Speckle x-ray imaging: detecting early changes in lung microstructure
散斑 X 射线成像:检测肺微结构的早期变化
基本信息
- 批准号:10560958
- 负责人:
- 金额:$ 63.79万
- 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:2023-02-01 至 2026-11-30
- 项目状态:未结题
- 来源:
- 关键词:AddressAffectAlveolusAnimal ExperimentationAnimal ExperimentsAnimal ModelAnimalsArchitectureAreaBiologicalCancer SurvivorClinicalClinical ResearchDarknessDataDedicationsDiagnostic X-RayDiseaseDoseEarly DiagnosisElectromagnetic EnergyEquipmentEvaluationGasesGoalsImageImaging DeviceIndividualInterferometryInvestmentsLaboratory ResearchLungLung diseasesMembraneMethodsModelingMonitorMusOpticsOutcomePaperPatternPerformancePhasePhotonsPhysicsProton RadiationPulmonary FibrosisPulmonary alveolar structureRadiationRadiation Dose UnitRadiation ToxicityRadiation exposureRadiation therapyResearchResolutionRoentgen RaysShapesShockSignal TransductionSiteSourceStructureSynchrotronsSystemTechniquesToxic effectTranslatingTranslationsTreatment outcomeTreatment-related toxicityUnited StatesX-Ray Medical Imagingattenuationcontrast imagingcostdeep learningdesigndetectordiagnostic accuracydiagnostic toolearly onsetexpirationimaging detectionimprovedin vivoin vivo evaluationlongitudinal animal studymetallicitymicroCTnanoparticlenovelparticleportabilitypre-clinicalpreclinical evaluationpreclinical imagingpreclinical studyprospectiveproton therapyprototypepublic health relevanceresearch facilityside effectsoftware infrastructuresurvivorshiptargeted treatmenttooltransmission processtrend
项目摘要
Abstract.
In the United States alone, the number of proton therapy centers has increased to 41 sites, with many more
currently under construction or in planning stage. While the investment for such centers is in the hundreds of
millions of US dollars, research is ongoing to determine whether proton therapy improves treatment outcomes.
A sensitive diagnostic tool for the evaluation of alveoli architecture in this active research area would not only
enable early targeted treatment to slow down progression of radiation-induced lung fibrosis but also
significantly benefit the ongoing preclinical evaluation. The imaging tools currently in use have a poor to
moderate sensitivity that is insufficient for detecting early changes in the lungs and/or are proving impractical
with respect to radiation dose and logistical complexity for longitudinal preclinical studies. To address this critical
need, we introduce an imaging tool for early detection of lung microstructural changes by advancing the
emerging field of x-ray darkfield imaging. In conventional x-ray, image contrast is formed by attenuation based
on the interpretation of x-rays as particles. If sensing x-rays as electromagnetic waves, additional x-ray contrast
mechanisms such as diffraction, phase-shift and small-angle scattering can be accessed. X-ray scattering on
healthy, gas-filled pulmonary alveoli generates a strong darkfield signal, and the signal decreases when
the integrity of the alveoli is affected. Preliminary in-vivo small animal experiments successfully demonstrated
an on average ten-weeks-earlier detection of early onset of radiation-induced lung fibrosis from
conventional photon therapy. A number of methods for acquiring x-ray darkfield images have been investigated
in recent years. However, current solutions require complicated, shock-sensitive and expensive hardware
implementations. A more practical method involves the use of filters consisting of random structures (so-called
diffusers) to generate near-field interference speckle patterns for acquiring darkfield images. Our long-term
goal is translating x-ray dark-field imaging from physics research laboratories into the preclinical imaging arena
to provide the needed tool for longitudinal lung assessment. Our solution includes the design of novel deep-
learning based speckle tracking in combination with a diffuser design based on nanoparticles which is
inexpensive to fabricate compared to gratings. The following specific aims will be pursued: (1) to develop a
software infrastructure for in-vivo small animal x-ray darkfield imaging, (2) to implement an x-ray darkfield
prototype for detection of early pulmonary toxicity from radiotherapy, and (3) to evaluate x-ray darkfield prototype
performance in phantoms and in-vivo longitudinal animal studies. This proposal will advance the field of speckle-
based x-ray dark-field imaging by deepening the basic understanding and by translating it from physics
research laboratories into the preclinical arena. Toward this end, we anticipate that our x-ray dark-field
imaging concept will serve as a low-dose tool for longitudinal in-vivo small animal studies. The proposed
solutions have the potential to drive the translation of x-ray dark-field imaging forward into the clinical routine.
摘要。
项目成果
期刊论文数量(0)
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科研奖励数量(0)
会议论文数量(0)
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Peter B Noël其他文献
Reproducible spectral CT thermometry with liver-mimicking phantoms for image-guided thermal ablation
通过模拟肝脏模型进行可重复的光谱 CT 测温,用于图像引导热消融
- DOI:
10.1101/2023.10.04.23296423 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Leening P Liu;Rizza Pua;Derick N Rosario;Olivia F Sandvold;Amy E Perkins;David P Cormode;Nadav Shapira;Michael C Soulen;Peter B Noël - 通讯作者:
Peter B Noël
Automatic bolus tracking in abdominal CT scans with convolutional neural networks
使用卷积神经网络进行腹部 CT 扫描的自动推注跟踪
- DOI:
10.1101/2022.06.29.22276968 - 发表时间:
2022 - 期刊:
- 影响因子:2.8
- 作者:
Angela T. Li;Peter B Noël;N. Shapira - 通讯作者:
N. Shapira
Phantom-based quantification of the spectral accuracy in dual-layer spectral CT for pediatric imaging at 100 kVp
基于体模的 100 kVp 儿科成像双层能谱 CT 中能谱精度的量化
- DOI:
10.1101/2022.02.27.22271573 - 发表时间:
2022 - 期刊:
- 影响因子:2.8
- 作者:
S. Meyer;Leening P. Liu;H. Litt;S. Halliburton;N. Shapira;Peter B Noël - 通讯作者:
Peter B Noël
PixelPrint: generating patient-specific phantoms for spectral CT using dual filament 3D printing
PixelPrint:使用双丝 3D 打印生成用于光谱 CT 的患者特定模型
- DOI:
10.1117/12.3006512 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Pouyan Pasyar;J. Y. Im;Kai Mei;Leening P. Liu;O. Sandvold;M. Geagan;Peter B Noël - 通讯作者:
Peter B Noël
Peter B Noël的其他文献
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