Poma, Ana L. (2018) Delineación de volúmenes tumorales para planificación en RT a partir de imágenes hídricas con 18"F-FDG PET/CT. / RT planning tumor volume delineation from 18F-FDG PET/CT hybrid images. Maestría en Física Médica, Universidad Nacional de Cuyo, Instituto Balseiro.
![[img]](/style/images/fileicons/application_pdf.png)
| PDF (Tesis) Disponible bajo licencia Creative Commons: Reconocimiento - No comercial - Compartir igual. Español 28Mb |
Resumen en español
Las imágenes PET/CT han mostrado ser de gran utilidad en la estadificación de patologías neoplásicas. Conjuntamente, se han desarrollado técnicas mas precisas de irradiación, aumentando la precisión en la distribución de dosis de RT en lesiones tumorales así como en tejidos sanos. Esto genero interés en utilizar imágenes PET en la delineación del volumen tumoral, siendo usadas en la actualidad en diferentes centros de RT para la definición del volumen de tratamiento y/o el escalamiento de dosis dentro de la lesión. En el ultimo tiempo, se han desarrollado diferentes métodos de segmentación que permiten delinear volúmenes de tratamiento a partir de imágenes híbridas PET/CT, aunque aun no hay un consenso sobre las técnicas mas adecuadas para cada situación. En este trabajo se hizo un análisis de los distintos métodos propuestos y se evaluaron algunas de estas técnicas de segmentación. Para ello, se adquirieron imágenes FDG-PET/CT de fantasmas diseñados específicamente para este trabajo, que permiten el análisis de distribuciones de actividad no uniforme. Se analizaron además los mismos métodos de segmentación en lesiones correspondientes a imágenes clínicas de una paciente con cáncer de cérvix. El cáncer de cuello uterino, tiene una alta incidencia en América Latina y resulta de interés en la tomografía FDG-PET dado que la captación de FDG por vejiga es elevada, eclipsando muchas veces lesiones cercanas. Si bien los resultados obtenidos en este trabajo son preliminares, pueden servir para el desarrollo de herramientas que aporten a la delineación de volúmenes de tratamiento de RT de pacientes con diferentes patologías cancerígenas en nuestro país y en particular, en INTECNUS.
Resumen en inglés
PET/CT imaging has proven to be very useful in the staging of neoplastic pathologies. In recent years, radiotherapy techniques have improved dramatically, allowing us to deliver dose distributions with increased accuracy. This has led to an increasing interest in the potential use of PET/CT imaging as a tool for treatment volume contouring. Many centres are currently using PET/CT imaging for radiotherapy planning in order to dene treatment and/or dose escalation volumes. Although dierent segmentation methods do exist, there is still no consensus on the proper way to carry this out on PET/CT images. This project aimed to analyse some of the methods available. PET/CT images were obtained of specially designed phantoms, filled with 18"F-FDG. These images were then used to analyse non-uniform activity distributions. The same segmentation methods as had been used on the phantom images, were then used to analyse clinical images of one patient suffering from cervical cancer. Cervical cancer is of particular interest, as it has a high incidence rate in Latin America; optimisation of PET/CT images of these patients may be complicated by high bladder uptake, which may mask neighbouring lesions. Although the results obtained during this project are preliminary, they could possible be used in the future to develop tools to help delineate treatment volumes for patients undergoing radiotherapy for different pathologies, both here in Argentina and in INTECNUS.
| Tipo de objeto: | Tesis (Maestría en Física Médica) |
|---|---|
| Palabras Clave: | Tomography; Tomografía; [Hybrid PET-MRI tomography;Tomografía híbrida PET-MRI; Positrón emission tomography; Tomografía por emisión de positrones; Phantom design; Diseño de fantomas] |
| Referencias: | [1] Cima, S., Perrone, A. M., Castellucci, P., Macchia, G., Buwenge, M., Cammelli, S., et al. Prognostic Impact of Pretreatment Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography SUVmax in Patients With Locally Advanced Cervical Cancer. International Journal of Gynecological Cancer, 28(3), 575-580, 2018. DOI: https://doi.org/10.1097/igc.0000000000001207. 1, 5 [2] Soussan, M., Orlhac, F., Boubaya, M., Zelek, L., Ziol, M., Eder, V., et al. Relationship between Tumor Heterogeneity Measured on FDG-PET/CT and Pathological Prognostic Factors in Invasive Breast Cancer. PLoS ONE, 9(4), 1-7, e94017, 2014. DOI: https://doi.org/10.1371/journal.pone.0094017. 1 [3] Kalyanaraman, B. Teaching the basics of cancer metabolism: Developing antitumor strategies by exploiting the differences between normal and cancer cell metabolism. Redox Biology, 12(2017), 833-842, 2017. DOI: https://doi.org/10.1016/j.redox.2017.04.018. 3, 6 [4] Vander Heiden, M. G., Cantley, L. C., y Thompson, C. B. Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation. Science, 324(5930), 1029-1033, 2009. DOI: https://doi.org/10.1126/science.1160809. 3, 6 [5] Speirs, C. K., Grigsby, P. W., Huang, J., Thorstad, W. L., Parikh, P. J., Robinson, C. G., et al. PET-Based Radiation Therapy Planning. eCancer Medical Journal, 10(1), 27-44, 2015. DOI: https://doi.org/10.1016/j.cpet.2014.09.003. 6, 8, 52 [6] Hatt, M., Lee, J. A., Schmidtlein, C. R., Naqa, I. E., Caldwell, C., De Bernardi, E., et al. Classication and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211. Medical Physics, 44(6), e1-e42, 2017. DOI: https://doi.org/10.1002/mp.12124. 3, 4, 5, 6, 7, 12, 13, 14, 31 [7] Paesmans, M., Garcia, C., Wong, C.Y., Patz, E.F. Jr,, Komaki, R., Eschmann, S., et al. Classication and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211. European Respiratory Society, 46(6), 1751-1761, 2015. DOI: https://doi.org/10.1183/13993003.00099-2015. 4 57 [8] Yang, S.N., Chiou, Y.R., Zhang, G.G., Chou, K.T., y Huang, T.C. The clinical outcome correlations between radiation dose and pretreatment metabolic tumor volume for radiotherapy in head and neck cancer. Medicine, 96(26), 1-8, 2017. DOI: https://doi.org/10.1097/md.0000000000007186. 4 [9] Mu, W., Chen, Z., Liang, Y., Shen, W., Yang, F., Dai, R., et al. Staging of cervical cancer based on tumor heterogeneity characterized by texture features on 18FFDG PET images. Physics in Medicine and Biology, 60(13), 5123-5139, 2015. DOI: https://doi.org/10.1088/0031-9155/60/13/5123. 4, 33 [10] Hanahan, D., y Weinberg, R. A. Hallmarks of Cancer: The Next Generation. Cell, 144(5), 646-674, 2011. DOI: https://doi.org/10.1016/j.cell.2011.02.013. 4 [11] Orlhac, F., Soussan, M., Maisonobe, J.A., Garcia, C.A., Vanderlinden, B., y Buvat, I. Tumor texture analysis in 18F-FDG PET: relationships between texture parameters, histogram indices, standardized uptake values, metabolic volumes, and total lesion glycolysis. Journal of Nuclear Medicine, 55(3), 414-422, 2014. DOI:https://doi.org/10.2967/jnumed.113.129858. 4 [12] Verma, V., Choi, J. I., Sawant, A., Gullapalli, R. P., Chen, W., Alavi, A., et al. Use of PET and Other Functional Imaging to Guide Target Delineation in Radiation Oncology. Seminars in Radiation Oncology, 28(3), 171-177, 2018. DOI: https://doi.org/10.1016/j.semradonc.2018.02.001. 5, 8 [13] Narayan, K., Hicks, R. J., Jobling, T., Bernshaw, D., y Mckenzie, A. F. A comparison of MRI and PET scanning in surgically staged loco-regionally advanced cervical cancer: Potential impact on treatment. International Journal of Gynecological Cancer, 11(4), 263-271, 2001. PMID: https://www.ncbi.nlm.nih.gov/pubmed/11520363. 5 [14] Lazzari, R., Cecconi1, A., Jereczek-Fossa1, B. A., Travaini, L. L., Dell'Acqua1, V., Cattani, F., et al. The role of [18F]FDG-PET/CT in staging and treatment planning for volumetric modulated Rapidarc radiotherapy in cervical cancer: experience of the European Institute of Oncology, Milan, Italy. eCancer Medical Journal, 8(409), 1-11, 2014. DOI: https://doi.org/10.3332/ecancer.2014.409. 5, 32, 35 [15] Niyazi, M., Landrock, S., Elsner, A., Manapov, F., Hacker, M., Belka, C., et al. Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT. Radiation Oncology, 8(180), 1-7, 2013. DOI: https://doi.org/10.1186/1748-717x-8-180. 6, 10, 34, 35 [16] Kao, C. H., Hsieh, T. C., Yu, C. Y., Yen, K. Y., Yang, S. N., Wang, Y. C., et al. 18F-FDG PET/CT-based gross tumor volume denition for radiotherapy in head and neck Cancer: a correlation study between suitable uptake value threshold and tumor parameters. Radiation Oncology, 5(76), 1-8, 2010. DOI: https://doi.org/10.1186/1748-717x-5-76. 6, 7, 8, 9, 13, 34, 35 [17] The International Commission on Radiation Units and Measurements. 18-F-FDG PET/CT for planning external beam radiotherapy alters therapy in 11% of 581 patients. Journal of the ICRU, 10(1), 1-92, 2010. DOI: https://doi.org/10.1093/jicru/ndq001. 7 [18] Birk-Christensen, C., Loft-Jakobsen, A., Munck af Rosenschold, P., Hjgaard, L., Roed, H., y Berthelsen, A. K. 18-F-FDG PET/CT for planning external beam radiotherapy alters therapy in 11% of 581 patients. Clinical Physiology and Functional Imaging, 38(2), 278-284, 2017. DOI: https://doi.org/10.1111/cpf.12411. 7, 33 [19] Upasani, M. N., Mahantshetty, U. M., Rangarajan, V., Purandare, N., Merchant, N., Thakur, M., et al. 18-Fluoro-Deoxy-Glucose Positron Emission Tomography With Computed Tomography-Based Gross Tumor Volume Estimation and Validation With Magnetic Resonance Imaging for Locally Advanced Cervical Cancers. International Journal of Gynecological Cancer, 22(6), 1031-1036, 2012. DOI: https://doi.org/10.1097/igc.0b013e318251046b. 8, 34, 35 [20] Berthon, B., Marshall, C., Holmes, R., y Spezi, E. A novel phantom technique for evaluating the performance of PET auto-segmentation methods in delineating heterogeneous and irregular lesions. EJNMI Physics, 2(13), 1-17, 2015. DOI:https://doi.org/10.1186/s40658-015-0116-1. 13, 33 [21] Altazi, B. A., Zhang, G. G., Fernandez, D. C., Montejo, M. E., Hunt, D., Werner, J., et al. Reproducibility of F18-FDG PET radiomic features for different cervical tumor segmentation methods, gray-level discretization, and reconstruction algorithms. Journal of Applied Clinical Medical Physics, 18(6), 32-48, 2017. DOI:https://doi.org/10.1002/acm2.12170. 9, 32 [22] Oh, D., Huh, S. J., Park, W., Ju, S. G., Nam, H., y Lee, J. E. Clinical outcomes in cervical cancer patients treated by FDG-PET/CT-based 3-dimensional planning for the rst brachytherapy session. Medicine, 95(25), 1-7, 2016. DOI: https://doi.org/10.1097/md.0000000000003895. 8, 33 [23] Vees, H., Casanova, N., Zilli, T., Imperiano, H., Ratib, O., Popowski, Y., et al. Impact of 18F-FDG PET/CT on target volume delineation in recurrent or residual gynaecologic carcinoma. Radiation Oncology, 7(176), 1-7, 2012. DOI: https://doi.org/10.1186/1748-717x-7-176. 8, 34 [24] Geets, X., Tomsej, M., Lee, J. A., Duprez, T., Coche, E., Cosnard, G., et al. Adaptive biological image-guided IMRT with anatomic and functional imaging in pharyngo-laryngeal tumors: Impact on target volume delineation and dose distribution using helical tomotherapy. Radiotherapy and Oncology, 85(1), 105-115, 2007. DOI: https://doi.org/10.1016/j.radonc.2007.05.010. 8, 33, 35, 36 [25] Wu, V. W. C., Leung, W., Wong, K., Chan, Y., Law, W., Leung, W., et al. The impact of positron emission tomography on primary tumour delineation and dosimetric outcome in intensity modulated radiotherapy of early Tstage nasopharyngeal carcinoma. Radiation Oncology, 11(109), 1-7, 2016. DOI:https://doi.org/10.1186/s13014-016-0685-8. 8, 9, 33 [26] Dewalle-Vignion, A.-S., Betrouni, N., Baillet, C., y Vermandel, M. Is STAPLE algorithm condent to assess segmentation methods in PET imaging? Physics in Medicine and Biology, 60(24), 9473-9491, 2015. DOI: https://doi.org/10.1088/0031-9155/60/24/9473. 8, 13, 14, 33 [27] Bayne, M., Hicks, R. J., Everitt, S., Fimmell, N., Ball, D., Reynolds, J., et al. Reproducibility of "Intelligent" Contouring of Gross Tumor Volume in Non-Small-Cell Lung Cancer on PET/CT Images Using a Standardized Visual Method. Internatio- nal Journal of Radiation Oncology*Biology*Physics, 77(4), 1151-1157, 2010. DOI:https://doi.org/10.1016/j.ijrobp.2009.06.032. 9, 34, 35 [28] Nam, H., Huh, S. J., Ju, S. G., Park, W., Lee, J. E., Choi, J. Y., et al. 18F-fluorodeoxyglucose Positron Emisson Tomography/Computed Tomography Guided Conformal Brachytherapy for Cervical Cancer. International Journal of Radiation Oncology*Biology*Physics, 60(24), 9473-9491, 2012. DOI: https://doi.org/10. 1016/j.ijrobp.2012.02.055. 9, 33 [29] Bundschuh, R. A., Essler, M., Dinges, J., Berchtenbreiter, C., Mariss, J., Martínez- Moller, A., et al. Semiautomatic Algorithm for Lymph Node Analysis Corrected for Partial Volume Eects in Combined Positron Emission Tomography-Computed Tomography. Molecular Imaging, 9(6), 319-328, 2010. DOI: https://doi.org/10.2310/7290.2010.00019. 9, 34 [30] Zhang, G., Han, D., Ma, C., Lu, J., Sun, T., Liu, T., et al. Gradient-based delineation of the primary GTV on FLT PET in squamous cell cancer of the thoracic esophagus and impact on radiotherapy planning. Radiation Oncology, 10(11), 1-7, 2015. DOI: https://doi.org/10.1186/s13014-014-0304-5. 10, 33 [31] Bagade, S., Fowler, K. J., Schwarz, J. K., Grigsby, P. W., y Dehdashti, F. PET/MRI Evaluation of Gynecologic Malignancies and Prostate Cancer. Seminars in Nuclear Medicine, 45(4), 293-303, 2015. DOI: https://doi.org/10.1053/j.semnuclmed.2015.03.005. 10, 12 [32] van den Bosch, S., Dijkema, T., Kunze-Busch, M. C., Terhaard, C. H. J., Raaijmakers, C. P. J., Doornaert, P. A. H., et al. Uniform FDG-PET guided GRAdient Dose prEscription to reduce late Radiation Toxicity (UPGRADE-RT): study protocol for a randomized clinical trial with dose reduction to the elective neck in head and neck squamous cell carcinoma. BMC Cancer, 17(1), 7153-7168, 2017. DOI: https://doi.org/10.1186/s12885-017-3195-7. 10, 33 [33] Differding, S., Sterpin, E., Hermand, N., Vanstraelen, B., Nuyts, S., de Patoul, N., et al. Radiation dose escalation based on FDG-PET driven dose painting by numbers in oropharyngeal squamous cell carcinoma: a dosimetric comparison between TomoTherapy-HA and RapidArc. Radiation Oncology, 12(59), 1-10, 2017. DOI: https://doi.org/10.1186/s13014-017-0793-0. 10, 11, 33 [34] Reuzffe, S., Schernberg, A., Orlhac, F., Sun, R., Chargari, C., Dercle, L., et al. Radiomics in Nuclear Medicine Applied to Radiation Therapy: Methods, Pitfalls, and Challenges. International Journal of Radiation Oncology*Biology*Physics, 102(4), 1117-1142, 2018. DOI: https://doi.org/10.1016/j.ijrobp.2018.05.022. 10,11 [35] Parodi, K. Vision 20/20: Positron emission tomography in radiation therapy planning, delivery, and monitoring. Medical Physics, 42(12), 7153-7168, 2015. DOI:https://doi.org/10.1118/1.4935869. 11 [36] Clement, C. H. (editor). Realistic reference phantoms: An ICRP/ICRU joint effort. Annals of the ICRP, 39(2), 1-167, 2009. DOI: https://doi.org/10.1016/j.icrp.2009.09.001. 15 [37] Siewerdsen, J. H., Waese, A. M., Moseley, D. J., Richard, S., y Jafray, D. A. Spektr: A computational tool for x-ray spectral analysis and imaging system optimization. Medical Physics, 31(11), 3057-3067, 2004. DOI: https://doi.org/10.1118/1.1758350. xiii, 16, 17 [38] Boone, J. M., Brink, J. A., Edyvean, S., Huda, W., Leitz, W., McCollough, C. H., y McNitt-Gray, M. F. CT X-Ray-Spectrum Characterization. Journal of the ICRU, 12(1), 47-53, 2012. DOI: https://doi.org/10.1093/jicru/nds005. 17 [39] Kalfoglou, N. K., y Chafey, C. E. Effects of extrusion on the structure and properties of high-impact polystyrene. Polymer Engineering and Science, 19(8), 552-557, 1979. DOI: https://doi.org/10.1002/pen.760190805. 16 [40] Hamad, K., Kaseem, M., Yang, H. W., Deri, F., y Ko, Y. G. Properties and medical applications of polylactic acid: A review. Express Polymer Letters, 9(5), 435-455 2015. DOI: https://doi.org/10.3144/expresspolymlett.2015.42. [41] Dizon, J. R. C., Espera, A. H., Jr., Chen, Q., y Advincula, R. C. Mechanical characterization of 3D-printed polymers. Additive Manufacturing, 20, 44-67 2018. DOI: https://doi.org/10.1016/j.addma.2017.12.002. [42] Kumar, R., Sharma, S. D., Deshpande, S., Ghadi, Y., Shaiju, V.S., Amols, H.I., y Mayya, Y. S. Acrylonitrile Butadiene Styrene (ABS) plastic based low cost tissue equivalent phantom for verification dosimetry in IMRT. Journal of Applied Clinical Medical Physics, 11(1), 24-32 2009. PMID: https://www.ncbi.nlm.nih.gov/pubmed/20160681. [43] Ligon, S. C., Liska, R., Stamp, J., Gurr, M., y Mulhaupt, R. Polymers for 3D Printing and Customized Additive Manufacturing. Chemical Reviews, 117(15), 10212-10290 2017. DOI: https://doi.org/10.1021/acs.chemrev.7b00074. 16 [44] Seltzer, S. XCOM-Photon Cross Sections Database, NIST Standard Reference Database 8 [Data set]. National Institute of Standards and Technology, 117(15), 1987. DOI: https://doi.org/10.18434/t48g6x. 16, 17 [45] Feeman, T. G. The Mathematics of Medical Imaging. Springer Undergraduate Texts in Mathematics and Technology. Springer International Publishing, 117(15), 2015. DOI: https://doi.org/10.1007/978-3-319-22665-1. 16 [46] Simon R. Cherry, S. R., Sorenson, J. A., y Phelps, M. A. Capítulo 6: Interaction of Radiation with Matter. W.B. Saunders, Fourth Edition, 63-85 2012. DOI: https://doi.org/10.1016/B978-1-4160-5198-5.00006-X. 26 [47] Paulino, A. C., Koshy, M., Howell, R., Schuster, D., y Davis, L. W. Comparison of CT- and FDG-PET-dened gross tumor volume in intensity-modulated radiotherapy for head-and-neck cancer. International Journal of Radiation Oncology*Biology*Physics, 61(5), 1385-1392 2005. DOI: https://doi.org/10.1016/j.ijrobp.2004.08.037. 32, 35 [48] Miller, T. R., y Grigsby, P. W. Measurement of tumor volume by PET to evaluate prognosis in patients with advanced cervical cancer treated by radiation therapy. International Journal of Radiation Oncology*Biology*Physics, 53(2), 353-359 2002. DOI: https://doi.org/10.1016/S0360-3016(02)02705-0. 32, 35 [49] Ma, D. J., Zhu, J.-M., y Grigsby, P. W. Tumor volume discrepancies between FDGPET and MRI for cervical cancer. Radiotherapy and Oncology, 98(1), 139-142 2011. DOI: https://doi.org/10.1016/j.radonc.2010.10.004. 32 [50] Withofs, N., Bernard, C., van der Rest, C., Martinive, P., Hatt, M., Jodogne, S., et al. FDG PET/CT for rectal carcinoma radiotherapy treatment planning: comparison of functional volume delineation algorithms and clinical challenges. Journal of Applied Clinical Medical Physics, 15(5), 216-228 2014. DOI: https://doi.org/10.1120/jacmp.v15i5.4696. 32, 35 [51] Biehl, K.J., Kong, F.M., Dehdashti, F., Jin, J.Y., Mutic, S., El Naqa, I., et al. 18F-FDG PET denition of gross tumor volume for radiotherapy of non-small cell lung cancer: is a single standardized uptake value threshold approach appropriate? Journal of Nuclear Medicine, 47(11), 1808-1812 2006. PMID: https://www.ncbi.nlm.nih.gov/pubmed/17079814. 32, 35 [52] Chung, H. H., Cheon, G. J., Kim, J.-W., Park, N.-H., y Song, Y. S. Prognostic importance of lymph node-to-primary tumor standardized uptake value ratio in invasive squamous cell carcinoma of uterine cervix. European Journal of Nuclear Medicine and Molecular Imaging, 44(11), 1862-1869 2017. DOI: https://doi.org/10.1007/s00259-017-3729-x. 32, 35 [53] Daisne, J.-F., Sibomana, M., Bol, A., Doumont, T., Lonneux, M., y Gregoire, V. Tri-dimensional automatic segmentation of PET volumes based on measured source-to-background ratios: influence of reconstruction algorithms. Radiotherapy and Oncology, 69(3), 247-250 2003. DOI: https://doi.org/10.1016/s0167-8140(03)00270-6. 32, 35, 37, 38 [54] Schaefer, A., Kremp, S., Hellwig, D., Rube, C., Kirsch, C.-M., y Nestle, U. contrast-oriented algorithm for FDG-PET-based delineation of tumour volumes for the radiotherapy of lung cancer: derivation from phantom measurements and validation in patient data. A European Journal of Nuclear Medicine and Molecular Imaging, 35(11), 1989-1999 2008. DOI: https://doi.org/10.1007/s00259-008-0875-1. 32 [55] Hatt, M., Cheze Le Rest, C., Albarghach, N., Pradier, O., y Visvikis, D. PET functional volume delineation: a robustness and repeatability study. European Journal of Nuclear Medicine and Molecular Imaging, 38(4), 663-672 2011. DOI:https://doi.org/10.1007/s00259-010-1688-6. 32, 35 [56] Hoetjes, N. J., van Velden, F. H. P., Hoekstra, O. S., Hoekstra, C. J., Krak, N. C., Lammertsma, A. A., et al. Partial volume correction strategies for quantitative FDG PET in oncology. European Journal of Nuclear Medicine and Molecular Imaging, 37(9), 1679-1687 2010. DOI: https://doi.org/10.1007/s00259-010-1472-7. 32 [57] Kachnic, L. A., Winter, K., Myerson, R. J., Goodyear, M. D., Willins, J., Esthappan, J., et al. RTOG 0529: A Phase 2 Evaluation of Dose-Painted Intensity Modulated Radiation Therapy in Combination With 5-Fluorouracil and Mitomycin-C for the Reduction of Acute Morbidity in Carcinoma of the Anal Canal. International Journal of Radiation Oncology*Biology*Physics, 86(1), 27-33 2013. DOI: https://doi.org/10.1016/j.ijrobp.2012.09.023. 32 [58] Rusten, E., Rekstad, B. L., Undseth, C., Al-Haidari, G., Hanekamp, B., Hernes, E., et al. Target volume delineation of anal cancer based on magnetic resonance imaging or positron emission tomography. Radiation Oncology, 12(147), 1-8 2017. DOI: https://doi.org/10.1186/s13014-017-0883-z. 32 [59] Han, K., Croke, J., Foltz, W., Metser, U., Xie, J., Shek, T.,, et al. A prospective study of DWI, DCE-MRI and FDG PET imaging for target delineation in brachytherapy for cervical cancer. Radiotherapy and Oncology, 120(3), 519-525 2016. DOI: https://doi.org/10.1016/j.radonc.2016.08.002. 32 [60] Parlak, C., Topkan, E., Onal, C., Reyhan, M., y Selek, U. Prognostic value of gross tumor volume delineated by FDG-PET-CT based radiotherapy treatment planning in patients with locally advanced pancreatic cancer treated with chemoradiotherapy. Radiation Oncology, 7(37), 1-8 2012. DOI: https://doi.org/10.1186/1748-717x-7-37. 33 [61] Geets, X., Lee, J. A., Bol, A., Lonneux, M., y Gregoire, V. A gradient-based method for segmenting FDG-PET images: methodology and validation. European Journal of Nuclear Medicine and Molecular Imaging, 34(9), 1427-1438 2007. DOI:https://doi.org/10.1007/s00259-006-0363-4. 33, 35, 36 [62] El Naqa, I., Yang, D., Apte, A., Khullar, D., Mutic, S., Zheng, J., et al. Concurrent multimodality image segmentation by active contours for radiotherapy treatment planning. Medical Physics, 34(12), 4738-4749 2007. DOI: https://doi.org/10.1118/1.2799886. 33 [63] Jaouen, V., Gonzalez, P., Stute, S., Guilloteau, D., Chalon, S., Buvat, I., et al. Variational segmentation of vector-valued images with gradient vector flow. IEEE Transactions on image processing, , 1-13 2014. DOI: https://doi.org/10.1118/1.2799886. 33 [64] Carles, M., Torres-Espallardo, I., Alberich-Bayarri, A., Olivas, C., Bello, P., Nestle, U., et al. Evaluation of PET texture features with heterogeneous phantoms: complementarity and effect of motion and segmentation method. Physics in Medicine and Biology, 62(2), 652-668 2016. DOI: https://doi.org/10.1088/1361-6560/62/2/652. 33 [65] Hofheinz, F., Langner, J., Petr, J., Beuthien-Baumann, B., Steinbach, J., Kotzerke, J., et al. An automatic method for accurate volume delineation of heterogeneous tumors in PET. Medical Physics, 40(8), 082503/1-10 2013. DOI: https://doi.org/10.1118/1.4812892. 33, 35 [66] Nioche, C., Orlhac, F., Boughdad, S., Reuze, S., Goya-Outi, J., Robert, C., et al. LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity. Cancer Research, 78(16), 4786-4789 2018. DOI: https://doi.org/10.1158/0008-5472.can-18-0125. 33, 35 [67] Reuze, S., Orlhac, F., Chargari, C., Nioche, C., Limkin, E., Riet, F., et al. Prediction of cervical cancer recurrence using textural features extracted from 18F-FDG PET images acquired with different scanners. Oncotarget, 8(26), 43169-43179 2017. DOI: https://doi.org/10.18632/oncotarget.17856. 33 [68] Nestle, U., Kremp, S., Schaefer-Schuler, S., Sebastian-Welsch, C., Hellwig, D., Rube, C., y Kirsch, C. M. Comparison of different methods for delineation of 18FFDG PET-positive tissue for target volume denition in radiotherapy of patients with non-small cell lung cancer Journal of Nuclear Medicine, 46(8), 1342-1348 2005. PMID: https://www.ncbi.nlm.nih.gov/pubmed/16085592. 34, 35 |
| Materias: | Medicina > Física médica |
| Divisiones: | Centro Integral de Medicina Nuclear y Radioterapia. Fundación INTECNUS |
| Código ID: | 766 |
| Depositado Por: | Tamara Cárcamo |
| Depositado En: | 12 Feb 2021 12:22 |
| Última Modificación: | 12 Feb 2021 12:22 |
Personal del repositorio solamente: página de control del documento
