CAREER: Image critical dental diseases that current dental X-ray/CT fails to detect, without ionizing radiation

职业：在没有电离辐射的情况下对当前牙科 X 射线/CT 无法检测到的严重牙科疾病进行成像

• 批准号: 2046929
• 负责人: Jian Xu
• 金额: $ 50万
• 依托单位: Louisiana State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2046929&HistoricalAwards=false
• 关键词: CAREER; Image; critical; dental; diseases

More than 2/3 of Americans have to receive dental imaging routinely. Current dental diagnosis largely relies on dental X-ray/CT (computed tomography), with several major drawbacks: 1) current dental X-ray/CT fails to detect some critical diseases with high incidence rates: for instance, 34-74% of people have tooth cracks. Due to highly variable symptoms, crack is notoriously difficult to be diagnosed even for experienced dentists. 2) the ionizing radiation of dental X-ray was found to increase the risk of meningioma, thyroid cancer, and delivery of low-birth-weight baby. Ionizing radiation is more concerned in children, as they are required to take 3-6 times more frequent dental X-ray/CT, and in dental professionals, as they operate X-ray/CT much more frequently, than normal patients. 3) It is also challenging to hold bulky X-ray/CT sensor immobile by many people, such as children. This project is to address these drawbacks by developing a novel dental imaging scheme with a lab-designed sensitive near-infrared fluorescence photonic imaging system, consisting of a high-resolution camera and a spectroscopic device, for real-time dental imaging. In addition, this project will teach students and educate the general public on the cutting-edge bio-imaging knowledge to help them tackle practical challenges, such as COVID-19.The project goal is to develop a sensitive near-infrared fluorescence imaging system, including a high-resolution camera and a spectroscopic device, together with nanofluorophore, to image critical dental structures and diseases, including those undetectable by state-of-the-art dental X-ray/CT, in real time, and to eliminate the risks of ionizing radiation and the necessity of biting bulky sensors immobile. To achieve the goal, the following approaches are to be used: 1) Design a high-resolution dental imaging system and study the fundamental mechanism of dye distribution in dental tissues and the impact of dye distribution on imaging performance; 2) Systematically compare this dental imaging scheme to other state-of-the-art imaging modalities on critical dental diseases and structures on both animal and human teeth; 3) Optimize the dental imaging strategy with indocyanine green delivery by mouthwash. The research activity of this project has intellectual significances in several aspects: A) This research advances interdisciplinary knowledge. First, this research may advance the fundamental understanding of bio-distributions of dye in soft and hard biomaterials. FDA-approved near-infrared dye, the indocyanine green, is well understood for the distribution into soft tissues via blood and lymphatic circulations. However, how indocyanine green is distributed into hard structures, such as teeth, remains unknown. This study will investigate the indocyanine green distribution approaches in hard structures, how the biodistribution is affected by imaging factors (for example, dye dosage, observation time) and how these factors may quantitatively impact the imaging performance. Second, this research advances the fundamental understanding of how hard and soft biostructures interacts with different electromagnetic waves (such as near-infrared I (700-1000 nm), near-infrared II (1000-1700 nm), and X-ray) and how these interactions impact the choice of electromagnetic waves and imaging parameters when imaging various dental diseases. B) This work is innovative in the field of dental imaging. This work employs FDA-approved indocyanine green as a biocompatible near-infrared II fluorophore to facilitate the translation of human applications, and a user-friendly “mouthwash” delivery of dye, as opposed to the traditional intravenous injection; both are the pioneering works in the field. C) This work is transformative. In contrast with the current dental X-ray/CT (10-2-101 nm) imaging, this works uses completely different light (700-1700 nm) to eliminate the ionizing radiation, thus leading to the revolutionary change of dental practice by providing continuous real-time dental imaging at various angles/distances without health concerns.This project is being jointly funded by Electrical, Communications and Cyber Systems (ECCS) in Engineering Directorate and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

超过三分之二的美国人必须定期接受牙科成像。目前的牙科诊断主要依靠牙科X射线/CT（计算机断层扫描），有几个主要缺点：1）目前的牙科X射线/CT无法发现一些发病率很高的危重疾病：例如，34-74%的人有牙齿裂缝。由于高度可变的症状，裂纹是出了名的难以诊断，即使是有经验的牙医。2)牙科X光的电离辐射被发现会增加脑膜瘤、甲状腺癌和低出生体重婴儿的风险。电离辐射在儿童中更受关注，因为他们需要接受3-6倍的牙科X光/CT检查，在牙科专业人员中，因为他们比正常患者更频繁地操作X光/CT。3)将笨重的X射线/CT传感器固定在许多人（诸如儿童）的手中也是具有挑战性的。该项目是通过开发一种新型的牙科成像方案来解决这些缺点，该方案具有实验室设计的灵敏的近红外荧光光子成像系统，该系统由高分辨率相机和光谱设备组成，用于实时牙科成像。此外，该项目还将向学生和公众传授前沿生物成像知识，以帮助他们应对实际挑战，例如COVID-19。该项目的目标是开发一种灵敏的近红外荧光成像系统，包括高分辨率相机和光谱设备，以及纳米荧光团，以成像关键的牙齿结构和疾病，包括那些不能被现有技术的牙科X射线/CT检测到的，在真实的时间，并消除电离辐射的风险和咬笨重的传感器不动的必要性。本研究的主要目的是：1）设计一种高分辨率的牙科成像系统，研究染料在牙体组织中分布的基本机制以及染料分布对成像性能的影响; 2）系统地比较该成像系统与其他成像系统在牙体组织中的成像效果; 3）通过漱口水递送吲哚菁绿色优化牙科成像策略。本项目的研究活动具有以下几个方面的知识意义：A）本研究促进了跨学科知识的发展。首先，这项研究可能会促进染料在软，硬生物材料中的生物分布的基本理解。FDA批准的近红外染料吲哚菁绿色通过血液和淋巴循环分布到软组织中。然而，吲哚菁绿色如何分布到坚硬的结构中，如牙齿，仍然是未知的。本研究将探讨吲哚菁绿色在硬结构中的分布途径，成像因素（例如，染料剂量，观察时间）如何影响生物分布，以及这些因素如何定量影响成像性能。其次，这项研究推进了对硬和软生物结构如何与不同电磁波（如近红外I（700-1000 nm），近红外II（1000-1700 nm）和X射线）相互作用的基本理解，以及这些相互作用如何影响各种牙科疾病成像时电磁波和成像参数的选择。B）这项工作在牙科成像领域具有创新性。这项工作采用FDA批准的吲哚菁绿色作为生物相容性近红外II荧光团，以促进人类应用的翻译，以及用户友好的“漱口水”输送染料，而不是传统的静脉注射;两者都是该领域的开创性工作。（3）这项工作是变革性的。与目前的牙科X射线/CT相比，（10-2-101纳米）成像，这部作品使用完全不同的光（700-1700 nm），消除电离辐射，从而通过在各种角度/距离提供连续实时牙科成像而不会引起健康问题，从而导致牙科实践的革命性变化。该项目由电气，通信和网络系统（ECCS）工程理事会和既定计划，以刺激竞争力的研究（EPSCoR）。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Nearly-lossless-to-lossy medical image compression by the optimized JPEGXT and JPEG algorithms through the anatomical regions of interest

• DOI: 10.1016/j.bspc.2023.104711
• 发表时间: 2023-02-23
• 期刊: BIOMEDICAL SIGNAL PROCESSING AND CONTROL
• 影响因子: 5.1
• 作者: Li, Zhongqiang;Ramos, Alexandra;Xu, Jian
• 通讯作者: Xu, Jian

Detection of pancreatic cancer by convolutional-neural-network-assisted spontaneous Raman spectroscopy with critical feature visualization

• DOI: 10.1016/j.neunet.2021.09.006
• 发表时间: 2021-09-25
• 期刊: NEURAL NETWORKS
• 影响因子: 7.8
• 作者: Li, Zhongqiang;Li, Zheng;Xu, Jian
• 通讯作者: Xu, Jian

Machine-learning-assisted spontaneous Raman spectroscopy classification and feature extraction for the diagnosis of human laryngeal cancer

• DOI: 10.1016/j.compbiomed.2022.105617
• 发表时间: 2022-05-21
• 期刊: COMPUTERS IN BIOLOGY AND MEDICINE
• 影响因子: 7.7
• 作者: Li, Zheng;Li, Zhongqiang;Xu, Jian
• 通讯作者: Xu, Jian

A novel method for detection of pancreatic Ductal Adenocarcinoma using explainable machine learning

• DOI: 10.1016/j.cmpb.2024.108019
• 发表时间: 2024-01
• 期刊: Computer methods and programs in biomedicine
• 影响因子: 6.1
• 作者: Murtaza Aslam;Fozia Rajbdad;Shoaib Azmat;Zheng Li;J. Boudreaux;R. Thiagarajan;Shaomian Yao;Jian Xu

An optimized JPEG-XT-based algorithm for the lossy and lossless compression of 16-bit depth medical image

一种基于 JPEG-XT 的优化算法，用于 16 位深度医学图像的有损和无损压缩

• DOI: 10.1016/j.bspc.2020.102306
• 发表时间: 2021
• 期刊: Biomedical Signal Processing and Control
• 影响因子: 5.1
• 作者: Li, Zhongqiang;Ramos, Alexandra;Li, Zheng;Osborn, Michelle L.;Li, Xin;Li, Yanping;Yao, Shaomian;Xu, Jian
• 通讯作者: Xu, Jian