Evidence map›Paper›PMID 41908063›Full record

ArticleBJR open2026

Assessing current and future demand for PET-CT imaging in England: a comparative analysis of 2013 and 2022 Royal College of Radiologists Guidelines.

Nadia A S Smith, Rebecca Nutbrown, Alba Eisner, Raj Jena

Abstract read
In one paragraph

Article in BJR open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

4 authors.

Nadia A S SmithNuclear Technologies, TÜV SÜD UK, Warrington, WA3 6AE, United Kingdom.ORCID https://orcid.org/0000-0002-6503-3001
Rebecca NutbrownNuclear Technologies, TÜV SÜD UK, Warrington, WA3 6AE, United Kingdom.
Alba EisnerDepartment of Oncology, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, United Kingdom.
Raj JenaDepartment of Oncology, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aimed to provide a comprehensive analysis of the increasing demand for PET-CT imaging in England, driven by advancements in technology and updated clinical guidelines. By comparing the 2013 and 2022 guidelines issued by the Royal College of Radiologists, the analysis sought to quantify the gap between actual PET-CT provision and modeled requirements, benchmarked against international comparators, to inform strategic planning for equitable access to advanced imaging. Methods: A detailed modeling approach was developed, mapping guideline-based PET-CT scan requirements to disease incidence and stage for major oncological indications (prostate, lymphoma, neuroendocrine tumors, lung, breast, gynecological cancers) and key non-oncological conditions (dementia, cardiovascular disease). Actual scan volumes were extracted from the NHS Diagnostic Imaging Dataset and cross-referenced with provider data. Unmodeled indications were estimated using proportional scaling. Model outputs were validated against PET-CT utilization rates in Finland, adjusted for UK disease incidence. Future demand projections incorporated population growth, demographic shifts, and evolving disease prevalence. Results: For 2021, modeled estimates indicated a substantial shortfall in PET-CT provision for several high-impact indications, notably prostate cancer, dementia, neuroendocrine tumors, and breast cancer, where actual scan volumes were 2-7 times lower than modeled need. Modeled demand for England (361 900 scans/year) exceeded actual provision (239 367 scans/year) by over 50%. Comparative analysis with Finland confirmed that England's PET-CT rates lagged for most indications except lung cancer. Projections suggest continued growth in demand, particularly for dementia and neuroendocrine tumors, with overall PET-CT needs expected to rise sharply by 2040. Conclusions: England's current PET-CT capacity falls significantly short of evidence-based requirements, especially for emerging indications in neurology and oncology. Without strategic investment and expansion, this gap will widen, risking delayed diagnosis and suboptimal care. Enhanced data collection and ongoing validation are critical for responsive service planning. Advances in knowledge: This is the first study to comprehensively model PET-CT demand in England across multiple disease categories using updated clinical guidelines and international benchmarking. It provides a robust, data-driven framework for forecasting imaging needs, supporting national policy and equitable resource allocation.

Indexed as

cancerdata standardizationdementiahealthcare planningPET-CT demandpredictive modeling

Identifiers

PMID41908063
PMCPMC13020349

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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.