Evidence map›Paper›PMID 35499198›Full record

ArticleJournal of applied clinical medical physics2022

How to estimate R50% for cranial SRS/SRT cases with overlapping 50% isodose volumes: A proposed system.

Dharmin D Desai, Ivan L Cordrey

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. A predictive model for Gamma Knife intermediate dose spill: R50%Journal of applied clinical medical physics · 2025
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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

2 authors.

Dharmin D DesaiDepartment of Radiation Oncology, CHI Memorial Hospital, Chattanooga, Tennessee, USA.
Ivan L CordreyRegional Cancer Center, Cumberland Medical Center, Crossville, Tennessee, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inevitably in clinical stereotactic cranial single isocenter multiple target cases treated with linac-based multi-leaf collimated (MLC) delivery, one encounters planning target volumes (PTVs) in close proximity with overlapping 50% isodose clouds (IDC50%). In such cases, it is very difficult to separate the IDC50% attributable to each individual target and, thus, assess the intermediate dose conformality or R50%. Such scenarios happen regardless of what metric is used to measure intermediate dose spill. Now that universal standards for intermediate dose spill have been proposed, it is important to have a consistent method for apportioning these overlapping IDC50% volumes to allow comparison with the proposed standards when multiple PTVs have overlapping IDC50%. We propose a systematic method for apportioning the IDC50% of multiple targets with overlapping IDC50% based on the relative surface area of each target volume; we call this the fair value estimate (FVE). This FVE system of apportionment is tested for reasonableness by comparing the apportionment of multiple target single isocenter stereotactic treatment with widely spaced targets where the IDC50% can be obviously assigned to demonstrate that the FVE results are very similar to the actual R50% results. We then demonstrate how the FVE system would be applied to cases with overlapping IDC50%. We propose this FVE system for consideration by the cranial stereotactic community for apportioning the intermediate dose spill when that intermediate dose spill overlaps among multiple targets.

Indexed as

Brain NeoplasmsRadiosurgeryHumansParticle AcceleratorsRadiotherapy DosageRadiotherapy Planning, Computer-Assistedcranial SRS/SRTfair value estimateIDC50% overlapR50%SIMT

Identifiers

PMID35499198
PMCPMC9278687

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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.