Evidence map›Paper›PMID 42461410›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

Automated lesion tracking and treatment response classification on [

Theo Lucas, Mikaela Dell'Oro, Jeremy S L Ong, Martin A Ebert, Kaylee Molin, Jake Kendrick

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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. Not yet cited in PubMed.

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0cells of the map it votes in
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

6 authors.

Theo LucasSchool of Physics, Mathematics and Computing, University of Western Australia, Perth, WA, Australia. 22965157@student.uwa.edu.au.ORCID http://orcid.org/0009-0004-3585-0897
Mikaela Dell'OroCurtin Medical School, Curtin University, Perth, WA, Australia.
Jeremy S L OngDepartment of Nuclear Medicine, Fiona Stanley Hospital, Murdoch, WA, Australia.
Martin A EbertSchool of Physics, Mathematics and Computing, University of Western Australia, Perth, WA, Australia.
Kaylee MolinSchool of Physics, Mathematics and Computing, University of Western Australia, Perth, WA, Australia.
Jake KendrickSchool of Physics, Mathematics and Computing, University of Western Australia, Perth, WA, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to validate an automated lesion-tracking algorithm for [

methodsPaired baseline and follow-up [

resultsA total of 1,066 lesions were identified (559 baseline, 507 follow-up), including 371 CLs, 188 DLs, and 136 NLs, yielding 695 matching decisions. The lesion matching algorithm achieved 95.1% matching accuracy. Lesion mismatches were associated with poorer registration quality. Algorithm-derived patient-level response classifications showed high concordance with ground-truth frameworks, with classification accuracy of 95.5% for RECIP 1.0, 96.2% for PPP, and 96.2% for TLW. All frameworks retained prognostic significance for OS, with progressive disease conferring hazard ratios (HR) of-RECIP 1.0 HR = 2.57 (95% CI 1.33-4.98), PPP HR = 2.02 (95% CI 1.04-3.90), and TLW HR = 2.29 (95% CI 1.22-4.28).

conclusionThe automated lesion-tracking algorithm reproduced expert matches with high accuracy and preserved the prognostic utility of RECIP 1.0, PPP, and TLW in a BCR cohort, supporting its use as a reproducible lesion-matching method for quantitative response assessment on PSMA PET/CT. TRIAL REGISTRATION NUMBER: ACTRN ACTRN12615000608561. Registered 11 June 2015. Retrospectively registered.

Indexed as

Edetic AcidImage Processing, Computer-AssistedOligopeptidesPositron Emission Tomography Computed TomographyProstatic NeoplasmsAgedAlgorithmsAutomationGallium IsotopesGallium RadioisotopesHumansMaleMiddle AgedTreatment OutcomeEdetic Acidgallium 68 PSMA-11Gallium IsotopesGallium RadioisotopesOligopeptidesPSMA-11Biochemically recurrent prostate cancerLesion-trackingPPPPSMA PETRECIP 1.0TLW

Identifiers

PMID42461410
PMCPMC13633376

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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.