ReviewComputational and mathematical methods in medicine2016
Spectral Analysis of Dynamic PET Studies: A Review of 20 Years of Method Developments and Applications.
Review in Computational and mathematical methods in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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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.
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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.
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Who cites it
20 citing papers in PubMed.
- Muscarinic Receptor PET in Neurodegeneration: Promise, Pitfalls, and Translational Priorities.Medical sciences (Basel, Switzerland) · 2026Review
- Whole-Body Dynamic Positron Emission and Computed Tomography (WBD-PET/CT): Latest Developments, Challenges and Opportunities.Diagnostics (Basel, Switzerland) · 2026Review
- On the analysis of functional PET (fPET)-FDG: Baseline mischaracterization can introduce artifactual metabolic (de)activations.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Parametric net influx rate imaging ofAnnals of nuclear medicine · 2024Article
- Quantitation of dynamic total-body PET imaging: recent developments and future perspectives.European journal of nuclear medicine and molecular imaging · 2023Review
- Kinetic evaluation and assessment of longitudinal changes in reference region and extracerebral [Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023Article
- NRM 2021 Abstract Booklet.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021Article
- Parametric Mapping for TSPO PET Imaging with Spectral Analysis Impulsive Response Function.Molecular imaging and biology · 2021Article
- A Generalized Linear modeling approach to bootstrapping multi-frame PET image data.Medical image analysis · 2021Article
- Quantification of Hypoxia in Human Glioblastoma using PET with 18F-FMISO.Nuclear medicine and molecular imaging · 2021Article
- Analysis of Four-Dimensional Data for Total Body PET Imaging.PET clinics · 2021Review
- Evaluation of [EJNMMI research · 2020Article
- Assessment of simplified methods for quantification of [Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2020Article
- Does whole-body PatlakEuropean radiology · 2019Article
- Practical Methods for Estimating Metabolic Flux (Ki) to Assess Response to Therapy via Static PET Scans.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2019Article
- Dynamic whole-body PET imaging: principles, potentials and applications.European journal of nuclear medicine and molecular imaging · 2019Review
- The kinetics ofEJNMMI research · 2018Article
- Parametric mapping using spectral analysis forEuropean journal of nuclear medicine and molecular imaging · 2018Article
- Impact of tissue kinetic heterogeneity on PET quantification: case study with the L-[1-Scientific reports · 2018Article
- Pharmacokinetic modeling of [EJNMMI research · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
In Positron Emission Tomography (PET), spectral analysis (SA) allows the quantification of dynamic data by relating the radioactivity measured by the scanner in time to the underlying physiological processes of the system under investigation. Among the different approaches for the quantification of PET data, SA is based on the linear solution of the Laplace transform inversion whereas the measured arterial and tissue time-activity curves of a radiotracer are used to calculate the input response function of the tissue. In the recent years SA has been used with a large number of PET tracers in brain and nonbrain applications, demonstrating that it is a very flexible and robust method for PET data analysis. Differently from the most common PET quantification approaches that adopt standard nonlinear estimation of compartmental models or some linear simplifications, SA can be applied without defining any specific model configuration and has demonstrated very good sensitivity to the underlying kinetics. This characteristic makes it useful as an investigative tool especially for the analysis of novel PET tracers. The purpose of this work is to offer an overview of SA, to discuss advantages and limitations of the methodology, and to inform about its applications in the PET field.
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Registered trials
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.