Purpose: To describe expected imaging features on chest computed tomography (CT) after percutaneous radiofrequency ablation (RFA) of lung tumors, and their frequency over time after the procedure.
Methods: In this double-center retrospective study, we reviewed CT scans from patients who underwent RFA for primary or secondary lung tumors. Patients with partial ablation or tumor recurrence during the imaging follow-up were not included. The imaging features were assessed in pre-defined time points: immediate post-procedure, ≤4 weeks, 5-24 weeks, 25-52 weeks and ≥52 weeks. Late follow-up (3 and 5 years after procedure) was assessed clinically in 48 patients.
Results: The study population consisted of 69 patients and 144 pulmonary tumors. Six out of 69 (9%) patients had primary lung nodules (stage I) and 63/69 (91 %) had metastatic pulmonary nodules. In a patient-level analysis, immediately after lung RFA, the most common CT features were ground glass opacities (66/69, 96 %), consolidation (56/69, 81 %), and hyperdensity within the nodule (47/69, 68 %). Less than 4 weeks, ground glass opacities (including reversed halo sign) was demonstrated in 20/22 (91 %) patients, while consolidation and pleural thickening were detected in 17/22 patients (77 %). Cavitation, pneumatocele, pneumothorax and pleural effusions were less common features. From 5 weeks onwards, the most common imaging features were parenchymal bands.
Conclusions: Our study demonstrated the expected CT features after lung RFA, a safe and effective minimally invasive treatment for selected patients with primary and secondary lung tumors. Diagnostic and interventional radiologists should be familiar with the expected imaging features immediately after RFA and their change over time in order to avoid misinterpretation and inadequate treatments.
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http://dx.doi.org/10.1016/j.ejro.2020.100276 | DOI Listing |
BMC Med Inform Decis Mak
January 2025
Department of Digital Systems, University of Piraeus, Piraeus, Greece.
Vitiligo, alopecia areata, atopic, and stasis dermatitis are common skin conditions that pose diagnostic and assessment challenges. Skin image analysis is a promising noninvasive approach for objective and automated detection as well as quantitative assessment of skin diseases. This review provides a systematic literature search regarding the analysis of computer vision techniques applied to these benign skin conditions, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.
View Article and Find Full Text PDFBMC Infect Dis
January 2025
Department of Oncology, General Hospital of Western Theatre Command, No. 270, Tianhui Road, Rongdu Avenue, Jinniu District, Chengdu, Sichuan, 610000, People's Republic of China.
Background: Nocardia are widely present in nature and considered opportunistic pathogens. They can result in hematogenous spread infection through the ruptured skin or respiratory tract when the host's immune system is compromised. Currently, 119 species of Nocardia have been identified, with 54 capable of causing infections in humans.
View Article and Find Full Text PDFBMC Med Imaging
January 2025
Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Purpose: We used knowledge discovery from radiomics of T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (T1C) for assessing relapse risk in patients with high-grade meningiomas (HGMs).
Methods: 279 features were extracted from each ROI including 9 histogram features, 220 Gy-level co-occurrence matrix features, 20 Gy-level run-length matrix features, 5 auto-regressive model features, 20 wavelets transform features and 5 absolute gradient statistics features. The datasets were randomly divided into two groups, the training set (~ 70%) and the test set (~ 30%).
BMC Infect Dis
January 2025
Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia.
Background: Early diagnosis of syphilis is vital for its effective control. This study aimed to develop an Artificial Intelligence (AI) diagnostic model based on radiomics technology to distinguish early syphilis from other clinical skin lesions.
Methods: The study collected 260 images of skin lesions caused by various skin infections, including 115 syphilis and 145 other infection types.
BMC Med Imaging
January 2025
Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Problem: Breast cancer is a leading cause of death among women, and early detection is crucial for improving survival rates. The manual breast cancer diagnosis utilizes more time and is subjective. Also, the previous CAD models mostly depend on manmade visual details that are complex to generalize across ultrasound images utilizing distinct techniques.
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