Evidence map›Paper›PMID 31403226›Full record

ArticleMagnetic resonance in medicine2020

MEMRI-based imaging pipeline for guiding preclinical studies in mouse models of sporadic medulloblastoma.

Harikrishna Rallapalli, I-Li Tan, Eugenia Volkova, Alexandre Wojcinski, Benjamin C Darwin, Jason P Lerch, Alexandra L Joyner, Daniel H Turnbull

Open access · greenAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 33% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

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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

8 authors at 5 institutions in 2 countries.

Harikrishna RallapalliSkirball Institute of Biomolecular Medicine, New York University School of Medicine, New York, New York.
I-Li TanDevelopmental Biology Program, Sloan Kettering Institute, New York, New York.
Eugenia VolkovaSkirball Institute of Biomolecular Medicine, New York University School of Medicine, New York, New York.
Alexandre WojcinskiDevelopmental Biology Program, Sloan Kettering Institute, New York, New York.
Benjamin C DarwinMouse Imaging Centre, The Hospital for Sick Children, Toronto, Ontario, Canada.
Jason P LerchMouse Imaging Centre, The Hospital for Sick Children, Toronto, Ontario, Canada.
Alexandra L JoynerDevelopmental Biology Program, Sloan Kettering Institute, New York, New York.
Daniel H TurnbullSkirball Institute of Biomolecular Medicine, New York University School of Medicine, New York, New York.ORCID 0000-0003-0889-5155
New York University · USCornell University · USHospital for Sick Children · CAKettering University · USUniversity of Toronto · CA

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Ultrasound and MR Imaging of Mouse Brain Development.R01NS038461 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI TURNBULL, DANIEL H · 1999 to 2016
$6.5M
Quantitative Imaging of Mouse Brain DevelopmentR01NS102904 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ZHANG, JIANGYANG · 2018 to 2022
$3.1M
Developmental studies to inform clinical stratification and targeting of SHH MBR01CA192176 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI JOYNER, ALEXANDRA L. · 2016 to 2020
$2.3M
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA192176NINDS NIH HHS R01 NS038461NINDS NIH HHS R01 NS102904
6 · The paper itself

Abstract

purposeGenetically engineered mouse models of sporadic cancers are critical for studying tumor biology and for preclinical testing of therapeutics. We present an MRI-based pipeline designed to produce high resolution, quantitative information about tumor progression and response to novel therapies in mouse models of medulloblastoma (MB).

methodsSporadic MB was modeled in mice by inducing expression of an activated form of the Smoothened gene (aSmo) in a small number of cerebellar granule cell precursors. aSmo mice were imaged and analyzed at defined time-points using a 3D manganese-enhanced MRI-based pipeline optimized for high-throughput.

resultsA semi-automated segmentation protocol was established that estimates tumor volume in a time-frame compatible with a high-throughput pipeline. Both an empirical, volume-based classifier and a linear discriminant analysis-based classifier were tested to distinguish progressing from nonprogressing lesions at early stages of tumorigenesis. Tumor centroids measured at early stages revealed that there is a very specific location of the probable origin of the aSmo MB tumors. The efficacy of the manganese-enhanced MRI pipeline was demonstrated with a small-scale experimental drug trial designed to reduce the number of tumor associated macrophages and microglia.

conclusionOur results revealed a high level of heterogeneity between tumors within and between aSmo MB models, indicating that meaningful studies of sporadic tumor progression and response to therapy could not be conducted without an imaging-based pipeline approach.

Indexed as

Magnetic Resonance ImagingAlgorithmsAnimalsCerebellumDiscriminant AnalysisDisease Models, AnimalDisease ProgressionImage Processing, Computer-AssistedImaging, Three-DimensionalLinear ModelsMedulloblastomaMicePattern Recognition, AutomatedSignal TransductionSmoothened ReceptorSmoothened ReceptorSmo protein, mouselinear discriminant analysis (LDA)MRIsegmentation; Sonic hedgehog (SHH)tumor associated macrophages and microglia (TAMs)

Identifiers

PMID31403226
PMCPMC6778701
OpenAlexW2969025765

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.