ArticleMolecular imaging and biology2015
Clinical assessment of MR-guided 3-class and 4-class attenuation correction in PET/MR.
Article in Molecular imaging and biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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23 citing papers in PubMed, 62 citations in OpenAlex.
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- Respiratory motion-corrected quiescent period gating magnetic resonance attenuation correction (Q.MRAC) for enhancing quantitative accuracy in hepatic [18F]FDG PET/MRI: a dual-domain motion compensation study.Quantitative imaging in medicine and surgery · 2026Article
- Enhanced direct joint attenuation and scatter correction of whole-body PET images via context-aware deep networks.Zeitschrift fur medizinische Physik · 2025Article
- Optimizing MR-based attenuation correction in hybrid PET/MR using deep learning: validation with a flatbed insert and consistent patient positioning.European journal of nuclear medicine and molecular imaging · 2025Article
- Advancements in synthetic CT generation from MRI: A review of techniques, and trends in radiation therapy planning.Journal of applied clinical medical physics · 2024Review
- Artificial intelligence-based joint attenuation and scatter correction strategies for multi-tracer total-body PET.EJNMMI physics · 2024Article
- A review of PET attenuation correction methods for PET-MR.EJNMMI physics · 2023Review
- Detection of distant metastases and distant second primary cancers in head and neck squamous cell carcinoma: comparison of [Insights into imaging · 2022Article
- MRI-guided attenuation correction in torso PET/MRI: Assessment of segmentation-, atlas-, and deep learning-based approaches in the presence of outliers.Magnetic resonance in medicine · 2022Article
- The impact of MR-based attenuation correction in spinal cord FDG-PET/MR imaging for neurological studies.Medical physics · 2021Article
- A decade of multi-modality PET and MR imaging in abdominal oncology.The British journal of radiology · 2021Review
- Deep-JASC: joint attenuation and scatter correction in whole-bodyEuropean journal of nuclear medicine and molecular imaging · 2020Article
- Deep learning-guided joint attenuation and scatter correction in multitracer neuroimaging studies.Human brain mapping · 2020Article
- mDixon-Based Synthetic CT Generation for PET Attenuation Correction on Abdomen and Pelvis Jointly Using Transfer Fuzzy Clustering and Active Learning-Based Classification.IEEE transactions on medical imaging · 2020Article
- PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques.Medical physics · 2020Review
- Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI.European journal of nuclear medicine and molecular imaging · 2019Article
- Impact of Tissue Classification in MRI-Guided Attenuation Correction on Whole-Body Patlak PET/MRI.Molecular imaging and biology · 2019Article
- Validation of MR-Based Attenuation Correction of a Newly Released Whole-Body Simultaneous PET/MR System.BioMed research international · 2019Article
- Local recurrence of squamous cell carcinoma of the head and neck after radio(chemo)therapy: Diagnostic performance of FDG-PET/MRI with diffusion-weighted sequences.European radiology · 2018Article
- One registration multi-atlas-based pseudo-CT generation for attenuation correction in PET/MRI.European journal of nuclear medicine and molecular imaging · 2016Article
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Authors and funding
6 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeWe compare the quantitative accuracy of magnetic resonance imaging (MRI)-based attenuation correction (AC) using the 3-class attenuation map (PET-MRAC3c) implemented on the Ingenuity TF PET/MRI and the 4-class attenuation map (PET-MRAC4c) similar to the approach used on the Siemens mMR PET/MR considering CT-based attenuation-corrected PET images (PET-CTAC) as standard of reference. PROCEDURES: Fourteen patients with malignant tumors underwent whole-body sequential 2-deoxy-2-[(18)F]fluoro-D-glucose ((18)F-FDG) positron emission tomography (PET)/X-ray computed tomography (CT) and PET/MR imaging. A 3-class attenuation map was obtained from segmentation of T1-weighted MR images followed by assignment of attenuation coefficients (air 0 cm(-1), lung 0.022 cm(-1), soft tissue 0.096 cm(-1)), whereas a 4-class attenuation map was derived from a MR Dixon sequence (air 0 cm(-1), lung 0.018 cm(-1), fat 0.086 cm(-1), soft tissue 0.096 cm(-1)). Additional adipose tissue class and inner body air cavities (e.g., sinus and abdomen) were also considered. Different attenuation coefficients were assigned to the lungs since the two techniques were implemented as they were proposed without any modification. Standardized uptake value (SUV)mean and SUVmax metrics were calculated for volumes of interest in various organs/tissues and malignant lesions. Well-established metrics were used for the analysis of SUVs estimated using both PET-MRAC techniques and PET-CTAC including relative error, Spearman rank correlation, and Bland and Altman analysis.
resultsPET-MRAC3c and PET-MRAC4c revealed significant underestimation of SUV for normal organs (-17.4 ± 8.5 and -22.0 ± 6.8%, respectively) compared to PET-CTAC. Lesions' SUV presented the same trend with larger underestimation for PET-MRAC4c (-9.2 ± 6.1%) compared to PET-MRAC3c (-3.9 ± 9.0). The different attenuation coefficients assigned to the lungs with both techniques resulted in significant positive bias on PET-MRAC3c (18.6 ± 15.3%) and low negative bias on PET-MRAC4c (-0.5 ± 13.3%). Both approaches yielded the largest differences in and near bony structures. Despite the large bias, there was good correlation between PET-MRAC3c (R = 0.97, P < 0.01) and PET-CTAC, and PET-MRAC4c (R = 0.97, P < 0.01) and PET-CTAC, respectively.
conclusionsPET-MRAC3c resulted in significant systematic positive bias in the lungs owing to the lower attenuation coefficient used and negative bias in other regions. PET-MRAC4c slightly underestimated tracer uptake in the lungs and led to even larger negative bias than PET-MRAC3c in other body regions. The presence of artifacts in the MRAC might lead to misinterpretation of clinical studies. As such, the attenuation map needs to be checked for artifacts as part of the reading procedure to avoid misinterpretation of SUV measurements.
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