Evidence map›Paper›PMID 28341992›Full record

ArticleNeuroradiology2017

A semi-automated volumetric software for segmentation and perfusion parameter quantification of brain tumors using 320-row multidetector computed tomography: a validation study.

Soo Young Chae, Sangil Suh, Inseon Ryoo, Arim Park, Kyoung Jin Noh, Hackjoon Shim, Hae Young Seol

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Neuroradiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI.International journal of computer assisted radiology and surgery · 2020
    Article
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Soo Young ChaeDepartment of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea.
Sangil SuhDepartment of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea. sangil.suh@gmail.com.
Inseon RyooDepartment of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea.
Arim ParkDepartment of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea.
Kyoung Jin NohDepartment of Electronic Engineering, Soonchunhyang University, Asan, South Korea.
Hackjoon ShimToshiba Medical Systems Korea Co., Seoul, South Korea.
Hae Young SeolDepartment of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe developed a semi-automated volumetric software, NPerfusion, to segment brain tumors and quantify perfusion parameters on whole-brain CT perfusion (WBCTP) images. The purpose of this study was to assess the feasibility of the software and to validate its performance compared with manual segmentation.

methodsTwenty-nine patients with pathologically proven brain tumors who underwent preoperative WBCTP between August 2012 and February 2015 were included. Three perfusion parameters, arterial flow (AF), equivalent blood volume (EBV), and Patlak flow (PF, which is a measure of permeability of capillaries), of brain tumors were generated by a commercial software and then quantified volumetrically by NPerfusion, which also semi-automatically segmented tumor boundaries. The quantification was validated by comparison with that of manual segmentation in terms of the concordance correlation coefficient and Bland-Altman analysis.

resultsWith NPerfusion, we successfully performed segmentation and quantified whole volumetric perfusion parameters of all 29 brain tumors that showed consistent perfusion trends with previous studies. The validation of the perfusion parameter quantification exhibited almost perfect agreement with manual segmentation, with Lin concordance correlation coefficients (ρ

conclusionsNPerfusion successfully performs segmentation of brain tumors and calculates perfusion parameters of brain tumors. We validated this semi-automated segmentation software by comparing it with manual segmentation. NPerfusion can be used to calculate volumetric perfusion parameters of brain tumors from WBCTP.

Indexed as

SoftwareAdultAgedAlgorithmsBlood VolumeBrain NeoplasmsContrast MediaFemaleHumansIohexolMaleMiddle AgedMultidetector Computed TomographyPattern Recognition, AutomatedRadiographic Image Interpretation, Computer-AssistedRetrospective StudiesContrast MediaIohexoliopromideBrain tumorCT perfusionSegmentationSemi-automated segmentationWhole-brain CT perfusion

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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.