Neural Network-derived perfusion maps: a Model-free approach to computed tomography perfusion in patients with acute ischemic stroke

TL;DR

This study demonstrates that a CNN can generate clinically relevant perfusion maps from CT data in stroke patients, offering a potentially simpler and lower-dose alternative to traditional deconvolution methods.

Contribution

The paper introduces a CNN-based method for generating perfusion maps that are comparable to state-of-the-art techniques, reducing data requirements and potentially lowering radiation exposure.

Findings

CNN-derived maps have Dice scores > 0.70 indicating good agreement.

High correlation (0.98-0.99) between CNN and ground truth lesion volumes.

Method produces clinically relevant perfusion maps with less data.

Abstract

Purpose: In this study we investigate whether a Convolutional Neural Network (CNN) can generate clinically relevant parametric maps from CT perfusion data in a clinical setting of patients with acute ischemic stroke. Methods: Training of the CNN was done on a subset of 100 perfusion data, while 15 samples were used as validation. All the data used for the training/validation of the network and to generate ground truth (GT) maps, using a state-of-the-art deconvolution-algorithm, were previously pre-processed using a standard pipeline. Validation was carried out through manual segmentation of infarct core and penumbra on both CNN-derived maps and GT maps. Concordance among segmented lesions was assessed using the Dice and the Pearson correlation coefficients across lesion volumes. Results: Mean Dice scores from two different raters and the GT maps were > 0.70 (good-matching). Inter-rater concordance was also high and strong correlation was found between lesion volumes of CNN maps and GT maps (0.99, 0.98). Conclusion: Our CNN-based approach generated clinically relevant perfusion maps that are comparable to state-of-the-art perfusion analysis methods based on deconvolution of the data. Moreover, the proposed technique requires less information to estimate the ischemic core and thus might allow the development of novel perfusion protocols with lower radiation dose.