PET Detector Time-Lag Calibration Using TOF Image Data
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Solution Overview
Problem
Existing Time-of-Flight (TOF) Positron Emission Tomography (PET) systems require manual time calibration using external radiation sources, which is time-consuming and exposes technicians to radiation.
Innovation Solution
A PET apparatus that estimates time lag between detectors using TOF information and reconstructed images, allowing for automated and radiation-free calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual time calibration using external radiation source is performed, then TOF calibration accuracy is improved, but calibration time and radiation exposure increase
Solution Approach 1:
The system performs self-calibration by automatically estimating time lag between detectors using TOF information from coincidence data and reconstructed images, eliminating the need for manual calibration with external radiation sources. The processing circuitry autonomously identifies time lag and adjusts detection timing without human intervention.
Solution Approach 2:
The patent uses TOF information from coincidence counting data as an intermediary to estimate time lag between detectors. Instead of directly measuring time lag with external equipment, the system uses the TOF data already collected during normal operation to indirectly determine and correct timing offsets.
2Measurement precision
If manual time calibration using external radiation source is performed, then TOF calibration accuracy is improved, but operator radiation exposure increases
Solution Approach 1:
The system performs self-calibration by automatically estimating time lag between detectors using TOF information from coincidence data and reconstructed images, eliminating the need for manual calibration with external radiation sources. The processing circuitry autonomously identifies time lag and adjusts detection timing without human intervention.
Solution Approach 2:
The patent converts the TOF information, which is normally used only for image reconstruction, into a useful resource for calibration. By repurposing the existing TOF data and coincidence information from patient scans, the system transforms routine operational data into a calibration tool, eliminating the need for separate calibration procedures involving radiation exposure.
3Productivity
If automated calibration using TOF information is implemented, then calibration efficiency is improved, but system complexity increases
Solution Approach 1:
The processing circuitry performs multiple functions: it reconstructs PET images from coincidence data, calculates TOF information for image quality, and simultaneously uses the same TOF information for time lag estimation and calibration. This multi-functionality eliminates the need for separate calibration hardware or procedures.
Solution Approach 2:
The system performs self-calibration by automatically estimating time lag between detectors using TOF information from coincidence data and reconstructed images, eliminating the need for manual calibration with external radiation sources. The processing circuitry autonomously identifies time lag and adjusts detection timing without human intervention.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Facilitates efficient and simplified TOF calibration, reducing manual effort and radiation exposure by using collected patient data for calibration, enabling accurate TOF reconstruction.
Implementation Method 1
a PET detector 101... detects a gamma ray that is emitted from living tissue in which positron-emitting radionuclide that is given to a subject P is captured
Implementation Method 2
In recent years, in a Time-of-Flight (TOF)-Positron Emission computed Tomography (PET) apparatus, TOF resolution is improved and it becomes possible to perform reconstruction using TOF information with improved accuracy
Data Source
AI summary
A PET apparatus according to one embodiment includes processing circuitry. The processing circuitry acquires list mode data. The processing circuitry reconstructs a PET image based on the list mode data. The processing circuitry identifies first coincidence data that is obtained by coincidence counting by a first detector and a second detector that is different from the first detector from among a plurality of pieces of coincidence data included in the list mode data. The processing circuitry estimates a time lag amount between the first detector and the second detector based on TOF information included in the first coincidence data and the PET image.


