Neurosurgery
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Deep neural networks (DNNs) have not been proven to detect blood loss (BL) or predict surgeon performance from video. ⋯ BL and task outcome classification are important components of an automated assessment of surgical performance. DNNs can predict BL and outcome of hemorrhage control from video alone; their performance is improved with surgical instrument presence data. The generalizability of DNNs trained on hemorrhage control tasks should be investigated.
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Radiation necrosis (RN) after stereotactic radiosurgery (SRS) for brain metastases (BM) can result in significant morbidity, compounded by the effects of extended steroid therapy. Laser interstitial thermal therapy (LITT) is a minimally invasive procedure that can offer definitive treatment for RN while potentially obviating the need for prolonged steroid use. ⋯ These data suggest that LITT for treatment of biopsy-proven RN after SRS for BM significantly decreases time to steroid independence. Prospective trials should be designed to further validate the utility of LITT for RN and its impact on steroid-induced morbidity.
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Multicenter Study
Rapid Automated Analysis of Skull Base Tumor Specimens Using Intraoperative Optical Imaging and Artificial Intelligence.
Accurate specimen analysis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative specimen interpretation can be challenging because of the wide range of skull base pathologies and lack of intraoperative pathology resources. ⋯ SRH with trained artificial intelligence models can provide rapid and accurate intraoperative analysis of skull base tumor specimens to inform surgical decision-making.
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When evaluating children with mild traumatic brain injuries (mTBIs) and intracranial injuries (ICIs), neurosurgeons intuitively consider injury size. However, the extent to which such measures (eg, hematoma size) improve risk prediction compared with the kids intracranial injury decision support tool for traumatic brain injury (KIIDS-TBI) model, which only includes the presence/absence of imaging findings, remains unknown. ⋯ Although measures of ICI size have clear intuitive value, the tradeoff between higher specificity and lower sensitivity does not support the addition of such information to the KIIDS-TBI model.