Evidence map›Paper›PMID 34854969›Full record

ArticleSkeletal radiology2022

An Investigation of 2D Spine Magnetic Resonance Imaging (MRI) with Compressed Sensing (CS).

Jianxing Qiu, Jing Liu, Zhongxu Bi, Xiaowei Sun, Qingping Gu, Geli Hu, Naishan Qin

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Article in Skeletal radiology, 2022. 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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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

3 citing papers in PubMed.

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4 · The record

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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

7 authors.

Jianxing QiuDepartment of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China.
Jing LiuDepartment of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China.
Zhongxu BiDepartment of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China.
Xiaowei SunDepartment of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China.
Qingping GuPhilips Healthcare, Beijing, China.
Geli HuPhilips Healthcare, Beijing, China.
Naishan QinDepartment of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China. Qinnaishan@bjmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the feasibility of compressed sensing MRI (CS-MRI) in the application of 2D spinal imaging and compare its performance with conventional MR imaging (non-CS-MRI).

methodsThe CS imaging protocol was optimized on 5 volunteers. Non-CS-MRI and CS-MRI of 2D sagittal T1 weighted imaging (WI), Sag T2WI, and axial T2WI were performed for 71 patients (22 cervical, 8 thoracic, 41 lumbar MRI). Paired t tests were conducted to compare the total scan time. Three radiologists assessed image quality and lesion diagnosis independently. A Kendall W test was performed to assess interobserver agreement of the image quality scores and lesion diagnosis between readers. A nonparametric test (Wilcoxon test) was performed to compare the image quality. For lesion diagnosis, the interobserver and interstudy agreements were evaluated by kappa analysis. Paired t tests were conducted for SNR and CNR comparison.

resultsThe mean scan time for spine CS-MRI (4 min 28.7 s ± 34.6 s) was significantly shorter than that with non-CS-MRI (7 min 21.3 s ± 38.7 s, t =  - 47.464, P < 0.0001). CS-MRI achieved higher SNR and CNR than Non-CS-MRI in image quality assessment. Interobserver agreements of lesion diagnosis were excellent between non-CS-MRI and CS-MRI (kappa value from 0.913 to 1.000, P < 0.001). Interstudy agreements of lesion assessments were also excellent (kappa value = 1.000, with P < 0.001).

conclusionCS-MRI spine imaging can significantly reduce the scan time, while maintaining comparable imaging quality to non-CS-MRI.

Indexed as

Imaging, Three-DimensionalMagnetic Resonance ImagingHumansPressureSpineCompressed sensingImage qualityLesion assessmentSpine magnetic resonance (MR) imaging

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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.