Evidence map›Paper›PMID 42610017›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2025

ISIT-GEN: An in silico imaging trial to assess the inter-scanner generalizability of CTLESS for myocardial perfusion SPECT on defect-detection task.

Zitong Yu, Nu Ri Choi, Zezhang Yang, Nancy A Obuchowski, Barry A Siegel, Abhinav K Jha

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PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Zitong YuDepartment of Biomedical Engineering, Washington University, St. Louis, MO, USA.
Nu Ri ChoiMallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA.
Zezhang YangDepartment of Electrical and Systems Engineering, Washington University, St. Louis, MO, USA.
Nancy A ObuchowskiDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA.
Barry A SiegelMallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA.
Abhinav K JhaDepartment of Biomedical Engineering, Washington University, St. Louis, MO, USA.

Funding

Validation and dissemination of novel physical phantoms for quantitative theranostics researchR01EB031962 · NIBIB · WASHINGTON UNIVERSITY · PI JHA, ABHINAV K · 2022 to 2025
$2.4M
A no-gold-standard framework to objectively evaluate quantitative imaging methods with patient dataR01EB031051 · NIBIB · WASHINGTON UNIVERSITY · PI JHA, ABHINAV K · 2021 to 2025
$2.1M
NIBIB NIH HHS R01 EB031051NIBIB NIH HHS R01 EB031962
6 · The paper itself

Abstract

A recently proposed scatter-window and deep learning-based attenuation compensation (AC) method for myocardial perfusion imaging (MPI) by single-photon emission computed tomography (SPECT), namely CTLESS, demonstrated promising performance on the clinical task of myocardial perfusion defect detection with retrospective data acquired on SPECT scanners from a single vendor. For clinical translation of CTLESS, it is important to assess the generalizability of CTLESS across different SPECT scanners. For this purpose, we conducted a virtual imaging trial, titled

Indexed as

deep learninggeneralizabilityIn silico imaging trialmyocardial perfusion SPECTtransmission-less attenuation compensation

Identifiers

PMID42610017
PMCPMC13479871

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.