Evidence map›Paper›PMID 28556394›Full record

ArticleMagnetic resonance in medicine2018

A robust diffusion tensor model for clinical applications of MRI to cartilage.

Uran Ferizi, Amparo Ruiz, Ignacio Rossi, Jenny Bencardino, José G Raya

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Article in Magnetic resonance in medicine, 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Uran FeriziDepartment of Radiology, New York University School of Medicine, New York, New York, USA.
Amparo RuizDepartment of Radiology, New York University School of Medicine, New York, New York, USA.
Ignacio RossiCentro de Diagnostico Dr. Enrique Rossi, Buenos Aires, Argentina.
Jenny BencardinoDepartment of Radiology, New York University School of Medicine, New York, New York, USA.
José G RayaDepartment of Radiology, New York University School of Medicine, New York, New York, USA.

Funding

Diffusion Tensor Imaging as a Biomarker for the Early Diagnosis, Staging and Progression of OsteoarthritisR01AR067789 · NIAMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI RAYA GARCIA DEL OLMO, JOSE MARIA · 2015 to 2019
$2.8M
Diffusion Tensor Imaging as a Probe of Cartilage Integrity after Knee InjuryR21AR066897 · NIAMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BENCARDINO, JENNY T., RAYA GARCIA DEL OLMO, JOSE MARIA · 2014 to 2015
$410k
NIAMS NIH HHS R01 AR067789NIAMS NIH HHS R21 AR066897
6 · The paper itself

Abstract

purposeDiffusion tensor imaging (DTI) of articular cartilage is a promising technique for the early diagnosis of osteoarthritis (OA). However, in vivo diffusion tensor (DT) measurements suffer from low signal-to-noise ratio (SNR) that can result in bias when estimating the six parameters of the full DT, thus reducing sensitivity. This study seeks to validate a simplified four-parameter DT model (zeppelin) for obtaining more robust and sensitive in vivo DTI biomarkers of cartilage.

methodsWe use simulations in a substrate to mimic changes during OA; and analytic simulations of the DT drawn from a range of fractional anisotropies (FA) measured with high-quality DT data from ex vivo human cartilage. We also use in vivo data from the knees of a healthy subject and two OA patients with Kellgren-Lawrence (KL) grades 1 and 2.

resultsFor simulated in vivo cartilage SNR (∼25) and anisotropy levels, the estimated mean values of MD from the DT and zeppelin models were identical to the ground truth values. However, zeppelin's FA is more accurate in measuring water restriction. More specifically, the FA estimations of the DT model were additionally biased by between +2% and +48% with respect to zeppelin values. Additionally, both mean diffusivity (MD) and FA of the zeppelin had lower parameter variance compared to the full DT (F-test, P < 0.05). We observe the same trends from in vivo values of patient data.

conclusionThe zeppelin is more robust than the full DT for cartilage diffusion anisotropy and SNR at levels typically encountered in clinical applications of articular cartilage. Magn Reson Med 79:1157-1164, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Indexed as

AdultCartilage, ArticularComputer SimulationDiffusion Tensor ImagingFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedOsteoarthritis, KneeSignal-To-Noise Ratiobiomarkersdiffusion MRIkneeknee cartilageosteoarthritiszeppelin

Identifiers

PMID28556394
PMCPMC5705580

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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.