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Finkelstein AJ, Liao C, Cao X, Mani M, Schifitto G, Zhong J. High-fidelity intravoxel incoherent motion parameter mapping using locally low-rank and subspace modeling. Neuroimage 2024; 292:120601. [PMID: 38588832 DOI: 10.1016/j.neuroimage.2024.120601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 03/23/2024] [Accepted: 04/01/2024] [Indexed: 04/10/2024] Open
Abstract
PURPOSE Intravoxel incoherent motion (IVIM) is a quantitative magnetic resonance imaging (MRI) method used to quantify perfusion properties of tissue non-invasively without contrast. However, clinical applications are limited by unreliable parameter estimates, particularly for the perfusion fraction (f) and pseudodiffusion coefficient (D*). This study aims to develop a high-fidelity reconstruction for reliable estimation of IVIM parameters. The proposed method is versatile and amenable to various acquisition schemes and fitting methods. METHODS To address current challenges with IVIM, we adapted several advanced reconstruction techniques. We used a low-rank approximation of IVIM images and temporal subspace modeling to constrain the magnetization dynamics of the bi-exponential diffusion signal decay. In addition, motion-induced phase variations were corrected between diffusion directions and b-values, facilitating the use of high SNR real-valued diffusion data. The proposed method was evaluated in simulations and in vivo brain acquisitions in six healthy subjects and six individuals with a history of SARS-CoV-2 infection and compared with the conventionally reconstructed magnitude data. Following reconstruction, IVIM parameters were estimated voxel-wise. RESULTS Our proposed method reduced noise contamination in simulations, resulting in a 60%, 58.9%, and 83.9% reduction in the NRMSE for D, f, and D*, respectively, compared to the conventional reconstruction. In vivo, anisotropic properties of D, f, and D* were preserved with the proposed method, highlighting microvascular differences in gray matter between individuals with a history of COVID-19 and those without (p = 0.0210), which wasn't observed with the conventional reconstruction. CONCLUSION The proposed method yielded a more reliable estimation of IVIM parameters with less noise than the conventional reconstruction. Further, the proposed method preserved anisotropic properties of IVIM parameter estimates and demonstrated differences in microvascular perfusion in COVID-affected subjects, which weren't observed with conventional reconstruction methods.
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Affiliation(s)
- Alan J Finkelstein
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Xiaozhi Cao
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Merry Mani
- Department of Radiology, University of Iowa, Iowa City, IA, USA
| | - Giovanni Schifitto
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA; Department of Neurology, University of Rochester, Rochester, NY, USA; Department of Imaging Sciences, University of Rochester, Rochester, NY, USA
| | - Jianhui Zhong
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA; Department of Imaging Sciences, University of Rochester, Rochester, NY, USA; Department of Physics and Astronomy, University of Rochester, Rochester, NY, USA.
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Prieto-González LS, Agulles-Pedrós L. Exploring the Potential of Machine Learning Algorithms to Improve Diffusion Nuclear Magnetic Resonance Imaging Models Analysis. J Med Phys 2024; 49:189-202. [PMID: 39131437 PMCID: PMC11309135 DOI: 10.4103/jmp.jmp_10_24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 03/27/2024] [Accepted: 04/15/2024] [Indexed: 08/13/2024] Open
Abstract
Purpose This paper explores different machine learning (ML) algorithms for analyzing diffusion nuclear magnetic resonance imaging (dMRI) models when analytical fitting shows restrictions. It reviews various ML techniques for dMRI analysis and evaluates their performance on different b-values range datasets, comparing them with analytical methods. Materials and Methods After standard fitting for reference, four sets of diffusion-weighted nuclear magnetic resonance images were used to train/test various ML algorithms for prediction of diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), and kurtosis (K). ML classification algorithms, including extra-tree classifier (ETC), logistic regression, C-support vector, extra-gradient boost, and multilayer perceptron (MLP), were used to determine the existence of diffusion parameters (D, D*, f, and K) within single voxels. Regression algorithms, including linear regression, polynomial regression, ridge, lasso, random forest (RF), elastic-net, and support-vector machines, were used to estimate the value of the diffusion parameters. Performance was evaluated using accuracy (ACC), area under the curve (AUC) tests, and cross-validation root mean square error (RMSECV). Computational timing was also assessed. Results ETC and MLP were the best classifiers, with 94.1% and 91.7%, respectively, for the ACC test and 98.7% and 96.3% for the AUC test. For parameter estimation, RF algorithm yielded the most accurate results The RMSECV percentages were: 8.39% for D, 3.57% for D*, 4.52% for f, and 3.53% for K. After the training phase, the ML methods demonstrated a substantial decrease in computational time, being approximately 232 times faster than the conventional methods. Conclusions The findings suggest that ML algorithms can enhance the efficiency of dMRI model analysis and offer new perspectives on the microstructural and functional organization of biological tissues. This paper also discusses the limitations and future directions of ML-based dMRI analysis.
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Affiliation(s)
| | - Luis Agulles-Pedrós
- Department of Physics, Medical Physics Group, National University of Colombia, Campus Bogotá, Bogotá, Colombia
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Ma C, Tian S, Song Q, Chen L, Meng X, Wang N, Lin L, Wang J, Liu A, Song Q. Amide Proton Transfer-Weighted Imaging Combined With Intravoxel Incoherent Motion for Evaluating Microsatellite Instability in Endometrial Cancer. J Magn Reson Imaging 2023; 57:493-505. [PMID: 35735273 DOI: 10.1002/jmri.28287] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/24/2022] [Accepted: 05/26/2022] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Microsatellite instability (MSI), caused by mismatch repair (MMR) protein defects that lead to uncorrectable mismatch bases, results in the accumulation of gene mutations and ultimately to tumors. Preoperative prediction of MSI can provide a basis for personalized and precise treatment of endometrial cancer (EC) patients. PURPOSE To investigate amide proton transfer weighting (APTw) imaging combined with intravoxel incoherent motion (IVIM) in the assessment of MSI in EC. STUDY TYPE Retrospective. POPULATION A total of 71 patients with EC (12 classified as the MSI group and 22 as the microsatellite stabilization [MSS] group after entering and leaving the group standard). FIELD STRENGTH/SEQUENCE A 3.0 T/IVIM, diffusion-weighted imaging (DWI) and APTw. ASSESSMENT Amide proton transfer (APT) value, apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) were calculated and compared between MSI and MSS groups. STATISTICAL TESTS The Kendall's W test; Mann-Whitney U-test; Chi-square test or Fisher's exact test; logistic regression analysis; Area under the receiver operating characteristic (ROC) curve (AUC); The Delong test; Pearson or Spearman correlation coefficients. The significance threshold was set at P < 0.05. RESULTS APT and D* values of the MSI group were significantly higher than those of the MSS group. While ADC, D, and f values in the MSI group were significantly lower than those in the MSS group. The multivariate analysis revealed that only APT and D* values were independent predictors to evaluate the MSI status. And the ROC curves indicated that the combination of APT and D* values could distinguish the MSI status of EC with the highest diagnostic efficacy (AUC = 0.973), even without significant difference to those by APT (AUC = 0.894) or D* (AUC = 0.920) value separately (P = 0.149 and 0.078, respectively). CONCLUSION Combination of APTw and IVIM imaging may serve as an effective noninvasive method for clinical assessment of MSI in EC. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Changjun Ma
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Shifeng Tian
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Qingling Song
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Lihua Chen
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Xing Meng
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Women and Children's Medical Group, Dalian, Liaoning, China
| | - Nan Wang
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Liangjie Lin
- Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Jiazheng Wang
- Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Ailian Liu
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Qingwei Song
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
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Hu J, Yu X, Yin P, Du B, Cai X. Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging for Monitoring the Immune Response of Immunogenic Chemotherapy. Front Oncol 2022; 12:796936. [PMID: 35646652 PMCID: PMC9136146 DOI: 10.3389/fonc.2022.796936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveTo evaluate the predictive value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in the quantitative assessment of conventional chemotherapy-activated immune responses in mouse tumor models and clinics.MethodsA total of 19 subcutaneous tumor-bearing mice were randomly divided into treated and control groups. Both groups had orderly IVIM DWI examinations before and on days 6 and 12 after the administration of cyclophosphamide (CPA) or saline. Pathologic examinations were performed, including HE staining and immunohistochemistry (IHC). The expressions of immune-related genes in the tumor were measured by qPCR. In addition, six patients with breast cancer requiring neoadjuvant chemotherapy (NACT) also underwent functional MRI examinations and IHC to determine potential antitumor immune response.ResultsAt the end of the study, the CPA treatment group showed the lowest tumor volume compared to the control group. For pathological examinations, the CPA treatment group showed a lower percentage of CD31 staining (P < 0.01) and Ki-67 staining (P<0.01), and a higher percentage of TUNEL staining (P < 0.01). The tumoral pseudodiffusion coefficient (D*) value showed a positive correlation with the CD31-positive staining rate (r = 0.729, P < 0.0001). The diffusion related parameters (D) value was positively correlated with TUNEL (r = 0.858, P < 0.0001) and negatively correlated with Ki-67 (r = -0.904, P < 0.0001). Moreover, a strong induction of the expression of the immune responses in the CPA treatment group was observed on day 12. D values showed a positive correlation with the Ifnb1-, CD8a-, Mx1-, Cxcl10- (r = 0.868, 0.864, 0.874, and 0.885, respectively, P < 0.0001 for all). Additionally, the functional MRI parameters and IHC results in patients with breast cancer after NACT also showed a close correlation between D value and CD8a (r = 0.631, P = 0.028).ConclusionsThe treatment response induced by immunogenic chemotherapy could be effectively evaluated using IVIM-DWI. The D values could be potential, sensitive imaging marker for identifying the antitumor immune response initiated by immunogenic chemotherapy.
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Affiliation(s)
- Junjiao Hu
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China
- Medical Imaging Center, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Xin Yu
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Peidi Yin
- Department of Pathology, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Bin Du
- Department of Pathology, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China
- *Correspondence: Xiangran Cai, ; Bin Du,
| | - Xiangran Cai
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China
- *Correspondence: Xiangran Cai, ; Bin Du,
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Henriksen OM, del Mar Álvarez-Torres M, Figueiredo P, Hangel G, Keil VC, Nechifor RE, Riemer F, Schmainda KM, Warnert EAH, Wiegers EC, Booth TC. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques. Front Oncol 2022; 12:810263. [PMID: 35359414 PMCID: PMC8961422 DOI: 10.3389/fonc.2022.810263] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 01/05/2022] [Indexed: 01/16/2023] Open
Abstract
Objective Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.
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Affiliation(s)
- Otto M. Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | | | - Patricia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics-Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Gilbert Hangel
- Department of Neurosurgery, Medical University, Vienna, Austria
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University, Vienna, Austria
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Ruben E. Nechifor
- International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Department of Clinical Psychology and Psychotherapy, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | | | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Thomas C. Booth
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School of Biomedical Engineering and Imaging Sciences, St. Thomas’ Hospital, King’s College London, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
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Wang DJJ, Le Bihan D, Krishnamurthy R, Smith M, Ho ML. Noncontrast Pediatric Brain Perfusion: Arterial Spin Labeling and Intravoxel Incoherent Motion. Magn Reson Imaging Clin N Am 2021; 29:493-513. [PMID: 34717841 DOI: 10.1016/j.mric.2021.06.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Noncontrast magnetic resonance imaging techniques for measuring brain perfusion include arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM). These techniques provide noninvasive and repeatable assessment of cerebral blood flow or cerebral blood volume without the need for intravenous contrast. This article discusses the technical aspects of ASL and IVIM with a focus on normal physiologic variations, technical parameters, and artifacts. Multiple pediatric clinical applications are presented, including tumors, stroke, vasculopathy, vascular malformations, epilepsy, migraine, trauma, and inflammation.
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Affiliation(s)
- Danny J J Wang
- USC Institute for Neuroimaging and Informatics, SHN, 2025 Zonal Avenue, Health Sciences Campus, Los Angeles, CA 90033, USA
| | - Denis Le Bihan
- NeuroSpin, Centre d'études de Saclay, Bâtiment 145, Gif-sur-Yvette 91191, France
| | - Ram Krishnamurthy
- Department of Radiology, Nationwide Children's Hospital, 700 Children's Drive - ED4, Columbus, OH 43205, USA
| | - Mark Smith
- Department of Radiology, Nationwide Children's Hospital, 700 Children's Drive - ED4, Columbus, OH 43205, USA
| | - Mai-Lan Ho
- Department of Radiology, Nationwide Children's Hospital, 700 Children's Drive - ED4, Columbus, OH 43205, USA.
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Merisaari H, Federau C. Signal to noise and b-value analysis for optimal intra-voxel incoherent motion imaging in the brain. PLoS One 2021; 16:e0257545. [PMID: 34555054 PMCID: PMC8459980 DOI: 10.1371/journal.pone.0257545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 09/06/2021] [Indexed: 11/28/2022] Open
Abstract
Intravoxel incoherent motion (IVIM) is a method that can provide quantitative information about perfusion in the human body, in vivo, and without contrast agent. Unfortunately, the IVIM perfusion parameter maps are known to be relatively noisy in the brain, in particular for the pseudo-diffusion coefficient, which might hinder its potential broader use in clinical applications. Therefore, we studied the conditions to produce optimal IVIM perfusion images in the brain. IVIM imaging was performed on a 3-Tesla clinical system in four healthy volunteers, with 16 b values 0, 10, 20, 40, 80, 110, 140, 170, 200, 300, 400, 500, 600, 700, 800, 900 s/mm2, repeated 20 times. We analyzed the noise characteristics of the trace images as a function of b-value, and the homogeneity of the IVIM parameter maps across number of averages and sub-sets of the acquired b values. We found two peaks of noise of the trace images as function of b value, one due to thermal noise at high b-value, and one due to physiological noise at low b-value. The selection of b value distribution was found to have higher impact on the homogeneity of the IVIM parameter maps than the number of averages. Based on evaluations, we suggest an optimal b value acquisition scheme for a 12 min scan as 0 (7), 20 (4), 140 (19), 300 (9), 500 (19), 700 (1), 800 (4), 900 (1) s/mm2.
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Affiliation(s)
- Harri Merisaari
- Department of Diagnostic Radiology, University of Turku, Turku, Finland
- Department of Future Technologies, University of Turku, Turku, Finland
| | - Christian Federau
- Institute for Biomedical Engineering, ETH, Zürich and University Zürich, Zürich, Switzerland
- AI Medical, Zürich, Switzerland
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