Evidence map›Paper›PMID 35006411›Full record

ArticleEJNMMI physics2022

The effect of Q.Clear reconstruction on quantification and spatial resolution of 18F-FDG PET in simultaneous PET/MR.

Defeng Tian, Hongwei Yang, Yan Li, Bixiao Cui, Jie Lu

Abstract read
In one paragraph

Article in EJNMMI physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Optimisation of Q.Clear (BSREM) Reconstruction Parameters forBioengineering (Basel, Switzerland) · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. β1600 Q.Clear Digital Reconstruction of [Journal of clinical medicine · 2024
    Article
  12. Reduction of [EJNMMI physics · 2024
    Article
  13. Reduced count pediatric whole-bodyPediatric radiology · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Article
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

5 authors.

Defeng TianDepartment of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45# Changchun Street, Xicheng District, Beijing, China.
Hongwei YangDepartment of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45# Changchun Street, Xicheng District, Beijing, China.
Yan LiDepartment of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45# Changchun Street, Xicheng District, Beijing, China.
Bixiao CuiDepartment of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45# Changchun Street, Xicheng District, Beijing, China.
Jie LuDepartment of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45# Changchun Street, Xicheng District, Beijing, China. imaginglu@hotmail.com.ORCID http://orcid.org/0000-0003-0425-3921

Funding

beijing municipal administration of hospitals clinical medicine development of special funding support DFL20180802national natural science foundation of china 81974261
6 · The paper itself

Abstract

backgroundQ.Clear is a block sequential regularized expectation maximization penalized-likelihood reconstruction algorithm for Positron Emission Tomography (PET). It has shown high potential in improving image reconstruction quality and quantification accuracy in PET/CT system. However, the evaluation of Q.Clear in PET/MR system, especially for clinical applications, is still rare. This study aimed to evaluate the impact of Q.Clear on the

methodsA PET National Electrical Manufacturers Association/ International Electrotechnical Commission (NEMA/IEC) phantom was scanned on GE SIGNA PET/MR, based on NEMA NU 2-2012 standard. Metrics including contrast recovery (CR), background variability (BV), signal-to-noise ratio (SNR) and spatial resolution were evaluated for phantom data. For clinical data, lesion SNR, signal to background ratio (SBR), noise level and visual scores were evaluated. PET images reconstructed from OSEM + TOF and Q.Clear were visually compared and statistically analyzed, where OSEM + TOF adopted point spread function as default procedure, and Q.Clear used different β values of 100, 200, 300, 400, 500, 800, 1100 and 1400.

resultsFor phantom data, as β value increased, CR and BV of all sizes of spheres decreased in general; images reconstructed from Q.Clear reached the peak SNR with β value of 400 and generally had better resolution than those from OSEM + TOF. For clinical data, compared with OSEM + TOF, Q.Clear with β value of 400 achieved 138% increment in median SNR (from 58.8 to 166.0), 59% increment in median SBR (from 4.2 to 6.8) and 38% decrement in median noise level (from 0.14 to 0.09). Based on visual assessment from two physicians, Q.Clear with β values ranging from 200 to 400 consistently achieved higher scores than OSEM + TOF, where β value of 400 was considered optimal.

conclusionsThe present study indicated that, on

Indexed as

OSEMPenalization factor βPET/MRQ.Clear

Identifiers

PMID35006411
PMCPMC8748582

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.