Evidence map›Paper›PMID 30216765›Full record

ArticleTranslational oncology2018

Clinical Validation of Automatable Gaussian Normalized CBV in Brain Tumor Analysis: Superior Reproducibility and Slightly Better Association with Survival than Current Standard Manual Normal Appearing White Matter Normalization.

Lei Qin, Xiang Li, Angie Li, Suchun Cheng, Jinrong Qu, Katherine Reinshagen, Jiani Hu, Nathan Himes, Gao Lu, Xiaoyin Xu and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational oncology, 2018. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. CDC7 as a novel biomarker and druggable target in cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2022
    Review
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

11 authors.

Lei QinDana-Farber Cancer Institute, Department of Imaging, Boston, MA, USA; Harvard Medical School, Department of Radiology, Boston, MA, USA.
Xiang LiBrigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Affiliated Cancer Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, Henan, China.
Angie LiBrigham and Women's Hospital, Department of Radiology, Boston, MA, USA; The Robert Larner, M.D. College of Medicine at the University of Vermont, Burlington, VT, USA.
Suchun ChengDana-Farber Cancer Institute, Department of Biostatistics and Computational Biology, Boston, MA, USA.
Jinrong QuBrigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Affiliated Cancer Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, Henan, China.
Katherine ReinshagenHarvard Medical School, Department of Radiology, Boston, MA, USA; Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Massachusetts Eye and Ear Infirmary, Department of Radiology, Boston, MA, USA.
Jiani HuDana-Farber Cancer Institute, Department of Biostatistics and Computational Biology, Boston, MA, USA.
Nathan HimesBrigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Medical Imaging of Lehigh Valley, Lehigh Valley Hospital, Allentown, PA, USA.
Gao LuBrigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Peking Union Medical College Hospital, Department of Neurosurgery, Beijing, China.
Xiaoyin XuPeking Union Medical College Hospital, Department of Neurosurgery, Beijing, China; Peking Union Medical College Hospital, Department of Neurosurgery, Beijing, China.
Geoffrey S YoungDana-Farber Cancer Institute, Department of Imaging, Boston, MA, USA; Harvard Medical School, Department of Radiology, Boston, MA, USA; Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA. Electronic address: gsyoung@partners.org.

Funding

Computer aided diagnosis of cancer metastases in the brainR01LM012434 · NLM · BRIGHAM AND WOMEN'S HOSPITAL · PI YOUNG, GEOFFREY · 2016 to 2020
$2.9M
NLM NIH HHS R01 LM012434
6 · The paper itself

Abstract

purposeTo validate Gaussian normalized cerebral blood volume (GN-nCBV) by association with overall survival (OS) in newly diagnosed glioblastoma patients and compare this association with current standard white matter normalized cerebral blood volume (WN-nCBV).

methodsWe retrieved spin-echo echo-planar dynamic susceptibility contrast MRI acquired after maximal resection and prior to radiation therapy between 2006 and 2011 in 51 adult patients (28 male, 23 female; age 23-87 years) with newly diagnosed glioblastoma. Software code was developed in house to perform Gaussian normalization of CBV to the standard deviation of the whole brain CBV. Three expert readers manually selected regions of interest in tumor and normal-appearing white matter on CBV maps. Receiver operating characteristics (ROC) curves associating nCBV with 15-month OS were calculated for both GN-nCBV and WN-nCBV. Reproducibility and interoperator variability were compared using within-subject coefficient of variation (wCV) and intraclass correlation coefficients (ICCs).

resultsGN-nCBV ICC (≥0.82) and wCV (≤21%) were superior to WN-nCBV ICC (0.54-0.55) and wCV (≥46%). The area under the ROC curve analysis demonstrated both GN-nCBV and WN-nCBV to be good predictors of OS, but GN-nCBV was consistently superior, although the difference was not statistically significant.

conclusionGN-nCBV has a slightly better association with clinical gold standard OS than conventional WM-nCBV in our glioblastoma patient cohort. This equivalent or superior validity, combined with the advantages of higher reproducibility, lower interoperator variability, and easier automation, makes GN-nCBV superior to WM-nCBV for clinical and research use in glioma patients. We recommend widespread adoption and incorporation of GN-nCBV into commercial dynamic susceptibility contrast processing software.

Identifiers

PMID30216765
PMCPMC6138997

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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.