Evidence map›Paper›PMID 33458387›Full record

ArticlePhysics and imaging in radiation oncology2018

Analyses of regional radiosensitivity of white matter structures along tract axes using novel white matter segmentation and diffusion imaging biomarkers.

Jordan Houri, Roshan Karunamuni, Michael Connor, Niclas Pettersson, Carrie McDonald, Nikdokht Farid, Nathan White, Anders Dale, Jona A Hattangadi-Gluth, Vitali Moiseenko

Open access · goldAbstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
  4. Article
  5. Imaging science and development in modern high-precision radiotherapy.Physics and imaging in radiation oncology · 2019
    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

10 authors at 2 institutions in 3 countries.

Jordan HouriDepartment of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
Roshan KarunamuniDepartment of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
Michael ConnorDepartment of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
Niclas PetterssonDepartment of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
Carrie McDonaldDepartment of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
Nikdokht FaridDepartment of Radiology, University of California San Diego, La Jolla, CA, USA.
Nathan WhiteDepartment of Radiology, University of California San Diego, La Jolla, CA, USA.
Anders DaleDepartment of Radiology, University of California San Diego, La Jolla, CA, USA.
Jona A Hattangadi-GluthDepartment of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
Vitali MoiseenkoDepartment of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
University of California San Diego · USSahlgrenska University Hospital · SE

Funding

San Diego Clinical and Translational Research InstituteUL1TR000100 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S · 2012 to 2015
$19.7M
Multimodal Imaging of Language in the Preoperative Evaluation of EpilepsyR01NS065838 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCDONALD, CARRIE R · 2010 to 2018
$4.4M
Clinical and Transtional Science InstituteTL1TR000144 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GRANDIS, JENNIFER RUBIN · 2012 to 2015
$643k
HSRD VA TPR 15-229NCATS NIH HHS TL1 TR000144NCATS NIH HHS UL1 TR000100NINDS NIH HHS R01 NS065838
6 · The paper itself

Abstract

background and purposeBrain radiotherapy (RT) can cause white matter damage and downstream neurocognitive decline. We developed a computational neuroimaging tool to regionally partition individual white matter tracts, then analyze regional changes in diffusion metrics of white matter damage following brain RT. MATERIALS AND

methodsRT dose, diffusion metrics and white matter tract structures were extracted and mapped to a reference brain for 49 patients who received brain RT, and underwent diffusion tensor imaging pre- and 9-12 months post-RT. Based on their elongation, 23 of 48 white matter tracts were selected. The Tract-Crawler software was developed in MATLAB to create cross-sectional slice planes normal to a tract's computed medial axis. We then performed slice- and voxel-wise analysis of radiosensitivity, defined as percent change in mean diffusivity (MD) and fractional anisotropy (FA) as a function of dose relative to baseline.

resultsDistinct patterns of FA/MD radiosensitivity were seen for specific tracts, including the corticospinal tract, medial lemniscus, and inferior cerebellar peduncle, in particular at terminal ends. These patterns persisted for corresponding tracts in left and right hemispheres. Local sensitivities were as high as 40%/Gy (e.g., voxel-wise: -39 ± 31%/Gy in right corticospinal tract FA, -45 ± 25%/Gy in right inferior cerebellar peduncle FA), p < 0.05.

conclusionsTract-Crawler, a novel tool to visualize and analyze cuts of white matter structures normal to medial axes, was used to demonstrate that particular white matter tracts exhibit significant regional variations in radiosensitivity based on diffusion biomarkers.

Indexed as

Diffusion tensor imagingRadiation therapyWhite matter

Identifiers

PMID33458387
PMCPMC7807616
OpenAlexW2802116845

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.