TY - GEN
T1 - Developing a computer-aided image analysis and visualization tool to predict region-specific brain tissue "at risk" for developing acute ischemic stroke
AU - Danala, Gopichandh
AU - Heidari, Morteza
AU - Aghaei, Faranak
AU - Ray, Bappaditya
AU - Zheng, Bin
N1 - Funding Information:
This work is supported in part by Grant R01-CA197150 from the National Cancer Institute, National Institutes of Health, USA. The authors also acknowledge the support of TSET Cancer Center Program, Oklahoma Tobacco Settlement Endowment Trust, Peggy, and Charles Stephenson Cancer Center, the University of Oklahoma.
Publisher Copyright:
© 2019 SPIE.
PY - 2019
Y1 - 2019
N2 - Advent of advanced imaging technology and better neuro-interventional equipment have resulted in timely diagnosis and effective treatment for acute ischemic stroke (AIS) due to large vessel occlusion (LVO). However, objective clinicoradiologic correlate to identify appropriate candidates and their respective clinical outcome is largely unknown. The purpose of the study is to develop and test a new computer-aided detection algorithm to quantify region-specific AIS and "at risk" brain volumes prior to thrombectomy using CT perfusion imaging protocol. Fourteen patients with LVO related AIS and assessed radiologically for their eligibility to undergo mechanical thrombectomy was retrospectively analyzed for the study. First, the scheme automatically categorizes images into multiple series of scans acquired from a section of brain. Each image in series is labeled to a specified brain location. Next, image segmentation is performed to separate brain region from skull. The brain is then split into left and right hemispheres, followed by detecting amount of blood in each hemisphere. Last, comparison between amount of blood in each hemisphere over the series of scans is made to observe the wash-in and wash-out rate of blood to assess the extent of already damaged and "at risk" brain tissue. By integrating the scheme into a user graphic interface, the study builds a unique image feature analysis and visualization tool to observe and quantify the delayed or reduced blood flow (brain "at risk" to develop AIS) in the corresponding hemisphere, which has potential to assist radiologists to quickly visualize and more accurately assess the extent of AIS.
AB - Advent of advanced imaging technology and better neuro-interventional equipment have resulted in timely diagnosis and effective treatment for acute ischemic stroke (AIS) due to large vessel occlusion (LVO). However, objective clinicoradiologic correlate to identify appropriate candidates and their respective clinical outcome is largely unknown. The purpose of the study is to develop and test a new computer-aided detection algorithm to quantify region-specific AIS and "at risk" brain volumes prior to thrombectomy using CT perfusion imaging protocol. Fourteen patients with LVO related AIS and assessed radiologically for their eligibility to undergo mechanical thrombectomy was retrospectively analyzed for the study. First, the scheme automatically categorizes images into multiple series of scans acquired from a section of brain. Each image in series is labeled to a specified brain location. Next, image segmentation is performed to separate brain region from skull. The brain is then split into left and right hemispheres, followed by detecting amount of blood in each hemisphere. Last, comparison between amount of blood in each hemisphere over the series of scans is made to observe the wash-in and wash-out rate of blood to assess the extent of already damaged and "at risk" brain tissue. By integrating the scheme into a user graphic interface, the study builds a unique image feature analysis and visualization tool to observe and quantify the delayed or reduced blood flow (brain "at risk" to develop AIS) in the corresponding hemisphere, which has potential to assist radiologists to quickly visualize and more accurately assess the extent of AIS.
KW - Acute ischemic stroke (AIS)
KW - and mechanical thrombectomy
KW - computer-aided detection (CAD)
KW - large vessel occlusion (LVO)
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U2 - 10.1117/12.2512850
DO - 10.1117/12.2512850
M3 - Conference contribution
AN - SCOPUS:85068366615
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2019
A2 - Gimi, Barjor
A2 - Krol, Andrzej
PB - SPIE
T2 - Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging
Y2 - 19 February 2019 through 21 February 2019
ER -