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Combined radiation acoustics and ultrasound imaging for real-time guidance in radiotherapy

Combined radiation acoustics and ultrasound imaging for real-time guidance in radiotherapy
结合辐射声学和超声成像,用于放射治疗的实时指导
批准号:
10582051
负责人:
Issam M. El Naqa
金额:
$47.98万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2025-07-31
关键词:
3-Dimensional3D ultrasoundAbdomenAcousticsAffectAnatomyAnimalsAreaCalibrationCancer PatientCaringCesarean sectionCharacteristicsClinicClinicalClinical ResearchClinical TreatmentCompensationDepositionDetectionDiagnostic ImagingDoseEffectivenessElementsExposure toFeedbackGelGenerationsGeometryGoalsImageInvestigationIonizing radiationLasersLinear Accelerator Radiotherapy SystemsLiverLocationMagnetic Resonance ImagingMalignant NeoplasmsMalignant neoplasm of abdomenMalignant neoplasm of gastrointestinal tractMalignant neoplasm of liverMalignant neoplasm of pancreasMeasurementMeasuresMedical ImagingMethodsModelingMonitorMorphologic artifactsMotionNormal tissue morphologyOncologyOnline SystemsOpticsOrganOryctolagus cuniculusOutcomePancreasPatientsPatternPenetrationPerformancePhysiologicalPilot ProjectsPre-Clinical ModelProcessPropertyRadiationRadiation Dose UnitRadiation OncologyRadiation PhysicsRadiation therapyReportingResolutionRoentgen RaysRotationSafetyShapesSignal TransductionSystemSystems IntegrationTechnologyTestingThree-Dimensional ImagingTimeTissuesToxic effectTransducersTreatment outcomeUltrasonographyUncertaintyVariantabsorptionacoustic imaginganatomic imagingcancer sitecancer typecostcost effectivedetectordosimetryeffective therapyimage guidedimprovedin vivonoveloptimal treatmentsphantom modelphotoacoustic imagingradiation deliveryreal-time imagesrespiratoryresponseside effectsystems researchtomographytranslational potentialtreatment planningtumortumor eradicationultrasound

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PROJECT SUMMARY: Radiotherapy can be a highly effective treatment for many types of cancers. A major impediment to achieving its full curative promise is the current delivery process, where typically the originally planned tumor area is exposed to a fixed pattern of ionizing radiation over time irrespective of target deformations, organ motion, or function. To avoid misses, geometric uncertainties in this feedforward process are dealt with by increasing the planning margin around the tumor, but of necessity result in unnecessary exposure of uninvolved tissue which can lead to debilitating toxicities. We hypothesize that the unwanted radiation dose to normal tissues could be significantly reduced by using a feedback system that would “know” the shape and location of the tumor as well as the location and intensity of the irradiated dose during delivery. This framework would require the unique ability to simultaneously image the absorbed dose and the targeted tumor anatomy during radiation delivery, which is not possible with currently existing technologies. A known phenomenon in radiation physics is the generation of acoustic waves due to thermal expansion of a substance following the absorption of penetrating radiation. Detection of this radiation induced acoustic signal from clinical treatment beams has been recently demonstrated but has not been clinically realized. That signal exists “for free” in real time as a consequence of the treatment beam. The signal can be measured with ultrasound detectors and processed to reveal the location and intensity of the deposited energy/dose. Furthermore, ultrasound technologies have also long been established for medical imaging and monitoring of tumor size, shape and location, without introducing ionizing radiation. Therefore, we propose to combine measurements of radiation acoustics and ultrasound imaging in an integrated system using advanced matrix array probes to determine in real-time the volumetric delivered radiation dose with respect to that day's tumor shape and location, and ultimately to optimize tumor targeting via online feedback. The system will be optimized in phantoms and preclinical models. Then, its feasibility and versatility will be tested for treatment of tumors in the liver and the pancreas, two aggressive cancer sites where misplaced dose due to deformation and physiological motion not only compromises tumor eradication but also affects vital functions in the patient and subsequent treatment outcomes. Impact statement: We aim to implement new, safe, simple, cost effective technology and methods for online guidance of radiotherapy delivery that can provide simultaneous tumor tracking and dose compensation capabilities. These technologies will be evaluated in a pilot clinical study of liver and pancreatic cancers to demonstrate feasibility and potentials for translation. If successful, this feedback technology will have a significant impact on personalizing radiotherapy delivery and achieving optimal treatment outcomes.
期刊论文(3)
专著(0)
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会议论文
DOI: 10.1002/mp.14358
发表时间: 2020-10
期刊: Medical physics
影响因子: 3.8
作者: [Oraiqat I, Zhang W, Litzenberg D, Lam K, Ba Sunbul N, Moran J, Cuneo K, Carson P, Wang X, El Naqa I]
通讯作者: El Naqa I
DOI: 10.1002/mp.15188
发表时间: 2021-10
期刊: Medical physics
影响因子: 3.8
作者: [Ba Sunbul NH, Zhang W, Oraiqat I, Litzenberg DW, Lam KL, Cuneo K, Moran JM, Carson PL, Wang X, Clarke SD, Matuszak MM, Pozzi SA, El Naqa I]
通讯作者: El Naqa I
DOI: 10.1002/mp.14685
发表时间: 2021-03
期刊: Medical physics
影响因子: 3.8
作者: [Ba Sunbul N, Oraiqat I, Rosen B, Miller C, Meert C, Matuszak MM, Clarke S, Pozzi S, Moran JM, El Naqa I]
通讯作者: El Naqa I
Cerenkov Multi-Spectral Imaging (CMSI) for Adaptation and Real-Time Imaging in Radiotherapy
  • 批准号:
    10080509
  • 项目类别:
  • 资助金额:
    $32.72万
  • 财政年份:
    2020
  • 负责人:
    Issam M. El Naqa
  • 依托单位:
Optimal Decision Making in Radiotherapy Using Panomics Analytics
Federated Learning for Optimal Decision Making in Radiotherapy Using Panomics Analytics
Optimal Decision Making in Radiotherapy Using Panomics Analytics
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