Development and evaluation of a combined X-ray transmission and diffraction imaging system for pathology
用于病理学的组合 X 射线透射和衍射成像系统的开发和评估
基本信息
- 批准号:10699271
- 负责人:
- 金额:$ 88.76万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-09-08 至 2025-08-31
- 项目状态:未结题
- 来源:
- 关键词:AffectAlgorithmic SoftwareArea Under CurveBenchmarkingBreastCalibrationCarcinomaCaringClassificationClinicalClinical PathologyCollaborationsDataDevelopmentDiagnosisDiagnosticDiseaseEconomicsEquilibriumEvaluationFaceFacultyGoalsHistologicHospitalsHourImageImaging technologyIndividualInsuranceLaboratoriesLocationMalignant NeoplasmsManualsMarketingMeasurementMedicalMetadataMethodsMicroscopeMicroscopicMicroscopyMolecular ProfilingOperative Surgical ProceduresPalpationPathologistPathologyPerformancePhasePlayPreparationProcessProductivityPublishingReceiver Operating CharacteristicsReproducibilityResearchResectedResolutionRoentgen RaysRoleSamplingScanningSeriesSliceSlideSmall Business Innovation Research GrantSpecimenSpeedSurfaceSystemTechnologyTestingThickTimeTissuesUniversitiesWorkWorkloadX ray diffraction analysisabsorptionbiobankcancer siteclassification algorithmclinical diagnosisclinical imagingclinical translationcohortcommercializationcostfield studyimage reconstructionimaging softwareimaging systemimprovedmalignant breast neoplasmnew technologypathology imagingprototyperesponsesatisfactionskillssoftware developmentstandard of caretooltransmission processtumorusabilityuser friendly software
项目摘要
ABSTRACT
Pathology, which plays a vital role in clinical diagnosis, faces numerous challenges that impact its efficacy. For
example, resected specimens often require preparing and analysis of as many as 30-40 slide blocks under a
microscope until the disease is confirmed; selection of slices for slide preparation uses subjective methods such
as palpation, which depend greatly on the skill of the individual performing the assessment and introduces
inconsistency in the clinical process; and for each slide block examined, analysis and annotation requires manual
observation of every microscopic region of the tissue. As a result, most pathology evaluations often take 1-3
weeks to analyze samples and reach a conclusion regarding potential cancers. An added challenge is that
insurance reimbursements are capped per case regardless of the number of slide blocks processed, with any
additional costs being absorbed by the hospital. Consequently, hospitals must balance the trade-off between
minimizing the number of slices (for economic viability) and not compromising diagnostic care. These challenges
affect not only clinical pathology but also research involving pathology specimens and tissue selection for
biobanking. There is a critical need to eliminate subjectivity, reduce pathologists’ workload, and increase
throughput in histological analysis. We propose to meet this need by developing a new technology called X-ray
diffraction imaging (XRDI), which can scan any number of surgically resected, sliced pathology specimens and
automatically indicate the likelihood and location of disease in each slice within minutes. In collaboration with
Duke University, we previously built a research prototype XRDI system and demonstrated its utility by scanning
and evaluating 300 breast cancer slices with high accuracy and resolution. In this direct-to-phase-II SBIR
application, we will now construct a new clinical version of the XRDI scanner that is affordable, reliable, and
accurate, and can be directly integrated into the clinical pathology workflow. We will build the scanner, test and
evaluate its performance, and demonstrate its utility through field-testing in collaboration with clinical pathology
laboratories in the US. This project will provide a first-of-its-kind, commercially feasible XRDI scanner for rapid,
non-destructive imaging of pathology specimens with the ability to inform pathologists about the presence and
location of cancer within the different tissue slices. The proposed clinical scanner will enable: 1) analysis of the
whole slice volume of the specimen rather than a few microns at the surface of a subset of the slices, which is
the current standard of care process using microscopy, 2) quantitative identification of disease based on XRD
information obtained directly from the tissue, and 3) slice selection based on quantitative, reproducible
measurements, thereby eliminating user-related subjectivity. Importantly, it would significantly speed up
pathology workflow, providing decisions within hours instead of days, and improve the productivity and
profitability of pathology labs by reducing the number of slide blocks analyzed per case.
摘要
病理学在临床诊断中起着至关重要的作用,但它面临着许多影响其疗效的挑战。为
例如,切除的标本通常需要在一个或多个温度下制备和分析多达30-40个滑块。
在显微镜下检查,直到疾病得到确认;选择切片制备使用主观方法,如
触诊,这在很大程度上取决于个人的技能进行评估,并介绍
临床过程中的不一致性;对于检查的每个滑块,分析和注释需要手动
观察组织的每个微观区域。因此,大多数病理学评估通常需要1-3个
分析样本并得出关于潜在癌症的结论。另一个挑战是,
无论处理的幻灯片数量如何,每个案例的保险报销都有上限,
额外费用由医院承担。因此,医院必须在以下方面进行权衡:
最小化切片的数量(为了经济可行性)并且不损害诊断护理。这些挑战
不仅影响临床病理学,而且影响涉及病理学标本和组织选择的研究,
生物库迫切需要消除主观性,减少病理学家的工作量,
组织学分析的吞吐量。我们建议通过开发一种称为X射线的新技术来满足这种需要
衍射成像(XRDI),它可以扫描任何数量的手术切除,切片病理标本,
在几分钟内自动指示每个切片中疾病的可能性和位置。协同
杜克大学,我们以前建立了一个研究原型XRDI系统,并证明了其效用,通过扫描
并以高精度和分辨率评估300个乳腺癌切片。在这个直接进入第二阶段的SBIR中,
应用程序,我们现在将构建一个新的临床版本的XRDI扫描仪,是负担得起的,可靠的,
准确,可以直接集成到临床病理工作流程中。我们将建立扫描仪,测试和
评估其性能,并通过与临床病理学合作的现场测试证明其实用性
美国的实验室。该项目将提供一个第一个同类的,商业上可行的XRDI扫描仪,
病理学标本的非破坏性成像,能够告知病理学家
不同组织切片中的癌症位置。拟议的临床扫描仪将能够:1)分析
样本的整个切片体积,而不是切片子集表面的几微米,
目前使用显微镜的护理过程标准,2)基于XRD的疾病定量鉴定
直接从组织获得的信息,以及3)基于定量的、可再现的
测量,从而消除与用户相关的主观性。重要的是,这将大大加快
病理学工作流程,在数小时内而不是数天内提供决策,并提高生产率,
通过减少每个病例分析的滑块数量,提高病理学实验室的盈利能力。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Joel Greenberg其他文献
Joel Greenberg的其他文献
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{{ truncateString('Joel Greenberg', 18)}}的其他基金
Multimodality X-ray transmission and diffraction scanner for molecular analysis of cancer specimens
用于癌症样本分子分析的多模态 X 射线透射和衍射扫描仪
- 批准号:
10656798 - 财政年份:2021
- 资助金额:
$ 88.76万 - 项目类别:
Multimodality X-ray transmission and diffraction scanner for molecular analysis of cancer specimens
用于癌症样本分子分析的多模态 X 射线透射和衍射扫描仪
- 批准号:
10693406 - 财政年份:2021
- 资助金额:
$ 88.76万 - 项目类别:
Multimodality X-ray transmission and diffraction scanner for molecular analysis of cancer specimens
用于癌症样本分子分析的多模态 X 射线透射和衍射扫描仪
- 批准号:
10113151 - 财政年份:2021
- 资助金额:
$ 88.76万 - 项目类别:
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