ORACLE: An analytical approach for T1, T2, proton density, and off-resonance mapping with phase-cycled balanced steady-state free precession

IF 3 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Nils M. J. Plähn, Yasaman Safarkhanlo, Berk C. Açikgöz, Adèle L. C. Mackowiak, Piotr Radojewski, Gabriele Bonanno, Eva S. Peper, Rahel Heule, Jessica A. M. Bastiaansen
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Bastiaansen","doi":"10.1002/mrm.30388","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Purpose</h3>\n \n <p>To develop and validate a novel analytical approach simplifying <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>1</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_1 $$</annotation>\n </semantics></math>, <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>2</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_2 $$</annotation>\n </semantics></math>, proton density (PD), and off-resonance <span></span><math>\n <semantics>\n <mrow>\n <mi>Δ</mi>\n <mi>f</mi>\n </mrow>\n <annotation>$$ \\Delta f $$</annotation>\n </semantics></math> quantifications from phase-cycled balanced steady-state free precession (bSSFP) data. Additionally, to introduce a method to correct aliasing effects in undersampled bSSFP profiles.</p>\n </section>\n \n <section>\n \n <h3> Theory and Methods</h3>\n \n <p>Off-resonant-encoded analytical parameter quantification using complex linearized equations (ORACLE) provides analytical solutions for bSSFP profiles. which instantaneously quantify <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>1</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_1 $$</annotation>\n </semantics></math>, <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>2</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_2 $$</annotation>\n </semantics></math>, proton density (PD), and <span></span><math>\n <semantics>\n <mrow>\n <mi>Δ</mi>\n <mi>f</mi>\n </mrow>\n <annotation>$$ \\Delta f $$</annotation>\n </semantics></math>. An aliasing correction formalism was derived to allow undersampling of bSSFP profiles. ORACLE was used to quantify <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>1</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_1 $$</annotation>\n </semantics></math>, <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>2</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_2 $$</annotation>\n </semantics></math>, PD, <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>1</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_1 $$</annotation>\n </semantics></math>/<span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>2</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_2 $$</annotation>\n </semantics></math>, and <span></span><math>\n <semantics>\n <mrow>\n <mi>Δ</mi>\n <mi>f</mi>\n </mrow>\n <annotation>$$ \\Delta f $$</annotation>\n </semantics></math> based on fully sampled (<span></span><math>\n <semantics>\n <mrow>\n <mi>N</mi>\n <mo>=</mo>\n <mn>20</mn>\n </mrow>\n <annotation>$$ N=20 $$</annotation>\n </semantics></math>) bSSFP profiles from numerical simulations and 3T MRI experiments in phantom and 10 healthy subjects' brains. Obtained values were compared with reference scans in the same scan session. Aliasing correction was validated in subsampled (<span></span><math>\n <semantics>\n <mrow>\n <mi>N</mi>\n <mo>=</mo>\n <mn>4</mn>\n </mrow>\n <annotation>$$ N=4 $$</annotation>\n </semantics></math>) bSSFP profiles in numerical simulations and human brains.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>ORACLE quantifications agreed well with input values from simulations and phantom reference values (<i>R</i><sup>2</sup> = 0.99). In human brains, <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>1</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_1 $$</annotation>\n </semantics></math> and <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>2</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_2 $$</annotation>\n </semantics></math> quantifications when compared with reference methods showed coefficients of variation below 2.9% and 3.9%, biases of 182 and 16.6 ms, and mean white-matter values of 642 and 51 ms using ORACLE. The <span></span><math>\n <semantics>\n <mrow>\n <mi>Δ</mi>\n <mi>f</mi>\n </mrow>\n <annotation>$$ \\Delta f $$</annotation>\n </semantics></math> quantification differed less than 3 Hz between both methods. PD and <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>1</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_1 $$</annotation>\n </semantics></math> maps had comparable histograms. The <span></span><math>\n <semantics>\n <mrow>\n <mi>Λ</mi>\n </mrow>\n <annotation>$$ \\varLambda $$</annotation>\n </semantics></math> maps effectively identified cerebrospinal fluid. Aliasing correction removed aliasing-related quantification errors in undersampled bSSFP profiles, significantly reducing scan time.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>ORACLE enables simplified and rapid quantification of <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>1</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_1 $$</annotation>\n </semantics></math>, <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>T</mi>\n <mn>2</mn>\n </msub>\n </mrow>\n <annotation>$$ {T}_2 $$</annotation>\n </semantics></math>, PD, and <span></span><math>\n <semantics>\n <mrow>\n <mi>Δ</mi>\n <mi>f</mi>\n </mrow>\n <annotation>$$ \\Delta f $$</annotation>\n </semantics></math> from phase-cycled bSSFP profiles, reducing acquisition time and eliminating biomarker maps' coregistration issues.</p>\n </section>\n </div>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":"93 4","pages":"1657-1673"},"PeriodicalIF":3.0000,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Magnetic Resonance in Medicine","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/mrm.30388","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose

To develop and validate a novel analytical approach simplifying T 1 $$ {T}_1 $$ , T 2 $$ {T}_2 $$ , proton density (PD), and off-resonance Δ f $$ \Delta f $$ quantifications from phase-cycled balanced steady-state free precession (bSSFP) data. Additionally, to introduce a method to correct aliasing effects in undersampled bSSFP profiles.

Theory and Methods

Off-resonant-encoded analytical parameter quantification using complex linearized equations (ORACLE) provides analytical solutions for bSSFP profiles. which instantaneously quantify T 1 $$ {T}_1 $$ , T 2 $$ {T}_2 $$ , proton density (PD), and Δ f $$ \Delta f $$ . An aliasing correction formalism was derived to allow undersampling of bSSFP profiles. ORACLE was used to quantify T 1 $$ {T}_1 $$ , T 2 $$ {T}_2 $$ , PD, T 1 $$ {T}_1 $$ / T 2 $$ {T}_2 $$ , and Δ f $$ \Delta f $$ based on fully sampled ( N = 20 $$ N=20 $$ ) bSSFP profiles from numerical simulations and 3T MRI experiments in phantom and 10 healthy subjects' brains. Obtained values were compared with reference scans in the same scan session. Aliasing correction was validated in subsampled ( N = 4 $$ N=4 $$ ) bSSFP profiles in numerical simulations and human brains.

Results

ORACLE quantifications agreed well with input values from simulations and phantom reference values (R2 = 0.99). In human brains, T 1 $$ {T}_1 $$ and T 2 $$ {T}_2 $$ quantifications when compared with reference methods showed coefficients of variation below 2.9% and 3.9%, biases of 182 and 16.6 ms, and mean white-matter values of 642 and 51 ms using ORACLE. The Δ f $$ \Delta f $$ quantification differed less than 3 Hz between both methods. PD and T 1 $$ {T}_1 $$ maps had comparable histograms. The Λ $$ \varLambda $$ maps effectively identified cerebrospinal fluid. Aliasing correction removed aliasing-related quantification errors in undersampled bSSFP profiles, significantly reducing scan time.

Conclusion

ORACLE enables simplified and rapid quantification of T 1 $$ {T}_1 $$ , T 2 $$ {T}_2 $$ , PD, and Δ f $$ \Delta f $$ from phase-cycled bSSFP profiles, reducing acquisition time and eliminating biomarker maps' coregistration issues.

ORACLE:用相循环平衡稳态自由进动进行T1, T2,质子密度和非共振映射的分析方法。
目的:开发并验证一种新的分析方法,简化从相循环平衡稳态自由进动(bSSFP)数据中量化t1 $$ {T}_1 $$、t2 $$ {T}_2 $$、质子密度(PD)和非共振Δ f $$ \Delta f $$。此外,介绍了一种校正欠采样bSSFP轮廓中混叠效应的方法。理论与方法:利用复线性化方程(ORACLE)对非共振编码的分析参数进行量化,为bSSFP剖面提供了解析解。它可以即时量化t1 $$ {T}_1 $$, t2 $$ {T}_2 $$,质子密度(PD)和Δ f $$ \Delta f $$。推导了一种允许bSSFP剖面欠采样的混叠校正形式。基于全采样(N = 20 $$ N=20 $$)的幻影和10名健康受试者的数值模拟和3T MRI实验bSSFP谱,使用ORACLE对t1 $$ {T}_1 $$、t2 $$ {T}_2 $$、PD、t1 $$ {T}_1 $$ / t2 $$ {T}_2 $$和Δ f $$ \Delta f $$进行量化。将获得的值与同一扫描会话中的参考扫描进行比较。在数值模拟和人脑的次采样(N = 4 $$ N=4 $$) bSSFP剖面中验证了混叠校正。结果:ORACLE定量结果与模拟输入值和模拟参考值吻合良好(R2 = 0.99)。在人脑中,t1 $$ {T}_1 $$和t2 $$ {T}_2 $$量化方法与参考方法相比,变异系数低于2.9% and 3.9%, biases of 182 and 16.6 ms, and mean white-matter values of 642 and 51 ms using ORACLE. The Δ f $$ \Delta f $$ quantification differed less than 3 Hz between both methods. PD and T 1 $$ {T}_1 $$ maps had comparable histograms. The Λ $$ \varLambda $$ maps effectively identified cerebrospinal fluid. Aliasing correction removed aliasing-related quantification errors in undersampled bSSFP profiles, significantly reducing scan time.Conclusion: ORACLE enables simplified and rapid quantification of T 1 $$ {T}_1 $$ , T 2 $$ {T}_2 $$ , PD, and Δ f $$ \Delta f $$ from phase-cycled bSSFP profiles, reducing acquisition time and eliminating biomarker maps' coregistration issues.
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来源期刊
CiteScore
6.70
自引率
24.20%
发文量
376
审稿时长
2-4 weeks
期刊介绍: Magnetic Resonance in Medicine (Magn Reson Med) is an international journal devoted to the publication of original investigations concerned with all aspects of the development and use of nuclear magnetic resonance and electron paramagnetic resonance techniques for medical applications. Reports of original investigations in the areas of mathematics, computing, engineering, physics, biophysics, chemistry, biochemistry, and physiology directly relevant to magnetic resonance will be accepted, as well as methodology-oriented clinical studies.
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