Evidence map›Paper›PMID 30461183›Full record

ArticleJournal of applied clinical medical physics2019

A dosimetric analysis of a spine SBRT specific treatment planning system.

Daniel L Saenz, Richard Crownover, Sotirios Stathakis, Niko Papanikolaou

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2019. 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
–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

9 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

4 authors.

Daniel L SaenzUniversity of Texas Health San Antonio, Mays Cancer Center, San Antonio, TX, USA.
Richard CrownoverUniversity of Texas Health San Antonio, Mays Cancer Center, San Antonio, TX, USA.
Sotirios StathakisUniversity of Texas Health San Antonio, Mays Cancer Center, San Antonio, TX, USA.
Niko PapanikolaouUniversity of Texas Health San Antonio, Mays Cancer Center, San Antonio, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe Brainlab Elements treatment planning system utilizes distinct modules for treatment planning specific to stereotactic treatment sites including single or multiple brain lesions as well as spine. This work investigates the hypothesis that an optimization tailored specifically to spine can in fact create dosimetrically superior plans to those created in more general use treatment planning systems (TPS).

methodsTen spine patients at our institution were replanned in Brainlab Elements, Phillips Pinnacle

resultsAll TPS produced clinically acceptable plans. The sharpest dose gradient was achieved with Elements (mean 3.3 ± 0.2 mm). This resulted in lowest spinal cord maximum point doses (6.6 ± 1.0 Gy). Gradient indices were also the smallest for Elements (3.6 ± 0.5). Further improvement in gradient index and spinal cord sparing were not performed due to the subsequent violation of the PTV D5% < 25 Gy constraint or the loss of conformity due to the loss of coverage at the PTV-spinal canal interface.

conclusionsBrainlab Elements planning which relies on arc duplication to specifically optimize for spine anatomy did result in dosimetrically superior plans while holding prescription levels constant. While any planning system can improve upon specific dosimetric objectives, the simultaneous satisfaction of all constraints was best achieved with Brainlab Elements.

Indexed as

HumansOrgans at RiskRadiosurgeryRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedSpinal NeoplasmsMonte Carlospinestereotactic body radiosurgerytreatment planning

Identifiers

PMID30461183
PMCPMC6333144

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LicenceCC BY
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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.