Biomedical Imaging and Medical Image Analysis Scientist Services

INTRODUCTION: THIS IS A PRE-SOLICITATION NON-COMPETITIVE (NOTICE OF INTENT) SYNOPSIS TO AWARD A CONTRACT OR PURCHASE ORDER WITHOUT PROVIDING FOR FULL AND OPEN COMPETITION (INCLUDING BRAND-NAME). The National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), Office of Acquisitions (OA) on behalf of the National Institute of Digestive and Diabetes and Kidney Diseases (NIDDK) intends to award a purchase order without providing for full and open competition (including brand-name) to Optimal Systems, LLC for the procurement of services of a Biomedical Imaging and Medical Image Analysis Scientist. NORTH AMERICAN INDUSTRY CLASSIFICATION SYSTEM (NAICS) CODE: The intended procurement is classified under NAICS code 541511 with a Size Standard of $34M. REGULATORY AUTHORITY: The resultant contract will include all applicable provisions and clauses in effect through the Federal Acquisition Circular 2022-08 Effective 10/28/2022. This acquisition is conducted under the procedures prescribed in FAR Part 13 - Simplified Acquisition Procedures at an amount not exceeding the simplified acquisition threshold ($250,000). STATUTORY AUTHORITY: This acquisition is conducted under the authority of the Federal Acquisition Regulation (FAR) Part 13 - Simplified Acquisition Procedures, Subpart 13.106-1 (b)(1), Soliciting from a single source for purchases not exceeding the simplified acquisition threshold. Contracts awarded using FAR Part 13 - Simplified Acquisition Procedures are exempt from the requirements of FAR Part 6 - Competition Requirements. BACKGROUND: Chronic liver disease (from fatty infiltration or infections), with accompanying hepatic inflammation and subsequent fibrosis, affects over 4 million Americans and often progresses to cirrhosis and primary liver cancer with approximately 51,000 deaths per year in the US. Early assessment of inflammation is of the utmost importance for improved liver treatment and recovery. However, inflammation is difficult to diagnose and the progression of inflammation to fibrosis and cirrhosis in chronic liver diseases is a continuous process that requires invasive biopsy to quantify for appropriate medical management. Invasive biopsy provides subjective histopathologic ranked scoring systems that attempt to classify fibrosis and inflammation. Even though biopsy is considered to be the gold standard for quantifying liver fibrosis and inflammation, it suffers from sampling errors that may not reflects the true extent of pathology in addition to being an invasive technique that causes pain and potential complications to patients. As the liver becomes fibrotic, nodules and abnormal spherical areas of cells form as dying liver cells are replaced by regenerating cells. This regeneration of cells causes the liver to become stiffer. Recent radiological advances allow bedside assessment of liver stiffness with various vibrator-assisted imaging techniques such as Fibroscan, acoustic radiation force impulse (ARFI) and magnetic resonance elastography (MRE). Yet none of these methods has been shown to accurately detect and clinically quantify the amount of inflammation. Furthermore, they neglect the potential effect of tissue inflammation on liver stiffness measurement accuracy. The accurate non-invasive assessment of liver inflammation in addition to fibrosis assessment has become increasingly important as it allows for individualized early treatment management. The lack of accuracy and reproducibility, and challenges in assessment has been a major limitation for both clinical management and in liver disease research. Liver damage can be prevented and, in many cases, reversed if liver disease is treated in its early stages in which inflammation precedes fibrosis. Biopsy, while the gold standard is also hardly justifiable in early stages. Biomedical and Metabolic Imaging Branch requires a project to target this dilemma by offering to develop a safe, non-invasive, and affordable alternative to biopsy to assess liver inflammation and provide adjusted quantification of liver stiffness. Tens of millions of liver disease patients may benefit from these techniques either for early disease assessment and treatment or following up treatment effects, or in longitudinal clinical pharmacological studies in which the effect of new medication can be followed in patients without intervention. In order to accomplish the goals of this project, The National Institutes of Health (NIH), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), Biomedical and Metabolic Imaging Branch has a requirement to obtain services of a scientist with extensive expertise in biomedical imaging and medical image analysis with demonstrated understanding of, and ability to apply principles, concepts, practices and standards associated with biomedical imaging and medical image analysis. The scientist must demonstrate experience and understanding of techniques directly applicable to the Biomedical and Metabolic Imaging Branch research (medical imaging, image processing, machine learning, etc.) and must be self-motivated and driven to achieve milestones and exceed goals with minimal direction. Furthermore, they must possess a PhD with 20+ years of demonstrated expertise in biomedical imaging and medical image analysis research. OBJECTIVE: The objective of this requirement is to procure the services of a scientist with specialized skills beyond what the NIDDK's current resources can provide in order to accomplish the goals of this project. Specialized skills include extensive expertise in biomedical imaging and medical image analysis with demonstrated understanding of, and ability to apply principles, concepts, practices and standards associated with biomedical imaging and medical image analysis. The NIDDK specifically requires the Contractor to have the following: PhD degree in Biomedical Engineering or any related field with 20+ years of directly relevant experience in medical imaging, or medical image analysis. Strong research and presentation skills. Ability to define and implement critical studies needed to support hypothesis-based research. Ability to write protocols and study reports, produce and maintain accurate records. Expert in deep learning methodologies: RNN, CNN, LSTM, DNN, etc. Proven experience working with Python, Keras, TensorFlow and/or PyTorch. Expertise in image processing, computer vision and machine learning theory. Proven experience working with OpenCV, ITK, and VTK. Excellent analytical and problem-solving skills. Excellent knowledge in OOP concepts. Experience with Unix/Linux. The Contractor is expected to deliver scientific data and results and implement the following: Develop and implement a 3D MRE technique and algorithms to analyze 3D MRE liver. Develop and implement analysis algorithms optimized for liver tissue deformation imaging driven by inherent cardiac motion to measure liver tissue biomechanical properties. Develop and implement machine learning algorithms to estimate the levels of inflammation and accordingly correct the fibrosis stage using liver tissue biomechanical properties. Write well-designed, testable, efficient code Interpret, analyze and present data; work in fast-paced, result oriented research environment Contribute to project advancement by developing new methods or technologies and troubleshooting existing protocol Write protocols and study reports, produce and maintain accurate records Prepare manuscripts for journal publications To successfully complete the requirement, the following Task Areas shall be accomplished by Contractor: Task Area 1 - Drive discovery and translational research aimed at developing and implementing a 3D MRE technique and algorithms to analyze 3D MRE liver. The Contractor shall create their own research plans with minimum support from the principal investigator. The Contractor shall be able to run research plans independently. Weekly/as needed meetings will be held to evaluate the work and provide directions for next steps. Task Area 2 - Define and implement critical studies needed to develop analysis algorithms optimized for liver tissue deformation imaging driven by inherent cardiac motion to measure liver tissue biomechanical properties. The Contractor's progress will be parodically evaluated and the Contractor will be provided with feedback and directions. Task Area 3 - The Contractor shall develop and implement machine learning algorithms to estimate the levels of inflammation and accordingly correct the fibrosis stage using liver tissue biomechanical properties. Task Area 4 - The Contractor shall make contributions to scientific literature and conferences through publication and presentation of research results. The Contractor shall be evaluated based on preparing manuscripts and abstracts for scientific publications. Task Area 5 - The Contractor shall organize data prior to scientific publication submission. The data will be reviewed and evaluated by the principal investigator. CONTRACTING WITHOUT PROVIDING FOR FULL OR OPEN COMPETITION (INCLUDING BRAND-NAME) DETERMINATION: Ahmed Abdelfadeel of Optimal Systems LLC possesses extensive expertise in biomedical imaging and medical image analysis, which is vital to the Biomedical and Metabolic Imaging Branch study of developing novel medical imaging technologies for the early diagnosis, assessment, and treatment of several chronic diseases related to metabolic disorders and obesity. The Biomedical and Metabolic Imaging Branch has been unable to locate on the market, other Contractors with the required expertise and knowledge. In addition, this is an ongoing project that requires specific knowledge of the history of the development of each technique and the thought process that led to each conclusion. Thus, these unique capabilities cannot be easily replicated in other Contractors. The determination by the Government to award a contract without providing for full and open competition is based upon the market research conducted as prescribed in FAR Part 10 - Market Research. Only one source is available: Per FAR 13.106-1(b)(1) the Contracting Officer has determined OPTIMAL SYSTEMS, LLC to be the only reasonably available source to provide the expert services of a Biomedical Imaging and Medical Image Analysis Scientist the NIDDK requires. PERIOD OF PERFORMANCE: The period of performance for this order is 2/2/2023 - 2/1/2024. The Contractor shall work 40 hours per week, Monday through Friday, totaling 2080 hours per year. PLACE OF PERFORMANCE: National Institutes of Health National Institute of Digestive and Diabetes and Kidney Diseases Building 10 9000 Rockville Pike Bethesda MD 20892 CLOSING STATEMENT: This synopsis is not a request for competitive proposals. However, interested parties may identify their interest and capability in response to this notice. Responses to this notice shall contain sufficient information to establish the interested parties bona-fide capabilities for fulfilling the requirement and include: descriptive literature, delivery timeframe, warranties and/or other information that demonstrates that the offer meets all the foregoing requirements, the prompt payment discount terms, the F.O.B. Point (Destination or Origin), the Unique Entity ID (UEI), the Taxpayer Identification Number (TIN), and the certification of business size. All offerors must have an active registration in the System for Award Management (SAM) www.SAM.gov. A determination by the Government not to compete this proposed contract based upon responses to this notice is solely within the discretion of the Government. The information received will normally be considered solely for the purposes of determining whether to proceed on a non-competitive basis or to conduct a competitive procurement. - All responsible sources may submit a bid, proposal, or quotation which shall be considered by the agency. All responses to this notice shall be submitted electronically by 12:00 pm Eastern Standard Time, on Friday, January 13, 2023, to the Contract Specialist, Kerry-Ann Chisholm, at kerry-ann.chisholm@nih.gov. Assessment of Capability: Lowest Price Technically Acceptable