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Wang Z, Cao X, LaBella A, Zeng X, Biegon A, Franceschi D, Petersen E, Clayton N, Ulaner GA, Zhao W, Goldan AH. High-resolution and high-sensitivity PET for quantitative molecular imaging of the monoaminergic nuclei: A GATE simulation study. Med Phys 2022; 49:4430-4444. [PMID: 35390182 PMCID: PMC11025683 DOI: 10.1002/mp.15653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 02/03/2022] [Accepted: 03/07/2022] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Quantitative in vivo molecular imaging of fine brain structures requires high-spatial resolution and high-sensitivity. Positron emission tomography (PET) is an attractive candidate to introduce molecular imaging into standard clinical care due to its highly targeted and versatile imaging capabilities based on the radiotracer being used. However, PET suffers from relatively poor spatial resolution compared to other clinical imaging modalities, which limits its ability to accurately quantify radiotracer uptake in brain regions and nuclei smaller than 3 mm in diameter. Here we introduce a new practical and cost-effective high-resolution and high-sensitivity brain-dedicated PET scanner, using our depth-encoding Prism-PET detector modules arranged in a conformal decagon geometry, to substantially reduce the partial volume effect and enable accurate radiotracer uptake quantification in small subcortical nuclei. METHODS Two Prism-PET brain scanner setups were proposed based on our 4-to-1 and 9-to-1 coupling of scintillators to readout pixels using1.5 × 1.5 × 20 $1.5 \times 1.5 \times 20$ mm3 and0.987 × 0.987 × 20 $0.987 \times 0.987 \times 20$ mm3 crystal columns, respectively. Monte Carlo simulations of our Prism-PET scanners, Siemens Biograph Vision, and United Imaging EXPLORER were performed using Geant4 application for tomographic emission (GATE). National Electrical Manufacturers Association (NEMA) standard was followed for the evaluation of spatial resolution, sensitivity, and count-rate performance. An ultra-micro hot spot phantom was simulated for assessing image quality. A modified Zubal brain phantom was utilized for radiotracer imaging simulations of 5-HT1A receptors, which are abundant in the raphe nuclei (RN), and norepinephrine transporters, which are highly concentrated in the bilateral locus coeruleus (LC). RESULTS The Prism-PET brain scanner with 1.5 mm crystals is superior to that with 1 mm crystals as the former offers better depth-of-interaction (DOI) resolution, which is key to realizing compact and conformal PET scanner geometries. We achieved uniform 1.3 mm full-width-at-half-maximum (FWHM) spatial resolutions across the entire transaxial field-of-view (FOV), a NEMA sensitivity of 52.1 kcps/MBq, and a peak noise equivalent count rate (NECR) of 957.8 kcps at 25.2 kBq/mL using 450-650 keV energy window. Hot spot phantom results demonstrate that our scanner can resolve regions as small as 1.35 mm in diameter at both center and 10 cm away from the center of the transaixal FOV. Both 5-HT1A receptor and norepinephrine transporter brain simulations prove that our Prism-PET scanner enables accurate quantification of radiotracer uptake in small brain regions, with a 1.8-fold and 2.6-fold improvement in the dorsal RN as well as a 3.2-fold and 4.4-fold improvement in the bilateral LC compared to the Biograph Vision and EXPLORER, respectively. CONCLUSIONS Based on our simulation results, the proposed high-resolution and high-sensitivity Prism-PET brain scanner is a promising cost-effective candidate to achieve quantitative molecular neuroimaging of small but important brain regions with PET clinically viable.
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Affiliation(s)
- Zipai Wang
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Xinjie Cao
- Department of Electrical and Computer Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Andy LaBella
- Department of Radiology, Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Xinjie Zeng
- Department of Electrical and Computer Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Anat Biegon
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
| | - Dinko Franceschi
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
| | - Eric Petersen
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Nicholas Clayton
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
| | - Gary A. Ulaner
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Molecular Imaging and Therapy, Hoag Family Cancer Institute, Newport Beach, California, USA
| | - Wei Zhao
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
| | - Amir H. Goldan
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
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Wang Y, Liu Z, Sun D, Sun L, Cao G, Dai J. The Connectome and Chemo-Connectome Databases for Mice Brain Connection Analysis. Front Neuroanat 2022; 16:886925. [PMID: 35756500 PMCID: PMC9218099 DOI: 10.3389/fnana.2022.886925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
The various brain functions rely on the intricate connection networks and certain molecular characteristics of neurons in the brain. However, the databases for the mouse brain connectome and chemo-connectome are still inadequate, hindering the brain circuital and functional analysis. Here, we created mice brain connectome and chemo-connectome databases based on mouse brain projection data of 295 non-overlapping brain areas and in situ hybridization (ISH) data of 50 representative neurotransmission-related genes from the Allen Brain Institute. Based on this connectome and chemo-connectome databases, functional connection patterns and detailed chemo-connectome for monoaminergic nuclei were analyzed and visualized. These databases will aid in the comprehensive research of the mouse connectome and chemo-connectome in the whole brain and serve as a convenient resource for systematic analysis of the brain connection and function.
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Affiliation(s)
- Yang Wang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.,College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Zhixiang Liu
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.,College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.,Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
| | - Da Sun
- College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - Leqiang Sun
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.,College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Gang Cao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.,College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.,Biomedical Center, Huazhong Agricultural University, Wuhan, China
| | - Jinxia Dai
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.,College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
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de la Cruz F, Wagner G, Schumann A, Suttkus S, Güllmar D, Reichenbach JR, Bär KJ. Interrelations between dopamine and serotonin producing sites and regions of the default mode network. Hum Brain Mapp 2021; 42:811-823. [PMID: 33128416 PMCID: PMC7814772 DOI: 10.1002/hbm.25264] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 10/05/2020] [Accepted: 10/14/2020] [Indexed: 12/13/2022] Open
Abstract
Recent functional magnetic resonance imaging (fMRI) studies showed that blood oxygenation level-dependent (BOLD) signal fluctuations in the default mode network (DMN) are functionally tightly connected to those in monoaminergic nuclei, producing dopamine (DA), and serotonin (5-HT) transmitters, in the midbrain/brainstem. We combined accelerated fMRI acquisition with spectral Granger causality and coherence analysis to investigate causal relationships between these areas. Both methods independently lead to similar results and confirm the existence of a top-down information flow in the resting-state condition, where activity in core DMN areas influences activity in the neuromodulatory centers producing DA/5-HT. We found that latencies range from milliseconds to seconds with high inter-subject variability, likely attributable to the resting condition. Our novel findings provide new insights into the functional organization of the human brain.
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Affiliation(s)
- Feliberto de la Cruz
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Germany
| | - Gerd Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Germany
| | - Andy Schumann
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Germany
| | - Stefanie Suttkus
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Germany
| | - Daniel Güllmar
- Medical Physics Group, Department of Diagnostic and Interventional Radiology, Jena University Hospital, Germany
| | - Jürgen R Reichenbach
- Medical Physics Group, Department of Diagnostic and Interventional Radiology, Jena University Hospital, Germany
| | - Karl-Jürgen Bär
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Germany
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