Detection of bone metastasis in nasopharyngeal carcinoma by bone scintigraphy: A retrospective study in perspective of limited resource settings

2015 ◽  
Vol 4 (1) ◽  
pp. 17
Author(s):  
Akhil Kapoor ◽  
Ashok Kalwar ◽  
Narender Kumar ◽  
Sitaram Maharia ◽  
RajKumar Nirban ◽  
...  
2014 ◽  
Vol 28 (5) ◽  
pp. 411-416 ◽  
Author(s):  
Zhongyi Yang ◽  
Yongping Zhang ◽  
Wei Shi ◽  
Beiling Zhu ◽  
Silong Hu ◽  
...  

Diagnostics ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 518
Author(s):  
Da-Chuan Cheng ◽  
Te-Chun Hsieh ◽  
Kuo-Yang Yen ◽  
Chia-Hung Kao

This study aimed to explore efficient ways to diagnose bone metastasis early using bone scintigraphy images through negative mining, pre-training, the convolutional neural network, and deep learning. We studied 205 prostate cancer patients and 371 breast cancer patients and used bone scintigraphy data from breast cancer patients to pre-train a YOLO v4 with a false-positive reduction strategy. With the pre-trained model, transferred learning was applied to prostate cancer patients to build a model to detect and identify metastasis locations using bone scintigraphy. Ten-fold cross validation was conducted. The mean sensitivity and precision rates for bone metastasis location detection and classification (lesion-based) in the chests of prostate patients were 0.72 ± 0.04 and 0.90 ± 0.04, respectively. The mean sensitivity and specificity rates for bone metastasis classification (patient-based) in the chests of prostate patients were 0.94 ± 0.09 and 0.92 ± 0.09, respectively. The developed system has the potential to provide pre-diagnostic reports to aid in physicians’ final decisions.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Furaha Nzanzu Blaise Pascal ◽  
Agnes Malisawa ◽  
Andreas Barratt-Due ◽  
Felix Namboya ◽  
Gregor Pollach

An amendment to this paper has been published and can be accessed via the original article.


2010 ◽  
Vol 67 (6) ◽  
pp. 453-458 ◽  
Author(s):  
Silvija Lucic ◽  
Katarina Nikoletic ◽  
Andrea Peter ◽  
Milos Lucic ◽  
Dusan Jovanovic

Background/Aim. Bone scintigraphy is well-known method for the detection of neoplastic lesions with a high sensitivity and, at the same time, a lower specificity. On the other hand magnetic resonance imaging (MRI) is previously established noninvasive imaging method regarding its diagnostic specificity. The aim of this study was to determine the possibilities and to correlate two different diagnostic methods - bone scintigraphy and MRI in the detection of bone metastasis in the spine and pelvic bones. Methods. A total of 123 patients who underwent both bone scintigraphy and spine and pelvic MRI on 1.5 T MR imager were enrolled in this study. Scans were subsequently analyzed in total and divided in regions of interest (cervical, upper, middle and lower thoracic, upper and lower lumbar and pelvic region, which includes sacral spinal segment); afterwards the total number of 585 matching regions were compared and statistically analyzed. Results. The statistical analysis demonstrated significant correlation between the findings of both methods in total. Divided by regions of interest, significant degrees of correlation were demonstrated in all of them, except in the cervical spine region where the r-value was in the range of low correlation. Conclusion. Having a high mutual correlation, bone scintigraphy and MRI are to be considered as the complementary diagnostic methods in the detection of bone metastases. Still, increased diagnostic potential of MRI may highlights negative bone scintigraphy findings in the patients with solitary metastatic lesions or diffuse vertebral infiltration. Advances in the bone scintigraphy (single photon emission tomography - SPECT, SPECTcomputed tomography - SPECT-CT) and MRI (whole body MRI, diffusion MRI), make it possible the diagnostic potential of both methods will result in a further improvement in bone metastasis detection.


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