Evidence map›Paper›PMID 35150363›Full record

ArticleMagma (New York, N.Y.)2022

Pseudo-T2 mapping for normalization of T2-weighted prostate MRI.

Kaia Ingerdatter Sørland, Mohammed R S Sunoqrot, Elise Sandsmark, Sverre Langørgen, Helena Bertilsson, Christopher G Trimble, Gigin Lin, Kirsten M Selnæs, Pål E Goa, Tone F Bathen and 1 more

Open access · hybridAbstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Magma (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

5 citing papers in PubMed, 9 citations in OpenAlex.

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  5. Review
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

11 authors at 3 institutions in 2 countries.

Kaia Ingerdatter SørlandDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway. kaia.i.sorland@ntnu.no.ORCID http://orcid.org/0000-0001-9335-9968
Mohammed R S SunoqrotDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway.
Elise SandsmarkDepartment of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
Sverre LangørgenDepartment of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
Helena BertilssonDepartment of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway.
Christopher G TrimbleDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway.
Gigin LinDepartment of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou and Chang Gung University, 5 Fuhsing St., Guishan, Taoyuan, 33382, Taiwan.
Kirsten M SelnæsDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway.
Pål E GoaDepartment of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
Tone F Bathen *Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway.
Mattijs Elschot *Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Olav Kyrres Gate 9, 7030, Trondheim, Norway. mattijs.elschot@ntnu.no.
Norwegian University of Science and Technology · NOSt Olav's University Hospital · NOChang Gung University · TW

Funding

Chang Gung Medical Foundation CLRPG3K0022Chang Gung Medical Foundation CPRPG3G0023Ministry of Science and Technology, Taiwan MOST 109-2628-B-182A-007National Health Research Institutes NHRI-109BCCO-MF-202009-02The Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology 90265300The Liaison Committee for Education, Research and Innovation in Central Norway 905481The Research Council of Norway 295013
6 · The paper itself

Abstract

objectiveSignal intensity normalization is necessary to reduce heterogeneity in T2-weighted (T2W) magnetic resonance imaging (MRI) for quantitative analysis of multicenter data. AutoRef is an automated dual-reference tissue normalization method that normalizes transversal prostate T2W MRI by creating a pseudo-T2 map. The aim of this study was to evaluate the accuracy of pseudo-T2s and multicenter standardization performance for AutoRef with three pairs of reference tissues: fat/muscle (AutoRef MATERIALS AND

methodsT2s measured by multi-echo spin echo (MESE) were compared to AutoRef pseudo-T2s in the whole prostate (WP) and zones (PZ and TZ/CZ/AFS) for seven asymptomatic volunteers with a paired Wilcoxon signed-rank test. AutoRef normalization was assessed on T2W images from a multicenter evaluation set of 1186 prostate cancer patients. Performance was measured by inter-patient histogram intersections of voxel intensities in the WP before and after normalization in a selected subset of 80 cases.

resultsAutoRef DISCUSSION: All AutoRef versions reduced variation in the multicenter data. AutoRef

Indexed as

ProstateProstatic NeoplasmsHumansMagnetic Resonance ImagingMagnetic Resonance SpectroscopyMalePelvisMagnetic resonance imagingMedical image processingMulticenter studyProstateProstatic neoplasms

Identifiers

PMID35150363
PMCPMC9363383
OpenAlexW4211029287

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.