Center for Molecular Imaging Technology & Translation (CMITT)

分子成像技术中心

• 批准号: 10807429
• 负责人: Georges El Fakhri
• 金额: $ 41.68万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-30 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10807429
• 关键词: Acceleration; Adoption; Affect; Anatomy; Animal Model; Artificial Intelligence; Australia; Award; B-Lymphocytes; Biochemical; Biochemical Reaction; Biological Markers; Biomedical Engineering; Brain; Canada; Cellular Membrane; Communities; Country; Data; Data Science; Demyelinations; Development; Direct Costs; Discipline; Disease; Drug Kinetics; Educational workshop; Electrophysiology (science); Endowment; Engineering; Environment; Evolution; Faculty; Funding; General Hospitals; Geography; Goals; Growth; Heart; Hospitals; Human; Image; Imaging technology; Immune response; Institution; International; Joints; Kinetics; Knowledge; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Malignant Neoplasms; Manufacturer; Maps; Massachusetts; Measurement; Measures; Medical Imaging; Medical center; Membrane Potentials; Methodology; Methods; Modality; Modeling; Molecular; Molecular Probes; Motion; National Institute of Biomedical Imaging and Bioengineering; Normal tissue morphology; Organ; Pathway interactions; Photons; Physicians; Physics; Physiological; Physiology; Positioning Attribute; Positron-Emission Tomography; Postdoctoral Fellow; Potassium Channel; Property; Radiochemistry; Radiolabeled; Radiology Specialty; Research; Resources; Science; Scientist; Services; Signal Transduction; Site; Skeletal Muscle; Students; System; T-Lymphocyte; Technology; Training; Translating; Translations; Uncertainty; Vision; Visualization; Work; attenuation; biomedical imaging; chemical reaction; clinical translation; collaborative environment; data analysis pipeline; deep learning; design; first-in-human; image reconstruction; image translation; imaging agent; imaging facilities; imaging modality; imaging scientist; innovation; interest; kinetic model; mitochondrial membrane; molecular imaging; monocyte; nanoparticle; novel; radioligand; radiotracer; reconstruction; skills; soft tissue; spectroscopic imaging; technology development; temporal measurement; tomography; trafficking; training opportunity; transfer learning; translational approach

Project Summary / Abstract for the Center for Molecular Imaging Technology and Translation The Center for Molecular Imaging Technology and Translation (CMITT) is a National Center for Biomedical Imaging and Bioengineering located within the Gordon Center for Medical Imaging (GCMI) at the Massachusetts General Hospital. Working within the interdisciplinary environment (e.g., imaging and data sciences; image reconstruction, processing and AI; pharmacokinetics; radiochemistry) of the Gordon Center, the aim of the CMITT is to develop, validate and disseminate cutting-edge imaging technologies that take advantage of the game-changing capabilities afforded by simultaneous acquisition of PET and MR. CMITT approaches PET/MR as a truly synergistic modality, with novel radiochemistry, kinetic modeling, quantitative methods, image reconstruction and AI that exploit properties of PET and MR signals. Thus CMITT advances the methodology of PET/MR and covers the entire range of radiochemistry/radiopharmacy to image formation and processing including tomographic reconstruction and estimation/quantitation, paving the way for research applications and clinical translation. Our pioneering work during the initial funding cycle, Y1-4, of our P41 in quantitative PET/MR, has provided solutions to some of the most vexing problems affecting PET/MR, including reliable and accurate corrections for attenuation and involuntary subject motion (TR&D 1 in Y1-4). We have provided unique contributions to PET quantitation and image reconstruction by using deep learning (TR&D 2 in Y1-4). We have also advanced novel radioligands and new molecular measurements, starting from first concept to actual application (TR&D 3 in Y1-4). Accordingly, in this renewal application, we are in a strong position to propose and develop new field-leading technologies pertaining to Molecular Imaging using PET and MR. The TR&D1 of the renewal develops and delivers multi-parametric quantitative PET/MR imaging technologies that not only enable physiological high-impact novel PET/MR but will also benefit standalone MR research. The TR&D2 of the renewal develops an innovative artificial intelligence-based pipeline of data processing in PET/MR, including image reconstruction, transfer learning, and uncertainty estimation. The TR&D3 of the renewal uses the developments achieved in TR&Ds 1&2 to translate applications of PET/MR from physiological concept to measurements in animal models and then on to first-in-human studies. The National Resource provides a unique environment with an interdisciplinary team of highly accomplished scientists, engineers, and clinicians with diverse expertise in multiple modalities and disciplines that supports service use of the Center's facilities by imaging scientists throughout the country as well as Canada and Australia. CMITT will provide extensive training opportunities for students, post-doctoral fellows, and faculty, and seeks to advance the field of molecular imaging of normal function and disease through active dissemination of new knowledge and technology.

分子影像技术与翻译中心项目概要/摘要 分子成像技术和翻译中心（CMITT）是一个国家生物医学中心， 位于马萨诸塞州戈登医学成像中心（GCMI）的成像和生物工程 综合医院在跨学科环境中工作（例如，成像与数据科学 重建，处理和AI;药代动力学;放射化学），CMITT的目的是 开发、验证和传播尖端成像技术，利用改变游戏规则的 CMITT将PET/MR作为一种真正的协同方法， 模态，具有新颖的放射化学，动力学建模，定量方法，图像重建和AI， PET和MR信号的特性。因此，CMITT推进了PET/MR的方法并涵盖了整个范围 放射化学/放射性药物学对图像形成和处理的影响，包括断层重建， 估计/定量，为研究应用和临床翻译铺平道路。我们的开创性工作， 我们的P41定量PET/MR的最初资助周期Y1 - 4为一些最令人烦恼的问题提供了解决方案， 影响PET/MR的问题，包括衰减和受试者不自主运动的可靠和准确校正 (TR& D 1 in Y1 - 4）.我们已经提供了独特的贡献，PET定量和图像重建， 深度学习（TR & D 2 in Y1 - 4）。我们还开发了新的放射性配体和新的分子测量方法， 从最初的概念到实际应用（Y1 - 4的TR & D 3）。因此，在此更新申请中，我们在 在提出和开发与使用PET的分子成像相关的新的领域领先技术方面处于有利地位 更新的TR&D1开发并提供多参数定量PET/MR成像 技术不仅能够实现生理高影响的新型PET/MR，而且还将使独立MR受益 research.更新的TR&D2开发了一种创新的基于人工智能的数据处理管道 在PET/MR中，包括图像重建、迁移学习和不确定性估计。更新的TR&D3 使用TR & Ds 1&2中取得的进展，将PET/MR的应用从生理学概念转化为 在动物模型中进行测量，然后进行首次人体研究。国家资源提供了一个独特的 环境与高度成就的科学家，工程师和临床医生的跨学科团队，具有不同的 在多种模式和学科的专业知识，支持成像科学家使用中心的设施服务 全国各地以及加拿大和澳大利亚。CMITT将提供广泛的培训机会， 学生，博士后研究员和教师，并寻求推进正常功能的分子成像领域 通过积极传播新知识和新技术来防治疾病。

项目成果

VoxelHop: Successive Subspace Learning for ALS Disease Classification Using Structural MRI.

• DOI: 10.1109/jbhi.2021.3097735
• 发表时间: 2022-03
• 期刊: IEEE journal of biomedical and health informatics
• 影响因子: 7.7
• 作者: Liu X;Xing F;Yang C;Kuo CJ;Babu S;Fakhri GE;Jenkins T;Woo J
• 通讯作者: Woo J

A Comprehensive Primer on Radiation Oncology for Non-Radiation Oncologists.

• DOI: 10.3390/cancers15204906
• 发表时间: 2023-10-10
• 期刊: CANCERS
• 影响因子: 5.2
• 作者: Beddok, Arnaud;Lim, Ruth;Thariat, Juliette;Shih, Helen A.;El Fakhri, Georges
• 通讯作者: El Fakhri, Georges

PET imaging studies to investigate functional expression of mGluR2 using [11C]mG2P001.

使用 [11C]mG2P001 进行 PET 成像研究以研究 mGluR2 的功能表达。

• DOI: 10.1177/0271678x221130387
• 发表时间: 2023
• 期刊: Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
• 作者: Yuan,Gengyang;Dhaynaut,Maeva;Guehl,NicolasJ;Neelamegam,Ramesh;Moon,Sung-Hyun;Qu,Xiying;Poutiainen,Pekka;Afshar,Sepideh;Fakhri,GeorgesEl;Normandin,MarcD;Brownell,Anna-Liisa
• 通讯作者: Brownell,Anna-Liisa

Preclinical Validation of a Single-Scan Rest/Stress Imaging Technique for 13N-Ammonia Positron Emission Tomography Cardiac Perfusion Studies.

用于 13N-氨正电子发射断层扫描心脏灌注研究的单扫描静息/应激成像技术的临床前验证。

• DOI: 10.1161/circimaging.119.009407
• 发表时间: 2020
• 期刊: Circulation. Cardiovascular imaging
• 作者: Guehl,NicolasJ;Pelletier-Galarneau,Matthieu;Wooten,DustinW;Guerrero,JLuis;Kas,Aurélie;Normandin,MarcD;Fakhri,GeorgesEl;Alpert,NathanielM
• 通讯作者: Alpert,NathanielM

Attentive continuous generative self-training for unsupervised domain adaptive medical image translation.

• DOI: 10.1016/j.media.2023.102851
• 发表时间: 2023-08
• 期刊: MEDICAL IMAGE ANALYSIS
• 影响因子: 10.9
• 作者: Liu, Xiaofeng;Prince, Jerry L.;Xing, Fangxu;Zhuo, Jiachen;Reese, Timothy;Stone, Maureen;El Fakhri, Georges;Woo, Jonghye
• 通讯作者: Woo, Jonghye