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activities:theme1:projects:iofi [2015/12/21 14:59]
janin
activities:theme1:projects:iofi [2021/01/15 10:16] (current)
ahuaulme
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 ===== General purpose ===== ===== General purpose =====
  
-Survival prognosis from low grade glioma (LGG) is increased when the maximum tumoral tissue has been removed, slowing down evolution into high grade glioma (HGG), which is much more agressive (14 months mean survival rate). Intraoperative Positron Surface Imaging (PSI) has been suggested recently in neurosurgery to help the surgeon in detecting precise tumor margins. Originally designed in the mamography context by Pr. Dr. Nassir Navab (Munich, ​Allemagne), this method relies on scanning the resection cavity with a tracked freehand beta probe. In conjunction with a [18F]-based radiotracer,​ such system generates reconstructed surface images of the brain resection cavity. By introducing intraoperative freehand functional images in the operating room (OR), the resection gesture of the surgeon will be enhanced, driving to a better patient outcome. ​+Survival prognosis from low grade glioma (LGG) is increased when the maximum tumoral tissue has been removed, slowing down evolution into high grade glioma (HGG), which is much more agressive (14 months mean survival rate). Intraoperative Positron Surface Imaging (PSI) has been suggested recently in neurosurgery to help the surgeon in detecting precise tumor margins. Originally designed in the mamography context by Pr. Dr. Nassir Navab (Munich, ​Germany), this method relies on scanning the resection cavity with a tracked freehand beta probe. In conjunction with a [18F]-based radiotracer,​ such system generates reconstructed surface images of the brain resection cavity. By introducing intraoperative freehand functional images in the operating room (OR), the resection gesture of the surgeon will be enhanced, driving to a better patient outcome. ​
  
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 ===== Description ===== ===== Description =====
  
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 In addition, our project aims to developp new acquisition models for PSI systems, dedicated to brain tumor surgery. From previous validation studies, reconstructions generated with detection models gave good performances in term of residual tumor detection, at the trade of high computation time (about 30 mn without GPU improvement). In the OR, the required computation time to generate images should be low to not interrup (that much) the surgical workflow. Thus, we proposed a new acquisition model more suitable for intraoperative usage. Our model gives lower computation time and better performances than the off the shelf original model. \\  In addition, our project aims to developp new acquisition models for PSI systems, dedicated to brain tumor surgery. From previous validation studies, reconstructions generated with detection models gave good performances in term of residual tumor detection, at the trade of high computation time (about 30 mn without GPU improvement). In the OR, the required computation time to generate images should be low to not interrup (that much) the surgical workflow. Thus, we proposed a new acquisition model more suitable for intraoperative usage. Our model gives lower computation time and better performances than the off the shelf original model. \\ 
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 In this project, international collaborations and knowledge have been involved. On the one hand, CAMP team from the Technische Universitat Munchen gave us the opportunity to work on their PSI system and understand its behavior, while MediCIS team brings it skills in image guided neurosurgery. With this collaboration,​ acquisition on phantom and software engineering have been performed. On the second hand, a collaboration with a laboratory of the Harvard Medical Scool has been started. A validation framework has been developped in association with a neurosurgeon in Brigham and Women'​s Hospital in Boston, for future clinical validation, finalizing our feasibility study. ​ In this project, international collaborations and knowledge have been involved. On the one hand, CAMP team from the Technische Universitat Munchen gave us the opportunity to work on their PSI system and understand its behavior, while MediCIS team brings it skills in image guided neurosurgery. With this collaboration,​ acquisition on phantom and software engineering have been performed. On the second hand, a collaboration with a laboratory of the Harvard Medical Scool has been started. A validation framework has been developped in association with a neurosurgeon in Brigham and Women'​s Hospital in Boston, for future clinical validation, finalizing our feasibility study. ​
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