AI for Medical Imaging and Virtual Human Twins
Welcome to the AI for Medical Imaging and Research Group. We specialize in leveraging artificial intelligence to advance medical research and improve patient care in four critical areas: stroke, neurological and psychological diseases, cardiovascular diseases, and oncology. Our interdisciplinary team integrates expertise in AI, medical imaging, and clinical practices to develop innovative solutions that enhance diagnosis, treatment, and patient outcomes. By focusing on these key health challenges, we aim to transform healthcare delivery and contribute to the development of cutting-edge medical technologies.
Value of Automatically Derived Full Thrombus Characteristics
Value of Automatically Derived Full Thrombus Characteristics investigates the relationship between detailed thrombus characteristics and clinical outcomes in ischemic stroke patients, finding significant correlations between higher thrombus perviousness and better functional outcomes, as well as between lower thrombus volume and improved technical success and reperfusion rates.
Thrombus Composition and Its Clinical Significance
Thrombus Composition and Its Clinical Significance aims to analyze the composition of thrombi and its clinical significance, linking specific thrombus characteristics to treatment outcomes and guiding more effective intervention strategies.
Investigating Predictors of Thrombectomy Success
Investigating Predictors of Thrombectomy Success to identifies key predictors that influence the success rates of thrombectomy procedures, providing insights into factors that can enhance the efficacy of stroke interventions.
Development and evaluation of AI models
Development and evaluation of AI models to assess vascular involvement and classify tumor resectability in patients with pancreatic ductal adenocarcinoma (PDAC) using CT scans. We aim to segmentsthe tumor and surrounding vasculature, to quantify vascular involvement, and classifies resectability based on established criteria.
Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke
Work on “Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke” which is a new method for analyzing CT perfusion data using the Spatio-temporal Perfusion Physics-Informed Neural Network (SPPINN). This approach accurately estimates cerebral perfusion parameters even with high noise levels and differentiates between healthy and infarcted tissue, showing high correspondence with reference standard infarct core segmentations.
Treatment Response Prediction in Major Depressive Disorder Using Multimodal MRI and Clinical Data
Treatment Response Prediction in Major Depressive Disorder Using Multimodal MRI and Clinical Data to evaluate a multimodal machine learning approaches to predict early response to sertraline in patients with major depressive disorder. Our work show that integrating MRI and clinical data enhances prediction accuracy, with perfusion imaging being particularly contributive, indicating that such models can potentially individualize and improve treatment planning.
Faculty
Postdocs
PhDs
Prediction of methylphenidate treatment response for ADHD using conventional and radiomics T1 and DTI features: Secondary analysis of a randomized clinical trial
Chen, M., van der Pal, Z., Poirot, M. G., Schrantee, A., Bottelier, M., Kooij, S. J. J., Marquering, H. A., Reneman, L. & Caan, M. W. A., 1 Jan 2025, In: NeuroImage: Clinical. 45, 103707.Research output: Contribution to journal › Article › Academic › peer-review
Artificial intelligence for assessment of vascular involvement and tumor resectability on CT in patients with pancreatic cancer
Bereska, J. I., Janssen, B. V., Nio, C. Y., Kop, M. P. M., Kazemier, G., Busch, O. R., Struik, F., Marquering, H. A., Stoker, J., Besselink, M. G. & Verpalen, I. M., 1 Dec 2024, In: European Radiology Experimental. 8, 1, 18.Research output: Contribution to journal › Article › Academic › peer-review
Enhancement of early proximal caries annotations in radiographs: introducing the Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset
Valenzuela, R. E. G., Mettes, P., Loos, B. G., Marquering, H. & Berkhout, E., 1 Dec 2024, In: BMC oral health. 24, 1, 1325.Research output: Contribution to journal › Article › Academic › peer-review
Development and external evaluation of a self-learning auto-segmentation model for Colorectal Cancer Liver Metastases Assessment (COALA)
Bereska, J. I., Zeeuw, M., Wagenaar, L., Jenssen, H. V. B., Wesdorp, N. J., van der Meulen, D., Bereska, L. F., Gavves, E., Janssen, B. V., Besselink, M. G., Marquering, H. A., van Waesberghe, J.-H. T. M., Aghayan, D. L., Pelanis, E., van den Bergh, J., Nota, I. I. M., Moos, S., Kemmerich, G., Syversveen, T. & Kolrud, F. K. & 44 others, , 1 Dec 2024, In: Insights into imaging. 15, 1, 279.Research output: Contribution to journal › Article › Academic › peer-review
ATOMMIC: An Advanced Toolbox for Multitask Medical Imaging Consistency to facilitate Artificial Intelligence applications from acquisition to analysis in Magnetic Resonance Imaging
Karkalousos, D., Išgum, I., Marquering, H. A. & Caan, M. W. A., 1 Nov 2024, In: Computer methods and programs in biomedicine. 256, 108377.Research output: Contribution to journal › Article › Academic › peer-review
Left Atrial Appendage Opacification on Cardiac Computed Tomography in Acute Ischemic Stroke: The Clinical Implications of Slow-Flow
Nio, S. S., Rinkel, L. A., Cramer, O. N., Özata, Z. B., Beemsterboer, C. F. P., Guglielmi, V., Bouma, B. J., Boekholdt, S. M., Lobé, N. H. J., Beenen, L. F. M., Marquering, H. A., Majoie, C. B. L. M., Roos, Y. B. W. E. M., van Randen, A., Planken, R. N. & Coutinho, J. M., 3 Sept 2024, In: Journal of the American Heart Association. 13, 17, e034106.Research output: Contribution to journal › Article › Academic › peer-review
Deep learning-based white matter lesion volume on CT is associated with outcome after acute ischemic stroke
van Voorst, H., Pitkänen, J., van Poppel, L., de Vries, L., Mojtahedi, M., Martou, L., Emmer, B. J., Roos, Y. B. W. E. M., van Oostenbrugge, R., Postma, A. A., Marquering, H. A., Majoie, C. B. L. M., Curtze, S., Melkas, S., Bentley, P. & Caan, M. W. A., Aug 2024, In: European radiology. 34, 8, p. 5080-5093 14 p.Research output: Contribution to journal › Article › Academic › peer-review
Long-Term Clinical Implications of High-Risk Cardiac Computed Tomography Findings in Patients With Acute Ischemic Stroke
Rinkel, L. A., Cramer, O. N., Özata, Z. B., Beemsterboer, C. F. P., Guglielmi, V., Nio, S. S., Bouma, B. J., Boekholdt, S. M., Lobé, N. H. J., Beenen, L. F. M., Marquering, H. A., Majoie, C. B. L. M., Roos, Y. B. W. E. M., van Randen, A., Planken, R. N. & Coutinho, J. M., 7 May 2024, In: Journal of the American Heart Association. 13, 9, e033175.Research output: Contribution to journal › Article › Academic › peer-review
Thrombus Imaging Characteristics to Predict Early Recanalization in Anterior Circulation Large Vessel Occlusion Stroke
on behalf of the MR CLEAN Registry Investigators, Apr 2024, In: Journal of cardiovascular development and disease. 11, 4, 107.Research output: Contribution to journal › Article › Academic › peer-review
Impact of Intracranial Volume and Brain Volume on the Prognostic Value of Computed Tomography Perfusion Core Volume in Acute Ischemic Stroke
Hoving, J. W., Konduri, P. R., Tolhuisen, M. L., Koopman, M. S., van Voorst, H., van Poppel, L. M., Daems, J. D., van Es, A. C. G. M., van Walderveen, M. A. A., Lingsma, H. F., Dippel, D. W. J. & on behalf of the MR CLEAN Registry Investigators, 1 Mar 2024, In: Journal of cardiovascular development and disease. 11, 3, 80.Research output: Contribution to journal › Article › Academic › peer-review
Radiomics for the prediction of a postoperative pancreatic fistula following a pancreatoduodenectomy: A systematic review and radiomic score quality assessment
Ingwersen, E. W., Rijssenbeek, P. M. W., Marquering, H. A., Kazemier, G. & Daams, F., Mar 2024, In: Pancreatology. 24, 2, p. 306-313 8 p.Research output: Contribution to journal › Article › Academic › peer-review
Treatment Response Prediction in Major Depressive Disorder Using Multimodal MRI and Clinical Data: Secondary Analysis of a Randomized Clinical Trial
Poirot, M. G., Ruhe, H. G., Mutsaerts, H.-J. M. M., Maximov, I. I., Groote, I. R., Bjørnerud, A., Marquering, H. A., Reneman, L. & Caan, M. W. A., 1 Mar 2024, In: American journal of psychiatry. 181, 3, p. 223-233 11 p.Research output: Contribution to journal › Article › Academic › peer-review
Value of Automatically Derived Full Thrombus Characteristics: An Explorative Study of Their Associations with Outcomes in Ischemic Stroke Patients
Mojtahedi, M., Bruggeman, A. E., van Voorst, H., Ponomareva, E., Kappelhof, M., van der Lugt, A., Hoving, J. W., Dutra, B. G., Dippel, D., Cavalcante, F., Yo, L., Coutinho, J., Brouwer, J., Treurniet, K., Tolhuisen, M. L., LeCouffe, N., Arrarte Terreros, N., Konduri, P. R., van Zwam, W. & Roos, Y. & 3 others, , 1 Mar 2024, In: Journal of clinical medicine. 13, 5, 1388.Research output: Contribution to journal › Article › Academic › peer-review
Towards a Generation of Digital Twins in Healthcare of Ischaemic and Haemorrhagic Stroke
Hoekstra, A. G. & GEMINI consortium, 2024, Computational Science – ICCS 2024 - 24th International Conference, 2024, Proceedings. Franco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V. V., Dongarra, J. J. & Sloot, P. M. A. (eds.). Springer Science and Business Media Deutschland GmbH, Vol. 14834 LNCS. p. 239-245 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14834 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Deep learning for efficient reconstruction of highly accelerated 3D FLAIR MRI in neurological deficits
Liebrand, L. C., Karkalousos, D., Poirion, É., Emmer, B. J., Roosendaal, S. D., Marquering, H. A., Majoie, C. B. L. M., Savatovsky, J. & Caan, M. W. A., 2024, (E-pub ahead of print) In: Magnetic Resonance Materials in Physics, Biology and Medicine.Research output: Contribution to journal › Article › Academic › peer-review
The Multicentre Acute ischemic stroke imaGIng and Clinical data (MAGIC) repository: rationale and blueprint
Baazaoui, H., Engelter, S. T., Gensicke, H., Enz, L. S., Psychogios, M., Mutke, M., Michel, P., Strambo, D., Salerno, A., Marquering, H. A., Nederkoorn, P. J., Wali, N., Tanadini-Lang, S., Menze, B., de la Rosa, E., Yang, K., de Marchis, G. M., Dittrich, T. D., Valletta, F. & Germann, M. & 6 others, , 2024, In: Frontiers in neuroinformatics. 18, 1508161.Research output: Contribution to journal › Article › Academic › peer-review
High-Risk Embolic Sources on Cardiac Computed Tomography in Patients with Acute Ischemic Stroke: A Case-Control Study
Nio, S. S., Rinkel, L. A., van Schuppen, J., Spijkerboer, A. M., Beemsterboer, C. F. P., Guglielmi, V., Bouma, B. J., Boekholdt, S. M., Lobé, N. H. J., Beenen, L. F. M., Marquering, H. A., Majoie, C. B. L. M., Roos, Y. B. W. E. M., van Randen, A., Planken, R. N. & Coutinho, J. M., 2024, (E-pub ahead of print) In: Stroke.Research output: Contribution to journal › Article › Academic › peer-review
Prehospital Detection of Large Vessel Occlusion Stroke With EEG: Results of the ELECTRA-STROKE Study
van Stigt, M. N., Groenendijk, E. A., van Meenen, L. C. C., van de Munckhof, A. A. G. A., Theunissen, M., Franschman, G., Smeekes, M. D., van Grondelle, J. A. F., Geuzebroek, G., Siegers, A., Visser, M. C., van Schaik, S. M., Halkes, P. H. A., Majoie, C. B. L. M., Roos, Y. B. W. E. M., Koelman, J. H. T. M., Koopman, M. S., Marquering, H. A., Potters, W. V. & Coutinho, J. M., 12 Dec 2023, In: Neurology. 101, 24, p. E2522-E2532 doi: 10.1212/WNL.0000000000207831.Research output: Contribution to journal › Article › Academic › peer-review
Identifying Genetic Mutation Status in Patients with Colorectal Cancer Liver Metastases Using Radiomics-Based Machine-Learning Models
Wesdorp, N., Zeeuw, M., van der Meulen, D., van ‘t Erve, I., Bodalal, Z., Roor, J., van Waesberghe, J. H., Moos, S., van den Bergh, J., Nota, I., van Dieren, S., Stoker, J., Meijer, G., Swijnenburg, R.-J., Punt, C., Huiskens, J., Beets-Tan, R., Fijneman, R. & on behalf of the Dutch Colorectal Cancer Group Liver Expert Panel, 1 Dec 2023, In: Cancers. 15, 23, 5648.Research output: Contribution to journal › Article › Academic › peer-review
A simplified mesoscale 3D model for characterizing fibrinolysis under flow conditions
Petkantchin, R., Rousseau, A., Eker, O., Zouaoui Boudjeltia, K., Raynaud, F., Chopard, B., Majoie, C., van Bavel, E., Marquering, H., Arrarte-Terreros, N., Konduri, P., Georgakopoulou, S., Roos, Y., Hoekstra, A., Padmos, R., Azizi, V., Miller, C., van der Kolk, M., van der Lugt, A. & Dippel, D. W. J. & 28 others, , 1 Dec 2023, In: Scientific reports. 13, 1, 13681.Research output: Contribution to journal › Article › Academic › peer-review