Current Applications of Diffusion Tensor Imaging and Tractography in Intracranial Tumor Resection

In the treatment of brain tumors, surgical intervention remains a common and effective therapeutic option. Recent advances in neuroimaging have provided neurosurgeons with new tools to overcome the challenge of differentiating healthy tissue from tumor-infiltrated tissue, with the aim of increasing the likelihood of maximizing the extent of resection volume while minimizing injury to functionally important regions. Novel applications of diffusion tensor imaging (DTI), and DTI-derived tractography (DDT) have demonstrated that preoperative, non-invasive mapping of eloquent cortical regions and functionally relevant white matter tracts (WMT) is critical during surgical planning to reduce postoperative deficits, which can decrease quality of life and overall survival. In this review, we summarize the latest developments of applying DTI and tractography in the context of resective surgery and highlight its utility within each stage of the neurosurgical workflow: preoperative planning and intraoperative management to improve postoperative outcomes

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

MRI Findings of Causalgia of the Lower Extremity Following Transsphenoidal Resection of Pituitary Tumor

Background. Causalgia is continuing pain, allodynia, or hyperalgesia after nerve injury with edema, changes in skin blood flow, or abnormal sudomotor activity. Here we report a case of lower extremity causalgia following elective transsphenoidal resection of a pituitary tumor in a young man. Clinical Presentation. A 33-year-old man with acromegaly underwent elective sublabial transsphenoidal resection of his pituitary tumor. During the three-hour surgery, the lower limbs were kept in a supine, neutral position with a pillow under the knees. The right thigh was slightly internally rotated with a tape to expose fascia lata, which was harvested to repair the sella. Postoperatively, he developed causalgia in a distal sciatic and common peroneal nerve distribution. Pain was refractory to several interventions. Finally, phenoxybenzamine improved his pain significantly. Conclusions. Malpositioning in the operating room resulted in causalgia in this young man. Phenoxybenzamine improved, and ultimately resolved, his symptoms. Improvement in his pain symptoms correlated with resolution of imaging changes in the distal sciatic and peroneal nerves on the side of injury

Biopsy Confirmed Glioma Recurrence Predicted by Multi-Modal Neuroimaging Metrics

Histopathological verification is currently required to differentiate tumor recurrence from treatment effects related to adjuvant therapy in patients with glioma. To bypass the complications associated with collecting neural tissue samples, non-invasive classification methods are needed to alleviate the burden on patients while providing vital information to clinicians. However, uncertainty remains as to which tissue features on magnetic resonance imaging (MRI) are useful. The primary objective of this study was to quantitatively assess the reliability of combining MRI and diffusion tensor imaging metrics to discriminate between tumor recurrence and treatment effects in histopathologically identified biopsy samples. Additionally, this study investigates the noise adjuvant radiation therapy introduces when discriminating between tissue types. In a sample of 41 biopsy specimens, from a total of 10 patients, we derived region-of-interest samples from MRI data in the ipsilateral hemisphere that encompassed biopsies obtained during resective surgery. This study compares normalized intensity values across histopathology classifications and contralesional volumes reflected across the midline. Radiation makes noninvasive differentiation of abnormal-nontumor tissue to tumor recurrence much more difficult. This is because radiation exhibits opposing behavior on key MRI modalities: specifically, on post-contrast T1, FLAIR, and GFA. While radiation makes noninvasive differentiation of tumor recurrence more difficult, using a novel analysis of combined MRI metrics combined with clinical annotation and histopathological correlation, we observed that it is possible to successfully differentiate tumor tissue from other tissue types. Additional work will be required to expand upon these findings

Neuroendoscopic Resection of Intraventricular Tumors and Cysts through a Working Channel with a Variable Aspiration Tissue Resector: A Feasibility and Safety Study

Pure neuroendoscopic resection of intraventricular lesions through a burr hole is limited by the instrumentation that can be used with a working channel endoscope. We describe a safety and feasibility study of a variable aspiration tissue resector, for the resection of a variety of intraventricular lesions. Our initial experience using the variable aspiration tissue resector involved 16 patients with a variety of intraventricular tumors or cysts. Nine patients (56%) presented with obstructive hydrocephalus. Patient ages ranged from 20 to 88 years (mean 44.2). All patients were operated on through a frontal burr hole, using a working channel endoscope. A total of 4 tumors were resected in a gross total fashion and the remaining intraventricular lesions were subtotally resected. Fifteen of 16 patients had relief of their preoperative symptoms. The 9 patients who presented with obstructive hydrocephalus had restoration of cerebrospinal fluid flow though one required a ventriculoperitoneal shunt. Three patients required repeat endoscopic resections. Use of a variable aspiration tissue resector provides the ability to resect a variety of intraventricular lesions in a safe, controlled manner through a working channel endoscope. Larger intraventricular tumors continue to pose a challenge for complete removal of intraventricular lesions