Evidence map›Paper›PMID 42062586›Full record

ReviewSkeletal radiology2026

MRI findings for differentiating benign and malignant soft tissue tumors: a narrative review- Part 1: diagnostic performance.

Mahad Rehman, Shyam Ramachandran, Muaz Wahid, Aayush Sharma, Majid Chalian, Gitanjali Bajaj, Jim S Wu, Hillary Garner, Jonathan Samet, Shivani Ahlawat and 4 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Skeletal 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

14 authors.

Mahad RehmanUT Southwestern Medical Center, TX, Dallas, USA.
Shyam RamachandranTexas A&M School of Medicine, College Station, Bryan, TX, USA.
Muaz WahidUT Southwestern Medical Center, TX, Dallas, USA.
Aayush SharmaRosalind Franklin University of Medicine and Science, North Chicago, IL, USA. Aayush27@gmail.com.
Majid ChalianDepartment of Radiology, University of Washington, Seattle, WA, USA.
Gitanjali BajajDepartment of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Jim S WuDepartment of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Hillary GarnerDepartment of Radiology, Mayo Clinic, Jacksonville, FL, USA.
Jonathan SametDepartment of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Shivani AhlawatRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA.
Kambiz MotamediDepartment of Radiology, University of California, Los Angeles, CA, USA.
Ty SubhawongDepartment of Radiology, University of Miami Miller School of Medicine, Miami, FL, USA.
Mark MurpheyUniformed Services University of the Health Sciences, Bethesda, MD, USA.
Avneesh ChhabraUTSW, Dallas, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review aims to assess the diagnostic performance of MRI in distinguishing benign from malignant soft tissue tumors and evaluate conventional MRI sequences (Aim 1), as well as assess diffusion-weighted imaging (DWI) for tumor differentiation (Aim 2A) and tumor grading (Aim 2B). PubMed, Scopus, Embase, and CENTRAL were searched from inception to March 2025 using keywords like "MRI," "soft tissue sarcoma," "sensitivity," "specificity," and "diffusion." Studies with ≥ 20 cases reporting sensitivity and specificity for MRI or DWI were included for Aims 1/2A; studies on DWI for grading were included for Aim 2B. Four reviewers screened titles, abstracts, and full texts, resolving disagreements by consensus. A total of 224 studies were initially identified, and 34 were included for final analysis (Aim 1: 16, Aim 2A: 12, Aim 2B: 6). Conventional MRI (Aim 1) demonstrated sensitivities of 61-100%, specificities of 37-98%, and high negative predictive values (up to 98%) but lower positive predictive values (38-60%). DWI (Aim 2A) showed sensitivities of 73-100%, specificities of 63-94%, and lower ADC values in malignant tumors. ADC values were typically lower in high-grade tumors (Aim 2B). Overall, MRI appears to offer high diagnostic performance in excluding malignancy but lower positive predictive value and thus should be paired with histopathology or supplemental imaging. Integrating DWI into MRI protocols may enhance diagnostic accuracy by increasing specificity and confidence in distinguishing between benign and malignant tumors. ADC values from diffusion-weighted imaging were inversely correlated with tumor grade, suggesting utility in differentiating between low- and high-grade sarcomas.

Indexed as

Magnetic Resonance ImagingSoft Tissue NeoplasmsDiagnosis, DifferentialDiffusion Magnetic Resonance ImagingHumansNeoplasm GradingSarcomaSensitivity and SpecificityDiagnostic performanceDWIMRI, Diffusion weighted imagingSoft tissue sarcoma

Identifiers

PMID42062586
PMCPMC13521960

What OpenQuestion holds

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Registered trials

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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.