Evidence map›Paper›PMID 37121955›Full record

ArticleInsights into imaging2023

Dual-energy CT virtual non-calcium: an accurate method for detection of knee osteoarthritis-related edema-like marrow signal intensity.

Heng Zhao, Hui Li, Xia Xie, Hai-Yan Tang, Xiao-Xin Liu, Yi Wen, Xin Xiao, Lu Ye, You-Wei Tang, Gao-Yue Dai and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Insights into imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

2 citing papers in PubMed.

  1. Review
  2. Review
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

15 authors.

Heng Zhao *The First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Hui Li *The First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Xia XieThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Hai-Yan TangThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Xiao-Xin LiuThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Yi WenThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Xin XiaoThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Lu YeThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
You-Wei TangThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Gao-Yue DaiThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Jia-Ni HeThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Li ChenThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Qian WangThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
De-Qiu TangThe First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China. deqiu.t@163.com.
Shi-Nong PanDepartment of Radiology, Shengjing Hospital of China Medical University, Sanhao Street No. 36, Heping District, Shenyang, 110004, Liaoning, China. cjr.panshinong@vip.163.com.

Funding

345 Talent Project and Natural Science Foundation of Liaoning Province Grant No. 2019-ZD-0794Hunan Provincial Science and Technology Innovation Program of China Grant No. 2021JJ30621Scientific Research Project of Hunan Provincial Department of Education, Key project Grant No. 20A437Scientific research project of hunan provincial health department of China Grant No. B2004-097the National Natural Science Foundation of China Grant No. 81271538
6 · The paper itself

Abstract

objectivesTo evaluate the performance of a dual-energy computed tomography (DECT) virtual non-calcium (VNCa) technique in the detection of edema-like marrow signal intensity (ELMSI) in patients with knee joint osteoarthritis (OA) compared to magnetic resonance imaging (MRI).

methodsThe study received local ethics board approval, and written informed consent was obtained. DECT and MRI were used to examine 28 knees in 24 patients with OA. VNCa images were generated by dual-energy subtraction of calcium. The knee joint was divided into 15 regions for ELMSI grading, performed independently by two musculoskeletal radiologists, with MRI as the reference standard. We also analyzed CT numbers through receiver operating characteristics and calculated cut-off values.

resultsFor the qualitative analysis, we obtained CT sensitivity (Readers 1, 2 = 83.7%, 89.8%), specificity (Readers 1, 2 = 99.5%, 99.5%), positive predictive value (Readers 1, 2 = 95.3%, 95.7%), and negative predictive value (Readers 1, 2 = 97.9%, 98.7%) for ELMSI. The interobserver agreement was excellent (κ = 0.92). The area under the curve for Reader 1 and Reader 2 was 0.961 (95% CI 0.93, 0.99) and 0.992 (95% CI 0.98, 1.00), respectively. CT numbers obtained from the VNCa images were significantly different between regions with and without ELMSI (p < .001).

conclusionsVNCa images have good diagnostic performance for the qualitative and quantitative analysis of knee osteoarthritis-related ELMSI.

Indexed as

Edema like marrow signal intensityMRIOsteoarthritisVirtual non-calcium

Identifiers

PMID37121955
PMCPMC10149542

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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.