Evidence map›Paper›PMID 26229630›Full record

ArticleJournal of medical radiation sciences2014

Relationship of computed tomography perfusion and positron emission tomography to tumour progression in malignant glioma.

Timothy P C Yeung, Slav Yartsev, Ting-Yim Lee, Eugene Wong, Wenqing He, Barbara Fisher, Lauren L VanderSpek, David Macdonald, Glenn Bauman

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical radiation sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
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

9 authors at 3 institutions in 1 country.

Timothy P C YeungLondon Regional Cancer Program, London Health Sciences Centre Ontario, Canada, N6A 4L6 ; Robarts Research Institute, The University of Western Ontario Ontario, Canada, N6A 5B7 ; Department of Medical Biophysics, The University of Western Ontario Ontario, Canada, N6A 5C1.
Slav YartsevLondon Regional Cancer Program, London Health Sciences Centre Ontario, Canada, N6A 4L6 ; Department of Medical Biophysics, The University of Western Ontario Ontario, Canada, N6A 5C1 ; Department of Oncology, The University of Western Ontario, London Health Sciences Centre, London Regional Cancer Program Ontario, Canada, N6A 4L6.
Ting-Yim LeeRobarts Research Institute, The University of Western Ontario Ontario, Canada, N6A 5B7 ; Department of Medical Biophysics, The University of Western Ontario Ontario, Canada, N6A 5C1 ; Department of Oncology, The University of Western Ontario, London Health Sciences Centre, London Regional Cancer Program Ontario, Canada, N6A 4L6 ; Department of Medical Imaging, The University of Western Ontario, London Health Sciences Centre, Victoria Hospital Ontario, Canada, N6A 5W9 ; Lawson Health Research Institute, St. Joseph's Health Care London Ontario, Canada, N6A 4V2.
Eugene WongLondon Regional Cancer Program, London Health Sciences Centre Ontario, Canada, N6A 4L6 ; Department of Oncology, The University of Western Ontario, London Health Sciences Centre, London Regional Cancer Program Ontario, Canada, N6A 4L6 ; Department of Physics and Astronomy, The University of Western Ontario Ontario, Canada, N6A 3K7.
Wenqing HeDepartment of Statistical and Actuarial Sciences, The University of Western Ontario Ontario, Canada, N6A 5B7.
Barbara FisherLondon Regional Cancer Program, London Health Sciences Centre Ontario, Canada, N6A 4L6 ; Department of Oncology, The University of Western Ontario, London Health Sciences Centre, London Regional Cancer Program Ontario, Canada, N6A 4L6.
Lauren L VanderSpekLondon Regional Cancer Program, London Health Sciences Centre Ontario, Canada, N6A 4L6 ; Department of Oncology, The University of Western Ontario, London Health Sciences Centre, London Regional Cancer Program Ontario, Canada, N6A 4L6.
David MacdonaldLondon Regional Cancer Program, London Health Sciences Centre Ontario, Canada, N6A 4L6 ; Department of Oncology, The University of Western Ontario, London Health Sciences Centre, London Regional Cancer Program Ontario, Canada, N6A 4L6 ; Department of Clinical Neurological Sciences, The University of Western Ontario, London Health Sciences Centre, University Hospital Ontario, Canada, N6A 5A5.
Glenn BaumanLondon Regional Cancer Program, London Health Sciences Centre Ontario, Canada, N6A 4L6 ; Department of Medical Biophysics, The University of Western Ontario Ontario, Canada, N6A 5C1 ; Department of Oncology, The University of Western Ontario, London Health Sciences Centre, London Regional Cancer Program Ontario, Canada, N6A 4L6.
London Health Sciences Centre · CAWestern University · CASt Joseph's Health Care · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IntroductionThis study aimed to explore the potential for computed tomography (CT) perfusion and 18-Fluorodeoxyglucose positron emission tomography (FDG-PET) in predicting sites of future progressive tumour on a voxel-by-voxel basis after radiotherapy and chemotherapy. MethodsTen patients underwent pre-radiotherapy magnetic resonance (MR), FDG-PET and CT perfusion near the end of radiotherapy and repeated post-radiotherapy follow-up MR scans. The relationships between these images and tumour progression were assessed using logistic regression. Cross-validation with receiver operating characteristic (ROC) analysis was used to assess the value of these images in predicting sites of tumour progression. ResultsPre-radiotherapy MR-defined gross tumour; near-end-of-radiotherapy CT-defined enhancing lesion; CT perfusion blood flow (BF), blood volume (BV) and permeability-surface area (PS) product; FDG-PET standard uptake value (SUV); and SUV:BF showed significant associations with tumour progression on follow-up MR imaging (P < 0.0001). The mean sensitivity (±standard deviation), specificity and area under the ROC curve (AUC) of PS were 0.64 ± 0.15, 0.74 ± 0.07 and 0.72 ± 0.12 respectively. This mean AUC was higher than that of the pre-radiotherapy MR-defined gross tumour and near-end-of-radiotherapy CT-defined enhancing lesion (both AUCs = 0.6 ± 0.1, P ≤ 0.03). The multivariate model using BF, BV, PS and SUV had a mean AUC of 0.8 ± 0.1, but this was not significantly higher than the PS only model. ConclusionPS is the single best predictor of tumour progression when compared to other parameters, but voxel-based prediction based on logistic regression had modest sensitivity and specificity.

Indexed as

18-Fluorodeoxyglucose PETcontrast enhancementCT perfusionmalignant gliomatumour progression

Identifiers

PMID26229630
PMCPMC4175825
OpenAlexW1972526069

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.