Evidence map›Paper›PMID 42712958›Full record

ArticlePolish journal of radiology2026

Exploratory quantitative magnetic resonance imaging characterization of histopathologic subtype heterogeneity in osteosarcoma.

Ismi Ayu Putri Rahmadillah, Rosy Setiawati, Amri Wicaksono Pribadi, James Griffith

Abstract read
In one paragraph

Article in Polish journal of radiology, 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

4 authors.

Ismi Ayu Putri Rahmadillah *Department of Radiology, Faculty of Medicine, Universitas Airlangga, Dr. Soetomo General Academic Hospital, Surabaya, Indonesia.
Rosy Setiawati *Department of Radiology, Faculty of Medicine, Universitas Airlangga, Dr. Soetomo General Academic Hospital, Surabaya, Indonesia.
Amri Wicaksono PribadiDepartment of Radiology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
James GriffithDepartment of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Osteosarcoma is the most common primary malignant bone tumor in children and young adults and demonstrates substantial histopathologic heterogeneity that complicates diagnosis and treatment monitoring. Conventional imaging and biopsy may not adequately reflect whole-tumor biology because of spatial sampling limitations. Multiparametric magnetic resonance imaging (MRI), including dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI), provides quantitative biomarkers related to tumor vascularity and cellularity. The aim of this study was to evaluate the association between quantitative DCE-MRI parameters and apparent diffusion coefficient (ADC) values across osteosarcoma subtypes and to explore their role in reflecting histopathologic heterogeneity. Material and methods: This retrospective exploratory study included 43 patients with histopathologically confirmed osteosarcoma who underwent pre-treatment 3.0-T MRI, including DCE-MRI and DWI, between January 2023 and February 2025. The cohort consisted of 17 osteoblastic, 9 fibroblastic, 6 chondroblastic, 5 giant cell-rich, 5 telangiectatic, and 1 extraskeletal osteosarcoma cases. Quantitative pharmacokinetic parameters (K Results: K Conclusions: Quantitative DCE-MRI parameters, particularly K

Indexed as

angiogenesisdynamic contrast enhanced magnetic resonance imagingosteosarcomapermeability

Identifiers

PMID42712958
PMCPMC13551578

What Socratic holds

Textmetadata
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 Socratic graph.