Active pulmonary tuberculosis: something old, something new, something borrowed, something blue

Explore the Application Value of Metagenomic Next-Generation Sequencing of Bronchoalveolar Lavage Fluid in the Early Diagnosis of Pulmonary Tuberculosis

Objective

Compare the diagnostic efficacy of bronchoalveolar lavage fluid (BALF) metagenomic next-generation sequencing (mNGS) with that of four traditional methods in the diagnosis of pulmonary tuberculosis (PTB), and explore the application value of BALF mNGS in the early diagnosis of PTB.

Methods

A retrospective analysis was performed on 102 patients with suspected PTB in Wuming Hospital Affiliated with Guangxi Medical University from January 2021 to August 2024, among which 61 cases were PTB and 41 cases were non - PTB. Diagnostic performance metrics (sensitivity, specificity, positive/negative predictive value [PPV/NPV], accuracy) were calculated for BALF mNGS, sputum TB-DNA, sputum acid-fast bacilli (AFB) smear, BALF AFB smear, and BALF TB-DNA, using clinical diagnosis as the reference standard.

Results

BALF mNGS demonstrated a sensitivity of 75.41% (46/61), specificity of 87.80% (36/41), PPV of 90.20% (46/51), NPV of 70.59% (36/51), and accuracy of 80.39% (82/102). Its accuracy was significantly higher than sputum-based methods (53.03-58.82%, P < 0.0125) and second only to BALF TB-DNA (84.13%, P > 0.0125). BALF mNGS exhibited superior sensitivity compared to sputum TB-DNA (38.00%), sputum AFB smear (41.67%), and BALF AFB smear (41.50%) (P < 0.0125). While specificity and PPV showed no significant differences among methods, BALF mNGS had a higher NPV than sputum-based assays (53.03-54.17%) but lower than BALF TB-DNA (82.53%, P < 0.0125). Both BALF mNGS (Kappa = 0.608, P < 0.001) and BALF TB-DNA (Kappa = 0.670, P < 0.001) showed strong concordance with clinical diagnosis.

Conclusion

BALF mNGS demonstrates high sensitivity and accuracy for PTB diagnosis, outperforming conventional sputum-based methods. Although BALF TB-DNA achieved the highest specificity and NPV, BALF mNGS serves as a robust supplementary tool, particularly for early-stage or paucibacillary PTB. Integration of these molecular techniques may optimize diagnostic workflows in high-TB-burden settings.

Harnessing miRNAs: A Novel Approach to Diagnosis and Treatment of Tuberculosis

Mycobacterium tuberculosis (Mtb) complex, responsible for tuberculosis (TB) infection, continues to be a predominant global cause of mortality due to intricate host-pathogen interactions that affect disease progression. MicroRNAs (miRNAs), essential posttranscriptional regulators, have become pivotal modulators of these relationships. Recent findings indicate that miRNAs actively regulate immunological responses to Mtb complex by modulating autophagy, apoptosis, and immune cell activities. This has resulted in increased interest in miRNAs as prospective diagnostic indicators for TB, especially in differentiating active infection from latent or inactive stages. Variations in miRNA expression during Mtb infection indicate disease progression and offer insights into the immune response. Furthermore, miRNAs present potential as therapeutic targets in host-directed therapy (HDT) techniques for TB infection. This work examines the function of miRNAs in TB pathogenesis, with the objective of identifying particular miRNAs that regulate the immune response to the Mtb complex, evaluating their diagnostic value and exploring their therapeutic implications in host-directed therapy for TB infection. The objective is to enhance comprehension of how miRNAs can facilitate improved diagnosis and treatment of TB.

Development and Validation of Deep Learning-Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study

BACKGROUND

Pulmonary tuberculosis (PTB) poses a global health challenge owing to the time-intensive nature of traditional diagnostic tests such as smear and culture tests, which can require hours to weeks to yield results.

OBJECTIVE

This study aimed to use artificial intelligence (AI)-based chest radiography (CXR) to evaluate the infectivity of patients with PTB more quickly and accurately compared with traditional methods such as smear and culture tests.

METHODS

We used DenseNet121 and visualization techniques such as gradient-weighted class activation mapping and local interpretable model-agnostic explanations to demonstrate the decision-making process of the model. We analyzed 36,142 CXR images of 4492 patients with PTB obtained from Severance Hospital, focusing specifically on the lung region through segmentation and cropping with TransUNet. We used data from 2004 to 2020 to train the model, data from 2021 for testing, and data from 2022 to 2023 for internal validation. In addition, we used 1978 CXR images of 299 patients with PTB obtained from Yongin Severance Hospital for external validation.

RESULTS

In the internal validation, the model achieved an accuracy of 73.27%, an area under the receiver operating characteristic curve of 0.79, and an area under the precision-recall curve of 0.77. In the external validation, it exhibited an accuracy of 70.29%, an area under the receiver operating characteristic curve of 0.77, and an area under the precision-recall curve of 0.8. In addition, gradient-weighted class activation mapping and local interpretable model-agnostic explanations provided insights into the decision-making process of the AI model.

CONCLUSIONS

This proposed AI tool offers a rapid and accurate alternative for evaluating PTB infectivity through CXR, with significant implications for enhancing screening efficiency by evaluating infectivity before sputum test results in clinical settings, compared with traditional smear and culture tests.

Kimura disease, a rare Ethiopian case report

Introduction

Kimura disease is a chronic inflammatory disorder predominantly affecting the head and neck region. The etiology of Kimura disease remains unclear. The disease mainly affects young adult males of Asian descent, with a higher prevalence in East Asian countries.

Clinical presentation

a 48-year-old Ethiopian woman presented with swelling in both her lower extremities, which gradually progressed to include her abdomen and the rest of her body. Additionally, she had pain in multiple joints in her upper and lower extremities, high-grade fever, loss of appetite, night sweats, and unexplained weight loss over the same duration. Physical examination revealed swelling around the eyes (periorbital puffiness), enlarged nodes in the axillary, and inguinal areas on both sides of the body, and pitting edema. Investigations showed pneumonia, elevated renal function tests and kimura disease. Unfortunately, the patient signed medical advice before completing her management.

Conclusion

despite its rarity in Ethiopia, it is imperative to consider Kimura disease as a potential diagnosis when evaluating lymphadenopathy and renal derangement.

Mimics of primary ovarian cancer and primary peritoneal carcinomatosis - A pictorial review

Numerous conditions can mimic ovarian malignancy. Identifying the origin of a pelvic mass or disseminated peritoneal abnormality on imaging is important to ensure that the patient receives optimal management by the appropriate clinical team. Ovarian cancer mimics include infections and other neoplastic processes, for example, actinomycosis, lymphoma, and sarcoma. We will illustrate intraperitoneal and extraperitoneal ovarian and non-ovarian mimics. Primary peritoneal carcinomatosis mimics include processes such as deep infiltrating endometriosis and rare causes such as gliomatosis peritonei and diffuse peritoneal leiomyomatosis. We aim to illustrate the multimodality key imaging appearances of common and rarer types of mimics.

Imaging diagnostics of pulmonary ground-glass nodules: a narrative review with current status and future directions

Background and Objective

The incidence rate of lung cancer, which also has the highest mortality rates for both men and women worldwide, is increasing globally. Due to advancements in imaging technology and the growing inclination of individuals to undergo screening, the detection rate of ground-glass nodules (GGNs) has surged rapidly. Currently, artificial intelligence (AI) methods for data analysis and interpretation, image processing, illness diagnosis, and lesion prediction offer a novel perspective on the diagnosis of GGNs. This article aimed to examine how to detect malignant lesions as early as possible and improve clinical diagnostic and treatment decisions by identifying benign and malignant lesions using imaging data. It also aimed to describe the use of computed tomography (CT)-guided biopsies and highlight developments in AI techniques in this area.

Methods

We used PubMed, Elsevier ScienceDirect, Springer Database, and Google Scholar to search for information relevant to the article's topic. We gathered, examined, and interpreted relevant imaging resources from the Second Affiliated Hospital of Nanchang University's Imaging Center. Additionally, we used Adobe Illustrator 2020 to process all the figures.

Key Content and Findings

We examined the common signs of GGNs, elucidated the relationship between these signs and the identification of benign and malignant lesions, and then described the application of AI in image segmentation, automatic classification, and the invasiveness prediction of GGNs over the last three years, including its limitations and outlook. We also discussed the necessity of conducting biopsies of persistent pure GGNs.

Conclusions

A variety of imaging features can be combined to improve the diagnosis of benign and malignant GGNs. The use of CT-guided puncture biopsy to clarify the nature of lesions should be considered with caution. The development of new AI tools brings new possibilities and hope to improving the ability of imaging physicians to analyze GGN images and achieving accurate diagnosis.

Reversed halo sign as a radiological feature of tuberculosis - Report of two cases

Reversed halo sign (RHS) is a radiological feature described as a focal, rounded area of ground-glass opacity surrounded by a ring of consolidation. In this report we describe two unique radiological cases demonstrating diffuse bilateral infiltrates with multiple RHSs in chest CT scans. Both patients were ultimately diagnosed as having tuberculosis (TB) and had been exposed to silica in the past. This report presents for the first time an association between silica exposure and RHS on CT scans among TB patients. It highlights the importance of having a high index of suspicion for TB in similar scenarios.

Chest Radiograph Screening for Detecting Subclinical Tuberculosis in Asymptomatic Household Contacts, Peru

The World Health Organization's end TB strategy promotes the use of symptom and chest radiograph screening for tuberculosis (TB) disease. However, asymptomatic early states of TB beyond latent TB infection and active disease can go unrecognized using current screening criteria. We conducted a longitudinal cohort study enrolling household contacts initially free of TB disease and followed them for the occurrence of incident TB over 1 year. Among 1,747 screened contacts, 27 (52%) of the 52 persons in whom TB subsequently developed during follow-up had a baseline abnormal radiograph. Of contacts without TB symptoms, persons with an abnormal radiograph were at higher risk for subsequent TB than persons with an unremarkable radiograph (adjusted hazard ratio 15.62 [95% CI 7.74-31.54]). In young adults, we found a strong linear relationship between radiograph severity and time to TB diagnosis. Our findings suggest chest radiograph screening can extend to detecting early TB states, thereby enabling timely intervention.

Technical Quality and Diagnostic Impact of Chest X-rays in Tuberculosis Screening: Insights From a Saudi Teleradiology Cohort

Objectives To assess the standard of chest X-ray techniques in tuberculosis (TB) screening within Saudi Arabian healthcare facilities and evaluate the impact of technical quality on radiological interpretation. Materials and methods Analysis of 250 posteroanterior chest radiographs sourced from a network of five clinics was conducted. These images were scrutinized for technical quality by a radiologist. Results Of the radiographs analyzed, 57% exhibited technical issues, with overexposure and clothing artifacts being the most commonly encountered. Notably, only 14% of these radiographs were deemed to have compromised diagnostic ability. Conclusion The presence of technical issues in most chest X-rays for TB screening highlights a significant area for improvement. However, the relatively low percentage of radiographs impacting diagnostic quality indicates that most issues do not critically hinder the radiologist's interpretative capability. This underscores the importance of balanced quality control measures in radiographic practices for effective TB detection in the region.

Imaging of thoracic tuberculosis: pulmonary and extrapulmonary

Tuberculosis (TB) remains the leading cause of death from a single infectious agent globally, despite being a potentially curable disease. This disease typically affects the lungs but may involve many extrapulmonary sites, especially in patients with risk factors such as HIV infection. The clinical features of extrapulmonary TB may mimic many different disease entities, particularly at less common thoracic sites such as the heart, chest wall, and breast. Imaging has an important role in the early diagnosis of TB, helping to detect disease, guide appropriate laboratory investigation, demonstrate complications, and monitor disease progress and response to treatment. Imaging supports the clinical objective of achieving effective treatment outcome and complication prevention. This review aims to highlight the imaging spectrum of TB affecting both pulmonary and extrapulmonary sites in the thorax. We also briefly provide key background information about TB, such as epidemiology, pathogenesis, and diagnosis.

Distinguishing infectivity in patients with pulmonary tuberculosis using deep learning

Introduction

This study aimed to develop and assess a deep-learning model based on CT images for distinguishing infectivity in patients with pulmonary tuberculosis (PTB).

Methods

We labeled all 925 patients from four centers with weak and strong infectivity based on multiple sputum smears within a month for our deep-learning model named TBINet's training. We compared TBINet's performance in identifying infectious patients to that of the conventional 3D ResNet model. For model explainability, we used gradient-weighted class activation mapping (Grad-CAM) technology to identify the site of lesion activation in the CT images.

Results

The TBINet model demonstrated superior performance with an area under the curve (AUC) of 0.819 and 0.753 on the validation and external test sets, respectively, compared to existing deep learning methods. Furthermore, using Grad-CAM, we observed that CT images with higher levels of consolidation, voids, upper lobe involvement, and enlarged lymph nodes were more likely to come from patients with highly infectious forms of PTB.

Conclusion

Our study proves the feasibility of using CT images to identify the infectivity of PTB patients based on the deep learning method.

Pulmonary tuberculosis presenting with cluster sign and galaxy sign

In a routine medical check-up, a healthy man in his 20s was found to have an upper left lung abnormality. Subsequent chest CT revealed the cluster sign (CS) and galaxy sign (GS). Although tests such as sputum analysis and interferon-gamma assays reduced the likelihood of tuberculosis, these abnormalities remained unchanged. A lung biopsy indicated non-caseating granuloma unrelated to tuberculosis. Initially suspected of sarcoidosis, the patient later developed fever and malaise. Follow-up CT showed CS progressing to a cavitatory shadow and GS intensification. The detection of Mycobacterium tuberculosis (M. tuberculosis) in a subsequent sputum analysis prompted treatment with antitubercular drugs, leading to symptom relief.CS and GS are usually associated with sarcoidosis but can also occur in tuberculosis, connected to slower pathogen growth and lower isolation rates. Furthermore, pulmonary tuberculosis may ultimately be present even when biopsies show non-caseating granulomas that are not typical of M. tuberculosis and sputum culture results are negative for M. tuberculosis Tuberculosis should not be ruled out lightly, and patients should be carefully followed-up.