ArticleBioengineering (Basel, Switzerland)2026
Hybrid [
Article in Bioengineering (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.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Breast cancer (BC) requires the evaluation of tumor aggressiveness features to guide treatment decisions. Biopsy-derived prognostic information may differ from surgical histopathology due to tumor heterogeneity. Hybrid PET/MRI can provide additional information for tumor characterization, supporting initial therapy planning and prognosis. In this work, we acquired 157 BC patients using a hybrid PET/MRI scanner. The PET data were combined with ADC and semi-quantitative DCE-MRI metrics to derive "hybrid PET/MRI parameters." Pathological data such as tumor grade, hormone receptors, proliferation index (Ki67), and surrogate molecular subtype were collected, and we evaluated their associations with hybrid imaging, also comparing with the PET and MRI data analyzed separately. Ki67 showed moderate correlations with PET, ADCmin, and most hybrid parameters. The PET and hybrid data differentiate histopathological factors, while ADCmin differentiates G1 vs. G2 and luminal A vs. luminal B. In the ROC analysis, hybrid SUVmax/ADCmin shows better performance to predict luminal B from luminal A (AUC 0.720, sensitivity 73.1%, specificity 63.2%, PPV 54.3%, NPV 79.7%) than SUVmean alone. Our findings suggest that these novel hybrid PET/MRI parameters may help the characterization of tumor tissue in IDC. However, a multivariate analysis is needed to confirm our preliminary results.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.