Evidence map›Paper›PMID 17786434›Full record

ArticleSkeletal radiology2007

Optimization of b value in diffusion-weighted MRI for the differential diagnosis of benign and malignant vertebral fractures.

Guangyu Tang, Yong Liu, Wei Li, Jiping Yao, Baoping Li, Peng Li

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Skeletal radiology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
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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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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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  8. Evaluation of Apparent Diffusion Coefficient Values in Spinal Tuberculosis by MRI.Journal of clinical and diagnostic research : JCDR · 2016
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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

6 authors.

Guangyu TangDepartment of Radiology, Affiliated Tenth People's Hospital of Tongji University, Shanghai 200072, China. guangyutang@tom.com
Yong Liu
Wei Li
Jiping Yao
Baoping Li
Peng Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe objective was to explore the optimal b value in diffusion-weighted imaging (DWI) of MRI for differential diagnosis of benign and malignant vertebral fractures. MATERIALS AND

methodsThirty-four consecutive patients with vertebral compression fractures underwent sagittal diffusion-weighted imaging (DWI) with different b values. The group included 14 patients with 18 benign vertebral fractures due to osteoporosis and/or trauma and 20 patients with 27 malignant vertebral fractures due to malignancy. The quality of the images was analyzed qualitatively on a three-point scale and quantitatively by measurement of the signal-to-noise ratio (SNR). Apparent diffusion coefficient (ADC) values were also calculated.

resultsSmaller b values correlated with better DW image quality. We found significant differences in the qualitative points values among the DW images with different b values (F=302.18, p<0.001). The mean SNR of the images ranged from 21.75+/-3.64 at a b value of 0 s/mm2 to 5.31+/-3.17 at a b value of 800 s/mm2. The SNR of DWI with a b value of 300 s/mm2 (18.62+/-2.47) was significantly different from that with other b values (p<0.01). The mean combined ADC values of malignant fractures were significantly lower than those of benign ones on DWI with a b value of 300 s/mm2 (t=9.097, p<0.01). Four cases of benign vertebral fractures were misdiagnosed as being malignant when b values of 0 s/mm2 and 100 s/mm2 were used.

conclusionsWhen DWI with multiple b values is used to differentiate benign from malignant vertebral compression fractures, b values within the range of around 300 s/mm2 are recommended, taking into account both SNR and diffusion weighting of water molecules.

Indexed as

AdultAgedArtifactsCarcinomaDiagnosis, DifferentialDiffusion Magnetic Resonance ImagingEcho-Planar ImagingFemaleFractures, CompressionHumansImage EnhancementImage Processing, Computer-AssistedMaleMiddle AgedOsteoporosisProspective Studies

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Registered trials

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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.