Differentiating benign from malignant mediastinal lymph nodes visible at EBUS using grey-scale textural analysis

Enhancing Lung Cancer Care in Portugal: Bridging Gaps for Improved Patient Outcomes

Lung cancer has the highest incidence and cancer-related mortality worldwide. In Portugal, it ranks as the fourth most common cancer, with nearly 6000 new cases being diagnosed every year. Lung cancer is the main cause of cancer-related death among males and the third cause of cancer-related death in females. Despite the globally accepted guidelines and recommendations for what would be the ideal path for a lung cancer patient, several challenges occur in real clinical management across the world. The recommendations emphasize the importance of adequate screening of high-risk individuals, a precise tumour biopsy, and an accurate final diagnosis to confirm the neoplastic nature of the nodule. A detailed histological classification of the lung tumour type and a comprehensive molecular characterization are of utmost importance for the selection of an efficacious and patient-directed therapeutic approach. However, in the context of the Portuguese clinical organization and the national healthcare system, there are still several gaps in the ideal pathway for a lung cancer patient, involving aspects ranging from the absence of a national lung cancer screening programme through difficulties in histological diagnosis and molecular characterization to challenges in therapeutic approaches. In this manuscript, we address the most relevant weaknesses, presenting several proposals for potential solutions to improve the management of lung cancer patients, helping to decisively improve their overall survival and quality of life.

Artificial intelligence in interventional pulmonology

PURPOSE OF REVIEW

In recent years, there has been remarkable progress in the field of artificial intelligence technology. Artificial intelligence applications have been extensively researched and actively implemented across various domains within healthcare. This study reviews the current state of artificial intelligence research in interventional pulmonology and engages in a discussion to comprehend its capabilities and implications.

RECENT FINDINGS

Deep learning, a subset of artificial intelligence, has found extensive applications in recent years, enabling highly accurate identification and labeling of bronchial segments solely from intraluminal bronchial images. Furthermore, research has explored the use of artificial intelligence for the analysis of endobronchial ultrasound images, achieving a high degree of accuracy in distinguishing between benign and malignant targets within ultrasound images. These advancements have become possible due to the increased computational power of modern systems and the utilization of vast datasets, facilitating detections and predictions with greater precision and speed.

SUMMARY

Artificial intelligence integration into interventional pulmonology has the potential to enhance diagnostic accuracy and patient safety, ultimately leading to improved patient outcomes. However, the clinical impacts of artificial intelligence enhanced procedures remain unassessed. Additional research is necessary to evaluate both the advantages and disadvantages of artificial intelligence in the field of interventional pulmonology.

Efficacy of texture analysis of ultrasonographic images in the differentiation of metastatic and non-metastatic cervical lymph nodes in patients with squamous cell carcinoma of the tongue

OBJECTIVE

We investigated the efficacy of using texture analysis of ultrasonographic images of the cervical lymph nodes of patients with squamous cell carcinoma of the tongue to differentiate between metastatic and non-metastatic lymph nodes.

STUDY DESIGN

We analyzed 32 metastatic and 28 non-metastatic lymph nodes diagnosed by histopathologic examination on presurgical US images. Using the LIFEx texture analysis program, we extracted 36 texture features from the images and calculated the statistical significance of differences in texture features between metastatic and non-metastatic lymph nodes using the t test. To assess the diagnostic ability of the significantly different texture features to discriminate between metastatic and non-metastatic nodes, we performed receiver operating characteristic curve analysis and calculated the area under the curve. We set the cutoff points that maximized the sensitivity and specificity for each curve according to the Youden J statistic.

RESULTS

We found that 20 texture features significantly differed between metastatic and non-metastatic lymph nodes. Among them, only the gray-level run length matrix feature of run length non-uniformity and the gray-level zone length matrix features of gray-level non-uniformity and zone length non-uniformity showed an excellent ability to discriminate between metastatic and non-metastatic lymph nodes as indicated by the area under the curve and the sum of sensitivity and specificity.

CONCLUSIONS

Analysis of the texture features of run length non-uniformity, gray-level non-uniformity, and zone length non-uniformity values allows for differentiation between metastatic and non-metastatic lymph nodes, with the use of gray-level non-uniformity appearing to be the best means of predicting metastatic lymph nodes.

The Application of Texture Feature Analysis of Rectus Femoris Based on Local Binary Pattern (LBP) Combined With Gray-Level Co-Occurrence Matrix (GLCM) in Sarcopenia

OBJECTIVES

In order to detect the changes in muscle texture of sarcopenia and to explore a new method of ultrasound assessment of muscle changes in sarcopenia.

METHODS

we used the local binary pattern (LBP) combined with gray-level co-occurrence matrix (GLCM) method to extract and quantitatively analyze the texture information of the rectus femoris of different people, and initially verified the robustness of this method to image gain changes. We recruited young volunteers, elderly volunteers without sarcopenia, and elderly volunteers with sarcopenia in this cross-sectional study. We scanned the rectus femoris and extracted their muscle texture features.

RESULTS

We found that when ultrasonographic gain varied from 40% to 70%, the intraclass correlation coefficient (ICC) of contrast, entropy, and homogeneity were 0.989, 0.973, and 0.989, respectively. Body mass index was significantly related to contrast (r = 0.285, P < .05), and age had a significant correlation with contrast and homogeneity (r = -0.259 and r = 0.269, P < .05). The elderly volunteers with sarcopenia had the highest entropy (0.363 [0.342-0.403]) and homogeneity (2.203 [2.162-2.277]) in the texture of the rectus femoris among the three groups, and at the same time had the lowest contrast (44.583 [43.492-47.399]), and all P < .05.

CONCLUSION

LBP combined with GLCM can be a stable method for extracting muscle texture features. At the same time, the contrast, entropy, and homogeneity of the rectus femoris of the elderly with sarcopenia were significantly different from those of the young volunteers and the elderly without sarcopenia, suggesting the texture features of rectus femoris are potential parameters for evaluating muscle function and pathological changes.

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.

Diagnostic utility of endobronchial ultrasound (EBUS) features in differentiating malignant and benign lymph nodes - A systematic review and meta-analysis

BACKGROUND

EBUS is being widely used today for echolocation of lymph nodes for FNAC. We present a systematic review and meta-analysis to assess the diagnostic accuracy of EBUS characteristics of lymph nodes in diagnosing malignancy.

METHODS

A systematic search of published literature was undertaken using databases like PubMed, Web of Science, Cochrane, Google Scholar and Researchgate. Those studies reporting any endobronchial ultrasonography features of malignant lymph nodes like size, margins, echogenicity, shape, central hilar structure (CHS), coagulation necrosis sign (CNS) or color power doppler index (CPDI) were included for review. Random effects model was used to calculate pooled sensitivity, specificity, positive and negative likelihood ratios (LR), and diagnostic odds ratio (DOR). The review protocol was registered with the International prospective register of systematic reviews (PROSPERO registration no. CRD42019117716).

RESULTS

992 articles were retrieved of which 542 articles were evaluated in detail and finally 29 articles met the inclusion criteria. All EBUS features except CPDI showed a statistically significant area under the SROC curve. CNS showed highest area under the SROC curve [0.81 (SE: 0.09)] with maximum pooled specificity [0.93, 95%CI: 0.92-0.94], maximum pooled LR+ [5.12, 95%CI: 2.56-10.2] and DOR [9.23, 95%CI 3.85-22.15]. Maximum sensitivity was seen for CHS 0.91 [95%CI: 0.90-0.92].

CONCLUSION

EBUS features have the potential to help in more precise location of a malignant lymph node thereby helping in increasing the diagnostic yield. However, high diagnostic accuracy of various EBUS features can currently only be said to supplement tissue diagnosis.

Committee II: Guidelines for cytologic sampling techniques of lung and mediastinal lymph nodes

The Papanicolaou Society of Cytopathology has developed a set of guidelines for pulmonary cytology including indications for bronchial brushings, washings, and endobronchial ultrasound guided transbronchial fine-needle aspiration (EBUS-TBNA), technical recommendations for cytological sampling, recommended terminology and classification schemes, recommendations for ancillary testing and recommendations for post-cytological management and follow-up. All recommendations are based on the expertise of the authors, an extensive literature review and feedback from presentations at national and international conferences. This document selectively presents the results of these discussions. The present document summarizes recommendations regarding techniques used to obtain cytological and small histologic specimens from the lung and mediastinal lymph nodes including rapid on-site evaluation (ROSE), and the triage of specimens for immunocytochemical and molecular studies.

The optimal sequence for bronchial brushing and forceps biopsy in lung cancer diagnosis: a random control study

BACKGROUND

Optimizing basic techniques in diagnostic bronchoscopy is important for improving medical services in developing countries. In this study, the optimal sequence of bronchial brushing relative to bronchial biopsy for lung cancer diagnosis was evaluated.

METHODS

A total of 420 patients with visible endobronchial tumors were prospectively and randomly enrolled in two groups: a pre-biopsy brushing group, receiving two brushings before biopsy; two brushings which performed afterwards; were set as self-control and compared with the pre-biopsy brushings as the intra-group comparison; and a post-biopsy brushing group, only receiving two brushings after biopsy, which were compared with the pre-biopsy brushings as the inter-group comparison. Diagnostic yield of brushing was compared before and after biopsy, and as well as for different tumor pathologies and bronchoscopic morphologies. The occurrence of treated bleeding which defined as bleeding needed further intervention with argon plasma coagulation and/or anti-coagulation drugs in two groups was also compared.

RESULTS

Only patients with a definitive cytological or histological diagnosis of lung cancer based on bronchoscopy or other confirmatory techniques were included. Patients were excluded if they had submucosal lesions, extrinsic compressions, pulmonary metastasis of extrapulmonary malignancies or uncommon non-small cell lung carcinoma (NSCLC). A total of 362 patients who met the inclusion criteria were analyzed. Diagnostic yield for pre-biopsy brushing (49.2%, 88/179) was significantly higher than for post-biopsy brushing within the same pre-biopsy brushing group (31.8%, 57/179) (P=0.007) as the intra-group comparison, and significantly higher than for post-biopsy brushing in the post group (30.6%, 56/183) (P<0.001) as the inter-group comparison. No difference in occurrence of treated bleeding for pre- vs. post-biopsy bronchial brushing was found.

CONCLUSIONS

Supplementing bronchoscopic forceps biopsy with brushing improves diagnostic yield in lung cancer. In cases of endobronchial exophytic tumors, pre-biopsy brushing appears to be superior to post-biopsy brushing.

Endoscopic ultrasound: Elastographic lymph node evaluation

Different imaging techniques can bring different information which will contribute to the final diagnosis and further management of the patients. Even from the time of Hippocrates, palpation has been used in order to detect and characterize a body mass. The so-called virtual palpation has now become a reality due to elastography, which is a recently developed technique. Elastography has already been proving its added value as a complementary imaging method, helpful to better characterize and differentiate between benign and malignant masses. The current applications of elastography in lymph nodes (LNs) assessment by endoscopic ultrasonography will be further discussed in this paper, with a review of the literature and future perspectives.