Evidence map›Paper›PMID 41750759›Full record

ArticleDiagnostics (Basel, Switzerland)2026

Time-Dependent DCE-MRI Radiomics to Predict Response to Neoadjuvant Therapy in Breast Cancer: A Multicenter Study with External Validation.

Giulia Vatteroni, Riccardo Levi, Paola Nardi, Giulia Pruneddu, Elisa Salpietro, Federica Fici, Cinzia Monti, Rubina Manuela Trimboli, Daniela Bernardi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2026. 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

9 authors.

Giulia VatteroniDepartment of Biomedical Sciences, Humanitas University, Via R. Montalcini 4, 20072 Pieve Emanuele, Italy.
Riccardo LeviDepartment of Biomedical Sciences, Humanitas University, Via R. Montalcini 4, 20072 Pieve Emanuele, Italy.ORCID 0000-0001-9030-0071
Paola NardiDepartment of Biomedical Sciences, Humanitas University, Via R. Montalcini 4, 20072 Pieve Emanuele, Italy.
Giulia PrunedduRadiology Department, IRCCS Humanitas Research Hospital, Via A. Manzoni 56, 20089 Rozzano, Italy.
Elisa SalpietroRadiology Department, Humanitas Gavazzeni, Via Mauro Gavazzeni 21, 24125 Bergamo, Italy.
Federica FiciRadiology Department, Humanitas Gavazzeni, Via Mauro Gavazzeni 21, 24125 Bergamo, Italy.
Cinzia MontiRadiology Department, Humanitas Gavazzeni, Via Mauro Gavazzeni 21, 24125 Bergamo, Italy.
Rubina Manuela TrimboliRadiology Department, IRCCS Humanitas Research Hospital, Via A. Manzoni 56, 20089 Rozzano, Italy.
Daniela BernardiDepartment of Biomedical Sciences, Humanitas University, Via R. Montalcini 4, 20072 Pieve Emanuele, Italy.ORCID 0000-0002-4329-8121

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

breast cancermachine learningMRIneo-adjuvant therapyradiomicsresponse prediction

Identifiers

PMID41750759
PMCPMC12939715

What OpenQuestion holds

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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.