Core and penumbra estimation using deep learning-based AIF in association with clinical measures in computed tomography perfusion (CTP)

Bal, Sukhdeep Singh, Yang, Fan-pei Gloria, Chi, Nai-Fang, Yin, Jiu Haw, Wang, Tao-Jung, Peng, Giia Sheun, Chen, Ke ORCID: 0000-0002-6093-6623, Hsu, Ching-Chi and Chen, Chang-I (2023) Core and penumbra estimation using deep learning-based AIF in association with clinical measures in computed tomography perfusion (CTP). INSIGHTS INTO IMAGING, 14 (1). 161-.

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Official URL: http://dx.doi.org/10.1186/s13244-023-01472-z

Abstract

<h4>Objectives</h4>To investigate whether utilizing a convolutional neural network (CNN)-based arterial input function (AIF) improves the volumetric estimation of core and penumbra in association with clinical measures in stroke patients.<h4>Methods</h4>The study included 160 acute ischemic stroke patients (male = 87, female = 73, median age = 73 years) with approval from the institutional review board. The patients had undergone CTP imaging, NIHSS and ASPECTS grading. convolutional neural network (CNN) model was trained to fit a raw AIF curve to a gamma variate function. CNN AIF was utilized to estimate the core and penumbra volumes which were further validated with clinical scores.<h4>Results</h4>Penumbra estimated by CNN AIF correlated positively with the NIHSS score (r = 0.69; p < 0.001) and negatively with the ASPECTS (r = - 0.43; p < 0.001). The CNN AIF estimated penumbra and core volume matching the patient symptoms, typically in patients with higher NIHSS (> 20) and lower ASPECT score (< 5). In group analysis, the median CBF < 20%, CBF < 30%, rCBF < 38%, Tmax > 10 s, Tmax > 10 s volumes were statistically significantly higher (p < .05).<h4>Conclusions</h4>With inclusion of the CNN AIF in perfusion imaging pipeline, penumbra and core estimations are more reliable as they correlate with scores representing neurological deficits in stroke.<h4>Critical relevance statement</h4>With CNN AIF perfusion imaging pipeline, penumbra and core estimations are more reliable as they correlate with scores representing neurological deficits in stroke.

Item Type:	Article
Uncontrolled Keywords:	Arterial input function, Ischemic stroke, Core, Penumbra, Perfusion parameters
Divisions:	Faculty of Science and Engineering > School of Physical Sciences
Depositing User:	Symplectic Admin
Date Deposited:	10 Nov 2023 15:41
Last Modified:	10 Nov 2023 15:41
DOI:	10.1186/s13244-023-01472-z
Open Access URL:	https://doi.org/10.1186/s13244-023-01472-z
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3176725