BACKGROUND AND OBJECTIVES

The Philippines faces challenges in the screening of tuberculosis (TB), one of them being the shortage in the health workforce who are skilled and allowed to screen TB. Deep learning neural networks (DLNNs) have shown potential in the TB screening process utilizing chest radiographs (CXRs). However, local studies on AIbased TB screening are limited. This study evaluated qXR3.0 technology's diagnostic performance for TB screening in Filipino adults aged 15 and older. Specifically, we evaluated the specificity and sensitivity of qXR3.0 compared to radiologists' impressions and determined whether it meets the World Health Organization (WHO) standards.

A prospective cohort design was used to perform a study on comparing screening and diagnostic accuracies of qXR3.0 and two radiologist gradings in accordance with the Standards for Reporting Diagnostic Accuracy (STARD). Subjects from two clinics in Metro Manila which had qXR 3.0 seeking consultation at the time of study were invited to participate to have CXRs and sputum collected. Radiologists' and qXR3.0 readings and impressions were compared with respect to the reference standard Xpert MTB/RiF assay. Diagnostic accuracy measures were calculated.

With 82 participants, qXR3.0 demonstrated 100% sensitivity and 72.7% specificity with respect to the reference standard. There was a strong agreement between qXR3.0 and radiologists' readings as exhibited by the 0.7895 (between qXR 3.0 and CXRs read by at least one radiologist), 0.9362 (qXR 3.0 and CXRs read by both radiologists), and 0.9403 (qXR 3.0 and CXRs read as not suggestive of TB by at least one radiologist) concordance indices.

qXR3.0 demonstrated high sensitivity to identify presence of TB among patients, and meets the WHO standard of at least 70% specificity for detecting true TB infection. This shows an immense potential for the tool to supplement the shortage of radiologists for TB screening in the country. Future research directions may consider larger sample sizes to confirm these findings and explore the economic value of mainstream adoption of qXR 3.0 for TB screening.

Human ; Diagnostic Tests, Routine ; Urolithiasis ; Urologists

Background and Objectives: The Philippines faces challenges in the screening of tuberculosis (TB), one of them being the shortage in the health workforce who are skilled and allowed to screen TB. Deep learning neural networks (DLNNs) have shown potential in the TB screening process utilizing chest radiographs (CXRs). However, local studies on AIbased TB screening are limited. This study evaluated qXR3.0 technology's diagnostic performance for TB screening in Filipino adults aged 15 and older. Specifically, we evaluated the specificity and sensitivity of qXR3.0 compared to radiologists' impressions and determined whether it meets the World Health Organization (WHO) standards. Methods: A prospective cohort design was used to perform a study on comparing screening and diagnostic accuracies of qXR3.0 and two radiologist gradings in accordance with the Standards for Reporting Diagnostic Accuracy (STARD). Subjects from two clinics in Metro Manila which had qXR 3.0 seeking consultation at the time of study were invited to participate to have CXRs and sputum collected. Radiologists' and qXR3.0 readings and impressions were compared with respect to the reference standard Xpert MTB/RiF assay. Diagnostic accuracy measures were calculated. Results: With 82 participants, qXR3.0 demonstrated 100% sensitivity and 72.7% specificity with respect to the reference standard. There was a strong agreement between qXR3.0 and radiologists' readings as exhibited by the 0.7895 (between qXR 3.0 and CXRs read by at least one radiologist), 0.9362 (qXR 3.0 and CXRs read by both radiologists), and 0.9403 (qXR 3.0 and CXRs read as not suggestive of TB by at least one radiologist) concordance indices. Conclusions qXR3.0 demonstrated high sensitivity to identify presence of TB among patients, and meets the WHO standard of at least 70% specificity for detecting true TB infection. This shows an immense potential for the tool to supplement the shortage of radiologists for TB screening in the country. Future research directions may consider larger sample sizes to confirm these findings and explore the economic value of mainstream adoption of qXR 3.0 for TB screening.
Tuberculosis ; Diagnostic Imaging ; Deep Learning

BACKGROUND: The thoracic small biopsy sampling procedure including transbronchial forceps lung biopsy (TBLB) and endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) can be accompanied by rapid on-site evaluation (ROSE) of sample material to provide immediate feedback for the proceduralist. The present study aims to investigate the supplemental effect of ROSE smear samples for lung cancer molecular test. METHODS: In a retrospective study, 308 patients admitted to our hospital from August 2020 to December 2022 undergoing diagnostic TBLB and EBUS-TBNA with ROSE and subsequently diagnosed as non-small cell lung cancer (NSCLC) were analyzed. The matched formalin-fixed paraffin-embedding (FFPE) tissue section and ROSE smears for tumor cellularity were compared. DNA yields of smears were determined. Real-time polymerase chain reaction (PCR) and next-generation sequencing (NGS) were performed on adequate smear samples. RESULTS: ROSE smear samples were enriched in tumor cells. Among 308 biopsy samples, 78 cases (25.3%) exhibited inadequate FFPE tissue sections, whereas 44 cases (14.3%) yielded adequate smear samples. Somatic mutations detected in the FFPE tissue section samples were also detected in the matching adequate smear sample. CONCLUSIONS ROSE smear samples of the thoracic small biopsies are beneficial supplemental materials for ancillary testing of lung cancer. Combined use of cytology smear samples with traditional FFPE section samples can enhance the detection rate of informative mutations in patients with advanced NSCLC. We recommend that the laboratory could further evaluate the ROSE cell smears of the patient when FFPE tissue sections are inadequate, and that adequate cell smears can be used as a supplemental source for the molecular testing of NSCLC.
Humans ; Carcinoma, Non-Small-Cell Lung/pathology* ; Lung Neoplasms/pathology* ; Rapid On-site Evaluation ; Retrospective Studies ; Molecular Diagnostic Techniques ; Endoscopic Ultrasound-Guided Fine Needle Aspiration/methods*

OBJECTIVE: To investigate a new noninvasive diagnostic model for nonalcoholic fatty liver disease (NAFLD) based on features of tongue images. METHODS: Healthy controls and volunteers confirmed to have NAFLD by liver ultrasound were recruited from China-Japan Friendship Hospital between September 2018 and May 2019, then the anthropometric indexes and sampled tongue images were measured. The tongue images were labeled by features, based on a brief protocol, without knowing any other clinical data, after a series of corrections and data cleaning. The algorithm was trained on images using labels and several anthropometric indexes for inputs, utilizing machine learning technology. Finally, a logistic regression algorithm and a decision tree model were constructed as 2 diagnostic models for NAFLD. RESULTS: A total of 720 subjects were enrolled in this study, including 432 patients with NAFLD and 288 healthy volunteers. Of them, 482 were randomly allocated into the training set and 238 into the validation set. The diagnostic model based on logistic regression exhibited excellent performance: in validation set, it achieved an accuracy of 86.98%, sensitivity of 91.43%, and specificity of 80.61%; with an area under the curve (AUC) of 0.93 [95% confidence interval (CI) 0.68-0.98]. The decision tree model achieved an accuracy of 81.09%, sensitivity of 91.43%, and specificity of 66.33%; with an AUC of 0.89 (95% CI 0.66-0.92) in validation set. CONCLUSIONS The features of tongue images were associated with NAFLD. Both the 2 diagnostic models, which would be convenient, noninvasive, lightweight, rapid, and inexpensive technical references for early screening, can accurately distinguish NAFLD and are worth further study.
Humans ; Non-alcoholic Fatty Liver Disease/diagnostic imaging* ; Ultrasonography ; Anthropometry ; Algorithms ; China

Hepatocellular carcinoma (HCC) is one of the most common malignancies and is a major cause of cancer-related mortalities worldwide (Forner et al., 2018; He et al., 2023). Sarcopenia is a syndrome characterized by an accelerated loss of skeletal muscle (SM) mass that may be age-related or the result of malnutrition in cancer patients (Cruz-Jentoft and Sayer, 2019). Preoperative sarcopenia in HCC patients treated with hepatectomy or liver transplantation is an independent risk factor for poor survival (Voron et al., 2015; van Vugt et al., 2016). Previous studies have used various criteria to define sarcopenia, including muscle area and density. However, the lack of standardized diagnostic methods for sarcopenia limits their clinical use. In 2018, the European Working Group on Sarcopenia in Older People (EWGSOP) renewed a consensus on the definition of sarcopenia: low muscle strength, loss of muscle quantity, and poor physical performance (Cruz-Jentoft et al., 2019). Radiological imaging-based measurement of muscle quantity or mass is most commonly used to evaluate the degree of sarcopenia. The gold standard is to measure the SM and/or psoas muscle (PM) area using abdominal computed tomography (CT) at the third lumbar vertebra (L3), as it is linearly correlated to whole-body SM mass (van Vugt et al., 2016). According to a "North American Expert Opinion Statement on Sarcopenia," SM index (SMI) is the preferred measure of sarcopenia (Carey et al., 2019). The variability between morphometric muscle indexes revealed that they have different clinical relevance and are generally not applicable to broader populations (Esser et al., 2019).
Humans ; Aged ; Sarcopenia/diagnostic imaging* ; Carcinoma, Hepatocellular/diagnostic imaging* ; Muscle, Skeletal/diagnostic imaging* ; Deep Learning ; Prognosis ; Radiomics ; Liver Neoplasms/diagnostic imaging* ; Retrospective Studies

INTRODUCTION: Ultrasonography (US) is the current standard of care for imaging surveillance in patients at risk of hepatocellular carcinoma (HCC). Magnetic resonance imaging (MRI) has been explored as an alternative, given the higher sensitivity of MRI, although this comes at a higher cost. We performed a cost-effective analysis comparing US and dual-sequence non-contrast-enhanced MRI (NCEMRI) for HCC surveillance in the local setting. METHODS: Cost-effectiveness analysis of no surveillance, US surveillance and NCEMRI surveillance was performed using Markov modelling and microsimulation. At-risk patient cohort was simulated and followed up for 40 years to estimate the patients' disease status, direct medical costs and effectiveness. Quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio were calculated. RESULTS: Exactly 482,000 patients with an average age of 40 years were simulated and followed up for 40 years. The average total costs and QALYs for the three scenarios - no surveillance, US surveillance and NCEMRI surveillance - were SGD 1,193/7.460 QALYs, SGD 8,099/11.195 QALYs and SGD 9,720/11.366 QALYs, respectively. CONCLUSION Despite NCEMRI having a superior diagnostic accuracy, it is a less cost-effective strategy than US for HCC surveillance in the general at-risk population. Future local cost-effectiveness analyses should include stratifying surveillance methods with a variety of imaging techniques (US, NCEMRI, contrast-enhanced MRI) based on patients' risk profiles.
Humans ; Adult ; Carcinoma, Hepatocellular/diagnostic imaging* ; Liver Neoplasms/diagnostic imaging* ; Cost-Effectiveness Analysis ; Cost-Benefit Analysis ; Quality-Adjusted Life Years ; Magnetic Resonance Imaging/methods*

Humans ; Myocarditis/diagnostic imaging* ; Magnetic Resonance Imaging ; Myocardium ; Giant Cells

Humans ; Myocarditis/diagnostic imaging* ; Magnetic Resonance Imaging ; Myocardium ; Giant Cells

Objective: To summarize the original CT features of Pneumocystis Jirovecii pneumonia in patients with hematological diseases. Methods: A retrospective analysis was carried out in 46 patients with proven pneumocystis pneumonia (PJP) in the Hospital of Hematology, Chinese Academy of Medical Sciences between January 2014 and December 2021. All patients had multiple chests CT and related laboratory examinations, imaging typing were conducted based on the initial CT presentation, and the distinct imaging types were analyzed against the clinical data. Results: In the analysis, there were 46 patients with proven pathogenesis, 33 males, and 13 females, with a median age of 37.5 (2-65) years. The diagnosis was validated by bronchoalveolar lavage fluid (BALF) hexamine silver staining in 11 patients and clinically diagnosed in 35 cases. Of the 35 clinically diagnosed patients, 16 were diagnosed by alveolar lavage fluid macrogenomic sequencing (BALF-mNGS) and 19 by peripheral blood macrogenomic sequencing (PB-mNGS) . The initial chest CT presentation was categorized into 4 types, including ground glass (GGO) type in 25 cases (56.5%) , nodular type in 10 cases (21.7%) , fibrosis type in 4 cases (8.7%) , and mixed type in 5 cases (13.0%) . There was no substantial discrepancy in CT types among confirmed patients, BALF-mNGS diagnosed patients and PB-mNGS diagnosed patients (χ(2)=11.039, P=0.087) . The CT manifestations of confirmed patients and PB-mNGS diagnosed patients were primarily GGO type (67.6%, 73.7%) , while that of BALF-mNGS diagnosed patients were nodular type (37.5%) . Of the 46 patients, 63.0% (29/46) had lymphocytopenia in the peripheral blood, 25.6% (10/39) with positive serum G test, and 77.1% (27/35) with elevated serum lactate dehydrogenase (LDH) . There were no great discrepancies in the rates of lymphopenia in peripheral blood, positive G-test, and increased LDH among different CT types (all P>0.05) . Conclusion: The initial chest CT findings of PJP in patients with hematological diseases were relatively prevalent with multiple GGO in both lungs. Nodular and fibrosis types were also the initial imaging findings for PJP.
Male ; Female ; Humans ; Adult ; Middle Aged ; Aged ; Pneumonia, Pneumocystis/diagnostic imaging* ; Retrospective Studies ; Pneumocystis carinii ; Hematologic Diseases/complications* ; Tomography, X-Ray Computed ; Fibrosis