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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.

项目主任/主要研究者（最后，第一，中间）：Durkin，Anthony J. 摘要这一为期3年的竞争性R 01更新的中心目标是表征和应用一种新的、紧凑的、临床- 友好的空间频域成像（SFDI）设备，可对烧伤进行客观和非侵入性分类大面积皮肤上的严重程度（烧伤等级）。延迟确定烧伤严重程度直接影响患者治疗计划（包括是否移植的决定）、感染率和瘢痕形成率、住院时间最后是护理费用。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。虽然浅表层和全层烧伤通常基于视觉临床印象容易诊断，部分厚度烧伤难以分类和携带有相当大的并发症的可能性。烧伤严重程度分类的准确性，即使是专家，只有60- 80%。我们对动物模型的研究表明，SFDI数据可以成功地用于分类不同区域的烧伤严重程度。通常，这些差异对于肉眼和肉眼来说并不明显临床医生需要大量的培训和经验才能准确区分它们。使用研究级的混合SFDI装置表明，可以使用SFDI提供的客观参数在伤后24小时内，对烧伤严重程度进行准确分类。具体来说，我们在一个猪烧伤模型，研究级SFDI优于激光散斑成像和热成像在24 在烧伤后几个小时，在预测烧伤是否需要移植方面。然而，翻译这些由于几个装置的限制，将结果应用于临床是困难的。研究级SFDI设备具有可能导致运动伪影的缓慢采集时间。它对环境光也很敏感，在临床环境中。此外，SFDI设备生成如此多的不同数据（含氧和脱氧血红蛋白、水分数、在多个波长处的减少的散射系数），不存在这是一种将其呈现给临床用户以快速做出决定的明显方式。为此，我们建议，研究改进的下一代SFDI器件，通过使用更亮的LED解决这些问题，更少的波长，以减少运动伪影并独立于临床的方式快速收集数据照明条件。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。这3年竞争R 01的中心目标更新的目的是表征并修改新的临床友好型SFDI器械（Clarifi），以便客观地将其分类为- 大面积不同烧伤严重程度的体内区域。拟议中的研究试图通过以下方式调查这一点：以下特定目的：1）测试和验证临床SFDI仪器，2）比较临床SFDI仪器与分级烧伤的长期猪模型的其他模式，3）开发空间分辨分类基于SFDI数据的烧伤严重度地图，4）使用新的 SFDI器械和基于SFDI数据的空间分辨烧伤严重度分类图。

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：
10.1117/1.jbo.24.2.020501
发表时间：
2019
期刊：
Journal of biomedical optics
影响因子：
3.5
作者：
Saager,RolfB;Rowland,RebeccaA;Baldado,MelissaL;Kennedy,GordonT;Bernal,NicoleP;Ponticorvo,Adrien;Christy,RobertJ;Durkin,AnthonyJ
通讯作者：
Durkin,AnthonyJ

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

DOI：
10.1117/1.jbo.29.1.016006
发表时间：
2024-01
期刊：
Journal of biomedical optics
影响因子：
3.5
作者：
通讯作者：

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

DOI：
10.1097/sap.0000000000003017
发表时间：
2021-10-01
期刊：
Annals of plastic surgery
影响因子：
1.5
作者：
Sayadi LR;Rowland R;Naides A;Tomlinson L;Ponticorvo A;Durkin AJ;Widgerow AD
通讯作者：
Widgerow AD

Spatial Frequency Domain Imaging (SFDI) of clinical burns: A case report.

临床烧伤的空间频域成像 (SFDI)：病例报告。

DOI：
10.1016/j.burnso.2020.02.004
发表时间：
2020
期刊：
Burns open : an international open access journal for burn injuries
影响因子：
0
作者：
Ponticorvo,Adrien;Rowland,Rebecca;Baldado,Melissa;Kennedy,GordonT;Hosking,Anna-Marie;Burmeister,DavidM;Christy,RobertJ;Bernal,NicoleP;Durkin,AnthonyJ
通讯作者：
Durkin,AnthonyJ

Method using in vivo quantitative spectroscopy to guide design and optimization of low-cost, compact clinical imaging devices: emulation and evaluation of multispectral imaging systems.