Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Impact of Free Water Correction on the Mean Diffusivity of Glioblastoma is Regional and b-value Dependent: A Retrospective Study on Open-source Datasets.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine·2026

Same author

The current state of demographic subgroup reporting for commercially available AI for radiology: a scoping review.

European radiology·2026

Same author

Endoscopic Supracerebellar Transtentorial Approach for a Low-Grade Epilepsy-Associated Tumor in the Posterior Mesial Temporal Lobe: A 2-Dimensional Operative Video.

Operative neurosurgery (Hagerstown, Md.)·2026

Same author

Assessing and mitigating demographic bias in large language models for diagnostic radiology.

Japanese journal of radiology·2026

Same author

Uncertainty-Aware Super-Resolution for Mammography Phantoms using a Dropout-Enabled SwinIR.

Journal of imaging informatics in medicine·2026

Same author

Legal liability of physicians and new governance in the AI era.

Japanese journal of radiology·2026

Search research articles

Related Experiment Video

Updated: Jul 20, 2025

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on ¹⁸F-AV-1451

Published on: April 18, 2025

AI-based Virtual Synthesis of Methionine PET from Contrast-enhanced MRI: Development and External Validation Study.

Hirotaka Takita¹, Toshimasa Matsumoto¹, Hiroyuki Tatekawa¹

¹From the Department of Diagnostic and Interventional Radiology, Graduate School of Medicine (H. Takita, T.M., H. Tatekawa, Y. Mitsuyama, S.L.W., Y. Miki, D.U.), Smart Life Science Laboratory, Center for Health Science Innovation (T.M., D.U.), and Department of Neurosurgery, Graduate School of Medicine (K.N., T.U.), Osaka Metropolitan University, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan; and Department of Radiology, Osaka Metropolitan University Hospital, Osaka, Japan (Y.K.).

|August 1, 2023

Summary

This summary is machine-generated.

Artificial intelligence (AI) can now generate synthetic methionine PET images from MRI scans, offering a promising alternative for glioma management by overcoming limitations of traditional PET imaging.

More Related Videos

MRI and PET in Mouse Models of Myocardial Infarction

MRI and PET in Mouse Models of Myocardial Infarction

Published on: December 19, 2013

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis

Published on: October 25, 2024

Related Experiment Videos

Last Updated: Jul 20, 2025

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on ¹⁸F-AV-1451

Published on: April 18, 2025

MRI and PET in Mouse Models of Myocardial Infarction

MRI and PET in Mouse Models of Myocardial Infarction

Published on: December 19, 2013

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis

Published on: October 25, 2024

Area of Science:

Neuroimaging
Artificial Intelligence
Oncology

Background:

¹¹C-methionine PET is valuable for glioma management but faces limitations due to radiation exposure and facility availability.
Developing alternative imaging methods is crucial for wider clinical application.

Purpose of the Study:

To create synthetic methionine PET images using an AI-based model from contrast-enhanced (CE) MRI.
To evaluate the performance of these synthetic PET images for glioma grading and prognosis compared to real PET.

Main Methods:

An AI image-to-image translation model was developed and validated using a dataset of patients with both methionine PET and CE MRI.
Pearson correlation coefficients were calculated for tumor to background ratios (TBR_max, TBR_mean) and lesion volume.
External validation was performed on open-source glioma datasets using receiver operating characteristic curve analysis for grading and survival analysis for prognosis.

Main Results:

Synthetic PET images showed strong correlations with real PET images for TBR_max (0.68), TBR_mean (0.76), and lesion volume (0.92) in the internal test set.
The AI model achieved an AUC of 0.81 for classifying high-grade versus low-grade gliomas in the external test set.
Significant differences in overall survival were observed between high and low TBR_max groups derived from synthetic PET images.

Conclusions:

AI-generated synthetic methionine PET images closely mimic real PET findings.
The AI model demonstrates robust performance in glioma grading and prognostication, offering a potential solution to the limitations of conventional PET imaging.