SolvingDynamics, Inc. — Department of Health and Human Services SBIR Phase I: R

Description

Summary This project seeks to prove the commercial feasibility of a new approach to analyzing dynamic positron emission tomographyPETdata that would improve sensitivityquantitative accuracyand accessibility of imaging the biomarkers of Alzheimerandapos s diseaseADRecent progress in understanding the nature of neurodegenerative diseasesespecially evidence that the onset of cognitive symptoms of AD can be mitigatedamplify the critical need of improved quantitative evaluation of AD biomarkersDynamic PET may be the most accurate modality capable of achieving this goalHowevercurrent strategies of analyzing dynamic PET images either require complex acquisition protocols with invasive arterial blood sampling procedures or rely on accuracy degrading approximations such as compartment modelingWe have developed Intelligent Dynamics Driven Quantitative DiagnosticsIDDQDa novel processing approach based on factor analysis of dynamic structures with partial clustering used to initiate the processWe have shown that an early version of IDDQD can extract blood and tissue tracer dynamics and the corresponding spatial distributions fromC PIB PET scansSolvingDynamics Inc plans to offer a Research as a Service data processing workflow that will apply IDDQD to dynamic brain PET datasets acquired by the customersproducing accurate quantitative tracer dynamics time activity curvesTACsand the distribution of the targeted tissuesincluding the AD biomarkers beta amyloid and tauOur proprietary algorithm does not require the tracer dynamics model to achieve steady stateso a shorter scan can be used to generate results of similar or better accuracy than those produced by current approachessuch as reference tissuebased methodsIn this proposalSolvingDynamics seeks to prove the feasibility of our proposed approach by comparing the diagnostics obtained using IDDQD analysis of dynamic PET data and those obtained from independent measurementsA subcontract group at Lawrence Berkeley National Laboratory has been conducting dynamicC PIB PET studies for several years and has accumulated overcases with PET data matched to both cognitive memory tests and to post mortem pathology studiesSolvingDynamics will retrospectively apply its analysis technique to these datasets and compare its computed tissue distributions to standardized uptake volume ratioSUVRand distribution volume ratioDVRdataA subset ofdynamicC PIB PET datasets ranging in length fromtominutes will also be analyzed in order to validate the feasibility of reducing the imaging timeIn additionsimilar studies aimed at reducing imaging time with IDDQD will be performed forPET scans acquired usingF AVtracer to image tau PROJECT NARRATIVE Positron emission tomography image analysis methodology to be validated in this project aims to improve sensitivity and specificity of tissue analysis in dynamic positron emission tomographyimproving diagnosis of Alzheimerandapos s diseases and other neurodegenerative disordersThe main benefits are expected in medical research developing treatments for dementia and in clinical diagnosisallowing early detection of the disease with less cost and reduced radiation dose to the patients