Evidence map›Paper›PMID 40868387›Full record

ArticleBioengineering (Basel, Switzerland)2025

Automatic 3D Tracking of Liver Metastases: Follow-Up Assessment of Cancer Patients in Contrast-Enhanced MRI.

Sophia Schulze-Weddige, Uli Fehrenbach, Johannes Kolck, Richard Ruppel, Georg Lukas Baumgärtner, Maximilian Lindholz, Isabel Theresa Schobert, Anna-Maria Haack, Henning Jann, Martina Mogl and 3 more

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

13 authors.

Sophia Schulze-WeddigeDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.ORCID 0000-0003-4248-5563
Uli FehrenbachDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.ORCID 0000-0003-3622-3268
Johannes KolckDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.ORCID 0000-0001-9843-2247
Richard RuppelDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.ORCID 0009-0002-7081-0300
Georg Lukas BaumgärtnerDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.ORCID 0000-0003-3046-0019
Maximilian LindholzDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.
Isabel Theresa SchobertDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.ORCID 0000-0003-3659-0914
Anna-Maria HaackDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.ORCID 0009-0001-0293-3942
Henning JannDivision of Gastroenterology, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany.
Martina MoglDepartment of Surgery, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany.ORCID 0000-0002-3676-047X
Dominik GeiselDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.
Bertram WiedenmannDivision of Gastroenterology, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany.ORCID 0000-0002-7890-2552
Tobias PenzkoferDepartment of Radiology, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTracking differential growth of secondary liver metastases is important for early detection of progression but remains challenging due to variable tumor growth rates. We aimed to automate accurate, consistent, and efficient longitudinal monitoring.

methodsWe developed an automatic 3D segmentation and tracking algorithm to quantify differential growth, tested on contrast-enhanced MRI follow-ups of patients with neuroendocrine liver metastases (NELMs). The output was integrated into a decision support tool to distinguish between progressive disease, stable disease, and partial/complete response. A user study involving an expert group of seven expert radiologists evaluated its impact. Group comparisons used the Friedman test with post hoc analyses.

resultsOur algorithm detected 991 metastases in 30 patients: 13% new, 30% progressive, 18% stable, and 18% regressive; the remainder were either too small to measure (15%) or merged with another metastasis in the follow-up assessment (6%). Diagnostic accuracy improved with additional information on hepatic tumor load and differential growth, albeit not significantly (

conclusionsWe automated segmentation and quantification of individual NELMs, enabling comprehensive longitudinal analysis of differential tumor growth with the potential to enhance clinical decision-making.

Indexed as

follow-up studieslivermagnetic resonance imagingneoplasm metastasisneuroendocrine tumors

Identifiers

PMID40868387
PMCPMC12383499

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.