Clinical Evaluation of Burns using Spatial Frequency Domain Imaging

使用空间频域成像对烧伤进行临床评估

基本信息

批准号：
10453731
负责人：
ANTHONY J DURKIN
金额：
$ 38.9万
依托单位：
UNIVERSITY OF CALIFORNIA-IRVINE
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-01 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10453731
关键词：
Address Admission activity Animal Model Area Biometry Blood Vessels Burn Centers Burn injury Calibration Categories Cicatrix Classification Clinic Clinical Clinical assessments Collaborations Custom Data Detection Devices Diagnosis Diagnostic Enrollment Eye Family suidae Female Friends Hemoglobin Hospitalization Hour Hybrids Image Imaging Device Injury Laser Speckle Imaging Lasers Light Lighting Machine Learning Maps Measurement Measures Medical center Methods Modality Modeling Morphologic artifacts Motion Noise Optics Output Patients Physicians Principal Investigator Property Reporting Research Severities Side Signal Transduction Skin Spatial Frequency Domain Imaging System Techniques Testing Thick Time Tissues Training Translating Ulcer Variant Visual Water Work burden of illness burn model burn wound care costs clinical imaging cost data acquisition data integrity data modeling data reduction diverse data experience healing human data imaging system impression improved in vivo infection rate machine learning classification male next generation novel optical imaging porcine model pre-clinical programs research clinical testing second degree burn stability testing third degree burn treatment planning

项目摘要

Program Director/Principal Investigator (Last, First, Middle): Durkin, Anthony J. Abstract The central aim of this 3 year competing R01 renewal is to characterize and apply a new, compact, clinic- friendly Spatial Frequency Domain Imaging (SFDI) device to objectively and non-invasively classify burn severity (burn grade) over a large areas of skin. Delays in determining burn severity directly impacts patient treatment plans (including decisions whether to graft), rates of infection and scarring, duration of hospitalization and ultimately cost of care. Currently, the primary method of determining burn severity continues to be clinical assessment, which is highly subjective. While both superficial thickness and full-thickness burns are typically readily diagnosed based on visual clinical impression, partial thickness burns are difficult to classify and carry with them considerable potential for complications. Burn severity classification accuracy, even by experts, is only 60–80%. Our research in animal models demonstrates that SFDI data can successfully be used to classify different regions of burn severities. Typically, these differences are not apparent to the unaided eye and a great deal of training and experience is required in order for clinicians to accurately differentiate them Our work using a research grade, hybrid-SFDI device suggests that objective parameters provided by SFDI can be used within 24 hours after injury, to accurately classify burn severity. Specifically, we have demonstrated in a porcine burn model that the research grade SFDI outperforms laser speckle imaging and thermal imaging at 24 hours post-burn, in terms of predicting whether a burn will require a graft or not. However, translating these results to the clinic has been difficult due to several device limitations. The research grade SFDI device has slow acquisition times that can result in motion artifacts. It is also sensitive to ambient light which is often an issue in a clinical setting. Additionally, the SFDI device generates so much diverse data (oxygenated and deoxygenated hemoglobin, water fraction, reduced scattering coefficients at multiple wavelengths), there is no obvious way to present it to a clinical user to make a quick decision. To this end, we propose to methodically investigate an improved next generation SFDI device that addresses these issues by using brighter LEDs and fewer wavelengths to rapidly collect data in a way that reduces motion artifacts and is independent of clinical lighting conditions. In addition, we will develop a machine learning based classification framework that will provide the clinical with actionalble diagnostic information. The central aim of this 3 year competing R01 renewal is to characterize and then modify a new clinic-friendly SFDI device (Clarifi) to objectively classify in- vivo regions of different burn severity over large areas. The proposed research seeks to investigate this via the following Specific Aims: 1) Test & Validate Clinical SFDI Instrument, 2) Compare Clinical SFDI Instrument to other Modalities on a Long Term Swine Model of Graded Burns, 3) Develop Spatially Resolved Classification Maps of Burn Severity based on SFDI Data, 4) Conduct Clinical Measurements of Burn Severity using the new SFDI device and Spatially Resolved Burn Severity Classification Maps based on SFDI data.

项目总监/首席研究员（最后、第一、中间）：Durkin, Anthony J. 抽象的 R01 更新为期 3 年的竞争性更新的中心目标是描述和应用一种新的、紧凑的临床- 友好的空间频域成像 (SFDI) 设备，可客观、非侵入性地对烧伤进行分类大面积皮肤的严重程度（烧伤等级）的延迟确定会直接影响患者。治疗计划（包括是否移植的决定）、感染率和疤痕形成率、住院时间目前，确定烧伤严重程度的主要方法仍然是临床。评估，这是非常主观的，而浅层烧伤和全层烧伤通常都是主观的。根据视觉临床印象很容易诊断，部分厚度烧伤难以分类和携带即使对于专家来说，烧伤严重程度分类的准确性也有很大的可能性。我们对动物模型的研究表明，SFDI 数据可以成功用于分类。通常，这些差异对于肉眼和肉眼来说并不明显。步兵需要大量的训练和经验才能准确区分他们我们的工作使用研究级混合 SFDI 设备表明可以使用 SFDI 提供的客观参数在受伤后 24 小时内，准确地对烧伤严重程度进行分类，我们已经在一份报告中进行了演示。猪烧伤模型表明，研究级 SFDI 在 24 ℃ 的性能优于激光散斑成像和热成像烧伤后数小时，以预测烧伤是否需要移植。由于研究级 SFDI 设备的一些设备限制，临床结果一直很困难。采集时间慢，可能会导致运动伪影，而且它对环境光也很敏感，这通常是一个问题。此外，SFDI 设备会生成大量不同的数据（含氧数据和数据）。脱氧血红蛋白、水分数、多个波长下的散射系数降低），没有将其呈现给临床用户以做出快速决定的明显方式为此，我们建议有条不紊地进行。研究改进的下一代 SFDI 设备，该设备通过使用更亮的 LED 来解决这些问题更少的波长来快速收集数据，从而减少运动伪影并且独立于临床此外，我们将开发一个基于机器学习的分类框架。为临床提供可操作的诊断信息本次 R01 竞赛的核心目标是 3 年。更新是表征并修改一种新的临床友好型 SFDI 设备 (Clarifi)，以客观地对 in- 拟议的研究旨在通过大面积不同烧伤严重程度的体内区域来调查这一点。以下具体目标：1) 测试和验证临床 SFDI 仪器，2) 将临床 SFDI 仪器与猪分级烧伤长期模型的其他模式，3) 开发空间分辨分类基于 SFDI 数据的烧伤严重程度图，4) 使用新的方法进行烧伤严重程度的临床测量 SFDI 设备和基于 SFDI 数据的空间解析烧伤严重程度分类图。

项目成果

期刊论文数量（15）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Impact of hemoglobin breakdown products in the spectral analysis of burn wounds using spatial frequency domain spectroscopy.

使用空间频域光谱对烧伤创面进行光谱分析时血红蛋白分解产物的影响。

DOI：
发表时间：
2019
期刊：
影响因子：
3.5
作者：
Saager, Rolf B;Rowland, Rebecca A;Baldado, Melissa L;Kennedy, Gordon T;Bernal, Nicole P;Ponticorvo, Adrien;Christy, Robert J;Durkin, Anthony J
通讯作者：
Durkin, Anthony J

Motion-resistant three-wavelength spatial frequency domain imaging system with ambient light suppression using an 8-tap CMOS image sensor.

使用 8 抽头 CMOS 图像传感器的防运动三波长空间频域成像系统，具有环境光抑制功能。

DOI：
发表时间：
2024-01
期刊：
影响因子：
3.5
作者：
Feng, Yu;Cao, Chen;Shimada, Yuto;Yasutomi, Keita;Kawahito, Shoji;Kennedy, Gordon T;Durkin, Anthony J;Kagawa, Keiichiro
通讯作者：
Kagawa, Keiichiro

Solid tissue simulating phantoms having absorption at 970 nm for diffuse optics.

实体组织模拟在 970 nm 处具有漫射光学吸收的模型。

DOI：
发表时间：
2017-07-01
期刊：
影响因子：
3.5
作者：
Kennedy, Gordon T;Lentsch, Griffin R;Trieu, Brandon;Ponticorvo, Adrien;Saager, Rolf B;Durkin, Anthony J
通讯作者：
Durkin, Anthony J

A Quantitative Assessment of Wound Healing With Oxygenated Micro/Nanobubbles in a Preclinical Burn Model.

临床前烧伤模型中氧化微/纳米气泡伤口愈合的定量评估。

DOI：
发表时间：
2021-10-01
期刊：
影响因子：
1.5
作者：
Sayadi, Lohrasb R;Rowland, Rebecca;Naides, Alexandra;Tomlinson, Luke;Ponticorvo, Adrien;Durkin, Anthony J;Widgerow, Alan D
通讯作者：
Widgerow, Alan D

Quantitative long-term measurements of burns in a rat model using Spatial Frequency Domain Imaging (SFDI) and Laser Speckle Imaging (LSI).

使用空间频域成像 (SFDI) 和激光散斑成像 (LSI) 对大鼠模型烧伤进行定量长期测量。

DOI：
发表时间：
2017-03
期刊：
影响因子：
2.4
作者：
Ponticorvo, Adrien;Burmeister, David M;Rowland, Rebecca;Baldado, Melissa;Kennedy, Gordon T;Saager, Rolf;Bernal, Nicole;Choi, Bernard;Durkin, Anthony J
通讯作者：
Durkin, Anthony J