Evidence map›Paper›PMID 29891199›Full record

ArticleInternational journal of radiation oncology, biology, physics2018

Velocity-based Adaptive Registration and Fusion for Fractionated Stereotactic Radiosurgery Using the Small Animal Radiation Research Platform.

Paul J Black, Deborah R Smith, Kunal Chaudhary, Eric P Xanthopoulos, Christine Chin, Catherine S Spina, Mark E Hwang, Mark Mayeda, Yi-Fang Wang, Eileen P Connolly and 5 more

Open access · greenAbstract read
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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

15 authors at 1 institution in 1 country.

Paul J BlackDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Deborah R SmithDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Kunal ChaudharyDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Eric P XanthopoulosDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Christine ChinDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Catherine S SpinaDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Mark E HwangDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Mark MayedaDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Yi-Fang WangDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Eileen P ConnollyDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Tony J C WangDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York; Department of Neurological Surgery, Columbia University Medical Center, New York, New York; Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York.
Cheng-Shie WuuDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York.
Tom K HeiDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York; Center for Radiological Research, Columbia University, New York, New York.
Simon K ChengDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York. Electronic address: sc3225@cumc.columbia.edu.
Cheng-Chia WuDepartment of Radiation Oncology, Columbia University Medical Center, New York, New York. Electronic address: chw9088@nyp.org.
Columbia University Irving Medical Center · US

Funding

Small Animal CT Image Guided Xray Irradiation SystemS10OD010631 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WUU, CHENG-SHIE · 2012 to 2012
$590k
NIH HHS S10 OD010631
6 · The paper itself

Abstract

purposeTo implement Velocity-based image fusion and adaptive deformable registration to enable treatment planning for preclinical murine models of fractionated stereotactic radiosurgery (fSRS) using the small animal radiation research platform (SARRP). METHODS AND MATERIALS: C57BL6 mice underwent 3 unique cone beam computed tomography (CBCT) scans: 2 in the prone position and a third supine. A single T1-weighted post-contrast magnetic resonance imaging (MRI) series of a murine metastatic brain tumor model was selected for MRI-to-CBCT registration and gross tumor volume (GTV) identification. Two arms were compared: Arm 1, where we performed 3 individual MRI-to-CBCT fusions using rigid registration, contouring GTVs on each, and Arm 2, where the authors performed MRI-to-CBCT fusion and contoured GTV on the first CBCT followed by Velocity-based adaptive registration. The first CBCT and associated GTV were exported from MuriPlan (Xstrahl Life Sciences) into Velocity (Varian Medical Systems, Inc, Palo Alto, CA). In Arm 1, the second and third CBCTs were exported similarly along with associated GTVs (Arm 1), while in Arm 2, the first (prone) CBCT was fused separately to the second (prone) and third (supine) CBCTs, performing deformable registrations on initial CBCTs and applying resulting matrices to the contoured GTV. Resulting GTVs were compared between Arms 1 and 2.

resultsComparing GTV overlays using repeated MRI fusion and GTV delineation (Arm 1) versus those of Velocity-based CBCT and GTV adaptive fusion (Arm 2), mean deviations ± standard deviation in the axial, sagittal, and coronal planes were 0.46 ± 0.16, 0.46 ± 0.22, and 0.37 ± 0.22 mm for prone-to-prone and 0.52 ± 0.27, 0.52 ± 0.36, and 0.68 ± 0.31 mm for prone-to-supine adaptive fusions, respectively.

conclusionsVelocity-based adaptive fusion of CBCTs and contoured volumes allows for efficient fSRS planning using a single MRI-to-CBCT fusion. This technique is immediately implementable on current SARRP systems, facilitating advanced preclinical treatment paradigms using existing clinical treatment planning software.

Indexed as

AnimalsBrain NeoplasmsCone-Beam Computed TomographyMagnetic Resonance ImagingMaleMiceMice, Inbred C57BLRadiosurgeryRadiotherapy Planning, Computer-AssistedTumor Burden

Identifiers

PMID29891199
PMCPMC6202197
OpenAlexW2800677298

What OpenQuestion holds

Textmetadata
LicenceTDM
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.