Evidence map›Paper›PMID 30286187›Full record

ArticlePloS one2018

Comparison of the IPSA and HIPO algorithms for interstitial tongue high-dose-rate brachytherapy.

Chang Heon Choi, So-Yeon Park, Jong Min Park, Hong-Gyun Wu, Jin-Ho Kim, Jung-In Kim

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In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

8 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

6 authors.

Chang Heon ChoiDepartment of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.
So-Yeon ParkDepartment of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.
Jong Min ParkDepartment of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.
Hong-Gyun WuDepartment of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.
Jin-Ho KimDepartment of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.
Jung-In KimDepartment of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.ORCID 0000-0002-0305-5969

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to compare the inverse planning simulated annealing (IPSA) stochastic algorithm with the hybrid inverse planning and optimization (HIPO) algorithm for interstitial tongue high-dose-rate (HDR) brachytherapy.

methodsTwenty patients who received radiotherapy for tongue cancer using interstitial HDR brachytherapy were retrospectively selected for this study. Oncentra Brachy v. 4.3 was used for IPSA and HIPO planning. Four to eight fixed catheter configurations were determined according to the target shape. During the optimization process, predetermined constrain values were used for each IPSA and HIPO plan. The dosimetric parameters and dwell time were analyzed to evaluate the performances of the plans.

resultsThe total dwell time using IPSA was 4 seconds longer than that of HIPO. The number of active positions per catheter for the IPSA plans were approximately 2.5 fewer than those of the HIPO plans. The dose-volumetric parameters related to the clinical target volume with IPSA were lower than those with HIPO. In terms of the dose-volumetric parameters related to normal tissue, HIPO tended to associate with slightly higher values than IPSA, without statistical significance. After GrO, the target coverages were satisfied to clinical goal for all patients. The total dwell times was approximately increased by 10%.

conclusionsThe IPSA and HIPO dose optimization algorithms generate similar dosimetric results. In terms of the dwell time, HIPO appears to be more beneficial.

Indexed as

AlgorithmsBrachytherapyCathetersDose-Response Relationship, RadiationFemaleHumansMaleMandibleRadiation DosageRadiotherapy Planning, Computer-AssistedTongueTongue Neoplasms

Identifiers

PMID30286187
PMCPMC6171910

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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.