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Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study
SIMPLE SUMMARY: This preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. In addition, synthetic MR could provide contrast images analogous to standard T1- and...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9179589/ https://www.ncbi.nlm.nih.gov/pubmed/35681631 http://dx.doi.org/10.3390/cancers14112651 |
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author | Konar, Amaresha Shridhar Shah, Akash Deelip Paudyal, Ramesh Fung, Maggie Banerjee, Suchandrima Dave, Abhay Hatzoglou, Vaios Shukla-Dave, Amita |
author_facet | Konar, Amaresha Shridhar Shah, Akash Deelip Paudyal, Ramesh Fung, Maggie Banerjee, Suchandrima Dave, Abhay Hatzoglou, Vaios Shukla-Dave, Amita |
author_sort | Konar, Amaresha Shridhar |
collection | PubMed |
description | SIMPLE SUMMARY: This preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. In addition, synthetic MR could provide contrast images analogous to standard T1- and T2-weighted images. The reproducibility and repeatability of this method have been previously established for brain imaging. This study reports and analyzes the quantitative T1 and T2 values for 11 BM patients (17 BM lesions) with a total of 82 regions of interest (ROIs) delineated by an experienced neuroradiologist. The initial results, which need to be further validated in a larger patient cohort, demonstrated the ability of T1 and T2 metric values to characterize BMs and normal-appearing brain tissues. The T1 and T2 metrics could be potential surrogate biomarkers for BM free water content (cellularity) and tumor morphology, respectively. ABSTRACT: The present preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. We acquired synthetic MRI data from 11 BM patients on a 3T scanner. A multiple-dynamic multiple-echo (MDME) sequence was used for data acquisition and synthetic image reconstruction, including post-processing. MDME is a multi-contrast sequence that enables absolute quantification of physical tissue properties, including T1 and T2, independent of the scanner settings. In total, 82 regions of interest (ROIs) were analyzed, which were obtained from both normal-appearing brain tissue and BM lesions. The mean values obtained from the 48 normal-appearing brain tissue regions and 34 ROIs of BM lesions (T1 and T2) were analyzed using standard statistical methods. The mean T1 and T2 values were 1143 ms and 78 ms, respectively, for normal-appearing gray matter, 701 ms and 64 ms for white matter, and 4206 ms and 390 ms for cerebrospinal fluid. For untreated BMs, the mean T1 and T2 values were 1868 ms and 100 ms, respectively, and 2211 ms and 114 ms for the treated group. The quantitative T1 and T2 values generated from synthetic MRI can characterize BM and normal-appearing brain tissues. |
format | Online Article Text |
id | pubmed-9179589 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91795892022-06-10 Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study Konar, Amaresha Shridhar Shah, Akash Deelip Paudyal, Ramesh Fung, Maggie Banerjee, Suchandrima Dave, Abhay Hatzoglou, Vaios Shukla-Dave, Amita Cancers (Basel) Article SIMPLE SUMMARY: This preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. In addition, synthetic MR could provide contrast images analogous to standard T1- and T2-weighted images. The reproducibility and repeatability of this method have been previously established for brain imaging. This study reports and analyzes the quantitative T1 and T2 values for 11 BM patients (17 BM lesions) with a total of 82 regions of interest (ROIs) delineated by an experienced neuroradiologist. The initial results, which need to be further validated in a larger patient cohort, demonstrated the ability of T1 and T2 metric values to characterize BMs and normal-appearing brain tissues. The T1 and T2 metrics could be potential surrogate biomarkers for BM free water content (cellularity) and tumor morphology, respectively. ABSTRACT: The present preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. We acquired synthetic MRI data from 11 BM patients on a 3T scanner. A multiple-dynamic multiple-echo (MDME) sequence was used for data acquisition and synthetic image reconstruction, including post-processing. MDME is a multi-contrast sequence that enables absolute quantification of physical tissue properties, including T1 and T2, independent of the scanner settings. In total, 82 regions of interest (ROIs) were analyzed, which were obtained from both normal-appearing brain tissue and BM lesions. The mean values obtained from the 48 normal-appearing brain tissue regions and 34 ROIs of BM lesions (T1 and T2) were analyzed using standard statistical methods. The mean T1 and T2 values were 1143 ms and 78 ms, respectively, for normal-appearing gray matter, 701 ms and 64 ms for white matter, and 4206 ms and 390 ms for cerebrospinal fluid. For untreated BMs, the mean T1 and T2 values were 1868 ms and 100 ms, respectively, and 2211 ms and 114 ms for the treated group. The quantitative T1 and T2 values generated from synthetic MRI can characterize BM and normal-appearing brain tissues. MDPI 2022-05-27 /pmc/articles/PMC9179589/ /pubmed/35681631 http://dx.doi.org/10.3390/cancers14112651 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Konar, Amaresha Shridhar Shah, Akash Deelip Paudyal, Ramesh Fung, Maggie Banerjee, Suchandrima Dave, Abhay Hatzoglou, Vaios Shukla-Dave, Amita Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study |
title | Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study |
title_full | Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study |
title_fullStr | Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study |
title_full_unstemmed | Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study |
title_short | Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study |
title_sort | quantitative synthetic magnetic resonance imaging for brain metastases: a feasibility study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9179589/ https://www.ncbi.nlm.nih.gov/pubmed/35681631 http://dx.doi.org/10.3390/cancers14112651 |
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