Benign Mediastinal Nodes Research Articles

Optimal selection of b-values for differential diagnosis of mediastinal lymph nodes using diffusion-weighted imaging

This study proposed to investigate the optimal selection of b-values in diffusion-weighted imaging for distinguishing malignant from benign mediastinal lymph nodes. Diffusion-weighted imaging with six b-values was performed on 35 patients at 1.5 T. Image quality score, signal-to-noise ratio, and relative contrast ratio of lymph node to chest muscle were compared between the diffusion-weighted images with a b-value up to 800 and 1000 s/mm2. Using a lower and an upper b-value in the range of 0–1000 s/mm2, eight apparent diffusion coefficient maps were obtained from a mono-exponential model. Receiver operating characteristic analysis was employed to evaluate the performance of the apparent diffusion coefficients for distinguishing malignant from benign mediastinal lymph nodes by using the area under the curve as a criterion.The mean image quality score and the relative contrast ratio showed no difference between b-values of 800 and 1000 s/mm2. In the receiver operating characteristic analysis, the areas under the curve of apparent diffusion coefficient with b-value pairs of (0, 800), (0, 1000), and (50, 800) s/mm2 were significantly higher than those from the other b-value pairs. No significant difference was observed among the three b-value pairs. Apparent diffusion coefficient obtained from b-value pairs of (0, 800), (0, 1000), and (50, 800) s/mm2 showed superior diagnostic performance compared to the other b-value combinations. Based on several practical considerations, the b-value pair of (50, 800) s/mm2 is recommended for differential diagnosis of mediastinal lymph nodes.

Castlemans Disease – Presenting with Recurrent Pleuropericardial Effusions- Mimicking Tuberculosis

Castleman disease (CD) is an uncommon heterogeneous group of lymphoproliferative disorders which can affect the lymph nodes of the neck, chest, abdomen and pelvis. It was first described by Castleman, in 1954, known as benign mediastinal lymph node hyperplasia, which was histologically similar to thymoma of unknown cause. [1] It is divided into unicentric (localized ) Castleman disease (UCD) and multicentric ( generalized) Castleman disease (MCD) based on the number of lymph nodes involved. Castleman disease has varied presentations. Clinically it can present as localized masses, or localized lymph node enlargement. Symptoms can result from compression effects of the enlarged lymph nodes and in asymptomatic patients it can be an incidental finding on radiological imaging. It can also present as diffuse lymphadenopathy with severe systemic symptoms . Rarely it presents with pleuro-pericardial effusions . We present a case of a; young gentleman presenting with anorexia, weight loss and night sweats . He had large exudative pleural effusion with pericardial effusion leading to constrictive pericarditis .He was started on ATT empirically, which was later stopped due to poor response . Extensive radiological work revealed multi loculated pleural effusion and multiple lymph nodes in the axillary and cervical area . Excisional Biopsy of the lymph nodes revealed Castleman disease .

Can artificial intelligence distinguish between malignant and benign mediastinal lymph nodes using sonographic features on EBUS images?

Aims This study aimed to develop a new intelligent diagnostic approach using an artificial neural network (ANN). Moreover, we investigated whether the learning-method-guided quantitative analysis approach adequately described mediastinal lymphadenopathies on endobronchial ultrasound (EBUS) images. Methods In total, 345 lymph nodes (LNs) from 345 EBUS images were used as source input datasets for the application group. The group consisted of 300 and 45 textural patterns as input and output variables, respectively. The input and output datasets were processed using MATLAB. All these datasets were utilized for the training and testing of the ANN. Results The best diagnostic accuracy was 82% of that obtained from the textural patterns of the LNs pattern (89% sensitivity, 72% specificity, and 78.2% area under the curve). The negative predictive values were 81% compared to the corresponding positive predictive values of 83%. Due to the application group’s pattern-based evaluation, the LN pattern was statistically significant (p = .002). Conclusions The proposed intelligent approach could be useful in making diagnoses. Further development is required to improve the diagnostic accuracy of the visual interpretation.

Endobronchial Ultrasound Elastography for Differentiating Benign and Malignant Lymph Nodes

Background: Endobronchial ultrasound elastography that provides information on tissue stiffness may help distinguish malignant from benign mediastinal and hilar lymph nodes. Objectives: In this prospective trial, we assessed the diagnostic value of elastographic images and the interobserver agreement in its evaluation. Method: Elastographic images from 77 lymph nodes in 65 patients were reviewed by 3 pneumologists. The elastographic image was classified based on the predominant colour: predominantly green, intermediary, and predominantly blue. With 2 or 3 interobserver matches, the corresponding elastographic image was correlated with the pathological result obtained from endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and/or other invasive procedures. Results: All 3 reviewers had agreement in classifying elastographic images in 45% (35/77). Overall, the interobserver agreement among the 3 readers for classifying elastographic pattern was found to be moderate (Fleiss Kappa index = 0.519; 95% CI = [0.427; 0.611]). On cytological/histological evaluation, 55 lymph nodes were malignant and 22 were benign. In classifying “green” as benign and “blue” as malignant, the sensitivity and specificity were 71% (95% CI = [54%; 85%]) and 67% (95%-CI = [35%; 90%]), respectively. Conclusions: Elastography will not replace invasive EBUS-TBNA due to a moderate interobserver agreement and insufficient sensitivity and specificity. However, elastography will, maybe, present an additional feature to identify malignant lymph nodes in the context of clinical, radiological, and cytological results.

Comparison of transbronchial needle aspiration with and without ultrasound guidance for diagnosing benign lymph node adenopathy

BackgroundTransbronchial needle aspiration (TBNA) is a minimally invasive procedure performed to diagnose lymph node (LN) adenopathy. TBNA with and without endobronchial ultrasound (EBUS) guidance has a high diagnostic yield for malignant LN enlargement, but the value for diagnosing benign LN enlargement has been less thoroughly investigated.MethodsWe retrospectively evaluated 3540 patients with mediastinal LN enlargement who received TBNA. One hundred sixty-six patients with benign mediastinal lymphadenopathy were included and 293 LNs were biopsied. A positive result was defined as a specific histological abnormality. Conventional TBNA (cTBNA) and EBUS-TBNA, as well as cTBNA and transbronchial forceps biopsy (TBFB), were compared. The subgroup analysis was stratified by disease type and LN size.ResultsA diagnosis was made in 76.84% of the EBUS-TBNA and 61.31% of the cTBNA (P < 0.05). EBUS-TBNA was superior to cTBNA for both granulomatous (65.18% vs. 45.45%, P < 0.05) and non-granulomatous disease (96.92% vs. 84.06%, P < 0.05). In contrast, the diagnostic yield of EBUS-TBNA was higher than that of cTBNA for LNs < 20 mm (79.44% vs. 64.29%, P < 0.05), but for LNs > 20 mm the difference was marginal. These findings were confirmed in a group of independent patients who received cTBNA plus EBUS-TBNA. The diagnostic yield did not differ between cTBNA and TBFB, but significantly increased to 76.67% when both modalities were employed.ConclusionsEBUS-TBNA is the preferred minimally invasive diagnostic method for benign mediastinal LN disease. Combined cTBNA and TBFB is a safe and feasible alternative when EBUS is unavailable.

Performance of Endobronchial Ultrasound Elastography in the Differentiation of Malignant and Benign Mediastinal Lymph Nodes: Results in Real-life Practice.

Little data exists regarding the performance of elastography in EBUS-TBNA. The aim of the study was to evaluate the elastography score proposed and previously published by Izumo, in particular its capacity to perfectly identify benign lymph node, and to discriminate malignant ones. This study included patients undergoing EBUS-TBNA for mediastinal lymph nodes (LN). Before LN needle aspiration, an elastography was performed which allowed a color elastogram to be superimposed on the ultrasound image. Three blinded assessors classified these elastograms into 3 types using the score published by Izumo: type 1 (predominantly not blue), type 2 (partially blue, partially not blue), or type 3 (predominantly blue). These types were then compared with pathology results. A total of 217 LN (114 patients) were analyzed: histologic findings identified 97 benign LN (44.7% of the lymph nodes) and 120 malignant LN (55.3%). There were 44 elastographies (20.2%) that were classified as type 1, 90 elastographies (41.5%) classified as type 2, and 83 elastographies (38.3%) classified as type 3. Considering type 1 as benign and type 3 as malignant, sensitivity, specificity, positive predictive value, and negative predictive value were respectively 87.0%, 68.0% , 80.0% , and 77.0%. Ten (23%) of the 44 lymph nodes with a type 1 elastogram were malignant. Elastography does not preclude performing TBNA of the lymph nodes. It does not preclude EBUS-TBNA when a type 1 elastogram pattern is found. All lymph nodes visualized should be sampled by EBUS-TBNA, regardless of elastography pattern.

Quantitative computed tomography texture analysis: can it improve diagnostic accuracy to differentiate malignant lymph nodes?

Background and objectiveMediastinal lymph node (LN) staging in individuals with non-small-cell lung cancer plays an important role in staging and treatment planning. This study aimed to assess the accuracy of computed tomography (CT) texture analysis (CTTA) in differentiating benign and malignant mediastinal LNs.MethodsPathologically confirmed malignant and benign mediastinal LN samples, obtained using endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), were retrospectively reviewed, in addition to chest CT and 18-fluorodeoxyglucose (FDG) uptake positron emission tomography (PET) data. For each LN, CTTA was performed using “AVIEW” software (Coreline Soft, Republic of Korea) by drawing a region of interest.ResultsA total of 132 LNs from 80 patients were included and classified into two groups according to pathology results: malignant (n = 61) and benign (n = 71). In EBUS, size > 1 cm, round shape, heterogeneous echogenicity, and presence of coagulation necrosis sign were more prevalent in malignant than in benign LNs; length was the only feature that distinguished the two groups. Among CTTA features, compactness and normalized standard deviation (SD) showed differences between the two groups. The ability to distinguish malignant LNs was higher using high standard uptake value (SUV) on FDG PET/CT (SUVmax ≥ 5) and normalized SD on CTTA (area under the receiver operating characteristic curve 0.739 versus 0.742, respectively); however, normalized SD demonstrated very low sensitivity despite high specificity.ConclusionsCTTA may be helpful in distinguishing between benign and malignant LNs; however, the diagnostic value was not high. Therefore, integrated evaluation with other imaging modalities is needed.

Mediastinal lymph node malignancy detection in computed tomography images using fully convolutional network

Differential diagnosis of malignant and benign mediastinal lymph nodes (LNs) through invasive pathological tests is a complex and painful procedure because of sophisticated anatomical locations of LNs in the chest. The image based automatic machine learning techniques have been attempted in the past for malignancy detection. But these conventional methods suffer from complex selection of hand-crafted features and trade-off between performance parameters due to them. Today deep learning approaches are outperforming conventional machine learning techniques and able to overcome these issues. However, the existing convolutional neural network (CNN) based models also are prone to overfitting because of fully connected (FC) layers. Therefore, in this paper authors have proposed a fully convolutional network (FCN) based deep learning model for lymph nodes malignancy detection in computed tomography (CT) images. Moreover, the proposed FCN has been customized with batch normalization and advanced activation function Leaky ReLU to accelerate the training and to overcome the problem of dying ReLU, respectively. The performance of the proposed FCN has been also tuned to its best for smaller data size using data augmentation methods. The generalization of the proposed model is tested using the network parameter variation. To understand the reliability of the proposed model, it has also been compared with state-of-art related deep learning networks. The proposed FCN model has achieved an average accuracy, sensitivity, specificity, and area under curve as 90.28%, 90.63%, 89.95%, and 0.90, respectively. Our results also confirms the successful usabilility of augmentation methods for working on smaller datasets and deep learning approaches.

Conventional MRI to detect the differences between mass-like tuberculosis and lung cancer.

The aim of this study was to investigate differences in the imaging features of mass-like tuberculosis and lung cancer on conventional MR sequences to improve the diagnostic ability for pulmonary masses. Thirty patients with suspicious pulmonary lesions were enrolled and diagnosed with tuberculosis by pathology or comprehensive clinical diagnoses. Twenty-six cases of lung cancer were retrospectively analyzed. Transverse fat-suppressed T2-weighted (T2W) imaging and T1-weighted (T1W) imaging were obtained at 1.5 Tesla. The imaging characteristics of lesions on the T2W and T1W images were compared between the two groups. The imaging features of enlarged mediastinal lymph nodes on T2W images were studied and compared. On T2W images, there was a higher percentage of lesions containing hypointensity in the tuberculosis group (GTB) than in the lung cancer group (GLC) (P=0.004).The incidence of lesions demonstrating heterogeneous intensity was significantly greater in the GTB than in the GLC (70.0% vs. 7.7%, P=0.001). Approximately 92.3% of the lung cancer cases showed hyperintensity, a proportion substantially greater than that in the GTB (6.7%). On T1W images, more cases showed hyperintensity in the GTB than in the GLC (43.3% vs. 7.7%, P=0.003). The signal intensity ratios (SIRs) of the lesion to rhomboid muscle on T2W and T1W images were significantly different between the two groups. The mean intrasubject standard deviation (SD) of lesions in the GTB was markedly greater than that in the GLC on both T2W and T1W images. Benign mediastinal lymph nodes in the GTB showed a variety of signals on T2W images, whereas 80% of metastatic mediastinal lymph nodes displayed slight homogeneous hyperintensity, and this difference between the two groups was statistically significant. Conventional MR sequences can reveal the essential differences between mass-like tuberculosis and lung cancer and may be helpful for discriminating pulmonary masses.

Differentiating malignant and benign lymph nodes using endobronchial ultrasound elastography.

Endobronchial ultrasound (EBUS) elastography is a new technique that provides information on tissue compressibility during endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA). The purposes of this study were to evaluate the utility of EBUS elastography in differentiating malignant and benign mediastinal lymph nodes (LNs) and to explore the factors that influence its accuracy. A retrospective chart review of patients who underwent EBUS-TBNA from October 2016 to July 2017 was performed. EBUS with conventional B-mode features and elastographic patterns were compared with the final pathology results or clinical follow-up. We used the following EBUS elastographic patterns for classification: type 1, predominantly non-blue (green, yellow and red); type 2, part blue, part non-blue; type 3, predominantly blue. The potential impacts of the characteristics of LNs, the underlying lung diseases and obtaining fibrotic components from EBUS-TBNA specimens were evaluated relative to the accuracy of EBUS elastography. A total of 206 LNs from 94 patients were retrospectively evaluated. In classifying type 1 as 'benign' and type 3 as 'malignant,' the sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy rate were 90.6, 82.6, 71.6, 94.7 and 85.2%, respectively. The EBUS elastographic patterns had higher diagnostic yields and negative predictive values than conventional B-mode features. Logistic regression analysis revealed that central necrosis was a factor that influenced the accuracy of elastography in malignant LNs. The fibrotic component within benign LNs could cause an incorrect elastographic pattern. EBUS elastography is a valuable tool in discriminating benign and malignant mediastinal LNs.

Benign and malignant enlarged chest nodes staging by diffusion-weighted MRI: an alternative to mediastinoscopy?

To evaluate the accuracy of diffusion-weighted MRI with background suppression (DWIBS) in differentiating between malignant and benign mediastinal lymph-nodes. Consecutive patients with enlarged mediastinal lymph-nodes underwent MRI DWIBS within 10 days prior to mediastinoscopy. Relative contrast ratios (RCRs) were computed on b800 and apparent diffusion coefficient (ADC) maps by dividing the node signal with the chest muscle signal, using manually drawn regions of interest (ROIs) by radiologists, blinded to pathology. Unpaired Student's t-tests were used to compare RCR-b800 and ADC between malignant and benign nodes. Receiver operating characteristic curves analyses were also performed. Six patients were excluded for poor image quality. Analysis was performed for 54 patients. Mean ADC values were significantly higher for benign (1740 ± 401 × 10-6 mm2 s-1) compared with malignant nodes (1266 ± 403 × 10-6 mm2 s-1, p = 0.0001). Mean RCR-b800 values were significantly lower for benign (2.64 ± 1.07) compared with malignant nodes (6.44 ± 3.47, p < 0.0001). Receiver operating characteristic analysis for RCR-b800 (cut-off of 3.6), showed a sensitivity of 90.9%, a specificity 83% and an accuracy 85% for differentiating benign from malignant nodes. For ADC (cut-off of 1285), the sensitivity was 68.2%, the specificity 84.6% and the accuracy 80.4%. DWIBS can accurately differentiate malignant from benign states in enlarged mediastinal lymph-nodes and represents an alternative method in aetiological work-up of mediastinal lymphadenopathies. Advances in knowledge: DWIBS may represent a useful adjunctive imaging modality, particularly for diagnosis of benign mediastinal lymph node, and thus may reduce the frequency of futile mediastinoscopy, which remains an invasive procedure.

Discrimination of Malignant versus Benign Mediastinal Lymph Nodes Using Diffusion MRI with an IVIM Model.

To investigate the value of an intravoxel incoherent motion (IVIM) diffusion model for discriminating malignant versus benign mediastinal lymph nodes (MLN). Thirty-five subjects with enlarged MLN were scanned at 1.5 Tesla. Diffusion-weighted imaging was performed with eight b-values. IVIM parameters D, D*, and f, as well as apparent diffusion coefficient (ADC) from a mono-exponential model were obtained. 91 nodes (49 malignant and 42 benign) were analysed with pathologic (n=90) or radiologic (n=1) confirmations. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance. The mean values of D, ADC, and f for the malignant group were significantly lower than those for the benign group (p<0.001), while D* showed no significant difference (p=0.281). In the ROC analysis, the combination of D and f produced the largest area under the curve (0.953) compared to ADC or other individual IVIM parameters, leading to the best specificity (92.9%) and diagnostic accuracy (90.1%). This study demonstrates that the combination of IVIM parameters can improve differentiation between malignant and benign MLN as compared to using ADC alone. • Diffusion MRI is useful for non-invasively discriminating malignant versus benign lymph nodes. • A mono-exponential model is not adequate to characterise diffusion process in lymph nodes. • IVIM model is advantageous over mono-exponential model for assessing lymph node malignancy. • Combination of IVIM parameters improves differentiation of malignant versus benign lymph nodes.

The role of endobronchial ultrasound elastography in the diagnosis of mediastinal and hilar lymph nodes.

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) has been widely used for diagnosis and mediastinal lymph nodes staging in patients with suspicious lung cancer. Ultrasound elastography is a novel sonographical technique that can evaluate tissue compressibility. The aim of the present study was to investigate the diagnostic yield of elastography for differentiating malignant and benign mediastinal lymph nodes. Conventional EBUS B-mode features, including size, shape, border distinction, echogenicity, central hilar structure with central blood vessel and coagulation necrosis were also evaluated. The ultrasonic features were compared with the pathological results from EBUS-TBNA. 133 lymph nodes in 60 patients were assessed. Elastography displayed the highest area under the curve (AUC) (type 3 versus type 1: AUC, 0.825; 95% confidence interval [CI], 0.707-0.910) with an impressive sensitivity (100%) and an acceptable specificity (65%). The combined model covering the four positive criteria (elastography, heterogeneity, size, and shape) showed that the odds ratio for malignance is 9.44 with a 95% CI of 3.99 to 22.32 (p <0.0001). The combined model was superior to elastography alone (AUC, 0.851; sensitivity, 89.89%; specificity, 72.73%; p <0.0001). This prospective study showed that elastography is a feasible technique for classifying mediastinal lymph nodes, especially in combination with conventional EBUS imaging.

Texture Analysis and Synthesis of Malignant and Benign Mediastinal Lymph Nodes in Patients with Lung Cancer on Computed Tomography

Texture analysis of computed tomography (CT) imaging has been found useful to distinguish subtle differences, which are in- visible to human eyes, between malignant and benign tissues in cancer patients. This study implemented two complementary methods of texture analysis, known as the gray-level co-occurrence matrix (GLCM) and the experimental semivariogram (SV) with an aim to improve the predictive value of evaluating mediastinal lymph nodes in lung cancer. The GLCM was explored with the use of a rich set of its derived features, whereas the SV feature was extracted on real and synthesized CT samples of benign and malignant lymph nodes. A distinct advantage of the computer methodology presented herein is the alleviation of the need for an automated precise segmentation of the lymph nodes. Using the logistic regression model, a sensitivity of 75%, specificity of 90%, and area under curve of 0.89 were obtained in the test population. A tenfold cross-validation of 70% accuracy of classifying between benign and malignant lymph nodes was obtained using the support vector machines as a pattern classifier. These results are higher than those recently reported in literature with similar studies.

87P Qualitative and quantitative interpretation of F-18 FDG PET/CT to differentiate metastatic mediastinal lymph node in non-small cell lung carcinoma patients with benign mediastinal lymph node hyperplasia

87P Qualitative and quantitative interpretation of F-18 FDG PET/CT to differentiate metastatic mediastinal lymph node in non-small cell lung carcinoma patients with benign mediastinal lymph node hyperplasia

Increased x-ray attenuation in malignant vs. benign mediastinal nodes in an orthotopic model of lung cancer.

Staging of lung cancer is typically performed with fluorodeoxyglucose-positron emission tomography-computed tomography (FDG-PET/CT); however, false positive PET scans can occur due to inflammatory disease. The CT scan is used for anatomic registration and attenuation correction. Herein, we evaluated x-ray attenuation (XRA) within nodes on CT and correlated this with the presence of malignancy in an orthotopic lung cancer model in rats. 1×10⁶ NCI-H460 cells were injected transthoracically in six National Institutes of Health nude rats and six animals served as controls. After two weeks, animals were sacrificed; lymph nodes were extracted and scanned with a micro-CT to determine their XRA prior to histologic analysis. Median CT density in malignant lymph nodes (n=20) was significantly higher than benign lymph nodes (n=12; P = 0.018). Short-axis diameter of metastatic lymph nodes was significantly different than benign nodes (3.4 mm vs. 2.4 mm; P = 0.025). Area under the curve for malignancy was higher for density-based lymph node analysis compared with size measurements (0.87 vs. 0.7). XRA of metastatic mediastinal lymph nodes is significantly higher than benign nodes in this lung cancer model. This suggests that information on nodal density may be useful when used in combination with the results of FDG-PET in determining the likelihood of malignant adenopathy.

Endobronchial ultrasound elastography strain ratio for mediastinal lymph node diagnosis.

BackgroundUltrasound elastography is an imaging procedure that can assess the biomechanical characteristics of different tissues. The aim of this study was to define the diagnostic value of the endobronchial ultrasound (EBUS) elastography strain ratio of mediastinal lymph nodes in patients with a suspicion of lung cancer. The diagnostic values of the strain ratios were compared with the EBUS brightness mode (B-mode) features of selected mediastinal lymph nodes and with their cytological diagnoses.Patients and methodsThis prospective, single-centre study enrolled patients with an indication for biopsy and mediastinal staging after a non-invasive diagnostic workup of a lung tumour. EBUS with standard B-mode evaluation and elastography with strain ratio measurement were performed before endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA).ResultsThirty-three patients with 80 suspicious mediastinal lymph nodes were included. Malignant infiltration was confirmed in 34 (42.5%) lymph nodes. The area under the receiver operating characteristic curve for the strain ratio was 0.87 (p < 0.0001). At a strain ratio ≥ 8, the accuracy for malignancy prediction was 86.25% (sensitivity 88.24%, specificity 84.78%, positive predictive value [PPV] 81.08%, negative predictive value [NPV] 90.70%). The strain ratio is more accurate than conventional B-mode EBUS modalities for differentiating between malignant and benign lymph nodes.ConclusionsEBUS-guided elastography with strain ratio assessment can distinguish malignant from benign mediastinal lymph nodes with greater accuracy than conventional EBUS modalities. This new method may reduce the number of mediastinal EBUS-TBNAs and thus reduce the invasiveness and expense of mediastinal staging in patients with non-small lung cancer (NSCLC).

NOTES and the mediastinum

When natural orifice transluminal endoscopic surgery (NOTES) was introduced more than 10 years ago, it presented the possibility of less-invasive, initially abdominal procedures through the gut wall without skin incision. As procedures were carried out without sufficient basis of experience and knowledge about possible hazards, the most critical points and possible complications of NOTES procedures were defined early on in a white paper 1. When interest was shown in applying NOTES through the esophagus into the mediastinum 2, it was thought to be an unreasonable and hazardous undertaking. Years earlier, in the mid-1990 s, introduction of mediastinal endoscopic ultrasound-fine-needle aspiration (EUS-FNA) caused similar disapproval amongst thoracic surgeons. However, the technique later proved to be a safe and minimally invasive technique that allows complete inspection of and tissue sampling in the entire mediastinum when used in combination with endobronchial ultrasound (EBUS). EUS-FNA has largely replaced standard video-assisted mediastinoscopy (VAM) for evaluation and tissue sampling of malignant and benign mediastinal nodes and lesions. Evolving experience with NOTES over the last 10 years, since its role in the thoracic and medisastinal space was initially explored, facilitated further understanding of the potential hazards of endoscopic access to the mediastinum. The recent hype around per-oral endoscopic Heller myotomy (POEM), although not strictly NOTES, suggests that a transesophageal approach (to the non-luminal musculature of the esophagus and submucosal tumors through the new “third space”, the submucosal tunnel) may become one of the most useful settings for a NOTES-like procedure 3 4. One of the few groups with noteworthy experience with NOTES in the thoracic space has published a study in this issue 5. In accord with the Noscar White paper, the authors concentrated on feasibility, access, potential hazards, and safety 1. Most of the studies available to date were performed in an animal model and only a few in humans, if POEM procedures are excluded 6 7. This is mainly due to concerns about the safety of the currently available access and closure methods and devices and uncertainty about whether possible complications, including infection and bleeding, can be addressed adequately.

Quantitative CT texture and shape analysis: can it differentiate benign and malignant mediastinal lymph nodes in patients with primary lung cancer?

To assess the accuracy of CT texture and shape analysis in the differentiation of benign and malignant mediastinal nodes in lung cancer. Forty-three patients with biopsy-proven primary lung malignancy with pathological mediastinal nodal staging and unenhanced CT of the thorax were studied retrospectively. Grey-level co-occurrence and run-length matrix textural features, as well as morphological features, were extracted from 72 nodes. Differences between benign and malignant features were assessed using Mann-Whitney U tests. Receiver operating characteristic (ROC) curves for each were constructed and the area under the curve (AUC) calculated with histopathology diagnosis as outcome. Combinations of features were also entered as predictors in logistic regression models and optimal threshold criteria were used to estimate sensitivity and specificity. Using optimum-threshold criteria, the combined textural and shape features identified malignant mediastinal nodes with 81% sensitivity and 80% specificity (AUC = 0.87, P < 0.0001). Using this combination, 84% malignant and 71% benign nodes were correctly classified. Quantitative CT texture and shape analysis has the potential to accurately differentiate malignant and benign mediastinal nodes in lung cancer. • Mediastinal nodal staging is crucial in the management of lung cancer • Mediastinal nodal metastasis affects prognosis and suitability for surgical treatment • Computed tomography (CT) is limited for mediastinal nodal staging • Texture analysis measures tissue heterogeneity not perceptible to human vision • CT texture analysis may accurately differentiate malignant and benign mediastinal nodes.

PET-CT in the assessment of lung cancer at Rikshospitalet from 2007-2011.

PET-CT is an aid in the assessment of lung cancer for identifying operable patients. The examination is recommended for most patients with non-small cell lung cancer whom the primary assessment has indicated may have a curable disease. The aim was to assess the usefulness of PET-CT for patients assumed to be operable who underwent an examination at Rikshospitalet. Patients admitted for lung cancer assessment are registered consecutively in the department's quality database. We analysed data for the period 2007-2011 for patients whom a primary assessment had revealed to have a potentially operable tumour. For capacity reasons, some patients underwent surgery without a prior PET-CT. Of 651 potentially operable patients, 533 had had a PET-CT scan of which 403 (76%) had undergone surgery. We calculated that the examination had a sensitivity of 78% (95% CI 70-86) and specificity 88% (95% CI 85-91%), positive predictive value 64% (95% CI 55-72) and negative predictive value 94% (95% CI 91-96) for spreading to mediastinal lymph nodes. Diagnostic accuracy was 86% (95% CI 83-89) with kappa agreement 0.61 (95% CI 0.53-0.69) between PET-CT and actual findings of malignant or benign mediastinal lymph nodes. PET-CT was a useful tool for selecting potentially operable lung cancer patients at Rikshospitalet in the period 2007-2011. Provided that the population we scan with PET-CT does not change, patients with a negative PET-CT can with few exceptions be referred directly for surgery without further invasive assessment.