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Related Concept Videos

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Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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Overview of Advanced Functional Groups02:22

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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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Accurate analysis of complex samples often requires advanced preparation techniques to achieve reliable and reproducible results. Samples containing inorganic or organic materials can be challenging to dissolve or decompose effectively. Standard sample preparation methods include acid digestion, fusion, dry ashing, and wet digestion.
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Related Experiment Video

Updated: Jan 30, 2026

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
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Multisite reliability and repeatability of an advanced brain MRI protocol.

Daniel L Schwartz1,2, Ian Tagge1, Katherine Powers1

  • 1Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA.

Journal of Magnetic Resonance Imaging : JMRI
|January 18, 2019
PubMed
Summary
This summary is machine-generated.

This study assessed the reliability and repeatability of advanced MRI techniques across multiple sites. Quantitative magnetization transfer ratio (MTR) and longitudinal relaxation rate (R1) showed excellent reliability and repeatability for neuroimaging studies.

Keywords:
MRImultiple sclerosismultisitereliabilityrepeatability

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Area of Science:

  • Neuroimaging
  • Medical Imaging
  • Radiology

Background:

  • Magnetic Resonance Imaging (MRI) is crucial for neurological disease diagnosis and treatment assessment.
  • Harmonizing advanced MRI techniques across multiple sites remains a challenge, limiting its full potential.
  • Standardization is needed for reliable multisite neuroimaging studies.

Purpose of the Study:

  • To develop and assess a method for evaluating the reliability and repeatability of advanced multisite neuroimaging studies.
  • To specifically evaluate the reliability of an advanced MRI protocol, including multiband fMRI and diffusion tensor MRI, in a multisite setting.
  • To introduce new statistical and graphical methods for assessing reliability and repeatability.

Main Methods:

  • A prospective study involving a single subject with relapsing-remitting multiple sclerosis (MS) measured twice at seven institutions.
  • An advanced 3 Tesla (T) MRI protocol was used, including high-resolution anatomical scans, quantitative R1 mapping, quantitative magnetization transfer imaging (MTI), diffusion tensor imaging (DTI), and resting-state functional MRI (rsFMRI).
  • Intrasite repeatability and intersite reliability were assessed using Student's t-test, Pearson's r, and intraclass correlation coefficient (ICC), alongside novel statistical metrics and a graphical assessment method.

Main Results:

  • Intrasite repeatability was excellent for quantitative R1, MTR, and diffusion-weighted imaging (DWI) metrics (r > 0.95), but less so for rsFMRI (r = 0.8).
  • Intersite reliability was excellent for R1, MTR, and DWI (ICC > 0.9), and moderate for rsFMRI (ICC ≈ 0.4).
  • A new reliability metric ranked MTR > R1 > DWI > rsFMRI, and for repeatability, MTR > DWI > R1 > rsFMRI.

Conclusions:

  • Quantitative R1 and MTR demonstrate high reliability and repeatability in multisite neuroimaging, making them suitable for advanced studies.
  • rsFMRI metrics showed lower reliability and repeatability, indicating a need for further standardization.
  • The developed methods provide a robust framework for assessing and ensuring the quality of multisite, multisession neuroimaging data.