Evidence map›Paper›PMID 42149177›Full record

ReviewRecent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer2026

(Hybrid) SPECT and PET Technologies.

Teresa Lemainque, Nicolas Gross-Weege, Volkmar Schulz

Abstract readReview
PubMed Publisher
In one paragraph

Review in Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer, 2026. 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
–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

0 citing papers in PubMed.

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

3 authors.

Teresa LemainqueChair of Diagnostic and Interventional Radiology, University Clinic RWTH Aachen, Aachen, Germany.
Nicolas Gross-WeegeChair of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany.
Volkmar SchulzChair of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany. volkmar.schulz@lfb.rwth-aachen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SPECT and PET are nuclear tomographic imaging modalities that visualize functional information based on the accumulation of radioactive tracer molecules. However, SPECT and PET lack anatomical information, which has motivated their combination with an anatomical imaging modality such as CT or MRI. This chapter begins with an overview of the fundamental physics of SPECT and PET, followed by a presentation of the respective detector technologies, including detection requirements, principles, and different detector concepts. The reader is subsequently provided with an introduction to hybrid imaging concepts, before a dedicated section presents the challenges that arise when hybridizing SPECT or PET with MRI, namely, mutual distortions of the different electromagnetic fields in MRI on the nuclear imaging system and vice versa, and MR-based attenuation correction. The chapter then gives an overview about current hybrid imaging systems of both clinical and preclinical kinds and recent technological developments such as total body PET-CT, before describing the role of artificial intelligence in hybrid imaging. Finally, future developments in hybrid SPECT and PET technology are discussed.

Indexed as

Multimodal ImagingPositron-Emission TomographyTomography, Emission-Computed, Single-PhotonAnimalsArtificial IntelligenceHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingRadioactive TracersTomography, X-RayRadioactive TracersArtificial intelligenceAttenuation correctionDetector technologyHybrid imagingImage reconstructionPET-CTPET-MRISPECT-CTSPECT-MRI

Identifiers

PMID42149177

What OpenQuestion holds

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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.