Evidence map›Paper›PMID 39883257›Full record

ReviewEJNMMI physics2025

A review of state-of-the-art resolution improvement techniques in SPECT imaging.

Zhibiao Cheng, Ping Chen, Jianhua Yan

Abstract readReview
In one paragraph

Review in EJNMMI physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Clinical performance of [European journal of nuclear medicine and molecular imaging · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Quantitative SPECT/CT: Technique and Clinical Applications.Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer · 2026
    Review
  12. Review
  13. Review
  14. AI in SPECT Imaging: Opportunities and Challenges.Seminars in nuclear medicine · 2025
    Review
  15. 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

3 authors.

Zhibiao ChengSchool of Information and Communication Engineering, North University of China, Taiyuan, 030051, China. zhibiao.cheng@foxmail.com.ORCID http://orcid.org/0000-0001-7636-5311
Ping ChenSchool of Information and Communication Engineering, North University of China, Taiyuan, 030051, China. chenping@nuc.edu.cn.
Jianhua YanDepartment of Nuclear Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, Anhui, China. Jianhua.yan@gmail.com.

Funding

Fundamental Research Program of Shanxi Province, China 202403021212022National Key R&D Program of China 2023YFE0205800National Natural Science Foundation of China U23A20285Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi, China 2024L191
6 · The paper itself

Abstract

Single photon emission computed tomography (SPECT), a technique capable of capturing functional and molecular information, has been widely adopted in theranostics applications across various fields, including cardiology, neurology, and oncology. The spatial resolution of SPECT imaging is relatively poor, which poses a significant limitation, especially the visualization of small lesions. The main factors affecting the limited spatial resolution of SPECT include projection sampling techniques, hardware and software. Both hardware and software innovations have contributed substantially to improved SPECT imaging quality. The present review provides an overview of state-of-the-art methods for improving spatial resolution in clinical and pre-clinical SPECT systems. It delves into advancements in detector design and modifications, projection sampling techniques, traditional reconstruction algorithm development and optimization, and the emerging role of deep learning. Hardware enhancements can result in SPECT systems that are both lighter and more compact, while also improving spatial resolution. Software innovations can mitigate the costs of hardware modifications. This survey offers a thorough overview of the rapid advancements in resolution enhancement techniques within the field of SPECT, with the objective of identifying the most recent trends. This is anticipated to facilitate further optimization and improvement of clinical systems, enabling the visualization of small lesions in the early stages of tumor detection, thereby enhancing accurate localization and facilitating both diagnostic imaging and radionuclide therapy, ultimately benefiting both clinicians and patients.

Indexed as

Deep learningHardwareResolution improvementSoftwareSPECT system

Identifiers

PMID39883257
PMCPMC11782768

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.