.0%-98.0% (median DFS 82.6%, OS 85.5%). Both DFS and OS were always higher for PSNs <80%.

CONCLUSION

A clear definition of the upper limit of solid component of a PSN is needed to avoid misclassification because cell-types and outcomes are different for PSN and solid nodules. The workup should be based on the size of the solid component.

KEY POINTS

• Lung cancers manifesting as PSNs are slow growing with high cure rates. • Upper limits of the solid component are important for correct interpretation. • Consensus definition is important for the management of PSNs. • Median disease-free-survival (DFS) increased with decreasing size of the nodule.

Lung adenocarcinomas: correlation of computed tomography and pathology findings

Adenocarcinoma is the most common histologic type of lung cancer. Recent lung adenocarcinoma classifications from the International Association for the Study of Lung cancer, the American Thoracic Society and the European Respiratory Society (IASLC/ETS/ERS, 2011) and World Health Organization (WHO, 2015) define a wide range of adenocarcinoma types and subtypes featuring different prognosis and management. This spectrum of lesions translates into various CT presentations and features, which generally show good correlation with histopathology, stressing the key role of the radiologist in the diagnosis and management of those patients. This review aims at helping radiologists to understand the basics of the up-to-date adenocarcinoma pathological classifications, radio-pathological correlations and how to use them in the clinical setting, as well as other imaging-related correlations (radiogenomics, quantitative analysis, PET-CT).