UNLABELLED: MR-based attenuation correction is instrumental for integrated PET/MR imaging. It is generally achieved by segmenting MR images into a set of tissue classes with known attenuation properties (e.g., air, lung, bone, fat, soft tissue). Bone identification with MR imaging is, however, quite challenging, because of the low proton density and fast decay time of bone tissue. The clinical evaluation of a novel, recently published method for zero-echo-time (ZTE)-based MR bone depiction and segmentation in the head is presented here. METHODS: A new paradigm for MR imaging bone segmentation, based on proton density-weighted ZTE imaging, was disclosed earlier in 2014. In this study, we reviewed the bone maps obtained with this method on 15 clinical datasets acquired with a PET/CT/MR trimodality setup. The CT scans acquired for PET attenuation-correction purposes were used as reference for the evaluation. Quantitative measurements based on the Jaccard distance between ZTE and CT bone masks and qualitative scoring of anatomic accuracy by an experienced radiologist and nuclear medicine physician were performed. RESULTS: The average Jaccard distance between ZTE and CT bone masks evaluated over the entire head was 52% ± 6% (range, 38%-63%). When only the cranium was considered, the distance was 39% ± 4% (range, 32%-49%). These results surpass previously reported attempts with dual-echo ultrashort echo time, for which the Jaccard distance was in the 47%-79% range (parietal and nasal regions, respectively). Anatomically, the calvaria is consistently well segmented, with frequent but isolated voxel misclassifications. Air cavity walls and bone/fluid interfaces with high anatomic detail, such as the inner ear, remain a challenge. CONCLUSION: This is the first, to our knowledge, clinical evaluation of skull bone identification based on a ZTE sequence. The results suggest that proton density-weighted ZTE imaging is an efficient means of obtaining high-resolution maps of bone tissue with sufficient anatomic accuracy for, for example, PET attenuation correction.
UNLABELLED: MR-based attenuation correction is instrumental for integrated PET/MR imaging. It is generally achieved by segmenting MR images into a set of tissue classes with known attenuation properties (e.g., air, lung, bone, fat, soft tissue). Bone identification with MR imaging is, however, quite challenging, because of the low proton density and fast decay time of bone tissue. The clinical evaluation of a novel, recently published method for zero-echo-time (ZTE)-based MR bone depiction and segmentation in the head is presented here. METHODS: A new paradigm for MR imaging bone segmentation, based on proton density-weighted ZTE imaging, was disclosed earlier in 2014. In this study, we reviewed the bone maps obtained with this method on 15 clinical datasets acquired with a PET/CT/MR trimodality setup. The CT scans acquired for PET attenuation-correction purposes were used as reference for the evaluation. Quantitative measurements based on the Jaccard distance between ZTE and CT bone masks and qualitative scoring of anatomic accuracy by an experienced radiologist and nuclear medicine physician were performed. RESULTS: The average Jaccard distance between ZTE and CT bone masks evaluated over the entire head was 52% ± 6% (range, 38%-63%). When only the cranium was considered, the distance was 39% ± 4% (range, 32%-49%). These results surpass previously reported attempts with dual-echo ultrashort echo time, for which the Jaccard distance was in the 47%-79% range (parietal and nasal regions, respectively). Anatomically, the calvaria is consistently well segmented, with frequent but isolated voxel misclassifications. Air cavity walls and bone/fluid interfaces with high anatomic detail, such as the inner ear, remain a challenge. CONCLUSION: This is the first, to our knowledge, clinical evaluation of skull bone identification based on a ZTE sequence. The results suggest that proton density-weighted ZTE imaging is an efficient means of obtaining high-resolution maps of bone tissue with sufficient anatomic accuracy for, for example, PET attenuation correction.
Authors: D L Bailey; B J Pichler; B Gückel; H Barthel; A J Beer; J Bremerich; J Czernin; A Drzezga; C Franzius; V Goh; M Hartenbach; H Iida; A Kjaer; C la Fougère; C N Ladefoged; I Law; K Nikolaou; H H Quick; O Sabri; J Schäfer; M Schäfers; H F Wehrl; T Beyer Journal: Mol Imaging Biol Date: 2015-10 Impact factor: 3.488
Authors: Pengjiang Qian; Yangyang Chen; Jung-Wen Kuo; Yu-Dong Zhang; Yizhang Jiang; Kaifa Zhao; Rose Al Helo; Harry Friel; Atallah Baydoun; Feifei Zhou; Jin Uk Heo; Norbert Avril; Karin Herrmann; Rodney Ellis; Bryan Traughber; Robert S Jones; Shitong Wang; Kuan-Hao Su; Raymond F Muzic Journal: IEEE Trans Med Imaging Date: 2019-08-16 Impact factor: 10.048
Authors: Edwin E G W Ter Voert; Patrick Veit-Haibach; Sangtae Ahn; Florian Wiesinger; M Mehdi Khalighi; Craig S Levin; Andrei H Iagaru; Greg Zaharchuk; Martin Huellner; Gaspar Delso Journal: Eur J Nucl Med Mol Imaging Date: 2017-01-26 Impact factor: 9.236
Authors: Kevin T Chen; David Izquierdo-Garcia; Clare B Poynton; Daniel B Chonde; Ciprian Catana Journal: Eur J Nucl Med Mol Imaging Date: 2016-08-29 Impact factor: 9.236