Emerging Imaging and Operative Techniques for Glioma Surgery
Bibliographic record
Abstract
Malignant gliomas are the most common adult primary brain cancers and are amongst the most devastating of human malignancies. These cancers are characterized by high proliferation and invasion into normal brain. Treatment consists of a combination of surgery, radiotherapy, and chemotherapy. Despite years of experience and refinement of these treatments, patients suffering from World Health Organization grade four gliomas have a mean survival of 14 months The goal of surgery is to remove the entirety of the tumor as strong emerging evidence suggests that completeness of resection improves cancer control and lengthens survival. Extent of resection, for malignant gliomas, is based on gadolinium-enhanced magnetic resonance imaging (MRI). In cases of complete resection, radiotherapy is then delivered to a 2 cm border along the resection cavity. In cases of incomplete resection, radiotherapy is delivered to the residual tumor and a 2 cm border along the residual tumor and resection cavity. The rational for this radiotherapy strategy is that invasive cancer cells can be found up to 2 cm distant from the main tumor mass. Studies examining the location of malignant glioma recurrence following surgery and adjuvant radiotherapy and chemotherapy have found that most cancers recur within a 1 cm border along the surgical resection cavity, even in cases in which no residual gadoliniumenhancing tumor was evident on immediate post-operative MRI. This suggests that gadolinium-enhanced MRI does not sufficiently reveal the entire tumor resulting in residual tumor post-operatively. Other common MRI sequences, including FLAIR and T2, do not adequately distinguish non-gadolinium enhancing cancer cells from peritumoral edema. The inability to accurately visualize the whole tumor, including invasive cells, on imaging decreases the likelihood of complete resection. Recently, attempts to visualize malignant gliomas with newer imaging techniques, including metabolic labeled positron emission tomography (PET), have identified tumor borders beyond those seen with gadoliniumenhanced MRI. These technologies may have profound implications regarding surgical planning in malignant glioma surgery. Historically, extent of tumor resection has been determined by the surgeon's qualitative assessment at the time of operation, often reporting a gross total resection. More recently, the use of immediate post-operative MRI has revealed that complete resection of the gadolinium-enhancing portion of the tumor is achieved at a much lower rate. This overestimation by surgeons is, in part, owing to the difficulty distinguishing cancer cells www.intechopen.com Advances in Cancer Management 140 from normal brain. Since malignant gliomas are highly invasive tumors, the margin between tumor and normal brain is typically not obvious. Reluctant to cause an irreversible neurological deficit, surgeons will error on the side of caution. The downside is that malignant cancer cells will remain. Since adjuvant radiation and chemotherapies are only modestly effective Intraoperative tools designed to help surgeons distinguish cancer cells from normal brain include ultrasound and fluorescence guided surgical resection. Comparative studies using these tools have shown higher rates of complete resection compared to standard operating techniques. Here we review current and emerging imaging technologies designed to better visualize the tumor on preoperative imaging. We also review developing surgical technologies to help surgeons distinguish cancer cells from normal brain intraoperatively. The development of these technologies will lead to an increased rate of complete resection and thus improved cancer control.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".