MR-Based Attenuation Correction Using Ultrashort-Echo-Time Pulse Sequences in Dementia Patients

Abstract

Attenuation correction (AC) is a critical requirement for quantitative PET reconstruction. Accounting for bone information in the attenuation map (μ map) is of paramount importance for accurate brain PET quantification. However, to measure the signal from bone structures represents a challenging task in MR. Recent 18 F-FDG PET/MR studies showed quantitative bias for the assessment of radiotracer concentration when bone was ignored. This work is focused on 18 F-FDG PET/MR neurodegenerative dementing disorders. These are known to lead to specific patterns of 18 F-FDG hypometabolism, mainly in superficial brain structures, which might suffer from attenuation artifacts and thus have immediate diagnostic consequences. A fully automatic method to estimate the μ map, including bone tissue using only MR information, is presented. Methods: The algorithm was based on a dual-echo ultrashort-echo-time MR imaging sequence to calculate the R 2 map, from which the μ map was derived. The R 2 -based μ map was postprocessed to calculate an estimated distribution of the bone tissue. μ maps calculated from datasets of 9 patients were compared with their CT-based μ maps (μ map CT ) by determining the confusion matrix. Additionally, a regionof-interest comparison between reconstructed PET data, corrected using different μ maps, was performed. PET data were reconstructed using a Dixon-based μ map (μ map DX ) and a dual-echo ultrashort-echotime-based μ map (μ map UTE ), which are both calculated by the scanner, and the R 2 -based μ map presented in this work was compared with reconstructed PET data using the μ map CT as a reference. Results: Errors were approximately 20% higher using the μ map DX and μ map UTE for AC, compared with reconstructed PET data using the reference μ map CT . However, PET AC using the R 2 -based μ map resulted, for all the patients and all the analyzed regions of interest, in a significant improvement, reducing the error to −5.8% to 2.5%. Conclusion: The proposed method successfully showed significantly reduced errors in quantification, compared with the μ map DX and μ map UTE , and therefore delivered more accurate PET image quantification for an improved diagnostic workup in dementia patients. Thecur rent aging population is leading to an increased attention to dementing disorders and their most common cause, neurodegenerative Alzheimer disease. One of the earliest features seen on PET neuroimaging that these neuropsychiatric disorders show is reduced brain glucose metabolism in specific regions in neocortical brain areas. In addition to established biomarkers representing neuronal dysfunction such as 18 F-FDG, newer protein aggregation PET biomarkers for in vivo amyloid imaging in the brain have been developed and were recently included into the guidelines of the National Institute on Aging and the Alzheimer Association (1,2). For all of these PET techniques, a highly accurate and robust tracer quantification is required for the early diagnosis and accurate monitoring of therapeutics such as amyloid-modifyi...

Hybrid Imaging: Instrumentation and Data Processing

“…The creation of such parametric images can be divided into [208], (E) Anazodo et al [209], (F) Izquierdo-Garcia et al [210], (G) Burgos et al [211], (H) Merida et al [212]; MLAA-based methods: (I) Benoit et al [213]; Segmentation-based methods: (J) Cabello et al [214], (K) Juttukonda et al [215], (L) Ladefoged et al [216]. Graphical analyses methods include the Gjedde-Patlak equation [251,252], which describes irreversibly bound tracers, such as [ 18 F]FDG and the Logan-plot, which can be used to describe the reversibly bound tracers [253].…”

Clinical Evaluation of Zero-Echo-Time Attenuation Correction for Brain 18F-FDG PET/MRI: Comparison with Atlas Attenuation Correction

“…Even if the classification of the bone/ soft-tissue component is completely precise, the PET bias is within 610% in one study and is 4.0% 6 3.7% in the other study (11,31). Also, several studies revealed that adding the continuous bone attenuation value calculated from T2 relaxation time using dual UTE sequences contributes to improve AC (9,10,31).…”

“…The first family is that of template-/atlas-/model-based approaches (5)(6)(7). The second one is that of segmentation approaches (8)(9)(10)(11)(12). The third one constitutes methods directly estimating attenuation information from emission data (13,14).…”

MRI-Based Attenuation Correction for PET/MRI Using Multiphase Level-Set Method

“…Thus, the most widely used clinical PET/MRI system (Biograph mMR; Siemens Healthcare) offers the UTE-based MR-AC along with the Dixon-based method for brain PET/MRI studies. However, the initial versions of the UTE sequence (i.e., mMR software version VB18P) yielded frequent segmentation errors at the boundary between soft tissue, bone, and air, and misclassification of the ventricle as air (33)(34)(35). Although a recent upgrade of the software from VB18P to VB20P offers more reliable attenuation maps than before, significant segmentation errors in the regions around the inferior part of the brain (i.e., sinus and lower skull structures) still exist.…”

“…Although a recent upgrade of the software from VB18P to VB20P offers more reliable attenuation maps than before, significant segmentation errors in the regions around the inferior part of the brain (i.e., sinus and lower skull structures) still exist. Moreover, considerable quantification errors because of the inaccurate UTE MR-AC have been reported in several articles (33)(34)(35).…”