Skip to main content
SpringerLink
Log in

Use of Anatomical and Functional MRI in Radiation Treatment Planning

  • Chapter
  • First Online:
Image-Guided High-Precision Radiotherapy

  • 536 Accesses

Abstract

The introduction of magnetic resonance imaging (MRI) in the radiotherapy (RT) workflow, from target definition to response and toxicity assessment, represented a paradigm-shifting change in clinical practice.

The role of MRI in RT planning and contouring are presented in this chapter, focusing on the most important anatomical sites for the radiation oncologist.

Short questions about the applications of this imaging technique to everyday radiotherapy clinical practice are being discussed as a practical vademecum for the clinician.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Nyholm T, Jonsson J. Counterpoint: opportunities and challenges of a magnetic resonance imaging-only radiotherapy work flow. Semin Radiat Oncol. 2014;24:175–80.

    PubMed  Google Scholar 

  2. Just M, Rösler HP, Higer HP, Kutzner J, Thelen M. MRI-assisted radiation therapy planning of brain tumors--clinical experiences in 17 patients. Magn Reson Imaging. 1991;9:173–7.

    CAS  PubMed  Google Scholar 

  3. Remedios D, France B, Alexander M. Making the best value of clinical radiology: iRefer guidelines, 8th edition. Clin Radiol. 2017;72:705–7.

    CAS  PubMed  Google Scholar 

  4. Dirix P, Haustermans K, Vandecaveye V. The value of magnetic resonance imaging for radiotherapy planning. Semin Radiat Oncol. 2014;24:151–9.

    PubMed  Google Scholar 

  5. Owrangi AM, Greer PB, Glide-Hurst CK. MRI-only treatment planning: benefits and challenges. Phys Med Biol. 2018;63:05TR01.

    PubMed  PubMed Central  Google Scholar 

  6. Fraass BA, McShan DL, Diaz RF, Ten Haken RK, Aisen A, Gebarski S, Glazer G, Lichter AS. Integration of magnetic resonance imaging into radiation therapy treatment planning: I. technical considerations. Int J Radiat Oncol Biol Phys. 1987;13:1897–908.

    CAS  PubMed  Google Scholar 

  7. Devic S. MRI simulation for radiotherapy treatment planning. Med Phys. 2012;39:6701–11.

    PubMed  Google Scholar 

  8. Jolicoeur M, Racine M-L, Trop I, Hathout L, Nguyen D, Derashodian T, David S. Localization of the surgical bed using supine magnetic resonance and computed tomography scan fusion for planification of breast interstitial brachytherapy. Radiother Oncol. 2011;100:480–4.

    PubMed  Google Scholar 

  9. Steenbakkers RJHM, Deurloo KEI, Nowak PJCM, Lebesque JV, van Herk M, Rasch CRN. Reduction of dose delivered to the rectum and bulb of the penis using MRI delineation for radiotherapy of the prostate. Int J Radiat Oncol Biol Phys. 2003;57:1269–79.

    PubMed  Google Scholar 

  10. Pötter R, Dimopoulos J, Georg P, et al. Clinical impact of MRI assisted dose volume adaptation and dose escalation in brachytherapy of locally advanced cervix cancer. Radiother Oncol. 2007;83:148–55.

    PubMed  Google Scholar 

  11. Clinical Applications of MRI in Radiotherapy Planning | SpringerLink. https://link.springer.com/chapter/10.1007/978-3-030-14442-5_4. Accessed 25 Mar 2020.

  12. Mabray MC, Barajas RF, Cha S. Modern brain tumor imaging. Brain Tumor Res Treat. 2015;3:8–23.

    PubMed  PubMed Central  Google Scholar 

  13. Kono K, Inoue Y, Nakayama K, Shakudo M, Morino M, Ohata K, Wakasa K, Yamada R. The role of diffusion-weighted imaging in patients with brain tumors. AJNR Am J Neuroradiol. 2001;22:1081–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Stadnik TW, Chaskis C, Michotte A, Shabana WM, van Rompaey K, Luypaert R, Budinsky L, Jellus V, Osteaux M. Diffusion-weighted MR imaging of intracerebral masses: comparison with conventional MR imaging and histologic findings. AJNR Am J Neuroradiol. 2001;22:969–76.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Hilario A, Sepulveda JM, Perez-Nuñez A, Salvador E, Millan JM, Hernandez-Lain A, Rodriguez-Gonzalez V, Lagares A, Ramos A. A prognostic model based on preoperative MRI predicts overall survival in patients with diffuse gliomas. AJNR Am J Neuroradiol. 2014;35:1096–102.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Bulakbasi N, Guvenc I, Onguru O, Erdogan E, Tayfun C, Ucoz T. The added value of the apparent diffusion coefficient calculation to magnetic resonance imaging in the differentiation and grading of malignant brain tumors. J Comput Assist Tomogr. 2004;28:735–46.

    PubMed  Google Scholar 

  17. Haacke EM, Xu Y, Cheng Y-CN, Reichenbach JR. Susceptibility weighted imaging (SWI). Magn Reson Med. 2004;52:612–8.

    PubMed  Google Scholar 

  18. Haacke EM, Mittal S, Wu Z, Neelavalli J, Cheng Y-CN. Susceptibility-weighted imaging: technical aspects and clinical applications, part 1. AJNR Am J Neuroradiol. 2009;30:19–30.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Elhawary H, Liu H, Patel P, Norton I, Rigolo L, Papademetris X, Hata N, Golby AJ. Intraoperative real-time querying of white matter tracts during frameless stereotactic neuronavigation. Neurosurgery. 2011;68:506–16; discussion 516.

    PubMed  Google Scholar 

  20. Knopp EA, Cha S, Johnson G, Mazumdar A, Golfinos JG, Zagzag D, Miller DC, Kelly PJ, Kricheff II. Glial neoplasms: dynamic contrast-enhanced T2*-weighted MR imaging. Radiology. 1999;211:791–8.

    CAS  PubMed  Google Scholar 

  21. Cha S. Update on brain tumor imaging: from anatomy to physiology. AJNR Am J Neuroradiol. 2006;27:475–87.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Horská A, Barker PB. Imaging of brain tumors: MR spectroscopy and metabolic imaging. Neuroimaging Clin N Am. 2010;20:293–310.

    PubMed  PubMed Central  Google Scholar 

  23. Lee MH, Smyser CD, Shimony JS. Resting-state fMRI: a review of methods and clinical applications. AJNR Am J Neuroradiol. 2013;34:1866–72.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. White NS, McDonald CR, Farid N, Kuperman JM, Kesari S, Dale AM. Improved conspicuity and delineation of high-grade primary and metastatic brain tumors using “restriction spectrum imaging”: quantitative comparison with high B-value DWI and ADC. AJNR Am J Neuroradiol. 2013;34:958–964, S1.

    Google Scholar 

  25. Niyazi M, Brada M, Chalmers AJ, et al. ESTRO-ACROP guideline “target delineation of glioblastomas”. Radiother Oncol. 2016;118:35–42.

    PubMed  Google Scholar 

  26. Sanai N, Chang S, Berger MS. Low-grade gliomas in adults. J Neurosurg. 2011;115:948–65.

    PubMed  Google Scholar 

  27. Pignatti F, van den Bent M, Curran D, et al. Prognostic factors for survival in adult patients with cerebral low-grade glioma. J Clin Oncol. 2002;20:2076–84.

    PubMed  Google Scholar 

  28. Fairchild A, Weber DC, Bar-Deroma R, Gulyban A, Fenton PA, Stupp R, Baumert BG. Quality assurance in the EORTC 22033-26033/CE5 phase III randomized trial for low grade glioma: the digital individual case review. Radiother Oncol. 2012;103:287–92.

    PubMed  Google Scholar 

  29. Flickinger JC, Lunsford LD, Kondziolka D. Dose prescription and dose-volume effects in radiosurgery. Neurosurg Clin N Am. 1992;3:51–9.

    CAS  PubMed  Google Scholar 

  30. Straathof CS, de Bruin HG, Dippel DW, Vecht CJ. The diagnostic accuracy of magnetic resonance imaging and cerebrospinal fluid cytology in leptomeningeal metastasis. J Neurol. 1999;246:810–4.

    CAS  PubMed  Google Scholar 

  31. Nagai A, Shibamoto Y, Mori Y, Hashizume C, Hagiwara M, Kobayashi T. Increases in the number of brain metastases detected at frame-fixed, thin-slice MRI for gamma knife surgery planning. Neuro-Oncology. 2010;12:1187–92.

    PubMed  PubMed Central  Google Scholar 

  32. Gondi V, Pugh SL, Tome WA, et al. Preservation of memory with conformal avoidance of the hippocampal neural stem-cell compartment during whole-brain radiotherapy for brain metastases (RTOG 0933): a phase II multi-institutional trial. J Clin Oncol. 2014;32:3810–6.

    PubMed  PubMed Central  Google Scholar 

  33. Maclean J, Fersht N, Short S. Controversies in radiotherapy for meningioma. Clin Oncol (R Coll Radiol). 2014;26:51–64.

    CAS  PubMed  Google Scholar 

  34. Rogers CL, Won M, Vogelbaum MA, et al. High-risk meningioma: initial outcomes from NRG oncology/RTOG 0539. Int J Radiat Oncol Biol Phys. 2020;106:790–9.

    PubMed  Google Scholar 

  35. Weber DC, Ares C, Villa S, et al. Adjuvant postoperative high-dose radiotherapy for atypical and malignant meningioma: a phase-II parallel non-randomized and observation study (EORTC 22042-26042). Radiother Oncol. 2018;128:260–5.

    PubMed  Google Scholar 

  36. Klinke T, Daboul A, Maron J, Gredes T, Puls R, Jaghsi A, Biffar R. Artifacts in magnetic resonance imaging and computed tomography caused by dental materials. PLoS One. 2012; https://doi.org/10.1371/journal.pone.0031766.

  37. Khoo VS, Dearnaley DP, Finnigan DJ, Padhani A, Tanner SF, Leach MO. Magnetic resonance imaging (MRI): considerations and applications in radiotherapy treatment planning. Radiother Oncol. 1997;42:1–15.

    CAS  PubMed  Google Scholar 

  38. Emami B, Sethi A, Petruzzelli GJ. Influence of MRI on target volume delineation and IMRT planning in nasopharyngeal carcinoma. Int J Radiat Oncol Biol Phys. 2003;57:481–8.

    PubMed  Google Scholar 

  39. Prestwich RJD, Sykes J, Carey B, Sen M, Dyker KE, Scarsbrook AF. Improving target definition for head and neck radiotherapy: a place for magnetic resonance imaging and 18-fluoride fluorodeoxyglucose positron emission tomography? Clin Oncol (R Coll Radiol). 2012;24:577–89.

    CAS  PubMed  Google Scholar 

  40. Abdel Khalek Abdel Razek A, King A. MRI and CT of nasopharyngeal carcinoma. AJR Am J Roentgenol. 2012;198:11–8.

    PubMed  Google Scholar 

  41. Wippold FJ. Head and neck imaging: the role of CT and MRI. J Magn Reson Imaging. 2007;25:453–65.

    PubMed  Google Scholar 

  42. Mathur A, Jain N, Kesavadas C, Thomas B, Kapilamoorthy T. Imaging of skull base pathologies: role of advanced magnetic resonance imaging techniques. Neuroradiol J. 2015;28:426–37.

    PubMed  PubMed Central  Google Scholar 

  43. Chung N-N, Ting L-L, Hsu W-C, Lui LT, Wang P-M. Impact of magnetic resonance imaging versus CT on nasopharyngeal carcinoma: primary tumor target delineation for radiotherapy. Head Neck. 2004;26:241–6.

    PubMed  Google Scholar 

  44. Zima AJ, Wesolowski JR, Ibrahim M, Lassig AAD, Lassig J, Mukherji SK. Magnetic resonance imaging of oropharyngeal cancer. Top Magn Reson Imaging. 2007;18:237–42.

    PubMed  Google Scholar 

  45. Abraham J. Imaging for head and neck cancer. Surg Oncol Clin N Am. 2015;24:455–71.

    PubMed  Google Scholar 

  46. Ahmed M, Schmidt M, Sohaib A, et al. The value of magnetic resonance imaging in target volume delineation of base of tongue tumours--a study using flexible surface coils. Radiother Oncol. 2010;94:161–7.

    PubMed  Google Scholar 

  47. Law CP, Chandra RV, Hoang JK, Phal PM. Imaging the oral cavity: key concepts for the radiologist. Br J Radiol. 2011;84:944–57.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Kirsch C. Oral cavity cancer. Top Magn Reson Imaging. 2007;18:269–80.

    PubMed  Google Scholar 

  49. Lewis-Jones H, Colley S, Gibson D. Imaging in head and neck cancer: United Kingdom National Multidisciplinary Guidelines. J Laryngol Otol. 2016;130:S28–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Joshi VM, Wadhwa V, Mukherji SK. Imaging in laryngeal cancers. Indian J Radiol Imaging. 2012;22:209–26.

    PubMed  PubMed Central  Google Scholar 

  51. Chen AY, Hudgins PA. Pitfalls in the staging squamous cell carcinoma of the hypopharynx. Neuroimaging Clin N Am. 2013;23:67–79.

    PubMed  Google Scholar 

  52. Kawaguchi M, Kato H, Tomita H, Mizuta K, Aoki M, Hara A, Matsuo M. Imaging characteristics of malignant Sinonasal tumors. J Clin Med. 2017; https://doi.org/10.3390/jcm6120116.

  53. Freling NJ. Imaging of the salivary glands. CT and MRI. Radiologe. 1994;34:264–72.

    CAS  PubMed  Google Scholar 

  54. Swartz JD, Rothman MI, Marlowe FI, Berger AS. MR imaging of parotid mass lesions: attempts at histopathologic differentiation. J Comput Assist Tomogr. 1989;13:789–96.

    CAS  PubMed  Google Scholar 

  55. Afzelius P, Nielsen M-Y, Ewertsen C, Bloch KP. Imaging of the major salivary glands. Clin Physiol Funct Imaging. 2016;36:1–10.

    PubMed  Google Scholar 

  56. Yousem DM, Kraut MA, Chalian AA. Major salivary gland imaging. Radiology. 2000;216:19–29.

    CAS  PubMed  Google Scholar 

  57. Cardoso M, Min M, Jameson M, Tang S, Rumley C, Fowler A, Estall V, Pogson E, Holloway L, Forstner D. Evaluating diffusion-weighted magnetic resonance imaging for target volume delineation in head and neck radiotherapy. J Med Imaging Radiat Oncol. 2019;63:399–407.

    PubMed  Google Scholar 

  58. Law BKH, King AD, Bhatia KS, Ahuja AT, Kam MKM, Ma BB, Ai QY, Mo FKF, Yuan J, Yeung DKW. Diffusion-weighted imaging of nasopharyngeal carcinoma: can pretreatment DWI predict local failure based on long-term outcome? AJNR Am J Neuroradiol. 2016;37:1706–12.

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Samołyk-Kogaczewska N, Sierko E, Zuzda K, Gugnacki P, Szumowski P, Mojsak M, Burzyńska-Śliwowska J, Wojtukiewicz MZ, Szczecina K, Jurgilewicz DH. PET/MRI-guided GTV delineation during radiotherapy planning in patients with squamous cell carcinoma of the tongue. Strahlenther Onkol. 2019;195:780–91.

    PubMed  PubMed Central  Google Scholar 

  60. Choi SH, Seong J. Strategic application of radiotherapy for hepatocellular carcinoma. Clin Mol Hepatol. 2018;24:114–34.

    PubMed  PubMed Central  Google Scholar 

  61. Mahadevan A, Blanck O, Lanciano R, Peddada A, Sundararaman S, D’Ambrosio D, Sharma S, Perry D, Kolker J, Davis J. Stereotactic body radiotherapy (SBRT) for liver metastasis – clinical outcomes from the international multi-institutional RSSearch® patient registry. Radiat Oncol. 2018; https://doi.org/10.1186/s13014-018-0969-2.

  62. Nair VJ, Pantarotto JR. Treatment of metastatic liver tumors using stereotactic ablative radiotherapy. World J Radiol. 2014;6:18–25.

    PubMed  PubMed Central  Google Scholar 

  63. Yang DS, Yoon WS, Lee JA, Lee NK, Lee S, Kim CY, Yim HJ, Lee SH, Chung HH, Cha SH. The effectiveness of gadolinium MRI to improve target delineation for radiotherapy in hepatocellular carcinoma: a comparative study of rigid image registration techniques. Phys Med. 2014;30:676–81.

    CAS  PubMed  Google Scholar 

  64. Heusch P, Antoch G. Morphologic and functional imaging of non-colorectal liver metastases. Viszeralmedizin. 2015;31:387–92.

    PubMed  PubMed Central  Google Scholar 

  65. Voroney J-P, Brock KK, Eccles C, Haider M, Dawson LA. Prospective comparison of computed tomography and magnetic resonance imaging for liver cancer delineation using deformable image registration. Int J Radiat Oncol Biol Phys. 2006;66:780–91.

    PubMed  Google Scholar 

  66. Pech M, Mohnike K, Wieners G, Bialek E, Dudeck O, Seidensticker M, Peters N, Wust P, Gademann G, Ricke J. Radiotherapy of liver metastases. Comparison of target volumes and dose-volume histograms employing CT- or MRI-based treatment planning. Strahlenther Onkol. 2008;184:256–61.

    PubMed  Google Scholar 

  67. Nair VJ, Szanto J, Vandervoort E, Henderson E, Avruch L, Malone S, Jason RP. Feasibility, detectability and clinical experience with platinum fiducial seeds for MRI/CT fusion and real-time tumor tracking during CyberKnife® stereotactic ablative radiotherapy†. J Radiosurg SBRT. 2015;3:315–23.

    PubMed  PubMed Central  Google Scholar 

  68. Namasivayam S, Martin DR, Saini S. Imaging of liver metastases: MRI. Cancer Imaging. 2007;7:2–9.

    PubMed  PubMed Central  Google Scholar 

  69. Danet I-M, Semelka RC, Leonardou P, Braga L, Vaidean G, Woosley JT, Kanematsu M. Spectrum of MRI appearances of untreated metastases of the liver. AJR Am J Roentgenol. 2003;181:809–17.

    PubMed  Google Scholar 

  70. Sica GT, Ji H, Ros PR. Computed tomography and magnetic resonance imaging of hepatic metastases. Clin Liver Dis. 2002;6:165–179, vii.

    Google Scholar 

  71. Kanematsu M, Goshima S, Watanabe H, Kondo H, Kawada H, Noda Y, Moriyama N. Diffusion/perfusion MR imaging of the liver: practice, challenges, and future. Magn Reson Med Sci. 2012;11:151–61.

    PubMed  Google Scholar 

  72. Vilgrain V, Esvan M, Ronot M, Caumont-Prim A, Aubé C, Chatellier G. A meta-analysis of diffusion-weighted and gadoxetic acid-enhanced MR imaging for the detection of liver metastases. Eur Radiol. 2016;26:4595–615.

    PubMed  Google Scholar 

  73. Lencioni R, Cioni D, Della Pina C, Crocetti L, Bartolozzi C. Imaging diagnosis. Semin Liver Dis. 2005;25:162–70.

    PubMed  Google Scholar 

  74. Hamm B, Thoeni RF, Gould RG, Bernardino ME, Lüning M, Saini S, Mahfouz AE, Taupitz M, Wolf KJ. Focal liver lesions: characterization with nonenhanced and dynamic contrast material-enhanced MR imaging. Radiology. 1994;190:417–23.

    CAS  PubMed  Google Scholar 

  75. Goodwin MD, Dobson JE, Sirlin CB, Lim BG, Stella DL. Diagnostic challenges and pitfalls in MR imaging with hepatocyte-specific contrast agents. Radiographics. 2011;31:1547–68.

    PubMed  Google Scholar 

  76. Zech CJ, Herrmann KA, Reiser MF, Schoenberg SO. MR imaging in patients with suspected liver metastases: value of liver-specific contrast agent Gd-EOB-DTPA. Magn Reson Med Sci. 2007;6:43–52.

    PubMed  Google Scholar 

  77. Marrero JA, Hussain HK, Nghiem HV, Umar R, Fontana RJ, Lok AS. Improving the prediction of hepatocellular carcinoma in cirrhotic patients with an arterially-enhancing liver mass. Liver Transpl. 2005;11:281–9.

    PubMed  Google Scholar 

  78. Caravatta L, Macchia G, Mattiucci GC, et al. Inter-observer variability of clinical target volume delineation in radiotherapy treatment of pancreatic cancer: a multi-institutional contouring experience. Radiat Oncol. 2014;9:198.

    PubMed  PubMed Central  Google Scholar 

  79. Fokas E, Spezi E, Patel N, Hurt C, Nixon L, Chu K-Y, Staffurth J, Abrams R, Mukherjee S. Comparison of investigator-delineated gross tumour volumes and quality assurance in pancreatic cancer: analysis of the on-trial cases for the SCALOP trial. Radiother Oncol. 2016;120:212–6.

    PubMed  PubMed Central  Google Scholar 

  80. Gurney-Champion OJ, Versteijne E, van der Horst A, et al. Addition of MRI for CT-based pancreatic tumor delineation: a feasibility study. Acta Oncol. 2017;56:923–30.

    PubMed  Google Scholar 

  81. Hall WA, Heerkens HD, Paulson ES, et al. Pancreatic gross tumor volume contouring on computed tomography (CT) compared with magnetic resonance imaging (MRI): results of an international contouring conference. Pract Radiat Oncol. 2018;8:107–15.

    PubMed  Google Scholar 

  82. Caravatta L, Cellini F, Simoni N, et al. Magnetic resonance imaging (MRI) compared with computed tomography (CT) for interobserver agreement of gross tumor volume delineation in pancreatic cancer: a multi-institutional contouring study on behalf of the AIRO group for gastrointestinal cancers. Acta Oncol. 2019;58:439–47.

    PubMed  Google Scholar 

  83. O’Neill E, Hammond N, Miller FH. MR imaging of the pancreas. Radiol Clin N Am. 2014;52:757–77.

    PubMed  Google Scholar 

  84. Koay EJ, Hall W, Park PC, Erickson B, Herman JM. The role of imaging in the clinical practice of radiation oncology for pancreatic cancer. Abdom Radiol (NY). 2018;43:393–403.

    PubMed  Google Scholar 

  85. Heerkens HD, Hall WA, Li XA, et al. Recommendations for MRI-based contouring of gross tumor volume and organs at risk for radiation therapy of pancreatic cancer. Pract Radiat Oncol. 2017;7:126–36.

    CAS  PubMed  Google Scholar 

  86. Dalah E, Moraru I, Paulson E, Erickson B, Li XA. Variability of target and normal structure delineation using multimodality imaging for radiation therapy of pancreatic cancer. Int J Radiat Oncol Biol Phys. 2014;89:633–40.

    PubMed  Google Scholar 

  87. Couñago F, Sancho G, Catalá V, Hernández D, Recio M, Montemuiño S, Hernández JA, Maldonado A, del Cerro E. Magnetic resonance imaging for prostate cancer before radical and salvage radiotherapy: what radiation oncologists need to know. World J Clin Oncol. 2017;8:305–19.

    PubMed  PubMed Central  Google Scholar 

  88. Fiorino C, Reni M, Bolognesi A, Cattaneo GM, Calandrino R. Intra- and inter-observer variability in contouring prostate and seminal vesicles: implications for conformal treatment planning. Radiother Oncol. 1998;47:285–92.

    CAS  PubMed  Google Scholar 

  89. Milosevic M, Voruganti S, Blend R, Alasti H, Warde P, McLean M, Catton P, Catton C, Gospodarowicz M. Magnetic resonance imaging (MRI) for localization of the prostatic apex: comparison to computed tomography (CT) and urethrography. Radiother Oncol. 1998;47:277–84.

    CAS  PubMed  Google Scholar 

  90. Moghanaki D, Turkbey B, Vapiwala N, Ehdaie B, Frank SJ, McLaughlin PW, Harisinghani M. Advances in prostate cancer magnetic resonance imaging and positron emission tomography-computed tomography for staging and radiotherapy treatment planning. Semin Radiat Oncol. 2017;27:21–33.

    PubMed  Google Scholar 

  91. Rasch C, Barillot I, Remeijer P, Touw A, van Herk M, Lebesque JV. Definition of the prostate in CT and MRI: a multi-observer study. Int J Radiat Oncol Biol Phys. 1999;43:57–66.

    CAS  PubMed  Google Scholar 

  92. Villeirs GM, Van Vaerenbergh K, Vakaet L, Bral S, Claus F, De Neve WJ, Verstraete KL, De Meerleer GO. Interobserver delineation variation using CT versus combined CT + MRI in intensity-modulated radiotherapy for prostate cancer. Strahlenther Onkol. 2005;181:424–30.

    PubMed  Google Scholar 

  93. Hentschel B, Oehler W, Strauss D, Ulrich A, Malich A. Definition of the CTV prostate in CT and MRI by using CT-MRI image fusion in IMRT planning for prostate cancer. Strahlenther Onkol. 2011;187:183–90.

    PubMed  Google Scholar 

  94. Panje C, Panje T, Putora PM, Kim S-K, Haile S, Aebersold DM, Plasswilm L. Guidance of treatment decisions in risk-adapted primary radiotherapy for prostate cancer using multiparametric magnetic resonance imaging: a single center experience. Radiat Oncol. 2015;10:47.

    PubMed  PubMed Central  Google Scholar 

  95. Hanvey S, Sadozye AH, McJury M, Glegg M, Foster J. The influence of MRI scan position on image registration accuracy, target delineation and calculated dose in prostatic radiotherapy. Br J Radiol. 2012;85:e1256–62.

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Boehmer D, Maingon P, Poortmans P, Baron M-H, Miralbell R, Remouchamps V, Scrase C, Bossi A, Bolla M, EORTC Radiation Oncology Group. Guidelines for primary radiotherapy of patients with prostate cancer. Radiother Oncol. 2006;79:259–69.

    PubMed  Google Scholar 

  97. Salembier C, Villeirs G, De Bari B, et al. ESTRO ACROP consensus guideline on CT- and MRI-based target volume delineation for primary radiation therapy of localized prostate cancer. Radiother Oncol. 2018;127:49–61.

    PubMed  Google Scholar 

  98. Parker CC, Damyanovich A, Haycocks T, Haider M, Bayley A, Catton CN. Magnetic resonance imaging in the radiation treatment planning of localized prostate cancer using intra-prostatic fiducial markers for computed tomography co-registration. Radiother Oncol. 2003;66:217–24.

    CAS  PubMed  Google Scholar 

  99. Synopsis of the PI-RADS v2 Guidelines for Multiparametric Prostate Magnetic Resonance Imaging and Recommendations for Use. - PubMed - NCBI. https://www.ncbi.nlm.nih.gov/pubmed/26361169. Accessed 17 Feb 2020.

  100. Catalá V, Vilanova JC, Gaya JM, Algaba F, Martí T. Multiparametric magnetic resonance imaging and prostate cancer: what’s new? Radiologia. 2017;59:196–208.

    PubMed  Google Scholar 

  101. Pucar D, Hricak H, Shukla-Dave A, Kuroiwa K, Drobnjak M, Eastham J, Scardino PT, Zelefsky MJ. Clinically significant prostate cancer local recurrence after radiation therapy occurs at the site of primary tumor: magnetic resonance imaging and step-section pathology evidence. Int J Radiat Oncol Biol Phys. 2007;69:62–9.

    PubMed  Google Scholar 

  102. Cellini N, Morganti AG, Mattiucci GC, Valentini V, Leone M, Luzi S, Manfredi R, Dinapoli N, Digesu’ C, Smaniotto D. Analysis of intraprostatic failures in patients treated with hormonal therapy and radiotherapy: implications for conformal therapy planning. Int J Radiat Oncol Biol Phys. 2002;53:595–9.

    PubMed  Google Scholar 

  103. van der Heide UA, Korporaal JG, Groenendaal G, Franken S, van Vulpen M. Functional MRI for tumor delineation in prostate radiation therapy. Imaging Med. 2011;3:219.

    Google Scholar 

  104. Groenendaal G, van den Berg CAT, Korporaal JG, Philippens MEP, Luijten PR, van Vulpen M, van der Heide UA. Simultaneous MRI diffusion and perfusion imaging for tumor delineation in prostate cancer patients. Radiother Oncol. 2010;95:185–90.

    PubMed  Google Scholar 

  105. Langer DL, van der Kwast TH, Evans AJ, Trachtenberg J, Wilson BC, Haider MA. Prostate cancer detection with multi-parametric MRI: logistic regression analysis of quantitative T2, diffusion-weighted imaging, and dynamic contrast-enhanced MRI. J Magn Reson Imaging. 2009;30:327–34.

    PubMed  Google Scholar 

  106. Lips IM, van der Heide UA, Haustermans K, van Lin EN, Pos F, Franken SP, Kotte AN, van Gils CH, van Vulpen M. Single blind randomized phase III trial to investigate the benefit of a focal lesion ablative microboost in prostate cancer (FLAME-trial): study protocol for a randomized controlled trial. Trials. 2011;12:255.

    PubMed  PubMed Central  Google Scholar 

  107. Murray JR, Tree AC, Alexander E, et al. Standard and hypofractionated dose escalation to intraprostatic tumour nodules in localised prostate cancer: efficacy and toxicity in the DELINEATE trial. Int J Radiat Oncol Biol Phys. 2019; https://doi.org/10.1016/j.ijrobp.2019.11.402.

  108. Malone S, Croke J, Roustan-Delatour N, et al. Postoperative radiotherapy for prostate cancer: a comparison of four consensus guidelines and dosimetric evaluation of 3D-CRT versus tomotherapy IMRT. Int J Radiat Oncol Biol Phys. 2012;84:725–32.

    PubMed  Google Scholar 

  109. Lee E, Park W, Ahn SH, et al. Interobserver variation in target volume for salvage radiotherapy in recurrent prostate cancer patients after radical prostatectomy using CT versus combined CT and MRI: a multicenter study (KROG 13-11). Radiat Oncol J. 2018;36:11–6.

    PubMed  Google Scholar 

  110. Rans K, Berghen C, Joniau S, De Meerleer G. Salvage radiotherapy for prostate cancer. Clin Oncol (R Coll Radiol). 2020;32:156–62.

    CAS  PubMed  Google Scholar 

  111. Kitajima K, Hartman RP, Froemming AT, Hagen CE, Takahashi N, Kawashima A. Detection of local recurrence of prostate cancer after radical prostatectomy using Endorectal coil MRI at 3 T: addition of DWI and dynamic contrast enhancement to T2-weighted MRI. AJR Am J Roentgenol. 2015;205:807–16.

    PubMed  Google Scholar 

  112. Picardi C, Perret I, Miralbell R, Zilli T. Hypofractionated radiotherapy for prostate cancer in the postoperative setting: what is the evidence so far? Cancer Treat Rev. 2018;62:91–6.

    PubMed  Google Scholar 

  113. Gonzalez-Motta A, Roach M. Stereotactic body radiation therapy (SBRT) for high-risk prostate cancer: where are we now? Pract Radiat Oncol. 2018;8:185–202.

    PubMed  Google Scholar 

  114. Tharmalingam H, Alonzi R, Hoskin PJ. The role of magnetic resonance imaging in brachytherapy. Clin Oncol (R Coll Radiol). 2018;30:728–36.

    CAS  PubMed  Google Scholar 

  115. Schick U, Popowski Y, Nouet P, Bieri S, Rouzaud M, Khan H, Weber DC, Miralbell R. High-dose-rate brachytherapy boost to the dominant intra-prostatic tumor region: hemi-irradiation of prostate cancer. Prostate. 2011;71:1309–16.

    PubMed  Google Scholar 

  116. Ménard C, Susil RC, Choyke P, et al. MRI-guided HDR prostate brachytherapy in standard 1.5T scanner. Int J Radiat Oncol Biol Phys. 2004;59:1414–23.

    PubMed  PubMed Central  Google Scholar 

  117. Hsu CC, Hsu H, Pickett B, et al. Feasibility of MR imaging/MR spectroscopy-planned focal partial salvage permanent prostate implant (PPI) for localized recurrence after initial PPI for prostate cancer. Int J Radiat Oncol Biol Phys. 2013;85:370–7.

    PubMed  Google Scholar 

  118. Mason J, Al-Qaisieh B, Bownes P, Wilson D, Buckley DL, Thwaites D, Carey B, Henry A. Multi-parametric MRI-guided focal tumor boost using HDR prostate brachytherapy: a feasibility study. Brachytherapy. 2014;13:137–45.

    PubMed  Google Scholar 

  119. Hoskin PJ, Colombo A, Henry A, Niehoff P, Paulsen Hellebust T, Siebert F-A, Kovacs G. GEC/ESTRO recommendations on high dose rate afterloading brachytherapy for localised prostate cancer: an update. Radiother Oncol. 2013;107:325–32.

    PubMed  Google Scholar 

  120. Haack S, Nielsen SK, Lindegaard JC, Gelineck J, Tanderup K. Applicator reconstruction in MRI 3D image-based dose planning of brachytherapy for cervical cancer. Radiother Oncol. 2009;91:187–93.

    PubMed  Google Scholar 

  121. Hu Y, Esthappan J, Mutic S, Richardson S, Gay HA, Schwarz JK, Grigsby PW. Improve definition of titanium tandems in MR-guided high dose rate brachytherapy for cervical cancer using proton density weighted MRI. Radiat Oncol. 2013;8:16.

    PubMed  PubMed Central  Google Scholar 

  122. de Leeuw H, Seevinck PR, Bakker CJG. Center-out radial sampling with off-resonant reconstruction for efficient and accurate localization of punctate and elongated paramagnetic structures. Magn Reson Med. 2013;69:1611–22.

    PubMed  Google Scholar 

  123. Frank SJ, Stafford RJ, Bankson JA, Li C, Swanson DA, Kudchadker RJ, Martirosyan KS. A novel MRI marker for prostate brachytherapy. Int J Radiat Oncol Biol Phys. 2008;71:5–8.

    PubMed  Google Scholar 

  124. Lindenberg L, Ahlman M, Turkbey B, Mena E, Choyke P. Evaluation of prostate cancer with PET/MRI. J Nucl Med. 2016;57:111S–6S.

    CAS  PubMed  Google Scholar 

  125. Souvatzoglou M, Eiber M, Takei T, et al. Comparison of integrated whole-body [11C]choline PET/MR with PET/CT in patients with prostate cancer. Eur J Nucl Med Mol Imaging. 2013;40:1486–99.

    CAS  PubMed  Google Scholar 

  126. Bagheri MH, Ahlman MA, Lindenberg L, et al. Advances in medical imaging for the diagnosis and management of common genitourinary cancers. Urol Oncol. 2017;35:473–91.

    PubMed  PubMed Central  Google Scholar 

  127. Low RN, Fuller DB, Muradyan N. Dynamic gadolinium-enhanced perfusion MRI of prostate cancer: assessment of response to hypofractionated robotic stereotactic body radiation therapy. AJR Am J Roentgenol. 2011;197:907–15.

    PubMed  Google Scholar 

  128. Murray J, Tree AC. Prostate cancer - advantages and disadvantages of MR-guided RT. Clin Transl Radiat Oncol. 2019;18:68–73.

    PubMed  PubMed Central  Google Scholar 

  129. Pötter R, Haie-Meder C, Van Limbergen E, et al. Recommendations from gynaecological (GYN) GEC ESTRO working group (II): concepts and terms in 3D image-based treatment planning in cervix cancer brachytherapy-3D dose volume parameters and aspects of 3D image-based anatomy, radiation physics, radiobiology. Radiother Oncol. 2006;78:67–77.

    Google Scholar 

  130. Dimopoulos JCA, Petrow P, Tanderup K, Petric P, Berger D, Kirisits C, Pedersen EM, van Limbergen E, Haie-Meder C, Pötter R. Recommendations from Gynaecological (GYN) GEC-ESTRO working group (IV): basic principles and parameters for MR imaging within the frame of image based adaptive cervix cancer brachytherapy. Radiother Oncol. 2012;103:113–22.

    PubMed  PubMed Central  Google Scholar 

  131. Jung D-C, Kim M-K, Kang S, Seo S-S, Cho JY, Park N-H, Song Y-S, Park S-Y, Kang S-B, Kim JW. Identification of a patient group at low risk for parametrial invasion in early-stage cervical cancer. Gynecol Oncol. 2010;119:426–30.

    PubMed  Google Scholar 

  132. Hatano K, Sekiya Y, Araki H, Sakai M, Togawa T, Narita Y, Akiyama Y, Kimura S, Ito H. Evaluation of the therapeutic effect of radiotherapy on cervical cancer using magnetic resonance imaging. Int J Radiat Oncol Biol Phys. 1999;45:639–44.

    CAS  PubMed  Google Scholar 

  133. Lim K, Small W, Portelance L, et al. Consensus guidelines for delineation of clinical target volume for intensity-modulated pelvic radiotherapy for the definitive treatment of cervix cancer. Int J Radiat Oncol Biol Phys. 2011;79:348–55.

    PubMed  Google Scholar 

  134. Hricak H, Lacey CG, Sandles LG, Chang YC, Winkler ML, Stern JL. Invasive cervical carcinoma: comparison of MR imaging and surgical findings. Radiology. 1988;166:623–31.

    CAS  PubMed  Google Scholar 

  135. Torheim T, Groendahl AR, Andersen EKF, Lyng H, Malinen E, Kvaal K, Futsaether CM. Cluster analysis of dynamic contrast enhanced MRI reveals tumor subregions related to locoregional relapse for cervical cancer patients. Acta Oncol. 2016;55:1294–8.

    PubMed  Google Scholar 

  136. McVeigh PZ, Syed AM, Milosevic M, Fyles A, Haider MA. Diffusion-weighted MRI in cervical cancer. Eur Radiol. 2008;18:1058–64.

    PubMed  Google Scholar 

  137. Iwata S, Joja I, Okuno K, Miyagi Y, Sakaguchi Y, Kudo T, Hiraki Y. Cervical carcinoma with full-thickness stromal invasion: efficacy of dynamic MR imaging in the assessment of parametrial involvement. Radiat Med. 2002;20:247–55.

    PubMed  Google Scholar 

  138. Kuang F, Ren J, Zhong Q, Liyuan F, Huan Y, Chen Z. The value of apparent diffusion coefficient in the assessment of cervical cancer. Eur Radiol. 2013;23:1050–8.

    PubMed  Google Scholar 

  139. Viswanathan AN, Dimopoulos J, Kirisits C, Berger D, Pötter R. Computed tomography versus magnetic resonance imaging-based contouring in cervical cancer brachytherapy: results of a prospective trial and preliminary guidelines for standardized contours. Int J Radiat Oncol Biol Phys. 2007;68:491–8.

    PubMed  Google Scholar 

  140. Lim K, Erickson B, Jürgenliemk-Schulz IM, et al. Variability in clinical target volume delineation for intensity modulated radiation therapy in 3 challenging cervix cancer scenarios. Pract Radiat Oncol. 2015;5:e557–65.

    PubMed  PubMed Central  Google Scholar 

  141. Haack S, Pedersen EM, Jespersen SN, Kallehauge JF, Lindegaard JC, Tanderup K. Apparent diffusion coefficients in GEC ESTRO target volumes for image guided adaptive brachytherapy of locally advanced cervical cancer. Acta Oncol. 2010;49:978–83.

    PubMed  Google Scholar 

  142. van de Schoot AJAJ, de Boer P, Buist MR, Stoker J, Bleeker MCG, Stalpers LJA, Rasch CRN, Bel A. Quantification of delineation errors of the gross tumor volume on magnetic resonance imaging in uterine cervical cancer using pathology data and deformation correction. Acta Oncol. 2015;54:224–31.

    PubMed  Google Scholar 

  143. Zhang Y, Hu J, Li J, et al. Comparison of imaging-based gross tumor volume and pathological volume determined by whole-mount serial sections in primary cervical cancer. Onco Targets Ther. 2013;6:917–23.

    CAS  PubMed  PubMed Central  Google Scholar 

  144. Exner M, Kühn A, Stumpp P, Höckel M, Horn L-C, Kahn T, Brandmaier P. Value of diffusion-weighted MRI in diagnosis of uterine cervical cancer: a prospective study evaluating the benefits of DWI compared to conventional MR sequences in a 3T environment. Acta Radiol. 2016;57:869–77.

    PubMed  Google Scholar 

  145. Song Y, Erickson B, Chen X, Li G, Wu G, Paulson E, Knechtges P, Li XA. Appropriate magnetic resonance imaging techniques for gross tumor volume delineation in external beam radiation therapy of locally advanced cervical cancer. Oncotarget. 2018;9:10100–9.

    PubMed  PubMed Central  Google Scholar 

  146. Beadle BM, Jhingran A, Salehpour M, Sam M, Iyer RB, Eifel PJ. Cervix regression and motion during the course of external beam chemoradiation for cervical cancer. Int J Radiat Oncol Biol Phys. 2009;73:235–41.

    PubMed  Google Scholar 

  147. van de Bunt L, Jürgenliemk-Schulz IM, de Kort GAP, Roesink JM, Tersteeg RJHA, van der Heide UA. Motion and deformation of the target volumes during IMRT for cervical cancer: what margins do we need? Radiother Oncol. 2008;88:233–40.

    PubMed  Google Scholar 

  148. van de Bunt L, van der Heide UA, Ketelaars M, de Kort GAP, Jürgenliemk-Schulz IM. Conventional, conformal, and intensity-modulated radiation therapy treatment planning of external beam radiotherapy for cervical cancer: the impact of tumor regression. Int J Radiat Oncol Biol Phys. 2006;64:189–96.

    PubMed  Google Scholar 

  149. White IM, Scurr E, Wetscherek A, Brown G, Sohaib A, Nill S, Oelfke U, Dearnaley D, Lalondrelle S, Bhide S. Realizing the potential of magnetic resonance image guided radiotherapy in gynaecological and rectal cancer. Br J Radiol. 2019;92:20180670.

    PubMed  PubMed Central  Google Scholar 

  150. Bowen SR, Yuh WTC, Hippe DS, et al. Tumor radiomic heterogeneity: multiparametric functional imaging to characterize variability and predict response following cervical cancer radiation therapy. J Magn Reson Imaging. 2018;47:1388–96.

    PubMed  Google Scholar 

  151. Mayr NA, Wang JZ, Zhang D, et al. Longitudinal changes in tumor perfusion pattern during the radiation therapy course and its clinical impact in cervical cancer. Int J Radiat Oncol Biol Phys. 2010;77:502–8.

    PubMed  Google Scholar 

  152. Tanderup K, Fokdal LU, Sturdza A, et al. Effect of tumor dose, volume and overall treatment time on local control after radiochemotherapy including MRI guided brachytherapy of locally advanced cervical cancer. Radiother Oncol. 2016;120:441–6.

    PubMed  Google Scholar 

  153. Haie-Meder C, Pötter R, Van Limbergen E, et al. Recommendations from gynaecological (GYN) GEC-ESTRO working group (I): concepts and terms in 3D image based 3D treatment planning in cervix cancer brachytherapy with emphasis on MRI assessment of GTV and CTV. Radiother Oncol. 2005;74:235–45.

    PubMed  Google Scholar 

  154. International Commission on Radiation Units and Measurements (ICRU). https://icru.org/content/reports/prescribing-recording-and-reporting-brachytherapy-for-cancer-of-the-cervix-report-no-89. Accessed 1 Mar 2020.

  155. Viswanathan AN, Cormack R, Rawal B, Lee H. Increasing brachytherapy dose predicts survival for interstitial and tandem-based radiation for stage IIIB cervical cancer. Int J Gynecol Cancer. 2009;19:1402–6.

    PubMed  Google Scholar 

  156. Fokdal L, Sturdza A, Mazeron R, et al. Image guided adaptive brachytherapy with combined intracavitary and interstitial technique improves the therapeutic ratio in locally advanced cervical cancer: analysis from the retroEMBRACE study. Radiother Oncol. 2016;120:434–40.

    PubMed  Google Scholar 

  157. Viswanathan AN, Szymonifka J, Tempany-Afdhal CM, O’Farrell DA, Cormack RA. A prospective trial of real-time magnetic resonance-guided catheter placement in interstitial gynecologic brachytherapy. Brachytherapy. 2013;12:240–7.

    PubMed  Google Scholar 

  158. Kapur T, Egger J, Damato A, Schmidt EJ, Viswanathan AN. 3T MR-guided brachytherapy for gynecologic malignancies. Magn Reson Imaging. 2012;30:1279–90.

    PubMed  PubMed Central  Google Scholar 

  159. Schmidt MA, Payne GS. Radiotherapy planning using MRI. Phys Med Biol. 2015;60:R323–61.

    CAS  PubMed  PubMed Central  Google Scholar 

  160. Dean CJ, Sykes JR, Cooper RA, Hatfield P, Carey B, Swift S, Bacon SE, Thwaites D, Sebag-Montefiore D, Morgan AM. An evaluation of four CT-MRI co-registration techniques for radiotherapy treatment planning of prone rectal cancer patients. Br J Radiol. 2012;85:61–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  161. O’Neill BDP, Salerno G, Thomas K, Tait DM, Brown G. MR vs CT imaging: low rectal cancer tumour delineation for three-dimensional conformal radiotherapy. Br J Radiol. 2009;82:509–13.

    PubMed  Google Scholar 

  162. Tan J, Lim Joon D, Fitt G, Wada M, Lim Joon M, Mercuri A, Marr M, Chao M, Khoo V. The utility of multimodality imaging with CT and MRI in defining rectal tumour volumes for radiotherapy treatment planning: a pilot study. J Med Imaging Radiat Oncol. 2010;54:562–8.

    CAS  PubMed  Google Scholar 

  163. Seierstad T, Hole KH, Saelen E, Ree AH, Flatmark K, Malinen E. MR-guided simultaneous integrated boost in preoperative radiotherapy of locally advanced rectal cancer following neoadjuvant chemotherapy. Radiother Oncol. 2009;93:279–84.

    PubMed  Google Scholar 

  164. Furey E, Jhaveri KS. Magnetic resonance imaging in rectal cancer. Magn Reson Imaging Clin N Am. 2014;22(165–190):v–vi.

    Google Scholar 

  165. Suzuki C, Torkzad MR, Tanaka S, Palmer G, Lindholm J, Holm T, Blomqvist L. The importance of rectal cancer MRI protocols on interpretation accuracy. World J Surg Oncol. 2008;6:89.

    PubMed  PubMed Central  Google Scholar 

  166. Jhaveri KS, Hosseini-Nik H. MRI of rectal cancer: an overview and update on recent advances. AJR Am J Roentgenol. 2015;205:W42–55.

    PubMed  Google Scholar 

  167. Mir N, Sohaib SA, Collins D, Koh DM. Fusion of high b-value diffusion-weighted and T2-weighted MR images improves identification of lymph nodes in the pelvis. J Med Imaging Radiat Oncol. 2010;54:358–64.

    CAS  PubMed  Google Scholar 

  168. Cong G-N, Qin M-W, You H, et al. Diffusion weighted imaging combined with magnetic resonance conventional sequences for the diagnosis of rectal cancer. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2009;31:200–5.

    PubMed  Google Scholar 

  169. Kuang F, Yan Z, Wang J, Rao Z. The value of diffusion-weighted MRI to evaluate the response to radiochemotherapy for cervical cancer. Magn Reson Imaging. 2014;32:342–9.

    PubMed  Google Scholar 

  170. Alberda WJ, Dassen HPN, Dwarkasing RS, Willemssen FEJA, van der Pool AEM, de Wilt JHW, Burger JWA, Verhoef C. Prediction of tumor stage and lymph node involvement with dynamic contrast-enhanced MRI after chemoradiotherapy for locally advanced rectal cancer. Int J Color Dis. 2013;28:573–80.

    Google Scholar 

  171. Valentini V, Gambacorta MA, Barbaro B, et al. International consensus guidelines on clinical target volume delineation in rectal cancer. Radiother Oncol. 2016;120:195–201.

    PubMed  Google Scholar 

  172. Van den Begin R, Kleijnen J-P, Engels B, Philippens M, van Asselen B, Raaymakers B, Reerink O, De Ridder M, Intven M. Tumor volume regression during preoperative chemoradiotherapy for rectal cancer: a prospective observational study with weekly MRI. Acta Oncol. 2018;57:723–7.

    PubMed  Google Scholar 

  173. Lambregts DMJ, Yassien AB, Lahaye MJ, Betgen A, Maas M, Beets GL, van der Heide UA, van Triest B, Beets-Tan RGH. Monitoring early changes in rectal tumor morphology and volume during 5 weeks of preoperative chemoradiotherapy - an evaluation with sequential MRIs. Radiother Oncol. 2018;126:431–6.

    PubMed  Google Scholar 

  174. Fiorino C, Passoni P, Palmisano A, et al. Accurate outcome prediction after neo-adjuvant radio-chemotherapy for rectal cancer based on a TCP-based early regression index. Clin Transl Radiat Oncol. 2019;19:12–6.

    PubMed  PubMed Central  Google Scholar 

  175. Burbach JPM, den Harder AM, Intven M, van Vulpen M, Verkooijen HM, Reerink O. Impact of radiotherapy boost on pathological complete response in patients with locally advanced rectal cancer: a systematic review and meta-analysis. Radiother Oncol. 2014;113:1–9.

    PubMed  Google Scholar 

  176. Torkzad MR, Påhlman L, Glimelius B. Magnetic resonance imaging (MRI) in rectal cancer: a comprehensive review. Insights Imaging. 2010;1:245–67.

    PubMed  PubMed Central  Google Scholar 

  177. Sun Y-S, Zhang X-P, Tang L, Ji J-F, Gu J, Cai Y, Zhang X-Y. Locally advanced rectal carcinoma treated with preoperative chemotherapy and radiation therapy: preliminary analysis of diffusion-weighted MR imaging for early detection of tumor histopathologic downstaging. Radiology. 2010;254:170–8.

    PubMed  Google Scholar 

  178. Glynne-Jones R, Tan D, Hughes R, Hoskin P. Squamous-cell carcinoma of the anus: progress in radiotherapy treatment. Nat Rev Clin Oncol. 2016;13:447–59.

    CAS  PubMed  Google Scholar 

  179. Rusten E, Rekstad BL, Undseth C, Al-Haidari G, Hanekamp B, Hernes E, Hellebust TP, Malinen E, Guren MG. Target volume delineation of anal cancer based on magnetic resonance imaging or positron emission tomography. Radiat Oncol. 2017;12:147.

    PubMed  PubMed Central  Google Scholar 

  180. Glynne-Jones R, Nilsson PJ, Aschele C, Goh V, Peiffert D, Cervantes A, Arnold D, European Society for Medical Oncology (ESMO), European Society of Surgical Oncology (ESSO), European Society of Radiotherapy and Oncology (ESTRO). Anal cancer: ESMO-ESSO-ESTRO clinical practice guidelines for diagnosis, treatment and follow-up. Eur J Surg Oncol. 2014;40:1165–76.

    CAS  PubMed  Google Scholar 

  181. Peiffert D, Tournier-Rangeard L, Gérard J-P, et al. Induction chemotherapy and dose intensification of the radiation boost in locally advanced anal canal carcinoma: final analysis of the randomized UNICANCER ACCORD 03 trial. J Clin Oncol. 2012;30:1941–8.

    CAS  PubMed  Google Scholar 

  182. Jones M, Hruby G, Stanwell P, Gallagher S, Wong K, Arm J, Martin J. Multiparametric MRI as an outcome predictor for anal canal cancer managed with chemoradiotherapy. BMC Cancer. 2015;15:281.

    PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Rome, Italy

    Angela Romano, Luca Boldrini, Antonio Piras & Vincenzo Valentini

  2. Istituto di Radiologia, Università Cattolica del Sacro Cuore, Rome, Italy

    Luca Boldrini & Vincenzo Valentini

Authors
  1. Angela Romano
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Luca Boldrini
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Antonio Piras
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vincenzo Valentini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Luca Boldrini .

Editor information

Editors and Affiliations

  1. Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Dresden, Sachsen, Germany

    Esther G. C. Troost

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Romano, A., Boldrini, L., Piras, A., Valentini, V. (2022). Use of Anatomical and Functional MRI in Radiation Treatment Planning. In: Troost, E.G.C. (eds) Image-Guided High-Precision Radiotherapy. Springer, Cham. https://doi.org/10.1007/978-3-031-08601-4_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-08601-4_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08600-7

  • Online ISBN: 978-3-031-08601-4

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation