Evidence map›Paper›PMID 39900865›Full record

ReviewJournal of imaging informatics in medicine2025

FireVoxel: Interactive Software for Multi-Modality Analysis of Dynamic Medical Images.

Artem Mikheev, Joseph M DiMartino, Louisa Bokacheva, Henry Rusinek

Abstract readReview
In one paragraph

Review in Journal of imaging informatics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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

4 authors.

Artem MikheevDepartment of Radiology, NYU Grossman School of Medicine, 660 First Ave, Rm. 413, New York, NY, 10016, USA.
Joseph M DiMartinoDepartment of Radiology, NYU Grossman School of Medicine, 660 First Ave, Rm. 413, New York, NY, 10016, USA.
Louisa BokachevaDepartment of Neurology, NYU Grossman School of Medicine, New York, NY, 10016, USA.
Henry RusinekDepartment of Radiology, NYU Grossman School of Medicine, 660 First Ave, Rm. 413, New York, NY, 10016, USA. hr18@nyu.edu.ORCID http://orcid.org/0000-0001-6035-6314

Funding

Research Education ComponentP30AG066512 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Mary Sherman Mittelman · 2020 to 2026
$28.4M
TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Daniel K Sodickson · 2014 to 2026
$19.3M
Multi-scale and multi-modality imaging of neuropathology in VCIDU24NS135568 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI JAMES C GEE, Yulin Ge · 2023 to 2026
$6.6M
Advanced Software for MRI, PET, SPECT and CT Image AnalysisU24EB028980 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI RUSINEK, HENRY · 2019 to 2021
$1.2M
NIA NIH HHS P30 AG066512NIBIB NIH HHS P41 EB017183NIBIB NIH HHS U24 EB028980NINDS NIH HHS U24 NS135568
6 · The paper itself

Abstract

This article provides an overview of the FireVoxel software for quantitative analysis of medical images and its applications in the field. We describe FireVoxel's user interface, multi-layer design, dynamic parametric models, and several turn-key workflows. Additionally, we discuss its application in recent imaging projects. We outline basic image analysis tools such as segmentation, non-uniformity correction, and coregistration through a pictorial overview, with a focus on deformable coregistration and motion correction. Several example workflows and image-based dynamic modeling are also highlighted. Furthermore, we analyze peer-reviewed studies that utilized FireVoxel for image processing, categorizing published papers based on body structures/organs, image processing methods, and imaging modalities. For comparison, we searched the Ovid MEDLINE database to assess the general use of medical image analysis software. FireVoxel is used by over 3000 users worldwide, with 528 articles, including 413 in English, published in the past 15 years. MRI is the most commonly used imaging modality (78.2%), followed by CT (14.5%) and PET (7.3%). The most frequently used methods are dynamic modeling, segmentation, texture analysis, and coregistration. FireVoxel is commonly used in abdominal and genitourinary imaging studies, where it appears to fill a niche due to the lack of alternative software. The search of the Ovid MEDLINE suggests that quantitative medical imaging studies, on the other hand, focus on the brain and cardiovascular system. FireVoxel offers an effective set of quantitative tools, particularly for abdominal and genitourinary imaging, likely due to its ability to manage patient motion and correct for MR artifacts. The software is especially valuable for processing dynamic studies. The steady increase in publications utilizing FireVoxel reflects growing interest in this software and its relevance for image-based research.

Indexed as

Image Processing, Computer-AssistedMultimodal ImagingSoftwareHumansMagnetic Resonance ImagingUser-Computer InterfaceDiffusion-weighted imagingDynamic contrast-enhanced imagingDynamic imagingDynamic modelingMedical image analysisQuantitative imagingResearch software

Identifiers

PMID39900865
PMCPMC12701170

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.