AUTOMATED IMAGING DIAGNOSTICS, LLC - Florida Company Profile

Headquarter of

20231729945

COLORADO

AUTOMATED IMAGING DIAGNOSTICS, LLC (CO)

352-328-9915

angelos.barmpoutis@att.net

ANGELOS BARMPOUTIS

Self-Certified Small Disadvantaged Business

P2656379

XR5RXETUJBA9

95SF2

2025-11-26

2024-12-02

2021-09-15

2024-08-29

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Department of Health and Human Services

CLINICAL PERFORMANCE TESTING OF NEUROPACS IN PARKINSONISM DIAGNOSIS - PROJECT SUMMARY THE GROWTH RATE IN THE NUMBER OF PEOPLE DIAGNOSED WITH PARKINSONISM IS SUBSTANTIAL. ESTIMATES INDICATE THAT FROM 1990 TO 2015 THE NUMBER OF PARKINSONISM DIAGNOSES DOUBLED, WITH MORE THAN 6 MILLION PEOPLE CURRENTLY DIAGNOSED. BY 2040, THERE WILL BE 12 TO 14 MILLION PEOPLE DIAGNOSED WITH PARKINSONISM. PARKINSON’S DISEASE (PD), MULTIPLE SYSTEM ATROPHY PARKINSONIAN VARIANT (MSAP), AND PROGRESSIVE SUPRANUCLEAR PALSY (PSP) ARE NEURODEGENERATIVE FORMS OF PARKINSONISM, WHICH CAN BE DIFFICULT TO DIAGNOSE AS THEY SHARE SIMILAR MOTOR AND NON-MOTOR FEATURES, AND THEY EACH HAVE AN INCREASED CHANCE OF DEVELOPING DEMENTIA. IN THE FIRST FIVE YEARS OF A PD DIAGNOSIS, ABOUT 58% OF PD PATIENTS ARE MISDIAGNOSED, AND OF THESE MISDIAGNOSES ABOUT HALF HAVE EITHER MSAP OR PSP. SINCE PD, MSAP, AND PSP REQUIRE UNIQUE TREATMENT PLANS AND DIFFERENT MEDICATIONS, AND CLINICAL TRIALS TESTING NEW MEDICATIONS REQUIRE THE CORRECT DIAGNOSIS, THERE IS AN URGENT NEED FOR CLINICAL AND CLINICAL TRIAL READY DIAGNOSTIC MARKERS. A PROMISING APPROACH TO IDENTIFY DIFFERENT FORMS OF PARKINSONISM IS DIFFUSION MAGNETIC RESONANCE IMAGING (MRI), AS THERE IS NO CONTRAST DRUG, THE TECHNIQUE IS SAFE, AND IS ALREADY USED CLINICALLY IN TRAUMATIC BRAIN INJURY AND STROKE. USING THIS APPROACH IS ADVANTAGEOUS BECAUSE MRI ACQUISITION IS COMPATIBLE WITH STANDARD CLINICAL PRACTICE WHEN EVALUATING SUSPECTED PARKINSONISM IN PATIENTS AND CAN BE PERFORMED RAPIDLY ON WIDELY AVAILABLE 3 TESLA MRI SYSTEMS. AUTOMATED IMAGING DIAGNOSTICS IS DEVELOPING A COMMERCIAL SOFTWARE CALLED NEUROPACS™, A HIGH-THROUGHPUT BRAIN IMAGE PROCESSING AND AI-POWERED PRECISION DIAGNOSTIC TOOL TO ASSIST IN THE DIAGNOSIS OF PD, MSAP, AND PSP. RESULTS FROM OUR PHASE I PROGRAM HAVE ESTABLISHED CLEAR TECHNICAL FEASIBILITY AND THE DATA INDICATE NEUROPACS™ IS ROBUST IN THE CLINICAL CLASSIFICATION OF PD, MSAP, AND PSP WITH >90% ACCURACY. OUR NEXT GOAL IN THIS PHASE II PROJECT IS TO PERFORM A PRE-MARKET FIELD EVALUATION OF NEUROPACS™. WE WILL PERFORM A CLINICAL PERFORMANCE STUDY TO DETERMINE HOW THE ADDITION OF NEUROPACS™ INTO WORKFLOWS OF BOARD-CERTIFIED NEUROLOGISTS AFFECTS DIAGNOSTIC ACCURACY OF PD, MSAP, AND PSP. A SECOND MAJOR OBJECTIVE IS TO VALIDATE THE ACCURACY OF NEUROPACS™ FOR PREDICTING GOLD-STANDARD PATHOLOGICAL DIAGNOSIS. THIS IS AN IMPORTANT VALIDATION STEP BECAUSE OTHER AVAILABLE TECHNOLOGIES FAIL TO DISTINGUISH PATIENTS USING PATHOLOGICAL MARKERS OF PARKINSONISM, INCLUDING DOPAMINE DEFICIENCY AND BRAIN ATROPHY. THIS PHASE II PROJECT WILL FURTHER OUR EFFORTS TO DEVELOP A HIGH-PRECISION CLINICAL DECISION SUPPORT TOOL FOR PARKINSONISM AND POSITION OUR COMPANY TO ACHIEVE FDA BIOMARKER APPROVAL AND DEVICE QUALIFICATION MILESTONES.

736624.00

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2023-06-15

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Department of Health and Human Services

ASSESSMENT OF DEEP LEARNING CLASSIFICATION METHODS FOR PARKINSONISM - SUMMARY THE GROWTH RATE IN THE NUMBER OF PEOPLE DIAGNOSED WITH PARKINSONISM IS SUBSTANTIAL. ESTIMATES INDICATE THAT FROM 1990 TO 2015 THE NUMBER OF PARKINSONISM DIAGNOSES DOUBLED, WITH MORE THAN 6 MILLION PEOPLE CURRENTLY DIAGNOSED. BY 2040, THERE WILL BE BETWEEN 12-14 MILLION PEOPLE DIAGNOSED WITH PARKINSONISM. PARKINSON’S DISEASE (PD), MULTIPLE SYSTEM ATROPHY PARKINSONIAN VARIANT (MSAP), AND PROGRESSIVE SUPRANUCLEAR PALSY (PSP) ARE NEURODEGENERATIVE FORMS OF PARKINSONISM, WHICH CAN BE DIFFICULT TO DIAGNOSE AS THEY SHARE SIMILAR MOTOR AND NON-MOTOR FEATURES, AND THEY EACH HAVE AN INCREASED CHANCE OF DEVELOPING DEMENTIA. IN THE FIRST FIVE YEARS OF A PD DIAGNOSIS, ABOUT 58% OF PD ARE MISDIAGNOSED, AND OF THESE MISDIAGNOSES ABOUT HALF HAVE EITHER MSA OR PSP. SINCE PD, MSAP, AND PSP REQUIRE UNIQUE TREATMENT PLANS AND DIFFERENT MEDICATIONS, AND CLINICAL TRIALS TESTING NEW MEDICATIONS REQUIRE THE CORRECT DIAGNOSIS, THERE IS AN URGENT NEED FOR CLINIC READY DIAGNOSTIC LEVEL MARKERS FOR DIFFERENTIAL DIAGNOSIS OF PD, MSAP, AND PSP. A PROMISING APPROACH TO IDENTIFY DIFFERENT FORMS OF PARKINSONISM IS DIFFUSION MAGNETIC RESONANCE IMAGING (DMRI), AS THERE IS NO CONTRAST DRUG, THE TECHNIQUE IS SAFE AND IS ALREADY USED CLINICALLY IN TRAUMATIC BRAIN INJURY AND STROKE. THE DATA COLLECTION TAKES 6-12 MINUTES AND IS COMPATIBLE ON CURRENT 3 TESLA MRI SYSTEMS WORLDWIDE. BASED ON ACADEMIC RESEARCH AT UNIVERSITY OF FLORIDA, AUTOMATED IMAGING DIAGNOSTICS, LLC IS DEVELOPING A COMMERCIAL SOFTWARE PACKAGE USING FREE-WATER DIFFUSION IMAGING AS AN INNOVATIVE BIOMARKER TO HELP IN THE DIAGNOSIS OF PD, MSAP, AND PSP. THE SOFTWARE CURRENTLY DISTINGUISHES PD, MSAP, AND PSP WITH OVER 90% ACCURACY, AND CAN ACHIEVE THIS ACCURACY ON DIFFERENT SCANNER MANUFACTURES. OUR NEXT GOAL IN THIS PHASE I PROJECT IS TO FURTHER IMPROVE THE INNOVATION AND ACCURACY OF OUR SOFTWARE TECHNOLOGY BY EMPLOYING DEEP LEARNING CLASSIFICATION ALGORITHMS FOR THE DIAGNOSIS OF PARKINSONISM. THE SPECIFIC AIM OF THIS CURRENT PHASE I PROJECT IS TO SUBSTITUTE AND COMPARE THE USE OF OUR EXISTING SUPPORT VECTOR MACHINE (SVM) METHOD WITH TWO DIFFERENT RESIDUAL DEEP NEURAL NETWORK (RESDNN) ARCHITECTURES FOR ESTIMATING DISEASE TYPE (PD/MSAP/PSP) THROUGH THE FOLLOWING TWO MILESTONES. FIRST, IN MILESTONE 1 WE WILL DETERMINE IF A RESDNN METHOD THAT PROCESSES THE SAME FEATURE VECTOR AS OUR SVM SOLUTION IMPROVES THE ACCURACY FOR DIFFERENTIATING A) PD AND ATYPICAL PARKINSONISM (MSAP/PSP) AND B) MSAP AND PSP BY 5%. SECOND, IN MILESTONE 2, WE WILL DETERMINE IF A RESDNN METHOD THAT PROCESSES DIRECTLY THE RAW INPUT IMAGE DATA (INSTEAD OF OUR DERIVED FEATURE VECTOR) IMPROVES THE ACCURACY FOR DIFFERENTIATING A) PD AND ATYPICAL PARKINSONISM (MSAP/PSP) AND B) MSAP AND PSP BY 5%. THIS PHASE I PROJECT WILL FACILITATE OUR LONG-TERM OBJECTIVE OF DEVELOPING A HIGH-PRECISION DIAGNOSTIC SOFTWARE THAT CAN BE USED BY RADIOLOGISTS FOR DIAGNOSING DIFFERENT TYPES OF PARKINSONISM.

272736.00

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2022-08-09

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Department of Health and Human Services

AUTOMATED IMAGING DIFFERENTIATION OF PARKINSONISM - SUMMARY ACROSS THE GLOBE THE NUMBER OF PEOPLE DIAGNOSED WITH PARKINSONISM HAS INCREASED CONSIDERABLY. FROM 1990 TO 2015, THE NUMBER OF PARKINSONISM DIAGNOSES DOUBLED, WITH OVER 6 MILLION PEOPLE CURRENTLY CARRYING THE DIAGNOSIS. CURRENT ESTIMATES SUGGEST THAT 12-14 MILLION PEOPLE WILL BE DIAGNOSED WITH PARKINSONISM BY 2040. PARKINSON’S DISEASE (PD), MULTIPLE SYSTEM ATROPHY PARKINSONIAN VARIANT (MSAP), AND PROGRESSIVE SUPRANUCLEAR PALSY (PSP), WHICH ARE NEURODEGENERATIVE FORMS OF PARKINSONISM, CAN BE DIFFICULT TO DIAGNOSE AS THEY SHARE MOTOR AND NON-MOTOR FEATURES AND HAVE AN INCREASED RISK FOR DEMENTIA. DIAGNOSTIC ACCURACY IN EARLY PD (<5 YEARS DURATION) IS APPROXIMATELY 58%, AND 54% OF MISDIAGNOSED PATIENTS HAVE EITHER MSA OR PSP. WHILE THE FDA HAS APPROVED DOPAMINE TRANSPORTER IMAGING WITH DATSCAN™ TO HELP IDENTIFY PARKINSONISM, ABNORMAL DATSCAN IMAGING CANNOT DISTINGUISH BETWEEN PARKINSONISM FORMS THAT SHARE DOPAMINERGIC DEFICIENCY. THUS, NO CLINICALLY APPROVED CURRENT DIAGNOSTIC MARKER CAN DISTINGUISH AMONG FORMS OF PARKINSONISM. CORRECT DIAGNOSIS OF PARKINSONISM TYPE IS CRITICAL BECAUSE THE TREATMENTS, PROGNOSES (OFTEN MORE RAPID IN ATYPICAL PARKINSONISM), AND PATHOLOGIES OF THESE DISEASES DIFFER. INCORRECT DIAGNOSES RESULT IN PATIENTS RECEIVING INCORRECT MEDICATIONS, DEEP BRAIN STIMULATION SURGERIES PERFORMED IN PATIENTS THAT DO NOT HAVE PD, DIMINISHED QUALITY OF LIFE, AND INEFFECTIVE CARE. AS OUTLINED IN OUR ACCEPTED LETTER OF INTENT TO THE FDA BIOMARKER QUALIFICATION PROGRAM, A PROMISING APPROACH TO IDENTIFY DIFFERENT FORMS OF PARKINSONISM IS DIFFUSION MAGNETIC RESONANCE IMAGING (DMRI). OUR SOFTWARE METHOD IS BASED ON FREE-WATER IMAGING, WHICH IS A METHOD FOR ANALYZING DMRI DATA OF TISSUE MICROSTRUCTURE ASSOCIATED WITH INFLAMMATION AND NEURODEGENERATION. WE RECENTLY ANALYZED DMRI DATA FROM A RETROSPECTIVE MULTI-CENTER COHORT OF 1002 PARTICIPANTS COLLECTED WITH VARIOUS ACQUISITION PROTOCOLS USING 17 DIFFERENT MRI SCANNERS ACROSS THE WORLD. SUPPORT VECTOR MACHINE (SVM) LEARNING WAS CONDUCTED WITH AN AUTOMATED 5-FOLD CROSS-VALIDATION PROCEDURE IN A TRAINING AND VALIDATION COHORT AND THEN EVALUATED IN AN INDEPENDENT TEST COHORT. IN THE INDEPENDENT TEST COHORT, THERE WAS HIGH AREA UNDER THE CURVE FOR DISTINGUISHING AMONG PD, MSA, AND PSP WITH AID-P ACROSS THE MRI SITES. TWO KEY ISSUES RAISED IN THE FEEDBACK FROM OUR FDA BIOMARKER LETTER OF INTENT INCLUDED 1) EXAMINATION OF AID- P AT DIFFERENT LEVELS OF DISEASE SEVERITY; AND 2) EXAMINATION OF AID-P ON ONE MRI SCANNER VENDOR VERSUS COMBINING ACROSS MRI SCANNER VENDOR. IN THIS U01 PROJECT, WE WILL BE EXAMINING THESE TWO ANALYTICAL ISSUES TO FURTHER ENHANCE THE RIGOR FOR OUR FINAL QUALIFICATION PLAN. THESE KEY ISSUES COULD HAVE SIGNIFICANT IMPACT ON MODEL PREDICTION ACCURACY AND THUS IMPACT PATIENT CARE.

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