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Final ID: DP18

Deep learning based CT volume and density measures are associated with infarct growth rate during interhospital transfer for endovascular treatment

Abstract Body: Introduction:
Ischemic core growth rate in patients with a large vessel occlusion varies during transfer from a primary stroke center (PSC) to a comprehensive stroke center (CSC) for thrombectomy. Patients at risk for a high growth rate may be optimal candidates for neuroprotective treatments. We determined if deep learning based CT lesion (DLCT) volume and density measures are associated with growth rate.
Methods:
Patients with CT and CTP at the PSC and CTP or DWI at the CSC were included from the prospective CRISP 2 study. Growth rate per hour (mL/h) was measured as the difference between the CTP core volume (relative cerebral blood flow <30%) at the PSC and CTP ischemic core or manually segmented DWI lesion volume at the CSC. We used a validated deep learning model to segment the ischemic lesion on non-contrast CT and determined lesion volume, density in the lesion, and relative hypodensity; the percentage difference with contralateral voxels. Additional clinical, CT angiography, and CTP measurements were considered as independent variables (Figure 1). Stepwise regression with combined forward/backward selection optimized for the Akaike Information Criterion was used to select variables. For each variable, we report adjusted regression slopes with 95% confidence interval (aB[95%CI]) for their association with growth rate. R2 and adjusted R2 are reported to reflect model performance.
Results:
We included 269 patients; 113(42%) women, median age was 71(IQR:60-80) years, 185(69%) had witnessed onset of stroke symptoms. The stepwise optimized regression model had an R2 of 0.44 (adjusted R2: 0.41). DLCT variables with significant associations with growth rate were volume (aB/10mL:3.2[95%CI:2.3; 4.1]), >20% relative hypodensity volume (aB/10mL:-8.5[-11.6; -5.3]), and density standard deviation in the lesion (aB/HU:2[0.8; 3.2]). Penumbra volume (aB/10mL:-0.5[-0.8; -0.2]) was associated with core growth rate, while ischemic core volume (aB/10mL:0.62[-0.03; 1.27]) was not. Tan collaterals score (aB per point:-4.7[-6.6; -2.9]), clot burden score (aB/point:-1.6[-2.1; -1.0]), female sex (aB:-3.2[-5.7; -0.7]), and admission systolic blood pressure (aB/10mmHg:0.7[0.3; 1.2]) were also significantly associated with core growth rate.
Conclusion:
DLCT based volume and density measures have a strong association with ischemic core growth rate during interhospital transfer which might indicate that DLCT also identifies tissue at risk for irreversible ischemic damage.
  • Van Voorst, Henk  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Mlynash, Michael  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Zaharchuk, Greg  ( Stanford School of Medicine , Palo Alto , California , United States )
  • Lansberg, Maarten  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Albers, Gregory  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Heit, Jeremy  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Liu, Yongkai  ( Stanford School of Medicine , Palo Alto , California , United States )
  • Zamarud, Aroosa  ( Stanford University , Palo Alto , California , United States )
  • Wouters, Anke  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Seners, Pierre  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Mahammedi, Abdelkader  ( Stanford School of Medicine , Palo alto , California , United States )
  • Verhaaren, Benjamin  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Christensen, Soren  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Yuen, Nicole  ( Stanford Stroke Center , Palo Alto , California , United States )
  • Author Disclosures:
    Henk van Voorst: DO have relevant financial relationships ; Research Funding (PI or named investigator):Dutch Scientific Council (NWO):Active (exists now) ; Research Funding (PI or named investigator):Dutch Heart Foundation:Past (completed) ; Royalties/Patent Beneficiary:Stanford School of Medicine:Active (exists now) ; Researcher:Amsterdam UMC:Past (completed) | Michael Mlynash: DO NOT have relevant financial relationships | Greg Zaharchuk: DO have relevant financial relationships ; Ownership Interest:Subtle Medical Inc.:Active (exists now) | Maarten Lansberg: DO have relevant financial relationships ; Other (please indicate in the box next to the company name):Up To Date (Author):Active (exists now) ; Consultant:Biogen:Past (completed) ; Consultant:Roche:Past (completed) | Gregory Albers: DO have relevant financial relationships ; Consultant:iSchemaView:Active (exists now) ; Individual Stocks/Stock Options:iSchemaView:Active (exists now) ; Consultant:Genentech:Past (completed) | Jeremy Heit: DO have relevant financial relationships ; Consultant:Medtronic:Active (exists now) ; Ownership Interest:Dragon Medical:Active (exists now) ; Research Funding (PI or named investigator):NIH:Active (exists now) ; Consultant:Balt:Active (exists now) ; Consultant:MicroVention:Active (exists now) | Yongkai Liu: DO NOT have relevant financial relationships | Aroosa Zamarud: DO NOT have relevant financial relationships | Anke Wouters: DO NOT have relevant financial relationships | Pierre Seners: No Answer | Abdelkader Mahammedi: DO NOT have relevant financial relationships | Benjamin Verhaaren: No Answer | Soren Christensen: DO have relevant financial relationships ; Individual Stocks/Stock Options:Ischemaview:Active (exists now) ; Employee:Cercare Medical:Active (exists now) | Nicole Yuen: DO NOT have relevant financial relationships
Meeting Info:
Session Info:

Cerebrovascular Systems of Care Moderated Digital Posters

Wednesday, 02/05/2025 , 01:20PM - 01:50PM

Moderated Digital Poster Abstract Session

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Comparing hypodensity and volume measurements for ischemic stroke patients in admission CT between CTP ischemic core, DWI, and deep learning based CT regions of interest

Van Voorst Henk, Mlynash Michael, Zaharchuk Greg, Lansberg Maarten, Albers Gregory, Heit Jeremy, Zamarud Aroosa, Liu Yongkai, Wouters Anke, Seners Pierre, Mahammedi Abdelkader, Verhaaren Benjamin, Christensen Soren, Yuen Nicole

Functional outcome after endovascular treatment can be predicted using deep learning based CT volume and density measures with and without CTP before interhospital transfer

Van Voorst Henk, Mlynash Michael, Zaharchuk Greg, Lansberg Maarten, Albers Greg, Heit Jeremy, Liu Yongkai, Zamarud Aroosa, Wouters Anke, Seners Pierre, Mahammedi Abdelkader, Verhaaren Benjamin, Christensen Soren, Yuen Nicole

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