Software for Analyzing Brain Scans
ScAnVP (Scan Analysis and Visualization Processor) software has been developed by investigators at the Center for Neurosciences (CFN) of The Feinstein Institute for Medical Research (FIMR) for processing and analyzing multimodality neuroimaging data. This software, copyright © 2024 The Feinstein Institute for Medical Research, is being made freely available to the research community.
The Feinstein Institute requests the following acknowledgment in any communication reporting on research that made use of the software, including but not limited to preprints, reprints, Web sites, posts on social media, circulated reports, or publications of any kind:
“The use in this work of ScAnVP software, copyright © 2024 The Feinstein Institute for Medical Research, is hereby acknowledged.”
Please read the warning in the box below, then, if you want to continue, click “latest version” to download free software developed by the the Center for Neurosciences at The Feinstein Institute for Medical Research (FIMR) for processing and analyzing multimodality neuroimaging data..
The package works only in conjunction with MATLAB and is designed only for PCs running under the Windows operating system.
Many Web browsers and institutional servers block the downloading of executable files, and so, to avoid this problem, we are now supplying the package as a single Zip file, named “ScAnVP7.0web.zip.NS”. This means that the file you download will have to be renamed before you can use it. Simply rename it “ScAnVP7.0web.zip” (in other words, remove the characters “.NS”).
Before you extract the software package from “ScAnVP7.0web.zip”, move the Zip file to a convenient place in the directory structure of your system. (You may wish make a new directory/folder named “scanvp” in some convenient location on your system (e.g., c:\scanvp), and then move the Zip file to the new directory/folder. In any event, the extraction process will create a new subdirectory/folder wherever the Zip file resides.) Then extract the contents of “ScAnVP7.0web.zip” (“unZip” it) with standard Zip software. (You may find the option to extract the contents of the Zip file by right-clicking on it.)
After you unZip the file, the software creates a set of folders containing various programs, utilities, and documentation. The folder labeled “documentation” provides detailed information about the implementation of the analytic toolbox, as well as step-by-step instructions (with examples) on its use. You’ll find documentation on further installation in a file called “README7.0w.txt”. Read a general description of the software in the file “GENERALDescription7.0w.doc”. Basic operations are described under Help, on the main menu. Many users will be interested mainly in the SSM-PCA module of the software; you will find step-by-step instructions for that module in the file named “ScAnVP_Step_by_step_Instructions_2016.doc”.
If you find you cannot download the file, or if you have difficulty extracting the contents of the Zip file, please contact Dr. Yilong Ma at yma@northwell.edu.
ScAnVP software has undergone continuous development since the early 1990s, under the direction of Dr. Phoebe Spetsieris, Associate Investigator at FIMR. ScAnVP includes many applications for the retrieval, visualization, and group processing of single-volume brain images acquired via nuclear medicine (PET, SPECT) and other radiological techniques such as time-independent MRI (ASL, VBM, DTI, and ALFF of BOLD fMRI). Its wide-ranging functions include:
- Extraction and format conversion of brain images from various scanners;
- Graphic display of image information, such as rendering and cross-modality fusion;
- Spatial transformation and arithmetic manipulation of images;
- Creation of a brain atlas from the predefined volume of interest (VOI);
- Computation of VOI data from dynamic images; and
- Calculation of neurobiological parameters of interest from both functional and anatomical brain images.
ScAnVP also incorporates many useful computing routines for brain mapping analyses of VOI’s as well as individual voxels. In particular, ScAnVP has implemented one of the most versatile multivariate statistical approaches in the field of neuroimaging: the Scaled Subprofiling Model (SSM).
SSM, which is based on the use of principal component analysis (PCA), enables a disease-related covariance pattern to be identified from a single principal component (PC) or a linear combination of PC’s whose expression in individual subjects either discriminates between patients and healthy controls or correlates with independent measures of disease severity or behavioral performance. A topographic rating (TPR) algorithm is also available to compute the expression of this pattern prospectively in individual subjects.
The method is entirely data-driven: all computations for pattern derivation and prospective applications can be conducted automatically and blinded to the clinical, genetic, or treatment status of each subject. Principal component analysis with the Scaled Subprofiling Model (SSM-PCA) has led to a series of innovative research findings that establish viable imaging biomarkers in patients with a wide variety of neurodegenerative and neuropsychiatric disorders.
These biomarkers have been shown to be highly sensitive in enhancing differential diagnosis, assessing disease progression and its clinical correlates, and evaluating the therapeutic efficacy of emerging experimental treatments. SSM-PCA can be applied to brain images obtained via various imaging modalities, radiotracers, and imaging systems, as well as to images from diverse patient populations and even from various species of laboratory animal.