Automated final lesion segmentation in posterior circulation acute ischemic stroke using deep learning

Zoetmulder, R. et al. (2021) Automated final lesion segmentation in posterior circulation acute ischemic stroke using deep learning. Diagnostics, 11(9), 1621. (doi: 10.3390/diagnostics11091621)

Abstract

Final lesion volume (FLV) is a surrogate outcome measure in anterior circulation stroke (ACS). In posterior circulation stroke (PCS), this relation is plausibly understudied due to a lack of methods that automatically quantify FLV. The applicability of deep learning approaches to PCS is limited due to its lower incidence compared to ACS. We evaluated strategies to develop a convolutional neural network (CNN) for PCS lesion segmentation by using image data from both ACS and PCS patients. We included follow-up non-contrast computed tomography scans of 1018 patients with ACS and 107 patients with PCS. To assess whether an ACS lesion segmentation generalizes to PCS, a CNN was trained on ACS data (ACS-CNN). Second, to evaluate the performance of only including PCS patients, a CNN was trained on PCS data. Third, to evaluate the performance when combining the datasets, a CNN was trained on both datasets. Finally, to evaluate the performance of transfer learning, the ACS-CNN was fine-tuned using PCS patients. The transfer learning strategy outperformed the other strategies in volume agreement with an intra-class correlation of 0.88 (95% CI: 0.83–0.92) vs. 0.55 to 0.83 and a lesion detection rate of 87% vs. 41–77 for the other strategies. Hence, transfer learning improved the FLV quantification and detection rate of PCS lesions compared to the other strategies.

• Item Type: Articles
• Keywords: Posterior stroke, segmentation, transfer learning, deep learning, CT.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Muir, Professor Keith

Creator Roles

Muir, K. W.: Data curation, Writing – review and editing

• Authors: Zoetmulder, R., Konduri, P. R., Obdeijn, I. V., Gavves, E., Išgum, I., Majoie, C. B.L.M., Dippel, D. W. J., Roos, Y. B. W. E. M., Goyal, M., Mitchell, P. J., Campbell, B. C. V., Lopes, D. K., Reimann, G., Jovin, T. G., Saver, J. L., Muir, K. W., White, P., Bracard, S., Chen, B., Brown, S., Schonewille, W. J., Hoeven, E. v. d., Puetz, V., and Marquering, H. A.
• College/School: College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
• Journal Name: Diagnostics
• Publisher: MDPI
• ISSN: 2075-4418
• ISSN (Online): 2075-4418
• Published Online: 04 September 2021
• Copyright Holders: Copyright © 2021 The Authors
• First Published: First published in Diagnostics 11(9): 1621
• Publisher Policy: Reproduced under a Creative Commons License

Related URLs

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