R.G.H. Beets - Tan

Ubink, M., van Geffen, E. G. M., Sluckin, T. C., Hazen, S.-M. J. A., Horsthuis, K., Nederend, J., Beets-Tan, R. G. H., Intven, M. P. W., Verhoef, C., Kusters, M., & Tanis, P. J. (2025). Clinical nodal staging to assess the risk of local recurrence after rectal cancer resection: A nationwide cross-sectional study. Colorectal Disease, 27(10), Article e70257. https://doi.org/10.1111/codi.70257

Agrotis, G., Pooch, E. P., Marsitopoulos, K., Vlychou, M., Benndorf, M., Beets-Tan, R. G. H., & Schoots, I. G. (2025). Detection rates for prostate cancer using PI-RADS 2.1 upgrading rules in transition zone lesions align with risk assessment categories: a systematic review and meta-analysis. European Radiology, 35(10), 6454-6465. https://doi.org/10.1007/s00330-025-11618-w

Prata, I., Tanaka, M. D., Glimelius, B., Nagtegaal, I. D., Beets-Tan, R. G. H., Blomqvist, L. K., Couwenberg, A. M., van Etten, B., Hospers, G. A. P., Meershoek-Klein Kranenbarg, E., Peeters, K. C. M. J., Putter, H., Roodvoets, A. G. H., van de Velde, C. J. H., Nilsson, P. J., & Marijnen, C. A. M. (2025). Factors influencing locoregional recurrence rates in locally advanced rectal cancer after total neoadjuvant treatment versus chemoradiotherapy in the RAPIDO trial. British Journal of Surgery, 112(9), Article znaf190. https://doi.org/10.1093/bjs/znaf190

Beets, N. R. A., Verheij, F. S., Williams, H., Omer, D. M., Lin, S. T., Qin, L.-X., Beets, G. L., Beets-Tan, R. G. H., Wei, I. H., Widmar, M., Pappou, E. P., Weiser, M. R., Nash, G. M., Smith, J. J., Paty, P. B., Miranda, J., Kim, T.-H., Gollub, M. J., & Garcia-Aguilar, J. (2025). Association of Lateral Pelvic Lymph Nodes with Disease Recurrence and Organ Preservation in Patients with Distal Rectal Adenocarcinoma Treated with Total Neoadjuvant Therapy. Annals of Surgery, 282(2), 311-318. https://doi.org/10.1097/SLA.0000000000006305

Shkurti, J., van den Berg, K., Tissier, R. L. M., van der Mierden, S., Lahaye, M. J., Beets-Tan, R. G. H., & Nederend, J. (2025). Diagnostic accuracy of CT for identifying high-risk colon cancer: a systematic review and meta-analysis. European Radiology. https://doi.org/10.1007/s00330-025-11844-2

Rostami, S., Stutterheim, H. W., Maxouri, O., Willemse, J. R. J., Sanchez, D. I. R., Schats, W., van Golen, L. W., Vollebergh, M. A., Cheung, Z., Vogel, W. V., Marchetti, S., Snaebjornsson, P., Lahaye, M. J., Lambregts, D. M. J., Bodalal, Z., & Beets-Tan, R. G. H. (2025). Imaging of cancer of unknown primary: a systematic literature review of the past, present, and future. British Journal of Radiology, 98(1172), 1209-1226. Article tqaf039. https://doi.org/10.1093/bjr/tqaf039

Goedegebuure, E. P., Lahaye, M. J., Bogveradze, N., El Khababi, N., van Griethuysen, J. J. M., Khmelinksii, A., Maas, M., Beets-Tan, R. G. H., & Lambregts, D. M. J. (2025). Advancing MRI diagnostic practices in rectal cancer: exploring the impact of web-based multi-reader study participation. Abdominal Radiology. Advance online publication. https://doi.org/10.1007/s00261-025-05104-6

Yeghaian, M., Piek, M. W., Bartels-Rutten, A., Abdelatty, M. A., Herrero-Huertas, M., Vogel, W. V., de Boer, J. P., Hartemink, K. J., Bodalal, Z., Beets-Tan, R. G. H., Trebeschi, S., & van der Ploeg, I. M. C. (2025). Malignancy classification of thyroid incidentalomas using 18F-fluorodeoxy-d-glucose PET/computed tomography-derived radiomics. Nuclear Medicine Communications, Article 02031. Advance online publication. https://doi.org/10.1097/MNM.0000000000002031

Selenica, P., Dopeso, H., Repetto, M., Basili, T., Gazzo, A. M., Schwartz, C. J., Derakhshan, F., Marra, A., Ferrando, L., Beets-Tan, R. G. H., Wen, Y. H., Ross, D. S., Brogi, E., Zhang, H., Norton, L., Chandarlapaty, S., Razavi, P., Mandelker, D., Reis-Fiho, J. S., ... Pareja, F. (2025). Genomic landscape of breast cancer in elderly patients. npj Breast Cancer, 11(1), Article 70. https://doi.org/10.1038/s41523-025-00781-4

Ursprung, S., Agrotis, G., van Houdt, P. J., Ter Beek, L. C., Boellaard, T. N., Beets-Tan, R. G. H., Yakar, D., Padhani, A. R., & Schoots, I. G. (2025). Prostate MRI Using Deep Learning Reconstruction in Response to Cancer Screening Demands-A Systematic Review and Meta-Analysis. Journal of Personalized Medicine, 15(7), Article 284. https://doi.org/10.3390/jpm15070284