A finely segmented semi-monolithic detector tailored for high-resolution PET

被引:2
|
作者
Kuhl, Yannick [1 ]
Mueller, Florian [1 ]
Naunheim, Stephan [1 ]
Bovelett, Matthias [1 ]
Lambertus, Janko [1 ]
Schug, David [1 ,2 ]
Weissler, Bjoern [1 ,2 ]
Gegenmantel, Eike [2 ]
Gebhardt, Pierre [1 ]
Schulz, Volkmar [1 ,2 ,3 ]
机构
[1] Rhein Westfal TH Aachen, Inst Expt Mol Imaging, Dept Phys Mol Imaging Syst, Aachen, Germany
[2] Hyper Hybrid Imaging Syst GmbH, Aachen, Germany
[3] Rhein Westfal TH Aachen, Phys Inst B 3, Aachen, Germany
关键词
high-resolution Positron Emission Tomography (PET); machine learning GTB fan beam calibration; semi-monolith slab detector; DIGITAL-SILICON-PHOTOMULTIPLIER; SCINTILLATOR CRYSTALS; POSITIONING ALGORITHM; PET/MRI; SIPM;
D O I
10.1002/mp.16928
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
BackgroundPreclinical research and organ-dedicated applications use and require high (spatial-)resolution positron emission tomography (PET) detectors to visualize small structures (early) and understand biological processes at a finer level of detail. Researchers seeking to improve detector and image spatial resolution have explored various detector designs. Current commercial high-resolution systems often employ finely pixelated or monolithic scintillators, each with its limitations.PurposeWe present a semi-monolithic detector, tailored for high-resolution PET applications with a spatial resolution in the range of 1 mm or better, merging concepts of monolithic and pixelated crystals. The detector features LYSO slabs measuring (24 x 10 x 1) mm3, coupled to a 12 x 12 readout channel photosensor with 4 mm pitch. The slabs are grouped in two arrays of 44 slabs each to achieve a higher optical photon density despite the fine segmentation.MethodsWe employ a fan beam collimator for fast calibration to train machine-learning-based positioning models for all three dimensions, including slab identification and depth-of-interaction (DOI), utilizing gradient tree boosting (GTB). The data for all dimensions was acquired in less than 2 h. Energy calculation was based on a position-dependent energy calibration. Using an analytical timing calibration, time skews were corrected for coincidence timing resolution (CTR) estimation.ResultsLeveraging machine-learning-based calibration in all three dimensions, we achieved high detector spatial resolution: down to 1.18 mm full width at half maximum (FWHM) detector spatial resolution and 0.75 mm mean absolute error (MAE) in the planar-monolithic direction, and 2.14 mm FWHM and 1.03 mm MAE for DOI at an energy window of (435-585) keV. Correct slab interaction identification in planar-segmented direction exceeded 80%, alongside an energy resolution of 12.7% and a CTR of 450 ps FWHM.ConclusionsThe introduced finely segmented, high-resolution slab detector demonstrates appealing performance characteristics suitable for high-resolution PET applications. The current benchtop-based detector calibration routine allows these detectors to be used in PET systems.
引用
收藏
页码:3421 / 3436
页数:16
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