PyTIA: Voxel-Wise Time-Integrated Activity Maps

PyTIA is a Python package for computing voxel-wise time-integrated activity (TIA) maps from PET/SPECT imaging data.

Features

Multi-Timepoint Analysis

• Supports 2 or more activity images at different timepoints
• Automatic curve classification: rising, hump (gamma), falling (exponential)
• Advanced fitting models with physical decay tail extrapolation
• Bootstrap uncertainty quantification

Single-Timepoint Analysis

Calculate TIA from a single activity map using one of three methods:

1. Physical Decay — Pure radioactive decay extrapolation
2. Hänscheid Method — Effective half-life (accounting for biological clearance)
3. Prior Half-Life — Global or organ/lesion-specific half-lives from segmentation

Processing Features

• Automatic masking and denoising
• Noise floor filtering
• Regional ROI aggregation
• Comprehensive status tracking

Installation

pip install pytia

Quick Start

CLI

pytia run --config config.yaml

Python API

from pytia import run_tia

result = run_tia(
    images=["activity_t0.nii.gz", "activity_t1.nii.gz", "activity_t2.nii.gz"],
    times=[0.0, 30.0, 60.0],
    config={"physics": {"half_life_seconds": 21600.0}, "io": {"output_dir": "./output"}}
)

Documentation

• docs/USER_GUIDE.md — Comprehensive usage guide
• examples/ — Example scripts and configs
• docs/CONFIG.md — Configuration reference

License

MIT License — see LICENSE

PyTIA computes voxel-wise