Evidence map›Paper›PMID 38730599›Full record

ArticleCancers2024

Inter- and Intra-Patient Repeatability of Radiomic Features from Multiparametric Whole-Body MRI in Patients with Metastatic Prostate Cancer.

Ricardo Donners, Antonio Candito, Mihaela Rata, Adam Sharp, Christina Messiou, Dow-Mu Koh, Nina Tunariu, Matthew D Blackledge

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Predictive imaging biomarkers on whole-body diffusion-weighted MRI (WB-DWMRI) and [Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    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

8 authors.

Ricardo DonnersUniversity Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland.ORCID 0000-0002-1614-0521
Antonio CanditoThe Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG, UK.ORCID 0000-0003-3059-9328
Mihaela RataThe Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG, UK.
Adam SharpThe Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG, UK.
Christina MessiouThe Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG, UK.
Dow-Mu KohThe Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG, UK.
Nina TunariuThe Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG, UK.
Matthew D BlackledgeThe Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG, UK.ORCID 0000-0001-8117-9003

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

(1) Background: We assessed the test-re-test repeatability of radiomics in metastatic castration-resistant prostate cancer (mCPRC) bone disease on whole-body diffusion-weighted (DWI) and T1-weighted Dixon MRI. (2) Methods: In 10 mCRPC patients, 1.5 T MRI, including DWI and T1-weighted gradient-echo Dixon sequences, was performed twice on the same day. Apparent diffusion coefficient (ADC) and relative fat-fraction-percentage (rFF%) maps were calculated. Per study, up to 10 target bone metastases were manually delineated on DWI and Dixon images. All 106 radiomic features included in the Pyradiomics toolbox were derived for each target volume from the ADC and rFF% maps. To account for inter- and intra-patient measurement repeatability, the log-transformed individual target measurements were fitted to a hierarchical model, represented as a Bayesian network. Repeatability measurements, including the intraclass correlation coefficient (ICC), were derived. Feature ICCs were compared with mean ADC and rFF ICCs. (3) Results: A total of 65 DWI and 47 rFF% targets were analysed. There was no significant bias for any features. Pairwise correlation revealed fifteen ADC and fourteen rFF% feature sub-groups, without specific patterns between feature classes. The median intra-patient ICC was generally higher than the inter-patient ICC. Features that describe extremes in voxel values (minimum, maximum, range, skewness, and kurtosis) showed generally lower ICCs. Several mostly shape-based texture features were identified, which showed high inter- and intra-patient ICCs when compared with the mean ADC or mean rFF%, respectively. (4) Conclusions: Pyradiomics texture features of mCRPC bone metastases varied greatly in inter- and intra-patient repeatability. Several features demonstrated good repeatability, allowing for further exploration as diagnostic parameters in mCRPC bone disease.

Indexed as

diffusion magnetic resonance imagingneoplasm metastasesradiomics

Identifiers

PMID38730599
PMCPMC11083580

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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.