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Joo IL, Lam WW, Oakden W, Hill ME, Koletar MM, Morrone CD, Stanisz GJ, McLaurin J, Stefanovic B. Early alterations in brain glucose metabolism and vascular function in a transgenic rat model of Alzheimer's disease. Prog Neurobiol 2022; 217:102327. [PMID: 35870681 DOI: 10.1016/j.pneurobio.2022.102327] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 05/06/2022] [Accepted: 07/18/2022] [Indexed: 11/28/2022]
Abstract
Alteration in brain metabolism predates clinical onset of Alzheimer's Disease (AD). Realizing its potential as an early diagnostic marker, however, requires understanding how early AD metabolic dysregulation manifests on non-invasive brain imaging. We presently utilized magnetic resonance imaging and spectroscopy to map glucose and ketone metabolic profiles and image cerebrovascular function in a rat model of early stage AD - 9-month-old TgF344-AD (TgAD) rats - and their age-matched non-transgenic (nTg) littermates. Compared to the nTg rats, TgAD rats displayed attenuation in global cerebral and hippocampal vasoreactivity to hypercapnia, by 49±17% and 58±19%, respectively, while their functional hyperemia to somatosensory stimulation diminished by 69±5%. To assess brain glucose uptake, rats were fasted overnight and then challenged with an intravenous infusion of 2-deoxy-D-glucose (2DG). Compared to their non-transgenic littermates, TgAD rats exhibited 99±10% and 52±5% smaller glucose uptake in the entorhinal cortex and the hippocampus, respectively. Moreover, hippocampal glucose uptake reduction in male TgAD rats compared to the nTg was 54±36% greater than the reduction seen in female TgAD rats. TgAD rats also showed a 59±42% increase in total choline level in the hippocampus, suggesting increased membrane turnover. In combination with our earlier findings of impaired electrophysiological metrics at this early stage of AD pathology progression, our findings suggest that subtle neuronal function alterations that would be difficult to assess in a clinical population may be accompanied by MRI-detectable changes in brain glucose metabolism and cerebrovascular function.
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Affiliation(s)
- Illsung L Joo
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 3N5, Canada.
| | - Wilfred W Lam
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 3N5, Canada.
| | - Wendy Oakden
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 3N5, Canada.
| | - Mary E Hill
- Biological Sciences, Sunnybrook Research Institute, Toronto, ON M4N 3N5, Canada.
| | - Margaret M Koletar
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 3N5, Canada.
| | - Christopher D Morrone
- Biological Sciences, Sunnybrook Research Institute, Toronto, ON M4N 3N5, Canada; Department of Laboratory Medicine and Pathology, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
| | - Greg J Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 3N5, Canada; Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, ON M5G 1L7, Canada.
| | - JoAnne McLaurin
- Biological Sciences, Sunnybrook Research Institute, Toronto, ON M4N 3N5, Canada; Department of Laboratory Medicine and Pathology, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
| | - Bojana Stefanovic
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 3N5, Canada; Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, ON M5G 1L7, Canada.
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Saturation transfer MRI is sensitive to neurochemical changes in the rat brain due to chronic unpredictable mild stress. Sci Rep 2021; 11:19040. [PMID: 34561488 PMCID: PMC8463565 DOI: 10.1038/s41598-021-97991-0] [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: 05/14/2021] [Accepted: 08/31/2021] [Indexed: 02/08/2023] Open
Abstract
Chemical exchange saturation transfer (CEST) MRI was performed for the evaluation of cerebral metabolic changes in a rat model of depressive-like disease induced by chronic unpredictable mild stress (CUMS). CEST Z-spectra were acquired on a 7 T MRI with two saturation B1 amplitudes (0.5 and 0.75 µT) to measure the magnetization transfer ratio (MTR), CEST and relayed nuclear Overhauser effect (rNOE). Cerebral cortex and hippocampus were examined in two groups of animals: healthy control (n = 10) and stressed (n = 14), the latter of which was exposed to eight weeks of the CUMS protocol. The stressed group Z-spectrum parameters, primarily MTRs, were significantly lower than in controls, at all selected frequency offsets (3.5, 3.0, 2.0, - 3.2, - 3.6 ppm) in the cortex (the largest difference of ~ 3.5% at - 3.6 ppm, p = 0.0005) and the hippocampus (MTRs measured with a B1 = 0.5 µT). The hippocampal rNOE contributions decreased significantly in the stressed brains. Glutamate concentration (assessed using ELISA) and MTR at 3 ppm correlated positively in both brain regions. GABA concentration also correlated positively with CEST contributions in both cerebral areas, while such correlation with MTR was positive in hippocampus, and nonsignificant in cortex. Results indicate that CEST is sensitive to neurometabolic changes following chronic stress exposure.
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Chan RW, Lawrence LSP, Oglesby RT, Chen H, Stewart J, Theriault A, Campbell M, Ruschin M, Myrehaug S, Atenafu EG, Keller B, Chugh B, MacKenzie S, Tseng CL, Detsky J, Maralani PJ, Czarnota GJ, Stanisz GJ, Sahgal A, Lau AZ. Chemical exchange saturation transfer MRI in central nervous system tumours on a 1.5 T MR-Linac. Radiother Oncol 2021; 162:140-149. [PMID: 34280403 DOI: 10.1016/j.radonc.2021.07.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 07/06/2021] [Accepted: 07/08/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE To describe the implementation and initial results of using Chemical Exchange Saturation Transfer (CEST) for monitoring patients with central nervous system (CNS) tumours treated using a 1.5 tesla MR-guided radiotherapy system. METHODS CNS patients were treated with up to 30 fractions (total dose up to 60 Gy) using a 1.5 T Elekta Unity MR-Linac. CEST scans were obtained in 54 subjects at one or more time points during treatment. CEST metrics, including the amide magnetization transfer ratio (MTRAmide), nuclear Overhauser effect (NOE) MTR (MTRNOE) and asymmetry, were quantified in phantoms and CNS patients. The signal was investigated between tumour and white matter, across time, and across disease categories including high- and low-grade tumours. RESULTS The gross tumour volume (GTV) exhibited lower MTRAmide and MTRNOE and higher asymmetry compared to contralateral normal appearing white matter. Signal changes in the GTV during fractionated radiotherapy were observed. There were differences between high- and low-grade tumours, with higher CEST asymmetry associated with higher grade disease. CONCLUSION CEST MRI using a 1.5 T MR-Linac was demonstrated to be feasible for in vivo imaging of CNS tumours. CEST images showed tumour/white-matter contrast, temporal CEST signal changes, and associations with tumour grade. These results show promise for the eventual goal of using metabolic imaging to inform the design of adaptive radiotherapy protocols.
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Affiliation(s)
- Rachel W Chan
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada.
| | - Liam S P Lawrence
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Ryan T Oglesby
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Hanbo Chen
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - James Stewart
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Aimee Theriault
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Mikki Campbell
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Mark Ruschin
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Eshetu G Atenafu
- Department of Biostatistics, University Health Network, University of Toronto, Toronto, Canada
| | - Brian Keller
- Department of Biostatistics, University Health Network, University of Toronto, Toronto, Canada
| | - Brige Chugh
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada; Department of Physics, Ryerson University, Toronto, Canada
| | - Scott MacKenzie
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Pejman J Maralani
- Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Greg J Czarnota
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Greg J Stanisz
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Department of Neurosurgery and Pediatric Neurosurgery, Medical University of Lublin, Lublin, Poland
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Angus Z Lau
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
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Afarideh M, Jiang K, Ferguson CM, Woollard JR, Glockner JF, Lerman LO. Magnetization Transfer Imaging Predicts Porcine Kidney Recovery After Revascularization of Renal Artery Stenosis. Invest Radiol 2021; 56:86-93. [PMID: 33405430 PMCID: PMC7793546 DOI: 10.1097/rli.0000000000000711] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
MATERIALS AND METHODS Stenotic kidney (STK) and contralateral kidney magnetization transfer ratios (MTRs; Mt/M0) were measured at 3.0-T magnetic resonance imaging, at offset frequencies of 600 and 1000 Hz, before and 1 month post-PTRA in 7 RVD pigs. Stenotic kidney MTR was correlated to renal perfusion, renal blood flow (RBF), and glomerular filtration rate (GFR), determined using multidetector computed tomography and with ex vivo renal fibrosis (trichrome staining). Untreated RVD (n = 6) and normal pigs (n = 7) served as controls. RESULTS Renovascular disease induced hypertension and renal dysfunction. Blood pressure and renal perfusion were unchanged post-PTRA, but GFR and RBF increased. Baseline cortical STK-MTR predicted post-PTRA renal perfusion and RBF, and MTR changes associated inversely with changes in perfusion and normalized GFR. Stenotic kidney MTR at 600 Hz showed closer association with renal parameters, but both frequencies predicted post-PTRA cortical fibrosis. CONCLUSIONS Renal STK-MTR, particularly at 600 Hz offset, is sensitive to hemodynamic changes after PTRA in swine RVD and capable of noninvasively predicting post-PTRA kidney perfusion, RBF, and fibrosis. Therefore, STK-MTR may be a valuable tool to predict renal hemodynamic and functional recovery, as well as residual kidney fibrosis after revascularization in RVD.
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Affiliation(s)
| | - Kai Jiang
- From the Division of Nephrology and Hypertension
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Tan Z, Lam WW, Oakden W, Murray L, Koletar MM, Liu SK, Stanisz GJ. Saturation transfer properties of tumour xenografts derived from prostate cancer cell lines 22Rv1 and DU145. Sci Rep 2020; 10:21315. [PMID: 33277574 PMCID: PMC7718243 DOI: 10.1038/s41598-020-78353-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 11/24/2020] [Indexed: 12/24/2022] Open
Abstract
Histopathology is currently the most reliable tool in assessing the aggressiveness and prognosis of solid tumours. However, developing non-invasive modalities for tumour evaluation remains crucial due to the side effects and complications caused by biopsy procedures. In this study, saturation transfer MRI was used to investigate the microstructural and metabolic properties of tumour xenografts in mice derived from the prostate cancer cell lines 22Rv1 and DU145, which express different aggressiveness. The magnetization transfer (MT) and chemical exchange saturation transfer (CEST) effects, which are associated with the microstructural and metabolic properties in biological tissue, respectively, were analyzed quantitatively and compared amongst different tumour types and regions. Histopathological staining was performed as a reference. Higher cellular density and metabolism expressed in more aggressive tumours (22Rv1) were associated with larger MT and CEST effects. High collagen content in the necrotic regions might explain their higher MT effects compared to tumour regions.
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Affiliation(s)
- Ziyu Tan
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.,Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Wilfred W Lam
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.
| | - Wendy Oakden
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Leedan Murray
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | | | - Stanley K Liu
- Medical Biophysics, University of Toronto, Toronto, ON, Canada.,Radiation Oncology, University of Toronto, Toronto, ON, Canada.,Biological Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.,Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Greg J Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.,Medical Biophysics, University of Toronto, Toronto, ON, Canada.,Neurosurgery and Paediatric Neurosurgery, Medical University of Lublin, Lublin, Poland
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Chan RW, Chen H, Myrehaug S, Atenafu EG, Stanisz GJ, Stewart J, Maralani PJ, Chan AKM, Daghighi S, Ruschin M, Das S, Perry J, Czarnota GJ, Sahgal A, Lau AZ. Quantitative CEST and MT at 1.5T for monitoring treatment response in glioblastoma: early and late tumor progression during chemoradiation. J Neurooncol 2020; 151:267-278. [PMID: 33196965 DOI: 10.1007/s11060-020-03661-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 11/07/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE Quantitative MRI (qMRI) was performed using a 1.5T protocol that includes a novel chemical exchange saturation transfer/magnetization transfer (CEST/MT) approach. The purpose of this prospective study was to determine if qMRI metrics at baseline, at the 10th and 20th fraction during a 30 fraction/6 week standard chemoradiation (CRT) schedule, and at 1 month following treatment could be an early indicator of response for glioblastoma (GBM). METHODS The study included 51 newly diagnosed GBM patients. Four regions-of-interest (ROI) were analyzed: (i) the radiation defined clinical target volume (CTV), (ii) radiation defined gross tumor volume (GTV), (iii) enhancing-tumor regions, and (iv) FLAIR-hyperintense regions. Quantitative CEST, MT, T1 and T2 parameters were compared between those patients progressing within 6.9 months (early), and those progressing after CRT (late), using mixed modelling. Exploratory predictive modelling was performed to identify significant predictors of early progression using a multivariable LASSO model. RESULTS Results were dependent on the specific tumor ROI analyzed and the imaging time point. The baseline CEST asymmetry within the CTV was significantly higher in the early progression cohort. Other significant predictors included the T2 of the MT pools (for semi-solid at fraction 20 and water at 1 month after CRT), the exchange rate (at fraction 20) and the MGMT methylation status. CONCLUSIONS We observe the potential for multiparametric qMRI, including a novel pulsed CEST/MT approach, to show potential in distinguishing early from late progression GBM cohorts. Ultimately, the goal is to personalize therapeutic decisions and treatment adaptation based on non-invasive imaging-based biomarkers.
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Affiliation(s)
- Rachel W Chan
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.
| | - Hanbo Chen
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Eshetu G Atenafu
- Department of Biostatistics, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Greg J Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Department of Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
| | - James Stewart
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | | | - Aimee K M Chan
- Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Shadi Daghighi
- Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Mark Ruschin
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Sunit Das
- Division of Neurosurgery, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - James Perry
- Division of Neurology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Gregory J Czarnota
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Arjun Sahgal
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Angus Z Lau
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
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Kwiatkowski G, Kozerke S. Accelerating CEST MRI in the mouse brain at 9.4 T by exploiting sparsity in the Z-spectrum domain. NMR IN BIOMEDICINE 2020; 33:e4360. [PMID: 32621367 DOI: 10.1002/nbm.4360] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Revised: 05/20/2020] [Accepted: 06/05/2020] [Indexed: 06/11/2023]
Abstract
PURPOSE Chemical exchange saturation transfer (CEST) is an MR contrast modality offering an enhanced sensitivity for the detection of dilute metabolites with exchangeable protons. Quantitative analysis requires the acquisition of a number of images (usually between 20 and 50 RF offsets) per Z-spectrum, leading to long acquisition times of the order of 5-40 min in practice. In this work, we explore the possibility of employing sparsity in the Z-spectrum domain (irradiation offset dimension) to provide an accelerated acquisition scheme without compromising the quality of reconstructed CEST spectra. METHOD AND THEORY Ex vivo and in vivo data were acquired on an experimental, small animal 9.4 T system. Three different reconstruction methods were tested: k-Z SPARSE, k-Z SLR and k-Z principal component analysis (PCA) using retrospective undersampling with net acceleration factors R = 2, 3, 5. The quality of the reconstructed data was compared with respect to CEST spectra and full magnetization transfer ratio (MTR) asymmetry maps. RESULTS In both phantom and in vivo data, CEST spectra and the resulting MTR asymmetry maps were reconstructed without significant deterioration in data quality. For a low acceleration factor (R = 2, 3) all applied methods resulted in similar data quality, while for high acceleration factor (R = 5) only k-Z PCA and k-Z SLR could be used. Loss in spatial resolution was observed in reconstruction with k-Z PCA for all acceleration factors. An example of prospective undersampling with acceleration factor R = 3 and k-Z PCA reconstruction demonstrates improved CEST maps when compared with fully sampled data acquisition with either three times longer scan duration or threefold prolonged acquisition window per frequency offset. CONCLUSION The acquisition time of CEST spectra can be significantly accelerated by exploiting the sparsity of the Z-domain. For prospective and retrospective analysis using k-Z PCA, an acceleration factor of up to R = 3 can be used without significant loss in data quality.
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Affiliation(s)
- Grzegorz Kwiatkowski
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
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Huang X, Schurr RN, Wang S, Miao Q, Li T, Jia G. Development of Radiofrequency Saturation Amplitude-independent Quantitative Markers for Magnetization Transfer MRI of Prostate Cancer. Curr Med Imaging 2020; 16:695-702. [PMID: 32723241 DOI: 10.2174/1573405615666190318153328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 02/06/2019] [Accepted: 03/19/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND In the United States, prostate cancer has a relatively large impact on men's health. Magnetic resonance imaging (MRI) is useful for the diagnosis and treatment of prostate cancer. INTRODUCTION The purpose of this study was to develop a quantitative marker for use in prostate cancer magnetization transfer (MT) magnetic resonance imaging (MRI) studies that is independent of radiofrequency (RF) saturation amplitude. METHODS Eighteen patients with biopsy-proven prostate cancer were enrolled in this study. MTMRI images were acquired using four RF saturation amplitudes at 33 frequency offsets. ROIs were delineated for the peripheral zone (PZ), central gland (CG), and tumor. Z-spectral data were collected in each region and fit to a three-parameter equation. The three parameters are: the magnitude of the bulk water pool (Aw), the full width at half maximum of the water pool (Gw), and the magnitude of the bound pool (Ab), while, the slopes from the linear regressions of Gw and Ab on RF saturation amplitude (called kAb and kGw) were used as quantitative markers. RESULTS A pairwise statistically significant difference was found between the PZ and tumor regions for the two saturation amplitude-independent quantitative markers. No pairwise statistically significant differences were found between the CG and tumor regions for any quantitative markers. CONCLUSION The significant differences between the values of the two RF saturation amplitudeindependent quantitative markers in the PZ and tumor regions reveal that these markers may be capable of distinguishing healthy PZ tissue from prostate cancer.
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Affiliation(s)
- Xunan Huang
- Xi'an Key Laboratory of Big Data and Intelligent Vision, School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Ryan N Schurr
- Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA, 70803, United States
| | - Shuzhen Wang
- Xi'an Key Laboratory of Big Data and Intelligent Vision, School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Qiguang Miao
- Xi'an Key Laboratory of Big Data and Intelligent Vision, School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Tanping Li
- School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, Shaanxi 710071, China
| | - Guang Jia
- Xi'an Key Laboratory of Big Data and Intelligent Vision, School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
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An Automated Segmentation Pipeline for Intratumoural Regions in Animal Xenografts Using Machine Learning and Saturation Transfer MRI. Sci Rep 2020; 10:8063. [PMID: 32415137 PMCID: PMC7228927 DOI: 10.1038/s41598-020-64912-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 04/24/2020] [Indexed: 11/16/2022] Open
Abstract
Saturation transfer MRI can be useful in the characterization of different tumour types. It is sensitive to tumour metabolism, microstructure, and microenvironment. This study aimed to use saturation transfer to differentiate between intratumoural regions, demarcate tumour boundaries, and reduce data acquisition times by identifying the imaging scheme with the most impact on segmentation accuracy. Saturation transfer-weighted images were acquired over a wide range of saturation amplitudes and frequency offsets along with T1 and T2 maps for 34 tumour xenografts in mice. Independent component analysis and Gaussian mixture modelling were used to segment the images and identify intratumoural regions. Comparison between the segmented regions and histopathology indicated five distinct clusters: three corresponding to intratumoural regions (active tumour, necrosis/apoptosis, and blood/edema) and two extratumoural (muscle and a mix of muscle and connective tissue). The fraction of tumour voxels segmented as necrosis/apoptosis quantitatively matched those calculated from TUNEL histopathological assays. An optimal protocol was identified providing reasonable qualitative agreement between MRI and histopathology and consisting of T1 and T2 maps and 22 magnetization transfer (MT)-weighted images. A three-image subset was identified that resulted in a greater than 90% match in positive and negative predictive value of tumour voxels compared to those found using the entire 24-image dataset. The proposed algorithm can potentially be used to develop a robust intratumoural segmentation method.
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Oglesby RT, Lam WW, Stanisz GJ. In vitro characterization of the serotonin biosynthesis pathway by CEST MRI. Magn Reson Med 2020; 84:2389-2399. [DOI: 10.1002/mrm.28281] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 03/09/2020] [Accepted: 03/23/2020] [Indexed: 12/20/2022]
Affiliation(s)
- Ryan T. Oglesby
- Physical Sciences Sunnybrook Research Institute Toronto ON Canada
- Medical Biophysics University of Toronto Toronto ON Canada
| | - Wilfred W. Lam
- Physical Sciences Sunnybrook Research Institute Toronto ON Canada
| | - Greg J. Stanisz
- Physical Sciences Sunnybrook Research Institute Toronto ON Canada
- Medical Biophysics University of Toronto Toronto ON Canada
- Neurosurgery and Pediatric Neurosurgery Medical University of Lublin Lublin Poland
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Pagáčová E, Štefančíková L, Schmidt-Kaler F, Hildenbrand G, Vičar T, Depeš D, Lee JH, Bestvater F, Lacombe S, Porcel E, Roux S, Wenz F, Kopečná O, Falková I, Hausmann M, Falk M. Challenges and Contradictions of Metal Nano-Particle Applications for Radio-Sensitivity Enhancement in Cancer Therapy. Int J Mol Sci 2019; 20:ijms20030588. [PMID: 30704035 PMCID: PMC6387067 DOI: 10.3390/ijms20030588] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 01/24/2019] [Indexed: 12/12/2022] Open
Abstract
From the very beginnings of radiotherapy, a crucial question persists with how to target the radiation effectiveness into the tumor while preserving surrounding tissues as undamaged as possible. One promising approach is to selectively pre-sensitize tumor cells by metallic nanoparticles. However, though the "physics" behind nanoparticle-mediated radio-interaction has been well elaborated, practical applications in medicine remain challenging and often disappointing because of limited knowledge on biological mechanisms leading to cell damage enhancement and eventually cell death. In the present study, we analyzed the influence of different nanoparticle materials (platinum (Pt), and gold (Au)), cancer cell types (HeLa, U87, and SKBr3), and doses (up to 4 Gy) of low-Linear Energy Transfer (LET) ionizing radiation (γ- and X-rays) on the extent, complexity and reparability of radiation-induced γH2AX + 53BP1 foci, the markers of double stand breaks (DSBs). Firstly, we sensitively compared the focus presence in nuclei during a long period of time post-irradiation (24 h) in spatially (three-dimensionally, 3D) fixed cells incubated and non-incubated with Pt nanoparticles by means of high-resolution immunofluorescence confocal microscopy. The data were compared with our preliminary results obtained for Au nanoparticles and recently published results for gadolinium (Gd) nanoparticles of approximately the same size (2⁻3 nm). Next, we introduced a novel super-resolution approach-single molecule localization microscopy (SMLM)-to study the internal structure of the repair foci. In these experiments, 10 nm Au nanoparticles were used that could be also visualized by SMLM. Altogether, the data show that different nanoparticles may or may not enhance radiation damage to DNA, so multi-parameter effects have to be considered to better interpret the radiosensitization. Based on these findings, we discussed on conclusions and contradictions related to the effectiveness and presumptive mechanisms of the cell radiosensitization by nanoparticles. We also demonstrate that SMLM offers new perspectives to study internal structures of repair foci with the goal to better evaluate potential differences in DNA damage patterns.
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Affiliation(s)
- Eva Pagáčová
- Czech Academy of Sciences, Institute of Biophysics, v.v.i., Kralovopolska 135, 612 65 Brno, Czech Republic.
| | - Lenka Štefančíková
- Czech Academy of Sciences, Institute of Biophysics, v.v.i., Kralovopolska 135, 612 65 Brno, Czech Republic.
- Institute des Sciences Moléculaires d'Orsay (ISMO), Université Paris Saclay, Université Paris Sud, CNRS, 91405 Orsay Cedex, France.
| | - Franz Schmidt-Kaler
- Kirchhoff-Institute for Physics, University of Heidelberg, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany.
| | - Georg Hildenbrand
- Kirchhoff-Institute for Physics, University of Heidelberg, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany.
- Department of Radiation Oncology, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, 68159 Mannheim, Germany.
| | - Tomáš Vičar
- Brno University of Technology, Department of Biomedical Engineering, Technická 3082/12, 61600 Brno, Czech Republic.
| | - Daniel Depeš
- Czech Academy of Sciences, Institute of Biophysics, v.v.i., Kralovopolska 135, 612 65 Brno, Czech Republic.
| | - Jin-Ho Lee
- Kirchhoff-Institute for Physics, University of Heidelberg, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany.
| | - Felix Bestvater
- German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
| | - Sandrine Lacombe
- Institute des Sciences Moléculaires d'Orsay (ISMO), Université Paris Saclay, Université Paris Sud, CNRS, 91405 Orsay Cedex, France.
| | - Erika Porcel
- Institute des Sciences Moléculaires d'Orsay (ISMO), Université Paris Saclay, Université Paris Sud, CNRS, 91405 Orsay Cedex, France.
| | - Stéphane Roux
- Institute UTINAM, UMR CNRS 6213-Université de Bourgogne Franche-Comté, 25020 Besançon Cedex, France.
| | - Frederik Wenz
- Department of Radiation Oncology, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, 68159 Mannheim, Germany.
| | - Olga Kopečná
- Czech Academy of Sciences, Institute of Biophysics, v.v.i., Kralovopolska 135, 612 65 Brno, Czech Republic.
| | - Iva Falková
- Czech Academy of Sciences, Institute of Biophysics, v.v.i., Kralovopolska 135, 612 65 Brno, Czech Republic.
| | - Michael Hausmann
- Kirchhoff-Institute for Physics, University of Heidelberg, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany.
| | - Martin Falk
- Czech Academy of Sciences, Institute of Biophysics, v.v.i., Kralovopolska 135, 612 65 Brno, Czech Republic.
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