Evidence map›Paper›PMID 40851330›Full record

ArticleMagnetic resonance in medicine2026

Interpreting amide proton transfer-weighted imaging contrast between normal and tumor brain tissues using the asymmetry analysis method at 4.7 T.

Malvika Viswanathan, Yashwant Kurmi, Xiaoyu Jiang, Junzhong Xu, Zhongliang Zu

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Malvika ViswanathanVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0009-0001-9522-0780
Yashwant KurmiVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0003-4986-2106
Xiaoyu JiangVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0002-0369-6301
Junzhong XuVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0001-7895-4232
Zhongliang ZuVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0001-7361-7480

Funding

Nuclear Overhauser enhancement (NOE) MR imaging of choline phospholipids and their metabolismR01EB029443 · NIBIB · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ZU, ZHONGLIANG · 2021 to 2024
$1.5M
NIBIB NIH HHS R01 EB029443
6 · The paper itself

Abstract

purposeTo provide a comprehensive analysis of the contributors to the amide proton transfer-weighted (APTw) imaging signal using an asymmetry analysis method, as well as its contrast between tumors and the contralateral normal tissues at 4.7 T.

methodsFirst, a signal model was developed to demonstrate the dependence of APTw signal on various contributors, including water T

resultsOur findings reveal that at 2 μT, the APT effect is comparable to the NOE/asymmetric MT effects in tumors. Whereas at 3 μT, the APT effect becomes greater than the NOE/asymmetric MT effects in tumors. At these two B

conclusionThis study provides insights into the contributors to APTw signal and its contrast between tumors and normal tissues, thereby enhancing our understanding of APTw imaging.

Indexed as

AmidesBrainBrain NeoplasmsImage Processing, Computer-AssistedMagnetic Resonance ImagingAlgorithmsAnimalsMaleProtonsRatsRats, Sprague-DawleyAmidesProtonsamide proton transfer (APT)chemical exchange saturation transfer (CEST)

Identifiers

PMID40851330
PMCPMC12620183

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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.