Management of Incidental Lung Nodules

Subsolid Nodules: Significance and Current Understanding

Subsolid nodules are heterogeneously appearing and behaving entities, commonly encountered incidentally and in high-risk populations. Accurate characterization of subsolid nodules, and application of evolving surveillance guidelines, facilitates evidence-based and multidisciplinary patient-centered management.

ACR Appropriateness Criteria® Incidentally Detected Indeterminate Pulmonary Nodule

Incidental pulmonary nodules are common. Although the majority are benign, most are indeterminate for malignancy when first encountered making their management challenging. CT remains the primary imaging modality to first characterize and follow-up incidental lung nodules. This document reviews available literature on various imaging modalities and summarizes management of indeterminate pulmonary nodules detected incidentally. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Effectiveness of an Electronic Medical Record-Based Recognition Tool for the Identification of Incidental Pulmonary Nodules

BACKGROUND

Incidental pulmonary nodules (IPNs) are lung nodules detected on imaging studies performed for an unrelated reason. Approximately 1.6 million IPNs are detected in the United States every year. Unfortunately, close to 1.1 million (69%) of these IPNs are not managed with appropriate follow-up care. The goal of this study was to assess the utility of a noncommercial electronic medical record (EMR)-based IPN keyword recognition program in identifying IPNs and the ability of lung navigators to communicate these findings to patients.

METHODS

This is a observational, implementation study aimed identify IPNs using an EMR-based protocol and to relay results of findings to patients. The patient population included patients 16 and older undergoing computed tomography (CT) chest, CT chest/abdomen, CT angiogram chest, CT chest/abdomen/pelvis, and chest radiography through the radiology department within a large community tertiary medical campus between June 2019 and August 2020. EPIC EMR were queried using criteria designed to find IPNs. A lung navigator reviewed these cases and sorted them into categories based on their size and risk status. After identification of risk factors, actions were taken to directly communicate results to patients.

RESULTS

Seven hundred and fifty-three patients were found to have true IPNs without a history of active malignancy involving the lung. On the basis of radiographic measurements, 60% of the nodules identified were <6 mm, 17% were between 6 and 8 mm, 22% were >8 mm, and 12% were deemed nodular opacities. Lung navigators were able to contact a total of 637 (87%) individuals with IPNs and results were directly communicated. Of the 637 patients identified to have an IPN, a total of 12 (2%) cancers were diagnosed.

CONCLUSION

We have here demonstrated that the development of an EMR-based keyword recognition platform for the identification of IPNs is a useful and successful tool for communication of IPN findings to patients using lung navigators.

Watershed analysis in wedge resection of pulmonary pure ground-glass nodules hardly localized by CT-guided puncture

BACKGROUND

To investigate the feasibility and safety of watershed analysis after target pulmonary vascular occlusion for the wedge resection in patients with non-palpable and non-localizable pure ground-glass nodules during uniport thoracoscopic surgery.

METHODS

A total of 30 patients with pure ground-glass nodules < 1 cm in diameter, localized in the lateral third of the lung parenchyma, were enrolled. Three-dimensional reconstruction of thin-section computed tomography (CT) data was performed using Mimics software before surgery to observe and identify the target pulmonary vessels supplying the lung tissue in the area where the pulmonary nodules were localized and to temporarily block the target pulmonary vessels during surgery. Next, the extent of the watershed was determined with the expansion-collapse method, and finally, wedge resection was performed. After wedge resection of the target lung tissue, the blocked pulmonary vessel was released, thus allowing operators to complete the procedure without damaging pulmonary vessels.

RESULTS

None of the patients experienced postoperative complications. The chest CT of all patients was reviewed six months after the operation, revealing no tumor recurrence.

CONCLUSIONS

Our results suggest that watershed analysis following target pulmonary vascular occlusion for wedge resection in pulmonary pure ground-glass nodules is a safe and feasible approach.

Point-of-care access to clinical guidelines may improve management of incidental findings in the primary care setting

RATIONALE

Incidental radiographic findings are common, and primary care providers (PCPs) are often charged with the conducting or initiating an appropriate evaluation. Clinical guidelines are available for management of common 'incidentalomas' including lung and adrenal nodules, but guidelines-adherent evaluations are not always performed; for example, in the setting of incidental adrenal masses (IAMs), recent literature suggests that an evidence-based evaluation occurs in <25% of patients for whom it is warranted-a quality and safety concern.

AIMS AND OBJECTIVES

The objective of this study was to examine whether point-of-care access to concise clinical guidelines would promote appropriate evaluations of two common incidentalomas: IAMs and lung nodules.

METHOD

This study was a survey-based, single-blinded, randomized experiment of decision-making within clinical vignettes. Respondents were PCPs in a variety of clinical practice settings, and half were randomly assigned to surveys that included concise clinical guidelines while the other half served as controls without access to guidelines. Scenarios involved patients with IAMs and lung nodules, and the scenarios included both higher-risk and lower-risk lesions. Our primary analysis examined safe versus inappropriate clinical decisions, while a secondary analysis compared guidelines-concordant versus guidelines-discordant responses.

RESULTS

For both the higher-risk IAM and higher-risk lung nodule scenarios, safe answer choices were selected at a similar rate by respondents regardless of whether they had access to guidelines or not. However, for the lower risk scenarios, inappropriate answer choices were chosen substantially more frequently by respondents without access to guidelines compared to those with the guidelines (lung: 29.3% vs. 4.5%, p = 0.003, adrenal: 31.6% vs. 7.0%, p = 0.01). There was less variation in the secondary analysis.

CONCLUSION

Survey respondents were significantly more likely to make safe management decisions in lower-risk clinical scenarios when clinical guidelines were available. Point-of-care access to clinical guidelines for incidentalomas is an intervention that may reduce management errors and improve patient safety.

Artificial Intelligence Algorithm-Based Feature Extraction of Computed Tomography Images and Analysis of Benign and Malignant Pulmonary Nodules

This study was aimed to explore the effect of CT image feature extraction of pulmonary nodules based on an artificial intelligence algorithm and the image performance of benign and malignant pulmonary nodules. In this study, the CT images of pulmonary nodules were collected as the research object, and the lung nodule feature extraction model based on expectation maximization (EM) was used to extract the image features. The Dice similarity coefficient, accuracy, benign and malignant nodule edges, internal signs, and adjacent structures were compared and analyzed to obtain the extraction effect of this feature extraction model and the image performance of benign and malignant pulmonary nodules. The results showed that the detection sensitivity of pulmonary nodules in this model was 0.955, and the pulmonary nodules and blood vessels were well preserved in the image. The probability of burr sign detection in the malignant group was 73.09% and that in the benign group was 8.41%. The difference was statistically significant (P < 0.05). The probability of malignant component leaf sign (69.96%) was higher than that of a benign component leaf sign (0), and the difference was statistically significant (P < 0.05). The probability of cavitation signs in the malignant group (59.19%) was higher than that in the benign group (3.74%), and the probability of blood vessel collection signs in the malignant group (74.89%) was higher than that in the benign group (11.21%), with statistical significance (P < 0.05). The probability of the pleural traction sign in the malignant group was 17.49% higher than that in the benign group (4.67%), and the difference was statistically significant (P < 0.05). In summary, the feature extraction effect of CT images based on the EM algorithm was ideal. Imaging findings, such as the burr sign, lobulation sign, vacuole sign, vascular bundle sign, and pleural traction sign, can be used as indicators to distinguish benign and malignant nodules.

Clinical value of CT-guided biopsy of small (≤1.5 cm) suspicious lung nodules: Diagnostic accuracy, molecular characterization and long-term clinical outcomes

Small pulmonary nodules (≤1.5 cm) are frequently detected on routine chest imaging and lung cancer screening studies. Our goal was to determine the clinical value of CT-guided core needle biopsy (CNB) in the evaluation of such nodules. In this single-center study, we retrospectively analyzed patient data (n = 44) for CNBs on lung nodules (≤1.5 cm) performed at our biopsy center between May 2017 and March 2020. We analyzed for the rate of pathology diagnosis, molecular/biomarker analysis, complications, and change in clinical management and outcome over a period ranging up to 60 months after biopsy. A pathology diagnosis of malignancy or benign lesion was obtained in 97.9% of biopsies in this cohort. The rate of complications was low with only 6.8% of patients requiring the insertion of a temporary small profile interventional radiology (IR) pigtail chest tube for pneumothorax. Out of the subset of biopsy specimens that were sent for tissue molecular analysis, 90% had enough tissue preserved after initial pathological analysis to obtain at least one molecular marker. Our data show that CT-guided CNB is safe and reliable, and should be considered for the evaluation of small, suspicious lung nodules found on routine screenings for the early detection and evaluation of malignant lesions.

Establishment and validation of a clinical model for diagnosing solitary pulmonary nodules

OBJECTIVES

The main purpose of this study was to develop and validate a clinical model for estimating the risk of malignancy in solitary pulmonary nodules (SPNs).

METHODS

A total of 672 patients with SPNs were retrospectively reviewed. The least absolute shrinkage and selection operator algorithm was applied for variable selection. A regression model was then constructed with the identified predictors. The discrimination, calibration, and clinical validity of the model were evaluated by the area under the receiver-operating-characteristic curve (AUC), calibration curve, and decision curve analysis (DCA).

RESULTS

Ten predictors, including gender, age, nodule type, diameter, lobulation sign, calcification, vascular convergence sign, mediastinal lymphadenectasis, the natural logarithm of carcinoembryonic antigen, and combination of cytokeratin 19 fragment 21-1, were incorporated into the model. The prediction model demonstrated valuable prediction performance with an AUC of 0.836 (95% CI: 0.777-0.896), outperforming the Mayo (0.747, p = 0.024) and PKUPH (0.749, p = 0.018) models. The model was well-calibrated according to the calibration curves. The DCA indicated the nomogram was clinically useful over a wide range of threshold probabilities.

CONCLUSION

This study proposed a clinical model for estimating the risk of malignancy in SPNs, which may assist clinicians in identifying the pulmonary nodules that require invasive procedures and avoid the occurrence of overtreatment.

A Pilot Study to Estimate the Impact of High Matrix Image Reconstruction on Chest Computed Tomography

Objectives:

The objectives of the study were to estimate the impact of high matrix image reconstruction on chest computed tomography (CT) compared to standard image reconstruction.

Material and Methods:

This retrospective study included patients with interstitial or parenchymal lung disease, airway disease, and pulmonary nodules who underwent chest CT. Chest CT images were reconstructed using high matrix (1024 × 1024) or standard matrix (512 × 512), with all other parameters matched. Two radiologists, blinded to reconstruction technique, independently examined each lung, viewing image sets side by side and rating the conspicuity of imaging findings using a 5-point relative conspicuity scale. The presence of pulmonary nodules and confidence in classification of internal attenuation was also graded. Overall image quality and subjective noise/artifacts were assessed.

Results:

Thirty-four patients with 68 lungs were evaluated. Relative conspicuity scores were significantly higher using high matrix image reconstruction for all imaging findings indicative of idiopathic lung fibrosis (peripheral airway visualization, interlobular septal thickening, intralobular reticular opacity, and end-stage fibrotic change; P ≤ 0.001) along with emphysema, mosaic attenuation, and fourth order bronchi for both readers (P ≤ 0.001). High matrix reconstruction did not improve confidence in the presence or classification of internal nodule attenuation for either reader. Overall image quality was increased but not subjective noise/artifacts with high matrix image reconstruction for both readers (P < 0.001).

Conclusion:

High matrix image reconstruction significantly improves the conspicuity of imaging findings reflecting interstitial lung disease and may be useful for diagnosis or treatment response assessment.

Incidental Lung Nodules on Cross-sectional Imaging: Current Reporting and Management

Pulmonary nodules are the most common incidental finding in the chest, particularly on computed tomographs that include a portion or all of the chest, and may be encountered more frequently with increasing utilization of cross-sectional imaging. Established guidelines address the reporting and management of incidental pulmonary nodules, both solid and subsolid, synthesizing nodule and patient features to distinguish benign nodules from those of potential clinical consequence. Standard nodule assessment is essential for the accurate reporting of nodule size, attenuation, and morphology, all features with varying risk implications and thus management recommendations.

Shades of Gray: Subsolid Nodule Considerations and Management

Subsolid nodules are common on chest CT imaging and may be either benign or malignant. Their varied features and broad differential diagnoses present management challenges. Although subsolid nodules often represent lung adenocarcinomas, other possibilities are common and influence management. Practice guidelines exist for subsolid nodule management for both incidentally and screening-detected nodules, incorporating patient and nodule characteristics. This review highlights the similarities and differences among these algorithms, with the intent of providing a resource for comparison and aid in choosing management options.

Computed tomography-guided coil localization for sub-fissural lung nodules

This study was designed to explore the safety, feasibility, and clinical efficacy of preoperative computed tomography (CT)-guided coil localization of sub-fissural lung nodules (LNs). A total of 105 LN patients underwent CT-guided coil localization followed by video-assisted thoracoscopic surgery (VATS)-guided wedge resection at our hospital from January 2016 to December 2019. Of these patients, 4 had sub-fissural LNs and were therefore subjected to trans-fissural coil localization procedures. We analyzed data pertaining to the coil localization and VATS procedures in these patients. A total of 4 coils were used to localize 4 LNs in 4 separate patients. One of these patients suffered from parenchymal hemorrhage around the needle path, while one other patient exhibited asymptomatic pneumothorax following coil localization. A thoracoscope was able to successfully visualize the coil tails in all of these patients. There were no instances of coils having been dislodged, and wedge resection was conducted with a 100% technical success rate in these patients. These 4 LNs were subsequently diagnosed as adenocarcinomas in situ (n = 3) and benign nodules (n = 1). CT-guided coil localization can be used to safely and easily localize sub-fissural LNs in patients scheduled to undergo VATS.

The Use of Artificial Intelligence in the Differentiation of Malignant and Benign Lung Nodules on Computed Tomograms Proven by Surgical Pathology

The purpose of this work was to evaluate the performance of an existing commercially available artificial intelligence (AI) software system in differentiating malignant and benign lung nodules. The AI tool consisted of a vessel-suppression function and a deep-learning-based computer-aided-detection (VS-CAD) analyzer. Fifty patients (32 females, mean age 52 years) with 75 lung nodules (47 malignant and 28 benign) underwent low-dose computed tomography (LDCT) followed by surgical excision and the pathological analysis of their 75 nodules within a 3 month time frame. All 50 cases were then processed by the AI software to generate corresponding VS images and CAD outcomes. All 75 pathologically proven lung nodules were well delineated by vessel-suppressed images. Three (6.4%) of the 47 lung cancer cases, and 11 (39.3%) of the 28 benign nodules were ignored and not detected by the AI without showing a CAD analysis summary. The AI system/radiologists produced a sensitivity and specificity (shown in %) of 93.6/89.4 and 39.3/82.1 in distinguishing malignant from benign nodules, respectively. AI sensitivity was higher than that of radiologists, though not statistically significant (p = 0.712). Specificity obtained by the radiologists was significantly higher than that of the VS-CAD AI (p = 0.003). There was no significant difference between the malignant and benign lesions with respect to age, gender, pure ground-glass pattern, the diameter and location of the nodules, or nodules <6 vs. ≥6 mm. However, more part-solid nodules were proven to be malignant than benign (90.9% vs. 9.1%), and more solid nodules were proven to be benign than malignant (86.7% vs. 13.3%) with statistical significance (p = 0.001 and <0.001, respectively). A larger cohort and prospective study are required to validate the AI performance.

Multi-region exome sequencing reveals genomic evolution from preneoplasia to lung adenocarcinoma

There has been a dramatic increase in the detection of lung nodules, many of which are preneoplasia atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (ADC). The molecular landscape and the evolutionary trajectory of lung preneoplasia have not been well defined. Here, we perform multi-region exome sequencing of 116 resected lung nodules including AAH (n = 22), AIS (n = 27), MIA (n = 54) and synchronous ADC (n = 13). Comparing AAH to AIS, MIA and ADC, we observe progressive genomic evolution at the single nucleotide level and demarcated evolution at the chromosomal level supporting the early lung carcinogenesis model from AAH to AIS, MIA and ADC. Subclonal analyses reveal a higher proportion of clonal mutations in AIS/MIA/ADC than AAH suggesting neoplastic transformation of lung preneoplasia is predominantly associated with a selective sweep of unfit subclones. Analysis of multifocal pulmonary nodules from the same patients reveal evidence of convergent evolution.

There has been a drastic increase in detection of lung nodules, many of which are precancers, preinvasive, minimally invasive or sometimes invasive lung cancers. Here, Hu et al. perform multi-region exome sequencing to discern the evolutional trajectory from precancers to invasive lung cancers.

Comparison of lung imaging using three-dimensional ultrashort echo time and zero echo time sequences: preliminary study

OBJECTIVE

To determine the feasibility of using high-resolution volumetric zero echo time (ZTE) sequence in routine lung magnetic resonance imaging (MRI) and compare free breathing 3D ultrashort echo time (UTE) and ZTE lung MRI in terms of image quality and small-nodule detection.

MATERIALS AND METHODS

Our Institutional Review Board approved this study. Twenty patients underwent both UTE and ZTE sequences during routine lung MR. UTE and ZTE images were compared in terms of subjective image quality and detection of lung parenchymal signal, intrapulmonary structures, and sub-centimeter nodules. Differences between the two sequences were compared through statistical analysis.

RESULTS

Lung parenchyma showed significantly (p < 0.05) higher signal-to-noise ratio (SNR) in ZTE than in UTE. The SNR and contrast-to-noise ratio (CNR) of peripheral bronchus and small pulmonary arteries were significantly (all p < 0.05) higher in ZTE. Subjective image quality evaluated by two independent radiologists in terms of depicting normal structures and overall acceptability was superior in ZTE (p < 0.05). The diagnostic accuracy for sub-centimeter nodules was significantly higher for ZTE (reader 1: AUC, 0.972; p = 0.044; reader 2: AUC, 0.946; p = 0.045) than that for UTE (reader 1: AUC, 0.885; reader 2: AUC, 0.855). Mean scan time was 131 s (125-141 s) in ZTE and 467 s (453-508 s) in UTE. ZTE images were obtained with less acoustic noise.

CONCLUSION

Implementing ZTE as an additional sequence in routine lung MR is feasible. ZTE can provide high-resolution pulmonary structural information with better SNR and CNR using shorter time than UTE.

KEY POINTS

• Both UTE and ZTE techniques use very short TEs to capture signals from very short T2/T2* tissues. • ZTE is superior in capturing lung parenchymal signal than UTE. • ZTE provides high-resolution structural information with better SNR and CNR for normal intrapulmonary structures and small nodules using shorter scan time than UTE.