Evidence map›Paper›PMID 33517495›Full record

ReviewEuropean journal of orthopaedic surgery & traumatology : orthopedie traumatologie2021

Quantitative imaging of the spine in adolescent idiopathic scoliosis: shifting the paradigm from diagnostic to comprehensive prognostic evaluation.

Saba Pasha, Chamith R Rajapaske, Ravinder Reddy, Bassel Diebo, Patrick Knott, Brandon C Jones, Dushyant Kumar, Winnie Zhu, Edmond Lou, Nadav Shapira and 3 more

Abstract readReview
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In one paragraph

Review in European journal of orthopaedic surgery & traumatology : orthopedie traumatologie, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
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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

13 authors at 6 institutions in 2 countries.

Saba PashaDepartment of Orthopaedic Surgery, University of Pennsylvania, Philadelphia, USA. pashas@pennmedicine.upenn.edu.ORCID http://orcid.org/0000-0001-9172-2049
Chamith R RajapaskeDepartment of Orthopaedic Surgery, University of Pennsylvania, Philadelphia, USA.
Ravinder ReddyDepartment of Radiology, University of Pennsylvania, Philadelphia, USA.
Bassel DieboState University of New York Downstate Medical Center, New York, USA.
Patrick KnottRosalind Franklin University of Medicine and Science, Chicago, USA.
Brandon C JonesDepartment of Radiology, University of Pennsylvania, Philadelphia, USA.
Dushyant KumarDepartment of Radiology, University of Pennsylvania, Philadelphia, USA.
Winnie ZhuDepartment of Radiology, The Children's Hospital of Philadelphia, Philadelphia, USA.
Edmond LouDepartment of Electrical Computer Engineering, University of Alberta, Edmonton, Canada.
Nadav ShapiraDepartment of Radiology, University of Pennsylvania, Philadelphia, USA.
Peter NoelDepartment of Radiology, University of Pennsylvania, Philadelphia, USA.
Victor Ho-FungDepartment of Radiology, The Children's Hospital of Philadelphia, Philadelphia, USA.
Diego JaramilloDepartment of Radiology, Columbia University, New York, USA.
University of Pennsylvania · USChildren's Hospital of Philadelphia · USColumbia University · USRosalind Franklin University of Medicine and Science · USState University of New York · USUniversity of Alberta · CA

Funding

Data-Driven Framework for Classification and Surgical Planning of Spinal Deformity.R21AR075971 · NIAMS · UNIVERSITY OF PENNSYLVANIA · PI PASHA, SABA, WINKELSTEIN, BETH A · 2020 to 2021
$406k
NIAMS NIH HHS R21 AR075971NIH HHS NIH R01 AR068382 and R01 AR076392
6 · The paper itself

Abstract

purposeWe aimed to provide a perspective review of the available quantitative imaging modalities of the spine for prognostic evaluation of the adolescent idiopathic scoliosis (AIS).

methodsA technical description of the current imaging technologies for quantitative assessment of the pediatric spine with scoliosis was provided, and the pros and cons of each method were discussed. Imaging modalities that quantify the overall 3D alignment of the spine as well as the structural specification of the spinal bone, intervertebral disc, endplates, and ligaments as it pertains to development and progression of the idiopathic spinal deformities in adolescents were discussed.

resultsLow-dose and microdose stereoradiography, ultrasound, and rasterstereography provide quantitative imaging of the 3D spinal alignment with low or no radiation in standing posture which allows repetitive imaging for early detection of the curve development. Quantitative magnetic resonance imaging, including ultrashort dual-echo time and T1-rho can provide quantitative assessment of the spinal tissues relevant to development of idiopathic spinal deformity in pediatric population. New computed tomography scans that uses dual-energy can provides high-resolution measure of the current-state of the bone quality and morphology as well as the osteogenic properties of the bone by quantitative evaluation of the bone marrow.

conclusionThe presented imaging modalities can provide a wide spectrum of quantifiable information relevant to development and progression of the spinal deformity. Clinical application of these technologies can change the paradigm in clinical assessment of the pediatric scoliosis by improving our understanding of the pathogenesis of the idiopathic scoliosis.

Indexed as

Intervertebral DiscKyphosisScoliosisAdolescentChildHumansImaging, Three-DimensionalMagnetic Resonance ImagingPrognosisSpineAdolescent Idiopathic ScoliosisMagnetic resonanceQuantitative Medical ImagingRasterstereographySpineUltrasound

Identifiers

PMID33517495
OpenAlexW3128786682

What OpenQuestion holds

Textmetadata
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.