ArticleDiagnostics (Basel, Switzerland)2022
The Role of Chest CT Radiomics in Diagnosis of Lung Cancer or Tuberculosis: A Pilot Study.
Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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16 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Pooled it
- Role of Chest CT Radiomics in Differentiating Tumorlets and Granulomas: A Preliminary Study.Journal of clinical medicine · 2025Article
- Predictive radiomics based ensemble machine learning approach in CT lung nodule diagnosis.Journal of the Egyptian National Cancer Institute · 2025Article
- High-Resolution Magnetic Resonance Imaging Radiomics for Identifying High-Risk Intracranial Plaques.Translational stroke research · 2025Article
- Development of anQuantitative imaging in medicine and surgery · 2025Article
- AI-Based HRCT Quantification in Connective Tissue Disease-Associated Interstitial Lung Disease.Diagnostics (Basel, Switzerland) · 2025Article
- Impact of Field-of-view Zooming and Segmentation Batches on Radiomics Features Reproducibility and Machine Learning Performance in Thyroid Scintigraphy.Clinical nuclear medicine · 2025Article
- Early treatment monitoring of multidrug-resistant tuberculosis based on CT radiomics of cavity and cavity periphery.European radiology experimental · 2025Article
- Novel Prodrug Strategies for the Treatment of Tuberculosis.Chemistry, an Asian journal · 2024Review
- A Multichannel CT and Radiomics-Guided CNN-ViT (RadCT-CNNViT) Ensemble Network for Diagnosis of Pulmonary Sarcoidosis.Diagnostics (Basel, Switzerland) · 2024Article
- Combining Low-Dose Computer-Tomography-Based Radiomics and Serum Metabolomics for Diagnosis of Malignant Nodules in Participants of Lung Cancer Screening Studies.Biomolecules · 2023Article
- Article
- See Lung Cancer with an AI.Cancers · 2023Review
- Radiomics in Oncology III.Diagnostics (Basel, Switzerland) · 2023Article
- A Comprehensive Study on the Correlation of Treatment, Diagnosis and Epidemiology of Tuberculosis and Lung Cancer.Tanaffos · 2023Review
- Preoperative computed tomography-based tumoral radiomic features prediction for overall survival in resectable non-small cell lung cancer.Frontiers in oncology · 2023Article
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Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In many low-income countries, the poor availability of lung biopsy leads to delayed diagnosis of lung cancer (LC), which can appear radiologically similar to tuberculosis (TB). To assess the ability of CT Radiomics in differentiating between TB and LC, and to evaluate the potential predictive role of clinical parameters, from March 2020 to September 2021, patients with histological diagnosis of TB or LC underwent chest CT evaluation and were retrospectively enrolled. Exclusion criteria were: availability of only enhanced CT scans, previous lung surgery and significant CT motion artefacts. After manual 3D segmentation of enhanced CT, two radiologists, in consensus, extracted and compared radiomics features (T-test or Mann−Whitney), and they tested their performance, in differentiating LC from TB, via Receiver operating characteristic (ROC) curves. Forty patients (28 LC and 12 TB) were finally enrolled, and 31 were male, with a mean age of 59 ± 13 years. Significant differences were found in normal WBC count (p < 0.019) and age (p < 0.001), in favor of the LC group (89% vs. 58%) and with an older population in LC group, respectively. Significant differences were found in 16/107 radiomic features (all p < 0.05). LargeDependenceEmphasis and LargeAreaLowGrayLevelEmphasis showed the best performance in discriminating LC from TB, (AUC: 0.92, sensitivity: 85.7%, specificity: 91.7%, p < 0.0001; AUC: 0.92, sensitivity: 75%, specificity: 100%, p < 0.0001, respectively). Radiomics may be a non-invasive imaging tool in many poor nations, for differentiating LC from TB, with a pivotal role in improving oncological patients’ management; however, future prospective studies will be necessary to validate these initial findings.
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