Browsing by Subject "Monoclonal plasma cells"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    De Novo Plasmacytoma at the Site of Previous Anterior Cervical Fusion
    (Wolters Kluwer, 2023-12-07) Burket, Noah J.; Mobasser, Dillon C.; Alentado, Vincent J.; Mobasser, Jean-Pierre; Neurological Surgery, School of Medicine
    Background and importance: Solitary plasmacytoma of bone (SPB) is a rare tumor that forms from monoclonal plasma cells within bone. These tumors are typically found in patients in their fifth to sixth decade of life and often progress to multiple myeloma. Previous reports have noted the formation of these tumors at the site of previous procedures or trauma, yet none have reported the development of SPB at the same site of a previous spinal surgery. Clinical presentation: The authors report on a 47-year-old woman who developed a de novo plasmacytoma 6 years after anterior cervical discectomy and fusion at the surgical site. Conclusion: Although SPB is a rare tumor primarily seen in bone that has been unaffected by surgery, it should be included in the differential after finding a tumor at the site of a previous spine surgery. Furthermore, biopsy should be considered once a lesion is identified in the area of a previous spine surgery, as SPB may progress to multiple myeloma, resulting in worse outcomes.
  • Thumbnail Image
    Item
    High-throughput and high-accuracy diagnosis of multiple myeloma with multi-object detection
    (Optica Publishing Group, 2022-11-23) Mei, Liye; Shen, Hui; Yu, Yalan; Weng, Yueyun; Li, Xiaoxiao; Zahid, Kashif Rafiq; Huang, Jin; Wang, Du; Liu, Sheng; Zhou, Fuling; Lei, Cheng; Radiation Oncology, School of Medicine
    Multiple myeloma (MM) is a type of blood cancer where plasma cells abnormally multiply and crowd out regular blood cells in the bones. Automated analysis of bone marrow smear examination is considered promising to improve the performance and reduce the labor cost in MM diagnosis. To address the drawbacks in established methods, which mainly aim at identifying monoclonal plasma cells (monoclonal PCs) via binary classification, in this work, considering that monoclonal PCs is not the only basis in MM diagnosis, for the first we construct a multi-object detection model for MM diagnosis. The experimental results show that our model can handle the images at a throughput of 80 slides/s and identify six lineages of bone marrow cells with an average accuracy of 90.8%. This work makes a step further toward full-automatic and high-efficiency MM diagnosis.