Evidence map›Paper›PMID 42238441›Full record

ArticlemedRxiv : the preprint server for health sciences2026

MR-Guided PET Denoising and Resolution Enhancement Improves Visual Interpretation and Preserves Quantitative Behavior Across Amyloid Tracers.

Caroline Szujewski, Timothy M Shepherd, Munir Ghesani, Maria Ponisio, William Lavely, Georg Schramm, Ariane Bollack, Benjamin Aron, Gregory Lemberskiy

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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.

Caroline SzujewskiMicrostructure Imaging, Inc., 370 Jay St FL7, Brooklyn, 11201, NY, USA.ORCID 0000-0003-1291-7492
Timothy M ShepherdDepartment of Radiology, NYU Langone Health, New York, NY, USA.ORCID 0000-0003-0232-1636
Munir GhesaniDepartment of Radiology, Mount Sinai Health System, New York, NY, USA.ORCID 0000-0002-1044-0136
Maria PonisioMallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA.ORCID 0000-0002-4528-8971
William LavelyNorthside Radiology Associates, Atlanta, GA, USA.
Georg SchrammDepartment of Imaging and Pathology, KU Leuven, Leuven, Belgium.ORCID 0000-0002-2251-3195
Ariane BollackGE HealthCare, Chalfont St Giles, HP8 4SP, UK.ORCID 0000-0002-9169-7530
Benjamin AronMicrostructure Imaging, Inc., 370 Jay St FL7, Brooklyn, 11201, NY, USA.ORCID 0000-0001-5077-3341
Gregory LemberskiyMicrostructure Imaging, Inc., 370 Jay St FL7, Brooklyn, 11201, NY, USA.ORCID 0000-0002-8336-7486

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MONICA G. RIVERA-MINDT · 2016 to 2026
$226.7M
NIA NIH HHS U19 AG024904
6 · The paper itself

Abstract

Background: Amyloid- Methods: Standard (STN) and MRG PET images were compared for four tracers ([ Results: Across all tracers, MRG preserved quantitative SUVr and Centiloid metrics relative to STN ( Conclusions: MRG denoising and resolution enhancement improved perceived image quality, reader confidence, and accuracy for amyloid PET while preserving standard quantitative behavior across tracers. By improving cortical definition in visually challenging low-burden cases without disrupting established SUVr/Centiloid behavior, MRG may reduce visual-quantitative discordance and support more confident amyloid PET interpretation near the threshold of positivity.

Indexed as

Alzheimer’s diseaseAmyloid PETCentiloiddenoisingMRI-guided PETresolution enhancement

Identifiers

PMID42238441
PMCPMC13228655

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.