SpineTool

Ekaterina, P., Peter, V., Smirnova, D., Vyacheslav, C., Ilya, B. (2023). SpineTool is an open-source software for analysis of morphology of dendritic spines. Scientific Reports.13. 10.1038/s41598-023-37406-4.

Dendritic spines form most excitatory synaptic inputs in neurons and these spines are altered in many neurodevelopmental and neurodegenerative disorders. Reliable methods to assess and quantify dendritic spines morphology are needed, but most existing methods are subjective and labor intensive. To solve this problem, we developed an open-source software that allows segmentation of dendritic spines from 3D images, extraction of their key morphological features, and their classification and clustering. Instead of commonly used spine descriptors based on numerical metrics we used chord length distribution histogram (CLDH) approach. CLDH method depends on distribution of lengths of chords randomly generated within dendritic spines volume. To achieve less biased analysis, we developed a classification procedure that uses machine-learning algorithm based on experts’ consensus and machine-guided clustering tool. These approaches to unbiased and automated measurements, classification and clustering of synaptic spines that we developed should provide a useful resource for a variety of neuroscience and neurodegenerative research applications.

SpineTool Tutorial

System requirements

Windows 8 or newer
Minimum 1GB RAM
Minimum 6 GB disk space

Install

Download code
Unzip CGAL files next to code, e.g. PATH_TO_CODE\CGAL\...
Install Anaconda
Open Anaconda
Execute

cd PATH_TO_CODE
conda create --name spine-analysis -c conda-forge --file requirements.txt -y

Run

Open Anaconda
Execute

cd PATH_TO_CODE
conda activate spine-analysis
jupyter notebook

Example datasets

example_dendrite

Dataset consist of a .tif image of a dendrite, 22 polygonal meshes of dendrite spines and a dendrite polygonal mesh computed with dendrite-segmentation.ipynb notebook. This example dataset provides a demonstration of dendrite image segmentation performance and functionality of the methods from the Utilities.ipynb notebook.

0.025 0.025 0.1 dataset

Dataset consists of 270 polygonal meshes of dendrite spines related to 54 dendrites and of 54 polygonal meshes for dendrites computed with dendrite-segmentation.ipynb notebook. A dataset subdirectory named "manual_classification" contains the expert markups from 8 people obtained using the spine-manual-classification.ipynb and the results of merging the classifications to obtain a consensus classification. This example dataset provides a demonstration of dendrite spines classification and clustering performance and functionality of the methods from the Utilities.ipynb notebook.

Citation

TY  - JOUR
AU  - Ekaterina, Pchitskaya
AU  - Peter, Vasiliev
AU  - Smirnova, Daria
AU  - Vyacheslav, Chukanov
AU  - Ilya, Bezprozvanny
PY  - 2023/06/29
SP  - 
T1  - SpineTool is an open-source software for analysis of morphology of dendritic spines
VL  - 13
DO  - 10.1038/s41598-023-37406-4
JO  - Scientific Reports
ER  -

spbstu-applied-math/SpineTool.Software