Fully Automated Segmentation Algorithm for Perihematomal Edema Volumetry After Spontaneous Intracerebral Hemorrhage

Background: Perihematomal edema (PHE) is a promising marker of secondary injury in patients with spontaneous intracerebral hemorrhage (ICH). It can be challenging to accurately and rapidly quantify. The aims of this study are to derive and internally validate a fully automated segmentation algorithm for volumetric PHE analysis. Methods: Inpatient CT scans of 400 consecutive adults with spontaneous supratentorial ICH enrolled in the Intracerebral Hemorrhage Outcomes Project (2009-2018) were separated into training (n=360) and test (n=40) datasets. A fully automated algorithm was derived from manual segmentations in the training dataset using convolutional neural networks and its performance was compared to manual and semi-automated segmentation methods in the test dataset. Results: The mean volumetric Dice similarity coefficients for the fully automated algorithm were 0.838±0.294 and 0.843±0.293 with manual and semi-automated segmentations as reference standards, respectively. PHE volumes derived from fully automated vs. manual (R 2 =0.959;p<0.001), fully automated vs. semi-automated (R 2 =0.960;p<0.001) and semi-automated vs. manual (R 2 =0.961; p<0.001) methods had strong between group correlations. The fully automated algorithm (mean 18.0±1.8 seconds/scan) quantified PHE volumes at a significantly faster rate than manual (mean 316.4±168.8 seconds/scan; p<0.001) and semi-automated (mean 480.5±295.3 seconds/scan; p<0.001) methods. Conclusions: The fully automated algorithm accurately quantified PHE from CT scans of supratentorial ICH patients with high fidelity and greater efficiency compared with manual and semi-automated segmentation methods.

Download Full-text

Fully Automated Segmentation Algorithm for Hematoma Volumetric Analysis in Spontaneous Intracerebral Hemorrhage

Stroke ◽

10.1161/strokeaha.119.026561 ◽

2019 ◽

Vol 50 (12) ◽

pp. 3416-3423 ◽

Cited By ~ 4

Author(s):

Natasha Ironside ◽

Ching-Jen Chen ◽

Simukayi Mutasa ◽

Justin L. Sim ◽

Saurabh Marfatia ◽

...

Keyword(s):

Intracerebral Hemorrhage ◽

Volumetric Analysis ◽

Segmentation Algorithm ◽

Automated Segmentation ◽

Spontaneous Intracerebral Hemorrhage

Download Full-text

Abstract 78: Fully Automated Segmentation Algorithm for Hematoma Volumetric Analysis in Spontaneous Intracerebral Hemorrhage

Stroke ◽

10.1161/str.51.suppl_1.78 ◽

2020 ◽

Vol 51 (Suppl_1) ◽

Author(s):

Natasha Ironside ◽

Ching-Jen Chen ◽

Simukayi Mutasa ◽

Justin Sim ◽

David Roh ◽

...

Keyword(s):

Intracerebral Hemorrhage ◽

Volumetric Analysis ◽

Segmentation Algorithm ◽

Training Dataset ◽

Automated Segmentation ◽

Spontaneous Intracerebral Hemorrhage ◽

Similarity Coefficients ◽

Segmentation Methods ◽

Volume Measurements ◽

Similar Accuracy

Background and Purpose: Hematoma volume measurements influence prognosis and treatment decisions in patients with spontaneous intracerebral hemorrhage (ICH). The aims of this study are to derive and validate a fully automated segmentation algorithm for ICH volumetric analysis using deep learning methods. Methods: Inpatient computed tomography scans of 300 consecutive adults (age ≥18 years) with spontaneous, supratentorial ICH who were enrolled in the Intracerebral Hemorrhage Outcomes Project (2009-2018) were separated into training (n=260) and test (n=40) datasets. A fully automated segmentation algorithm was derived using convolutional neural networks (CNN), and it was trained on manual segmentations from the training dataset. The algorithm’s performance was assessed against manual and semi-automated segmentation methods in the test dataset. Results: The mean volumetric Dice similarity coefficients for the fully automated segmentation algorithm when tested against manual and semi-automated segmentation methods were 0.894±0.264 and 0.905±0.254, respectively. ICH volumes derived from fully automated vs. manual (R 2 =0.981;p<0.0001), fully automated vs. semi-automated (R 2 =0.978;p<0.0001), and semi-automated vs. manual (R 2 =0.990;p<0001) segmentation methods had strong between-group correlations. The fully automated segmentation algorithm (mean 12.0±2.7 seconds/scan) was significantly faster than both of the manual (mean 201.5±92.2 seconds/scan; p<0.001) and semi-automated (mean 288.58±160.3 seconds/scan; p<0.001) segmentation methods. Conclusions: The fully automated segmentation algorithm quantified hematoma volumes from CT scans of supratentorial ICH patients with similar accuracy and substantially greater efficiency compared with manual and semi-automated segmentation methods.

Download Full-text

Spreading depolarizations in patients with spontaneous intracerebral hemorrhage: Association with perihematomal edema progression

Journal of Cerebral Blood Flow & Metabolism ◽

10.1177/0271678x16651269 ◽

2016 ◽

Vol 37 (5) ◽

pp. 1871-1882 ◽

Cited By ~ 16

Author(s):

Raimund Helbok ◽

Alois Josef Schiefecker ◽

Christian Friberg ◽

Ronny Beer ◽

Mario Kofler ◽

...

Keyword(s):

Brain Injury ◽

Intracerebral Hemorrhage ◽

Electrode Placement ◽

Secondary Brain Injury ◽

Spontaneous Intracerebral Hemorrhage ◽

Strip Electrode ◽

Hematoma Evacuation ◽

Perihematomal Edema ◽

Pathophysiologic Mechanisms

Pathophysiologic mechanisms of secondary brain injury after intracerebral hemorrhage and in particular mechanisms of perihematomal-edema progression remain incompletely understood. Recently, the role of spreading depolarizations in secondary brain injury was established in ischemic stroke, subarachnoid hemorrhage and traumatic brain injury patients. Its role in intracerebral hemorrhage patients and in particular the association with perihematomal-edema is not known. A total of 27 comatose intracerebral hemorrhage patients in whom hematoma evacuation and subdural electrocorticography was performed were studied prospectively. Hematoma evacuation and subdural strip electrode placement was performed within the first 24 h in 18 patients (67%). Electrocorticography recordings started 3 h after surgery (IQR, 3–5 h) and lasted 157 h (median) per patient and 4876 h in all 27 patients. In 18 patients (67%), a total of 650 spreading depolarizations were observed. Spreading depolarizations were more common in the initial days with a peak incidence on day 2. Median electrocorticography depression time was longer than previously reported (14.7 min, IQR, 9–22 min). Postoperative perihematomal-edema progression (85% of patients) was significantly associated with occurrence of isolated and clustered spreading depolarizations. Monitoring of spreading depolarizations may help to better understand pathophysiologic mechanisms of secondary insults after intracerebral hemorrhage. Whether they may serve as target in the treatment of intracerebral hemorrhage deserves further research.

Download Full-text