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Stamatelatou A, Rizzo R, Simsek K, van Asten JJA, Heerschap A, Scheenen T, Kreis R. Diffusion-weighted MR spectroscopy of the prostate. Magn Reson Med 2024; 92:1323-1337. [PMID: 38775024 DOI: 10.1002/mrm.30141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/12/2024] [Accepted: 04/17/2024] [Indexed: 07/23/2024]
Abstract
PURPOSE Prostate tissue has a complex microstructure, mainly composed of epithelial and stromal cells, and of extracellular (acinar-luminal) spaces. Diffusion-weighted MR spectroscopy (DW-MRS) is ideally suited to explore complex microstructure in vivo with metabolites selectively distributed in different subspaces. To date, this technique has been applied to brain and muscle. This study presents the development and pioneering utilization of 1H-DW-MRS in the prostate, accompanied by in vitro studies to support interpretations of in vivo findings. METHODS Nine healthy volunteers underwent a prostate MR examination (mean age, 56 years; range, 31-66). Metabolic complexation was studied in vitro using solutions with major compounds found in prostatic fluid of the lumen. DW-MRS was performed at 3 T with a non-water-suppressed single-voxel sequence with metabolite-cycling to concurrently measure metabolite and water signals. The water signal was used in postprocessing as a reference in a motion-compensation scheme. The spectra were fitted simultaneously in the spectral and diffusion-weighting dimensions. Apparent diffusion coefficients (ADCs) were derived by fitting signal decays that were assumed to be mono-exponential for metabolites and biexponential for water. RESULTS DW-MRS of the prostate revealed relatively low ADCs for Cho and Cr compounds, aligning with their intracellular location and higher ADCs for citrate and spermine supporting their luminal origin. In vitro assessments of the ADCs of citrate and spermine demonstrated their complex formation and protein binding. Tissue concentrations of MRS-detectable metabolites were as expected for the voxel location. CONCLUSIONS This work successfully demonstrates the feasibility of 1H-DW-MRS of the prostate and its potential for providing valuable microstructural information.
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Affiliation(s)
- Angeliki Stamatelatou
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Rudy Rizzo
- Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
- Translational Imaging Center, sitem-insel, Bern, Switzerland
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Kadir Simsek
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
| | - Jack J A van Asten
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Roland Kreis
- Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
- Translational Imaging Center, sitem-insel, Bern, Switzerland
- Institute of Psychology, University of Bern, Bern, Switzerland
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2
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Loubrie S, Zou J, Rodriguez-Soto AE, Lim J, Andreassen MMS, Cheng Y, Batasin SJ, Ebrahimi S, Fang LK, Conlin CC, Seibert TM, Hahn ME, Dialani V, Wei CJ, Karimi Z, Kuperman J, Dale AM, Ojeda-Fournier H, Pisano E, Rakow-Penner R. Discrimination Between Benign and Malignant Lesions With Restriction Spectrum Imaging MRI in an Enriched Breast Cancer Screening Cohort. J Magn Reson Imaging 2024. [PMID: 39291552 DOI: 10.1002/jmri.29599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 08/16/2024] [Accepted: 08/20/2024] [Indexed: 09/19/2024] Open
Abstract
BACKGROUND Breast cancer screening with dynamic contrast-enhanced MRI (DCE-MRI) is recommended for high-risk women but has limitations, including variable specificity and difficulty in distinguishing cancerous (CL) and high-risk benign lesions (HRBL) from average-risk benign lesions (ARBL). Complementary non-invasive imaging techniques would be useful to improve specificity. PURPOSE To evaluate the performance of a previously-developed breast-specific diffusion-weighted MRI (DW-MRI) model (BS-RSI3C) to improve discrimination between CL, HRBL, and ARBL in an enriched screening population. STUDY TYPE Prospective. SUBJECTS Exactly 187 women, either with mammography screening recommending additional imaging (N = 49) or high-risk individuals undergoing routine breast MRI (N = 138), before the biopsy. FIELD STRENGTH/SEQUENCE Multishell DW-MRI echo planar imaging sequence with a reduced field of view at 3.0 T. ASSESSMENT A total of 72 women had at least one biopsied lesion, with 89 lesions categorized into ARBL, HRBL, CL, and combined CLs and HRBLs (CHRLs). DW-MRI data were processed to produce apparent diffusion coefficient (ADC) maps, and estimate signal contributions (C1, C2, and C3-restricted, hindered, and free diffusion, respectively) from the BS-RSI3C model. Lesion regions of interest (ROIs) were delineated on DW images based on suspicious DCE-MRI findings by two radiologists; control ROIs were drawn in the contralateral breast. STATISTICAL TESTS One-way ANOVA and two-sided t-tests were used to assess differences in signal contributions and ADC values among groups. P-values were adjusted using the Bonferroni method for multiple testing, P = 0.05 was used for the significance level. Receiver operating characteristics (ROC) curves and intra-class correlations (ICC) were also evaluated. RESULTS C1, √C1C2, andlog C 1 C 2 C 3 $$ \log \left(\frac{{\mathrm{C}}_1{\mathrm{C}}_2}{{\mathrm{C}}_3}\right) $$ were significantly different in HRBLs compared with ARBLs (P-values < 0.05). Thelog C 1 C 2 C 3 $$ \log \left(\frac{{\mathrm{C}}_1{\mathrm{C}}_2}{{\mathrm{C}}_3}\right) $$ had the highest AUC (0.821) in differentiating CHRLs from ARBLs, performing better than ADC (0.696), especially in non-mass enhancement (0.776 vs. 0.517). DATA CONCLUSION This study demonstrated the BS-RSI3C could differentiate HRBLs from ARBLs in a screening population, and separate CHRLs from ARBLs better than ADC. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE 2.
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Affiliation(s)
- Stephane Loubrie
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Jingjing Zou
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Ana E Rodriguez-Soto
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Jihe Lim
- Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Gyeonggi-do, Republic of Korea
| | - Maren M S Andreassen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research and Innovation, Vestre Viken, Drammen, Norway
| | - Yuwei Cheng
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Summer J Batasin
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Sheida Ebrahimi
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Lauren K Fang
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Christopher C Conlin
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Tyler M Seibert
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Radiation Medicine, University of California San Diego, La Jolla, California, USA
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Michael E Hahn
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Vandana Dialani
- Department of Radiology, Beth Israel Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Catherine J Wei
- Department of Radiology, Mass General Brigham - Salem Hospital, Salem, Massachusetts, USA
| | - Zahra Karimi
- Department of Radiology, Beth Israel Hospital, Boston, Massachusetts, USA
| | - Joshua Kuperman
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Haydee Ojeda-Fournier
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Etta Pisano
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- American College of Radiology, Reston, Virginia, USA
| | - Rebecca Rakow-Penner
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
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Le Bihan D. From Brownian motion to virtual biopsy: a historical perspective from 40 years of diffusion MRI. Jpn J Radiol 2024:10.1007/s11604-024-01642-z. [PMID: 39289243 DOI: 10.1007/s11604-024-01642-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Accepted: 08/07/2024] [Indexed: 09/19/2024]
Abstract
Diffusion MRI was introduced in 1985, showing how the diffusive motion of molecules, especially water, could be spatially encoded with MRI to produce images revealing the underlying structure of biologic tissues at a microscopic scale. Diffusion is one of several Intravoxel Incoherent Motions (IVIM) accessible to MRI together with blood microcirculation. Diffusion imaging first revolutionized the management of acute cerebral ischemia by allowing diagnosis at an acute stage when therapies can still work, saving the outcomes of many patients. Since then, the field of diffusion imaging has expanded to the whole body, with broad applications in both clinical and research settings, providing insights into tissue integrity, structural and functional abnormalities from the hindered diffusive movement of water molecules in tissues. Diffusion imaging is particularly used to manage many neurologic disorders and in oncology for detecting and classifying cancer lesions, as well as monitoring treatment response at an early stage. The second major impact of diffusion imaging concerns the wiring of the brain (Diffusion Tensor Imaging, DTI), allowing to obtain from the anisotropic movement of water molecules in the brain white-matter images in 3 dimensions of the brain connections making up the Connectome. DTI has opened up new avenues of clinical diagnosis and research to investigate brain diseases, neurogenesis and aging, with a rapidly extending field of application in psychiatry, revealing how mental illnesses could be seen as Connectome spacetime disorders. Adding that water diffusion is closely associated to neuronal activity, as shown from diffusion fMRI, one may consider that diffusion MRI is ideally suited to investigate both brain structure and function. This article retraces the early days and milestones of diffusion MRI which spawned over 40 years, showing how diffusion MRI emerged and expanded in the research and clinical fields, up to become a pillar of modern clinical imaging.
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Affiliation(s)
- Denis Le Bihan
- NeuroSpin, CEA, Paris-Saclay University, Bât 145, CEA-Saclay Center, 91191, Gif-sur-Yvette, France.
- Human Brain Research Center, Kyoto University, Kyoto, Japan.
- Department of System Neuroscience, National Institutes for Physiological Sciences, Okazaki, Japan.
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Zheng Y, Han N, Huang W, Jiang Y, Zhang J. Evaluating Mediastinal Lymph Node Metastasis of Non-Small Cell Lung Cancer Using Mono-exponential, Bi-exponential, and Stretched-exponential Models of Diffusion-weighted Imaging. J Thorac Imaging 2024; 39:285-292. [PMID: 38153288 DOI: 10.1097/rti.0000000000000771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
PURPOSE To explore and compare the diagnostic values of mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) parameters of primary lesions and lymph nodes (LNs) to predict mediastinal LN metastasis in patients with non-small cell lung cancer. PATIENTS AND METHODS Sixty-one patients with non-small cell lung cancer underwent preoperative magnetic resonance imaging, including multiple b -value DWI. The DWI parameters, including apparent diffusion coefficient (ADC) from a mono-exponential model, true diffusion (D) coefficient, pseudo-diffusion (D*) coefficient, and perfusion fraction (f) from a bi-exponential model, distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index (α) from a stretched-exponential model of primary tumors and LNs and the size characteristics of LNs, were measured and compared. Multivariate logistic regression analysis was used to establish models for predicting mediastinal LN metastasis. Receiver operating characteristic analysis was applied to evaluate diagnostic performances. RESULTS The DWI parameters of primary tumors showed no statistical significance between LN metastasis-positive and LN metastasis-negative groups. Nonmetastatic LNs had significantly higher ADC, D, DDC, and α values compared with metastatic LNs (all P < 0.05). The short-dimension, long-dimension, and short-long dimension ratio of metastatic LNs was significantly larger than those of nonmetastatic ones (all P < 0.05). The D value showed the best diagnostic performance among all DWI-derived single parameters, and the short dimension of LNs performed the same among all the size variables. Furthermore, the combination of DWI parameters (ADC and D) and the short dimension of LNs can significantly improve diagnostic efficiency. CONCLUSIONS The ADC, D, DDC, and α from the mono-exponential, bi-exponential, and stretched-exponential models were demonstrated efficient in differentiating benign from metastatic LNs, and the combination of ADC, D, and short dimension of LNs may have a better diagnostic performance than DWI or size-derived parameters either in combination or individually.
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Affiliation(s)
- Yu Zheng
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Na Han
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Wenjing Huang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Yanli Jiang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
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Curtis M, Bayat M, Garic D, Alfano AR, Hernandez M, Curzon M, Bejarano A, Tremblay P, Graziano P, Dick AS. Structural Development of Speech Networks in Young Children at Risk for Speech Disorder. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.23.609470. [PMID: 39229017 PMCID: PMC11370569 DOI: 10.1101/2024.08.23.609470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Characterizing the structural development of the neural speech network in early childhood is important for understanding speech acquisition. To investigate speech in the developing brain, 94 children aged 4-7-years-old at risk for early speech disorder were scanned using diffusion weighted imaging (DWI) magnetic resonance imaging (MRI). Additionally, each child completed the Syllable Repetition Task (SRT), a validated measure of phoneme articulation. The DWI data were modeled using multi-compartment restriction spectrum imaging (RSI) to measure restricted and hindered diffusion properties in both grey and white matter. Consequently, we analyzed the diffusion data using both whole brain analysis, and automated fiber quantification (AFQ) analysis to establish tract profiles for each of six fiber pathways thought to be important for supporting speech development. In the whole brain analysis, we found that SRT performance was associated with restricted diffusion in bilateral inferior frontal gyrus ( pars opercularis ), right pre-supplementary/ supplementary motor area (pre-SMA/SMA), and bilateral cerebellar grey matter ( p < .005). Age moderated these associations in left pars opercularis and frontal aslant tract (FAT). However, in both cases only the cerebellar findings survived a cluster correction. We also found associations between SRT performance and restricted diffusion in cortical association fiber pathways, especially left FAT, and in the cerebellar peduncles. Analyses using automatic fiber quantification (AFQ) highlighted differences in high and low performing children along specific tract profiles, most notably in left but not right FAT. These findings suggest that individual differences in speech performance are reflected in structural gray and white matter differences as measured by restricted and hindered diffusion metrics, and offer important insights into developing brain networks supporting speech in very young children.
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Karat BG, Genc S, Raven EP, Palombo M, Khan AR, Jones DK. The developing hippocampus: Microstructural evolution through childhood and adolescence. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.19.608590. [PMID: 39229062 PMCID: PMC11370384 DOI: 10.1101/2024.08.19.608590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
The hippocampus is a structure in the medial temporal lobe which serves multiple cognitive functions. While important, the development of the hippocampus in the formative period of childhood and adolescence has not been extensively investigated, with most contemporary research focusing on macrostructural measures of volume. Thus, there has been little research on the development of the micron-scale structures (i.e., microstructure) of the hippocampus, which engender its cognitive functions. The current study examined age-related changes of hippocampal microstructure using diffusion MRI data acquired with an ultra-strong gradient (300 mT/m) MRI scanner in a sample of children and adolescents (N=88; 8-19 years). Surface-based hippocampal modelling was combined with established microstructural approaches, such as Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion Density Imaging (NODDI), and a more advanced gray matter diffusion model Soma And Neurite Density Imaging (SANDI). No significant changes in macrostructural measures (volume, gyrification, and thickness) were found between 8-19 years, while significant changes in microstructure measures related to neurites (from NODDI and SANDI), soma (from SANDI), and mean diffusivity (from DTI) were found. In particular, there was a significant increase across age in neurite MR signal fraction and a significant decrease in extracellular MR signal fraction and mean diffusivity across the hippocampal subfields and long-axis. A significant negative correlation between age and MR apparent soma radius was found in the subiculum and CA1 throughout the anterior and body of the hippocampus. Further surface-based analyses uncovered variability in age-related microstructural changes between the subfields and long-axis, which may reflect ostensible developmental differences along these two axes. Finally, correlation of hippocampal surfaces representing age-related changes of microstructure with maps derived from histology allowed for postulation of the potential underlying microstructure that diffusion changes across age may be capturing. Overall, distinct neurite and soma developmental profiles in the human hippocampus during late childhood and adolescence are reported for the first time.
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Affiliation(s)
- Bradley G Karat
- Robarts Research Institute, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada
| | - Sila Genc
- Department of Neurosurgery, The Royal Children's Hospital, Melbourne, Australia
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Erika P Raven
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
| | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
| | - Ali R Khan
- Robarts Research Institute, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada
- Department of Medical Biophysics, Western University, London, ON, Canada
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
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Paus T. Development and Maturation of the Human Brain, from Infancy to Adolescence. Curr Top Behav Neurosci 2024. [PMID: 39138744 DOI: 10.1007/7854_2024_514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Abstract
This chapter describes basic principles and key findings regarding the development and maturation of the human brain, the former referring to the pre-natal and early post-natal periods and the latter concerning childhood and adolescence. In both cases, we focus on brain structure as revealed in vivo with multi-modal magnetic resonance imaging (MRI). We begin with a few numbers about the human brain and its cellular composition and a brief overview of a number of MRI-based metrics used to characterize age-related variations in grey and white matter. We then proceed with synthesizing current knowledge about developmental and maturational changes in the cerebral cortex (its thickness, surface area, and intra-cortical myelination) and the underlying white matter (volume and structural properties). To facilitate biological interpretations of MRI-derived metrics, we introduce the concept of virtual histology. We conclude the chapter with a few notes about future directions in the study of factors shaping the human brain from conception onwards.
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Affiliation(s)
- Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire, University of Montréal, Montreal, QC, Canada.
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Yun J, Huang Y, Miller ADC, Chang BL, Baldini L, Dhanabalan KM, Li E, Li H, Mukherjee A. Destabilized reporters for background-subtracted, chemically-gated, and multiplexed deep-tissue imaging. Chem Sci 2024; 15:11108-11121. [PMID: 39027298 PMCID: PMC11253201 DOI: 10.1039/d4sc00377b] [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: 01/16/2024] [Accepted: 05/23/2024] [Indexed: 07/20/2024] Open
Abstract
Tracking gene expression in deep tissues requires genetic reporters that can be unambiguously detected using tissue penetrant techniques. Magnetic resonance imaging (MRI) is uniquely suited for this purpose; however, there is a dearth of reporters that can be reliably linked to gene expression with minimal interference from background tissue signals. Here, we present a conceptually new method for generating background-subtracted, drug-gated, multiplex images of gene expression using MRI. Specifically, we engineered chemically erasable reporters consisting of a water channel, aquaporin-1, fused to destabilizing domains, which are stabilized by binding to cell-permeable small-molecule ligands. We showed that this approach allows for highly specific detection of gene expression through differential imaging. In addition, by engineering destabilized aquaporin-1 variants with orthogonal ligand requirements, it is possible to distinguish distinct subpopulations of cells in mixed cultures. Finally, we demonstrated this approach in a mouse tumor model through differential imaging of gene expression with minimal background.
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Affiliation(s)
- Jason Yun
- Department of Chemistry, University of California Santa Barbara CA 93106 USA
| | - Yimeng Huang
- Department of Chemistry, University of California Santa Barbara CA 93106 USA
| | - Austin D C Miller
- Biomolecular Science and Engineering Graduate Program, University of California Santa Barbara CA 93106 USA
| | - Brandon L Chang
- Department of Molecular, Cell, and Developmental Biology, University of California Santa Barbara CA 93106 USA
| | - Logan Baldini
- Department of Chemical Engineering, University of California Santa Barbara CA 93106 USA
| | - Kaamini M Dhanabalan
- Department of Chemical Engineering, University of California Santa Barbara CA 93106 USA
| | - Eugene Li
- Department of Chemical Engineering, University of California Santa Barbara CA 93106 USA
| | - Honghao Li
- Department of Chemistry, University of California Santa Barbara CA 93106 USA
| | - Arnab Mukherjee
- Department of Chemistry, University of California Santa Barbara CA 93106 USA
- Biomolecular Science and Engineering Graduate Program, University of California Santa Barbara CA 93106 USA
- Department of Chemical Engineering, University of California Santa Barbara CA 93106 USA
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Zheng Y, Zhou L, Huang W, Han N, Zhang J. Histogram analysis of multiple diffusion models for predicting advanced non-small cell lung cancer response to chemoimmunotherapy. Cancer Imaging 2024; 24:71. [PMID: 38863062 PMCID: PMC11167789 DOI: 10.1186/s40644-024-00713-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 05/28/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND There is an urgent need to find a reliable and effective imaging method to evaluate the therapeutic efficacy of immunochemotherapy in advanced non-small cell lung cancer (NSCLC). This study aimed to investigate the capability of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) histogram analysis based on different region of interest (ROI) selection methods for predicting treatment response to chemoimmunotherapy in advanced NSCLC. METHODS Seventy-two stage III or IV NSCLC patients who received chemoimmunotherapy were enrolled in this study. IVIM and DKI were performed before treatment. The patients were classified as responders group and non-responders group according to the Response Evaluation Criteria in Solid Tumors 1.1. The histogram parameters of ADC, Dslow, Dfast, f, Dk and K were measured using whole tumor volume ROI and single slice ROI analysis methods. Variables with statistical differences would be included in stepwise logistic regression analysis to determine independent parameters, by which the combined model was also established. And the receiver operating characteristic curve (ROC) were used to evaluate the prediction performance of histogram parameters and the combined model. RESULTS ADC, Dslow, Dk histogram metrics were significantly lower in the responders group than in the non-responders group, while the histogram parameters of f were significantly higher in the responders group than in the non-responders group (all P < 0.05). The mean value of each parameter was better than or equivalent to other histogram metrics, where the mean value of f obtained from whole tumor and single slice both had the highest AUC (AUC = 0.886 and 0.812, respectively) compared to other single parameters. The combined model improved the diagnostic efficiency with an AUC of 0.968 (whole tumor) and 0.893 (single slice), respectively. CONCLUSIONS Whole tumor volume ROI demonstrated better diagnostic ability than single slice ROI analysis, which indicated whole tumor histogram analysis of IVIM and DKI hold greater potential than single slice ROI analysis to be a promising tool of predicting therapeutic response to chemoimmunotherapy in advanced NSCLC at initial state.
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Affiliation(s)
- Yu Zheng
- Department of Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Liang Zhou
- Department of Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Wenjing Huang
- Department of Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Na Han
- Department of Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Jing Zhang
- Department of Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730030, China.
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China.
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10
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Ozawa Y, Nagata H, Ueda T, Oshima Y, Hamabuchi N, Yoshikawa T, Takenaka D, Ohno Y. Chest Magnetic Resonance Imaging: Advances and Clinical Care. Clin Chest Med 2024; 45:505-529. [PMID: 38816103 DOI: 10.1016/j.ccm.2024.02.017] [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] [Indexed: 06/01/2024]
Abstract
Many promising study results as well as technical advances for chest magnetic resonance imaging (MRI) have demonstrated its academic and clinical potentials during the last few decades, although chest MRI has been used for relatively few clinical situations in routine clinical practice. However, the Fleischner Society as well as the Japanese Society of Magnetic Resonance in Medicine have published a few white papers to promote chest MRI in routine clinical practice. In this review, we present clinical evidence of the efficacy of chest MRI for 1) thoracic oncology and 2) pulmonary vascular diseases.
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Affiliation(s)
- Yoshiyuki Ozawa
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Takahiro Ueda
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Yuka Oshima
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Nayu Hamabuchi
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Takeshi Yoshikawa
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Hyogo, Japan
| | - Daisuke Takenaka
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan; Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Hyogo, Japan
| | - Yoshiharu Ohno
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan; Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
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11
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Wang L, Wang X, Jiang F, Cao Y, Liu S, Chen H, Yang J, Zhang X, Yu T, Xu H, Lin M, Wu Y, Zhang J. Adding quantitative T1rho-weighted imaging to conventional MRI improves specificity and sensitivity for differentiating malignant from benign breast lesions. Magn Reson Imaging 2024; 108:98-103. [PMID: 38331054 DOI: 10.1016/j.mri.2024.02.005] [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: 06/13/2023] [Revised: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 02/10/2024]
Abstract
OBJECTIVES To investigate the feasibility of T1rho-weighted imaging in differentiating malignant from benign breast lesions and to explore the additional value of T1rho to conventional MRI. MATERIALS AND METHODS We prospectively enrolled consecutive women with breast lesions who underwent preoperative T1rho-weighted imaging, diffusion-weighted imaging, and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) between November 2021 and July 2023. The T1rho, apparent diffusion coefficient (ADC), and semi-quantitative parameters from DCE-MRI were obtained and compared between benign and malignant groups. The diagnostic performance was analyzed and compared using receiver operating characteristic (ROC) curves and the Delong Test. RESULTS This study included 113 patients (74 malignant and 39 benign lesions). The mean T1rho value in the benign group (92.61 ± 22.10 ms) was significantly higher than that in the malignant group (72.18 ± 16.37 ms) (P < 0.001). The ADC value and time to peak (TTP) value in the malignant group (1.13 ± 0.45 and 269.06 ± 106.01, respectively) were lower than those in the benign group (1.57 ± 0.45 and 388.30 ± 81.13, respectively) (all P < 0.001). T1rho combined with ADC and TTP showed good diagnostic performance with an area under the curve (AUC) of 0.896, a sensitivity of 81.0%, and a specificity of 87.1%. The specificity and sensitivity of the combination of T1rho, ADC, and TTP were significantly higher than those of the combination of ADC and TTP (87.1% vs. 84.6%, P < 0.005; 81.0% vs. 77.0%, P < 0.001). CONCLUSION T1rho-weighted imaging was a feasible MRI sequence for differentiating malignant from benign breast lesions. The combination of T1rho, ADC and TTP could achieve a favorable diagnostic performance with improved specificity and sensitivity, T1rho could serve as a supplementary approach to conventional MRI.
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Affiliation(s)
- Lu Wang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Xiaoxia Wang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Fujie Jiang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Ying Cao
- School of Medicine, Chongqing University, Chongqing 400030, China
| | - Shuling Liu
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Huifang Chen
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Jing Yang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | | | - Tao Yu
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Hanshan Xu
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Meng Lin
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Yongzhong Wu
- Radiation Oncology Center, Chongqing University, Chongqing 400030, China
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China.
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12
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Lu T, Li M, Wang Y, Li H, Wu M, Wang G. Standard diffusion-weighted, diffusion kurtosis and intravoxel incoherent motion in differentiating invasive placentas. Arch Gynecol Obstet 2024; 309:503-514. [PMID: 36790463 DOI: 10.1007/s00404-023-06947-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 01/20/2023] [Indexed: 02/16/2023]
Abstract
PURPOSE To investigate the diagnostic value of monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in distinguishing invasive placentas. METHODS A total of 53 patients with invasive placentas and 47 patients with noninvasive placentas undergoing conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) were retrospectively enrolled. The mean, minimum, and maximum parameters including the apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard DWI, diffusion kurtosis (MK), and diffusion coefficient (MD) from DKI and pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from IVIM were measured and compared from the volumetric analysis. Receiver operating characteristics (ROC) curve and logistic regression analyses were conducted to evaluate the diagnostic efficiency of different diffusion parameters for distinguishing invasive placentas. RESULTS Comparisons between accreta lesions in patients with invasive placentas (AL) and lower 1/3 part of the placenta in patients with noninvasive placentas (LP) demonstrated that MD mean, D mean, and D* mean were significantly lower while ADC max and D max were significantly higher in invasive placentas (all p < 0.05). Multivariate analysis demonstrated that D mean, D max and D* mean differed significantly among all the studied parameters for invasive placentas. A combined use of these three parameters yielded an AUC of 0.86 with sensitivity, specificity, and accuracy of 84.91%, 76.60%, and 80%, respectively. CONCLUSION The combined use of different IVIM parameters is helpful in distinguishing invasive placentas.
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Affiliation(s)
- Tao Lu
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Mou Li
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Yishuang Wang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Hang Li
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Mingpeng Wu
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Guotai Wang
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, West Hi-tech Zone, Chengdu, 611731, China.
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13
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Burzynska AZ, Anderson C, Arciniegas DB, Calhoun V, Choi IY, Mendez Colmenares A, Kramer AF, Li K, Lee J, Lee P, Thomas ML. Correlates of axonal content in healthy adult span: Age, sex, myelin, and metabolic health. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2024; 6:100203. [PMID: 38292016 PMCID: PMC10827486 DOI: 10.1016/j.cccb.2024.100203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 02/01/2024]
Abstract
As the emerging treatments that target grey matter pathology in Alzheimer's Disease have limited effectiveness, there is a critical need to identify new neural targets for treatments. White matter's (WM) metabolic vulnerability makes it a promising candidate for new interventions. This study examined the age and sex differences in estimates of axonal content, as well the associations of with highly prevalent modifiable health risk factors such as metabolic syndrome and adiposity. We estimated intra-axonal volume fraction (ICVF) using the Neurite Orientation Dispersion and Density Imaging (NODDI) in a sample of 89 cognitively and neurologically healthy adults (20-79 years). We showed that ICVF correlated positively with age and estimates of myelin content. The ICVF was also lower in women than men, across all ages, which difference was accounted for by intracranial volume. Finally, we found no association of metabolic risk or adiposity scores with the current estimates of ICVF. In addition, the previously observed adiposity-myelin associations (Burzynska et al., 2023) were independent of ICVF. Although our findings confirm the vulnerability of axons to aging, they suggest that metabolic dysfunction may selectively affect myelin content, at least in cognitively and neurologically healthy adults with low metabolic risk, and when using the specific MRI techniques. Future studies need to revisit our findings using larger samples and different MRI approaches, and identify modifiable factors that accelerate axonal deterioration as well as mechanisms linking peripheral metabolism with the health of myelin.
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Affiliation(s)
- Agnieszka Z Burzynska
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, CO, USA
| | - Charles Anderson
- Department of Computer Science, Colorado State University, Fort Collins, CO, USA
| | - David B. Arciniegas
- Marcus Institute for Brain Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - In-Young Choi
- Department of Neurology, Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Andrea Mendez Colmenares
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, CO, USA
| | - Arthur F Kramer
- Beckman Institute for Advanced Science and Technology at the University of Illinois, IL, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA, USA
| | - Kaigang Li
- Department of Health and Exercise Science, Colorado State University, Fort Collins, CO, USA
| | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Michael L Thomas
- Department of Psychology, Colorado State University, Fort Collins, CO, USA
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Zheng L, Jiang P, Lin D, Chen X, Zhong T, Zhang R, Chen J, Song Y, Xue Y, Lin L. Histogram analysis of mono-exponential, bi-exponential and stretched-exponential diffusion-weighted MR imaging in predicting consistency of meningiomas. Cancer Imaging 2023; 23:117. [PMID: 38053183 DOI: 10.1186/s40644-023-00633-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 11/03/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND The consistency of meningiomas is critical to determine surgical planning and has a significant impact on surgical outcomes. Our aim was to compare mono-exponential, bi-exponential and stretched exponential MR diffusion-weighted imaging in predicting the consistency of meningiomas before surgery. METHODS Forty-seven consecutive patients with pathologically confirmed meningiomas were prospectively enrolled in this study. Two senior neurosurgeons independently evaluated tumour consistency and classified them into soft and hard groups. A volume of interest was placed on the preoperative MR diffusion images to outline the whole tumour area. Histogram parameters (mean, median, 10th percentile, 90th percentile, kurtosis, skewness) were extracted from 6 different diffusion maps including ADC (DWI), D*, D, f (IVIM), alpha and DDC (SEM). Comparisons between two groups were made using Student's t-Test or Mann-Whitney U test. Parameters with significant differences between the two groups were included for Receiver operating characteristic analysis. The DeLong test was used to compare AUCs. RESULTS DDC, D* and ADC 10th percentile were significantly lower in hard tumours than in soft tumours (P ≤ 0.05). The alpha 90th percentile was significantly higher in hard tumours than in soft tumours (P < 0.02). For all histogram parameters, the alpha 90th percentile yielded the highest AUC of 0.88, with an accuracy of 85.10%. The D* 10th percentile had a relatively higher AUC value, followed by the DDC and ADC 10th percentile. The alpha 90th percentile had a significantly greater AUC value than the ADC 10th percentile (P ≤ 0.05). The D* 10th percentile had a significantly greater AUC value than the ADC 10th percentile and DDC 10th percentile (P ≤ 0.03). CONCLUSION Histogram parameters of Alpha and D* may serve as better imaging biomarkers to aid in predicting the consistency of meningioma.
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Affiliation(s)
- Lingmin Zheng
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Peirong Jiang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Danjie Lin
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Xiaodan Chen
- Department of Radiology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Tianjin Zhong
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Rufei Zhang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Jing Chen
- Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Yang Song
- MR Scientific Marketing, Healthineers Ltd, Siemens, Shanghai, China
| | - Yunjing Xue
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
| | - Lin Lin
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
- School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, 350004, China.
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15
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Stephens JA, Hernandez-Sarabia JA, Sharp JL, Leach HJ, Bell C, Thomas ML, Buryznska AZ, Weaver JA, Schmid AA. Adaptive yoga versus low-impact exercise for adults with chronic acquired brain injury: a pilot randomized control trial protocol. Front Hum Neurosci 2023; 17:1291094. [PMID: 38077184 PMCID: PMC10701427 DOI: 10.3389/fnhum.2023.1291094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/27/2023] [Indexed: 02/12/2024] Open
Abstract
Background Each year, millions of Americans sustain acquired brain injuries (ABI) which result in functional impairments, such as poor balance and autonomic nervous system (ANS) dysfunction. Although significant time and energy are dedicated to reducing functional impairment in acute phase of ABI, many individuals with chronic ABI have residual impairments that increase fall risk, decrease quality of life, and increase mortality. In previous work, we have found that yoga can improve balance in adults with chronic (i.e., ≥6 months post-injury) ABI. Moreover, yoga has been shown to improve ANS and brain function in healthy adults. Thus, adults with chronic ABI may show similar outcomes. This protocol details the methods used to examine the effects of a group yoga program, as compared to a group low-impact exercise, on primary and secondary outcomes in adults with chronic ABI. Methods This study is a single-blind randomized controlled trial comparing group yoga to group low-impact exercise. Participants must be ≥18 years old with chronic ABI and moderate balance impairments. Group yoga and group exercise sessions occur twice a week for 1 h for 8 weeks. Sessions are led by trained adaptive exercise specialists. Primary outcomes are balance and ANS function. Secondary outcomes are brain function and structure, cognition, quality of life, and qualitative experiences. Data analysis for primary and most secondary outcomes will be completed with mixed effect statistical methods to evaluate the within-subject factor of time (i.e., pre vs. post intervention), the between-subject factor of group (yoga vs. low-impact exercise), and interaction effects. Deductive and inductive techniques will be used to analyze qualitative data. Discussion Due to its accessibility and holistic nature, yoga has significant potential for improving balance and ANS function, along with other capacities, in adults with chronic ABI. Because there are also known benefits of exercise and group interaction, this study compares yoga to a similar, group exercise intervention to explore if yoga has a unique benefit for adults with chronic ABI.Clinical trial registration:ClinicalTrials.gov, NCT05793827. Registered on March 31, 2023.
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Affiliation(s)
- Jaclyn A. Stephens
- Department of Occupational Therapy, Colorado State University, Fort Collins, CO, United States
- Molecular Cellular and Integrative Neuroscience Program, Colorado State University, Fort Collins, CO, United States
- Sharp Analytics, LCC, Fort Collins, CO, United States
| | | | - Julia L. Sharp
- Department of Health and Exercise Science, Colorado State University, Fort Collins, CO, United States
| | | | | | - Michael L. Thomas
- Molecular Cellular and Integrative Neuroscience Program, Colorado State University, Fort Collins, CO, United States
- Department of Psychology, Colorado State University, Fort Collins, CO, United States
| | - Agnieszka Z. Buryznska
- Molecular Cellular and Integrative Neuroscience Program, Colorado State University, Fort Collins, CO, United States
- Department of Human Development and Family Studies, Colorado State University, Fort Collins, CO, United States
| | - Jennifer A. Weaver
- Department of Occupational Therapy, Colorado State University, Fort Collins, CO, United States
| | - Arlene A. Schmid
- Department of Occupational Therapy, Colorado State University, Fort Collins, CO, United States
- Center for Healthy Aging, Fort Collins, CO, United States
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Chowdhury R, Wan J, Gardier R, Rafael-Patino J, Thiran JP, Gibou F, Mukherjee A. Molecular Imaging with Aquaporin-Based Reporter Genes: Quantitative Considerations from Monte Carlo Diffusion Simulations. ACS Synth Biol 2023; 12:3041-3049. [PMID: 37793076 DOI: 10.1021/acssynbio.3c00372] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
Aquaporins provide a unique approach for imaging genetic activity in deep tissues by increasing the rate of cellular water diffusion, which generates a magnetic resonance contrast. However, distinguishing aquaporin signals from the tissue background is challenging because water diffusion is influenced by structural factors, such as cell size and packing density. Here, we developed a Monte Carlo model to analyze how cell radius and intracellular volume fraction quantitatively affect aquaporin signals. We demonstrated that a differential imaging approach based on subtracting signals at two diffusion times can improve specificity by unambiguously isolating aquaporin signals from the tissue background. We further used Monte Carlo simulations to analyze the connection between diffusivity and the percentage of cells engineered to express aquaporin and established a mapping that accurately determined the volume fraction of aquaporin-expressing cells in mixed populations. The quantitative framework developed in this study will enable a broad range of applications in biomedical synthetic biology, requiring the use of aquaporins to noninvasively monitor the location and function of genetically engineered devices in live animals.
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Affiliation(s)
| | | | - Remy Gardier
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Jonathan Rafael-Patino
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
- Radiology Department, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), 1005 Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
- Radiology Department, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), 1005 Lausanne, Switzerland
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Parker DM, Adams JN, Kim S, McMillan L, Yassa MA. NODDI-derived measures of microstructural integrity in medial temporal lobe white matter pathways are associated with Alzheimer's disease pathology and cognitive outcomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.11.561946. [PMID: 37905117 PMCID: PMC10614746 DOI: 10.1101/2023.10.11.561946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
INTRODUCTION Diffusion tensor imaging has been used to assess white matter (WM) changes in the early stages of Alzheimer's disease (AD). However, the tensor model is necessarily limited by its assumptions. Neurite Orientation Dispersion and Density Imaging (NODDI) can offer insights into microstructural features of WM change. We assessed whether NODDI more sensitively detects AD-related changes in medial temporal lobe WM than traditional tensor metrics. METHODS Standard diffusion and NODDI metrics were calculated for medial temporal WM tracts from 199 older adults drawn from ADNI3 who also received PET to measure pathology and neuropsychological testing. RESULTS NODDI measures in medial temporal tracts were more strongly correlated to cognitive performance and pathology than standard measures. The combination of NODDI and standard metrics exhibited the strongest prediction of cognitive performance in random forest analyses. CONCLUSIONS NODDI metrics offer additional insights into contributions of WM degeneration to cognitive outcomes in the aging brain.
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Affiliation(s)
- Dana M. Parker
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and Memory, University of California, Irvine
| | - Jenna N. Adams
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and Memory, University of California, Irvine
| | - Soyun Kim
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and Memory, University of California, Irvine
| | - Liv McMillan
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and Memory, University of California, Irvine
| | - Michael A. Yassa
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and Memory, University of California, Irvine
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Fang S, Yang Y, Tao J, Yin Z, Liu Y, Duan Z, Liu W, Wang S. Intratumoral Heterogeneity of Fibrosarcoma Xenograft Models: Whole-Tumor Histogram Analysis of DWI and IVIM. Acad Radiol 2023; 30:2299-2308. [PMID: 36481126 DOI: 10.1016/j.acra.2022.11.016] [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: 07/27/2022] [Revised: 11/08/2022] [Accepted: 11/14/2022] [Indexed: 12/12/2022]
Abstract
RATIONAL AND OBJECTIVE To explore the correlations of histogram parameters from diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) with the heterogeneous features in a nude mouse model of fibrosarcoma. MATERIALS AND METHODS A total of 44 fibrosarcoma xenograft models were established by inoculating HT-1080 cells on the right thigh of mice and subjected tumors to DWI and IVIM imaging with 3.0 T MRI. Whole-tumor histogram parameters were calculated on apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f). Heterogeneous features, including necrosis rate, cell density, Ki-67 labeling index (LI), and microvascular density (MVD) were measured. Intraclass correlation coefficients (ICC), Pearson or Spearman correlation tests, and receiver operating characteristics (ROC) were performed. RESULTS The 90th percentile, skewness and kurtosis of ADC and D histograms showed correlations with necrosis rate, and the highest correlation coefficient was found for D90th (r = 0.485). ADC and D histogram parameters showed correlations with cell density and Ki-67 LI; D90th showed the highest correlation coefficient with cell density (r = -0.504); and Dmedian showed the most significant correlation with Ki-67 LI (r = -0.525). D*skewness, D*kurtosis, D*90th, fmean, and fmedian showed correlations with MVD. ADC90th, ADCskewness, ADCkurtosis, D90th, and Dskewness showed significant differences between the low necrosis and high necrosis groups, and the combination model showed the best diagnostic ability (AUC = 0.882), with 97% sensitivity, and 72.7% specificity. CONCLUSION Whole-tumor histogram parameters of DWI and IVIM were correlated with heterogeneous features in nude murine models of fibrosarcoma.
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Affiliation(s)
- Shaobo Fang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Yanyu Yang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Juan Tao
- Department of Pathology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Zhenzhen Yin
- Department of Radiology, Suzhou Hospital of Anhui Medical University, Anhui, China
| | - Yajie Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Zhiqing Duan
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Wenyu Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China.
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Liao D, Liu YC, Liu JY, Wang D, Liu XF. Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study. BMC Med Imaging 2023; 23:119. [PMID: 37697237 PMCID: PMC10494379 DOI: 10.1186/s12880-023-01082-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 08/19/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging models in differentiating tumour progression from pseudoprogression in glioblastoma patients. METHODS Forty patients with pathologically confirmed glioblastoma exhibiting enhancing lesions after completion of chemoradiation therapy were enrolled in the study, which were then classified as tumour progression and pseudoprogression. All patients underwent conventional and multi-b diffusion-weighted MRI. The apparent diffusion coefficient (ADC) from a monoexponential model, the true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) from a biexponential model, and the distributed diffusion coefficient (DDC) and intravoxel heterogeneity index (α) from a stretched-exponential model were compared between tumour progression and pseudoprogression groups. Receiver operating characteristic curves (ROC) analysis was used to investigate the diagnostic performance of different DWI parameters. Interclass correlation coefficient (ICC) was used to evaluate the consistency of measurements. RESULTS The values of ADC, D, DDC, and α values were lower in tumour progression patients than that in pseudoprogression patients (p < 0.05). The values of D* and f were higher in tumour progression patients than that in pseudoprogression patients (p < 0.05). Diagnostic accuracy for differentiating tumour progression from pseudoprogression was highest for α(AUC = 0.94) than that for ADC (AUC = 0.91), D (AUC = 0.92), D* (AUC = 0.81), f (AUC = 0.75), and DDC (AUC = 0.88). CONCLUSIONS Multi-b DWI is a promising method for differentiating tumour progression from pseudoprogression with high diagnostic accuracy. In addition, the α derived from stretched-exponential model is the most promising DWI parameter for the prediction of tumour progression in glioblastoma patients.
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Affiliation(s)
- Dan Liao
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, 100010 China
| | - Yuan-Cheng Liu
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
| | - Jiang-Yong Liu
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
| | - Di Wang
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
| | - Xin-Feng Liu
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
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Villarreal-Haro JL, Gardier R, Canales-Rodríguez EJ, Fischi-Gomez E, Girard G, Thiran JP, Rafael-Patiño J. CACTUS: a computational framework for generating realistic white matter microstructure substrates. Front Neuroinform 2023; 17:1208073. [PMID: 37603781 PMCID: PMC10434236 DOI: 10.3389/fninf.2023.1208073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 07/13/2023] [Indexed: 08/23/2023] Open
Abstract
Monte-Carlo diffusion simulations are a powerful tool for validating tissue microstructure models by generating synthetic diffusion-weighted magnetic resonance images (DW-MRI) in controlled environments. This is fundamental for understanding the link between micrometre-scale tissue properties and DW-MRI signals measured at the millimetre-scale, optimizing acquisition protocols to target microstructure properties of interest, and exploring the robustness and accuracy of estimation methods. However, accurate simulations require substrates that reflect the main microstructural features of the studied tissue. To address this challenge, we introduce a novel computational workflow, CACTUS (Computational Axonal Configurator for Tailored and Ultradense Substrates), for generating synthetic white matter substrates. Our approach allows constructing substrates with higher packing density than existing methods, up to 95% intra-axonal volume fraction, and larger voxel sizes of up to 500μm3 with rich fibre complexity. CACTUS generates bundles with angular dispersion, bundle crossings, and variations along the fibres of their inner and outer radii and g-ratio. We achieve this by introducing a novel global cost function and a fibre radial growth approach that allows substrates to match predefined targeted characteristics and mirror those reported in histological studies. CACTUS improves the development of complex synthetic substrates, paving the way for future applications in microstructure imaging.
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Affiliation(s)
- Juan Luis Villarreal-Haro
- Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland
| | - Remy Gardier
- Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland
| | - Erick J. Canales-Rodríguez
- Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland
| | - Elda Fischi-Gomez
- Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Radiology Department, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Gabriel Girard
- Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Radiology Department, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Department of Computer Science, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Radiology Department, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Jonathan Rafael-Patiño
- Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland
- Radiology Department, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
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21
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Chakhoyan A, Shkrkova K, Sizdahkhani S, Huuskonen MT, Lamorie-Foote K, Diaz A, Chen S, Liu Q, D'Agostino C, Zhang H, Mack WJ, Sioutas C, Finch CE, Zlokovic B, Mack WJ. Magnetic resonance imaging of white matter response to diesel exhaust particles. RESEARCH SQUARE 2023:rs.3.rs-3087503. [PMID: 37503159 PMCID: PMC10371072 DOI: 10.21203/rs.3.rs-3087503/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Air pollution is associated with risks of dementia and accelerated cognitive decline. Rodent air pollution models have shown white matter vulnerability. This study uses diffusion tensor imaging (DTI) to quantify changes to white matter microstructure and tractography in multiple myelinated regions after exposure to diesel exhaust particulate (DEP). Adult C57BL/6 male mice were exposed to re-aerosolized DEP (NIST SRM 2975) at a concentration of 100 ug/m3 for 200 hours. Ex-vivo MRI analysis and fractional anisotropy (FA)-aided white matter tractography were conducted to study the effect of DEP exposure on the brain white matter tracts. Immunohistochemistry was used to assess myelin and axonal structure. DEP exposure for 8 weeks altered myelin composition in multiple regions. Diffusion tensor imaging (DTI) showed decreased FA in the corpus callosum (30%), external capsule (15%), internal capsule (15%), and cingulum (31 %). Separate immunohistochemistry analyses confirmed prior findings. Myelin basic protein (MBP) was decreased (corpus callosum: 28%, external capsule: 29%), and degraded MPB increased (corpus callosum: 32%, external capsule: 53%) in the DEP group. White matter is highly susceptible to chronic DEP exposure. This study demonstrates the utility of DTI as a neuroanatomical tool in the context of air pollution and white matter myelin vulnerability.
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Affiliation(s)
- Ararat Chakhoyan
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Kristina Shkrkova
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Saman Sizdahkhani
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Mikko T Huuskonen
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Krista Lamorie-Foote
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Arnold Diaz
- Leonard Davis School of Gerontology, University of Southern California
| | - Selena Chen
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Qinghai Liu
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Carla D'Agostino
- Leonard Davis School of Gerontology, University of Southern California
| | - Hongqiao Zhang
- Leonard Davis School of Gerontology, University of Southern California
| | - Wendy J Mack
- Department of Population and Public Health Sciences, Keck School of Medicine
| | | | - Caleb E Finch
- Leonard Davis School of Gerontology, University of Southern California
| | - Berislav Zlokovic
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - William J Mack
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
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22
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Chowdhury R, Wan J, Gardier R, Rafael-Patino J, Thiran JP, Gibou F, Mukherjee A. Molecular imaging with aquaporin-based reporter genes: quantitative considerations from Monte Carlo diffusion simulations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.09.544324. [PMID: 37333205 PMCID: PMC10274877 DOI: 10.1101/2023.06.09.544324] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Aquaporins provide a new class of genetic tools for imaging molecular activity in deep tissues by increasing the rate of cellular water diffusion, which generates magnetic resonance contrast. However, distinguishing aquaporin contrast from the tissue background is challenging because water diffusion is also influenced by structural factors such as cell size and packing density. Here, we developed and experimentally validated a Monte Carlo model to analyze how cell radius and intracellular volume fraction quantitatively affect aquaporin signals. We demonstrated that a differential imaging approach based on time-dependent changes in diffusivity can improve specificity by unambiguously isolating aquaporin-driven contrast from the tissue background. Finally, we used Monte Carlo simulations to analyze the connection between diffusivity and the percentage of cells engineered to express aquaporin, and established a simple mapping that accurately determined the volume fraction of aquaporin-expressing cells in mixed populations. This study creates a framework for broad applications of aquaporins, particularly in biomedicine and in vivo synthetic biology, where quantitative methods to measure the location and performance of genetic devices in whole vertebrates are necessary.
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Affiliation(s)
- Rochishnu Chowdhury
- Department of Mechanical Engineering, University of California, Santa Barbara, CA 93106, USA
| | - Jinyang Wan
- Department of Chemistry, University of California, Santa Barbara, CA 93106, USA
| | - Remy Gardier
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jonathan Rafael-Patino
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Radiology Department, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Radiology Department, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Frederic Gibou
- Department of Mechanical Engineering, University of California, Santa Barbara, CA 93106, USA
- Department of Computer Science, University of California, Santa Barbara, CA 93106, USA
| | - Arnab Mukherjee
- Department of Chemistry, University of California, Santa Barbara, CA 93106, USA
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA
- Biomolecular Science and Engineering, University of California, Santa Barbara, CA 93106, USA
- Biological Engineering, University of California, Santa Barbara, CA 93106, USA
- Neuroscience Research Institute, University of California, Santa Barbara, CA 93106, USA
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23
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Yun J, Baldini L, Huang Y, Li E, Li H, Chacko AN, Miller AD, Wan J, Mukherjee A. Engineering ligand stabilized aquaporin reporters for magnetic resonance imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.02.543364. [PMID: 37333371 PMCID: PMC10274688 DOI: 10.1101/2023.06.02.543364] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Imaging transgene expression in live tissues requires reporters that are detectable with deeply penetrant modalities, such as magnetic resonance imaging (MRI). Here, we show that LSAqp1, a water channel engineered from aquaporin-1, can be used to create background-free, drug-gated, and multiplex images of gene expression using MRI. LSAqp1 is a fusion protein composed of aquaporin-1 and a degradation tag that is sensitive to a cell-permeable ligand, which allows for dynamic small molecule modulation of MRI signals. LSAqp1 improves specificity for imaging gene expression by allowing reporter signals to be conditionally activated and distinguished from the tissue background by difference imaging. In addition, by engineering destabilized aquaporin-1 variants with different ligand requirements, it is possible to image distinct cell types simultaneously. Finally, we expressed LSAqp1 in a tumor model and showed successful in vivo imaging of gene expression without background activity. LSAqp1 provides a conceptually unique approach to accurately measure gene expression in living organisms by combining the physics of water diffusion and biotechnology tools to control protein stability.
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Affiliation(s)
- Jason Yun
- Department of Chemistry, University of California, Santa Barbara, CA 93106, USA
| | - Logan Baldini
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA
| | - Yimeng Huang
- Department of Chemistry, University of California, Santa Barbara, CA 93106, USA
| | - Eugene Li
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA
| | - Honghao Li
- Department of Chemistry, University of California, Santa Barbara, CA 93106, USA
| | - Asish N. Chacko
- Department of Chemistry, University of California, Santa Barbara, CA 93106, USA
| | - Austin D.C. Miller
- Biomolecular Science and Engineering, University of California, Santa Barbara, CA 93106, USA
| | - Jinyang Wan
- Department of Chemistry, University of California, Santa Barbara, CA 93106, USA
| | - Arnab Mukherjee
- Department of Chemistry, University of California, Santa Barbara, CA 93106, USA
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA
- Biomolecular Science and Engineering, University of California, Santa Barbara, CA 93106, USA
- Biological Engineering, University of California, Santa Barbara, CA 93106, USA
- Neuroscience Research Institute, University of California, Santa Barbara, CA 93106, USA
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24
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Pan Z, Ma X, Dai E, Auerbach EJ, Guo H, Uğurbil K, Wu X. Reconstruction for 7T high-resolution whole-brain diffusion MRI using two-stage N/2 ghost correction and L1-SPIRiT without single-band reference. Magn Reson Med 2023; 89:1915-1930. [PMID: 36594439 PMCID: PMC9992311 DOI: 10.1002/mrm.29573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 11/28/2022] [Accepted: 12/19/2022] [Indexed: 01/04/2023]
Abstract
PURPOSE To combine a new two-stage N/2 ghost correction and an adapted L1-SPIRiT method for reconstruction of 7T highly accelerated whole-brain diffusion MRI (dMRI) using only autocalibration scans (ACS) without the need of additional single-band reference (SBref) scans. METHODS The proposed ghost correction consisted of a 3-line reference approach in stage 1 and the reference-free entropy method in stage 2. The adapted L1-SPIRiT method was formulated within the 3D k-space framework. Its efficacy was examined by acquiring two dMRI data sets at 1.05-mm isotropic resolutions with a total acceleration of 6 or 9 (i.e., 2-fold or 3-fold slice and 3-fold in-plane acceleration). Diffusion analysis was performed to derive DTI metrics and estimate fiber orientation distribution functions (fODFs). The results were compared with those of 3D k-space GRAPPA using only ACS, all in reference to 3D k-space GRAPPA using both ACS and SBref (serving as a reference). RESULTS The proposed ghost correction eliminated artifacts more robustly than conventional approaches. Our adapted L1-SPIRiT method outperformed 3D k-space GRAPPA when using only ACS, improving image quality to what was achievable with 3D k-space GRAPPA using both ACS and SBref scans. The improvement in image quality further resulted in an improvement in estimation performances for DTI and fODFs. CONCLUSION The combination of our new ghost correction and adapted L1-SPIRiT method can reliably reconstruct 7T highly accelerated whole-brain dMRI without the need of SBref scans, increasing acquisition efficiency and reducing motion sensitivity.
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Affiliation(s)
- Ziyi Pan
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiaodong Ma
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Erpeng Dai
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Edward J. Auerbach
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Xiaoping Wu
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
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25
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Paudyal R, Shah AD, Akin O, Do RKG, Konar AS, Hatzoglou V, Mahmood U, Lee N, Wong RJ, Banerjee S, Shin J, Veeraraghavan H, Shukla-Dave A. Artificial Intelligence in CT and MR Imaging for Oncological Applications. Cancers (Basel) 2023; 15:cancers15092573. [PMID: 37174039 PMCID: PMC10177423 DOI: 10.3390/cancers15092573] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 04/13/2023] [Accepted: 04/17/2023] [Indexed: 05/15/2023] Open
Abstract
Cancer care increasingly relies on imaging for patient management. The two most common cross-sectional imaging modalities in oncology are computed tomography (CT) and magnetic resonance imaging (MRI), which provide high-resolution anatomic and physiological imaging. Herewith is a summary of recent applications of rapidly advancing artificial intelligence (AI) in CT and MRI oncological imaging that addresses the benefits and challenges of the resultant opportunities with examples. Major challenges remain, such as how best to integrate AI developments into clinical radiology practice, the vigorous assessment of quantitative CT and MR imaging data accuracy, and reliability for clinical utility and research integrity in oncology. Such challenges necessitate an evaluation of the robustness of imaging biomarkers to be included in AI developments, a culture of data sharing, and the cooperation of knowledgeable academics with vendor scientists and companies operating in radiology and oncology fields. Herein, we will illustrate a few challenges and solutions of these efforts using novel methods for synthesizing different contrast modality images, auto-segmentation, and image reconstruction with examples from lung CT as well as abdome, pelvis, and head and neck MRI. The imaging community must embrace the need for quantitative CT and MRI metrics beyond lesion size measurement. AI methods for the extraction and longitudinal tracking of imaging metrics from registered lesions and understanding the tumor environment will be invaluable for interpreting disease status and treatment efficacy. This is an exciting time to work together to move the imaging field forward with narrow AI-specific tasks. New AI developments using CT and MRI datasets will be used to improve the personalized management of cancer patients.
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Affiliation(s)
- Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | - Akash D Shah
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | - Oguz Akin
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | - Richard K G Do
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | - Amaresha Shridhar Konar
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | - Usman Mahmood
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | - Nancy Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | - Richard J Wong
- Head and Neck Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | | | | | - Harini Veeraraghavan
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, USA
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26
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Wichtmann BD, Fan Q, Eskandarian L, Witzel T, Attenberger UI, Pieper CC, Schad L, Rosen BR, Wald LL, Huang SY, Nummenmaa A. Linear multi-scale modeling of diffusion MRI data: A framework for characterization of oriented structures across length scales. Hum Brain Mapp 2023; 44:1496-1514. [PMID: 36477997 PMCID: PMC9921225 DOI: 10.1002/hbm.26143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 10/07/2022] [Accepted: 10/23/2022] [Indexed: 12/12/2022] Open
Abstract
Diffusion-weighted magnetic resonance imaging (DW-MRI) has evolved to provide increasingly sophisticated investigations of the human brain's structural connectome in vivo. Restriction spectrum imaging (RSI) is a method that reconstructs the orientation distribution of diffusion within tissues over a range of length scales. In its original formulation, RSI represented the signal as consisting of a spectrum of Gaussian diffusion response functions. Recent technological advances have enabled the use of ultra-high b-values on human MRI scanners, providing higher sensitivity to intracellular water diffusion in the living human brain. To capture the complex diffusion time dependence of the signal within restricted water compartments, we expand upon the RSI approach to represent restricted water compartments with non-Gaussian response functions, in an extended analysis framework called linear multi-scale modeling (LMM). The LMM approach is designed to resolve length scale and orientation-specific information with greater specificity to tissue microstructure in the restricted and hindered compartments, while retaining the advantages of the RSI approach in its implementation as a linear inverse problem. Using multi-shell, multi-diffusion time DW-MRI data acquired with a state-of-the-art 3 T MRI scanner equipped with 300 mT/m gradients, we demonstrate the ability of the LMM approach to distinguish different anatomical structures in the human brain and the potential to advance mapping of the human connectome through joint estimation of the fiber orientation distributions and compartment size characteristics.
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Affiliation(s)
- Barbara D. Wichtmann
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalCharlestownMassachusettsUSA
- Department of Diagnostic and Interventional RadiologyUniversity Hospital BonnBonnGermany
| | - Qiuyun Fan
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalCharlestownMassachusettsUSA
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics EngineeringTianjin UniversityTianjinChina
| | - Laleh Eskandarian
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalCharlestownMassachusettsUSA
| | | | - Ulrike I. Attenberger
- Department of Diagnostic and Interventional RadiologyUniversity Hospital BonnBonnGermany
| | - Claus C. Pieper
- Department of Diagnostic and Interventional RadiologyUniversity Hospital BonnBonnGermany
| | - Lothar Schad
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty MannheimHeidelberg UniversityMannheimGermany
| | - Bruce R. Rosen
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalCharlestownMassachusettsUSA
| | - Lawrence L. Wald
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalCharlestownMassachusettsUSA
- Harvard‐MIT Division of Health Sciences and TechnologyMassachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | - Susie Y. Huang
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalCharlestownMassachusettsUSA
- Harvard‐MIT Division of Health Sciences and TechnologyMassachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | - Aapo Nummenmaa
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalCharlestownMassachusettsUSA
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27
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Ferizi U, Müller-Oehring EM, Peterson ET, Pohl KM. The distortions of the free water model for diffusion MRI data when assuming single compartment relaxometry and proton density. Phys Med Biol 2023; 68:10.1088/1361-6560/acb30b. [PMID: 36638532 PMCID: PMC10100575 DOI: 10.1088/1361-6560/acb30b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 01/13/2023] [Indexed: 01/15/2023]
Abstract
Objective.To document the bias of thesimplifiedfree water model of diffusion MRI (dMRI) signal vis-à-vis aspecificmodel which, in addition to diffusion, incorporates compartment-specific proton density (PD), T1 recovery during repetition time (TR), and T2 decay during echo time (TE).Approach.Both models assume that volume fractionfof the total signal in any voxel arises from the free water compartment (fw) such as cerebrospinal fluid or edema, and the remainder (1-f) from hindered water (hw) which is constrained by cellular structures such as white matter (WM). Thespecificandsimplifiedmodels are compared on a synthetic dataset, using a range of PD, T1 and T2 values. We then fit the models to anin vivohealthy brain dMRI dataset. For bothsyntheticandin vivodata we use experimentally feasible TR, TE, signal-to-noise ratio (SNR) and physiologically plausible diffusion profiles.Main results.From the simulations we see that the difference between the estimatedsimplified fandspecific fis largest for mid-range ground-truthf, and it increases as SNR increases. The estimation of volume fractionfis sensitive to the choice of model,simplifiedorspecific, but the estimated diffusion parameters are robust to small perturbations in the simulation.Specific fis more accurate and precise thansimplified f. In the white matter (WM) regions of thein vivoimages,specific fis lower thansimplified f.Significance.In dMRI models for free water, accounting for compartment specific PD, T1 and T2, in addition to diffusion, improves the estimation of model parameters. This extra model specification attenuates the estimation bias of compartmental volume fraction without affecting the estimation of other diffusion parameters.
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Affiliation(s)
- Uran Ferizi
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States of America
| | - Eva M Müller-Oehring
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States of America
| | - Eric T Peterson
- Center for Health Sciences, SRI International, Menlo Park, CA, United States of America
| | - Kilian M Pohl
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States of America
- Center for Health Sciences, SRI International, Menlo Park, CA, United States of America
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28
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External auditory canal and middle ear tumors: characterization by morphology and diffusion features on CT and MRI. Eur Arch Otorhinolaryngol 2023; 280:605-611. [PMID: 35842859 DOI: 10.1007/s00405-022-07509-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 06/13/2022] [Indexed: 01/21/2023]
Abstract
PURPOSE To explore the value of morphology and diffusion features on CT and MRI in the characterization of external auditory canal and middle ear tumors (EAMETs). METHODS Forty-seven patients with histologically proved EAMETs (23 benign and 24 malignant) who underwent CT and MRI were retrospectively analyzed in this study. CT and MRI characteristics (including size, shape, signal intensity, border, enhancement degree, and bone changes) and apparent diffusion coefficient (ADC) value were analyzed and compared between benign and malignant EAMETs. Logistic regression, receiver operating characteristic (ROC) curve, and Delong test were performed to assess the diagnostic performance. RESULTS Compared with benign tumors, the malignant EAMETs are characterized by irregular shape, ill-defined border, invasive bone destruction, and intense enhancement (all p < 0.05). There were no significant differences on the size and signal intensity between benign and malignant tumors. The ADC value of malignant tumors were (879.96 ± 201.15) × 10-6 mm2/s, which was significantly lower than benign ones (p < 0.05). Logistic regression demonstrates the presence of ill-defined margin, invasive bone destruction, and low ADC value (≤ 920.33 × 10-6 mm2/s) have significant relationship with malignant EAMETs. The combination of characterization by morphology and diffusion features on CT and MRI can further improve the diagnostic efficiency when compared with morphology and diffusion features alone (both p < 0.05). CONCLUSION Some CT and MRI characteristics are helpful in identifying malignant EAMETs from benign ones (especially ill-defined margin, invasive bone destruction, and low ADC value), and the combination of morphology and diffusion features on CT and MRI has best diagnostic efficiency for discriminating these two entities.
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29
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Lu T, Wang Y, Deng Y, Wu C, Li X, Wang G. Diffusion and perfusion MRI parameters in the evaluation of placenta accreta spectrum disorders in patients with placenta previa. MAGMA (NEW YORK, N.Y.) 2022; 35:1009-1020. [PMID: 35802217 DOI: 10.1007/s10334-022-01023-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 05/22/2022] [Accepted: 06/19/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES To evaluate the placental function by monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in patients with placenta previa. METHODS A total of 62 patients with placenta accreta spectrum (PAS) disorders and 11 patients with normal placentas were retrospectively enrolled, who underwent conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI). The apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard DWI, mean kurtosis (MK), and diffusion coefficient (MD) from DKI, and pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from IVIM were measured and compared from the volumetric analysis. RESULTS Comparisons between patients with PAS disorders and patients with normal placentas demonstrated that MD mean, D mean, and D* mean values in patients with PAS disorders were significantly higher than those in patients with normal placentas (p < 0.05). Comparisons between patients with accreta, increta, and percreta, and patients with normal placentas showed that the D mean was significantly higher in patients with placenta increta and percreta than in patients with normal placentas (p < 0.05). CONCLUSION The accreta lesions in PAS disorders had deceased cellularity and increased blood movement. The alteration of placental cellularity was more prominent in placenta increta and percreta.
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Affiliation(s)
- Tao Lu
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Yishuang Wang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Yan Deng
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Chengqian Wu
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Xiangqi Li
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Guotai Wang
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, West Hi-tech Zone, Chengdu, 611731, China.
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Guo H, Liu J, Hu J, Zhang H, Zhao W, Gao M, Zhang Y, Yang G, Cui Y. Diagnostic performance of gliomas grading and IDH status decoding A comparison between 3D amide proton transfer APT and four diffusion-weighted MRI models. J Magn Reson Imaging 2022; 56:1834-1844. [PMID: 35488516 PMCID: PMC9790544 DOI: 10.1002/jmri.28211] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/13/2022] [Accepted: 04/14/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND The focus of neuro-oncology research has changed from histopathologic grading to molecular characteristics, and medical imaging routinely follows this change. PURPOSE To compare the diagnostic performance of amide proton transfer (APT) and four diffusion models in gliomas grading and isocitrate dehydrogenase (IDH) genotype. STUDY TYPE Prospective. POPULATION A total of 62 participants (37 males, 25 females; mean age, 52 ± 13 years) whose IDH genotypes were mutant in 6 of 14 grade II gliomas, 8 of 20 of grade III gliomas, and 4 of 28 grade IV gliomas. FIELD STRENGTH/SEQUENCE APT imaging using sampling perfection with application optimized contrasts by using different flip angle evolutions (SPACE) and DWI with q-space Cartesian grid sampling were acquired at 3 T. ASSESSMENT The ability of diffusion kurtosis imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging (NODDI), mean apparent propagator (MAP), and APT imaging for glioma grade and IDH status were assessed, with histopathological grade and genetic testing used as a reference standard. Regions of interest (ROIs) were drawn by two neuroradiologists after consensus. STATISTICAL TESTS T-test and Mann-Whitney U test; one-way analysis of variance (ANOVA); receiver operating curve (ROC) and area under the curve (AUC); DeLong test. P value < 0.05 was considered statistically significant. RESULTS Compared with IDH-mutant gliomas, IDH-wildtype gliomas showed a significantly higher mean, 5th-percentile (APT5 ), and 95th-percentile from APTw, the 95th-percentile value of axial, mean, and radial diffusivity from DKI, and 95th-percentile value of isotropic volume fraction from NODDI, and no significantly different parameters from DTI and MAP (P = 0.075-0.998). The combined APT model showed a significantly wider area under the curve (AUC 0.870) for IDH status, when compared with DKI and NODDI. APT5 was significantly different between two of the three groups (glioma II vs. glioma III vs. glioma IV: 1.35 ± 0.75 vs. 2.09 ± 0.93 vs. 2.71 ± 0.81). DATA CONCLUSION APT has higher diagnostic accuracy than DTI, DKI, MAP, and NODDI in glioma IDH genotype. APT5 can effectively identify both tumor grading and IDH genotyping, making it a promising biomarker for glioma classification. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Hu Guo
- Department of RadiologyThe Second Xiangya Hospital, Central South UniversityNo. 139 Middle Renmin Road, ChangshaHunan410011China
| | - Jun Liu
- Department of RadiologyThe Second Xiangya Hospital, Central South UniversityNo. 139 Middle Renmin Road, ChangshaHunan410011China,Department of Radiology Quality Control CenterHunan ProvinceChangsha410011China
| | - JunJiao Hu
- Department of RadiologyThe Second Xiangya Hospital, Central South UniversityNo. 139 Middle Renmin Road, ChangshaHunan410011China
| | - HuiTing Zhang
- MR Scientific Marketing, Siemens Healthineers Ltd.Wuhan430071China
| | - Wei Zhao
- Department of RadiologyThe Second Xiangya Hospital, Central South UniversityNo. 139 Middle Renmin Road, ChangshaHunan410011China
| | - Min Gao
- Department of RadiologyThe Second Xiangya Hospital, Central South UniversityNo. 139 Middle Renmin Road, ChangshaHunan410011China
| | - Yi Zhang
- Department of Biomedical EngineeringCollege of Biomedical Engineering & Instrument Science, Zhejiang UniversityHangzhouZhejiangChina
| | - Guang Yang
- Shanghai Key Laboratory of Magnetic ResonanceSchool of Physics and Electronic, East China Normal UniversityShanghaiChina
| | - Yan Cui
- Department of NeurosurgeryThe Second Xiangya Hospital, Central South UniversityNo. 139 Middle Renmin Rd, ChangshaHunan Province410011P.R. China
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Li X, Wu X, Qian J, Yuan Y, Wang S, Ye X, Sha Y, Zhang R, Ren H. Differentiation of lacrimal gland tumors using the multi-model MRI: classification and regression tree (CART)-based analysis. Acta Radiol 2022; 63:923-932. [PMID: 34058846 DOI: 10.1177/02841851211021039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Little is known about the value of dynamic contrast-enhanced (DCE) in combination with diffusion-weighted imaging (DWI) for the differentiation of lacrimal gland tumors. PURPOSE To evaluate the ability of DCE and DWI in differentiating lacrimal gland tumors. MATERIAL AND METHODS DCE and DWI were performed in 72 patients with lacrimal gland tumors. Time-intensity curve (TIC) patterns were categorized as type A, type B, type C, and type D. Apparent diffusion coefficient (ADC) was measured on DWI. Then, the diagnostic effectiveness of TIC in conjunction with ADC was assessed using classification and regression tree (CART) analysis. RESULTS Type A tumors were all epithelial; they could be further separated into pleomorphic adenoma sand carcinomas. Type B tumors were all non-epithelial tumors, which could be further separated into benign inflammatory infiltrates (BIIs) and lymphomas. Type C tumors contained both carcinomas and non-epithelial tumors, which could be diagnosed into carcinomas, BIIs and lymphomas. Type D tumors were all PAs. The mean ADC of epithelial tumors was significantly higher than that of non-epithelial tumors, and the mean ADC values were significantly different between PAs and carcinomas. Besides, the mean ADC value of BIIs was higher than that of lymphomas. Therefore, the CART decision tree made by ADC and TIC had a predictive accuracy of 86.1%, differentiating lacrimal gland tumors effectively. CONCLUSION Combined DCE and DWI-MRI can efficiently differentiate lacrimal gland tumors which can be of help to ophthalmologists in the diagnosis and treatment of these tumors.
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Affiliation(s)
- Xiaofeng Li
- Department of Ophthalmology, Eye and ENT Hospital of Fudan University, Shanghai, PR China
- NHC Key Laboratory of Myopia, Fudan University, Shanghai, PR China
- Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, PR China
| | - Xue Wu
- Department of Ophthalmology, Eye and ENT Hospital of Fudan University, Shanghai, PR China
- NHC Key Laboratory of Myopia, Fudan University, Shanghai, PR China
- Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, PR China
| | - Jiang Qian
- Department of Ophthalmology, Eye and ENT Hospital of Fudan University, Shanghai, PR China
- NHC Key Laboratory of Myopia, Fudan University, Shanghai, PR China
- Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, PR China
| | - Yifei Yuan
- Department of Ophthalmology, Eye and ENT Hospital of Fudan University, Shanghai, PR China
- NHC Key Laboratory of Myopia, Fudan University, Shanghai, PR China
- Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, PR China
| | - Shenjiang Wang
- Department of Radiology, Eye and ENT Hospital of Fudan University, Shanghai, PR China
| | - Xinpei Ye
- Department of Radiology, Eye and ENT Hospital of Fudan University, Shanghai, PR China
| | - Yan Sha
- Department of Radiology, Eye and ENT Hospital of Fudan University, Shanghai, PR China
| | - Rui Zhang
- Department of Ophthalmology, Eye and ENT Hospital of Fudan University, Shanghai, PR China
- NHC Key Laboratory of Myopia, Fudan University, Shanghai, PR China
- Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, PR China
| | - Hui Ren
- Department of Ophthalmology, Eye and ENT Hospital of Fudan University, Shanghai, PR China
- NHC Key Laboratory of Myopia, Fudan University, Shanghai, PR China
- Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, PR China
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Rotkopf LT, Kampf T, Triphan SMF, Schlemmer HP, Ziener CH. Influence of flow and susceptibility effects on spin dephasing in lung tissue. Med Phys 2022; 49:5981-5992. [PMID: 35638106 DOI: 10.1002/mp.15784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 05/17/2022] [Accepted: 05/21/2022] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Magnetic resonance imaging (MRI) of the lung can be used for diagnosis and monitoring of interstitial lung disease. Biophysical models of alveolar lung tissue are needed to understand the complex interplay of susceptibility, diffusion, and flow effects, and their influence on magnetic resonance (MR) spin dephasing. METHODS In this work, we present a method for modeling the signal decay of lung tissue by utilizing a two-compartment model, which considers the different spin dephasing mechanisms in the alveolar vasculature and interstitial tissue. This allows calculating the magnetization dynamics and the MR lineshape, which can be measured noninvasively using clinical MR scanners. RESULTS The accuracy of the method was evaluated using finite element simulations and the experimentally measured lineshapes of a healthy volunteer. In this comparison, the model performs well, indicating that the relevant spin dephasing mechanisms are correctly taken into account. CONCLUSIONS The proposed method can be used to estimate the influence of blood flow and alveolar geometry on the MR lineshape of lung tissue.
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Affiliation(s)
- Lukas T Rotkopf
- Department of Radiology, German Cancer Research Center, Im Neuenheimer Feld, Heidelberg, Germany.,Medical Faculty, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Thomas Kampf
- Department of Neuroradiology, Würzburg University Hospital, Würzburg, Germany.,Department of Experimental Physics 5, University of Würzburg, Würzburg, Germany
| | - Simon M F Triphan
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.,Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
| | - Heinz-Peter Schlemmer
- Department of Radiology, German Cancer Research Center, Im Neuenheimer Feld, Heidelberg, Germany
| | - Christian H Ziener
- Department of Radiology, German Cancer Research Center, Im Neuenheimer Feld, Heidelberg, Germany
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Wang Z, Zhao Z, Song Z, Wang Y, Zhao Z. The application of magnetic resonance imaging (MRI) for the prediction of surgical outcomes in trigeminal neuralgia. Postgrad Med 2022; 134:480-486. [PMID: 35503235 DOI: 10.1080/00325481.2022.2067612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Trigeminal neuralgia (TN) is a severe facial pain disorder that often requires surgical treatment. Neurovascular compression (NVC) has been widely accepted as the primary cause of classical TN (cTN). Vascular compression involving the near half of the cisternal segment of trigeminal nerve was the most likely cause of patient's symptoms. And severe NVC was a strong imaging predictor of an optimal surgical outcome. Operative treatments for cTN include microvascular decompression (MVD) and various ablative procedures. However, a significant proportion of cTN patients with significant NVC fail to achieve long-term pain relief after technically successful surgery. Neuroimaging using magnetic resonance imaging (MRI) provides a noninvasive method to generate objective biomarkers of eventual response to TN surgery. This paper reviewed the progress of research on the prediction of surgical outcomes in TN with MRI.
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Affiliation(s)
- Zairan Wang
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Zijun Zhao
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Zihan Song
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Yizheng Wang
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Zongmao Zhao
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
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Ozkok S, Sorkun M, Erdemli S, Dogan MB, Aslan A, Yucel IK, Celebi A. Liver parenchymal changes and association with cardiac magnetic resonance imaging findings in repaired tetralogy of Fallot: an intravoxel incoherent motion magnetic resonance imaging study. Pediatr Radiol 2022; 52:892-902. [PMID: 35147715 DOI: 10.1007/s00247-021-05271-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 11/01/2021] [Accepted: 12/04/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND Liver disease can develop in repaired tetralogy of Fallot (TOF) from hepatic congestion caused by volume and pressure overload of the right ventricle. Noninvasive assessment of the liver is important for diagnosing and managing children with TOF. OBJECTIVE To evaluate subclinical hepatic changes without liver function test abnormality in adolescents with repaired TOF using intravoxel incoherent motion (IVIM) MRI and cardiac MRI findings. MATERIALS AND METHODS We included 106 young adults (75 with repaired TOF and 31 healthy individuals) in the study. Liver IVIM MRI examinations were performed with 10 b values (0, 10, 20, 30, 50, 80, 100, 200, 400, 800 s/mm2). Two observers measured IVIM MRI parameters D true, D* and f, as well as apparent diffusion coefficient (ADC) values in liver segments 5-8. RESULTS D* and f values were significantly lower in adolescents with TOF (P = 0.003 vs. P = 0.05, respectively). ADC values were higher in adolescents with TOF (P = 0.005). However, we found no significant difference between adolescents with and without TOF in terms of Dtrue (P = 0.53). There was a significant correlation between f value and right ventricular ejection fraction. The intraclass correlation coefficient (ICC) analysis of the two observers showed substantial-to-excellent agreement for D, f, D true and ADC (0.7, 0.8, 0.9 and 0.8, respectively). CONCLUSION The results of our study suggest that impaired microperfusion with increased ADC values in adolescents with repaired TOF reflect hepatic congestion rather than fibrosis. Hepatic congestion characterized by decreased ADC values can be easily differentiated before fibrotic changes occur by using IVIM MRI to assess diffusion and microcapillary perfusion separately.
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Affiliation(s)
- Sercin Ozkok
- Goztepe Training and Research Hospital, Department of Radiology, Istanbul Medeniyet University, Dr. Erkin Street, No:6, Kadikoy, Istanbul, Turkey.
| | - Mine Sorkun
- Goztepe Training and Research Hospital, Department of Radiology, Istanbul Medeniyet University, Dr. Erkin Street, No:6, Kadikoy, Istanbul, Turkey
| | - Servet Erdemli
- Goztepe Training and Research Hospital, Department of Radiology, Istanbul Medeniyet University, Dr. Erkin Street, No:6, Kadikoy, Istanbul, Turkey
| | - Mahmut B Dogan
- Goztepe Training and Research Hospital, Department of Radiology, Istanbul Medeniyet University, Dr. Erkin Street, No:6, Kadikoy, Istanbul, Turkey
| | - Ahmet Aslan
- Goztepe Training and Research Hospital, Department of Radiology, Istanbul Medeniyet University, Dr. Erkin Street, No:6, Kadikoy, Istanbul, Turkey
| | - Ilker K Yucel
- Department of Pediatric Cardiology, Dr. Siyami Ersek Thoracic and Cardiovascular Surgery Training and Research Hospital, Istanbul, Turkey
| | - Ahmet Celebi
- Department of Pediatric Cardiology, Dr. Siyami Ersek Thoracic and Cardiovascular Surgery Training and Research Hospital, Istanbul, Turkey
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Lu T, Wang Y, Guo A, Cui W, Chen Y, Wang S, Wang G. Monoexponential, biexponential and diffusion kurtosis MR imaging models: quantitative biomarkers in the diagnosis of placenta accreta spectrum disorders. BMC Pregnancy Childbirth 2022; 22:349. [PMID: 35459146 PMCID: PMC9034554 DOI: 10.1186/s12884-022-04644-9] [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: 12/31/2021] [Accepted: 03/23/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To investigate the diagnostic value of monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in differentiating placenta accreta spectrum (PAS) disorders. METHODS A total of 65 patients with PAS disorders and 27 patients with normal placentas undergoing conventional DWI, IVIM, and DKI were retrospectively reviewed. The mean, minimum, and maximum parameters including the apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard DWI, diffusion kurtosis (MK), and mean diffusion coefficient (MD) from DKI and pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from IVIM were measured from the volumetric analysis and compared between patients with PAS disorders and patients with normal placentas. Univariate and multivariated logistic regression analyses were used to evaluate the value of the above parameters for differentiating PAS disorders. Receiver operating characteristics (ROC) curve analyses were used to evaluate the diagnostic efficiency of different diffusion parameters for predicting PAS disorders. RESULTS Multivariate analysis demonstrated that only D mean and D max differed significantly among all the studied parameters for differentiating PAS disorders when comparisons between accreta lesions in patients with PAS (AP) and whole placentas in patients with normal placentas (WP-normal) were performed (all p < 0.05). For discriminating PAS disorders, a combined use of these two parameters yielded an AUC of 0.93 with sensitivity, specificity, and accuracy of 83.08, 88.89, and 83.70%, respectively. CONCLUSION The diagnostic performance of the parameters from accreta lesions was better than that of the whole placenta. D mean and D max were associated with PAS disorders.
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Affiliation(s)
- Tao Lu
- Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Yishuang Wang
- Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Aiwen Guo
- Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Wei Cui
- Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Yazheng Chen
- Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, 32 West Second Section, First Ring Road, Chengdu, 610072, China
| | - Shaoyu Wang
- Siemens Healthineer, No.278, Zhouzhu Road, Pudong New Area District, Shanghai, 201318, China
| | - Guotai Wang
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, West Hi-tech Zone, Chengdu, 611731, China.
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Yuan J, Gong Z, Liu K, Song J, Wen Q, Tan W, Zhan S, Shen Q. Correlation between diffusion kurtosis and intravoxel incoherent motion derived (IVIM) parameters and tumor tissue composition in rectal cancer: a pilot study. Abdom Radiol (NY) 2022; 47:1223-1231. [PMID: 35107589 DOI: 10.1007/s00261-022-03426-3] [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: 11/25/2021] [Revised: 01/18/2022] [Accepted: 01/19/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE To correlate non-invasive quantitative diffusion kurtosis imaging (DKI) and intravoxel incoherent motion-derived (IVIM) parameters with rectal cancer composition assessed by the expression of caudal-type homeobox 2 (CDX-2), Vimentin (VIM), CD34 and Ki-67 on resected tissues, as well as the tumor stroma ratio (TSR) and the results of H&E and Masson staining. MATERIALS AND METHODS A prospective study of 26 patients with rectal cancer who underwent magnetic resonance (MR) imaging, including DKI with 4 b values and IVIM at 3.0 T prior to surgery. Primary tumor was harvested and fixed for H&E, immunohistochemistry and Masson staining. One-way ANOVA was used to test the differences. Pearson correlation coefficients and multiple linear regression analyses were applied to evaluation the correlations. RESULTS The apparent diffusion coefficient (ADCDKI) and MKDKI all exhibited significant differences in subgroups with different T stages (P < 0.05) and among high- and low- grade rectal cancer (P < 0.05). MDDKI showed a moderate negative correlation with CDX-2 (r = - 0.42, P = 0.040) and a moderate positive correlation with CD34 (r = 0.42, P = 0.041). ADCIVIM exhibited a moderate positive correlation with Masson staining (r = 0.426, P = 0.048) DIVIM showed a moderate negative correlation with CDX-2 (r = - 0.58, P = 0.005). [Formula: see text] showed a moderate positive correlation with VIM (r = 0.445, P = 0.033). CONCLUSION ADCDKI and MKDKI demonstrated a higher correlation with T stages and histologic grades. MDDKI showed significant correlations with CDX-2 and CD34. ADCIVIM showed significant correlation with Masson. DIVIM showed significant correlations with CDX-2 and [Formula: see text] showed significant correlation with VIM. These findings should be validated in a larger study.
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Affiliation(s)
- Jie Yuan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528, Zhangheng Road, Pudong District, Shanghai, China
| | - Zhigang Gong
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528, Zhangheng Road, Pudong District, Shanghai, China
| | - Kun Liu
- Department of Pathology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528, Zhangheng Road, Pudong District, Shanghai, China.
| | - Jingjing Song
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528, Zhangheng Road, Pudong District, Shanghai, China
| | - Qun Wen
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528, Zhangheng Road, Pudong District, Shanghai, China
| | - Wenli Tan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528, Zhangheng Road, Pudong District, Shanghai, China.
| | - Songhua Zhan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528, Zhangheng Road, Pudong District, Shanghai, China
| | - Qiang Shen
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528, Zhangheng Road, Pudong District, Shanghai, China
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Tamagawa S, Sakai D, Nojiri H, Sato M, Ishijima M, Watanabe M. Imaging Evaluation of Intervertebral Disc Degeneration and Painful Discs-Advances and Challenges in Quantitative MRI. Diagnostics (Basel) 2022; 12:707. [PMID: 35328260 PMCID: PMC8946895 DOI: 10.3390/diagnostics12030707] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 03/08/2022] [Accepted: 03/10/2022] [Indexed: 01/07/2023] Open
Abstract
In recent years, various quantitative and functional magnetic resonance imaging (MRI) sequences have been developed and used in clinical practice for the diagnosis of patients with low back pain (LBP). Until now, T2-weighted imaging (T2WI), a visual qualitative evaluation method, has been used to diagnose intervertebral disc (IVD) degeneration. However, this method has limitations in terms of reproducibility and inter-observer agreement. Moreover, T2WI observations do not directly relate with LBP. Therefore, new sequences such as T2 mapping, T1ρ mapping, and MR spectroscopy have been developed as alternative quantitative evaluation methods. These new quantitative MRIs can evaluate the anatomical and physiological changes of IVD degeneration in more detail than conventional T2WI. However, the values obtained from these quantitative MRIs still do not directly correlate with LBP, and there is a need for more widespread use of techniques that are more specific to clinical symptoms such as pain. In this paper, we review the state-of-the-art methodologies and future challenges of quantitative MRI as an imaging diagnostic tool for IVD degeneration and painful discs.
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Affiliation(s)
- Shota Tamagawa
- Department of Medicine for Orthopaedics and Motor Organ, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan; (S.T.); (H.N.); (M.I.)
- Department of Orthopaedic Surgery, Surgical Science, Tokai University School of Medicine, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan; (M.S.); (M.W.)
| | - Daisuke Sakai
- Department of Orthopaedic Surgery, Surgical Science, Tokai University School of Medicine, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan; (M.S.); (M.W.)
- Center for Musculoskeletal Innovative Research and Advancement (C-MiRA), Tokai University Graduate School, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan
| | - Hidetoshi Nojiri
- Department of Medicine for Orthopaedics and Motor Organ, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan; (S.T.); (H.N.); (M.I.)
| | - Masato Sato
- Department of Orthopaedic Surgery, Surgical Science, Tokai University School of Medicine, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan; (M.S.); (M.W.)
- Center for Musculoskeletal Innovative Research and Advancement (C-MiRA), Tokai University Graduate School, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan
| | - Muneaki Ishijima
- Department of Medicine for Orthopaedics and Motor Organ, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan; (S.T.); (H.N.); (M.I.)
| | - Masahiko Watanabe
- Department of Orthopaedic Surgery, Surgical Science, Tokai University School of Medicine, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan; (M.S.); (M.W.)
- Center for Musculoskeletal Innovative Research and Advancement (C-MiRA), Tokai University Graduate School, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan
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Differences in the MRI Signature and ADC Values of Diffuse Midline Gliomas with H3 K27M Mutation Compared to Midline Glioblastomas. Cancers (Basel) 2022; 14:cancers14061397. [PMID: 35326549 PMCID: PMC8946584 DOI: 10.3390/cancers14061397] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/26/2022] [Accepted: 03/06/2022] [Indexed: 12/21/2022] Open
Abstract
We conducted a two-center retrospective survey on standard MRI features including apparent diffusion coefficient mapping (ADC) of diffuse midline gliomas H3 K27M-mutant (DMG) compared to midline glioblastomas H3 K27M-wildtype (midGBM-H3wt). We identified 39 intracranial DMG and 18 midGBM-H3wt tumors. Samples were microscopically re-evaluated for microvascular proliferations and necrosis. Image analysis focused on location, peritumoral edema, degree of contrast enhancement and DWI features. Within DMG, MRI features between tumors with or without histomorphological GBM features were compared. DMG occurred in 15/39 samples from the thalamus (38%), in 23/39 samples from the brainstem (59%) and in 1/39 tumors involving primarily the cerebellum (2%). Edema was present in 3/39 DMG cases (8%) versus 78% in the control (midGBM-H3wt) group (p < 0.001). Contrast enhancement at the tumor rim was detected in 17/39 DMG (44%) versus 67% in control (p = 0.155), and necrosis in 24/39 (62%) versus 89% in control (p = 0.060). Strong contrast enhancement was observed in 15/39 DMG (38%) versus 56% in control (p = 0.262). Apparent diffusion coefficient (ADC) histogram analysis showed significantly higher skewness and kurtosis values in the DMG group compared to the controls (p = 0.0016/p = 0.002). Minimum relative ADC (rADC) values, as well as the 10th and 25th rADC-percentiles, were lower in DMGs with GBM features within the DMG group (p < 0.001/p = 0.012/p = 0.027). In conclusion, DMG cases exhibited markedly less edema than midGBM-H3wt, even if histomorphological malignancy was present. Histologically malignant DMGs and midGBM-H3wt more often displayed strong enhancement, as well as rim enhancement, than DMGs without histomorphological malignancy. DMGs showed higher skewness and kurtosis values on ADC-histogram analysis compared to midGBM-H3wt. Lower minimum rADC values in DMGs indicated malignant histomorphological features, likely representing a more complex tissue microstructure.
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Mir SM, Chen J, Pinezich MR, O'Neill JD, Huang SXL, Vunjak-Novakovic G, Kim J. Imaging-guided bioreactor for de-epithelialization and long-term cultivation of ex vivo rat trachea. LAB ON A CHIP 2022; 22:1018-1031. [PMID: 35166739 PMCID: PMC8942046 DOI: 10.1039/d1lc01105g] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Recent synergistic advances in organ-on-chip and tissue engineering technologies offer opportunities to create in vitro-grown tissue or organ constructs that can faithfully recapitulate their in vivo counterparts. Such in vitro tissue or organ constructs can be utilized in multiple applications, including rapid drug screening, high-fidelity disease modeling, and precision medicine. Here, we report an imaging-guided bioreactor that allows in situ monitoring of the lumen of ex vivo airway tissues during controlled in vitro tissue manipulation and cultivation of isolated rat trachea. Using this platform, we demonstrated partial removal of the rat tracheal epithelium (i.e., de-epithelialization) without disrupting the underlying subepithelial cells and extracellular matrix. Through different tissue evaluation assays, such as immunofluorescent staining, DNA/protein quantification, and electron beam microscopy, we showed that the epithelium of the tracheal lumen can be effectively removed with negligible disruption in the underlying tissue layers, such as cartilage and blood vessel. Notably, using a custom-built micro-optical imaging device integrated with the bioreactor, the trachea lumen was visualized at the cellular level, and removal of the endogenous epithelium and distribution of locally delivered exogenous cells were demonstrated in situ. Moreover, the de-epithelialized trachea supported on the bioreactor allowed attachment and growth of exogenous cells seeded topically on its denuded tissue surface. Collectively, the results suggest that our imaging-enabled rat trachea bioreactor and localized cell replacement method can facilitate creation of bioengineered in vitro airway tissue that can be used in different biomedical applications.
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Affiliation(s)
- Seyed Mohammad Mir
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, USA.
| | - Jiawen Chen
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, USA.
| | - Meghan R Pinezich
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - John D O'Neill
- Department of Cell Biology, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - Sarah X L Huang
- Center for Stem Cell and Regenerative Medicine, University of Texas Health Science Center, Houston, TX, USA
| | | | - Jinho Kim
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, USA.
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Vogl TJ, Jaraysa Y, Martin SS, Gruber-Rouh T, Savage RH, Nour-Eldin NEA, Mehmedovic A. A prospective randomized trial comparing microwave and radiofrequency ablation for the treatment of liver metastases using a dual ablation system ─ The Mira study. Eur J Radiol Open 2022; 9:100399. [PMID: 35155721 PMCID: PMC8822176 DOI: 10.1016/j.ejro.2022.100399] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 01/19/2022] [Accepted: 01/21/2022] [Indexed: 12/22/2022] Open
Abstract
Purpose The aim of this study was to prospectively compare the therapy response and safety of microwave (MWA) and radiofrequency ablation (RFA) for the treatment of liver metastases using a dual ablation system. Methods Fifty patients with liver metastases (23 men, mean age: 62.8 ± 11.8 years) were randomly assigned to MWA or RFA for thermal ablation using a one generator dual ablation system. Magnetic resonance imaging (MRI) was acquired before treatment and 24 h post ablation. The morphologic responses to treatment regarding size, volume, necrotic areas, and diffusion characteristics were evaluated by MRI. Imaging follow-up was obtained for one year in three months intervals, whereas clinical follow-up was obtained for two years in all patients. Results Twenty-six patients received MWA and 24 patients received RFA (mean diameter: 1.6 cm, MWA: 1.7 cm, RFA: 1.5 cm). The mean volume 24 h after ablation was 37.0 cm3 (MWA: 50.5 cm3, RFA: 22.9 cm3, P < 0.01). The local recurrence rate was 0% (0/26) in the MWA-group and 8.3% (2/24) in the RFA-group (P = 0.09). The rate of newly developed malignant formations was 38.0% (19/50) for both groups (MWA: 38.4%, RFA: 37.5%, P = 0.07). The overall survival rate was 70.0% (35/50) after two years (MWA: 76.9%, RFA: 62.5%, P = 0.60). No major complications were reported. Conclusion In conclusion, MWA and RFA are both safe and effective methods for the treatment of liver metastases with MWA generating greater volumes of ablation. No significant differences were found for overall survival, rate of neoplasm, or major complications between both groups. A dual ablation system allows for MWA and RFA treatment using the same hardware. Both methods are safe and effective for the treatment of liver metastases. MWA generates greater volumes of ablation and larger ablative margins compared to RFA.
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Affiliation(s)
- Thomas J. Vogl
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany
- Correspondence to: University Hospital Frankfurt, Department of Diagnostic and Interventional Radiology, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany.
| | - Yousef Jaraysa
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany
| | - Simon S. Martin
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany
| | - Tatjana Gruber-Rouh
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany
| | - Rock H. Savage
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - Nour-Eldin A. Nour-Eldin
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany
| | - Amela Mehmedovic
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany
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Rodríguez-Soto AE, Andreassen MMS, Fang LK, Conlin CC, Park HH, Ahn GS, Bartsch H, Kuperman J, Vidić I, Ojeda-Fournier H, Wallace AM, Hahn M, Seibert TM, Jerome NP, Østlie A, Bathen TF, Goa PE, Rakow-Penner R, Dale AM. Characterization of the diffusion signal of breast tissues using multi-exponential models. Magn Reson Med 2021; 87:1938-1951. [PMID: 34904726 DOI: 10.1002/mrm.29090] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 10/12/2021] [Accepted: 11/01/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE Restriction spectrum imaging (RSI) decomposes the diffusion-weighted MRI signal into separate components of known apparent diffusion coefficients (ADCs). The number of diffusion components and optimal ADCs for RSI are organ-specific and determined empirically. The purpose of this work was to determine the RSI model for breast tissues. METHODS The diffusion-weighted MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxels in cancer and control ROIs. Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative-fitting residuals and Bayesian information criterion were assessed. Contrast-to-noise ratio between cancer and fibroglandular tissue in RSI-derived signal contribution maps was compared to DCE imaging. RESULTS A total of 74 women with breast cancer were scanned at 3.0 Tesla MRI. The fitting residuals of conventional ADC and Bayesian information criterion suggest that a 3-component model improves the characterization of the diffusion signal over a biexponential model. Estimated ADCs of triexponential model were D1,3 = 0, D2,3 = 1.5 × 10-3 , and D3,3 = 10.8 × 10-3 mm2 /s. The RSI-derived signal contributions of the slower diffusion components were larger in tumors than in fibroglandular tissues. Further, the contrast-to-noise and specificity at 80% sensitivity of DCE and a subset of RSI-derived maps were equivalent. CONCLUSION Breast diffusion-weighted MRI signal was best described using a triexponential model. Tumor conspicuity in breast RSI model is comparable to that of DCE without the use of exogenous contrast. These data may be used as differential features between healthy and malignant breast tissues.
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Affiliation(s)
- Ana E Rodríguez-Soto
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Maren M Sjaastad Andreassen
- Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Lauren K Fang
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Christopher C Conlin
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Helen H Park
- School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Grace S Ahn
- School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Hauke Bartsch
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Joshua Kuperman
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Igor Vidić
- Department of Physics, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Haydee Ojeda-Fournier
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Anne M Wallace
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Michael Hahn
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Tyler M Seibert
- Department of Radiation Oncology, University of California San Diego, La Jolla, California, USA.,Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Neil Peter Jerome
- Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway
| | - Agnes Østlie
- Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway
| | - Tone Frost Bathen
- Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway
| | - Pål Erik Goa
- Department of Physics, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway
| | - Rebecca Rakow-Penner
- Department of Radiology, University of California San Diego, La Jolla, California, USA.,Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA
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Huang Z, Li X, Wang Z, Meng N, Fu F, Han H, Li D, Bai Y, Wei W, Fang T, Feng P, Yuan J, Yang Y, Wang M. Application of Simultaneous 18 F-FDG PET With Monoexponential, Biexponential, and Stretched Exponential Model-Based Diffusion-Weighted MR Imaging in Assessing the Proliferation Status of Lung Adenocarcinoma. J Magn Reson Imaging 2021; 56:63-74. [PMID: 34888990 DOI: 10.1002/jmri.28010] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/18/2021] [Accepted: 11/18/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Ki-67 proliferation index (PI) is important for providing information on tumor behavior, treatment response, and prognosis. Integrated positron emission tomography/magnetic resonance (PET/MR) may have the potential to assess Ki-67 PI in patients with lung adenocarcinoma. PURPOSE To explore the value of simultaneous 18 F-fluorodeoxyglucose (18 F-FDG) PET/MR-derived parameters in assessing the proliferation status of lung adenocarcinoma and to determine the best combination of parameters. STUDY TYPE Prospective. POPULATION Seventy-eight patients with lung adenocarcinoma and with Ki-67 PI. FIELD STRENGTH/SEQUENCE 3.0 T, simultaneous PET/MRI including diffusion-weighted imaging (DWI) and 18 F-FDG PET. ASSESSMENT DWI-derived parameters, namely, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), diffusion heterogeneity index (α), and distributed diffusion coefficient (DDC); and PET-derived parameters, namely, maximum standardized uptake value (SUVmax ), metabolic tumor volume (MTV), and total lesion glycolytic volume (TLG), were calculated and compared between the high (>25%) and low (≤25%) Ki-67 PI groups. The correlations between PET-derived parameters and DWI-derived parameters were analyzed. STATISTICAL TESTS Student's t-test, Mann-Whitney U test, chi-square test, and receiver operating characteristic (ROC) curves. A P-value <0.05 was considered statistically significant. RESULTS The SUVmax , MTV, TLG, ADC, D, and DDC values were significantly different between the high (N = 35) and low Ki-67 PI groups (N = 43). D, SUVmax , and MTV independently predicted the Ki-67 PI status. The combination of D, SUVmax , and MTV had the largest area under the ROC curve (AUC = 0.900), which was significantly larger than the AUC alone of DDC (AUC = 0.725), SUVmax (AUC = 0.815), MTV (AUC = 0.774), or TLG (AUC = 0.783). The perfusion fraction did not correlate with SUVmax , MTV, or TLG (r = -0.03, -0.11, and -0.04, respectively; P = 0.786, 0.348, and 0.733). DATA CONCLUSION The combination of D, SUVmax , and MTV may predict Ki-67 PI status. No correlation was observed between perfusion parameters and metabolic parameters. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Zhun Huang
- Department of Medical Imaging, Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China
| | - Xiaochen Li
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Zhixue Wang
- Department of Radiology, The First Affiliated Hospital of Henan University, Kaifeng, China
| | - Nan Meng
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Fangfang Fu
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Dujuan Li
- Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Yan Bai
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Wei Wei
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Ting Fang
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Pengyang Feng
- Department of Medical Imaging, Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China
| | - Jianmin Yuan
- Central Research Institute, UIH Group, Shanghai, China
| | - Yang Yang
- Beijing United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
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Wang C, Yu J, Lu M, Li Y, Shi H, Xu Q. Diagnostic Efficiency of Diffusion Sequences and a Clinical Nomogram for Detecting Lymph Node Metastases from Rectal Cancer. Acad Radiol 2021; 29:1287-1295. [PMID: 34802905 DOI: 10.1016/j.acra.2021.10.009] [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: 08/22/2021] [Revised: 09/30/2021] [Accepted: 10/01/2021] [Indexed: 11/30/2022]
Abstract
RATIONALE AND OBJECTIVES First, to evaluate and compare three different diffusion sequences (i.e., standard DWI, IVIM, and DKI) for nodal staging. Second, to combine the DWI, and anatomic information to assess metastatic lymph node (LN). MATERIALS AND METHODS We retrospectively identified 136 patients of rectal adenocarcinoma who met the inclusion criteria. Three diffusion sequences (i.e., standard DWI, IVIM, and DKI) were performed, and quantitative parameters were evaluated. Univariate and multivariate analyses were used to assess the associations between the anatomic and DWI information and LN pathology. Multivariate logistic regression was used to identify independent risk factors. A nomogram model was established, and the model performance was evaluated by the concordance index (c-index) and calibration curve. RESULTS There was a statistical difference in variables (LN long diameter, LN short diameter, LN boundary, LN signal, peri-LN signal intensity, ADC-1000, ADC-1400, ADC-2000, Kapp and D) between metastatic and non-metastatic LN for training and validation cohorts (p < 0.05). The ADC value derived from b = 1000 mm/s (ADC-1000) showed the relative higher AUC (AUC = 0.780) than the ADC value derived from b = 1400 mm/s (ADC-1400) (AUC = 0.703). The predictive accuracy of the nomogram measured by the c-index was 0.854 and 0.812 in the training and validation cohort, respectively. CONCLUSION The IVIM and DKI model's diagnostic efficiency was not significantly improved compared to conventional DWI. The diagnostic accuracy of metastatic LN can be enhanced using the nomogram model, leading to a rational therapeutic choice.
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Affiliation(s)
- Chen Wang
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO.300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Jing Yu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO.300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Ming Lu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO.300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Yang Li
- Department of Pathology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Hongyuan Shi
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO.300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Qing Xu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO.300, Guangzhou Road, Nanjing, Jiangsu 210029, China.
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Wang M, Perucho JA, Vardhanabhuti V, Ip P, Ngan HY, Lee EY. Radiomic Features of T2-weighted Imaging and Diffusion Kurtosis Imaging in Differentiating Clinicopathological Characteristics of Cervical Carcinoma. Acad Radiol 2021; 29:1133-1140. [PMID: 34583867 DOI: 10.1016/j.acra.2021.08.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 07/28/2021] [Accepted: 08/12/2021] [Indexed: 01/06/2023]
Abstract
RATIONALE AND OBJECTIVES Clinicopathological characteristics including histological subtypes, tumour grades and International Federation of Gynecology and Obstetrics (FIGO) stages are crucial factors in the clinical decision for cervical carcinoma (CC). The purpose of this study was to evaluate the ability of T2-weighted imaging (T2WI) and diffusion kurtosis imaging (DKI) radiomics in differentiating clinicopathological characteristics of CC. MATERIALS AND METHODS One hundred and seventeen histologically confirmed CC patients (mean age 56.5 ± 14.0 years) with pre-treatment magnetic resonance imaging were retrospectively reviewed. DKI was acquired with 4 b-values (0-1500 s/mm2). Volumes of interest were contoured around the tumours on T2WI and DKI. Radiomic features including shape, first-order and grey-level co-occurrence matrix with wavelet transforms were extracted. Intraclass correlation coeffient between 2 radiologists was used for features reduction. Feature selection was achieved by elastic net and minimum redundancy maximum relevance. Selected features were used to build random forest (RF) models. The performances for differentiating histological subtypes, tumour grades and FIGO stages were assessed by receiver operating characteristic analysis. RESULTS Area under the curves (AUCs) for T2WI-only RF models for discriminating histological subtypes, tumour grades and FIGO stages were 0.762, 0.686, and 0.719. AUCs for DWI-only models were 0.663, 0.645, and 0.868, respectively. AUCs of the combined T2WI and DKI models were 0.823, 0.790, and 0.850, respectively. CONCLUSION T2WI and DKI radiomic features could differentiate the clinicopathological characteristics of CC. A combined model showed excellent diagnostic discrimination for histological subtypes, while a DKI-only model presented the best performance in differentiating FIGO stages.
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Fang S, Yang Y, Chen B, Yin Z, Liu Y, Tao J, Zhang Y, Yuan Y, Wang Q, Wang S. DWI and IVIM Imaging in a Murine Model of Rhabdomyosarcoma: Correlations with Quantitative Histopathologic Features. J Magn Reson Imaging 2021; 55:225-233. [PMID: 34240504 DOI: 10.1002/jmri.27828] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/23/2021] [Accepted: 06/23/2021] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND High cellularity and abnormal interstitial structures are some of the unfavorable factors that affect the treatment outcomes and survival of rhabdomyosarcoma (RMS) patients. PURPOSE To explore the correlation between diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) with quantitative histopathologic features in a murine model of RMS. STUDY TYPE Prospective. ANIMAL MODEL Murine model of RMS (31 female BALB/c nude mice). FIELD STRENGTH/SEQUENCE 3.0 T; fast spin-echo (FSE) T1-weighted imaging, fast relaxation fast spin-echo (FRFSE) T2-weighted imaging, DWI PROPELLER FSE imaging sequence, and IVIM echo planar imaging sequence; 10 different b-values (0, 50, 100, 150, 200, 400, 600, 800, 1000, and 1200 s/mm2 ). ASSESSMENT Magnetic resonance imaging (MRI) was performed after 30-45 days of implantation. The following MRI parameters were calculated: apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f). Histopathologic features, which contained nuclear, cytoplasmic, and stromal fractions, and the nuclear-to-cytoplasmic ratio within the tumor were measured using image-based segmentation. STATISTICAL TESTS Pearson's correlation, multiple linear regression analysis, and receiver operating characteristic curve analysis were performed. A P < 0.05 was considered statistically significant. RESULTS The ADC value showed moderate negative correlation with nuclear fraction (r = -0.540), and moderate positive correlation with stroma fraction (r = 0.474). The D value showed moderate negative correlation with nuclear fraction (r = -0.491), and moderate positive correlation with stroma fraction (r = 0.421). The f value showed a moderate negative correlation with stroma fraction (r = -0.423). The D value showed the best diagnostic ability. The optimal cut-off D value of 0.460 was associated with 77.8% sensitivity and 68.2% specificity (area under the curve, 0.747). DATA CONCLUSION The ADC, D, and f values obtained from DWI and IVIM images showed moderate correlation with the quantitative histopathologic features in a murine model of RMS. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 3.
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Affiliation(s)
- Shaobo Fang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yanyu Yang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Bo Chen
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Zhenzhen Yin
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yajie Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Juan Tao
- Department of Pathology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yu Zhang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yuan Yuan
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Qi Wang
- Department of Respiratory, The Second Hospital, Dalian Medical University, Dalian, China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
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Wang YF, Tadimalla S, Hayden AJ, Holloway L, Haworth A. Artificial intelligence and imaging biomarkers for prostate radiation therapy during and after treatment. J Med Imaging Radiat Oncol 2021; 65:612-626. [PMID: 34060219 DOI: 10.1111/1754-9485.13242] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/18/2021] [Accepted: 05/02/2021] [Indexed: 12/15/2022]
Abstract
Magnetic resonance imaging (MRI) is increasingly used in the management of prostate cancer (PCa). Quantitative MRI (qMRI) parameters, derived from multi-parametric MRI, provide indirect measures of tumour characteristics such as cellularity, angiogenesis and hypoxia. Using Artificial Intelligence (AI), relevant information and patterns can be efficiently identified in these complex data to develop quantitative imaging biomarkers (QIBs) of tumour function and biology. Such QIBs have already demonstrated potential in the diagnosis and staging of PCa. In this review, we explore the role of these QIBs in monitoring treatment response during and after PCa radiotherapy (RT). Recurrence of PCa after RT is not uncommon, and early detection prior to development of metastases provides an opportunity for salvage treatments with curative intent. However, the current method of monitoring treatment response using prostate-specific antigen levels lacks specificity. QIBs, derived from qMRI and developed using AI techniques, can be used to monitor biological changes post-RT providing the potential for accurate and early diagnosis of recurrent disease.
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Affiliation(s)
- Yu-Feng Wang
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
| | - Sirisha Tadimalla
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
| | - Amy J Hayden
- Sydney West Radiation Oncology, Westmead Hospital, Wentworthville, New South Wales, Australia
- Faculty of Medicine, Western Sydney University, Sydney, New South Wales, Australia
- Faculty of Medicine, Health & Human Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Lois Holloway
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
- Liverpool and Macarthur Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia
| | - Annette Haworth
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
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47
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Kelley S, Plass J, Bender AR, Polk TA. Age-Related Differences in White Matter: Understanding Tensor-Based Results Using Fixel-Based Analysis. Cereb Cortex 2021; 31:3881-3898. [PMID: 33791797 DOI: 10.1093/cercor/bhab056] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 01/19/2021] [Accepted: 02/16/2021] [Indexed: 12/13/2022] Open
Abstract
Aging is associated with widespread alterations in cerebral white matter (WM). Most prior studies of age differences in WM have used diffusion tensor imaging (DTI), but typical DTI metrics (e.g., fractional anisotropy; FA) can reflect multiple neurobiological features, making interpretation challenging. Here, we used fixel-based analysis (FBA) to investigate age-related WM differences observed using DTI in a sample of 45 older and 25 younger healthy adults. Age-related FA differences were widespread but were strongly associated with differences in multi-fiber complexity (CX), suggesting that they reflected differences in crossing fibers in addition to structural differences in individual fiber segments. FBA also revealed a frontolimbic locus of age-related effects and provided insights into distinct microstructural changes underlying them. Specifically, age differences in fiber density were prominent in fornix, bilateral anterior internal capsule, forceps minor, body of the corpus callosum, and corticospinal tract, while age differences in fiber cross section were largest in cingulum bundle and forceps minor. These results provide novel insights into specific structural differences underlying major WM differences associated with aging.
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Affiliation(s)
- Shannon Kelley
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA
| | - John Plass
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Andrew R Bender
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI 48824, USA
| | - Thad A Polk
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA
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de Almeida Martins JP, Tax CMW, Reymbaut A, Szczepankiewicz F, Chamberland M, Jones DK, Topgaard D. Computing and visualising intra-voxel orientation-specific relaxation-diffusion features in the human brain. Hum Brain Mapp 2021; 42:310-328. [PMID: 33022844 PMCID: PMC7776010 DOI: 10.1002/hbm.25224] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/04/2020] [Accepted: 09/22/2020] [Indexed: 12/12/2022] Open
Abstract
Diffusion MRI techniques are used widely to study the characteristics of the human brain connectome in vivo. However, to resolve and characterise white matter (WM) fibres in heterogeneous MRI voxels remains a challenging problem typically approached with signal models that rely on prior information and constraints. We have recently introduced a 5D relaxation-diffusion correlation framework wherein multidimensional diffusion encoding strategies are used to acquire data at multiple echo-times to increase the amount of information encoded into the signal and ease the constraints needed for signal inversion. Nonparametric Monte Carlo inversion of the resulting datasets yields 5D relaxation-diffusion distributions where contributions from different sub-voxel tissue environments are separated with minimal assumptions on their microscopic properties. Here, we build on the 5D correlation approach to derive fibre-specific metrics that can be mapped throughout the imaged brain volume. Distribution components ascribed to fibrous tissues are resolved, and subsequently mapped to a dense mesh of overlapping orientation bins to define a smooth orientation distribution function (ODF). Moreover, relaxation and diffusion measures are correlated to each independent ODF coordinate, thereby allowing the estimation of orientation-specific relaxation rates and diffusivities. The proposed method is tested on a healthy volunteer, where the estimated ODFs were observed to capture major WM tracts, resolve fibre crossings, and, more importantly, inform on the relaxation and diffusion features along with distinct fibre bundles. If combined with fibre-tracking algorithms, the methodology presented in this work has potential for increasing the depth of characterisation of microstructural properties along individual WM pathways.
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Affiliation(s)
- João P. de Almeida Martins
- Division of Physical Chemistry, Department of ChemistryLund UniversityLundSweden
- Random Walk Imaging ABLundSweden
| | - Chantal M. W. Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
- University Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Alexis Reymbaut
- Division of Physical Chemistry, Department of ChemistryLund UniversityLundSweden
- Random Walk Imaging ABLundSweden
| | - Filip Szczepankiewicz
- Department of Clinical SciencesLund UniversityLundSweden
- Harvard Medical SchoolBostonMassachusettsUSA
- Radiology, Brigham and Women's HospitalBostonMassachusettsUSA
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
- Mary MacKillop Institute for Health Research, Australian Catholic UniversityMelbourneAustralia
| | - Daniel Topgaard
- Division of Physical Chemistry, Department of ChemistryLund UniversityLundSweden
- Random Walk Imaging ABLundSweden
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49
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Zhao L, Zhao M, Liu J, Yang H, Zhou X, Wen C, Li G, Duan Y. Mean apparent diffusion coefficient in a single slice may predict tumor response to whole-brain radiation therapy in non-small-cell lung cancer patients with brain metastases. Eur Radiol 2021; 31:5565-5575. [PMID: 33452628 DOI: 10.1007/s00330-020-07584-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 11/09/2020] [Accepted: 12/01/2020] [Indexed: 12/25/2022]
Abstract
OBJECTIVES This study aimed to access the performance of apparent diffusion coefficient (ADC) as a predictor for treatment response to whole-brain radiotherapy (WBRT) in patients with brain metastases (BMs) from non-small-cell lung cancer (NSCLC). METHODS A retrospective analysis was conducted of 102 NSCLC patients with BMs who underwent WBRT between 2012 and 2016. Diffusion-weighted MRI were performed pre-WBRT and within 12 weeks after WBRT started. Mean single-plane ADC value of ROIs was evaluated by two radiologists blinded to results of each other. The treatment response rate, intracranial progression-free survival (PFS), and overall survival (OS) were analyzed based on the ADC value and ΔADC respectively. At last, we used COX and logistic regression to do the multivariate analysis. RESULTS There was good inter-observer agreement of mean ADC value pre-WBRT, post-WBRT, and ΔADC between the 2 radiologists (Pearson correlation 0.915 [pre-WBRT], 0.950 [post-WBRT], 0.937 [ΔADC], p < 0.001, for each one). High mean ADC value were related with better response rate (72.2% vs 37.5%, p = 0.001) and iPFS (7.6 vs 6.4 months, p = 0.031). High ΔADC were related with better response rate (73.6% vs 36.7%, p < 0.001). Multivariate analysis shows that histopathology, BMs number, high ADC value pre-WBRT, and high ΔADC post-WBRT were related to better treatment response of WBRT, and KPS, BMs number, and low ADC value pre-WBRT increased the risk of developing intracranial relapse. CONCLUSIONS The mean single-plane ADC value pre-WBRT and ΔADC post-WBRT were potential predictor for intracranial tumor response to WBRT in NSCLC patients with brain metastases. KEY POINTS • ADC value is a potential predictor of intracranial treatment response to WBRT in NSCLC patients with brain metastases. • Higher mean ADC value pre-WBRT and ΔADC post-WBRT of brain metastases were related to better intracranial tumor response. • Prediction of response before WBRT using ADC value can help oncologists to make better therapy plans and avoid missing opportunities for rescue therapy.
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Affiliation(s)
- Lihao Zhao
- Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, No. 2 Fuxue Lane, Wenzhou, 325000, People's Republic of China
| | - Mengjing Zhao
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, South Baixiang Street, Wenzhou, 325000, People's Republic of China
| | - Jinjin Liu
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, South Baixiang Street, Wenzhou, 325000, People's Republic of China
| | - Han Yang
- Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, No. 2 Fuxue Lane, Wenzhou, 325000, People's Republic of China
| | - Xiaojun Zhou
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, South Baixiang Street, Wenzhou, 325000, People's Republic of China
| | - Caiyun Wen
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, South Baixiang Street, Wenzhou, 325000, People's Republic of China
| | - Gang Li
- Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, No. 2 Fuxue Lane, Wenzhou, 325000, People's Republic of China.
| | - Yuxia Duan
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, South Baixiang Street, Wenzhou, 325000, People's Republic of China.
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50
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Sani I, Stemmann H, Caron B, Bullock D, Stemmler T, Fahle M, Pestilli F, Freiwald WA. The human endogenous attentional control network includes a ventro-temporal cortical node. Nat Commun 2021; 12:360. [PMID: 33452252 PMCID: PMC7810878 DOI: 10.1038/s41467-020-20583-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Accepted: 12/07/2020] [Indexed: 01/29/2023] Open
Abstract
Endogenous attention is the cognitive function that selects the relevant pieces of sensory information to achieve goals and it is known to be controlled by dorsal fronto-parietal brain areas. Here we expand this notion by identifying a control attention area located in the temporal lobe. By combining a demanding behavioral paradigm with functional neuroimaging and diffusion tractography, we show that like fronto-parietal attentional areas, the human posterior inferotemporal cortex exhibits significant attentional modulatory activity. This area is functionally distinct from surrounding cortical areas, and is directly connected to parietal and frontal attentional regions. These results show that attentional control spans three cortical lobes and overarches large distances through fiber pathways that run orthogonally to the dominant anterior-posterior axes of sensory processing, thus suggesting a different organizing principle for cognitive control.
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Affiliation(s)
- Ilaria Sani
- grid.134907.80000 0001 2166 1519Laboratory of Neural Systems, The Rockefeller University, 1230 York Avenue, New York, NY 10065 USA ,grid.8591.50000 0001 2322 4988Laboratory of Neurology & Imaging of Cognition, University of Geneva, Chemin de mines 9, 1202 Geneva, CH Switzerland
| | - Heiko Stemmann
- grid.7704.40000 0001 2297 4381Institute for Brain Research and Center for Advanced Imaging, University of Bremen, 28334 Bremen, Germany
| | - Bradley Caron
- grid.411377.70000 0001 0790 959XDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, IN USA
| | - Daniel Bullock
- grid.411377.70000 0001 0790 959XDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, IN USA
| | - Torsten Stemmler
- grid.7704.40000 0001 2297 4381Institute for Brain Research and Center for Advanced Imaging, University of Bremen, 28334 Bremen, Germany
| | - Manfred Fahle
- grid.7704.40000 0001 2297 4381Institute for Brain Research and Center for Advanced Imaging, University of Bremen, 28334 Bremen, Germany
| | - Franco Pestilli
- grid.411377.70000 0001 0790 959XDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, IN USA ,grid.89336.370000 0004 1936 9924Department of Psychology, The University of Texas at Austin, Austin, TX 78712 USA
| | - Winrich A. Freiwald
- grid.134907.80000 0001 2166 1519Laboratory of Neural Systems, The Rockefeller University, 1230 York Avenue, New York, NY 10065 USA ,Center for Brains, Minds & Machines, Cambridge, MA USA
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