Literature DB >> 31356107

Treatment planning for proton therapy: what is needed in the next 10 years?

Hakan Nystrom1,2, Maria Fuglsang Jensen1, Petra Witt Nystrom1,2.   

Abstract

Treatment planning is the process where the prescription of the radiation oncologist is translated into a deliverable treatment. With the complexity of contemporary radiotherapy, treatment planning cannot be performed without a computerized treatment planning system. Proton therapy (PT) enables highly conformal treatment plans with a minimum of dose to tissues outside the target volume, but to obtain the most optimal plan for the treatment, there are a multitude of parameters that need to be addressed. In this review areas of ongoing improvements and research in the field of PT treatment planning are identified and discussed. The main focus is on issues of immediate clinical and practical relevance to the PT community highlighting the needs for the near future but also in a longer perspective. We anticipate that the manual tasks performed by treatment planners in the future will involve a high degree of computational thinking, as many issues can be solved much better by e.g. scripting. More accurate and faster dose calculation algorithms are needed, automation for contouring and planning is required and practical tools to handle the variable biological efficiency in PT is urgently demanded just to mention a few of the expected improvements over the coming 10 years.

Mesh:

Year:  2019        PMID: 31356107      PMCID: PMC7066942          DOI: 10.1259/bjr.20190304

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  108 in total

1.  Imaging Changes in Pediatric Intracranial Ependymoma Patients Treated With Proton Beam Radiation Therapy Compared to Intensity Modulated Radiation Therapy.

Authors:  Jillian R Gunther; Mariko Sato; Murali Chintagumpala; Leena Ketonen; Jeremy Y Jones; Pamela K Allen; Arnold C Paulino; M Fatih Okcu; Jack M Su; Jeffrey Weinberg; Nicholas S Boehling; Soumen Khatua; Adekunle Adesina; Robert Dauser; William E Whitehead; Anita Mahajan
Journal:  Int J Radiat Oncol Biol Phys       Date:  2015-05-16       Impact factor: 7.038

2.  Evaluating the accuracy of a three-term pencil beam algorithm in heterogeneous media.

Authors:  J W Chapman; N C Knutson; J D Fontenot; W D Newhauser; K R Hogstrom
Journal:  Phys Med Biol       Date:  2017-02-07       Impact factor: 3.609

Review 3.  Monte Carlo systems used for treatment planning and dose verification.

Authors:  Lorenzo Brualla; Miguel Rodriguez; Antonio M Lallena
Journal:  Strahlenther Onkol       Date:  2016-11-25       Impact factor: 3.621

4.  Contour scanning for penumbra improvement in pencil beam scanned proton therapy.

Authors:  G Meier; D Leiser; R Besson; A Mayor; S Safai; D C Weber; A J Lomax
Journal:  Phys Med Biol       Date:  2017-02-02       Impact factor: 3.609

5.  Variable Proton Relative Biological Effectiveness: How Do We Move Forward?

Authors:  Tracy Underwood; Harald Paganetti
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-05-01       Impact factor: 7.038

6.  Reoptimization of Intensity Modulated Proton Therapy Plans Based on Linear Energy Transfer.

Authors:  Jan Unkelbach; Pablo Botas; Drosoula Giantsoudi; Bram L Gorissen; Harald Paganetti
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-09-01       Impact factor: 7.038

7.  Comparison of Monte Carlo and analytical dose computations for intensity modulated proton therapy.

Authors:  Pablo Yepes; Antony Adair; David Grosshans; Dragan Mirkovic; Falk Poenisch; Uwe Titt; Qianxia Wang; Radhe Mohan
Journal:  Phys Med Biol       Date:  2018-02-09       Impact factor: 3.609

8.  Exploration and application of phenomenological RBE models for proton therapy.

Authors:  Eivind Rørvik; Lars Fredrik Fjæra; Tordis J Dahle; Jon Espen Dale; Grete May Engeseth; Camilla H Stokkevåg; Sara Thörnqvist; Kristian S Ytre-Hauge
Journal:  Phys Med Biol       Date:  2018-09-13       Impact factor: 3.609

9.  Clinical Commissioning of a Pencil Beam Scanning Treatment Planning System for Proton Therapy.

Authors:  Jatinder Saini; Ning Cao; Stephen R Bowen; Miguel Herrera; Daniel Nicewonger; Tony Wong; Charles D Bloch
Journal:  Int J Part Ther       Date:  2016-08-29

Review 10.  Assessing the Role of Artificial Intelligence (AI) in Clinical Oncology: Utility of Machine Learning in Radiotherapy Target Volume Delineation.

Authors:  Ian S Boon; Tracy P T Au Yong; Cheng S Boon
Journal:  Medicines (Basel)       Date:  2018-12-11
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  3 in total

1.  Proton therapy special feature: introductory editorial.

Authors:  Kathryn D Held; Antony J Lomax; Esther G C Troost
Journal:  Br J Radiol       Date:  2020-03       Impact factor: 3.039

Review 2.  Latest developments in in-vivo imaging for proton therapy.

Authors:  Katia Parodi
Journal:  Br J Radiol       Date:  2019-12-12       Impact factor: 3.039

3.  Influence of Target Location, Size, and Patient Age on Normal Tissue Sparing- Proton and Photon Therapy in Paediatric Brain Tumour Patient-Specific Approach.

Authors:  Mikaela Dell'Oro; Michala Short; Puthenparampil Wilson; Chia-Ho Hua; Melissa Gargone; Thomas E Merchant; Eva Bezak
Journal:  Cancers (Basel)       Date:  2020-09-10       Impact factor: 6.639

  3 in total

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