Evidence map›Paper›PMID 32034989›Full record

ArticleJournal of applied clinical medical physics2020

A novel, yet simple MLC-based 3D-crossfire technique for spatially fractionated GRID therapy treatment of deep-seated bulky tumors.

Damodar Pokhrel, Matthew Halfman, Lana Sanford, Quan Chen, Mahesh Kudrimoti

Open access · goldAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

17 citing papers in PubMed, 26 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

5 authors at 1 institution in 1 country.

Damodar PokhrelMedical Physics Graduate Program, Department of Radiation Medicine, University of Kentucky, Lexington, KY, USA.
Matthew HalfmanMedical Physics Graduate Program, Department of Radiation Medicine, University of Kentucky, Lexington, KY, USA.
Lana SanfordMedical Physics Graduate Program, Department of Radiation Medicine, University of Kentucky, Lexington, KY, USA.
Quan ChenMedical Physics Graduate Program, Department of Radiation Medicine, University of Kentucky, Lexington, KY, USA.
Mahesh KudrimotiMedical Physics Graduate Program, Department of Radiation Medicine, University of Kentucky, Lexington, KY, USA.
University of Kentucky · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTreating deep-seated bulky tumors with traditional single-field Cerrobend GRID-blocks has many limitations such as suboptimal target coverage and excessive skin toxicity. Heavy traditional GRID-blocks are a concern for patient safety at various gantry-angles and dosimetric detail is not always available without a GRID template in user's treatment planning system. Herein, we propose a simple, yet clinically useful multileaf collimator (MLC)-based three-dimensional (3D)-crossfire technique to provide sufficient target coverage, reduce skin dose, and potentially escalate tumor dose to deep-seated bulky tumors. MATERIALS/

methodsThirteen patients (multiple sites) who underwent conventional single-field cerrobend GRID-block therapy (maximum, 15 Gy in 1 fraction) were re-planned using an MLC-based 3D-crossfire method. Gross tumor volume (GTV) was used to generate a lattice pattern of 10 mm diameter and 20 mm center-to-center mimicking conventional GRID-block using an in-house MATLAB program. For the same prescription, MLC-based 3D-crossfire grid plans were generated using 6-gantry positions (clockwise) at 60° spacing (210°, 270°, 330°, 30°, 90°, 150°, therefore, each gantry angle associated with a complement angle at 180° apart) with differentially-weighted 6 or 18 MV beams in Eclipse. For each gantry, standard Millenium120 (Varian) 5 mm MLC leaves were fit to the grid-pattern with 90° collimator rotation, so that the tunneling dose distribution was achieved. Acuros-based dose was calculated for heterogeneity corrections. Dosimetric parameters evaluated include: mean GTV dose, GTV dose heterogeneities (peak-to-valley dose ratio, PVDR), skin dose and dose to other adjacent critical structures. Additionally, planning time and delivery efficiency was recorded. With 3D-MLC, dose escalation up to 23 Gy was simulated for all patient's plans.

resultsAll 3D-MLC crossfire GRID plans exhibited excellent target coverage with mean GTV dose of 13.4 ± 0.5 Gy (range: 12.43-14.24 Gy) and mean PVDR of 2.0 ± 0.3 (range: 1.7-2.4). Maximal and dose to 5 cc of skin were 9.7 ± 2.7 Gy (range: 5.4-14.0 Gy) and 6.3 ± 1.8 Gy (range: 4.1-11.1 Gy), on average respectively. Three-dimensional-MLC treatment planning time was about an hour or less. Compared to traditional GRID-block, average beam on time was 20% less, while providing similar overall treatment time. With 3D-MLC plans, tumor dose can be escalated up to 23 Gy while respecting skin dose tolerances.

conclusionThe simple MLC-based 3D-crossfire GRID-therapy technique resulted in enhanced target coverage for de-bulking deep-seated bulky tumors, reduced skin toxicity and spare adjacent critical structures. This simple MLC-based approach can be easily adopted by any radiotherapy center. It provides detailed dosimetry and a safe and effective treatment by eliminating the heavy physical GRID-block and could potentially provide same day treatment. Prospective clinical trial with higher tumor-dose to bulky deep-seated tumors is anticipated.

Indexed as

HumansNeoplasmsOrgans at RiskPrognosisRadiotherapy DosageRadiotherapy, High-EnergyRadiotherapy Planning, Computer-AssistedRetrospective Studies3D-MLC CrossfireBulky-tumorscerrobend GRID-blockdose-escalation

Identifiers

PMID32034989
PMCPMC7075376
OpenAlexW3004994356

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.