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Published on: May 19, 2020
The effect of limited MR field of view in MR/PET attenuation correction
Gaspar Delso1, Axel Martinez-Möller, Ralph A Bundschuh
1Nuklearmedizin, Klinikum Rechts der Isar, Technische Universität München, 81675 München, Germany. gaspar.delso@tum.de
Purpose:
A critical question in the development of combined MR/PET scanners is whether MR can provide the tissue attenuation data required for PET reconstruction. Unfortunately, MR images are often unable to encompass the entire patient. The resulting truncation in the transverse plane leads to incomplete attenuation maps, causing artifacts in the reconstructed PET image. This article describes the experiments performed to quantify these artifacts. A method to compensate the missing data was evaluated to determine whether software correction is possible or whether additional transmission hardware has to be included in the scanner.
Methods:
Three studies were made. First, simulated PET data were used to quantify the bias due to an incomplete attenuation map. A set of spherical lesions was simulated in the lungs and mediastinum of a patient. The data were reconstructed with complete and partial attenuation maps and the uptake differences were evaluated. Second, clinical data from PET/CT oncology patients were used. To reproduce the expected conditions in an MR/PET scanner, only patients scanned with the arms resting along the body were considered. These scans were then used to create maps of the reconstruction bias due to field of view (FOV) limitations. Lastly, a PET reconstruction with incomplete attenuation data was evaluated as a means to obtain attenuation information beyond the MR FOV. The patient outline was automatically segmented with a three-dimensional snake algorithm and used to fill the truncated data in the attenuation map.
Results:
Average bias up to 15% and local biases up to 50% were estimated when PET data were reconstructed with incomplete attenuation information. Completing the attenuation map with data extracted from a PET prereconstruction globally reduced these biases to below 10%. This correction proved to be tolerant to inaccuracies in positioning and attenuation values. However, local artifacts up to 20% could still be found near the edges of the MR FOV.
Conclusions:
MR FOV restrictions can indeed make the reconstructed PET data unacceptable for diagnostic purposes. Biases can be globally compensated by automatic preprocessing of the attenuation map. However, inaccuracies in the correction will result in small artifacts near the periphery of the image that could lead to false-positive findings.
Insights
Combined MR/PET scanners face challenges with incomplete attenuation maps from MR images. Software correction can reduce artifacts, but peripheral inaccuracies may still cause false positives in PET reconstructions.
Area of Science:
- Medical Imaging
- Radiology
- Nuclear Medicine
Background:
- Combined Magnetic Resonance (MR) and Positron Emission Tomography (PET) scanners offer advanced diagnostic capabilities.
- Accurate attenuation correction is crucial for quantitative PET imaging.
- MR images, often used for attenuation correction, may have limited fields of view (FOV), leading to incomplete data.
Purpose of the Study:
- To quantify artifacts in PET reconstructions caused by incomplete MR-based attenuation maps.
- To evaluate a software-based method for compensating missing attenuation data.
- To determine if hardware additions are necessary for MR/PET scanners.
Main Methods:
- Simulated PET data with spherical lesions were reconstructed using complete and partial attenuation maps.
- Clinical PET/CT oncology data (arms down) were used to map reconstruction bias from MR FOV limitations.
- A 3D snake algorithm segmented patient outlines to fill truncated attenuation data.
Main Results:
- Incomplete attenuation maps caused average biases up to 15% and local biases up to 50% in PET reconstructions.
- Completing attenuation maps using PET prereconstruction data reduced global biases to below 10%.
- Local artifacts up to 20% persisted near MR FOV edges despite correction.
Conclusions:
- MR FOV restrictions can render reconstructed PET data diagnostically unacceptable.
- Automatic attenuation map preprocessing can globally compensate for biases.
- Residual peripheral inaccuracies may lead to false-positive findings in PET imaging.
