17 research outputs found

    Treatment of Endovascular Coil and Stent Migration Using the Merci Retriever: Report of Three Cases

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    Background. Coil and stent migration is a potentially catastrophic complication in endovascular neurosurgery, which may lead to cerebral thromboembolism. Techniques for removing migrated coil and stent are not well established. Methods and Results. We present three cases in which coil or stent migration occurred during endovascular embolization of a cerebral aneurysm. The Merci Retrievers were used successfully in all cases to remove the displaced foreign bodies. Technical details are described. Conclusion. The Merci Retriever device can be utilized successfully for removal of migrated coils and stents in endovascular neurosurgery

    Federated learning enables big data for rare cancer boundary detection.

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    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

    Author Correction: Federated learning enables big data for rare cancer boundary detection.

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    10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

    Federated Learning Enables Big Data for Rare Cancer Boundary Detection

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    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

    Predictors of Long-Term Survival in Patients With Glioblastoma Multiforme: Advancements From the Last Quarter Century

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    Over the last quarter century there has been significant progress toward identifying certain characteristics and patterns in GBM patients to predict survival times and outcomes. We sought to identify clinical predictors of survival in GBM patients from the past 24 years. We examined patient survival related to tumor locations, surgical treatment, postoperative course, radiotherapy, chemotherapy, patient age, GBM recurrence, imaging characteristics, serum, and molecular markers. We present predictors that may increase, decrease, or play no significant role in determining a GBM patient's long-term survival or affect the quality of life

    Prophylactic vertebral cement augmentation at the uppermost instrumented vertebra and rostral adjacent vertebra for the prevention of proximal junctional kyphosis and failure following long-segment fusion for adult spinal deformity

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    Proximal junctional kyphosis (PJK) and proximal junctional failure (PJF) are common problems after long-segment (>5 levels) thoracolumbar instrumented fusions in the treatment of adult spinal deformity (ASD). No specific surgical strategy has definitively been shown to lower the risk of PJK as the result of a multifactorial etiology. The study aimed to assess the incidence of PJK and PJF in patients treated with prophylactic polymethylmethacrylate (PMMA) cement augmentation at the uppermost instrumented vertebrae (UIV) and rostral adjacent vertebrae (UIV+1). This is a retrospective cohort-matched surgical case series at an academic institutional setting. Eighty-five adult patients over a 16-year enrollment period were identified with long-segment (>5 levels) posterior thoracolumbar instrumented fusions for ASD. Primary outcomes measures were PJK magnitude and PJF formation. Secondary outcomes measures were spinopelvic parameters, as well as global and regional sagittal alignment. The impact of adjunctive PMMA use in long-segment (≥5 levels) fusion for ASD was assessed in adult patients aged 18 and older. Patients were included with at least one of the following: lumbar scoliosis >20°, pelvic tilt >25°, sagittal vertical axis >5 cm, central sacral vertical line >2 cm, and thoracic kyphosis >60°. The frequency of PJF and the magnitude of PJK were measured radiographically preoperatively, postoperatively, and at maximum follow-up in controls (Group A) and PMMA at the UIV and UIV+1 (Group B). Eighty-five patients (64±11.1 years) with ASD were identified: 47 control patients (58±10.6) and 38 patients (71±6.8) treated with PMMA at the UIV and UIV+1. The mean follow-up was 27.9 and 24.2 months in Groups A and B, respectively (p=.10). Preoperative radiographic parameters were not significantly different, except the pelvic tilt which was greater in Group A (26.6° vs. 31.4°, p=.03). Postoperatively, the lumbopelvic mismatch was greater in Group B (14.6° vs. 7.9°, p=.037), whereas the magnitude of PJK was greater in controls (9.36° vs. 5.65°, p=.023). The incidence of PJK was 36% (n=17) and 23.7% (n=9) in Groups A and B, respectively (p=.020). The odds ratio of PJK with vertebroplasty was 0.548 (95% confidence interval=0.211 to 1.424). Proximal junctional kyphosis was observed in 6 (12.8%) controls only (p=.031). The UIV+1 angle, a measure of PJK, was significantly greater in controls (10.0° vs. 6.8°, p=.02). No difference in blood loss was observed. No complications were attributed to PMMA use. The use of prophylactic vertebral cement augmentation at the UIV and rostral adjacent vertebral segment at the time of deformity correction appears to be preventative in the development of proximal junctional kyphosis and failure

    A review of stereotactic radiosurgery practice in the management of skull base meningiomas

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    Gross total resection of skull base meningiomas poses a surgical challenge due to their proximity to neurovascular structures. Once the gold standard therapy for skull base meningiomas, microsurgery has been gradually replaced by or used in combination with stereotactic radiosurgery (SRS). This review surveys the safety and efficacy of SRS in the treatment of cranial base meningiomas including 36 articles from 1991 to 2010. SRS produces excellent tumor control with low morbidity rates compared with surgery alone for asymptomatic small skull base meningiomas, patients with risk factors precluding conventional surgery, and as adjuvant therapy for recurrent or residual lesions
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