Peripheral solitary pulmonary nodule: CT findings in patients with pulmonary emphysema

Is 18F-fluorodeoxyglucose PET recommended for small lung nodules? CT findings of 18F-fluorodeoxyglucose non-avid lung cancer

OBJECTIVES

To determine the image characteristics associated with low 18F-FDG (18F-fluorodeoxyglucose) avidity among 8-15 mm solid lung cancer.

METHODS

Patients satisfying the following criteria were included: underwent surgery between January 2014 and December 2019 for lung cancer, presented 8-15 mm nodule without measurable ground glass component on preoperative CT, and underwent 18F-FDG PET before resection. Image characteristics, including air bronchogram, concave shape, pleural attachment, and background emphysema, were evaluated by two board-certified radiologists. The Mann-Whitney U test was used to compare maximum standardized uptake (SUVmax) values from 18F-FDG PET images.

RESULTS

The analysis included 235 patients. The SUVmax values of lesions with air bronchogram and concave shape were significantly lower than the SUVmax values of lesions without these features (median: 1.55 vs 2.56 and 1.66 vs 2.45, both P < .001), whereas lesions arising from emphysematous lungs had significantly higher SUVmax values than lesions arising from non-emphysematous lungs (2.90 vs 1.69, P < .001). No significant differences were detected between lesions attached and not attached to pleura. The interobserver agreement was almost perfect for air bronchograms and background emphysema (κ = 0.882 and 0.927, respectively), and 89.7% of lesions with air bronchograms and arising from non-emphysematous lungs showed SUVmax values below 2.5.

CONCLUSIONS

Among 8-15 mm solid lung cancer, the presence of air bronchograms and concave shape and the absence of background emphysema were associated with low 18F-FDG accumulation.

ADVANCES IN KNOWLEDGE

18F-FDG PET can be misleading in differentiating certain type of small solid lung cancer.

Nomograms Using CT Morphological Features and Clinical Characteristics to Identify COPD in Patients with Lung Cancer: A Multicenter Study

Purpose

This study aimed to screen out computed tomography (CT) morphological features and clinical characteristics of patients with lung cancer to identify chronic obstructive pulmonary disease (COPD). Further, we aimed to develop and validate different diagnostic nomograms for predicting whether lung cancer is comorbid with COPD.

Patients and Methods

This retrospective study examined data from 498 patients with lung cancer (280 with COPD, 218 without COPD; 349 in training cohort, 149 in validation cohort) from two centers. Five clinical characteristics and 20 CT morphological features were evaluated. Differences in all variables were assessed between COPD and non-COPD groups. Models were developed using multivariable logistic regression to identify COPD, including clinical, imaging, and combined nomograms. Receiver operating characteristic curves were used to evaluate and compare the performance of nomograms.

Results

Age, sex, interface, bronchus cutoff sign, spine-like process, and spiculation sign were independent predictors of COPD in patients with lung cancer. In the training and validation cohorts, the clinical nomogram showed good performance to predict COPD in lung cancer patients (areas under the curves [AUCs] of 0.807 [95% CI, 0.761-0.854] and 0.753 [95% CI, 0.674-0.832]); while the imaging nomogram showed slightly better performance (AUCs of 0.814 [95% CI, 0.770-0.858] and 0.780 [95% CI, 0.705-0.856]). For the combined nomogram generated with clinical and imaging features, the performance was further improved (AUC=0.863 [95% CI, 0.824-0.903], 0.811 [95% CI, 0.742-0.880] in the training and validation cohort). At 60% risk threshold, there were more true negative predictions (48 vs 44) and higher accuracy (73.15% vs 71.14%) for the combined nomogram compared with the clinical nomogram in the validation cohort.

Conclusion

The combined nomogram developed with clinical and imaging features outperformed clinical and imaging nomograms; this provides a convenient method to detect COPD in patients with lung cancer using one-stop CT scanning.

Solitary Pulmonary Nodule Evaluation: Pearls and Pitfalls

Lung nodules are frequently encountered while interpreting chest CTs and are challenging to detect, characterize, and manage given they can represent both benign or malignant etiologies. An understanding of features associated with malignancy and causes of interpretive pitfalls is helpful to avoid misdiagnoses. This review addresses pertinent topics related to the etiologies for missed lung nodules on radiography and CT. Additionally, CT imaging technical pitfalls and challenges in addition to issues in the evaluation of nodule morphology, attenuation, and size will be discussed. Nodule management guidelines will be addressed as well as recent investigations that further our understanding of lung nodules.

Adenocarcinoma in situ and minimally invasive adenocarcinoma in lungs of smokers: image feature differences from those in lungs of non-smokers

PURPOSE

We aimed to examine the characteristics of imaging findings of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) in the lungs of smokers compared with those of non-smokers.

MATERIALS AND METHODS

We included seven cases of AIS and 20 cases of MIA in lungs of smokers (pack-years ≥ 20) and the same number of cases of AIS and MIA in lungs of non-smokers (pack-years = 0). We compared the diameter of the entire lesion and solid component measured on computed tomography (CT) images, pathological size and invasive component diameter measured from pathological specimens, and CT values of the entire lesion and ground-glass opacity (GGO) portions between the smoker and non-smoker groups.

RESULTS

The diameters of AIS and MIA on CT images and pathological specimens of the smoker group were significantly larger than those of the non-smoker group (p = 0.036 and 0.008, respectively), whereas there was no significant difference in the diameter of the solid component on CT images or invasive component of pathological specimens between the two groups. Additionally, mean CT values of the entire lesion and GGO component of the lesions in the smoker group were significantly lower than those in the non-smoker group (p = 0.036 and 0.040, respectively).

CONCLUSION

AIS and MIA in smoker's lung tended to have larger lesion diameter and lower internal CT values compared with lesions in non-smoker's lung. This study calls an attention on smoking status in CT-based diagnosis for early stage adenocarcinoma.

Predicting lung adenocarcinoma invasiveness by measurement of pure ground-glass nodule roundness by using multiplanar reformation: a retrospective analysis

AIM

To explore the value of roundness measurement based on thin-section axial, coronal, and sagittal section computed tomography (CT) images for predicting pure ground-glass nodule (pGGN) invasiveness.

MATERIALS AND METHODS

A total of 168 pGGNs in 155 patients (44 male, 111 females; mean age, 55.74 ± 10.57 years), and confirmed by surgery and histopathology, were analysed retrospectively and divided into pre-invasive (n=72) and invasive (n=96) groups. Photoshop (CS6) software was used to measure pGGN roundness based on conventional axial section, as well as coronal and sagittal sections generated by multiplanar reformation, from thin-section (1-mm-thick) CT lung images.

RESULTS

pGGN roundness values, measured in axial, coronal, and sagittal thin-section CT sections from the pre-invasive group were 0.8 ± 0.049, 0.816 ± 0.05, and 0.818 ± 0.043, respectively, while those in the invasive group were 0.745 ± 0.077, 0.684 ± 0.106, and 0.678 ± 0.106; differences between the two groups were significant (all p<0.001). Binary logistic regression analysis showed that roundness values based on coronal and sagittal sections (p<0.001) were better than those from axial sections (p>0.05) in predicting pGGN invasiveness, with odds ratio (OR) values of 14.858 and 23.315, respectively. ROC analysis showed that evaluation of roundness measured in sagittal sections was better at predicting pGGN invasiveness than when coronal sections were used (AUC 0.870 versus 0.832).

CONCLUSION

Roundness is useful for predicting pGGN invasiveness, with measurements from coronal and sagittal sections better than those from conventional axial sections, with sagittal section images having the best predictive value.

Tumor size in patients with severe pulmonary emphysema might be underestimated on preoperative CT

OBJECTIVES

To evaluate the effect of emphysema on tumor diameter measured on preoperative computed tomography (CT) images versus pathological specimens.

MATERIALS AND METHODS

We investigated patients who underwent primary lung cancer surgery: 55 patients (57 tumors) with severe emphysema and 57 patients (57 tumors) without emphysema. The tumor diameters measured in the postoperative pathological specimens were compared with those measured on the axial CT images and on multiplanar reconstruction (MPR) CT images by two independent radiologists; a subgroup analysis according to tumor size was also performed. A paired or unpaired t test was performed, depending on the tested subjects.

RESULTS

In the emphysema group, the mean axial CT diameter was significantly smaller than the mean pathological diameter (p = 0.025/0.001 for reader 1/2), whereas in the non-emphysema group, the mean axial CT diameter was not significantly different from the pathological one for both readers. The difference between CT axial diameter and pathological diameter (= CT diameter - pathological diameter) was significantly smaller (i.e., had a stronger tendency toward underestimation on radiological measurements) in the emphysema group compared with the non-emphysema group (p = 0.014/0.008 for reader 1/2), and the difference was significantly smaller in tumors sized > 30 mm than tumors sized ≤ 20 mm in both groups.

CONCLUSIONS

Tumor size is significantly smaller on preoperative CT in patients with severe emphysema compared to patients without emphysema, especially in the case of large tumors. MPR measurement using the widest of three dimensions should be used to select T-stage for patients with severe emphysema.

KEY POINTS

• The presence of emphysema affects the accuracy of tumor size measurements on CT. • Compared to patients without emphysema, the tumor size in severe emphysema patients tends to be measured smaller in preoperative CT than the pathological specimen. • This trend is more evident when large tumors are measured on axial CT images alone.

Use of relative CT values to evaluate the invasiveness of pulmonary subsolid nodules in patients with emphysema

Background

Lung cancer is a major cause of death, and adenocarcinoma is the most common histologic subtype. Precise diagnosis and treatment of invasive adenocarcinoma (IAC) can substantially improve the survival of patients. However, early-stage adenocarcinomas frequently appear as subsolid nodules (SSN) on computed tomography (CT), and the optimal cut-off CT value for differentiating the invasiveness of SSNs in emphysematous patients is unclear.

Methods

High-resolution CT targeted scans of 187 pulmonary SSNs in 175 patients with emphysema as confirmed by surgery and histology were retrospectively reviewed. The mean CT value, the relative CT (rCT) values of 1 (nodule CT value - lung CT value), and 2 (nodule CT value/lung CT value), and the size of the SSNs were measured and calculated. The differentiating performance of the CT values between pre-invasive and invasive tumors was evaluated using a receiver operating characteristic (ROC) curve.

Results

Significant differences were found in the rCT values of 1 and 2 among pure ground-glass nodules (GGNs) with different levels of invasiveness, in the rCT values of 1 and 2 for the ground-glass component (GGC) and the mean CT value of the solid component (SC) of part-solid nodules (PSNs) between minimally invasive adenocarcinoma (MIA) and IAC (all P<<0.05). The size was significantly different among pure GGNs with different invasiveness (P<0.05). The cut-off rCT values of 1, 2 and nodule size for differentiating between pre-invasive and invasive pure GGNs were 293.82 [sensitivity 58.0%, specificity 94.7%; area under the curve (AUC) 0.783], 0.68 (sensitivity 89.5%, specificity 58.0%, AUC 0.742) and 1.10 cm (sensitivity 74.0%, specificity 79.0%, AUC 0.796), respectively. The AUCs of combining rCT values 1 and 2 with the size of nodule were 0.795 (sensitivity 62.5%, specificity 89.5%) and 0.845 (sensitivity 71.6%, specificity 89.5%) respectively. There were no significant differences in the mean CT values between pure GGNs with different levels of invasiveness and between the GGC of PSNs of MIA and IAC.

Conclusions

In patients with emphysema, the rCT values are more useful than the mean CT values for differentiating between SSNs with different invasiveness and can be valuable for patient management.

Effect of closed vacuum aspiration technique on lung collapse time in thoracoscopic anatomical segmentectomy

To investigate the effect of lung expansion and collapse method combined with closed vacuum aspiration technique on lung collapse time, reduce the waiting time of surgery.Forty patients with pulmonary peripheral nodules under thoracoscopic anatomical segmentectomy were divided into 20 cases of natural collapse group and 20 cases of modified collapse group. The natural collapse group used the traditional natural collapse method, and the modified collapse group used a lung expansion and collapse method combined with closed vacuum aspiration technique to record the lung collapse time and compare them.Thoracoscopic anatomical segmentectomy was successfully performed in both groups. The lung collapse time in the natural collapse group and the modified collapse group was 17.08 ± 1.35, 8.90 ± 0.39, respectively, P < .05.The lung expansion and collapse method combined with closed vacuum aspiration technique can reduced the waiting time of lung collapse during thoracoscopic anatomical segmentectomy, and can processed the inter-segment boundary better, thereby reduced the waiting time of surgery.

Management of incidental lung nodules <8 mm in diameter

Due to the increase of incidentally detected pulmonary nodules and the information obtained from several screening programs, updated guidelines with new recommendations for the management of small pulmonary nodules have been proposed. These international guidelines coincide in proposing periodic follow-up for small nodules, less than 8 mm of diameter. Fleischner and British Thoracic Society guidelines are the most recent and popular guidelines for incidental pulmonary nodules management. They have specific recommendations according to nodule characteristics (density and size) and cancer risk of the patient. Both guidelines separate recommendations for solid and subsolid nodules. Predictive risk models have been developed to improve the nodule management. In certain cases follow up may not be the best option. We discuss the scenarios and options to achieve a histologic diagnosis of these tiny pulmonary nodules.

Vasculature surrounding a nodule: A novel lung cancer biomarker

PURPOSE

To investigate whether the vessels surrounding a nodule depicted on non-contrast, low-dose computed tomography (LDCT) can discriminate benign and malignant screen detected nodules.

MATERIALS AND METHODS

We collected a dataset consisting of LDCT scans acquired on 100 subjects from the Pittsburgh Lung Screening study (PLuSS). Fifty subjects were diagnosed with lung cancer and 50 subjects had suspicious nodules later proven benign. For the lung cancer cases, the location of the malignant nodule in the LDCT scans was known; while for the benign cases, the largest nodule in the LDCT scan was used in the analysis. A computer algorithm was developed to identify surrounding vessels and quantify the number and volume of vessels that were connected or near the nodule. A nonparametric receiver operating characteristic (ROC) analysis was performed based on a single nodule per subject to assess the discriminability of the surrounding vessels to provide a lung cancer diagnosis. Odds ratio (OR) were computed to determine the probability of a nodule being lung cancer based on the vessel features.

RESULTS

The areas under the ROC curves (AUCs) for vessel count and vessel volume were 0.722 (95% CI=0.616-0.811, p<0.01) and 0.676 (95% CI=0.565-0.772), respectively. The number of vessels attached to a nodule was significantly higher in the lung cancer group 9.7 (±9.6) compared to the non-lung cancer group 4.0 (±4.3) CONCLUSION: Our preliminary results showed that malignant nodules are often surrounded by more vessels compared to benign nodules, suggesting that the surrounding vessel characteristics could serve as lung cancer biomarker for indeterminate nodules detected during LDCT lung cancer screening using only the information collected during the initial visit.

Worse survival after curative resection in patients with pathological stage I non-small cell lung cancer adjoining pulmonary cavity formation

BACKGROUND

A few investigators have suggested an association between lung cancer and pulmonary cavity. However, this clinical association and its carcinogenic correlations are not well recognized. This study aimed to clarify the clinical features and to demonstrate the associated survival outcomes after curative surgery in patients with early non-small cell lung cancer (NSCLC) adjoining pulmonary cavity formation.

METHODS

We retrospectively reviewed 275 patients with pathological stage I NSCLC by re-evaluating their chest computed tomography images. Among them, we detected NSCLC adjoining pulmonary cavity formation in 12 (4.4%) patients.

RESULTS

The median follow-up period for all 275 patients was 43.2 (range, 6.0-86.0) months. Of these patients, 6 (50.0%) in group CF (patients with NSCLC adjoining pulmonary cavity formation) and 19 (7.2%) in group C (the control group, n=263) died during the study period. Besides, 6 (50.0%) and 32 (12.2%) patients in groups CF and C, respectively, exhibited recurrence of the primary lung cancer. The cumulative overall survival (OS) in groups CF and C at 5 years was 37.0% and 91.7%, respectively (P<0.0001); the recurrence-free survival (RFS) in these groups at 5 years was 55.0% and 86.7%, respectively (P=0.001). Univariate analysis showed that male sex, smoking habits, non-adenocarcinoma, and presence of pulmonary cavity formation were associated with poor OS (P=0.008, P=0.001, P<0.0001, and P<0.0001, respectively). Multivariate analysis demonstrated that smoking, non-adenocarcinoma, and pulmonary cavity formation were independent prognostic factors predicting poor survival (P=0.043, P=0.004 and P<0.0001, respectively).

CONCLUSIONS

Our results suggest that patients with early-stage NSCLC adjoining pulmonary cavity formation have an increased risk of poor OS and RFS after surgical resection. Further prospective, multi-institutional investigations and substantial clinical studies are warranted.

Radiologic Features of Small Pulmonary Nodules and Lung Cancer Risk in the National Lung Screening Trial: A Nested Case-Control Study

Purpose To extract radiologic features from small pulmonary nodules (SPNs) that did not meet the original criteria for a positive screening test and identify features associated with lung cancer risk by using data and images from the National Lung Screening Trial (NLST). Materials and Methods Radiologic features in SPNs in baseline low-dose computed tomography (CT) screening studies that did not meet NLST criteria to be considered a positive screening examination were extracted. SPNs were identified for 73 incident case patients who were given a diagnosis of lung cancer at either the first or second follow-up screening study and for 157 control subjects who had undergone three consecutive negative screening studies. Multivariable logistic regression was used to assess the association between radiologic features and lung cancer risk. All statistical tests were two sided. Results Nine features were significantly different between case patients and control subjects. Backward elimination followed by bootstrap resampling identified a reduced model of highly informative radiologic features with an area under the receiver operating characteristic curve of 0.932 (95% confidence interval [CI]: 0.88, 0.96), a specificity of 92.38% (95% CI: 52.22%, 84.91%), and a sensitivity of 76.55% (95% CI: 87.50%, 95.35%) that included total emphysema score (odds ratio [OR] = 1.71; 95% CI: 1.39, 2.01), attachment to vessel (OR = 2.41; 95% CI: 0.99, 5.81), nodule location (OR = 3.25; 95% CI: 1.09, 8.55), border definition (OR = 7.56; 95% CI: 1.89, 30.8), and concavity (OR = 2.58; 95% CI: 0.89, 5.64). Conclusion A set of clinically relevant radiologic features were identified that that can be easily scored in the clinical setting and may be of use to determine lung cancer risk among participants with SPNs. ^© RSNA, 2017 Online supplemental material is available for this article.

Missed cancers in lung cancer screening--more than meets the eye

In lung cancer, early detection and diagnosis is of paramount importance. In 2011 the National Lung Screening Trial (NLST) demonstrated the effectiveness of computed tomography (CT) screening for lung cancer in reducing mortality, and results from other ongoing trials are expected to be published in the near future. A topic that has not been widely researched to date, however, is the cause for screening failure and missed lung cancers. In this issue of European Radiology, Scholten et al. describe a number of causes for false-negative screens. Some of the implications for CT screening and nodule management raised by this report are discussed. Key Points • Many causes exist for missed lung cancers in CT screening trials • Endobronchial structures, the hila and mediastinum are blind spots on screening CTs • The management of atypical nodular opacities on thoracic CT may be challenging.

Imaging incidental pulmonary nodules

The incidental nodule is an increasingly common clinical conundrum. This article outlines the characteristics that allow differentiation of benign and malignant pathologies and discusses strategies for their follow up and management.

Computer-aided diagnosis systems for lung cancer: challenges and methodologies

This paper overviews one of the most important, interesting, and challenging problems in oncology, the problem of lung cancer diagnosis. Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can increase the patient's chance of survival. For this reason, CAD systems for lung cancer have been investigated in a huge number of research studies. A typical CAD system for lung cancer diagnosis is composed of four main processing steps: segmentation of the lung fields, detection of nodules inside the lung fields, segmentation of the detected nodules, and diagnosis of the nodules as benign or malignant. This paper overviews the current state-of-the-art techniques that have been developed to implement each of these CAD processing steps. For each technique, various aspects of technical issues, implemented methodologies, training and testing databases, and validation methods, as well as achieved performances, are described. In addition, the paper addresses several challenges that researchers face in each implementation step and outlines the strengths and drawbacks of the existing approaches for lung cancer CAD systems.

Automatic segmentation of lung nodules with growing neural gas and support vector machine

Lung cancer is distinguished by presenting one of the highest incidences and one of the highest rates of mortality among all other types of cancer. Unfortunately, this disease is often diagnosed late, affecting the treatment outcome. In order to help specialists in the search and identification of lung nodules in tomographic images, many research centers have developed computer-aided detection systems (CAD systems) to automate procedures. This work seeks to develop a methodology for automatic detection of lung nodules. The proposed method consists of the acquisition of computerized tomography images of the lung, the reduction of the volume of interest through techniques for the extraction of the thorax, extraction of the lung, and reconstruction of the original shape of the parenchyma. After that, growing neural gas (GNG) is applied to constrain even more the structures that are denser than the pulmonary parenchyma (nodules, blood vessels, bronchi, etc.). The next stage is the separation of the structures resembling lung nodules from other structures, such as vessels and bronchi. Finally, the structures are classified as either nodule or non-nodule, through shape and texture measurements together with support vector machine. The methodology ensures that nodules of reasonable size be found with 86% sensitivity and 91% specificity. This results in a mean accuracy of 91% for 10 experiments of training and testing in a sample of 48 nodules occurring in 29 exams. The rate of false positives per exam was of 0.138, for the 29 exams analyzed.

Characterization of solitary pulmonary nodules: Use of washout characteristics at contrast-enhanced computed tomography

The purpose of this study was to determine whether computed tomographic scans and attenuation measurements on contrast material-enhanced and non-enhanced computed tomographic scans could be used to characterize solitary pulmonary nodules and, in particular, to characterize these lesions using washout characteristics on contrast-enhanced computed tomography. A total of 63 patients (38 males, 25 females; age range, 21-80 years; mean age, 58±13.2 years) with pulmonary nodules revealed on contrast-enhanced computed tomography underwent 20-min delayed enhanced scans. The mean diameter of the pulmonary nodules was 1.8±0.6 cm (range, 0.8-2.9). Region-of-interest measurements were obtained at non-enhanced, dynamic enhanced and delayed enhanced computed tomography and were used to calculate a relative percentage washout as follows: 1 - (Hounsfield unit measurement on delayed image/Hounsfield unit measurement on dynamic image) × 100%. There was a mean relative washout of 33% on the delayed computed tomographic scans (range, 12-46) in benign solitary pulmonary nodules; and a mean relative washout of 7% (range, -36-51) in malignant solitary pulmonary nodules (Mann-Whitney U test, p<0.001). Results of the receiver operating curve analysis revealed that a threshold relative washout of 14.5% had 74.3% sensitivity and 92.9% specificity for identifying malignant nodules. Calculation of the relative percentage washout on dynamic and delayed enhanced computed tomographic scans may lead to a highly specific test for solitary pulmonary nodule characterization and reduce the need for, and possibly obviate, follow-up imaging or biopsy.

Correlations between computed tomography findings and clinical manifestations of Streptococcus pneumoniae pneumonia

PURPOSE

The aim of this study was to characterize the imaging features and compare computed tomography (CT) findings with clinical features of patients with Streptococcus pneumoniae pneumonia.

MATERIALS AND METHODS

We retrospectively reviewed 75 patients (44 men, 31 women; mean age 67 years) diagnosed with S. pneumoniae pneumonia who underwent chest CT scanning at our institution between January 2007 and August 2008. Diagnoses were based on detection of the S. pneumoniae antigen in urine.

RESULTS

Chest CT scans revealed abnormalities in all patients. The predominant opacity patterns were an airspace pneumonia pattern (48%) and a bronchopneumonia pattern (48%), followed by an interstitial pneumonia pattern (4%). Consolidation was observed most frequently (84%) followed by ground glass opacity (82.7%), bronchial wall thickening (61.3%), and centrilobular nodules (49.3%). Airway dilatation (21.6%), pleural effusion (33.3%), lymphadenopathy (34.8%), and pulmonary emphysema (21.3%) were also observed. Pulmonary emphysema was significantly less frequent in patients with the bronchopneumonia pattern than in those without (p = 0.007). The clinical features and CT findings did not differ significantly.

CONCLUSION

CT image analysis showed that patients with S. pneumoniae pneumonia exhibited the bronchopneumonia and airspace pneumonia patterns with equal frequency. Bronchopneumonia pattern was less common in patients with preexisting emphysema.

Effects of formoterol-budesonide on airway remodeling in patients with moderate asthma

AIM

To evaluate the effect of inhaled formoterol-budesonide on airway remodeling in adult patients with moderate asthma.

METHODS

Thirty asthmatic patients and thirty control subjects were enrolled. Asthmatic subjects used inhaled Symbicort 4.5/160 μg twice daily for one year. The effect of formoterol-budesonide on airway remodeling was assessed with comparing high-resolution computer tomography (HRCT) images of asthmatic patients and controls, as well as expression levels of cytokines and growth factors, inflammatory cell count in induced sputum, and airway hyper-responsiveness.

RESULTS

The differences in age and gender between the two groups were not significant. However, differences in FVC %pred, FEV(1) %pred, and PC(20) between the two groups were significant. After treatment with formoterol-budesonide, the asthma patients' symptoms were relieved, and their lung function was improved. The WT and WA% of HRCT images in patients with asthma was increased, whereas treatment with formoterol-budesonide caused these values to decrease. The expression of MMP-9, TIMP-1, and TGF-β(1) in induced sputum samples increased in patients with asthma and decreased dramatically after treatment with formoterol-budesonide. The WT and WA% are correlated with the expression levels of cytokines and growth factors, inflammatory cell count in induced sputum, and airway hyper-responsiveness, while these same values are correlated negatively with FEV(1)/FVC and FEV(1)%.

CONCLUSION

Formoterol-budesonide might interfere in chronic inflammation and airway remodeling in asthmatic patients. HRCT can be used to effectively evaluate airway remodeling in asthmatic patients.

Development and validation of the random walk algorithm: application to the classification of diffuse heterogeneity in brain SPECT perfusion images

Heterogeneity analysis has been studied for radiological imaging, but few methods have been developed for functional images. Diffuse heterogeneous perfusion frequently appears in brain single photon emission computed tomography (SPECT) images, but objective quantification is lacking. An automatic method, based on random walk (RW) theory, has been developed to quantify perfusion heterogeneity. We assess the robustness of our algorithm in differentiating levels of diffuse heterogeneity even when focal defects are present.

METHODS

Heterogeneity is quantified by counting R (percentage), the mean rate of visited pixels in a fixed number of steps of the stochastic RW process. The algorithm has been tested on the numerical anthropomorphic Zubal head phantom. Seven diffuse cortical heterogeneity levels were simulated with an adjustable Gaussian function and 6 temporoparietal focal defects simulating Alzheimer Disease, leading to 42 phantoms. Data were projected and smoothed (full width at half maximum, 5.5 mm), and Poisson noise was added to the 64 projections. The SPECT data were reconstructed using filtered backprojection (Hamming filter, 0.5 c/p). R values for different levels of perfusion defect and diffuse heterogeneity were evaluated on 3 parameters: the number of slices studied (20 vs 40), the use of Talairach normalization versus original space, and the use of a cortical mask within the Talairach space. For each parameter, regression lines for heterogeneity and temporoparietal defect quantification were analyzed by covariance statistics. R values were also evaluated on SPECT images performed on 25 subjects with suspected focal dementia and on 15 normal controls. Scans were blindly ranked by 2 experienced nuclear physicians according to the degree of diffuse heterogeneity.

RESULTS

Variability of R was smaller than 0.17% for repeated measurements. R was more particularly influenced by diffuse heterogeneity compared with focal perfusion defect. The Talairach normalization had a significant influence on the heterogeneity quantification. The number of slices visited by the RW and the cortical masking have a weak influence on the heterogeneity quantification but only for very low heterogeneity levels. The Spearman coefficient between physicians' consensus and RW automatic ranking is 0.85, in the same order of magnitude as the Spearman coefficient between the rankings of the 2 senior physicians (0.86).

CONCLUSIONS

Random walk is an original and objective method and is able to quantify heterogeneous brain perfusion, even in presence of cortical defects. This method is repeatable, robust, and mainly influenced by spatial normalization.

Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT

We investigated the possibility of using computer analysis of high-resolution CT images to radiologically classify the shape of pulmonary nodules. From a total of 107 HRCT images of solid, solitary pulmonary nodules with prior differentiation as benign (n=55) or malignant (n=52), we extracted the desired pulmonary nodules and calculated two quantitative parameters for characterizing nodules: circularity and second central moment. Using discriminant analysis for two thresholds in differentiating malignant from benign states resulted in a sensitivity of 76.9%, a specificity of 80%, a positive predictive value of 78.4%, and a negative predictive value of 78.6%.

Role of baseline nodule density and changes in density and nodule features in the discrimination between benign and malignant solid indeterminate pulmonary nodules

PURPOSE

To retrospectively evaluate whether baseline nodule density or changes in density or nodule features could be used to discriminate between benign and malignant solid indeterminate nodules.

MATERIALS AND METHODS

Solid indeterminate nodules between 50 and 500 mm(3) (4.6-9.8mm) were assessed at 3 and 12 months after baseline lung cancer screening (NELSON study). Nodules were classified based on morphology (spherical or non-spherical), shape (round, polygonal or irregular) and margin (smooth, lobulated, spiculated or irregular). The mean CT density of the nodule was automatically generated in Hounsfield units (HU) by the Lungcare software.

RESULTS

From April 2004 to July 2006, 7310 participants underwent baseline screening. In 312 participants 372 solid purely intra-parenchymal nodules were found. Of them, 16 (4%) were malignant. Benign nodules were 82.8mm(3) (5.4mm) and malignant nodules 274.5mm(3) (8.1mm) (p=0.000). Baseline CT density for benign nodules was 42.7 HU and for malignant nodules -2.2 HU (p=ns). The median change in density for benign nodules was -0.1 HU and for malignant nodules 12.8 HU (p<0.05). Compared to benign nodules, malignant nodules were more often non-spherical, irregular, lobulated or spiculated at baseline, 3-month and 1-year follow-up (p<0.0001). In the majority of the benign and malignant nodules there was no change in morphology, shape and margin during 1 year of follow-up (p=ns).

CONCLUSION

Baseline nodule density and changes in nodule features cannot be used to discriminate between benign and malignant solid indeterminate pulmonary nodules, but an increase in density is suggestive for malignancy and requires a shorter follow-up or a biopsy.

Limited value of shape, margin and CT density in the discrimination between benign and malignant screen detected solid pulmonary nodules of the NELSON trial

PURPOSE

To evaluate prospectively the value of size, shape, margin and density in discriminating between benign and malignant CT screen detected solid non-calcified pulmonary nodules.

MATERIAL AND METHODS

This study was institutional review board approved. For this study 405 participants of the NELSON lung cancer screening trial with 469 indeterminate or potentially malignant solid pulmonary nodules (>50mm3) were selected. The nodules were classified based on size, shape (round, polygonal, irregular) and margin (smooth, lobulated, spiculated). Mean nodule density and nodule volume were automatically generated by software. Analyses were performed by univariate and multivariate logistic regression. Results were presented as likelihood ratios (LR) with 95% confidence intervals (CI). Receiver operating characteristic analysis was performed for mean density as predictor for lung cancer.

RESULTS

Of the 469 nodules, 387 (83%) were between 50 and 500mm3, 82 (17%) >500mm3, 59 (13%) malignant, 410 (87%) benign. The median size of the nodules was 103mm3 (range 50-5486mm3). In multivariate analysis lobulated nodules had LR of 11 compared to smooth; spiculated nodules a LR of 7 compared to smooth; irregular nodules a LR of 6 compared to round and polygonal; volume a LR of 3. The mean nodule CT density did not predict the presence of lung cancer (AUC 0.37, 95% CI 0.32-0.43).

CONCLUSION

In solid non-calcified nodules larger than 50mm3, size and to a lesser extent a lobulated or spiculated margin and irregular shape increased the likelihood that a nodule was malignant. Nodule density had no discriminative power.

The effect of lung volume on nodule size on CT

RATIONALE AND OBJECTIVES

We sought to determine how measures of nodule diameter and volume on computed tomography (CT) vary with changes in inspiratory level.

MATERIALS AND METHODS

CT scans were performed with inspiration suspended at total lung capacity (TLC) and then at residual volume (RV) in 41 subjects, in whom 75 indeterminate lung nodules were detected. A fully automated contouring program was used to segment the lungs; followed by segmentation of all nodules and the corresponding lobe using semiautomated contouring in both TLC and RV scans. The percent changes in lung and lobar volumes between TLC and RV were correlated with percent changes in nodule diameters and volumes.

RESULTS

Both nodule diameter and volume varied nonuniformly from TLC to RV-some nodules decreased in size, while others increased. There was a 16.8% mean change in absolute volume across all nodules. Stratified by size, the mean value of the absolute percent volume changes for nodules > or =5 mm and <5 mm were not significantly different (P = .26). Stratified by maximum attenuation, the mean value of the absolute percent volume changes between the TLC and RV series for noncalcified (17.7%, SD = 13.1) and completely calcified nodules (8.6% SD = 5.7) were significantly different (P < .05).

CONCLUSION

Significant differences in nodule size were measured between TLC and RV scans. This has important implications for standardizing acquisition protocols in any setting where size and, more important, size change are being used for purposes of lung cancer staging, nodule characterization, or treatment response assessment.

Imaging in the diagnosis and treatment of non-small cell lung cancer

The available tools for diagnosing and staging lung cancer patients can be broadly categorized into non-invasive, minimally invasive and invasive (surgical) modalities. Non-invasive modalities include CT and PET. Minimally invasive modalities are endoscopic approaches, including endoscopic ultrasound, endobronchial ultrasound and transbronchial fine needle aspiration without ultrasound guidance. This review focuses on the non-invasive and minimally invasive techniques involving imaging. Application of Bayesian principles indicates that tests with a high sensitivity and specificity for detection of both systemic metastases and mediastinal nodal involvement are required for treatment selection and planning in patients with non-small cell lung cancer who would be considered for treatment with curative intent. Combined PET/CT using the glucose analogue fluorine-18 fluorodeoxyglucose currently provides the best diagnostic performance for this purpose and should now be considered the standard of care for staging non-small cell lung cancer. Endoscopic ultrasound and endobronchial ultrasound have important complementary roles to allow further evaluation of equivocal nodal abnormalities on PET or CT and to allow pathological samples to be obtained. Diagnostic CT has an important role in defining tumour relations for patients deemed suitable for surgical resection and as the initial investigation for patients with potential symptoms of lung cancer or proven lung cancer that would not be considered for curative treatment on medical grounds.

Management of an incidentally discovered pulmonary nodule

The incidental finding of a pulmonary nodule on computed tomography (CT) is becoming an increasingly frequent event. The discovery of such a nodule should evoke the possibility of a small bronchogenic carcinoma, for which excision is indicated without delay. However, invasive diagnostic procedures should be avoided in the case of a benign lesion. The objectives of this review article are: (1) to analyze the CT criteria defining benign nodules, nodules of high suspicion of malignancy and indeterminate nodules, (2) to analyze the diagnostic performances and limitations of complementary investigations requested to characterize indeterminate lung nodules, (3) to review the criteria permitting to assess the probability of malignancy of indeterminate nodules and (4) to report on the new guidelines provided by the Fleischner Society for the management of small indeterminate pulmonary nodules, according to their prior probability of malignancy.