EUVIMEDEuropean Health Evidence
Uhr 7/7Sources Journal Tree
Easy Demo

Lokaler Crossref-Datenbestand · journal-article

Clinical Implementation and Validation of Automated Slice-to-Volume Reconstruction for Fetal MRI Using a Vendor-Neutral MONAI-Based Imaging Informatics Pipeline

Jungwhan John Choi, Bryan Luna, Stephen Clark, Alexander J. Towbin, Usha D. Nagaraj, Beth M. Kline-Fath, Jonathan R. Dillman, Elanchezhian Somasundaram

Journal of Imaging Informatics in Medicine · 2026

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Abstract This study aims to evaluate the clinical performance and operational reliability of a fully automated, vendor-neutral imaging informatics pipeline for fetal MRI slice-to-volume reconstruction using open-source Medical Open Network for Artificial Intelligence (MONAI) Deploy Express, DICOM routing, and PACS return. In this retrospective implementation study, consecutive singleton fetal MRI examinations performed at a tertiary fetal care center between October and December 2025 were processed using a MONAI Deploy Express pipeline triggered by DICOM routing. The pipeline performed automated series selection and motion-corrected SVR reconstruction for fetal brain and body imaging using routine single-shot fast spin-echo inputs. Reconstructed volumes were returned to PACS for radiologist review. Three fellowship-trained fetal radiologists independently scored reconstruction quality using a 5-point Likert scale. Primary outcomes included examination-level reconstruction acceptability, inter-reader reliability, failure modes, and operational time to PACS availability after transition to the finalized production workflow. Among 67 triggered examinations, 2 represented technical workflow events and were excluded from clinical performance analysis, leaving 65 examinations for image-quality evaluation. Mean gestational age was 28.9 weeks (range, 19–36 weeks) and most fetuses had structural abnormalities. Brain SVR was rated pass-or-higher in 59/65 examinations (90.8%) and body SVR was rated pass-or-higher in 57/65 examinations (87.7%). Inter-reader reliability was excellent for brain (ICC, 0.93) and body (ICC, 0.92) reconstruction quality assessments. Reconstruction failures were primarily associated with suboptimal or insufficient input stacks, severe fetal motion, amniotic fluid extremes, complex anatomic distortions, and early gestational age. In 57 consecutively processed examinations after finalized production integration, median time to PACS availability was 10 min 28 s for brain SVR and 11 min 50 s for body SVR. Automated fetal MRI SVR was operationally feasible using a DICOM-based, vendor-neutral deployment architecture integrated with routine PACS workflow. In this single-center, single-vendor cohort, the pipeline returned radiologist-acceptable reconstructions within a clinically practical timeframe. Multi-vendor and comparative reader studies are needed to establish geometric accuracy, generalizability, and diagnostic benefit.

Bibliografischer Nachweis

Publikationsdaten

Autor:innen
Jungwhan John Choi, Bryan Luna, Stephen Clark, Alexander J. Towbin, Usha D. Nagaraj, Beth M. Kline-Fath, Jonathan R. Dillman, Elanchezhian Somasundaram
Quelle
Journal of Imaging Informatics in Medicine
Publikation
2026-01-01
Band / Ausgabe
Nicht angegeben
Seiten
Nicht angegeben
ISSN / ISBN
2948-2933
Zitationen
0 laut Crossref
Referenzen
0 hinterlegt

Zitieren

Zitierfähiger Nachweis

Jungwhan John Choi, Bryan Luna, Stephen Clark, Alexander J. Towbin, Usha D. Nagaraj, Beth M. Kline-Fath, Jonathan R. Dillman, Elanchezhian Somasundaram (2026). Clinical Implementation and Validation of Automated Slice-to-Volume Reconstruction for Fetal MRI Using a Vendor-Neutral MONAI-Based Imaging Informatics Pipeline. Journal of Imaging Informatics in Medicine. https://doi.org/10.1007/s10278-026-02228-z
RIS BibTeX CSL-JSON

Kontext

Themen, Förderung und Nutzung

Lizenzhinweise: Lizenz 1