Evidence map›Paper›PMID 38587770›Full record

ArticleJournal of imaging informatics in medicine2024

An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer.

Yang Li, Maliha R Imami, Linmei Zhao, Alireza Amindarolzarbi, Esther Mena, Jeffrey Leal, Junyu Chen, Andrei Gafita, Andrew F Voter, Xin Li and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of imaging informatics in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Quantitative PSMA PET Biomarkers for Predicting Response toJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026
    Pooled it
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  9. A review of artificial intelligence in brachytherapy.Journal of applied clinical medical physics · 2025
    Review
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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

18 authors.

Yang LiRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Maliha R ImamiRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Linmei ZhaoRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Alireza AmindarolzarbiRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Esther MenaNational Institutes of Health, Bethesda, 20892, USA.
Jeffrey LealRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Junyu ChenRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Andrei GafitaRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Andrew F VoterRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Xin LiRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Yong DuRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Chengzhang ZhuSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China.
Peter L ChoykeNational Institutes of Health, Bethesda, 20892, USA.
Beiji ZouSchool of Informatics, Hunan University of Chinese Medicine, Changsha, 410208, China.
Zhicheng JiaoWarren Alpert Medical School of Brown University, Providence, 02903, USA.
Steven P RoweRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Martin G PomperRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA.
Harrison X BaiRussell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD 21287, USA. hbai7@jh.edu.

Funding

Prostate Cancer ImagingZIABC010655 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI CHOYKE, PETER L · 2009 to 2025
$49.2M
Growth Factor Imaging and PhotoimmunotherapyZIABC010656 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI CHOYKE, PETER L · 2009 to 2024
$31.6M
Training/Dissemination-Resource for Molecular Imaging Agents in Precision MedicineP41EB024495 · NIBIB · UT SOUTHWESTERN MEDICAL CENTER · PI MARTIN G POMPER · 2017 to 2026
$11.8M
PSMA-based Cancer Imaging AgentsR01CA134675 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI POMPER, MARTIN G · 2009 to 2025
$6.2M
Multi-Modality Quantitiative Imaging for Evaluation of Response to Cancer TherapyU01CA140204 · NCI · JOHNS HOPKINS UNIVERSITY · PI DU, YONG, SOLNES, LILJA · 2011 to 2022
$6.1M
Training for Clinician Scientists in Imaging ResearchT32EB006351 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI POMPER, MARTIN G · 2006 to 2022
$4.0M
Radiopharmaceutical Imaging and Therapy of CancerZIABC012167 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI CHOYKE, PETER L · 2024 to 2025
$3.9M
IEEE International Symposium on Biomedical Imaging (ISBI)2017R13EB024405 · NIBIB · INSTITUTE OF ELECTRICAL-ELECTRONIC ENGRS · PI AMINI, AMIR A · 2017 to 2017
$10k
NCI NIH HHS R01 CA134675NCI NIH HHS U01 CA140204NIBIB NIH HHS P41 EB024495NIBIB NIH HHS R13 EB024405NIBIB NIH HHS T32 EB006351NIH/NCI U01CA140204P41 EB024405R01 CA134675T32 T32EB006351
6 · The paper itself

Abstract

Uptake segmentation and classification on PSMA PET/CT are important for automating whole-body tumor burden determinations. We developed and evaluated an automated deep learning (DL)-based framework that segments and classifies uptake on PSMA PET/CT. We identified 193 [

Indexed as

Deep LearningPositron Emission Tomography Computed TomographyProstatic NeoplasmsAgedAntigens, SurfaceGlutamate Carboxypeptidase IIHumansLysineMaleUrea2-(3-(1-carboxy-5-((6-fluoropyridine-3-carbonyl)amino)pentyl)ureido)pentanedioic acidAntigens, SurfaceFOLH1 protein, humanGlutamate Carboxypeptidase IILysineUreaDeep learningDisease burdenPET/CTPSMASegmentation

Identifiers

PMID38587770
PMCPMC11522269

What Socratic 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 Socratic graph.