Navigated 3D-ultrasound power Doppler and visualization of lenticulostriate arteries during resections of insular gliomas
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Challenges with segmenting intraoperative ultrasound for brain tumours
Objective - Addressing the challenges that come with identifying and delineating brain tumours in intraoperative ultrasound. Our goal is to both qualitatively and quantitatively assess the interobserver variation, amongst experienced neuro-oncological intraoperative ultrasound users (neurosurgeons and neuroradiologists), in detecting and segmenting brain tumours on ultrasound. We then propose that, due to the inherent challenges of this task, annotation by localisation of the entire tumour mass with a bounding box could serve as an ancillary solution to segmentation for clinical training, encompassing margin uncertainty and the curation of large datasets. Methods - 30 ultrasound images of brain lesions in 30 patients were annotated by 4 annotators - 1 neuroradiologist and 3 neurosurgeons. The annotation variation of the 3 neurosurgeons was first measured, and then the annotations of each neurosurgeon were individually compared to the neuroradiologist’s, which served as a reference standard as their segmentations were further refined by cross-reference to the preoperative magnetic resonance imaging (MRI). The following statistical metrics were used: Intersection Over Union (IoU), Sørensen-Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD). These annotations were then converted into bounding boxes for the same evaluation. Results - There was a moderate level of interobserver variance between the neurosurgeons $$[IoU:0.789, \ DSC:0.876, \ HD:103.227]$$ [ I o U : 0.789 , D S C : 0.876 , H D : 103.227 ] and a larger level of variance when compared against the MRI-informed reference standard annotations by the neuroradiologist, mean across annotators $$[IoU:0.723, \ DSC:0.813, \ HD:115.675]$$ [ I o U : 0.723 , D S C : 0.813 , H D : 115.675 ] . After converting the segments to bounding boxes, all metrics improve, most significantly, the interquartile range drops by $$[IoU:37\%, \ DSC:41\%, \ HD:54\%]$$ [ I o U : 37 % , D S C : 41 % , H D : 54 % ] . Conclusion - This study highlights the current challenges with detecting and defining tumour boundaries in neuro-oncological intraoperative brain ultrasound. We then show that bounding box annotation could serve as a useful complementary approach for both clinical and technical reasons.
Challenges with segmenting intraoperative ultrasound for brain tumours
Objective - Addressing the challenges that come with identifying and delineating brain tumours in intraoperative ultrasound. Our goal is to both qualitatively and quantitatively assess the interobserver variation, amongst experienced neuro-oncological intraoperative ultrasound users (neurosurgeons and neuroradiologists), in detecting and segmenting brain tumours on ultrasound. We then propose that, due to the inherent challenges of this task, annotation by localisation of the entire tumour mass with a bounding box could serve as an ancillary solution to segmentation for clinical training, encompassing margin uncertainty and the curation of large datasets. Methods - 30 ultrasound images of brain lesions in 30 patients were annotated by 4 annotators - 1 neuroradiologist and 3 neurosurgeons. The annotation variation of the 3 neurosurgeons was first measured, and then the annotations of each neurosurgeon were individually compared to the neuroradiologist’s, which served as a reference standard as their segmentations were further refined by cross-reference to the preoperative magnetic resonance imaging (MRI). The following statistical metrics were used: Intersection Over Union (IoU), Sørensen-Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD). These annotations were then converted into bounding boxes for the same evaluation. Results - There was a moderate level of interobserver variance between the neurosurgeons $$[IoU:0.789, \ DSC:0.876, \ HD:103.227]$$ [ I o U : 0.789 , D S C : 0.876 , H D : 103.227 ] and a larger level of variance when compared against the MRI-informed reference standard annotations by the neuroradiologist, mean across annotators $$[IoU:0.723, \ DSC:0.813, \ HD:115.675]$$ [ I o U : 0.723 , D S C : 0.813 , H D : 115.675 ] . After converting the segments to bounding boxes, all metrics improve, most significantly, the interquartile range drops by $$[IoU:37\%, \ DSC:41\%, \ HD:54\%]$$ [ I o U : 37 % , D S C : 41 % , H D : 54 % ] . Conclusion - This study highlights the current challenges with detecting and defining tumour boundaries in neuro-oncological intraoperative brain ultrasound. We then show that bounding box annotation could serve as a useful complementary approach for both clinical and technical reasons.
Intraoperative visualization of cerebral aneurysms using navigated 3D-ultrasound power-Doppler angiography
Background The questions of whether the spatial resolution of navigated 3D-ultrasound (3D-US) power-Doppler angiography imaging rendered by existing 3D-US systems is sufficient for the intraoperative visualization of cerebral aneurysms, and in what percentage of cases, are largely unanswered. A study on this topic is lacking in the literature. Methods From 2015 to 2022, we performed 86 surgeries on 83 aneurysm patients. Navigated 3D-US was used at the discretion of the operating neurosurgeons when available (i.e., not being used during parallel tumor surgeries). Twenty-five aneurysms (15 ruptured) were operated on using 3D-US; 22 aneurysms were located at the middle cerebral artery (MCA). Patient 3D-US power-Doppler angiography images and surgical reports were retrospectively reviewed to assess the intraoperative ultrasound visibility of aneurysms. Results In 20 patients (80%) the aneurysms were successfully visualized. In five patients (20%), the aneurysms visualization was insufficient or absent. Nineteen of 22 aneurysms (86.4%) were visualized in the MCA aneurysm subgroup. We observed no association between aneurysm visibility and aneurysm size or the presence of subarachnoid hemorrhage. In the subgroup of MCA aneurysms, no association between aneurysm visibility and the presence of subarachnoid hemorrhage was found; a trend toward poor sonographic visibility of smaller aneurysms was observed (p = 0.09). Conclusions Our initial data show that intraoperative 3D-US power-Doppler angiography, rendered by current navigated 3D-US systems, clearly depicts the majority of aneurysms in the MCA aneurysm subgroup. However, future prospective studies performed on a higher number of aneurysms localized at various anatomic sites are needed to confirm our initial findings and determine their potential clinical relevance.
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