Outcome Prediction Based on Automatically Extracted Infarct Core Image Features in Patients with Acute Ischemic Stroke
Abstract
:1. Introduction
2. Materials and Methods
2.1. Datasets
2.2. Pre-Processing and Image Analysis
2.2.1. Image Registration
2.2.2. Lesion Segmentation
2.3. Feature Extraction
2.3.1. Convolutional Autoencoder
2.3.2. Radiomics
2.4. Classification
3. Results
3.1. Study Population
3.2. Autoencoder Image Reconstruction
3.3. Functional Outcome Prediction
3.4. Radiomic Feature Importance
4. Discussion
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Jansen, I.G.H.; Mulder, M.J.H.L.; Goldhoorn, R.J.B. Endovascular treatment for acute ischaemic stroke in routine clinical practice: Prospective, observational cohort study (MR CLEAN Registry). BMJ 2018, 360, k949. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Langhammer, B.; Sunnerhagen, K.S.; Lundgren-Nilsson, Å.; Sällström, S.; Becker, F.; Stanghelle, J.K. Factors enhancing activities of daily living after stroke in specialized rehabilitation: An observational multicenter study within the Sunnaas International Network. Eur. J. Phys. Rehabil. Med. 2017, 53, 725–734. [Google Scholar] [CrossRef] [PubMed]
- Boers, A.M.M.; Jansen, I.G.H.; Beenen, L.F.M.; Devlin, T.G.; San Roman, L.; Heo, J.H.; Ribó, M.; Brown, S.; Almekhlafi, M.A.; Liebeskind, D.S.; et al. Association of follow-up infarct volume with functional outcome in acute ischemic stroke: A pooled analysis of seven randomized trials. J. Neurointerv. Surg. 2018, 10, 1137–1142. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Goyal, M.; Ospel, J.M.; Menon, B.; Almekhlafi, M.; Jayaraman, M.; Fiehler, J.; Psychogios, M.; Chapot, R.; Van Der Lugt, A.; Liu, J.; et al. Challenging the Ischemic Core Concept in Acute Ischemic Stroke Imaging. Stroke 2020, 51, 3147–3155. [Google Scholar] [CrossRef] [PubMed]
- Konduri, P.; van Kranendonk, K.; Boers, A.; Treurniet, K.; Berkhemer, O.; Yoo, A.J.; van Zwam, W.; van Oostenbrugge, R.; van der Lugt, A.; Dippel, D.; et al. The Role of Edema in Subacute Lesion Progression After Treatment of Acute Ischemic Stroke. Front. Neurol. 2021, 12, 705221. [Google Scholar] [CrossRef]
- Wu, O.; Christensen, S.; Hjort, N.; Dijkhuizen, R.M.; Kucinski, T.; Fiehler, J.; Thomalla, G.; Röther, J.; Østergaard, L. Characterizing physiological heterogeneity of infarction risk in acute human ischaemic stroke using MRI. Brain 2006, 129, 2384–2393. [Google Scholar] [CrossRef] [Green Version]
- Wang, H.; Lin, J.; Zheng, L.; Zhao, J.; Song, B.; Dai, Y. Texture analysis based on ADC maps and T2-FLAIR images for the assessment of the severity and prognosis of ischaemic stroke. Clin. Imaging 2020, 67, 152–159. [Google Scholar] [CrossRef]
- Frindel, C.; Rouanet, A.; Giacalone, M.; Cho, T.H.; Østergaard, L.; Fiehler, J.; Pedraza, S.; Baron, J.C.; Wiart, M.; Berthezène, Y.; et al. Validity of Shape as a Predictive Biomarker of Final Infarct Volume in Acute Ischemic Stroke. Stroke 2015, 46, 976–981. [Google Scholar] [CrossRef] [Green Version]
- Qiu, W.; Kuang, H.; Nair, J.; Assis, Z.; Najm, M.; McDougall, C.; McDougall, B.; Chung, K.; Wilson, A.T.; Goyal, M.; et al. Radiomics-based intracranial thrombus features on CT and CTA predict recanalization with intravenous alteplase in patients with acute ischemic stroke. Am. J. Neuroradiol. 2019, 40, 39–44. [Google Scholar] [CrossRef]
- Hilbert, A.; Ramos, L.A.; van Os, H.J.A.; Olabarriaga, S.D.; Tolhuisen, M.L.; Wermer, M.J.H.; Barros, R.S.; van der Schaaf, I.; Dippel, D.; Roos, Y.B.W.E.M.; et al. Data-efficient deep learning of radiological image data for outcome prediction after endovascular treatment of patients with acute ischemic stroke. Comput. Biol. Med. 2019, 115, 103516. [Google Scholar] [CrossRef]
- Goyal, M.; Menon, B.K.; Van Zwam, W.H.; Dippel, D.W.J.; Mitchell, P.J.; Demchuk, A.M.; Dávalos, A.; Majoie, C.B.L.M.; Van Der Lugt, A.; De Miquel, M.A.; et al. Endovascular thrombectomy after large-vessel ischaemic stroke: A meta-analysis of individual patient data from five randomised trials. Lancet 2016, 387, 1723–1731. [Google Scholar] [CrossRef]
- Maier, O.; Menze, B.H.; von der Gablentz, J.; Häni, L.; Heinrich, M.P.; Liebrand, M.; Winzeck, S.; Basit, A.; Bentley, P.; Chen, L.; et al. ISLES 2015—A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI. Med. Image Anal. 2017, 35, 250–269. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- LeCouffe, N.E.; Kappelhof, M.; Treurniet, K.M.; Rinkel, L.A.; Bruggeman, A.E.; Berkhemer, O.A.; Wolff, L.; van Voorst, H.; Tolhuisen, M.L.; Dippel, D.W.J.; et al. A Randomized Trial of Intravenous Alteplase before Endovascular Treatment for Stroke. N. Engl. J. Med. 2021, 385, 1833–1844. [Google Scholar] [CrossRef] [PubMed]
- Kompanje, E.J.O.; van Dijck, J.T.J.M.; Chalos, V.; van den Berg, S.A.; Janssen, P.M.; Nederkoorn, P.J.; van der Jagt, M.; Citerio, G.; Stocchetti, N.; Dippel, D.W.J.; et al. Informed consent procedures for emergency interventional research in patients with traumatic brain injury and ischaemic stroke. Lancet Neurol. 2020, 19, 1033–1042. [Google Scholar] [CrossRef]
- Friston, K.J.; Ashburner, J.T.; Kiebel, S.; Nichols, T.E.; Penny, W.D. (Eds.) Statistical Parametric Mapping: The Analysis of Functional Brain Images, 1st ed.; Elsevier: Amsterdam, The Netherlands; Academic Press: Cambridge, MA, USA, 2007; ISBN 9780123725608. [Google Scholar]
- Shinohara, R.T.; Sweeney, E.M.; Goldsmith, J.; Shiee, N.; Mateen, F.J.; Calabresi, P.A.; Jarso, S.; Pham, D.L.; Reich, D.S.; Crainiceanu, C.M. Statistical normalization techniques for magnetic resonance imaging. NeuroImage Clin. 2014, 6, 9–19. [Google Scholar] [CrossRef] [Green Version]
- Kamnitsas, K.; Ledig, C.; Newcombe, V.F.J.; Simpson, J.P.; Kane, A.D.; Menon, D.K.; Rueckert, D.; Glocker, B. Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. Med. Image Anal. 2017, 36, 61–78. [Google Scholar] [CrossRef]
- Yushkevich, P.A.; Piven, J.; Hazlett, H.C.; Smith, R.G.; Ho, S.; Gee, J.C.; Gerig, G. User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. Neuroimage 2006, 31, 1116–1128. [Google Scholar] [CrossRef] [Green Version]
- Chollet, F.; Keras Team. GitHub. 2015. Available online: https://github.com/fchollet/keras (accessed on 17 July 2022).
- Van Griethuysen, J.J.M.; Fedorov, A.; Parmar, C.; Hosny, A.; Aucoin, N.; Narayan, V.; Beets-Tan, R.G.H.; Fillion-Robin, J.C.; Pieper, S.; Aerts, H.J.W.L. Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017, 77, e104–e107. [Google Scholar] [CrossRef] [Green Version]
- Pedregosa, F.; Varoquaux, G.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M.; Prettenhofer, P.; Weiss, R.; Dubourg, V.; et al. Scikit-learn: Machine Learning in {P}ython. J. Mach. Learn. Res. 2011, 12, 2825–2830. [Google Scholar]
- DeLong, E.R.; DeLong, D.M.; Clarke-Pearson, D.L. Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach. Biometrics 1988, 44, 837–845. [Google Scholar] [CrossRef]
- Lundberg, S.M.; Lee, S.-I. A Unified Approach to Interpreting Model Predictions. In Proceedings of the 31st International Conference on Neural Information Processing Systems (NIPS’17:), Long Beach, CA, USA, 4–9 December 2017; Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R., Eds.; Curran Associates, Inc.: Red Hook, NY, USA, 2017; Volume 32, pp. 4765–4774. [Google Scholar]
- Zwanenburg, A.; Leger, S.; Vallières, M.; Löck, S. Image biomarker standardisation initiative. arXiv 2016, arXiv:1612.07003. [Google Scholar] [CrossRef] [Green Version]
- Van Kranendonk, K.R.; Treurniet, K.M.; Boers, A.M.M.; Berkhemer, O.A.; Van Den Berg, L.A.; Chalos, V.; Lingsma, H.F.; Van Zwam, W.H.; Van Der Lugt, A.; Van Oostenbrugge, R.J.; et al. Hemorrhagic transformation is associated with poor functional outcome in patients with acute ischemic stroke due to a large vessel occlusion. J. Neurointerv. Surg. 2019, 11, 464–468. [Google Scholar] [CrossRef]
- Rios, T.; Van Stein, B.; Menzel, S.; Back, T.; Sendhoff, B.; Wollstadt, P. Feature Visualization for 3D Point Cloud Autoencoders. In Proceedings of the 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 19–24 July 2020. [Google Scholar] [CrossRef]
- Xie, Y.; Oster, J.; Micard, E.; Chen, B.; Douros, I.K.; Liao, L.; Zhu, F.; Soudant, M.; Felblinger, J.; Guillemin, F.; et al. Impact of Pretreatment Ischemic Location on Functional Outcome after Thrombectomy. Diagnostics 2021, 11, 2038. [Google Scholar] [CrossRef] [PubMed]
- Berkhemer, O.A.; Fransen, P.S.S.; Beumer, D.; van den Berg, L.A.; Lingsma, H.F.; Yoo, A.J.; Schonewille, W.J.; Vos, J.A.; Nederkoorn, P.J.; Wermer, M.J.H.; et al. A Randomized Trial of Intraarterial Treatment for Acute Ischemic Stroke. N. Engl. J. Med. 2014, 372, 11–20. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Saver, J.L.; Goyal, M.; Bonafe, A.; Diener, H.-C.; Levy, E.I.; Pereira, V.M.; Albers, G.W.; Cognard, C.; Cohen, D.J.; Hacke, W.; et al. Stent-Retriever Thrombectomy after Intravenous t-PA vs. t-PA Alone in Stroke. N. Engl. J. Med. 2015, 372, 2285–2295. [Google Scholar] [CrossRef] [Green Version]
- Campbell, B.C.V.; Mitchell, P.J.; Kleinig, T.J.; Dewey, H.M.; Churilov, L.; Yassi, N.; Yan, B.; Dowling, R.J.; Parsons, M.W.; Oxley, T.J.; et al. Endovascular Therapy for Ischemic Stroke with Perfusion-Imaging Selection. N. Engl. J. Med. 2015, 372, 1009–1018. [Google Scholar] [CrossRef] [Green Version]
- Jovin, T.G.; Chamorro, A.; Cobo, E.; de Miquel, M.A.; Molina, C.A.; Rovira, A.; San Román, L.; Serena, J.; Abilleira, S.; Ribó, M.; et al. Thrombectomy within 8 Hours after Symptom Onset in Ischemic Stroke. N. Engl. J. Med. 2015, 372, 2296–2306. [Google Scholar] [CrossRef] [Green Version]
- Goyal, M.; Demchuk, A.M.; Menon, B.K.; Eesa, M.; Rempel, J.L.; Thornton, J.; Roy, D.; Jovin, T.G.; Willinsky, R.A.; Sapkota, B.L.; et al. Randomized assessment of rapid endovascular treatment of ischemic stroke. N. Engl. J. Med. 2015, 372, 1019–1030. [Google Scholar] [CrossRef] [Green Version]
- Muir, K.W.; Ford, G.A.; Messow, C.M.; Ford, I.; Murray, A.; Clifton, A.; Brown, M.M.; Madigan, J.; Lenthall, R.; Robertson, F.; et al. Endovascular therapy for acute ischaemic stroke: The Pragmatic Ischaemic Stroke Thrombectomy Evaluation (PISTE) randomised, controlled trial. J. Neurol. Neurosurg. Psychiatry 2017, 88, 38–44. [Google Scholar] [CrossRef] [Green Version]
- Bracard, S.; Ducrocq, X.; Mas, J.L.; Soudant, M.; Oppenheim, C.; Moulin, T.; Guillemin, F. Mechanical thrombectomy after intravenous alteplase versus alteplase alone after stroke (THRACE): A randomised controlled trial. Lancet Neurol. 2016, 15, 1138–1147. [Google Scholar] [CrossRef]
Feature Extraction Method | Training Accuracy (n = 144) | Testing Accuracy (n = 41) | AUC (n = 41) | Precision (n = 41) | Recall (n = 41) | deLong’s Test p-Value |
---|---|---|---|---|---|---|
FIV only * | 0.73 | 0.74 | 0.79 | 0.78 | 0.73 | 0.15 |
Autoencoder ** | 0.76 | 0.71 | 0.81 | 0.70 | 0.71 | 0.37 |
Radiomics *** | 0.75 | 0.71 | 0.88 | 0.80 | 0.65 |
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Share and Cite
Tolhuisen, M.L.; Hoving, J.W.; Koopman, M.S.; Kappelhof, M.; van Voorst, H.; Bruggeman, A.E.; Demchuck, A.M.; Dippel, D.W.J.; Emmer, B.J.; Bracard, S.; et al. Outcome Prediction Based on Automatically Extracted Infarct Core Image Features in Patients with Acute Ischemic Stroke. Diagnostics 2022, 12, 1786. https://doi.org/10.3390/diagnostics12081786
Tolhuisen ML, Hoving JW, Koopman MS, Kappelhof M, van Voorst H, Bruggeman AE, Demchuck AM, Dippel DWJ, Emmer BJ, Bracard S, et al. Outcome Prediction Based on Automatically Extracted Infarct Core Image Features in Patients with Acute Ischemic Stroke. Diagnostics. 2022; 12(8):1786. https://doi.org/10.3390/diagnostics12081786
Chicago/Turabian StyleTolhuisen, Manon L., Jan W. Hoving, Miou S. Koopman, Manon Kappelhof, Henk van Voorst, Agnetha E. Bruggeman, Adam M. Demchuck, Diederik W. J. Dippel, Bart J. Emmer, Serge Bracard, and et al. 2022. "Outcome Prediction Based on Automatically Extracted Infarct Core Image Features in Patients with Acute Ischemic Stroke" Diagnostics 12, no. 8: 1786. https://doi.org/10.3390/diagnostics12081786