Evidence map›Paper›PMID 38302197›Full record

ArticleAJNR. American journal of neuroradiology2024

Reducing False-Positives in CT Perfusion Infarct Core Segmentation Using Contralateral Local Normalization.

Alexander Rau, Marco Reisert, Christian A Taschner, Theo Demerath, Samer Elsheikh, Benedikt Frank, Martin Köhrmann, Horst Urbach, Elias Kellner

Open access · hybridAbstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Alexander RauFrom the Department of Neuroradiology (A.R., C.A.T., T.D., S.E., H.U.), Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID 0000-0001-5881-6043
Marco ReisertMedical Physics, Department of Diagnostic and Interventional Radiology (M.R., E.K.), Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID 0000-0003-2742-1940
Christian A TaschnerFrom the Department of Neuroradiology (A.R., C.A.T., T.D., S.E., H.U.), Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Theo DemerathFrom the Department of Neuroradiology (A.R., C.A.T., T.D., S.E., H.U.), Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID 0000-0002-5869-1110
Samer ElsheikhFrom the Department of Neuroradiology (A.R., C.A.T., T.D., S.E., H.U.), Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID 0000-0002-3796-5709
Benedikt FrankDepartment of Neurology and Center for Translational Neuro- and Behavioral Sciences (B.F., M.K.), University Hospital Essen, Essen, Germany.
Martin KöhrmannDepartment of Neurology and Center for Translational Neuro- and Behavioral Sciences (B.F., M.K.), University Hospital Essen, Essen, Germany.ORCID 0000-0002-0701-9535
Horst UrbachFrom the Department of Neuroradiology (A.R., C.A.T., T.D., S.E., H.U.), Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID 0000-0001-7264-4807
Elias KellnerMedical Physics, Department of Diagnostic and Interventional Radiology (M.R., E.K.), Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany elias.kellner@uniklinik-freiburg.de.ORCID 0000-0001-9494-2354
University of Freiburg · DEEssen University Hospital · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeThe established global threshold of rCBF <30% for infarct core segmentation can lead to false-positives, as it does not account for the differences in blood flow between GM and WM and patient-individual factors, such as microangiopathy. To mitigate this problem, we suggest normalizing each voxel not only with a global reference value (ie, the median value of normally perfused tissue) but also with its local contralateral counterpart. MATERIALS AND

methodsWe retrospectively enrolled 2830 CTP scans with suspected ischemic stroke, of which 335 showed obvious signs of microangiopathy. In addition to the conventional, global normalization, a local normalization was performed by dividing the rCBF maps with their mirrored and smoothed counterpart, which sets each voxel value in relation to the contralateral counterpart, intrinsically accounting for GM and WM differences and symmetric patient individual microangiopathy. Maps were visually assessed and core volumes were calculated for both methods.

resultsCases with obvious microangiopathy showed a strong reduction in false-positives by using local normalization (mean 14.7 mL versus mean 3.7 mL in cases with and without microangiopathy). On average, core volumes were slightly smaller, indicating an improved segmentation that was more robust against naturally low blood flow values in the deep WM.

conclusionsThe proposed method of local normalization can reduce overestimation of the infarct core, especially in the deep WM and in cases with obvious microangiopathy. False-positives in CTP infarct core segmentation might lead to less-than-optimal therapy decisions when not correctly interpreted. The proposed method might help mitigate this problem.

Indexed as

Brain IschemiaStrokeCerebrovascular CirculationHumansInfarctionPerfusionPerfusion ImagingRetrospective StudiesTomography, X-Ray Computed

Identifiers

PMID38302197
PMCPMC11286109
OpenAlexW4391450734

What OpenQuestion 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 OpenQuestion graph.