ABSTRACT
In this report, we present a 53-year-old woman with primary mast cell sarcoma of the thoracic spine vertebrae. Mast cell sarcoma is an aggressive and rare cancer. To date, no cases of primary mast cell sarcoma have been reported in the spinal vertebrae. The patient initially presented with a 1-month history of pelvic and abdominal pain. Inconclusive gynecological evaluation resulted in a CT of the abdomen and pelvis, demonstrating a destructive lesion centered at the 11th thoracic vertebral body. The patient underwent a two-stage spine operation for T11 corpectomy and T7-L3 posterior spinal fusion. Histopathological, immunohistochemical, and flow cytometry studies of the resection specimens showed the tumor to be mostly composed of CD117-positive and mast cell tryptase-positive cells with features consistent with mast cell sarcoma. This is the first reported case of primary vertebral mast cell sarcoma, which may mimic other destructive lesions of the spine including osteomyelitis, vertebral tuberculosis, or plasmacytoma.â©.
Subject(s)
Mast-Cell Sarcoma/pathology , Mast-Cell Sarcoma/surgery , Spinal Neoplasms/surgery , Thoracic Vertebrae/surgery , Female , Humans , Mast-Cell Sarcoma/diagnosis , Middle Aged , Neurosurgical Procedures/methods , Spinal Neoplasms/pathology , Thoracic Vertebrae/pathology , Treatment OutcomeABSTRACT
Neurocritical care involves the care of highly complex patients with combinations of physiologic derangements in the brain and in extracranial organs. The level of evidence underpinning treatment recommendations remains low due to a multitude of reasons including an incomplete understanding of the involved physiology; lack of good quality, prospective, standardized data; and the limited success of conventional randomized controlled trials. Comparative effectiveness research can provide alternative perspectives and methods to enhance knowledge and evidence within the field of neurocritical care; these include large international collaborations for generation and maintenance of high quality data, statistical methods that incorporate heterogeneity and individualize outcome prediction, and finally advanced bioinformatics that integrate large amounts of variable-source data into patient-specific phenotypes and trajectories.
