All of the proposed novel methods have an average global performance within likely acceptable limits (±5% of CT-based reference), and the main difference among the methods was found in the robustness, outlier analysis, and clinical feasibility. Overall, the best performing methods were MR-ACBOSTON, MR-ACMAXPROB, MR-ACRESOLUTE and MR-ACUCL, ordered alphabetically. These methods all minimized the number of outliers, standard deviation, and average global and local error. The methods MR-ACMUNICH and MR-ACCAR-RiDR were both within acceptable quantitative limits, so these methods should be considered if processing time is a factor. The method MR-ACSEGBONE also demonstrates promising results, and performs well within the likely acceptable quantitative limits. For clinical routine scans where processing time can be a key factor, this vendor-provided solution currently outperforms most methods. With the performance of the methods presented here, it may be concluded that the challenge of improving the accuracy of MR-AC in adult brains with normal anatomy has been solved to a quantitatively acceptable degree, which is smaller than the quantification reproducibility in PET imaging.

MADPET4 is the first small animal PET insert with two layers of individually read out crystals in combination with silicon photomultiplier technology. It has a novel detector arrangement, in which all crystals face the center of field of view transaxially. In this work, the PET performance of MADPET4 was evaluated and compared to other preclinical PET scanners using the NEMA NU 4 measurements, followed by imaging a mouse-size hot-rod resolution phantom and two in vivo simultaneous PET/MRI scans in a 7 T MRI scanner. The insert had a peak sensitivity of 0.49%, using an energy threshold of 350 keV. A uniform transaxial resolution was obtained up to 15 mm radial offset from the axial center, using filtered back-projection with single-slice rebinning. The measured average radial and tangential resolutions (FWHM) were 1.38 mm and 1.39 mm, respectively. The 1.2 mm rods were separable in the hot-rod phantom using an iterative image reconstruction algorithm. The scatter fraction was 7.3% and peak noise equivalent count rate was 15.5 kcps at 65.1 MBq of activity. The FDG uptake in a mouse heart and brain were visible in the two in vivo simultaneous PET/MRI scans without applying image corrections. In conclusion, the insert demonstrated a good overall performance and can be used for small animal multi-modal research applications.

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...