Evidence map›Paper›PMID 36267964›Full record

ArticleFrontiers in oncology2022

Knowledge-based planning for multi-isocenter VMAT total marrow irradiation.

Kang-Hyun Ahn, Damiano Rondelli, Matthew Koshy, Julien A Partouche, Yasmin Hasan, Hongtao Liu, Kamil Yenice, Bulent Aydogan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

7 citing papers in PubMed, 9 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

8 authors at 2 institutions in 1 country.

Kang-Hyun AhnDepartment of Radiation Oncology, University of Illinois, Chicago, IL, United States.
Damiano RondelliDivision of Hematology/Oncology, University of Illinois, Chicago, IL, United States.
Matthew KoshyDepartment of Radiation Oncology, University of Illinois, Chicago, IL, United States.
Julien A PartoucheDepartment of Radiation and Cellular Oncology, University of Chicago, Chicago, IL, United States.
Yasmin HasanDepartment of Radiation and Cellular Oncology, University of Chicago, Chicago, IL, United States.
Hongtao LiuDepartment of Radiation and Cellular Oncology, University of Chicago, Chicago, IL, United States.
Kamil YeniceDepartment of Radiation and Cellular Oncology, University of Chicago, Chicago, IL, United States.
Bulent AydoganDepartment of Radiation and Cellular Oncology, University of Chicago, Chicago, IL, United States.
University of Chicago · USUniversity of Illinois Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Total marrow irradiation (TMI) involves optimization of extremely large target volumes and requires extensive clinical experience and time for both treatment planning and delivery. Although volumetric modulated arc therapy (VMAT) achieves substantial reduction in treatment delivery time, planning process still presents a challenge due to use of multiple isocenters and multiple overlapping arcs. We developed and evaluated a knowledge-based planning (KBP) model for VMAT-TMI to address these clinical challenges. Methods: Fifty-one patients previously treated in our clinic were selected for the model training, while 22 patients from another clinic were used as a test set. All plans used a 3-isocenter to cover sub-target volumes of head and neck (HN), chest, and pelvis. Chest plan was performed first and then used as the base dose for both the HN and pelvis plans to reduce hot spots around the field junctions. This resulted in a wide range of dose-volume histograms (DVH). To address this, plans without the base-dose plan were optimized and added to the library to train the model. Results: KBP achieved our clinical goals (95% of PTV receives 100% of Rx) in a single day, which used to take 4-6 days of effort without KBP. Statistically significant reductions with KBP were observed in the mean dose values to brain, lungs, oral cavity and lenses. KBP substantially improved 105% dose spillage (14.1% ± 2.4% vs 31.8% ± 3.8%), conformity index (1.51 ± 0.06 vs 1.81 ± 0.12) and homogeneity index (1.25 ± 0.02 vs 1.33 ± 0.03). Conclusions: KBP improved dosimetric performance with uniform quality. It reduced dependence on planner experience and achieved a factor of 5 reduction in planning time to produce quality plans to allow its wide-spread clinical implementation.

Indexed as

knowledge-based planningradiotherapyRapidPlanTMItotal marrow irradiationVMAT

Identifiers

PMID36267964
PMCPMC9577613
OpenAlexW4301395993

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Registered trials

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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.