Bone SPECT/CT in Oncology

2021 ◽  
pp. 133-163
Author(s):  
Kanhaiyalal Agrawal ◽  
Gopinath Gnanasegaran
Keyword(s):  
Bone Spect

Assessment of loading history of compartments in the knee using bone SPECT/CT: A study combining alignment and 99mTc-HDP tracer uptake/distribution patterns

2012 ◽  
Vol 31 (2) ◽  
pp. 268-274 ◽  
Author(s):  
Michael T. Hirschmann ◽  
Stephan Schön ◽  
Faik K. Afifi ◽  
Felix Amsler ◽  
Helmut Rasch ◽  
...  
Keyword(s):  
Distribution Patterns ◽  
Tracer Uptake ◽  
Loading History ◽  
History Of ◽  
Bone Spect

scholarly journals Phantom and clinical evaluation of bone SPECT/CT image reconstruction with xSPECT algorithm

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Noriaki Miyaji ◽  
Kenta Miwa ◽  
Ayaka Tokiwa ◽  
Hajime Ichikawa ◽  
Takashi Terauchi ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Clinical Evaluation ◽  
Ct Image ◽  
Bone Spect ◽  
Ct Image Reconstruction

Bone SPECT/CT of the Spine, Foot, and Ankle: Evaluation of Surgical Patients

2017 ◽  
Vol 47 (6) ◽  
pp. 639-646 ◽  
Author(s):  
Leah E. Waldman ◽  
Stephen C. Scharf
Keyword(s):  
Surgical Patients ◽  
Foot And Ankle ◽  
Bone Spect

scholarly journals Assessment of in vivo loading history of the patellofemoral joint: a study combining patellar position, tilt, alignment and bone SPECT/CT

2013 ◽  
Vol 22 (12) ◽  
pp. 3039-3046 ◽  
Author(s):  
Stephan N. Schön ◽  
Faik K. Afifi ◽  
Helmut Rasch ◽  
Felix Amsler ◽  
Niklaus F. Friederich ◽  
...  
Keyword(s):  
Patellofemoral Joint ◽  
Loading History ◽  
Patellar Position ◽  
History Of ◽  
Bone Spect ◽  
In Vivo Loading

scholarly journals Satisfied quantitative value can be acquired by short-time bone SPECT/CT using a whole-body cadmium–zinc–telluride gamma camera

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tomohiko Yamane ◽  
Masafumi Takahashi ◽  
Yohji Matsusaka ◽  
Kenji Fukushima ◽  
Akira Seto ◽  
...  
Keyword(s):  
Cadmium Zinc Telluride ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Zinc Telluride ◽  
Whole Body ◽  
Metastatic Lesions ◽  
Standardized Uptake Values ◽  
Bone Spect ◽  
Short Time ◽  
Cadmium Zinc

AbstractThe aim of this study was to evaluate the quantitative values of short-time scan (STS) of metastatic lesions compared with a standard scan (SS) when acquired by whole-body bone SPECT/CT with cadmium–zinc–telluride (CZT) detectors. We retrospectively reviewed 13 patients with bone metastases from prostate cancer, who underwent SPECT/CT performed on whole-body CZT gamma cameras. STSs were obtained using 75, 50, 25, 10, and 5% of the list-mode data for SS, respectively. Regions of interest (ROIs) were set on the increased uptake areas diagnosed as metastases. Intraclass correlation coefficients (ICCs) of standardized uptake values (SUVs) for the ROIs were calculated between the SS and each STS, and ICC ≥ 0.8 was set as a perfect correlation. Moreover, the repeatability coefficient (RC) was calculated, and RC ≤ 20% was defined as acceptable. A total of 152 metastatic lesions were included in the analysis. The ICCs between the SS vs. 75%-STS, 50%-STS, 25%-STS, 10%-STS, and 5%-STS were 0.999, 0.997, 0.994, 0.983, and 0.955, respectively. The RCs of the SS vs. 75%-STS, 50%-STS, 25%-STS, 10%-STS, and 5%-STS were 7.9, 12.4, 19.8, 30.8, and 41.3%, respectively. When evaluating the quality of CZT bone SPECT/CT acquired by a standard protocol, 25%-STS may provide adequate quantitative values.

scholarly journals Deep learning based automatic segmentation of metastasis hotspots in thorax bone SPECT images

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243253
Author(s):  
Qiang Lin ◽  
Mingyang Luo ◽  
Ruiting Gao ◽  
Tongtong Li ◽  
Zhengxing Man ◽  
...  
Keyword(s):  
Deep Learning ◽  
Fine Tuning ◽  
Disease Stage ◽  
Whole Body ◽  
Learning Technology ◽  
Automatic Assessment ◽  
Original Dataset ◽  
Bone Spect ◽  
Segmentation Models ◽  
Spect Images

SPECT imaging has been identified as an effective medical modality for diagnosis, treatment, evaluation and prevention of a range of serious diseases and medical conditions. Bone SPECT scan has the potential to provide more accurate assessment of disease stage and severity. Segmenting hotspot in bone SPECT images plays a crucial role to calculate metrics like tumor uptake and metabolic tumor burden. Deep learning techniques especially the convolutional neural networks have been widely exploited for reliable segmentation of hotspots or lesions, organs and tissues in the traditional structural medical images (i.e., CT and MRI) due to their ability of automatically learning the features from images in an optimal way. In order to segment hotspots in bone SPECT images for automatic assessment of metastasis, in this work, we develop several deep learning based segmentation models. Specifically, each original whole-body bone SPECT image is processed to extract the thorax area, followed by image mirror, translation and rotation operations, which augments the original dataset. We then build segmentation models based on two commonly-used famous deep networks including U-Net and Mask R-CNN by fine-tuning their structures. Experimental evaluation conducted on a group of real-world bone SEPCT images reveals that the built segmentation models are workable on identifying and segmenting hotspots of metastasis in bone SEPCT images, achieving a value of 0.9920, 0.7721, 0.6788 and 0.6103 for PA (accuracy), CPA (precision), Rec (recall) and IoU, respectively. Finally, we conclude that the deep learning technology have the huge potential to identify and segment hotspots in bone SPECT images.

scholarly journals Prevalence and prognostic value of increased uptake in bone SPECT/CT in asymptomatic wrists

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Maresa Allgayer ◽  
Urs Hug ◽  
Justus Egidius Roos ◽  
Maria del Sol Pérez Lago ◽  
Damian Wild ◽  
...  
Keyword(s):  
Prognostic Value ◽  
Bone Spect

scholarly journals Local validation of the use of Evolution for Bone for bone SPECT imaging

2015 ◽  
Vol 36 (9) ◽  
pp. 941-944
Author(s):  
Ceri E. Ashton ◽  
Susan C. Doyle ◽  
Stewart Redman ◽  
Richard Graham ◽  
Gordon J. Taylor ◽  
...  
Keyword(s):  
Spect Imaging ◽  
Bone Spect

Efficacy of Bone SPECT for Diagnosis of Meniscal tear

2001 ◽  
Vol 36 (6) ◽  
pp. 575
Author(s):  
Young Joon Choi ◽  
Key Yong Kim ◽  
Seung Ki Baek ◽  
Chung Hwan Kim ◽  
Eugene Kim ◽  
...  
Keyword(s):  
Meniscal Tear ◽  
Bone Spect
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