Evidence map›Paper›PMID 41381759›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

An explainable imaging-clinical biomarker for non-small cell lung cancer prognostication based on normalised hotspot to centroid distance and [

Mitchell Chen, Susan J Copley, Yidong Han, Mubarik A Arshad, Patrizia Viola, Kristofer Linton-Reid, Tina Stoycheva, Gary J R Cook, David Landau, Sue Chua and 6 more

Abstract readMulticenter Study
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

16 authors.

Mitchell ChenDepartment of Surgery and Cancer, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK. d.mitch.chen@gmail.com.ORCID 0000-0002-3779-5615
Susan J CopleyDepartment of Surgery and Cancer, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK.
Yidong HanDepartment of Radiology & Nuclear Medicine, Imperial College Healthcare NHS Trust, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK.
Mubarik A ArshadInstitute of Nuclear Medicine, University College London, London, NW1 2BU, UK.
Patrizia ViolaDepartment of Surgery and Cancer, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK.
Kristofer Linton-ReidDepartment of Surgery and Cancer, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK.
Tina StoychevaDepartment of Radiology & Nuclear Medicine, Imperial College Healthcare NHS Trust, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK.
Gary J R CookDepartment of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK.
David LandauDepartment of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK.
Sue ChuaDepartment of Nuclear Medicine, The Royal Marsden Hospital, Downs Road, Sutton, SM2 5PT, UK.
Richard O'ConnorDepartment of Nuclear Medicine, Queen's Medical Centre, Derby Road, Nottingham, NG7 2UH, UK.
Jeannette DicksonDepartment of Clinical Oncology, Mount Vernon Hospital, Rickmansworth Road, Northwood, HA6 2RN, UK.
Danielle PowerDepartment of Clinical Oncology, Imperial College Healthcare NHS Trust, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK.
Andrea G RockallDepartment of Surgery and Cancer, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK.
Tara D BarwickDepartment of Surgery and Cancer, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK.
Eric O AboagyeDepartment of Surgery and Cancer, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK.

Funding

Medical Research Council APP32148NIHR Imperial Biomedical Research Centre P62585NIHR Imperial Biomedical Research Centre WSCC P87324
6 · The paper itself

Abstract

purposeAccurate prognostication is crucial for guiding personalised treatment strategies in non-small cell lung cancer (NSCLC). While radiomics offers promise, few features are derived from cancer models with causal justification to support their biological validity. This study evaluated the prognostic utility of normalised hotspot-to-centroid distance (NHOC), a recently proposed [18F]FDG PET imaging metric derived from a cancer evolutionary model, and its integration with PET/CT radiomics and clinical features to form a composite signature, non-invasive lung cancer evolution vector (nLCEV).

methodsA retrospective, multi-centre study was conducted using pre-treatment [18F]FDG PET/CT scans from 285 NSCLC patients (mean age: 67.7 ± 10.1 years; male:female = 171:114, International Association for the Study of Lung Cancer stage: T1/2/3/4/unknown = 61/118/53/52/1, N0/1/2/3/unknown = 133/46/71/34/1, M0/1/unknown = 222/62/1) from Imperial College Healthcare NHS Trust as the discovery cohort. External validation cohorts included patients from King's College (n = 53), Royal Marsden (n = 63), Mount Vernon (n = 61), and Nottingham University (n = 38) hospitals. NHOC was evaluated for 3-year overall survival prediction and combined with a multi-regional PET/CT radiomics predictive vector (RPV) and disease stage to develop nLCEV.

resultsNHOC and RPV demonstrated independent prognostic value (hazard ratio (HR) [95% confidence interval]: 2.52 [1.60-3.98] and 2.68 [2.13-3.38], respectively). nLCEV achieved an area under the receiver operating characteristic curve of 0.76 [0.60-0.92] and stratified patients into high- and low-risk groups across all validation cohorts with significant HR: KCL 3.27 [1.31, 8.16], Marsden 2.21 [1.02, 4.78], Mount Vernon 2.60 [1.42, 4.76], and Nottingham 4.14 [1.44, 11.90] (all p < 0.05).

conclusionNHOC enhances NSCLC patient survival prediction, and when integrated with PET-CT radiomics and disease stage, offers a robust, non-invasive approach to disease prognostication.

Indexed as

Carcinoma, Non-Small-Cell LungFluorodeoxyglucose F18Image Processing, Computer-AssistedLung NeoplasmsPositron Emission Tomography Computed TomographyAgedAged, 80 and overFemaleHumansMaleMiddle AgedPrognosisRadiomicsRetrospective StudiesFluorodeoxyglucose F18[18F]FDGExplainable AINSCLCPET/CTPrognosisRadiomics

Identifiers

PMID41381759
PMCPMC13013418

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Registered trials

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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.