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

Implementation of lung cancer screening at the national level: Polish example

In Poland the national demonstration lung cancer screening program is about to be started in 2019. We share our concerns and discussing most important topics to be resolved while preparing such a program. The decisions made are virtually based on available scientific data and the results of two randomized controlled trials but also on the personal experience gained during the lung cancer screening studies performed in Poland. The most important and comprehensive guidelines and statements, both European and American, have been searched to find an optimal solution adjusted to the Polish national circumstances-as we assume that should be done in each country implementing such a program.

Management of pulmonary nodules

Pulmonary nodules are frequently detected during clinical practice and require a structured approach in their management in order to identify early lung cancers and avoid harm from over investigation. The article reviews the 2015 British Thoracic Society guidelines for the management of pulmonary nodules and the evidence behind them.

Probability of cancer in lung nodules using sequential volumetric screening up to 12 months: the UKLS trial

BACKGROUND

Estimation of the clinical probability of malignancy in patients with pulmonary nodules will facilitate early diagnosis, determine optimum patient management strategies and reduce overall costs.

METHODS

Data from the UK Lung Cancer Screening trial were analysed. Multivariable logistic regression models were used to identify independent predictors and to develop a parsimonious model to estimate the probability of lung cancer in lung nodules detected at baseline and at 3-month and 12-month repeat screening.

RESULTS

Of 1994 participants who underwent CT scan, 1013 participants had a total of 5063 lung nodules and 52 (2.6%) of the participants developed lung cancer during a median follow-up of 4 years. Covariates that predict lung cancer in our model included female gender, asthma, bronchitis, asbestos exposure, history of cancer, early and late onset of family history of lung cancer, smoking duration, FVC, nodule type (pure ground-glass and part-solid) and volume as measured by semiautomated volumetry. The final model incorporating all predictors had excellent discrimination: area under the receiver operating characteristic curve (AUC 0.885, 95% CI 0.880 to 0.889). Internal validation suggested that the model will discriminate well when applied to new data (optimism-corrected AUC 0.882, 95% CI 0.848 to 0.907). The risk model had a good calibration (goodness-of-fit χ[8] 8.13, p=0.42).

CONCLUSIONS

Our model may be used in estimating the probability of lung cancer in nodules detected at baseline and at 3 months and 12 months from baseline, allowing more efficient stratification of follow-up in population-based lung cancer screening programmes.

TRIAL REGISTRATION NUMBER

78513845.

Process improvement for follow-up radiology report recommendations of lung nodules

In the modern healthcare system, there are still wide gaps of communication of imaging results to physician and patient stakeholders and tracking of whether follow-up has occurred. Patients are also unaware of the significance of findings in radiology reports. With the increase in use of cross-sectional imaging such as CT, patients are not only being diagnosed with primary urgent findings but also with incidental findings such as lung nodules; however, they are not being told of their imaging findings nor what actions to take to mitigate their risks. In addition, patients at high risk for developing lung cancer often obtain serial CT scans, but tracking these patients is challenging for the clinician.

In order to advance quality improvement goals and improve patient outcomes, we developed a custom application and business process for radiology practitioners that mines available healthcare data, identifies patients with lung nodules in need of follow-up imaging, notifies the patient and the primary care physician via mail, and measures process efficacy via executed follow-up screenings and captured patient condition.

This integrated analytics and communication process increased our average rate of patient follow-ups for lung nodules from 26.50 in 2015 to 59.72% in 2017. 17.18% of these patients had new lung nodules or worsening severity of lung findings detected at follow-up. This new process has added missing quality and care coordination to an at-risk patient population.

The potential of breath analysis to improve outcome for patients with lung cancer

Lung cancer remains the most common cause of cancer related death in both the UK and USA. Development of diagnostic approaches that have the ability to detect lung cancer early are a research priority with potential to improve survival. Analysis of exhaled breath metabolites, or volatile organic compounds (VOCs) is an area of considerable interest as it could fulfil such requirements. Numerous studies have shown that VOC profiles are different in the breath of patients with lung cancer compared to healthy individuals or those with non-malignant lung diseases. This review provides a scientific and clinical assessment of the potential value of a breath test in lung cancer. It discusses the current understanding of metabolic pathways that contribute to exhaled VOC production in lung cancer and reviews the research conducted to date. Finally, we highlight important areas for future research and discuss how a breath test could be incorporated into various clinical pathways.

Prevalence and Clinical Relevance of Extracardiac Findings in Cardiovascular Magnetic Resonance Imaging

PURPOSE

To assess the prevalence of extracardiac findings (ECF) during cardiovascular magnetic resonance (CMR) examinations and their downstream effect on clinical management.

MATERIALS AND METHODS

We retrospectively identified 500 consecutive patients. Trans-axial balanced steady-state free precession nongated images acquired from the upper thorax to the upper abdomen were evaluated independently by 2 radiologists. ECF were classified as nonsignificant (benign, with no need for further investigation), significant (mandatory to be reported/monitored), and major (clinically remarkable pathology, mandatory to be reported/investigated/treated). Fifteen-month clinical follow-up information was collected through hospital records.

RESULTS

Of 500 patients, 108 (21.6%) showed a total of 153 ECF: 59 (11.8% of the entire study population; 38.5% of all ECF) nonsignificant, 76 (15.2%; 49.7%) significant, and 18 (3.6%; 11.8%) major ECF. The most frequent ECF were pleural effusion, hepatic cyst, renal cyst, and ascending aorta dilatation. Of 94 significant and major ECF, 46 were previously unknown and more common in older patients. Newly diagnosed major ECF (n=11, 2.2% of the entire study population, and 7.2% of all ECF)-including 5 tumors (1% of study population)-were confirmed by downstream evaluations and required specific treatment. Patients with major ECF were significantly older than patients without with major ECF. Newly diagnosed clinically significant and major ECF prompted downstream diagnostic tests in 44% and 100% of cases, respectively.

CONCLUSIONS

The detection of significant and major ECF is common during CMR reporting. The knowledge and the correct identification of most frequent ECF enable earlier diagnoses and faster treatment initiation of unknown extracardiac pathologies in patients referred to CMR imaging.

A Brief Report of Smoking Behaviors in Patients with Incidental Pulmonary Nodules: Associations with Communication and Risk Perception

Introduction:

Incidental pulmonary nodules (IPNs) are commonly found on routine chest imaging. Little is known about smoking behaviors among patients with IPNs or characteristics of patient-clinician communication that may contribute to these behaviors. We assessed the association of patient characteristics and communication quality with smoking behaviors and stage of change for tobacco cessation among patients with IPNs.

Materials and methods:

Prospective, repeated-measures, cohort study of current smokers and past-year quitters with IPNs treated within the Veterans Affairs Portland Health Care System. Eligible patients had newly reported, incidental nodules <3 cm planned for non-urgent computed tomography (CT) follow-up. Our primary outcomes were changes in amount smoked and stage of change for tobacco cessation throughout the follow-up period. We used multivariable-adjusted generalized estimating equations for analyses.

Results:

We identified 37 current smokers and 9 recent quitters. By the final visit, 8 of 36 (22%) baseline smokers had quit and 2 of 7 (29%) recent quitters had resumed smoking. Of 40 respondents, 23 (58%) reported receiving any tobacco treatment (recommendation to quit, medication, and/or behavioral treatment) at least once during follow-up. We found no significant associations of high-quality communication, patient distress, self-perceived risk of lung cancer, and self-reported clinician-recommended smoking cessation interventions with decrease in amount smoked or positive stage of change.

Conclusions:

Many smokers and recent quitters with IPNs quit during follow-up, though nearly half reported no quit support. We found no association between communication quality or quit support and decreased smoking. The intensity of tobacco treatment offered may have been insufficient to affect behavior.

Histogram-based models on non-thin section chest CT predict invasiveness of primary lung adenocarcinoma subsolid nodules

109 pathologically proven subsolid nodules (SSN) were segmented by 2 readers on non-thin section chest CT with a lung nodule analysis software followed by extraction of CT attenuation histogram and geometric features. Functional data analysis of histograms provided data driven features (FPC1,2,3) used in further model building. Nodules were classified as pre-invasive (P1, atypical adenomatous hyperplasia and adenocarcinoma in situ), minimally invasive (P2) and invasive adenocarcinomas (P3). P1 and P2 were grouped together (T1) versus P3 (T2). Various combinations of features were compared in predictive models for binary nodule classification (T1/T2), using multiple logistic regression and non-linear classifiers. Area under ROC curve (AUC) was used as diagnostic performance criteria. Inter-reader variability was assessed using Cohen’s Kappa and intra-class coefficient (ICC). Three models predicting invasiveness of SSN were selected based on AUC. First model included 87.5 percentile of CT lesion attenuation (Q.875), interquartile range (IQR), volume and maximum/minimum diameter ratio (AUC:0.89, 95%CI:[0.75 1]). Second model included FPC1, volume and diameter ratio (AUC:0.91, 95%CI:[0.77 1]). Third model included FPC1, FPC2 and volume (AUC:0.89, 95%CI:[0.73 1]). Inter-reader variability was excellent (Kappa:0.95, ICC:0.98). Parsimonious models using histogram and geometric features differentiated invasive from minimally invasive/pre-invasive SSN with good predictive performance in non-thin section CT.

Clinical characteristics and prognosis of ground-glass opacity nodules in young patients

Background

The detection rate of ground-glass opacity (GGO) in young patients has increased year by year with the increasingly widespread use of high-resolution computed tomography (HRCT) and the increased resolution of HRCT imaging. However, no scholars have reported the clinical characteristics and prognosis of GGO in young patients systematically. The purpose of this study is to investigate the clinical characteristics and prognosis presenting as GGO in young patients.

Methods

Clinical data of 127 young patients who were diagnosed as GGO and who underwent video-assisted thoracoscopic surgery (VATS) and had routine pathological examination were collected from January 2016 to January 2017. Nodules were classified according to benign and malignant: 26 benign nodules (Group A) and 115 malignant nodules (Group B). The pathological types, nodules size, surgical methods were analyzed, and the clinical characteristics and prognosis were evaluated.

Results

The results of pathological examination of 91 pure ground-glass opacities (pGGOs) revealed 16 adenocarcinoma in situs (AISs), 42 micro invasive adenocarcinomas (MIAs), 13 invasive adenocarcinomas (IAs), 8 atypical adenomatous hyperplasias (AAHs), 1 inflammatory granuloma, 2 pulmonary inflammatory pseudotumors (IPTs) and 9 other benign nodules. The results of pathological examination of 50 mixed ground-glass opacities (mGGOs) revealed 6 AISs, 29 MIAs, 9 IAs, 1 AAH, 2 inflammatory granulomas and 3 other benign nodules. All patients had no lymph nodes invasion. The rates of perioperative complications were 6.30%, compared to 7.63% for long-term complications. None of the patients with GGO experienced a recurrence and death [2-year recurrence-free survival (RFS), 100%; 2-year overall survival (OS), 100%].

Conclusions

The GGO in young patients that received VATS has a high proportion of malignant, its prognosis is satisfied.

Peripheral vessel and air bronchograms for detecting the pathologic patterns of subsolid nodules

PURPOSE

To assess the relationships of subsolid nodules (SSNs) with peripheral vessels and aerated bronchi using computed tomography (CT), and to correlate the imaging features with the benign/malignant pathological diagnoses.

METHODS

This study retrospectively analyzed data from 83 patients with a solitary SSN (January 2008 to December 2016). SSNs were imaged (LightSpeed 64-slice spiral CT, General Electric, USA), their mean diameter determined, and the relationship with peripheral vessels (types I-IV) and aerated bronchi (types I-V) were classified. Pathologic diagnoses were obtained from the surgical specimens.

RESULTS

SSNs were diagnosed as benign (n = 29), pre-invasive (n = 9), micro-invasive adenocarcinoma (n = 7) and invasive adenocarcinoma (n = 38). SSN size, peripheral vessel class and aerated bronchus class differed between pathologic types (P < 0.05). For benign SSNs, peripheral vessel type II (58.6%) was most common, followed by III (20.7%) and IV (6.9%). Aerated bronchus type V (65.5%) was most frequent, followed by IV (27.6%); type I aerated bronchus was not observed. No cases of micro-invasive or invasive adenocarcinoma were peripheral vessel type I or aerated bronchus type V. For invasive adenocarcinoma, 92.1% were peripheral vessel types III + IV while 71.8% were aerated bronchus types I + II.

CONCLUSIONS

SSN pathologic types differ with regard to peripheral vessel and aerated bronchus types. Type I peripheral vessel and type V aerated bronchus (both least involved) suggest a benign lesion, whereas type III/IV peripheral vessel and type I/II aerated bronchus (both most involved) suggest malignancy.

Post-imaging pulmonary nodule mathematical prediction models: are they clinically relevant?

OBJECTIVES

Post-imaging mathematical prediction models (MPMs) provide guidance for the management of solid pulmonary nodules by providing a lung cancer risk score from demographic and radiologists-indicated imaging characteristics. We hypothesized calibrating the MPM risk score threshold to a local study cohort would result in improved performance over the original recommended MPM thresholds. We compared the pre- and post-calibration performance of four MPM models and determined if improvement in MPM prediction occurs as nodules are imaged longitudinally.

MATERIALS AND METHODS

A common cohort of 317 individuals with computed tomography-detected, solid nodules (80 malignant, 237 benign) were used to evaluate the MPM performance. We created a web-based application for this study that allows others to easily calibrate thresholds and analyze the performance of MPMs on their local cohort. Thirty patients with repeated imaging were tested for improved performance longitudinally.

RESULTS

Using calibrated thresholds, Mayo Clinic and Brock University (BU) MPMs performed the best (AUC = 0.63, 0.61) compared to the Veteran's Affairs (0.51) and Peking University (0.55). Only BU had consensus with the original MPM threshold; the other calibrated thresholds improved MPM accuracy. No significant improvements in accuracy were found longitudinally between time points.

CONCLUSIONS

Calibration to a common cohort can select the best-performing MPM for your institution. Without calibration, BU has the most stable performance in solid nodules ≥ 8 mm but has only moderate potential to refine subjects into appropriate workup. Application of MPM is recommended only at initial evaluation as no increase in accuracy was achieved over time.

KEY POINTS

• Post-imaging lung cancer risk mathematical predication models (MPMs) perform poorly on local populations without calibration. • An application is provided to facilitate calibration to new study cohorts: the Mayo Clinic model, the U.S. Department of Veteran's Affairs model, the Brock University model, and the Peking University model. • No significant improvement in risk prediction occurred in nodules with repeated imaging sessions, indicating the potential value of risk prediction application is limited to the initial evaluation.

Computed Tomography-Based Radiomics Signature: A Potential Indicator of Epidermal Growth Factor Receptor Mutation in Pulmonary Adenocarcinoma Appearing as a Subsolid Nodule

BACKGROUND

Lung adenocarcinoma (LADC) with epidermal growth factor receptor (EGFR) mutation is considered a subgroup of lung cancer sensitive to EGFR-targeted tyrosine kinase inhibitors. We aimed to develop and validate a computed tomography (CT)-based radiomics signature for prediction of EGFR mutation status in LADC appearing as a subsolid nodule.

MATERIALS AND METHODS

A total of 467 eligible patients were divided into training and validation cohorts (n = 306 and 161, respectively). Radiomics features were extracted from unenhanced CT images by using Pyradiomics. A CT-based radiomics signature for distinguishing EGFR mutation status was constructed using the random forest (RF) method in the training cohort and then tested in the validation cohort. A combination of the radiomics signature with a clinical factors model was also constructed using the RF method. The performance of the model was evaluated using the area under the curve (AUC) of a receiver operating characteristic curve.

RESULTS

In this study, 64.2% (300/467) of the patients showed EGFR mutations. L858R mutation of exon 21 was the most common mutation type (185/301). We identified a CT-based radiomics signature that successfully discriminated between EGFR positive and EGFR negative in the training cohort (AUC = 0.831) and the validation cohort (AUC = 0.789). The radiomics signature combined with the clinical factors model was not superior to the simple radiomics signature in the two cohorts (p > .05).

CONCLUSION

As a noninvasive method, the CT-based radiomics signature can be used to predict the EGFR mutation status of LADC appearing as a subsolid nodule.

IMPLICATIONS FOR PRACTICE

Lung adenocarcinoma (LADC) with epidermal growth factor receptor (EGFR) mutation is considered a subgroup of lung cancer that is sensitive to EGFR-targeted tyrosine kinase inhibitors. However, some patients with inoperable subsolid LADC are unable to undergo tissue sampling by biopsy for molecular analysis in clinical practice. A computed tomography-based radiomics signature may serve as a noninvasive biomarker to predict the EGFR mutation status of subsolid LADCs when mutational profiling is not available or possible.

Detection of Pulmonary Nodule Growth with Chest Tomosynthesis: A Human Observer Study Using Simulated Nodules

RATIONALE AND OBJECTIVES

Chest tomosynthesis has been suggested as a suitable alternative to CT for follow-up of pulmonary nodules. The aim of the present study was to investigate the possibility of detecting pulmonary nodule growth using chest tomosynthesis.

MATERIALS AND METHODS

Simulated nodules with volumes of approximately 100 mm³ and 300 mm³ as well as additional versions with increasing volumes were created. The nodules were inserted into images from pairs of chest tomosynthesis examinations, simulating cases where the nodule had either remained stable in size or increased in size between the two imaging occasions. Nodule volume growths ranging from 11% to 252% were included. A simulated dose reduction was applied to a subset of the cases. Cases differing in terms of nodule size, dose level, and nodule position relative to the plane of image reconstruction were included. Observers rated their confidence that the nodules were stable in size or not. The rating data for the nodules that were stable in size was compared to the rating data for the nodules simulated to have increased in size using ROC analysis.

RESULTS

Area under the curve values ranging from 0.65 to 1 were found. The lowest area under the curve values were found when there was a mismatch in nodule position relative to the reconstructed image plane between the two examinations. Nodule size and dose level affected the results.

CONCLUSION

The study indicates that chest tomosynthesis can be used to detect pulmonary nodule growth. Nodule size, dose level, and mismatch in position relative to the image reconstruction plane in the baseline and follow-up examination may affect the precision.

Development of a Risk Prediction Model to Estimate the Probability of Malignancy in Pulmonary Nodules Being Considered for Biopsy

BACKGROUND

Malignancy probability models for pulmonary nodules (PN) are most accurate when used within populations similar to those in which they were developed. Our goal was to develop a malignancy probability model that estimates the probability of malignancy for PNs considered high enough risk to recommend biopsy.

METHODS

This retrospective analysis included training and validation datasets of patients with PNs who had a histopathologic diagnosis of malignant or benign. Radiographic and clinical characteristics associated with lung cancer were collected. Univariate logistic regression was used to identify potential predictors. Stepdown selection and multivariate logistic regression were used to build several models, each differing according to available data.

RESULTS

Two hundred malignant nodules and 101 benign nodules were used to generate and internally validate eight models. Predictors of lung cancer used in the final models included age, smoking history, upper lobe location, solid and irregular/spiculated nodule edges, emphysema, fluorodeoxyglucose-PET avidity, and history of cancer other than lung. The concordance index (C-index) of the models ranged from 0.75 to 0.81. They were more accurate than the Mayo Clinic model (P < .05 for four of the models), and each had fair to excellent calibration. In an independent sample used for validation, the C-index for our model was 0.67 compared with 0.63 for the Mayo Clinic model. The ratio of malignant to benign nodules within each probability decile showed a greater potential to influence clinical decisions than the Mayo Clinic model.

CONCLUSIONS

We developed eight models to help characterize PNs considered high enough risk by a clinician to recommend biopsy. These models may help to guide clinicians' decision-making and be used as a resource for patient communication.

Solitary pulmonary nodule: Comparison of quantitative capability for differentiation and management among dynamic CE-perfusion MRI at 3 T system, dynamic CE-perfusion ADCT and FDG-PET/CT

PURPOSE

To prospectively compare the capability of dynamic first-pass contrast-enhanced (CE) perfusion MR imaging with ultra-short TE and area-detector CT (ADCT), analyzed with the same mathematical methods, and that of FDG-PET/CT for diagnosis and management of solitary pulmonary nodules (SPNs).

METHODS AND MATERIALS

Our institutional review board approved this study and written informed consent was obtained from all subjects. A total 57 consecutive patients with 71 nodules prospectively underwent dynamic CE-perfusion ADCT and MR imaging with ultra-short TE, FDG-PET/CT, as well as microbacterial and/or pathological examinations. The nodules were classified into malignant nodules (n = 45) and benign nodules (n = 26). Pulmonary arterial, systemic arterial and total perfusions were determined by means of dual-input maximum slope models on ADCT and MR imaging and maximum values of standard uptake values (SUV_max) on PET/CT. Receiver operating characteristic (ROC) analysis was performed for each index, and sensitivity, specificity and accuracy were compared by McNemar's test.

RESULTS

Areas under the curve (Azs) of total perfusion on ADCT (Az = 0.89) and MR imaging (Az = 0.88) were significantly larger than those of systemic arterial perfusion and MR imaging (p<0.05). Accuracy of total perfusion on ADCT (87.3% [62/71]) and MR imaging (87.3% [62/71]) was significantly higher than that of systemic arterial perfusion for both methods (77.5% [55/71] p = 0.02) and SUV_max (78.9% [56/71], p = 0.03).

CONCLUSION

Dynamic CE-perfusion MR imaging with ultra-short TE and ADCT and have similar potential capabilities, and are superior to FDG-PET/CT in this setting.

[Imaging before and after endoscopic lung volume reduction]

The treatment of symptomatic lung emphysema by lung volume reduction has become established over the last 15 years. While surgical partial lung resection has profited from improved and less invasive surgical techniques, various endoscopic interventional procedures have been developed and are now available for use. All treatment approaches are dependent on individual anatomical variants and a regional distribution of the lung emphysema, which is why no procedure can be designated as the gold standard for all patients. High-resolution computed tomography can be qualitatively evaluated and provides decisive information for treatment, which is why radiologists play a particularly important role in treatment planning and aftercare of an intervention for reduction of the lung volume. This article presents the various endoscopic techniques, names the demands of the treating physician on the advising radiologist and finally describes how a treatment decision is derived from the results obtained.

Use of an Anthropomorphic Chest Model to Evaluate Multiple Scanning Protocols for High-Definition and Standard-Definition Computed Tomography to Detect Small Pulmonary Nodules

BACKGROUND This study aimed to use the LUNGMAN N1 anthropomorphic chest model to evaluate protocols for high-definition computed tomography (HDCT) and standard-definition CT (SDCT) to detect and compare small pulmonary nodules and determine the most appropriate low-dose scanning protocols. MATERIAL AND METHODS HDCT imaging used the Discovery HD750 scanner (80, 100, 120 and 140 kVp; 360, 320, 280, 240, 200, 160, 120, 80, 40, and 20 mA), and SDCT imaging used the Lightspeed VCT scanner (80, 120, and 140 kVp; 360, 320, 280, 240, 200, 160, 120, 80, 40, and 20 mA). The LUNGMAN N1 anthropomorphic chest model contained artificial pulmonary nodules (diameter: 5, 8, 10, and 12 mm). Low-dose scanning protocols were used in image acquisition. Two experienced radiologists evaluated the image quality. The combinations of voltage, tube current, image noise, and radiation dose were recorded. Consistency of the image quality between raters was assessed by kappa statistical analysis. RESULTS Seventy CT scans of pulmonary nodules (diameter, 5-12 mm) were performed. There was a high degree of consistency for image quality between the two observers (K=0.929 for 5 mm nodules; K=0.819 for overall image quality). For 8 mm nodules, 100% were detected on both SDCT and HDCT. HDCT outperformed SDCT by 5%, in terms of effective dose. There was no significant difference in image quality between the SDCT and HDCT scanners. CONCLUSIONS Using an anthropomorphic chest model, the identification and image quality using SDCT was similar to that of HDCT for small pulmonary nodules between 5-12 mm.

Efficiency and reproducibility in pulmonary nodule detection in simulated dose reduction lung CT images

Purpose

To determine the reproducibility and productivity of reduced dose chest computed tomography (CT) using a nodule detection task.

Materials and methods

Eighty-eight consecutive non-contrast CT examinations were performed using an automatic exposure system with a reference standard deviation of 8.5. Simulated raw data of a reduced dose scan (standard deviation at 21 and 29) were generated with a dose simulator. Original and simulated raw data were reconstructed to series of 7-mm-thick images (Original, Simulation A, Simulation B). In the first part of the reading experiment, three readers independently interpreted these images (88 cases × 3 series) and recorded the size, type, and location of the pulmonary nodules. The reading time for every case was recorded. In the second part of the experiment, the repeated interpretation of standard dose images was performed by two readers. Concordance or discordance of nodule detection between the first and the repeated reading result was assessed.

Results

A statistically significant difference in the detected nodule counts for lesions less than 5 mm by one reader was observed in simulation B images. Discordance of the interpretation result was found only in ground-glass nodules larger than 5 mm detected by one reader in simulation B images. There was no statistically significant difference in the reading time among the three image types.

Conclusion

Simulated standard deviation 21 images can reproduce the image interpretation result of original images, whereas simulated standard deviation 29 images may compromise the accuracy of nodule assessment. The effect on the reading time was not observed with dose reduction simulation.

Spectral CT and its specific values in the staging of patients with non-small cell lung cancer: technical possibilities and clinical impact

AIM

To investigate how spectral computed tomography (SCT) values impact the staging of non-small cell lung cancer (NSCLC) patients.

MATERIALS AND METHODS

One hundred and thirteen patients with confirmed NSCLC were included in a prospective cohort study. All patients underwent single-phase contrast-enhanced SCT (using the fast tube voltage switching technique, 80-140 kV). SCT values (iodine content [IC], spectral slope pitch, and radiodensity increase) of malignant tissue (primary and metastases) and lymph nodes (LNs) were measured. Adrenal masses were evaluated in a virtual non-contrast series (VNS). If pulmonary embolism was present, pulmonary perfusion was analysed as an additional finding.

RESULTS

Fifty-two untreated primary NSCLC lesions were evaluable. Lung adenocarcinoma had significantly higher normalised IC (NIC: 19.37) than squamous cell carcinoma (NIC: 12.03; p=0.035). Pulmonary metastases were not significantly different from benign lung nodules. A total of 126 LNs were analysed and histologically proven metastatic LNs (2.08 mg/ml) had significantly lower IC than benign LNs (2.58 mg/ml; p=0.023). Among 34 adrenal masses, VNS identified adenomas with high sensitivity (91%) and specificity (100%). In two patients, a perfusion defect due to pulmonary embolism was detected in the iodine images.

CONCLUSION

SCT may contribute to the differentiation of histological NSCLC subtypes and improve the identification of LN metastases. VNS differentiates adrenal adenoma from metastasis. In case of pulmonary embolism, iodine imaging can visualise associated pulmonary perfusion defects.

Transthoracic computed tomography-guided lung biopsy in the new era of personalized medicine

Computed tomography-guided lung biopsy is a valid and safe procedure for characterizing pulmonary nodules. In the past years, this technique has been mainly used to confirm the malignant nature of undetermined pulmonary lesions; however, today its role has been completely renewed. With the advent of target therapy and immunotherapy, it has arisen for lung cancer, in inoperable patients, the necessity to obtain adequate bioptical material to perform a correct molecular characterization of the lesion. Moreover, the possibility of acquired drug-resistance mechanisms makes it necessary in some cases to rebiopsy these lesions over time. For these reasons, it is likely that the request of computed tomography-guided lung biopsy will increase in the future, therefore every radiologist should be confident with its most important aspects.

Incidentalomas in Spine and Spinal Cord Imaging

Incidentalomas are common in magnetic resonance imaging (MRI) of the spine. These incidental findings (IFs) can be seen involving the spinal cord, nerve root, vertebral body, posterior arch and the extraspinal region. This review article describes the imaging findings, stratifies the IFs similar to the computed tomography (CT) colonography reporting and data system and briefly mentions the current recommendations for further evaluation and management of IFs. Radiologists are the first to detect these lesions, suggest further evaluation and management of IFs. It is therefore mandatory for them to be aware of recommendations in clinical practice in order to avoid increased patient anxiety, excessive healthcare expenditure and inadvertent therapeutic procedures.

CT Characteristics and Pathologic Basis of Solitary Cystic Lung Cancer

There are increasing reports of a type of lung cancer that manifests as solitary cystic airspaces. The purpose of this case series was to identify the CT features and possible mechanisms of solitary cystic lung cancer, on the basis of CT observations and pathologic characteristics. The clinical, imaging, and pathologic data of 106 patients with solitary cystic lung cancer were collected and analyzed between January 2011 and December 2017. CT images were reviewed independently by three radiologists who were blinded to pathologic findings. Demographic data and clinical and smoking status were extracted from the medical records. The mean age was 58.8 years 6 10.6 (standard deviation) (range, 30–82 years). CT features in the 106 patients included nonuniform cystic walls in 96 (90.6%) patients, cyst septations in 62 (58.5%) patients, nodular walls in 58 (54.7%) patients, ground-glass opacity around the cyst in 53 patients (50.0%), and irregular margins in 42 (39.6%) patients. At histologic examination, the majority of cases (81 [87.1%] of 93) were adenocarcinoma.

Interchangeability between real and three-dimensional simulated lung tumors in computed tomography: an interalgorithm volumetry study

Using hybrid datasets consisting of patient-derived computed tomography (CT) images with digitally inserted computational tumors, we establish volumetric interchangeability between real and computational lung tumors in CT. Pathologically-confirmed malignancies from 30 thoracic patient cases from the RIDER database were modeled. Tumors were either isolated or attached to lung structures. Patient images were acquired on one of two CT scanner models (Lightspeed 16 or VCT; GE Healthcare) using standard chest protocol. Real tumors were segmented and used to inform the size and shape of simulated tumors. Simulated tumors developed in Duke Lesion Tool (Duke University) were inserted using a validated image-domain insertion program. Four readers performed volume measurements using three commercial segmentation tools. We compared the volume estimation performance of segmentation tools between real tumors in actual patient CT images and corresponding simulated tumors virtually inserted into the same patient images (i.e., hybrid datasets). Comparisons involved (1) direct assessment of measured volumes and the standard deviation between simulated and real tumors across readers and tools, respectively, (2) multivariate analysis, involving segmentation tools, readers, tumor shape, and attachment, and (3) effect of local tumor environment on volume measurement. Volume comparison showed consistent trends (9% volumetric difference) between real and simulated tumors across all segmentation tools, readers, shapes, and attachments. Across all cases, readers, and segmentation tools, an intraclass correlation coefficient = 0.99 indicates that simulated tumors correlated strongly with real tumors ( p = 0.95 ). In addition, the impact of the local tumor environment on tumor volume measurement was found to have a segmentation tool-related influence. Strong agreement between simulated tumors modeled in this study compared to their real counterparts suggests a high degree of similarity. This indicates that, volumetrically, simulated tumors embedded into patient CT data can serve as reasonable surrogates to real patient data.

Effect of Dynamic Workstation Use on Radiologist Detection of Pulmonary Nodules on CT

PURPOSE

The aim of this study was to determine the effects of using a treadmill workstation during CT interpretation on radiologists' sensitivity for lung nodule detection, accuracy and adherence to accepted management recommendations, and examination interpretation time.

METHODS

This HIPAA-compliant study was approved by the institutional review board. Three radiologists performed a retrospective review of 55 CT examinations of the chest originally performed for lung cancer screening. These studies were reviewed both while sitting at a conventional workstation and while walking at a treadmill workstation. A separate thoracic radiologist reviewed the examinations at a conventional workstation only to serve as a control. The number of pulmonary nodules detected, accuracy of or adherence to follow-up recommendations, and time required for examination interpretation were recorded and compared between each condition.

RESULTS

There was no statistically significant difference in the total number of nodules detected while walking versus seated. Intraobserver follow-up recommendations were consistent to highly consistent between sitting and walking. There was moderate interobserver agreement between the radiologists' recommendation for seated versus walking conditions. There was a statistically significant difference in time taken to complete each examination, with interpretation during walking taking less time than during sitting.

CONCLUSIONS

Use of a treadmill workstation does not significantly affect the detection of lung nodules on CT or lead to changes in management recommendations but does decrease examination interpretation time.

Implementation planning for lung cancer screening in China

Lung cancer is the leading cause of cancer-related deaths in China, with over 690 000 lung cancer deaths estimated in 2018. The mortality has increased about five-fold from the mid-1970s to the 2000s. Lung cancer low-dose computerized tomography (LDCT) screening in smokers was shown to improve survival in the US National Lung Screening Trial, and more recently in the European NELSON trial. However, although the predominant risk factor, smoking contributes to a lower fraction of lung cancers in China than in the UK and USA. Therefore, it is necessary to establish Chinese-specific screening strategies. There have been 23 associated programmes completed or still ongoing in China since the 1980s, mainly after 2000; and one has recently been planned. Generally, their entry criteria are not smoking-stringent. Most of the Chinese programmes have reported preliminary results only, which demonstrated a different high-risk subpopulation of lung cancer in China. Evidence concerning LDCT screening implementation is based on results of randomized controlled trials outside China. LDCT screening programmes combining tobacco control would produce more benefits. Population recruitment (e.g. risk-based selection), screening protocol, nodule management and cost-effectiveness are discussed in detail. In China, the high-risk subpopulation eligible for lung cancer screening has not as yet been confirmed, as all the risk parameters have not as yet been determined. Although evidence on best practice for implementation of lung cancer screening has been accumulating in other countries, further research in China is urgently required, as China is now facing a lung cancer epidemic.

Does aggressive management of solitary pulmonary nodules pay off?

Indeterminate solitary pulmonary nodules (SPNs), measuring up to 3 cm in diameter, are incidental radiological findings. The ever-growing use of modern imaging has increased their detection. The majority of those nodules are benign; however, the possibility of diagnosing early-stage lung cancer still stands. Guidelines for the management of SPNs have never been validated in prospective comparative studies.

Positron emission tomography (PET) is a useful tool to provide functional information on SPNs. However, overall sensitivity and specificity of PET in detecting malignant SPNs of at least 10 mm in diameter are about 90% and false-negative results are reported.

The development of video-assisted thoracic surgery has provided minimally invasive diagnosis and treatment of SPNs. In our series, 105 patients underwent surgery based on combined increased ¹⁸F-labelled 2-fluoro-2-deoxy-d-glucose (FDG) uptake on PET computed tomography and radiological features (morphology and density) without prior histological confirmation. We detected 26 false negatives (24.8%) and only nine false positives (8.57%). Therefore, our minimally invasive surgical approach prevented 25% of patients with lung cancer from a delayed treatment versus only 9% undergoing “overtreatment”.

In our monocentric cohort, patients with SPNs with large diameter, irregular outline, no calcifications, central location, increased FDG uptake and/or subsolid aspect benefited from a primary surgical resection.

There is much debate on the best management of solitary pulmonary nodules. Even if they are mostly benign, they may represent an early-stage lung cancer. Minimally invasive surgical removal is probably the best approach to this insidious disease.http://ow.ly/wMKz30nemjR

Diagnostic and clinical features of lung cancer associated with cystic airspaces

"Lung cancer associated with cystic airspaces" is an uncommon manifestation, in which lung cancer presents on imaging studies with a cystic area with associated consolidation and/or ground glass. With the widespread use of computed tomography (CT), both in clinical practice and for lung cancer screening, these tumors are being more frequently recognized. An association of this entity with smoking has been established with the majority of cases reported being in former and current smokers. The true pathogenesis of the cystic airspace is not yet fully understood. Different causes of this cystic airspace have been described, including a check-valve mechanism obstructing the small airways, lepidic growth of adenocarcinoma on emphysematous lung parenchyma, cyst formation of tumor and tumor growth along the wall of a pre-existing bulla. Adenocarcinoma is the commonest histological type, followed by squamous cell carcinoma. Two classification systems have been described, based on morphological features of the lesion, taking into account both the cystic airspace as well as the morphology of the surrounding consolidation or ground glass. The cystic component may mislead radiologists to a benign etiology and the many different faces on imaging can make early diagnosis challenging. Special attention should be made to focal or diffuse wall thickening and consolidation or ground glass abutting or interspersed with cystic airspaces. Despite their atypical morphology, staging and management currently are still similar to that of other lung cancer types. Although the rarity of this entity will hamper larger studies, numerous aspects regarding this particular lung cancer type still need to be unraveled. This manuscript reviews the CT-imaging findings and gives an overview of available data in the English literature on pathogenesis, histopathology and clinical findings. Differential diagnosis and pitfalls are discussed as well as future directions regarding staging and management.

CT-guided coaxial biopsy of malignant lung lesions: are cores from 20-gauge needle adequate for histologic diagnosis and molecular analysis?

Background

To determine the number of cores adequate for histopathologic diagnosis as well as evaluate the success rate of molecular analyses in CT-guided percutaneous core needle biopsy (PCNB) for malignant pulmonary lesions using a 20-guage coaxial needle.

Methods

Biopsy records of 196 malignant lung lesions were reviewed. Core obtained from each needle pass was put in a separate container for individual pathological analysis. Types of molecular analysis attempted and their success rates were recorded for each patient. We categorized each patient into one of six groups according to the number of cores (n=1, n=2, n=3, n=4, n=5, n≥6) acquired, and diagnostic sensitivity for histopathologic diagnosis was calculated for each core in each group. In order to assess the increase in cumulative sensitivity up to 4th core, the data from 1st to 4th needle passes in 4-, 5-, and ≥6-core groups were pooled and cumulative diagnostic sensitivities up to 4th core were calculated.

Results

Of 196 cases of lung malignancies, five different types of molecular studies (EGFR mutation, ALK translocation, KRAS mutation, RET and ROS1 rearrangements) were attempted with PCNB specimens in 100 cases and successfully done in 96 cases (96.0%). In ≥4-core group (4-, 5-, and ≥6-core groups combined; n=148), cumulative sensitivity increased from 83.8% to 89.9% between 1st and 2nd cores, 89.9% to 93.2% between 2nd and 3rd cores, and 93.2% to 94.6% between 3rd and 4th cores.

Conclusions

The cumulative diagnostic sensitivity for the histopathologic diagnosis increases significantly between the second and fourth sampling. Multiple samples obtained with a 20-guage coaxial needle are adequate and have a high success rate for various molecular studies for lung malignancy.

Electromagnetic navigation bronchoscopic dye marking for localization of small subsolid nodules: Retrospective observational study

Thoracoscopic resection of small subsolid nodules is challenging and requires preoperative localization. We investigated the efficacy, safety, and factors affecting accuracy in localizing pulmonary nodules with electromagnetic navigation bronchoscopy (ENB)-guided dye marking.Patients with small subsolid nodule(s) who underwent thoracoscopic resection after ENB-guided dye marking were retrospectively reviewed. Dye marking was performed at the nearest pleura and the localized nodule(s) was resected thoracoscopically. Efficacy was evaluated by success rates of dye marking and resection of nodules. Navigation accuracy was represented by target distance, which was the closest distance between target and the tip of locatable guide. Factors affecting target distance were evaluated by linear regression analyses.Twenty-nine ENB-guided dye markings were done for 24 nodules in 20 patients. The success rate of the dye marking and nodule localization were 93.1% (27/29) and 95.8% (23/24), respectively. Twenty-three nodules were completely resected thoracoscopically without conversion. There were no ENB-related complications: pneumothorax or bronchopulmonary hemorrhage. Nine targets were in the upper, 14 in the middle, and 6 in the lower zone. Even though navigation time was longer in the upper zone, target distance showed no significant inter-zone difference. Approach angle was the only significant predictor for target distance (0-45°, estimate = -1.24, P = .01; 45-90°, estimate = -1.26, P = .006; reference = ≥90°).Localization with ENB-guided dye marking is effective and safe for thoracoscopic resection of small subsolid nodules. For better performance, a pathway with smaller approach angle (<90°) should be selected to increase the navigation accuracy.

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.

Explaining Deep Features Using Radiologist-Defined Semantic Features and Traditional Quantitative Features

Quantitative features are generated from a tumor phenotype by various data characterization, feature-extraction approaches and have been used successfully as a biomarker. These features give us information about a nodule, for example, nodule size, pixel intensity, histogram-based information, and texture information from wavelets or a convolution kernel. Semantic features, on the other hand, can be generated by an experienced radiologist and consist of the common characteristics of a tumor, for example, location of a tumor, fissure, or pleural wall attachment, presence of fibrosis or emphysema, concave cut on nodule surface. These features have been derived for lung nodules by our group. Semantic features have also shown promise in predicting malignancy. Deep features from images are generally extracted from the last layers before the classification layer of a convolutional neural network (CNN). By training with the use of different types of images, the CNN learns to recognize various patterns and textures. But when we extract deep features, there is no specific naming approach for them, other than denoting them by the feature column number (position of a neuron in a hidden layer). In this study, we tried to relate and explain deep features with respect to traditional quantitative features and semantic features. We discovered that 26 deep features from the Vgg-S neural network and 12 deep features from our trained CNN could be explained by semantic or traditional quantitative features. From this, we concluded that those deep features can have a recognizable definition via semantic or quantitative features.

The use of ultrasound in detecting and defining ground-glass opacities: results of an ex vivo evaluation

OBJECTIVES

To evaluate the role of ultrasound in detecting and defining ground-glass opacities (GGOs) in surgical specimens of patients undergoing thoracoscopic diagnostic resection.

METHODS

We performed an observational single-centre study of all consecutive patients undergoing thoracoscopic diagnostic resection of GGOs. In each patient, the specimen was scanned with ultrasound; then, a needle was inserted into the lesion to facilitate its detection by the pathologist. We evaluated the rate of detection with ultrasound, compared the size and depth measurements of the lesions as determined from ultrasound scans with those from the histological specimens and correlated the ultrasound findings with the histological subtypes of adenocarcinomas.

RESULTS

We reviewed 17 tissue samples. The final diagnoses were 1 (6%) atypical adenomatous hyperplasia, 5 (29%) adenocarcinomas in situ, 4 (24%) minimally invasive adenocarcinomas and 7 (41%) invasive adenocarcinomas. All tumours were successfully identified using ultrasound. The size (P = 0.87) and depth (P = 0.25) of the lesions measured with ultrasound did not significantly differ from the measurements obtained from the histological specimens. In addition, ultrasound size (r = 0.945; P < 0.0001) and depth (r = 0.588; P = 0.013) were significantly correlated with the pathological measurements. All lesions with hyperechoic findings (n = 6) were pure GGOs, whereas lesions with mixed echoic (n = 11) patterns were mixed GGOs. We were unable to differentiate the histological subtypes of adenocarcinomas using the ultrasound scans.

CONCLUSIONS

Detection of GGOs on ultrasound scans is feasible, but differentiation of the histological subtypes of adenocarcinomas is not possible. The next step is to evaluate the intraoperative reproducibility of our results.

Adoption of a Closed-Loop Communication Tool to Establish and Execute a Collaborative Follow-Up Plan for Incidental Pulmonary Nodules

OBJECTIVE. The purpose of this study is to assess radiologists' adoption of a closed-loop communication and tracking system, Result Alert and Development of Automated Resolution (RADAR), for incidental pulmonary nodules and to measure its effect on the completeness of radiologists' follow-up recommendations. MATERIALS AND METHODS. This retrospective study was performed at a tertiary academic center that performs more than 600,000 radiology examinations annually. Before RADAR, the institution's standard of care was for radiologists to generate alerts for newly discovered incidental pulmonary nodules using a previously described PACS-embedded software tool. RADAR is a new closed-loop communication tool embedded in the PACS and enterprise provider workflow that enables establishing a collaborative follow-up plan between a radiologist and referring provider and helps automate collaborative follow-up plan tracking and execution. We assessed RADAR adoption for incidental pulmonary nodules, the primary outcome, in our thoracic radiology division (study period March 9, 2018, through August 2, 2018). The secondary outcome was the completeness of follow-up recommendation for incidental pulmonary nodules, defined as explicit imaging modality and time frame for follow-up. RESULTS. After implementation, 106 of 183 (58%) incidental pulmonary nodules alerts were generated using RADAR. RADAR adoption increased by 75% during the study period (40% in the first 3 weeks vs 70% in the last 3 weeks; p < 0.001 test for trend). All RADAR alerts had explicit documentation of imaging modality and follow-up time frame, compared with 71% for non-RADAR alerts for incidental pulmonary nodules (p < 0.001). CONCLUSION. A closed-loop communication system that enables establishing and executing a collaborative follow-up plan for incidental pulmonary nodules can be adopted and improves the quality of radiologists' follow-up recommendations.

Spontaneous pneumothorax in the elderly: a sign of a malignancy?

BACKGROUND

Spontaneous pneumothorax usually occurs as a result of rupture of a subpleural bleb or emphysematous bulla. Spontaneous pneumothorax, which is more common in younger age groups, might be the first sign of pulmonary malignancy, especially when it manifests in older patients.

METHODS

Data of all patients who were treated for spontaneous pneumothorax in our clinic between June 2013 and June 2017 were examined retrospectively. The demographic characteristics, diagnostic methods, pathologic subtypes, and treatment protocols applied in patients diagnosed with malignancy during the treatment period were investigated.

RESULTS

Out of 1187 patients, 9 (0.8%) had incidental pulmonary malignancies. Metastatic lung cancer was detected in 2 of 9 patients, while primary lung cancer was detected in the other 7. Six patients were operated on and the other 3 were referred for oncologic treatment for various reasons.

CONCLUSIONS

We suggest that cases of spontaneous pneumothorax in advanced age should be evaluated in a more detailed fashion, and further investigations should be carried out with suspicion of an underlying pulmonary malignancy.

MR Volumetry of Lung Nodules: A Pilot Study

Introduction: Computed tomography (CT) is currently the reference modality for the detection and follow-up of pulmonary nodules. While 2D measurements are commonly used in clinical practice to assess growth, increasingly 3D volume measurements are being recommended. The goal of this pilot study was to evaluate preliminarily the capabilities of 3D MRI using ultra-short echo time for lung nodule volumetry, as it would provide a radiation-free modality for this task. Material and Methods: Artificial nodules were manufactured out of Agar and measured using an ultra-short echo time MRI sequence. CT data were also acquired as a reference. Image segmentation was carried out using an algorithm based on signal intensity thresholding (SIT). For comparison purposes, we also performed manual slice by slice segmentation. Volumes obtained with MRI and CT were compared. Finally, the volumetry of a lung nodule was evaluated in one human subject in comparison with CT. Results: Using the SIT technique, minimal bias was observed between CT and MRI across the entire range of volumes (2%) with limits of agreement below 14%. Comparison of manually segmented MRI and CT resulted in a larger bias (8%) and wider limits of agreement (-23% to 40%). In vivo, nodule volume differed of <16% between modalities with the SIT technique. Conclusion: This pilot study showed very good concordance between CT and UTE-MRI to quantify lung nodule volumes, in both a phantom and human setting. Our results enhance the potential of MRI to quantify pulmonary nodule volume with similar performance to CT.

The clinical significance of indeterminate pulmonary nodules in melanoma patients at baseline and during follow-up chest CT

Objective

This study aims to determine an appropriate timeline to monitor indeterminate pulmonary nodules (IPN) in melanoma patients to confirm metastatic origin.

Materials and Methods

588 clinically non-metastatic melanoma patients underwent curative intent surgery during 3 years. Patients with baseline chest CT and at least one follow-up (FU) CT were retrospectively analyzed to assess for IPN. Patients with definitely benign nodules, metastases and non-melanoma malignancies were excluded. Change in volume from first to FU CT, initial diameter (D1) and volume (V1), distance from pleura, peripheral and perifissural location, density and clinical stage were evaluated. Nodules were volumetrically measured on CTs and were considered metastases if they increased in size between two CTs or if increase was accompanied by multiple new nodules or extrapulmonary metastases.

Results

148 patients were included. Two out of 243 baseline IPN detected in 70 patients, increased significantly in volume in 3 and 5 months and were proven metastases. During FU, 86% of 40 interval IPN detected in 28 patients, were proven metastases. Interval nodule (p < 0.0001, HR:243,CI:[57.32,1033.74]), 3-month volume change (OR:1.023,CI:[1.014,1.033]), V1 (OR:1.006,CI:[1.003,1.009]), D1 (OR:1.424,CI:[1.23,1.648]), distance from pleura (OR:1.03,CI:[1.003,1.059]), and combined stage IIC + III (OR:11.29,CI:[1.514,84.174]), were associated with increased risk for metastasis. 43%, 72% and 94% of patients with IPN were confirmed with metastases in the first FU CT at 3, 6 and 12 months respectively.

Conclusion

Baseline IPN are most likely benign, while interval IPN are high risk for metastasis. Absence of volume increase of IPN within 6 months excluded metastasis in most patients.

CT-guided Microcoil Pulmonary Nodule Localization prior to Video-assisted Thoracoscopic Surgery: Diagnostic Utility and Recurrence-Free Survival

Background CT-guided microcoil localization has been shown to reduce the need for thoracotomy or video-assisted thoracoscopic surgery (VATS) anatomic resection. However, only short-term follow-up after CT-guided microcoil localization and lung resection has been previously reported. Purpose To assess the diagnostic utility and recurrence-free survival over a minimum of 2 years following CT-guided microcoil localization and VATS. Materials and Methods Among 1950 VATS procedures performed in a single tertiary institution from October 2008 through April 2016, 124 consecutive patients with CT-guided microcoil localization were retrospectively evaluated. Patient demographics, nodule characteristics, and histopathologic findings were recorded. The primary end point was recurrence-free survival after 2 or more years of CT surveillance. Statistical analysis included Kaplan-Meier survival curves and Cox regression. Results In 124 patients (men, 35%; mean age, 65 years ± 12) with a nodule found at CT, microcoil localization and VATS resection were performed for a total of 126 nodules (mean size, 13 mm ± 6; mean distance to pleura, 20 mm ± 9). On presurgical CT evaluation, 42% (53 of 126) of nodules were solid, 33% (41 of 126) were ground glass, and 24% (30 of 126) were subsolid. VATS excisional biopsy altered cytopathologic diagnosis in 21% (five of 24) of patients with prior diagnostic premicrocoil CT-guided biopsy. At histopathologic examination, 17% (21 of 126) of the nodules were adenocarcinoma in situ, 17% (22 of 126) were minimally invasive adenocarcinoma, 30% (38 of 126) were invasive lung primary tumors, and 22% (28 of 126) were metastases. Among the 72 patients with malignancy at histopathologic examination and at least 2 years of CT surveillance, local recurrence occurred in 7% (five of 72), intrathoracic recurrence in 22% (16 of 72), and extrathoracic recurrence in 18% (13 of 72) after 2 or more years of CT surveillance. There was no recurrence for adenocarcinoma in situ, minimally invasive adenocarcinoma, or invasive lung tumors measuring less than 1 cm. After multivariable adjustment, nodule location at a distance greater than 10 mm from the pleura was an independent predictor of time to recurrence (hazard ratio, 2.9 [95% confidence interval: 1.1, 7.4]; P = .03). Conclusion CT-guided microcoil localization and video-assisted thoracoscopic surgical resection alter clinical management and were associated with excellent recurrence-free survival for superficial premalignant, minimally invasive, and small invasive lung tumors. © RSNA, 2019 Online supplemental material is available for this article.

Preoperative computed tomography-guided coil localization of lung nodules

Purpose: To evaluate the usefulness of preoperative computed tomography (CT)-guided coil localization in patients with lung nodules who underwent video-assisted thoracoscopic surgery (VATS) for lung resection.Material and methods: From October 2015 to January 2018, 76 patients with lung nodules underwent CT-guided coil localization and subsequent VATS in our center. The tail of the coil remained above the visceral pleura. Data regarding the technical success of coil localization and wedge resection were analyzed.Results: A total of 96 lung nodules in 76 patients were localized. The technical success rate of CT-guided coil localization was 97.9% (94/96). Among the 94 localized nodules, 88 coils were visible and six coils were palpated during VATS. Nine patients experienced pneumothorax and two patients experienced hemoptysis after coil localization. Two patients underwent VATS beyond 24 h after coil localization. The technical success rate of wedge resection of lung nodules was 97.9%. Seventeen patients with multiple target lung nodules underwent one-stage video-assisted resection of all target nodules after coil localization.Conclusion: Preoperative CT-guided coil localization is a safe and convenient method to facilitate a high success rate of diagnostic VATS wedge-resection of lung nodules. Coil localization can also facilitate one-stage VATS wedge-resection of multiple nodules.

Influences of scan-position on clinical ultra-high-resolution CT scanning: a preliminary study

The aim of this study is to access influences of scan-position on clinical ultra-high-resolution CT scanning. We proposed a breath-hold assisted ultra-high-resolution scanning technology (scan scheme G) and compared with scan scheme A (regular CT plain scan) and scheme B (1024 ultra-high-resolution scan with patients stay in supine position). A total of 30 patients with fGGO were included in this study. Three highly experienced chest imaging doctors were employed to score the image and to select regions of interest (ROIs) for CT value and signal-to-noise ratio (SNR) calculation. In comparison with scan A and B, this new scan scheme G shows more clear CT images and higher SNRs at overall lung field (the p-values of A versus G and B versus G are 0.041 and 0.065, respectively). These findings suggest that scan-G provides a better image quality and contributes significantly to clinical detection accuracy of fGGO.