Evidence map›Paper›PMID 32660504›Full record

ArticleRadiation oncology (London, England)2020

Voxel-level biological optimisation of prostate IMRT using patient-specific tumour location and clonogen density derived from mpMRI.

E J Her, A Haworth, H M Reynolds, Y Sun, A Kennedy, V Panettieri, M Bangert, S Williams, M A Ebert

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Radiation oncology (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 6 institutions in 2 countries.

E J HerSchool of Physics, Mathematics and Computing, University of Western Australia, Perth, Australia. emily.her@research.uwa.edu.au.ORCID http://orcid.org/0000-0002-3446-5469
A HaworthInstitute of Medical Physics, University of Sydney, Sydney, Australia.
H M ReynoldsThe Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia.
Y SunThe Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia.
A KennedyDepartment of Radiation Oncology, Sir Charles Gairdner Hospital, Perth, Australia.
V PanettieriAlfred Health Radiation Oncology, Melbourne, Australia.
M BangertDepartment of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
S WilliamsThe Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia.
M A EbertSchool of Physics, Mathematics and Computing, University of Western Australia, Perth, Australia.
The University of Melbourne · AUThe University of Western Australia · AUAlfred Health · AUGerman Cancer Research Center · DESir Charles Gairdner Hospital · AUThe University of Sydney · AU

Funding

Australian National Health and Medical Research Council APP1126955Cancer Therapeutics Top up FundingDepartment of Education, Australian Government Research Training Program ScholarshipProstate Cancer Foundation of Australia Movember Young Investigator GrantUniversity of Melbourne Melbourne International Research Scholarship
6 · The paper itself

Abstract

aimsThis study aimed to develop a framework for optimising prostate intensity-modulated radiotherapy (IMRT) based on patient-specific tumour biology, derived from multiparametric MRI (mpMRI). The framework included a probabilistic treatment planning technique in the effort to yield dose distributions with an improved expected treatment outcome compared with uniform-dose planning approaches.

methodsIMRT plans were generated for five prostate cancer patients using two inverse planning methods: uniform-dose to the planning target volume and probabilistic biological optimisation for clinical target volume tumour control probability (TCP) maximisation. Patient-specific tumour location and clonogen density information were derived from mpMRI and geometric uncertainties were incorporated in the TCP calculation. Potential reduction in dose to sensitive structures was assessed by comparing dose metrics of uniform-dose plans with biologically-optimised plans of an equivalent level of expected tumour control.

resultsThe planning study demonstrated biological optimisation has the potential to reduce expected normal tissue toxicity without sacrificing local control by shaping the dose distribution to the spatial distribution of tumour characteristics. On average, biologically-optimised plans achieved 38.6% (p-value: < 0.01) and 51.2% (p-value: < 0.01) reduction in expected rectum and bladder equivalent uniform dose, respectively, when compared with uniform-dose planning.

conclusionsIt was concluded that varying the dose distribution within the prostate to take account for each patient's clonogen distribution was feasible. Lower doses to normal structures compared to uniform-dose plans was possible whilst providing robust plans against geometric uncertainties. Further validation in a larger cohort is warranted along with considerations for adaptive therapy and limiting urethral dose.

Indexed as

AgedHumansMaleMiddle AgedMultiparametric Magnetic Resonance ImagingProstatic NeoplasmsRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedDose-paintingIMRTMultiparametric MRIProbabilistic treatment planningTumour control probability

Identifiers

PMID32660504
PMCPMC7805066
OpenAlexW3041025945

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.