The Simpson Grade was introduced in the era of limited resources, outdated techniques, and rudimentary surgical and imaging technologies. With the advent of modern techniques including pre- and post-operative imaging, microsurgical and endoscopic techniques, advanced histopathology and molecular analysis and adjuvant radiotherapy, the utility of the Simpson Grade scale for prognostication of recurrence after meningioma resection has become less useful. While the extent of resection remains an important factor in reducing recurrence, a subjective naked-eye criteria to Grade extent of resection cannot be generalized to all meningiomas regardless of their location or biology. Achieving the highest Simpson Grade resection should not always be the goal of surgery. It is prudent to take advantage of all the tools in the neurosurgeons' armamentarium to aim for maximal safe resection of meningiomas. The primary goal of this study was to review the literature highlighting the Simpson Grade and its association with recurrence in modern meningioma practice. A PubMed search was conducted using terms "Simpson", "Grade", "meningioma", "recurrence", "gross total resection", "extent of resection" "human". A separate search using the terms "intraoperative imaging", "intraoperative MRI" and "meningioma" were conducted. All studies reporting prognostic value of Simpson Grades were retrospective in nature. Simpson Grade I, II and III can be defined as gross total resection and were associated with lower recurrence compared to Simpson Grade IV or subtotal resection. The volume of residual tumor, a factor not considered in the Simpson Grade, is also a useful predictor of recurrence. Subtotal resection followed by stereotactic radiosurgery has similar recurrence-free survival as gross total resection. In current modern meningioma surgery, the Simpson Grade is no longer relevant and should be replaced with a grading scale that relies on post-operative MRI imaging that assess GTR versus STR and then divides STR into > or <4-5 cm3, in combination with modern molecular-based techniques for recurrence risk stratification.
