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444 results on '"Thorwarth, D."'

1. Adaptive radiotherapy for breast cancer

Author

De-Colle, C., Kirby, A., Russell, N., Shaitelman, S.F., Currey, A., Donovan, E., Hahn, E., Han, K., Anandadas, C.N., Mahmood, F., Lorenzen, E.L., van den Bongard, D., Groot Koerkamp, M.L., Houweling, A.C., Nachbar, M., Thorwarth, D., and Zips, D.

Published
2023
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5. Introducing FDG PET/CT-guided chemoradiotherapy for stage III NSCLC in low- and middle-income countries: preliminary results from the IAEA PERTAIN trial

Author

Konert, T., Vogel, W. V., Paez, D., Polo, A., Fidarova, E., Carvalho, H., Duarte, P. S., Zuliani, A. C., Santos, A. O., Altuhhova, D., Karusoo, L., Kapoor, R., Sood, A., Khader, J., Al-Ibraheem, A., Numair, Y., Abubaker, S., Soydal, C., Kütük, T., Le, T. A., Canh, N. X., Bieu, B. Q., Ha, L. N., Belderbos, J. S. A., MacManus, M. P., Thorwarth, D., and Hanna, G. G.

Published
2019
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11. Adaptive radiotherapy for breast cancer

Author

Experimentele klinische fysica, Cancer, Klinische Fysica RT, De-Colle, C, Kirby, A, Russell, N, Shaitelman, S F, Currey, A, Donovan, E, Hahn, E, Han, K, Anandadas, C N, Mahmood, F, Lorenzen, E L, van den Bongard, D, Groot Koerkamp, M L, Houweling, A C, Nachbar, M, Thorwarth, D, Zips, D, Experimentele klinische fysica, Cancer, Klinische Fysica RT, De-Colle, C, Kirby, A, Russell, N, Shaitelman, S F, Currey, A, Donovan, E, Hahn, E, Han, K, Anandadas, C N, Mahmood, F, Lorenzen, E L, van den Bongard, D, Groot Koerkamp, M L, Houweling, A C, Nachbar, M, Thorwarth, D, and Zips, D

Published
2023

12. Correction to: Value of PET imaging for radiation therapy

Author

Lapa, C., Nestle, U., Albert, N. L., Baues, C., Beer, A., Buck, A., Budach, V., Bütof, R., Combs, S. E., Derlin, T., Eiber, M., Fendler, W. P., Furth, C., Gani, C., Gkika, E., Grosu, A.-L., Henkenberens, C., Ilhan, H., Löck, S., Marnitz-Schulze, S., Miederer, M., Mix, M., Nicolay, N. H., Niyazi, M., Pöttgen, C., Todica, A. S., Weber, W., Wegen, S., Wiegel, T., Zamboglou, C., Zips, D., Zöphel, K., Zschaeck, S., Thorwarth, D., (0000-0001-9550-9050) Troost, E. G. C., Lapa, C., Nestle, U., Albert, N. L., Baues, C., Beer, A., Buck, A., Budach, V., Bütof, R., Combs, S. E., Derlin, T., Eiber, M., Fendler, W. P., Furth, C., Gani, C., Gkika, E., Grosu, A.-L., Henkenberens, C., Ilhan, H., Löck, S., Marnitz-Schulze, S., Miederer, M., Mix, M., Nicolay, N. H., Niyazi, M., Pöttgen, C., Todica, A. S., Weber, W., Wegen, S., Wiegel, T., Zamboglou, C., Zips, D., Zöphel, K., Zschaeck, S., Thorwarth, D., and (0000-0001-9550-9050) Troost, E. G. C.

Abstract

Correction to: Strahlenther Onkol 2021 https://doi.org/10.1007/s00066-021-01812-2

Published
2022

24. SP-0690 How did the first wave affect medical physics practice in Europe? ESTRO survey

Author

Bertholet, J., primary, Aznar, M., additional, Garibaldi, C., additional, Thwaites, D., additional, Gershvevitsh, E., additional, Thorwarth, D., additional, Verellen, D., additional, Heijmen, B., additional, Hurkmans, C., additional, Muren, L., additional, Røe Redalen, K., additional, Siebert, F., additional, Schwarz, M., additional, Van Elmpt, W., additional, Georg, D., additional, Jornet, N., additional, and Clark, C., additional

Published
2021
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26. Integration of quantitative imaging biomarkers in clinical trials for MR-guided radiotherapy: Conceptual guidance for multicentre studies from the MR-Linac Consortium Imaging Biomarker Working Group

Author

Houdt, Petra J. van, Saeed, Hina, Thorwarth, D., Fuller, Clifton D., Hall, W.A., McDonald, Brigid A., Keesman, R., Wetscherek, A., Heide, Uulke A. van der, Houdt, Petra J. van, Saeed, Hina, Thorwarth, D., Fuller, Clifton D., Hall, W.A., McDonald, Brigid A., Keesman, R., Wetscherek, A., and Heide, Uulke A. van der

Abstract

Contains fulltext : 236891.pdf (Publisher’s version ) (Closed access)

Published
2021

27. Value of PET imaging for radiation therapy

Author

Lapa, C., Nestle, U., Albert, N., Baues, C., Beer, A., Buck, A., Budach, V., Bütof, R., Combs, S., Derlin, T., Eiber, M., Fendler, W., Furth, C., Gani, C., Gkika, E., Grosu, A., Henkenberens, C., Ilhan, H., Löck, S., Marnitz-Schulze, S., Miederer, M., Mix, M., Nicolay, N., Niyazi, M., Pöttgen, C., Rödel, C., Schatka, I., Schwarzenboeck, S., Todica, A., Weber, W., Wegen, S., Wiegel, T., Zamboglou, C., Zips, D., Zöphel, K., Zschaeck, S., Thorwarth, D., (0000-0001-9550-9050) Troost, E. G. C., Lapa, C., Nestle, U., Albert, N., Baues, C., Beer, A., Buck, A., Budach, V., Bütof, R., Combs, S., Derlin, T., Eiber, M., Fendler, W., Furth, C., Gani, C., Gkika, E., Grosu, A., Henkenberens, C., Ilhan, H., Löck, S., Marnitz-Schulze, S., Miederer, M., Mix, M., Nicolay, N., Niyazi, M., Pöttgen, C., Rödel, C., Schatka, I., Schwarzenboeck, S., Todica, A., Weber, W., Wegen, S., Wiegel, T., Zamboglou, C., Zips, D., Zöphel, K., Zschaeck, S., Thorwarth, D., and (0000-0001-9550-9050) Troost, E. G. C.

Abstract

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.

Published
2021

29. ADC measurements on the Unity MR-linac - A recommendation on behalf of the Elekta Unity MR-linac consortium

Author

Kooreman, E.S., Houdt, P.J., Keesman, R., Pos, F.J., Pelt, V.W.J. van, Nowee, M.E., Wetscherek, A., Tijssen, R.H.N., Philippens, M.E., Thorwarth, D., Wang, J, Shukla-Dave, A., Hall, W.A., Paulson, E.S., Heide, U.A. van der, Kooreman, E.S., Houdt, P.J., Keesman, R., Pos, F.J., Pelt, V.W.J. van, Nowee, M.E., Wetscherek, A., Tijssen, R.H.N., Philippens, M.E., Thorwarth, D., Wang, J, Shukla-Dave, A., Hall, W.A., Paulson, E.S., and Heide, U.A. van der

Abstract

Item does not contain fulltext, BACKGROUND AND PURPOSE: Diffusion-weighted imaging (DWI) for treatment response monitoring is feasible on hybrid magnetic resonance linear accelerator (MR-linac) systems. The MRI scanner of the Elekta Unity system has an adjusted design compared to diagnostic scanners. We investigated its impact on measuring the DWI-derived apparent diffusion coefficient (ADC) regarding three aspects: the choice of b-values, the spatial variation of the ADC, and scanning during radiation treatment. The aim of this study is to give recommendations for accurate ADC measurements on Unity systems. MATERIALS AND METHODS: Signal-to-noise ratio (SNR) measurements with increasing b-values were done to determine the highest bvalue that can be measured reliably. The spatial variation of the ADC was assessed on six Unity systems with a cylindrical phantom of 40 cm diameter. The influence of gantry rotation and irradiation was investigated by acquiring DWI images before and during treatment of 11 prostate cancer patients. RESULTS: On the Unity system, a maximum b-value of 500 s/mm(2) should be used for ADC quantification, as a trade-off between SNR and diffusion weighting. Accurate ADC values were obtained within 7 cm from the iso-center, while outside this region ADC values deviated more than 5%. The ADC was not influenced by the rotating linac or irradiation during treatment. CONCLUSION: We provide Unity system specific recommendations for measuring the ADC. This will increase the consistency of ADC values acquired in different centers on the Unity system, enabling large cohort studies for biomarker discovery and treatment response monitoring.

Published
2020

31. The Image Biomarker Standardization Initiative: standardized quantitative radiomics for highthroughput image-based phenotyping

Author

Zwanenburg, A., Vallières, M., Abdalah, M. A., Aerts, H. J. W. L., Andrearczyk, V., Apte, A., Ashrafinia, S., Bakas, S., Beukinga, R. J., Boellaard, R., Bogowicz, M., Boldrini, L., Buvat, I., Cook, G. J. R., Davatzikos, C., Depeursinge, A., Desseroit, M.-C., Dinapoli, N., Viet Dinh, C., Echegaray, S., El Naqa, I., Fedorov, A. Y., Gatta, R., Gillies, R. J., Goh, V., Guckenberger, M., Götz, M., Min Ha, S., Hatt, M., Isensee, F., Lambin, P., Leger, S., Leijenaar, R. T. H., Lenkowicz, J., Lippert, F., Losnegård, A., Maier-Hein, K. H., Morin, O., Müller, H., Napel, S., Nioche, C., Orlhac, F., Pati, S., Pfaehler, E. A. G., Rahmim, A., Rao, A. U. K., Scherer, J., Musib Siddique, M., Sijtsema, N. M., Socarras Fernandez, J., Spezi, E., Steenbakkers, R. J. H. M., Tanadini-Lang, S., Thorwarth, D., (0000-0001-9550-9050) Troost, E. G. C., Upadhaya, T., Valentini, V., V. Van Dijk, L., Griethuysen, J., Velden, F. H. P., Whybra, P., (0000-0003-4261-4214) Richter, C., Löck, S., Zwanenburg, A., Vallières, M., Abdalah, M. A., Aerts, H. J. W. L., Andrearczyk, V., Apte, A., Ashrafinia, S., Bakas, S., Beukinga, R. J., Boellaard, R., Bogowicz, M., Boldrini, L., Buvat, I., Cook, G. J. R., Davatzikos, C., Depeursinge, A., Desseroit, M.-C., Dinapoli, N., Viet Dinh, C., Echegaray, S., El Naqa, I., Fedorov, A. Y., Gatta, R., Gillies, R. J., Goh, V., Guckenberger, M., Götz, M., Min Ha, S., Hatt, M., Isensee, F., Lambin, P., Leger, S., Leijenaar, R. T. H., Lenkowicz, J., Lippert, F., Losnegård, A., Maier-Hein, K. H., Morin, O., Müller, H., Napel, S., Nioche, C., Orlhac, F., Pati, S., Pfaehler, E. A. G., Rahmim, A., Rao, A. U. K., Scherer, J., Musib Siddique, M., Sijtsema, N. M., Socarras Fernandez, J., Spezi, E., Steenbakkers, R. J. H. M., Tanadini-Lang, S., Thorwarth, D., (0000-0001-9550-9050) Troost, E. G. C., Upadhaya, T., Valentini, V., V. Van Dijk, L., Griethuysen, J., Velden, F. H. P., Whybra, P., (0000-0003-4261-4214) Richter, C., and Löck, S.

Abstract

Background: Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical usage. Purpose: To standardize a set of 174 radiomic features. Materials and Methods: Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, fifteen teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value: <3 matches: weak; 3-5: moderate; 6-9: strong; ≥10 very strong. In the final phase (III), a public dataset of multi-modality imaging (CT, 18F-FDG-PET and T1-weighted MR) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features.. Results: Consensus on reference values was initially weak for 232/302 (76.8%; phase I) and 703/1075 (65.4%; phase II) features. At the final iteration, weak consensus remained for only 2/487 (0.4%; phase I) and 19/1347 (1.4%; phase II) features, and strong or better consensus was achieved for 463/487 (95.1%; phase I) and 1220/1347 (90.6%; phase II). Overall, 169/174 features were standardized in the first two phases. In the final validation phase (III), almost all standardized features could be excellently reproduced: CT:166/169 features; PET:164/169 and MRI: 164/169. Conclusion: A set of 169 radiomics features was standardized, which enables verification and calibration of different radiomics software.

Published
2020

32. The image biomarker standardization initiative: Standardized quantitative radiomics for high-throughput image-based phenotyping

Author

Zwanenburg, A., Vallieres, M., Abdalah, M. A., Aerts, H. J. W. L., Andrearczyk, V., Apte, A., Ashrafinia, S., Bakas, S., Beukinga, R. J., Boellaard, R., Bogowicz, M., Boldrini, Luca, Buvat, I., Cook, G. J. R., Davatzikos, C., Depeursinge, A., Desseroit, M. -C., Dinapoli, Nicola, Dinh, C. V., Echegaray, S., El Naqa, I., Fedorov, A. Y., Gatta, Roberto, Gillies, R. J., Goh, V., Gotz, M., Guckenberger, M., Ha, S. M., Hatt, M., Isensee, F., Lambin, P., Leger, S., Leijenaar, R. T. H., Lenkowicz, Jacopo, Lippert, F., Losnegard, A., Maier-Hein, K. H., Morin, O., Muller, H., Napel, S., Nioche, C., Orlhac, F., Pati, S., Pfaehler, E. A. G., Rahmim, A., Rao, A. U. K., Scherer, J., Siddique, M. M., Sijtsema, N. M., Socarras Fernandez, J., Spezi, E., Steenbakkers, R. J. H. M., Tanadini-Lang, S., Thorwarth, D., Troost, E. G. C., Upadhaya, T., Valentini, Vincenzo, van Dijk, L. V., van Griethuysen, J., van Velden, F. H. P., Whybra, P., Richter, C., Lock, S., Boldrini L., Dinapoli N., Gatta R., Lenkowicz J., Valentini V. (ORCID:0000-0003-4637-6487), Zwanenburg, A., Vallieres, M., Abdalah, M. A., Aerts, H. J. W. L., Andrearczyk, V., Apte, A., Ashrafinia, S., Bakas, S., Beukinga, R. J., Boellaard, R., Bogowicz, M., Boldrini, Luca, Buvat, I., Cook, G. J. R., Davatzikos, C., Depeursinge, A., Desseroit, M. -C., Dinapoli, Nicola, Dinh, C. V., Echegaray, S., El Naqa, I., Fedorov, A. Y., Gatta, Roberto, Gillies, R. J., Goh, V., Gotz, M., Guckenberger, M., Ha, S. M., Hatt, M., Isensee, F., Lambin, P., Leger, S., Leijenaar, R. T. H., Lenkowicz, Jacopo, Lippert, F., Losnegard, A., Maier-Hein, K. H., Morin, O., Muller, H., Napel, S., Nioche, C., Orlhac, F., Pati, S., Pfaehler, E. A. G., Rahmim, A., Rao, A. U. K., Scherer, J., Siddique, M. M., Sijtsema, N. M., Socarras Fernandez, J., Spezi, E., Steenbakkers, R. J. H. M., Tanadini-Lang, S., Thorwarth, D., Troost, E. G. C., Upadhaya, T., Valentini, Vincenzo, van Dijk, L. V., van Griethuysen, J., van Velden, F. H. P., Whybra, P., Richter, C., Lock, S., Boldrini L., Dinapoli N., Gatta R., Lenkowicz J., and Valentini V. (ORCID:0000-0003-4637-6487)

Abstract

Background: Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose: To standardize a set of 174 radiomic features. Materials and Methods: Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results: Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion: A set of 169 radiomics features was standardized, which enabled ver

Published
2020

33. Professional quality of life and burnout among medical physicists working in radiation oncology: The role of alexithymia and empathy

Author

Di Tella, M, Tesio, V, Bertholet, J, Gasnier, A, Gonzalez del Portillo, E, Spalek, M, Bibault, JE, Borst, G, van Elmpt, W, Thorwarth, D, Mullaney, L, Røe Redalen, K, Dubois, L, Chargari, C, Perryck, S, Petit, Steven, Lybeer, M, Castelli, L, Franco, P, Di Tella, M, Tesio, V, Bertholet, J, Gasnier, A, Gonzalez del Portillo, E, Spalek, M, Bibault, JE, Borst, G, van Elmpt, W, Thorwarth, D, Mullaney, L, Røe Redalen, K, Dubois, L, Chargari, C, Perryck, S, Petit, Steven, Lybeer, M, Castelli, L, and Franco, P

Published
2020

47. OC-0593: Alexithymia, empathy and burn-out amongst RTTs: results from the PRO BONO survey

Author

Franco, P., primary, Tesio, V., additional, Bertholet, J., additional, Gasnier, A., additional, del Portillo, E. Gonzalez, additional, Spalek, M., additional, Bibault, J., additional, Borst, G., additional, Van Elmpt, W., additional, Thorwarth, D., additional, Mullaney, L., additional, Redalen, K. Roe, additional, Dubois, L., additional, Bittner, M., additional, Chargari, C., additional, Perryck, S., additional, Heukelom, J., additional, Petit, S., additional, Lybeer, M., additional, and Castelli, L., additional

Published
2020
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49. PH-0368: Alexithymia, empathy and burn-out amongst medical physicists: the PRO BONO survey

Author

Franco, P., primary, Tesio, V., additional, Bertholet, J., additional, Gasnier, A., additional, del Portillo, E. Gonzalez, additional, Spalek, M., additional, Bibault, J., additional, Borst, G., additional, Van Elmpt, W., additional, Thorwarth, D., additional, Mullaney, L., additional, Redalen, K. Roe, additional, Dubois, L., additional, Bittner, M., additional, Chargary, C., additional, Perryck, S., additional, Heukelom, J., additional, Petit, S., additional, Lybeer, M., additional, and Castelli, L., additional

Published
2020
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