Based on the increased glucose metabolism of malignant tissue, positron emission tomography (PET), using the radiolabeled glucose analog 18F-fluorodeoxyglucose (FDG), allows identification of breast cancer. Based on the criteria implemented in image interpretation, sensitivity of PET imaging ranged from 68% to 94% with a specificity between 84% and 97%. However, sensitivity for small tumors (< 1 cm) was found to be low. PET demonstrates tumor involvement of regional lymph nodes with high accuracy, predominantly in patients with advanced breast cancer. The sensitivity for the detection of axillary lymph node metastases was 79%, increasing to 94% in patients with primary breast tumors larger than 2 cm in diameter. Corresponding specificities were 96 and 100%, respectively. Lymph node metastases could not be identified in four of six patients with small primary breast cancers (stage pT1), resulting in a sensitivity of only 33% in these patients. By visualizing primary tumors and metastases in one imaging procedure, PET imaging may allow the effective staging of breast cancer patients. Response to treatment may be assessed at an earlier point than with imaging techniques currently used. Therefore, indications for PET studies in the future may be the evaluation of loco-regional lymph nodes, whole-body staging, diagnosis of local recurrence and therapy monitoring.
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http://dx.doi.org/10.1007/s001170050276 | DOI Listing |
Iran J Parasitol
January 2024
Department of Veterinary Medicine, College of Veterinary Science, Assam, India.
A 2-year-old female Assam Hill goat was presented with a clinical history of anorexia, fever, mild anemia, rough body coat, dehydration, tachycardia, dyspnea and swelling of palpable lymph nodes. Hematology revealed low hemoglobin, packed cell volume, red blood cell and thrombocyte count. Biochemical analysis showed increased serum concentration of alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine and urea in comparison to the normal reference range.
View Article and Find Full Text PDFFront Oncol
December 2024
Department of Urology, Second Affiliated Hospital of Nanchang University, Nanchang, China.
Background And Purpose: Distant metastasis in bladder cancer is linked to poor prognosis and significant mortality. Machine learning (ML), a key area of artificial intelligence, has shown promise in the diagnosis, staging, and treatment of bladder cancer. This study aimed to employ various ML techniques to predict distant metastasis in patients with bladder cancer.
View Article and Find Full Text PDFFront Oncol
December 2024
Department of Thoracic Surgery, Shaoxing People's Hospital, Shaoxing, Zhejiang, China.
Background: Extramedullary hemopoiesis (EMH) is a rare condition characterized by abnormal blood cell production outside the bone marrow, commonly occurring in the liver, spleen, lymph nodes, and less frequently in the mediastinum.
Case Presentation: This case involves a 68-year-old male patient who was found to have a posterior mediastinal mass upon examination. A surgical biopsy was performed, and pathological examination confirmed it to be extramedullary hemopoiesis (EMH).
Front Immunol
December 2024
Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
Objective: To explore the value of combined radiomics and deep learning models using different machine learning algorithms based on mammography (MG) and magnetic resonance imaging (MRI) for predicting axillary lymph node metastasis (ALNM) in breast cancer (BC). The objective is to provide guidance for developing scientifically individualized treatment plans, assessing prognosis, and planning preoperative interventions.
Methods: A retrospective analysis was conducted on clinical and imaging data from 270 patients with BC confirmed by surgical pathology at the Third Hospital of Shanxi Medical University between November 2022 and April 2024.
J Cytol
November 2024
Department of Pathology, Tinsukia Medical College Hospital, Tinsukia, Assam, India.
Background: Fine-needle aspiration cytology (FNAC) of the lymph nodes is the first-line evaluation of lymphadenopathy of unknown etiology. For better diagnostic clarity and proper communication to clinicians, the Sydney System was proposed in 2020 for the performance, classification, and reporting of lymph node cytopathology. The present study was conducted to analyze the diagnostic performance and risk of malignancy (ROM) associated with each of the diagnostic categories of the proposed Sydney System.
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