Evidence map›Paper›PMID 38082197›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2024

Ultra-fast whole-body bone tomoscintigraphies achieved with a high-sensitivity 360° CZT camera and a dedicated deep-learning noise reduction algorithm.

Achraf Bahloul, Antoine Verger, Yechiel Lamash, Nathaniel Roth, Diawad Dari, Pierre-Yves Marie, Laetitia Imbert

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Article in European journal of nuclear medicine and molecular imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Quantitative SPECT/CT: Technique and Clinical Applications.Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer · 2026
    Review
  4. Article
  5. An European consensus on [EJNMMI physics · 2025
    Article
  6. Article
  7. 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

7 authors.

Achraf BahloulCHRU-Nancy, Department of Nuclear Medicine & Nancyclotep imaging platform, Université de Lorraine, Nancy, France.
Antoine VergerCHRU-Nancy, Department of Nuclear Medicine & Nancyclotep imaging platform, Université de Lorraine, Nancy, France.
Yechiel LamashSpectrum Dynamics Medical, Caesarea, Israel.
Nathaniel RothSpectrum Dynamics Medical, Caesarea, Israel.
Diawad DariCHRU-Nancy, Department of Nuclear Medicine & Nancyclotep imaging platform, Université de Lorraine, Nancy, France.
Pierre-Yves MarieCHRU-Nancy, Department of Nuclear Medicine & Nancyclotep imaging platform, Université de Lorraine, Nancy, France.
Laetitia ImbertCHRU-Nancy, Department of Nuclear Medicine & Nancyclotep imaging platform, Université de Lorraine, Nancy, France. l.imbert@chru-nancy.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 min, routinely provided by a high-sensitivity 360° cadmium and zinc telluride (CZT) camera, can be further reduced by a deep-learning noise reduction (DLNR) algorithm.

methodsDLNR was applied on whole-body images recorded after the injection of 545 ± 33 MBq of [

resultsIrrespective of recording time, DLNR enhanced the contrast-to-noise ratios and slightly decreased the standardized uptake values of bone lesions. Except in one markedly obese patient, the quality of DLNR processed images remained good-to-excellent down to 60% of the recording time, corresponding to around 6 min SPECT-recording.

conclusionUltra-fast SPECT recordings of 6 min can be achieved when DLNR is applied on whole-body bone 360° CZT-SPECT.

Indexed as

CadmiumDeep LearningHumansTelluriumTomography, Emission-Computed, Single-PhotonZincCadmiumCdZnTeTelluriumZincBone scintigraphyDeep learningRecording timeWhole-body CZT-camera

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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.