Tissue Probability-Based Attenuation Correction for Brain PET/MR by Using SPM8

Teuho, Jarmo; Lindén, Jani; Johansson, Jarkko; Tuisku, Jouni; Tuokkola, Terhi; Teräs, Mika

doi:10.1109/tns.2015.2513064

Cited by 11 publications

(10 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Zaidi and Fei proposed using T1-weighted MRI images, which are co-registered to PET data and segmented by fuzzy C-means clustering to air, scalp, skull, gray matter, white matter, and nasal sinuses [57,58]. Statistical parametric mapping version 8 (SPM8) has also been applied to extract the bone component from T1-weighted images, which is added to the Dixon-based attenuation map [59,60] or by deriving a threeto six-class attenuation map from T1-images alone [32,61]. The advantage of these methods is that they are straightforward to apply across multitude of datasets, as the only requirement is access to T1 data, which is collected routinely.…”

Section: Mrac Methods Based On Image Segmentationmentioning

confidence: 99%

Magnetic Resonance-Based Attenuation Correction and Scatter Correction in Neurological Positron Emission Tomography/Magnetic Resonance Imaging—Current Status With Emerging Applications

Teuho

Torrado‐Carvajal

Herzog³

et al. 2020

Front. Phys.

View full text Add to dashboard Cite

In this review, we will summarize the past and current state-of-the-art developments in attenuation and scatter correction approaches for hybrid positron emission tomography (PET) and magnetic resonance (MR) imaging. The current status of the methodological advances for producing accurate attenuation and scatter corrections on PET/MR systems are described, in addition to emerging clinical and research applications. Future prospects and potential applications that benefit from accurate data corrections to improve the quantitative accuracy and clinical applicability of PET/MR are also discussed. Novel clinical and research applications where improved attenuation and scatter correction methods are beneficial are highlighted.

show abstract

Section: Mrac Methods Based On Image Segmentationmentioning

confidence: 99%

Magnetic Resonance-Based Attenuation Correction and Scatter Correction in Neurological Positron Emission Tomography/Magnetic Resonance Imaging—Current Status With Emerging Applications

Teuho

Torrado‐Carvajal

Herzog³

et al. 2020

Front. Phys.

View full text Add to dashboard Cite

show abstract

“…sCT images were created based on the MRAC method [17,18], which enables creation of MRI-based attenuation maps for up to six tissue classes and has been shown to perform with good accuracy regarding PET quantification. The method is simple, fast, and straightforward to apply across different PET-MRI and MRI-only RTP systems.…”

Section: Generation Of Sct Images For Mri-only Rtpmentioning

confidence: 99%

“…Bone segmentation accuracy was determined by analysis of bone volume and Dice similarity coefficient (DSC). The MRAC method has previously been assessed in PET-MRI of the brain concerning both quantitative and visual accuracy of [18F]-fluorodeoxyglucose ([18F]-FDG) PET images [17,18].…”

Section: Introductionmentioning

confidence: 99%

Assessment of MRI-Based Attenuation Correction for MRI-Only Radiotherapy Treatment Planning of the Brain

et al. 2020

View full text Add to dashboard Cite

Magnetic resonance imaging-only radiotherapy treatment planning (MRI-only RTP) and positron emission tomography (PET)–MRI imaging require generation of synthetic computed tomography (sCT) images from MRI images. In this study, initial dosimetric evaluation was performed for a previously developed MRI-based attenuation correction (MRAC) method for use in MRI-only RTP of the brain. MRAC-based sCT images were retrospectively generated from Dixon MR images of 20 patients who had previously received external beam radiation therapy (EBRT). Bone segmentation performance and Dice similarity coefficient of the sCT conversion method were evaluated for bone volumes on CT images. Dose calculation accuracy was assessed by recalculating the CT-based EBRT plans using the sCT images as the base attenuation data. Dose comparison was done for the sCT- and CT-based EBRT plans in planning target volume (PTV) and organs at risk (OAR). Parametric dose comparison showed mean relative differences of <0.4% for PTV and <1.0% for OARs. Mean gamma index pass rates of 95.7% with the 2%/2 mm agreement criterion and 96.5% with the 1%/1 mm agreement criterion were determined for glioma and metastasis patients, respectively. Based on the results, MRI-only RTP using sCT images generated from MRAC images can be a feasible alternative for radiotherapy of the brain.

show abstract

“…Three m-maps were used to evaluate the effect of MRAC on the performance of scatter correction in both the phantom and the patient (13). MRAC 3class and MRAC 2class for patients were created using a method described previously (14). MRAC 3class was created similarly to that presented in Teuho et al (14) whereas MRAC 2class was created by replacing the skull m-values with soft tissue, ignoring the patient skull.…”

Section: Mr-based and Ct-based Attenuation Correction For Phantom Andmentioning

confidence: 99%

“…MRAC 3class and MRAC 2class for patients were created using a method described previously (14). MRAC 3class was created similarly to that presented in Teuho et al (14) whereas MRAC 2class was created by replacing the skull m-values with soft tissue, ignoring the patient skull. For CTAC, the head of each subject was carefully segmented out by semiautomatic regional contouring tools in Carimas 2.8 (Turku PET Centre).…”

Section: Mr-based and Ct-based Attenuation Correction For Phantom Andmentioning

confidence: 99%

Quantitative Evaluation of 2 Scatter-Correction Techniques for ¹⁸F-FDG Brain PET/MRI in Regard to MR-Based Attenuation Correction

et al. 2017

View full text Add to dashboard Cite

In PET, corrections for photon scatter and attenuation are essential for visual and quantitative consistency. MR attenuation correction (MRAC) is generally conducted by image segmentation and assignment of discrete attenuation coefficients, which offer limited accuracy compared with CT attenuation correction. Potential inaccuracies in MRAC may affect scatter correction, because the attenuation image (μ-map) is used in single scatter simulation (SSS) to calculate the scatter estimate. We assessed the impact of MRAC to scatter correction using 2 scatter-correction techniques and 3 μ-maps for MRAC. The tail-fitted SSS (TF-SSS) and a Monte Carlo-based single scatter simulation (MC-SSS) algorithm implementations on the Philips Ingenuity TF PET/MR were used with 1 CT-based and 2 MR-based μ-maps. Data from 7 subjects were used in the clinical evaluation, and a phantom study using an anatomic brain phantom was conducted. Scatter-correction sinograms were evaluated for each scatter correction method and μ-map. Absolute image quantification was investigated with the phantom data. Quantitative assessment of PET images was performed by volume-of-interest and ratio image analysis. MRAC did not result in large differences in scatter algorithm performance, especially with TF-SSS. Scatter sinograms and scatter fractions did not reveal large differences regardless of the μ-map used. TF-SSS showed slightly higher absolute quantification. The differences in volume-of-interest analysis between TF-SSS and MC-SSS were 3% at maximum in the phantom and 4% in the patient study. Both algorithms showed excellent correlation with each other with no visual differences between PET images. MC-SSS showed a slight dependency on the μ-map used, with a difference of 2% on average and 4% at maximum when a μ-map without bone was used. The effect of different MR-based μ-maps on the performance of scatter correction was minimal in non-time-of-flightF-FDG PET/MR brain imaging. The SSS algorithm was not affected significantly by MRAC. The performance of the MC-SSS algorithm is comparable but not superior to TF-SSS, warranting further investigations of algorithm optimization and performance with different radiotracers and time-of-flight imaging.

show abstract

Tissue Probability-Based Attenuation Correction for Brain PET/MR by Using SPM8

Cited by 11 publications

References 26 publications

Magnetic Resonance-Based Attenuation Correction and Scatter Correction in Neurological Positron Emission Tomography/Magnetic Resonance Imaging—Current Status With Emerging Applications

Magnetic Resonance-Based Attenuation Correction and Scatter Correction in Neurological Positron Emission Tomography/Magnetic Resonance Imaging—Current Status With Emerging Applications

Assessment of MRI-Based Attenuation Correction for MRI-Only Radiotherapy Treatment Planning of the Brain

Quantitative Evaluation of 2 Scatter-Correction Techniques for ¹⁸F-FDG Brain PET/MRI in Regard to MR-Based Attenuation Correction

Contact Info

Product

Resources

About

Tissue Probability-Based Attenuation Correction for Brain PET/MR by Using SPM8

Cited by 11 publications

References 26 publications

Magnetic Resonance-Based Attenuation Correction and Scatter Correction in Neurological Positron Emission Tomography/Magnetic Resonance Imaging—Current Status With Emerging Applications

Magnetic Resonance-Based Attenuation Correction and Scatter Correction in Neurological Positron Emission Tomography/Magnetic Resonance Imaging—Current Status With Emerging Applications

Assessment of MRI-Based Attenuation Correction for MRI-Only Radiotherapy Treatment Planning of the Brain

Quantitative Evaluation of 2 Scatter-Correction Techniques for 18F-FDG Brain PET/MRI in Regard to MR-Based Attenuation Correction

Contact Info

Product

Resources

About

Quantitative Evaluation of 2 Scatter-Correction Techniques for ¹⁸F-FDG Brain PET/MRI in Regard to MR-Based Attenuation Correction