Evidence map›Paper›PMID 35332447›Full record

ArticleMolecular imaging and biology2022

The Performance Comparison of

Haiqun Xing, Haiyan Ding, Bo Hou, Zhixin Hao, Ya Hu, Wenjia Zhu, Sayuan Liang, Feng Feng, Fang Li, Yupei Zhao and 1 more

Abstract read
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In one paragraph

Article in Molecular imaging and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 57% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 3 institutions in 1 country.

Haiqun XingDepartment of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan, Beijing, 100730, Dongcheng District, China.
Haiyan DingCenter for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Bo HouDepartments of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Zhixin HaoDepartment of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan, Beijing, 100730, Dongcheng District, China.
Ya HuDepartment of General Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Wenjia ZhuDepartment of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan, Beijing, 100730, Dongcheng District, China.
Sayuan LiangPET/MR Modality, GE Healthcare China, Beijing, 100176, China.
Feng FengDepartments of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Fang LiDepartment of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan, Beijing, 100730, Dongcheng District, China.
Yupei ZhaoDepartment of General Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Li HuoDepartment of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan, Beijing, 100730, Dongcheng District, China. huoli@pumch.cn.
Peking Union Medical College Hospital · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo determine the optimal imaging tool for clinical evaluation of pancreatic neoplasm by comparing the performance of PROCEDURES: Patients with suspected pancreatic neoplasms underwent PET/MRI and PET/CT in the same day prior to resection or endoscopic ultrasound-guided fine-needle aspiration. Histology served as the golden standard of lesion classification. Visual assessment on lesion type and lesion malignancy via PET/MRI and PET/CT images was compared. Standard uptake values (SUVs) of PET images from the two scanners were measured and their correlations were further evaluated.

resultsThirty-nine patients were included for the final analysis. In visual assessment, we found MRI achieved better performance than CT in differentiating solid and cystic neoplasms, with accuracy of 100% vs. 87%, respectively. In visual malignancy diagnosis, the accuracy of PET/CT was 92.3% for overall lesions and 90.9% for cysts, while the accuracy of PET/MRI was 92.3% and 86.4%, respectively. Besides, semi-quantitative analysis achieved better specificity than visual assessment for both hybrid modalities (100% vs. 87.5% for PET/CT; 100% vs. 81.5% for PET/MR). Furthermore, strong correlation of SUV was found between PET/CT and PET/MRI, with Pearson's correlation coefficients > 0.82.

conclusionsIn this study, we found PET/MRI and PET/CT, both using

Indexed as

Fluorodeoxyglucose F18Pancreatic NeoplasmsHumansMagnetic Resonance ImagingPositron-Emission TomographyPositron Emission Tomography Computed TomographyRadiopharmaceuticalsTomography, X-Ray ComputedFluorodeoxyglucose F18Radiopharmaceuticals18F-FDGPancreatic neoplasmPET/CTPET/MRSUV

Identifiers

PMID35332447
OpenAlexW4220711835

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.