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Background: Malignant pulmonary tumours in children are very rare; the majority are metastases. Nonspecific radiographic findings of these abnormalities are challenging and may delay the final diagnosis and treatment.
Case Report: A 10-year-old boy was admitted to our hospital because of the clinical and radiographic symptoms and signs of pneumonia with abscess formation in the left lower lobe. After initial improvement on antibiotic therapy, a significant deterioration of the patient's condition was observed, together with progression in radiographic examinations. The patient was treated surgically and transferred to the Haematology and Oncology Department with a final diagnosis of pulmonary metastasis of clear cell sarcoma.
Conclusions: Radiographic findings of metastatic diseases may mimic non-neoplastic pulmonary conditions. A lack of specific clinical symptoms and a confusing radiographic pattern in our patient with clear cell sarcoma lung metastasis caused serious diagnostic difficulties.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3389896 | PMC |
J Neurooncol
September 2025
Department of Neurosurgery, University of Michigan, Ann Arbor, MI, USA.
Purpose: Frailty measures are critical for predicting outcomes in metastatic spine disease (MSD) patients. This study aimed to evaluate frailty measures throughout the disease process.
Methods: This retrospective analysis measured frailty in MSD patients at multiple time points using a modified Metastatic Spinal Tumor Frailty Index (MSTFI).
Purpose: WU-KONG1B (ClinicalTrials.gov identifier: NCT03974022) is a multinational phase II, dose-randomized study to assess the antitumor efficacy of sunvozertinib in pretreated patients with advanced non-small cell lung cancer (NSCLC) with epidermal growth factor receptor () exon 20 insertion mutations (exon20ins).
Methods: Eligible patients with advanced-stage exon20ins NSCLC were randomly assigned by 1:1 ratio to receive sunvozertinib 200 mg or 300 mg once daily (200 and 300 mg-rand cohorts).
Cancer Pathog Ther
September 2025
Department of Medicine, Pakistan Institute of Medical Sciences, Islamabad, Islamabad Capital Territory, 44000, Pakistan.
Med Sci Monit
September 2025
Department of Radiology, Faculty of Medicine, Erzincan Binali Yildirim University, Erzincan, Turkey.
BACKGROUND This study used CT imaging analyzed with deep learning techniques to assess the diagnostic accuracy of lung metastasis detection in patients with breast cancer. The aim of the research was to create and verify a system for detecting malignant and metastatic lung lesions that uses YOLOv10 and transfer learning. MATERIAL AND METHODS From January 2023 to 2024, CT scans of 16 patients with breast cancer who had confirmed lung metastases were gathered retrospectively from Erzincan Mengücek Gazi Training and Research Hospital.
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