Romero Alcocer, Dorian A. (2023) Estudio de biomarcadores de PSMA-PET/MR en la planificación de la radiocirugía estereotáctica de próstata / Study of PSMA-PET/MR biomarkers in the planning stereotactic prostate. Maestría en Física Médica, Universidad Nacional de Cuyo, Instituto Balseiro.
![[img]](/style/images/fileicons/application_pdf.png)
| PDF (Tesis) Español 17Mb |
Resumen en español
La radioterapia corporal estereotáctica (SBRT) con boost focal simultáneo, es una técnica que administra dosis elevadas en pocas fracciones a subvolúmenes dentro de un volumen objetivo, con la finalidad de mejorar el control tumoral sin aumentar la toxicidad en los OARs. El objetivo del presente trabajo se enfocó en estudiar la información anatómica, funcional y molecular que ofrecen las imágenes PET/MR con F"18-PSMA, para identificar las lesiones intraprostáticas, susceptibles de ser utilizadas para la delimitación de un boost en los tratamientos por SBRT. Para ello, se estudiaron 12 pacientes con diagnóstico de Cáncer de próstata, a los cuales se adicionó una secuencia experimental bajo un modelo de pseudo-difusión, con el fin de obtener información similar a las imágenes de perfusión sin la necesidad de inyectar un medio de contraste. Asimismo, se configuraron las secuencias de adquisición en los protocolos mpMRI y PET/MR, y se desarrolló un programa en Python para el procesamiento de las imágenes de la secuencia experimental planteada, el cual realiza un ajuste a la señal aplicando un algoritmo de tres pasos, segmenta automáticamente la imagen resultante para visualizar solo los tejidos de interés, y asigna UIDs para poder ser reconocido por el sistema de planificación bajo un formato DICOM. En este contexto, para la delimitación del boost en los tratamientos por SBRT se utilizaron biomarcadores que brinden información de la densidad celular, vascularización y del metabolismo del radiofármaco F"18-PSMA en la glándula prostática, los cuales fueron registrados y fusionados con las imágenes CT para simular los planes de tratamiento. El procedimiento para identificar las lesiones intraprostáticas mediante imágenes PET/MR mostró una ventaja clínica para la marcación del boost en los tratamientos SBRT. Además, con la aplicación de la secuencia de pseudo-difusión se pudieron obtener biomarcadores de perfusión para aquellos pacientes con insuficiencia renal o venas frágiles. Asimismo, en la simulación de planes SBRT con boost integrado, se logró administrar altas dosis a la lesión tumoral con una cobertura óptima de la glándula prostática, sin superar las restricciones de dosis en la mayoría de los OARs. Este estudio mostró la factibilidad de emplear la modalidad híbrida PET/MR en conjunto con los biomarcadores de pseudo-difusión, para la delimitación de un boost en la planificación por RT, cuya técnica tiene potencial para ser empleado como un nuevo estándar de tratamiento.
Resumen en inglés
Stereotactic Body Radiation Therapy (SBRT) with simultaneous focal boost is a technique delivering high doses in a few fractions to subvolumes within a target volume, aiming to improve tumor control without increasing toxicity in OARs. The aim of the present work was focused on studying the anatomical, functional, and molecular information offered by PET/MR images with F"18-PSMA, to identify intraprostatic lesions, susceptible to be used for the delimitation of a boost in SBRT treatments. For this purpose, 12 patients with a diagnosis of prostate cancer were studied, to which an experimental sequence was added under a pseudo-diffusion model, in order to obtain information similar to perfusion images without the need to inject a contrast medium. Likewise, the acquisition sequences were configured in the mpMRI and PET/MR protocols, and a Python program was developed to process the images of the proposed experimental sequence, which adjusts the signal by applying a three-step algorithm, automatically segments the resulting image to visualize only the tissues of interest and assigns UIDs to be recognized by the planning system under a DICOM format. In this context, biomarkers providing information on cell density, vascularization, and metabolism of the radiopharmaceutical F"18-PSMA in the prostate gland were utilized for boost delineation in SBRT treatments, which were registered and fused with CT images to simulate treatment plans. The procedure to identify intraprostatic lesions by PET-MR imaging showed a clinical advantage for boost tagging in SBRT treatments. Furthermore, the application of the pseudodiffusion sequence allowed the acquisition of perfusion biomarkers for patients with renal insufficiency or fragile veins. Likewise, in the simulation of SBRT plans with integrated boost, it was possible to administer high doses to the tumor lesion with optimal coverage of the prostate gland, without exceeding the dose restrictions in most of the OARs. This study highlights the feasibility of employing the hybrid PET/MR modality in conjunction with pseudo-diffusion biomarkers for boost delineation in RT planning, which technique has the potential to be employed as a new standard of treatment.
| Tipo de objeto: | Tesis (Maestría en Física Médica) |
|---|---|
| Palabras Clave: | Prostate; Próstata; Neoplasms; Neoplasma; Radiotherapy; Radioterapia; [Cancer; Cáncer; Biomarkers; Biomarcadores; PET/MR images; Imágenes PET/MR] |
| Referencias: | [1] Zaorsky, N. G., Harrison, A. S., Trabulsi, E. J., Gomella, L. G., Showalter, T. N., Hurwitz, M. D., et al. Evolution of advanced technologies in prostate cancer radiotherapy. Nature Reviews Urology, 10 (10), 565–579, 2013. URL https: //doi.org/10.1038/nrurol.2013.185. 1, 2 [2] Benedict, S. H., Yenice, K. M., Followill, D., Galvin, J. M., Hinson, W., Kavanagh, B., et al. Stereotactic body radiation therapy: The report of AAPM Task Group 101. Medical Physics, 37 (8), 4078–4101, 2010. URL https: //aapm.onlinelibrary.wiley.com/doi/abs/10.1118/1.3438081. 1, 2, 3, 39, 52 [3] Khan, F. M., Gibbons, J. P. Khan’s the physics of radiation therapy. Lippincott Williams & Wilkins, 2014. 1, 3 [4] Benitez, C. M., Steinberg, M. L., Cao, M., Qi, X. S., Lamb, J. M., Kishan, A. U., et al. MRI-Guided Radiation Therapy for Prostate Cancer: The Next Frontier in Ultrahypofractionation. Cancers, 15 (18), 4657, 2023. URL https://doi.org/ 10.3390/cancers15184657. 3, 4 [5] Draulans, C., Van der Heide, U., Haustermans, K., Pos, F., van Zyp, J., De Boer, H., et al. ’SBRT and the Boost’, a love story: primary endpoint analysis of the phase II hypo-FLAME trial. UroToday-GU Oncology Today. [En l´ınea], 2020. [Citado el 23 de octubre de 2023]. URL https://www. urotoday.com/recent-abstracts/urologic-oncology/prostate-cancer/ 122180-sbrt-and-the-boost-a-love-story-primary-endpoint-analysisof- the-phase-ii-hypo-flame-trial-beyond-the-abstract.html. 3, 4, 55 [6] Draulans, C., van der Heide, U. A., Haustermans, K., Pos, F. J., van Zyp, J. v. d. V., De Boer, H., et al. Primary endpoint analysis of the multicentre phase II hypo-FLAME trial for intermediate and high risk prostate cancer. Radiotherapy and Oncology, 147, 92–98, 2020. URL https://doi.org/10.1016/j.radonc. 2020.03.015. 3 [7] Draulans, C., De Roover, R., van der Heide, U. A., Haustermans, K., Pos, F., Smeenk, R. J., et al. Stereotactic body radiation therapy with optional focal lesion ablative microboost in prostate cancer: Topical review and multicenter consensus. Radiotherapy and Oncology, 140, 131–142, 2019. URL https://doi.org/10. 1016/j.radonc.2019.06.023. 4, 55 [8] Mannaerts, C. K. Novel pathways in the diagnosis of prostate cancer. Tesis Doctoral, Universiteit van Amsterdam, 2021. URL https://hdl.handle.net/ 11245.1/0b0e478e-0afe-488e-8738-1ba17c315861. 4, 5, 6 [9] Wilson, A. The prostate gland: a review of its anatomy, pathology, and treatment. JAMA, 312 (5), 562–562, 2014. URL https://doi.org/10.1001/jama.2013. 279650. 5 [10] Bhavsar, A., Verma, S. Anatomic imaging of the prostate. BioMed research international, 2014, 1–9, 2014. ID 728539. URL https://doi.org/10.1155/ 2014/728539. 4, 29 [11] Hall, J. E. Guyton & Hall. Tratado de fisiología médica (14th ed.). Elsevier Health Sciences, 2021. 5 [12] Gross, A. J. Anatomy of the Prostate, págs. 9–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2023. URL https://doi.org/10.1007/978-3-662-67057-6_ 2. 5, 29 [13] Saladin, K. S., Porth, C. Anatomy & physiology: the unity of form and function, tomo 5. McGraw-Hill New York, 2010. 5 [14] Instituto Nacional del Cáncer. Significado de los cambios en la próstata: Guía de salud para los hombres. [En línea]. [Citado el 12 de agosto de 2023]. URL https://www.cancer.gov/espanol/tipos/prostata/ significado-cambios-en-la-prostata. 5, 6 [15] Grossman, S. C., Mattson Porth, C. Porth fisiopatología: alteraciones de la salud; conceptos básicos. Wolters Kluwer, 2014. 5, 6 [16] Giona, S. The epidemiology of prostate cancer. Exon Publications, págs. 1–15, 2021. URL https://doi.org/10.36255/exonpublications.prostatecancer. epidemiology.2021. 6 [17] Johnson, L. M., Turkbey, B., Figg, W. D., Choyke, P. L. Multiparametric MRI in prostate cancer management. Nature reviews Clinical oncology, 11 (6), 346–353, 2014. URL https://doi.org/10.1038/nrclinonc.2014.69. 6, 13, 18, 19, 30, 31 [18] Hernando, C. G., Esteban, L., Cañas, T., Van den Brule, E., Pastrana, M. The role of magnetic resonance imaging in oncology. Clinical and Translational Oncology, 12, 606–613, 2010. URL https://doi.org/10.1007/s12094-010-0565-x. 7 [19] Brown, R. W., Cheng, Y.-C. N., Haacke, E. M., Thompson, M. R., Venkatesan, R. Magnetic resonance imaging: physical principles and sequence design. John Wiley & Sons, 2014. 7, 9, 10, 11, 12, 16 [20] Ancari, L. Simulaci´on de radiocirug´ıa craneal estereot´actica guiada por resonancia magn´etica funcional. Maestr´ıa en f´ısica m´edica, Universidad Nacional de Cuyo, Instituto Balseiro, 2022. 7, 11, 12, 35 [21] Dance, D., Christofides, S., Maidment, A., McLean, I., Ng, K. Diagnostic radiology physics. International Atomic Energy Agency, 299, 2014. 7, 8, 9, 10, 11, 12 [22] McRobbie, D. W., Moore, E. A., Graves, M. J., Prince, M. R. MRI from Picture to Proton. Cambridge University Press, 2017. 8, 9, 10, 11, 13, 15, 16, 18, 19, 20, 21, 22 [23] Albella Héctor, I. Análisis y aplicación de The Bloch Simulator como herramienta didáctica para el estudio interactivo de los principios físicos de la Resonancia Magn´etica Nuclear. Tesis fin de grado en ingeniería biomédica, Universitat Polit` ecnica de Val`encia, 2016. 8, 10 [24] González, T. Implementación de secuencias de pseudo-difusión en el protocolo multiparamétrico por resonancia magnética para el cáncer de próstata. Bioingenier ´ıa, Universidad de Mendoza, 2023. 8, 10, 11, 12, 17, 40 [25] Martínez, A. Espectroscopías de resonancia magnética III. La mecánica cuántica. [En línea]. [Citado el 19 de agosto de 2023]. URL http://la-mecanica-cuantica.blogspot.com/2009/08/ espectroscopias-de-resonancia-iii.html. 8, 9 [26] Bloch, F. Nuclear induction. Physical review, 70 (7-8), 460, 1946. URL https: //doi.org/10.1103/PhysRev.70.460. 9 [27] Elster, A. Spin echo (SE). [En línea]. [Citado el 20 de agosto de 2023]. URL https://mriquestions.com/spin-echo1.html. 11 [28] Winston, G. P. The physical and biological basis of quantitative parameters derived from diffusion MRI. Quantitative imaging in medicine and surgery, 2 (4), 254, 2012. URL https://doi.org/10.3978/j.issn.2223-4292.2012.12.05. 11, 13, 15, 16, 17, 18 [29] Elster, A. Gradient echo (GE). [En línea]. [Citado el 20 de agosto de 2023]. URL https://mriquestions.com/gradient-echo.html. 12 [30] Elster, A. Parameter ”weighting”. [En línea]. [Citado el 21 de agosto de 2023]. URL https://mriquestions.com/meaning-of-weighting.html. 12 [31] Murphy, G., Haider, M., Ghai, S., Sreeharsha, B. The expanding role of MRI in prostate cancer. AJR Am J Roentgenol, 201 (6), 1229–1238, 2013. URL https: //doi.org/10.2214/AJR.12.10178. 12, 30, 31 [32] Caruyer, E. IRM de diffusion du Q-space: Acquisition et pr´e-traitements. Medical imaging, Universit´e Nice Sophia Antipolis, 2012. URL https://theses.hal. science/tel-00750144/. 13, 15, 16, 17 [33] Mukherjee, P., Berman, J., Chung, S. W., Hess, C., Henry, R. Diffusion tensor MR imaging and fiber tractography: theoretic underpinnings. American journal of neuroradiology, 29 (4), 632–641, 2008. URL https://doi.org/10.3174/ajnr. A1051. 13, 14, 15, 18, 19 [34] Einstein, A. Investigations on the Theory of the Brownian Movement. Courier Corporation, 1956. 13, 14, 15 [35] Wikipedia. Brownian motion. Wikipedia, the free encyclopedia. [En línea], 2023. [Citado el 31 de agosto de 2023]. URL https://en.wikipedia.org/wiki/ Brownian_motion. 13, 14, 15 [36] Quantpie. Brownian Motion: Introduction, Visualisation, and History including Brown, Einstein, and Wiener. [Video], 2018. [Citado el 31 de agosto de 2023]. URL https://www.youtube.com/watch?v=6EHzu-nyTyk. 14 [37] Quantpie. Diffusion Equation - Derivation and Explanation using Brownian. [Video], 2018. [Citado el 1 de septiembre de 2023]. URL https://www.youtube. com/watch?v=P9qar8mv3Tk. 14, 15 [38] Bryant, D., Payne, J., Firmin, D. N., Longmore, D. B. Measurement of flow with NMR imaging using a gradient pulse and phase difference technique. J Comput Assist Tomogr, 8 (4), 588–593, 1984. URL https://doi.org/10.1097/ 00004728-198408000-00002. 16, 17 [39] Young, H. D., Freedman, R. A., Ford, A. L. Sears y Zemansky F´ısica Universitaria con F´ısica Moderna 1. 14va edici´on. Pearson, 2018. 16 [40] Elster, A. Exponential ADC. [En línea]. [Citado el 3 de septiembre de 2023]. URL https://mriquestions.com/exponential-adc.html. 18 [41] Manenti, G., Nezzo, M., Chegai, F., Vasili, E., Bonanno, E., Simonetti, G., et al. DWI of prostate cancer: optimal-value in clinical practice. Prostate Cancer, 2014, 2014. URL https://doi.org/10.1155/2014/868269. 18, 30 [42] Ogura, A., Hatano, I., Osakabe, K., Yamaguchi, N., Koyama, D., Watanabe, H. Importance of fractional b value for calculating apparent diffusion coefficient in DWI. American Journal of Roentgenology, 207 (6), 1239–1243, 2016. URL https: //doi.org/10.2214/AJR.15.1594. 18, 19 [43] Cuenod, C., Balvay, D. Perfusion and vascular permeability: basic concepts and measurement in DCE-CT and DCE-MRI. Diagnostic and interventional imaging, 94 (12), 1187–1204, 2013. URL https://doi.org/10.1016/j.diii.2013.10. 010. 19, 20 [44] Ram´ırez, J. Implementación de estudio multiparamétrico de próstata con secuencias de Intravoxel Incoherent Motion y Elastograf´ıa por Resonancia Magn´etica. Maestr´ıa en f´ısica m´edica, Universidad Nacional de Cuyo, Instituto Balseiro, 2017. 19, 20, 31, 63 [45] Saraví, F., Salvarredi, L. Radiobiología. Maestría en Física Médica, Instituto Balseiro., 2012. 19, 21 [46] Folkman, J. Tumor angiogenesis: therapeutic implications. New england journal of medicine, 285 (21), 1182–1186, 1971. URL https://doi.org/10.1056/ NEJM197111182852108. 19, 21 [47] Villringer, A., Rosen, B. R., Belliveau, J. W., Ackerman, J. L., Lauffer, R. B., Buxton, R. B., et al. Dynamic imaging with lanthanide chelates in normal brain: contrast due to magnetic susceptibility effects. Magnetic resonance in medicine, 6 (2), 164–174, 1988. URL https://doi.org/10.1002/mrm.1910060205. 20 [48] Le Bihan, D., Breton, E., Lallemand, D., Grenier, P., Cabanis, E., Laval-Jeantet, M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology, 161 (2), 401–407, 1986. URL https: //doi.org/10.1148/radiology.161.2.3763909. 20, 23 [49] Detre, J. A., Zhang, W., Roberts, D. A., Silva, A. C., Williams, D. S., Grandis, D. J., et al. Tissue specific perfusion imaging using arterial spin labeling. NMR in Biomedicine, 7 (1-2), 75–82, 1994. URL https://doi.org/10.1002/ nbm.1940070112. 20 [50] Lausch, A. Nonrigid registration of dynamic contrast-enhanced MRI data using motion informed intensity corrections. Master of science graduate department of medical biophysics, University of Toronto Toronto, 2011. 20, 21, 22, 23, 31, 32 [51] O’Connor, J. P., Jackson, A., Parker, G. J., Jayson, G. C. DCE-MRI biomarkers in the clinical evaluation of antiangiogenic and vascular disrupting agents. British journal of cancer, 96 (2), 189–195, 2007. URL https://doi.org/10.1038/sj. bjc.6603515. 20, 21 [52] Khalifa, F., Soliman, A., El-Baz, A., Abou El-Ghar, M., El-Diasty, T., Gimel’farb, G., et al. Models and methods for analyzing DCE-MRI: A review. Medical physics, 41 (12), 124301, 2014. URL https://doi.org/10.1118/1.4898202. 21, 22 [53] Tofts, P. S., Brix, G., Buckley, D. L., Evelhoch, J. L., Henderson, E., Knopp, M. V., et al. Estimating kinetic parameters from dynamic contrast-enhanced T1-weighted MRI of a diffusable tracer: standardized quantities and symbols. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine, 10 (3), 223–232, 1999. URL https://doi.org/10.1002/(sici)1522-2586(199909)10:3<223:: aid-jmri2>3.0.co;2-s. 22, 23 [54] Yang, X., Knopp, M. V., et al. Quantifying tumor vascular heterogeneity with dynamic contrast-enhanced magnetic resonance imaging: a review. BioMed Research International, 2011, 2011. URL https://doi.org/10.1155/2011/732848. 22 [55] Le Bihan, D., Breton, E., Lallemand, D., Aubin, M.-L., Vignaud, J., Laval-Jeantet, M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology, 168 (2), 497–505, 1988. URL https://doi.org/10.1148/ radiology.168.2.3393671. 23, 24, 25 [56] Le Bihan, D., Iima, M., Federau, C., Sigmund, E. E. Intravoxel incoherent motion (IVIM) MRI: principles and applications. CRC Press, 2018. 23, 24, 25, 26, 27, 28, 44, 59 [57] ISMRM-ISMRT. ISMRM MR Academy – Introduction to IVIM. [Video], 2018. [Citado el 19 de septiembre de 2023]. URL https://www.youtube.com/watch?v= yluL093GMMA&list=PLzr-3nW8-EouP1JrfdC3BtmNMMjo8B78K&index=2&t=778s. 23, 24, 25, 26, 44, 59 [58] Le Bihan, D. Magnetic resonance imaging of perfusion. Magnetic resonance in medicine, 14 (2), 283–292, 1990. URL https://doi.org/10.1002/mrm.1910140213. 24, 25 [59] Le Bihan, D., Turner, R. The capillary network: a link between IVIM and classical perfusion. Magnetic resonance in medicine, 27 (1), 171–178, 1992. URL https: //doi.org/10.1002/mrm.1910270116. 26 [60] Elster, A. Diffusion kurtosis imaging. [En l´ınea]. [Citado el 20 de septiembre de 2023]. URL https://mriquestions.com/diffusion-kurtosis.html. 26, 27 [61] Jensen, J. H., Helpern, J. A., Ramani, A., Lu, H., Kaczynski, K. Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 53 (6), 1432–1440, 2005. URL https://doi.org/10.1002/mrm.20508. 26, 27, 45 [62] Iima, M., Le Bihan, D. Clinical intravoxel incoherent motion and diffusion MR imaging: past, present, and future. Radiology, 278 (1), 13–32, 2016. URL https: //doi.org/10.1148/radiol.2015150244. 26, 27 [63] Jensen, J. H., Helpern, J. A. MRI quantification of non-gaussian water diffusion by kurtosis analysis. NMR in Biomedicine, 23 (7), 698–710, 2010. URL https: //doi.org/10.1002/nbm.1518. 26, 28 [64] American College of Radiology Committee on PI-RADS (Prostate). Prostate imaging reporting and data system version 2.1, 2019. URL https://www.acr. org/-/media/ACR/Files/RADS/PI-RADS/PIRADS-V2-1.pdf. 29, 30, 31 [65] Barbosa, F. d. G., Queiroz, M. A., Nunes, R. F., Marin, J. F. G., Buchpiguel, C. A., Cerri, G. G. Clinical perspectives of PSMA PET/MRI for prostate cancer. Clinics, 73, 2018. URL https://doi.org/10.6061/clinics/2018/e586s. 32, 33, 77 [66] Hicks, R. M., Simko, J. P., Westphalen, A. C., Nguyen, H. G., Greene, K. L., Zhang, L., et al. Diagnostic accuracy of 68Ga-PSMA-11 PET/MRI compared with multiparametric MRI in the detection of prostate cancer. Radiology, 289 (3), 730–737, 2018. URL https://doi.org/10.1148/radiol.2018180788. 32, 33, 77 [67] Priv´e, B. M., Isra¨el, B., Schilham, M. G., Muselaers, C. H., Z´amecnik, P., Mulders, P. F., et al. Evaluating F-18-PSMA-1007-PET in primary prostate cancer and comparing it to multi-parametric MRI and histopathology. Prostate cancer and prostatic diseases, 24 (2), 423–430, 2021. URL https://doi.org/10.1038/ s41391-020-00292-2. 32, 33 [68] Veit-Haibach, P., Ahlstr¨om, H., Boellaard, R., Delgado Bolton, R. C., Hesse, S., Hope, T., et al. International EANM-SNMMI-ISMRM consensus recommendation for PET/MRI in oncology. European journal of nuclear medicine and molecular imaging, p´ags. 1–25, 2023. 33, 42, 77 [69] Giesel, F. L., Hadaschik, B., Cardinale, J., Radtke, J., Vinsensia, M., Lehnert, W., et al. F-18 labelled PSMA-1007: biodistribution, radiation dosimetry and histopathological validation of tumor lesions in prostate cancer patients. European journal of nuclear medicine and molecular imaging, 44, 678–688, 2017. URL https://doi.org/10.1007/s00259-016-3573-4. 34 [70] Innolitics. DICOM Standard Browser. Dicom Innolitics. [En línea], 2023. [Citado el 24 de octubre de 2023]. URL https://dicom.innolitics.com/ciods. 34, 35 [71] NEMA. Creating a Privately Defined Unique Identifier. Dicom NEMA. [En l´ınea], 2023. [Citado el 25 de octubre de 2023]. URL https://dicom.nema.org/dicom/ 2013/output/chtml/part05/chapter_B.html. 35, 36 [72] GE Healthcare. SIGNA PET/MR. Technical data, U.S.A., 2014. Págs.: A.1-A7. 37 [73] Mugneco, A. Dose Painting en cáncer de próstata a través de imágenes simult áneas PET/MR C11-Colina y multiparamétrico MR. Maestría en física médica, Universidad Nacional de Cuyo, Instituto Balseiro, 2017. 42 [74] GE Healthcare. GenIQ. User guide, U.S.A., 2019. 50 [75] Zhao, Y., Haworth, A., Rowshanfarzad, P., Ebert, M. A. Focal Boost in Prostate Cancer Radiotherapy: A Review of Planning Studies and Clinical Trials. Cancers, 15 (19), 2023. URL https://www.mdpi.com/2072-6694/15/19/4888. 55 |
| Materias: | Física > Física médica Medicina > Oncología |
| Divisiones: | FUESMEN Gcia. de área de Investigación y aplicaciones no nucleares > Gcia. de Física > Ciencias de materiales > Resonancias magnéticas |
| Código ID: | 1231 |
| Depositado Por: | Marisa G. Velazco Aldao |
| Depositado En: | 21 Mar 2024 12:52 |
| Última Modificación: | 21 Mar 2024 12:52 |
Personal del repositorio solamente: página de control del documento
