Evidence map›Paper›PMID 38853910›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Enhancing the Diagnostic Utility of ASL Imaging in Temporal Lobe Epilepsy through FlowGAN: An ASL to PET Image Translation Framework.

Alfredo Lucas, Chetan Vadali, Sofia Mouchtaris, T Campbell Arnold, James J Gugger, Catherine Kulick-Soper, Mariam Josyula, Nina Petillo, Sandhitsu Das, Jacob Dubroff and 3 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. 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

13 authors.

Alfredo LucasPerelman School of Medicine, University of Pennsylvania.ORCID 0000-0001-9439-735X
Chetan VadaliDepartment of Bioengineering, University of Pennsylvania.
Sofia MouchtarisDepartment of Bioengineering, University of Pennsylvania.
T Campbell ArnoldDepartment of Bioengineering, University of Pennsylvania.
James J GuggerDepartment of Neurology, University of Pennsylvania.ORCID 0000-0003-1113-2984
Catherine Kulick-SoperDepartment of Neurology, University of Pennsylvania.ORCID 0000-0002-8541-5912
Mariam JosyulaDepartment of Neurology, University of Pennsylvania.
Nina PetilloDepartment of Neurology, University of Pennsylvania.
Sandhitsu DasDepartment of Neurology, University of Pennsylvania.ORCID 0000-0003-0530-2887
Jacob DubroffDepartment of Radiology, University of Pennsylvania.ORCID 0000-0002-0732-2374
John A DetreDepartment of Neurology, University of Pennsylvania.ORCID 0000-0002-8115-6343
Joel M SteinDepartment of Radiology, University of Pennsylvania.
Kathryn A DavisDepartment of Neurology, University of Pennsylvania.ORCID 0000-0002-7020-6480

Funding

High Spatial and Temporal Resolution MRI Mapping of Oxygen Consumption in HumansP41EB029460 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI Ravinder Reddy · 2021 to 2026
$7.6M
Optimized Intracranial EEG Targeting in Focal Epilepsy based upon Neuroimaging ConnectomicsR01NS116504 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DAVIS, KATHRYN ADAMIAK · 2021 to 2025
$3.3M
The influence of nicotinic hepatic metabolism on neuroreceptor substrates of nicotine addictionK23DA038726 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI DUBROFF, JACOB · 2016 to 2020
$964k
Neuroimaging Phenotypes of Post-Traumatic EpilepsyK23NS135101 · NINDS · UNIVERSITY OF ROCHESTER · PI James J Gugger · 2024 to 2026
$664k
NIBIB NIH HHS P41 EB029460NIDA NIH HHS K23 DA038726NINDS NIH HHS K23 NS135101NINDS NIH HHS R01 NS116504
6 · The paper itself

Abstract

Background and Significance: Positron Emission Tomography (PET) using fluorodeoxyglucose (FDG-PET) is a standard imaging modality for detecting areas of hypometabolism associated with the seizure onset zone (SOZ) in temporal lobe epilepsy (TLE). However, FDG-PET is costly and involves the use of a radioactive tracer. Arterial Spin Labeling (ASL) offers an MRI-based quantification of cerebral blood flow (CBF) that could also help localize the SOZ, but its performance in doing so, relative to FDG-PET, is limited. In this study, we seek to improve ASL's diagnostic performance by developing a deep learning framework for synthesizing FDG-PET-like images from ASL and structural MRI inputs. Methods: We included 68 epilepsy patients, out of which 36 had well lateralized TLE. We compared the coupling between FDG-PET and ASL CBF values in different brain regions, as well as the asymmetry of these values across the brain. We additionally assessed each modality's ability to lateralize the SOZ across brain regions. Using our paired PET-ASL data, we developed FlowGAN, a generative adversarial neural network (GAN) that synthesizes PET-like images from ASL and T1-weighted MRI inputs. We tested our synthetic PET images against the actual PET images of subjects to assess their ability to reproduce clinically meaningful hypometabolism and asymmetries in TLE. Results: We found variable coupling between PET and ASL CBF values across brain regions. PET and ASL had high coupling in neocortical temporal and frontal brain regions (Spearman's Conclusions: FlowGAN improves ASL's diagnostic performance, generating synthetic PET images that closely mimic actual FDG-PET in depicting hypometabolism associated with TLE. This approach could improve non-invasive SOZ localization, offering a promising tool for epilepsy presurgical assessment. It potentially broadens the applicability of ASL in clinical practice and could reduce reliance on FDG-PET for epilepsy and other neurological disorders.

Identifiers

PMID38853910
PMCPMC11160820

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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.