Publications 2025
[1] H. S. Assadi et al., “Cardiac MRI Markers of Ageing: A Multicentre, Cross-sectional Cohort Study,” European Heart Journal Open, p. oeaf032, Mar. 2025, doi: 10.1093/ehjopen/oeaf032.
[2] R. Bajaj et al., “Examination of the performance of machine learning-based automated coronary plaque characterization by NIRS-IVUS and OCT with histology,” European Heart Journal - Digital Health, p. ztaf009, Mar. 2025, doi: 10.1093/ehjdh/ztaf009.
[3] O. D. Bijlstra et al., “Preoperative chemotherapy reduces the accumulation of indocyanine green around colorectal liver metastases for use in fluorescence-guided surgery,” Surgical Endoscopy, Sept. 2025, doi: 10.1007/s00464-025-12034-3.
[4] L. Cheng et al., “Non-invasive estimation of hemodynamic parameters in pulmonary hypertension with a deep learning approach integrating all B-mode cine loops in an echocardiographic exam,” European Heart Journal, vol. 46, no. Supplement_1, p. ehaf784.4395, Nov. 2025, doi: 10.1093/eurheartj/ehaf784.4395.
[5] Q. Du et al., “Predictive value of aorta enhancement on computed tomographic pulmonary angiography in pulmonary embolism,” PLOS ONE, vol. 20, no. 10, p. e0335055, Oct. 2025, doi: 10.1371/journal.pone.0335055.
[6] E. Erdogan et al., “Morphological characteristics of non-culprit lesions in patients with chronic and acute coronary syndromes: A NIRS-IVUS study,” in Diagnostic and Therapeutic Applications of Light in Cardiology 2025, SPIE, Mar. 2025, p. PC1329502. doi: 10.1117/12.3049890.
[7] R. Gao, P. Mody, C. Rao, F. Dankers, and M. Staring, “On factors that influence deep learning-based dose prediction of head and neck tumors,” Physics in Medicine and Biology, Apr. 2025, doi: 10.1088/1361-6560/adcfeb.
[8] P. Garg et al., “Haemodynamic implications of cardiovascular magnetic resonance pulmonary capillary wedge pressure in acute myocardial infarction,” European Heart Journal - Imaging Methods and Practice, vol. 3, no. 2, p. qyaf086, July 2025, doi: 10.1093/ehjimp/qyaf086.
[9] C. Grafton-Clarke et al., “Four-dimensional flow provides incremental diagnostic value over echocardiography in aortic stenosis,” Open Heart, vol. 12, no. 1, May 2025, doi: 10.1136/openhrt-2024-003081.
[10] Y. Han et al., “Vortices and Hemodynamic Forces in the Left Ventricle: Comparison between High Frame Rate Echo-Particle Image Velocimetry and 4D Flow MRI,” Ultrasound in Medicine & Biology, July 2025, doi: 10.1016/j.ultrasmedbio.2025.06.023.
[11] S. Iwańczyk et al., “Endothelial shear stress pattern in coronary artery aneurysm: A case report,” Kardiologia Polska, Feb. 2025, doi: 10.33963/v.phj.104603.
[12] T. N. Jensen et al., “Prediction of ventricular arrhythmias and sudden cardiac death by quantification and location of late gadolinium enhancement on cardiac magnetic resonance: A systematic review and meta-analysis,” EP Europace, vol. 27, no. 11, p. euaf214, Nov. 2025, doi: 10.1093/europace/euaf214.
[13] Y. Li, D. A. Ton, D. P. Shamonin, M. Reijnierse, A. H. M. van der Helm-van Mil, and B. C. Stoel, “Automatic joint inflammation estimation based on regression neural networks,” Medical Physics, vol. 52, no. 10, p. e70010, Oct. 2025, doi: 10.1002/mp.70010.
[14] Y. Li, D. P. Shamonin, T. Hassanzadeh, M. Reijnierse, A. H. M. van der Helm-van Mil, and B. C. Stoel, “Feature analysis for proper intensity scaling and feature distinction in class activation maps,” Knowledge-Based Systems, vol. 328, p. 114209, Oct. 2025, doi: 10.1016/j.knosys.2025.114209.
[15] K. Miyashita et al., “Quantitative optical assessment of high-intensity granules following drug coated balloon,” European Heart Journal, vol. 46, no. Supplement_1, p. ehaf784.3083, Nov. 2025, doi: 10.1093/eurheartj/ehaf784.3083.
[16] T. A. H. Newman et al., “Cardiac MRI-derived mean right atrial pressure and its prognostic importance,” Open Heart, vol. 12, no. 1, p. e003216, June 2025, doi: 10.1136/openhrt-2025-003216.
[17] J. Nicolaisen et al., “Induced Human-like Coronary Stenosis in Hypercholesterolemic PCSK9 Minipigs,” Journal of Cardiovascular Translational Research, Mar. 2025, doi: 10.1007/s12265-025-10607-0.
[18] A. Ramasamy et al., “Implications of imaging modalities on coronary vessel reconstruction and computation of the local hemodynamic forces,” Atherosclerosis, p. 120423, July 2025, doi: 10.1016/j.atherosclerosis.2025.120423.
[19] P. C. Revaiah et al., “Segmental post-PCI physiological gradients using ultrasonic or optical flow ratio: Insights from ASET JAPAN Study,” European Heart Journal - Imaging Methods and Practice, p. qyaf017, Jan. 2025, doi: 10.1093/ehjimp/qyaf017.
[20] S. Rezaei et al., “Bridging gaps with computer vision: AI in (bio)medical imaging and astronomy,” Astronomy and Computing, vol. 51, p. 100921, Apr. 2025, doi: 10.1016/j.ascom.2024.100921.
[21] R. Rissmann et al., “118 Multi-omics profiling reveals shared molecular signatures in psoriasis target plaques across disease severities during guselkumab induction therapy,” Journal of Investigative Dermatology, vol. 145, no. 11, p. e50, Nov. 2025, doi: 10.1016/j.jid.2025.09.135.
[22] K. A. Saville et al., “Association between arterial stiffness and long-term efficacy of renal sympathetic denervation: 5-year results of the ASORAS study,” Cardiovascular Intervention and Therapeutics, Sept. 2025, doi: 10.1007/s12928-025-01191-w.
[23] M. Selim et al., “Experimental evaluation of virtual needle insertion framework with enhanced haptic feedback,” International Journal of Computer Assisted Radiology and Surgery, June 2025, doi: 10.1007/s11548-025-03420-2.
[24] P. Serruys et al., “TCT-670 OCT iconography in 121 consecutive DCB treatments: When should we use rescue stenting?” JACC, vol. 86, no. 17_Supplement, pp. B291–B292, Oct. 2025, doi: 10.1016/j.jacc.2025.09.823.
[25] A. Sivananthan et al., “Deep-learning analysis of computed tomography coronary angiography data enables more accurate computation of the shear stress distribution than conventional analysis by experts: A head-to-head comparison with near-infrared spectroscopy-intravascular ultrasound-based modelling,” Journal of Cardiovascular Computed Tomography, vol. 0, no. 0, Oct. 2025, doi: 10.1016/j.jcct.2025.10.002.
[26] L. Tapper et al., “Enhancing accuracy of detecting left atrial dilatation on CT pulmonary angiography,” European Journal of Radiology Open, vol. 15, p. 100696, Dec. 2025, doi: 10.1016/j.ejro.2025.100696.
[27] R. Thomson et al., “Risk factors and outcomes associated with right ventricular mass: Exploring causality using Mendelian randomisation and cardiac MRI in UK Biobank,” European Heart Journal, vol. 46, no. Supplement_1, p. ehaf784.216, Nov. 2025, doi: 10.1093/eurheartj/ehaf784.216.
[28] W. Van Der Loo, V. O. Van Der Valk, T. J. Van Den Broek, D. E. Atsma, M. Staring, and R. W. C. Scherptong, “Towards expert-level AI-based classification of coronary angiography reports: A comparison of LLM approaches,” European Heart Journal, vol. 46, no. Supplement_1, p. ehaf784.4503, Nov. 2025, doi: 10.1093/eurheartj/ehaf784.4503.
[29] W. van der Loo, V. van der Valk, T. van den Broek, D. Atsma, M. Staring, and R. Scherptong, “Large Language Models for Structured Cardiovascular Data Extraction: A Foundation for Scalable Research and Clinical Applications,” European Heart Journal - Digital Health, p. ztaf127, Nov. 2025, doi: 10.1093/ehjdh/ztaf127.
[30] V. van der Valk, D. Atsma, R. Scherptong, and M. Staring, “Explainable ECG analysis by explicit information disentanglement with VAEs,” IEEE transactions on bio-medical engineering, vol. PP, Nov. 2025, doi: 10.1109/TBME.2025.3631143.
[31] A. L. van der Velden et al., “Prospective Registry Study on Thermal Liver Ablation of Primary and Secondary Liver Tumours Named the A-IMAGIO Study,” CardioVascular and Interventional Radiology, June 2025, doi: 10.1007/s00270-025-04093-9.
[32] G. C. M. van Erp et al., “Hydrodissection in microwave ablation: The effectiveness of 0.9 % NaCl versus 5 % dextrose in an ex vivo experimental set-up,” Research in Diagnostic and Interventional Imaging, vol. 14, p. 100060, June 2025, doi: 10.1016/j.redii.2025.100060.
[33] E. J. A. Verheijen et al., “Artificial intelligence for segmentation and classification in lumbar spinal stenosis: An overview of current methods,” European Spine Journal, Jan. 2025, doi: 10.1007/s00586-025-08672-9.
[34] N. A. L. Yap et al., “Implications of computed tomography reconstruction algorithms on coronary atheroma composition: A head-to-head comparison with multimodality near-infrared spectroscopy intravascular ultrasound imaging,” Journal of Cardiovascular Computed Tomography, Oct. 2025, doi: 10.1016/j.jcct.2025.10.009.
[35] B. Yu et al., “A Prompt-Aware Knowledge-Tuning Framework for Histopathology Subtype Classification with Scarce Annotation,” Neural Networks, p. 107993, Aug. 2025, doi: 10.1016/j.neunet.2025.107993.
[36] X. Zhao et al., “Insight into left ventricular diastolic compensation in hypertrophic cardiomyopathy with left ventricular outflow obstruction: A 4D flow CMR study,” European Heart Journal, vol. 46, no. Supplement_1, p. ehaf784.266, Nov. 2025, doi: 10.1093/eurheartj/ehaf784.266.
[37] X. Zhao et al., “The prognostic value of right ventricular kinetic energy for predicting adverse events in hypertrophic cardiomyopathy,” European Heart Journal, vol. 46, no. Supplement_1, p. ehaf784.267, Nov. 2025, doi: 10.1093/eurheartj/ehaf784.267.