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Deforming to Best Practice: Key considerations for deformable image registration in radiotherapy.
Barber, Jeffrey; Yuen, Johnson; Jameson, Michael; Schmidt, Laurel; Sykes, Jonathan; Gray, Alison; Hardcastle, Nicholas; Choong, Callie; Poder, Joel; Walker, Amy; Yeo, Adam; Archibald-Heeren, Ben; Harrison, Kristie; Haworth, Annette; Thwaites, David.
Affiliation
  • Barber J; Sydney West Radiation Oncology Network, Blacktown and Westmead, NSW, Australia.
  • Yuen J; Institute of Medical Physics, University of Sydney, Sydney, NSW, Australia.
  • Jameson M; St George Cancer Care Centre, Sydney, NSW, Australia.
  • Schmidt L; Ingham Institute for Applied Medical Research, Sydney, NSW, Australia.
  • Sykes J; South Western Clinical School, The University of New South Wales, Sydney, NSW, Australia.
  • Gray A; Liverpool and Macarthur Cancer Therapy Centres, Sydney, NSW, Australia.
  • Hardcastle N; Ingham Institute for Applied Medical Research, Sydney, NSW, Australia.
  • Choong C; South Western Clinical School, The University of New South Wales, Sydney, NSW, Australia.
  • Poder J; St George Cancer Care Centre, Sydney, NSW, Australia.
  • Walker A; Sydney West Radiation Oncology Network, Blacktown and Westmead, NSW, Australia.
  • Yeo A; Institute of Medical Physics, University of Sydney, Sydney, NSW, Australia.
  • Archibald-Heeren B; Liverpool and Macarthur Cancer Therapy Centres, Sydney, NSW, Australia.
  • Harrison K; Ingham Institute for Applied Medical Research, Sydney, NSW, Australia.
  • Haworth A; South Western Clinical School, The University of New South Wales, Sydney, NSW, Australia.
  • Thwaites D; Peter MacCallum Cancer Centre, Victoria, Australia.
J Med Radiat Sci ; 67(4): 318-332, 2020 Dec.
Article in En | MEDLINE | ID: mdl-32741090
Image registration is a process that underlies many new techniques in radiation oncology - from multimodal imaging and contour propagation in treatment planning to dose accumulation throughout treatment. Deformable image registration (DIR) is a subset of image registration subject to high levels of complexity in process and validation. A need for local guidance to assist in high-quality utilisation and best practice was identified within the Australian community, leading to collaborative activity and workshops. This report communicates the current limitations and best practice advice from early adopters to help guide those implementing DIR in the clinic at this early stage. They are based on the state of image registration applications in radiotherapy in Australia and New Zealand (ANZ), and consensus discussions made at the 'Deforming to Best Practice' workshops in 2018. The current status of clinical application use cases is presented, including multimodal imaging, automatic segmentation, adaptive radiotherapy, retreatment, dose accumulation and response assessment, along with uptake, accuracy and limitations. Key areas of concern and preliminary suggestions for commissioning, quality assurance, education and training, and the use of automation are also reported. Many questions remain, and the radiotherapy community will benefit from continued research in this area. However, DIR is available to clinics and this report is intended to aid departments using or about to use DIR tools now.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Radiotherapy Planning, Computer-Assisted / Radiotherapy, Image-Guided Type of study: Guideline / Qualitative_research Limits: Humans Language: En Journal: J Med Radiat Sci Year: 2020 Document type: Article Affiliation country: Australia Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Radiotherapy Planning, Computer-Assisted / Radiotherapy, Image-Guided Type of study: Guideline / Qualitative_research Limits: Humans Language: En Journal: J Med Radiat Sci Year: 2020 Document type: Article Affiliation country: Australia Country of publication: United States