Inactive

INTRODUCTION PURSUANT TO FAR Subpart 5.2—Synopses of Proposed Contract Actions, THIS IS A PRE-SOLICITATION NOTICE OF A PROPOSED CONTRACT TO ACTION. The National Institute on Drug Abuse (NIDA), Office ... INTRODUCTION PURSUANT TO FAR Subpart 5.2—Synopses of Proposed Contract Actions, THIS IS A PRE-SOLICITATION NOTICE OF A PROPOSED CONTRACT TO ACTION. The National Institute on Drug Abuse (NIDA), Office of Acquisitoin, Contracts Management Branch Blue on behalf of the National Institute on Aging intends to negotiate and award a contract for methodological and technical expertise in the processing of functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) as well as computed tomography (CT) images for the Balitmore Longitudinal Study of Aging (BLSA). EXTENT OF COMPETITION This acquisition is full and open with no set-aside restrictions. NORTH AMERICAN INDUSTRY CLASSIFICATION SYSTEM (NAICS) CODE The intended procurement is classified under NAICS code 621512 with a Size Standard of $16.5 million. REGULATORY AUTHORITY The resultant contract will include all applicable provisions and clauses in effect through the Federal Acquisition Circular (FAC) 2020-01 dated November 12, 2019. This acquisition is conducted under the procedures as prescribed in FAR Subpart 15—Contracting by Negotiation at an amount exceeding the simplified acquisition threshold inclusive of options. DESCRIPTION OF REQUIREMENT Project Description The Contactor shall work in collaboration with BLSA investigators and study staff of the National Institute on Aging to provide image processing services as follows: For each type of brain imaging data the contractor shall retrieve data and co-register all image data into a common coordinate system. Apply image processing tools developed and validated under a prior contract HHSN27101400118C: Define gray matter regions of interest. Targeted regions include the Hippocampus, Posterior Cingulate, Precuneus, and Medial Frontal cortex. DTI Pre-processing. The Contractor will perform and provide the Government with pre-processed image data, yielding fractional anisotropy (FA), mean diffusivity (MD), principal eigenvector (v1), and tensor (D) images for each subject. Define white matter tracts. The FA maps for each subject will be labeled with a white matter atlas (i.e., the Johns Hopkins “Eve” atlas). rs-fMRI Pre-processing. Pre-processing will yield functional connectivity maps for each gray matter and white matter region of interest. The Contractor shall use the defined gray matter regions of interest on structural data for rs-fMRI analysis. Region of Interest Analysis. The Contractor will generate and provide to the LBN, NIA a table of means and standard deviations of rs-fMRI, FA, and MD for all regions of interest. Implement mass-univariate temporal modeling. The Contractor shall work with the LBN/NIA team and their collaborators to select the most promising temporal association inference models (e.g., “causal”) to implement in current toolboxes. Characterize temporal inference in simulation. The Contractor shall perform data-driven simulations to verify that the inference method empirically performs according to theoretical predictions and is compatible with standard approaches for multiple comparisons corrections (e.g., false discovery rate [FDR]). Apply multi-modal temporal inference to BLSA 1.5T/3T cohort. The Contractor shall work with LBN investigators to execute structural-functional-covariate analysis in the form of a general linear model (GLM, voxelwise model of the form: Y=? X ) where both the regressors and the regressands may be longitudinally sampled imaging variables. The temporal relationships between sequenced regressors and regressands will be assessed. Additional non-imaging data may be provided for each subject in the form of an Excel document. These will be run as additional regressors. Scanner calibration. The Contractor shall develop and evaluate strategies for scanner calibration/correction, including modeling scanner changes as nuisance variables and using image preprocessing corrections. Develop, validate and apply image processing tools for BLSA MRI of the thigh, CT of the abdomen as well as CT of the leg. Develop, validate and apply image processing tools for BLSA MRI of the thigh, CT of the abdomen as well as CT of the leg. Support method translation to NIA intramural researchers. Purpose and Objectives The purpose of this requirement is to obtain methodological and technical expertise in the processing of functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) as well as computed tomography (CT) images. These services will continue the established protocols and statistical approaches for the analysis of white matter correlates of alterations in functional connectivity as well as functional connectivity correlates of white matter alterations in the brain. At the same time, this requirement will develop and implement new image processing techniques for the evaluation of body composition and bone morphometry in the abdomen and leg. The provision of these capabilities will facilitate the continued use of BLSA data in state-of-the-art imaging studies related to cognitive and motor function. Period of Performance The initial contract period will be one year beginning 9/30/20-9/29/21, plus 4 option years. It is anticipated that this contract will be a cost-reimbursement type contract. CLOSING STATEMENT The solicitation will be issued on or about January 7, 2020, and bids or proposals will be due about 30 days after the solicitation release date.

Inactive

SOURCES SOUGHT NOTICE Solicitation Number: 75N95020R00010 Title: Baltimore Longitudinal Study of Aging (BLSA) Image Processing Services. Classification Code: B537 NAICS Code: 621512 Description: This ... SOURCES SOUGHT NOTICE Solicitation Number: 75N95020R00010 Title: Baltimore Longitudinal Study of Aging (BLSA) Image Processing Services. Classification Code: B537 NAICS Code: 621512 Description: This is a Sources Sought notice. This is NOT a solicitation for proposals, proposal abstracts, or quotations. The purpose of this notice is to obtain information regarding the availability and capability of all qualified sources to perform a potential requirement. This notice is issued to help determine the availability of qualified companies technically capable of meeting the Government requirement and to determine the method of acquisition. It is not to be construed as a commitment by the Government to issue a solicitation or ultimately award a contract. Responses will not be considered as proposals or quotes. No award will be made as a result of this notice. The Government will NOT be responsible for any costs incurred by the respondents to this notice. This notice is strictly for research and information purposes only. Background: Begun in 1958, the BLSA is a continuously enrolled cohort study of community dwelling adults that seeks to evaluate change in medical, physiological, cognitive and physical function across the adult life span. In the modern era of the BLSA, study visits incorporate a wide range of tests including imaging studies. MRI evaluations of the brain have been acquired in subsets of BLSA participants since 1994 as part of the NIA Laboratory of Behavioral Neuroscience (LBN) research program on early markers of Alzheimer’s disease and cognitive decline, more generally. In addition to brain MRI, MRI images at mid-thigh have been acquired by the BLSA since 2011 to describe muscle and fat content in the leg. CT was introduced into the BLSA protocol in 2006 and captures information on bone, muscle, and fat. Evaluation of bone morphometry offers a quantitative assessment of osteoporosis, a risk factor for fracture and subsequent disability. In addition to decreases in bone density with age, it is understood that the quantity and distribution of muscle and fat change with age. These shifts in body composition are hypothesized to be key contributors to aging syndromes, chronic disease and disability. Imaging studies offer an opportunity to describe underlying tissue composition that is masked in anthropometric measurements such as body mass index or waist circumference. Rapid advances in image processing have occurred since the initiation of body composition and bone morphometry assessments in BLSA. The application of up to date methods and best practices for both newly acquired and historical images from thigh MRI and CT will offer more refined body composition information capable of addressing current research questions. Purpose and Objectives: The purpose of this requirement is to obtain methodological and technical expertise in the processing of functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) as well as computed tomography (CT) images. These services will continue the established protocols and statistical approaches for the analysis of white matter correlates of alterations in functional connectivity as well as functional connectivity correlates of white matter alterations in the brain. At the same time, this requirement will develop and implement new image processing techniques for the evaluation of body composition and bone morphometry in the abdomen and leg. The provision of these capabilities will facilitate the continued use of BLSA data in state-of-the-art imaging studies related to cognitive and motor function. Project requirements: The Contactor shall work in collaboration with BLSA investigators and study staff of the National Institute on Aging to provide image processing services as follows: For each type of brain imaging data the contractor shall retrieve data and co-register all image data into a common coordinate system. The Contractor will coordinate with the NIA to ensure that consistent common imaging reference spaces are used across projects. Apply image processing tools developed and validated under a prior contract HHSN27101400118C neuroimaging requirements: Define gray matter regions of interest. Targeted regions include the Hippocampus, Posterior Cingulate, Precuneus, and Medial Frontal cortex. DTI Pre-processing. The Contractor will perform and provide the Government with pre-processed image data, yielding fractional anisotropy (FA), mean diffusivity (MD), principal eigenvector (v1), and tensor (D) images for each subject. Define white matter tracts. The FA maps for each subject will be labeled with a white matter atlas (i.e., the Johns Hopkins “Eve” atlas). rs-fMRI Pre-processing. Pre-processing will yield functional connectivity maps for each gray matter and white matter region of interest. The Contractor shall use the defined gray matter regions of interest on structural data for rs-fMRI analysis. Region of Interest Analysis. The Contractor will generate and provide to the LBN, NIA a table of means and standard deviations of rs-fMRI, FA, and MD for all regions of interest. Implement mass-univariate temporal modeling. The Contractor shall work with the LBN/NIA team and their collaborators to select the most promising temporal association inference models (e.g., “causal”) to implement in current toolboxes. Characterize temporal inference in simulation. The Contractor shall perform data-driven simulations to verify that the inference method empirically performs according to theoretical predictions and is compatible with standard approaches for multiple comparisons corrections (e.g., false discovery rate [FDR]). Apply multi-modal temporal inference to BLSA 1.5T/3T cohort. The Contractor shall work with LBN investigators to execute structural-functional-covariate analysis in the form of a general linear model (GLM, voxelwise model of the form: Y=? X) where both the regressors and the regressands may be longitudinally sampled imaging variables. The temporal relationships between sequenced regressors and regressands will be assessed. Additional non-imaging data may be provided for each subject in the form of an Excel document. These will be run as additional regressors. Scanner calibration. The Contractor shall develop and evaluate strategies for scanner calibration/correction, including modeling scanner changes as nuisance variables and using image preprocessing corrections. Develop, validate and apply image processing tools for BLSA MRI of the thigh, CT of the abdomen as well as CT of the leg. The Contractor shall develop strategies for the segmentation and quantification of regions of interest captured in the BLSA thigh MRI protocol including, but not limited to: subcutaneous fat, inter-muscular fat, and muscle. The Contractor shall develop strategies for the segmentation and quantification of regions of interest in images captured in the BLSA CT protocol including images of the abdomen, thigh, as well as the proximal, mid and distal tibia. Regions of interest include but are not limited to: Abdominal subcutaneous and visceral fat Thigh subcutaneous fat, inter-muscular fat, muscle, and bone Tibia subcutaneous fat, inter-muscular fat, muscle, and bone The Contractor shall apply the image processing tools to both newly acquired images as well as the library of historical images to generate fully harmonized longitudinal thigh MRI and CT imaging data sets. Support method translation to NIA intramural researchers. The Contractor shall provide BLSA investigators and study staff with documentation of methods, including user manuals, and assist with installation and implementation of software as necessary. The Contractor shall document methodological contributions in the form of peer-reviewed publications. Anticipated period of performance: The period of performance for this contract will include a base year (09/30/20 – 09/29/21) with four (4) option years. Other important considerations: The Government will provide de-identified BLSA MRI and CT imaging data to the Contractor and associated metadata necessary for analyses, such as sex, age, cognitive status, as well as health variables. All data provided to the Contractor must be treated as confidential and not be disclosed to any third party. Capability statement /information sought: Information sent should be relevant and specific in the technical area under consideration, on each of the following qualifications: (1) Experience: An outline of previous similar projects and work; (2) Personnel: Name, professional qualifications and specific experience of scientific and/or technical personnel who may be assigned as project director and other key positions; (3) Facilities: Availability and description of facilities and equipment required to conduct this type of work. Any other specific and relevant information about this particular area of procurement that would improve our consideration and evaluation of the information presented is desirable. Interested organizations must demonstrate and document, in any capability statements submitted, extensive experience with and the ability to perform the above tasks. Organizations should demonstrate capability to administer and coordinate interrelated tasks in an effective and timely manner. Documentation may include, but not be limited to, contracts both Government and commercial the organization performed, references, i.e., names, titles, telephone numbers and any other information serving to document the organizations capability, e.g., awards, commendations, etc. All capability statements must provide the following: 1) company name and address; 2) point of contact, 3) phone/fax/email; 4) NAICS Code(s); 5) business size and status; 6) capability information in response to the requirement and qualifications identified in this notice; and 7) type of small business your organization classifies itself as (i.e.: women-owned, HUBZONE, etc.). Written capability statements must be RECEIVED NO LATER THAN November 29, 2019 and should be sent electronically to Jon Gottschalk (jon.gottschalk@nih.gov). THIS NOTICE IS NOT A REQUEST FOR PROPOSALS (RFP) OR A REQUEST FOR QUOTATIONS (RFQ). This notice does not obligate the Government to award a contract or otherwise pay for the information provided in response. The Government reserves the right to use information provided by respondents for any purpose deemed necessary and legally appropriate. Any organization responding to this notice should ensure that its response is complete and sufficiently detailed to allow the Government to determine the organization's qualifications to perform the work. Any proprietary information should be so marked. Respondents are advised that the Government is under no obligation to acknowledge receipt of the information received or to provide feedback to the respondents with respect to any information submitted. After a review of the responses received, an RFQ or RFP may be published. However, responses to this notice will not be considered an adequate response to a RFQ or RFP.