Evidence map›Paper›PMID 37090849›Full record

ArticleClinical and translational radiation oncology2023

Large anatomical changes in head-and-neck cancers - A dosimetric comparison of online and offline adaptive proton therapy.

Mislav Bobić, Arthur Lalonde, Konrad P Nesteruk, Hoyeon Lee, Lena Nenoff, Bram L Gorissen, Alejandro Bertolet, Paul M Busse, Annie W Chan, Brian A Winey and 4 more

Abstract read
In one paragraph

Article in Clinical and translational radiation oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

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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

14 authors.

Mislav BobićDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Arthur LalondeDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Konrad P NesterukDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Hoyeon LeeDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Lena NenoffDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Bram L GorissenStanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Alejandro BertoletDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Paul M BusseDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Annie W ChanDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Brian A WineyDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Gregory C SharpDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Joost M VerburgDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Antony J LomaxDepartment of Physics, ETH Zurich, Switzerland.
Harald PaganettiDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

Funding

Fast Individualized Delivery Adaptation in Proton TherapyR01CA229178 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI PAGANETTI, HARALD · 2019 to 2023
$1.5M
NCI NIH HHS R01 CA229178
6 · The paper itself

Abstract

Purpose: This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes. Methods: IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT. Results: Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D Conclusion: Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.

Identifiers

PMID37090849
PMCPMC10120292

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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.