scholarly journals Bone Metastasis Detection in the Chest and Pelvis from a Whole-Body Bone Scan Using Deep Learning and a Small Dataset

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1201
Author(s):  
Da-Chuan Cheng ◽  
Chia-Chuan Liu ◽  
Te-Chun Hsieh ◽  
Kuo-Yang Yen ◽  
Chia-Hung Kao
Keyword(s):  
Neural Network ◽  
Prostate Cancer ◽  
Bone Metastasis ◽  
Bone Scan ◽  
Diagnostic System ◽  
Whole Body ◽  
Satisfactory Performance ◽  
Body Bone ◽  
Early Diagnostic ◽  
Small Dataset

The aim of this study was to establish an early diagnostic system for the identification of the bone metastasis of prostate cancer in whole-body bone scan images by using a deep convolutional neural network (D-CNN). The developed system exhibited satisfactory performance for a small dataset containing 205 cases, 100 of which were of bone metastasis. The sensitivity and precision for bone metastasis detection and classification in the chest were 0.82 ± 0.08 and 0.70 ± 0.11, respectively. The sensitivity and specificity for bone metastasis classification in the pelvis were 0.87 ± 0.12 and 0.81 ± 0.11, respectively. We propose the use of hard example mining for increasing the sensitivity and precision of the chest D-CNN. The developed system has the potential to provide a prediagnostic report for physicians’ final decisions.

scholarly journals Accurate characterization of 99mTc-MDP uptake in extraosseous neoplasm mimicking bone metastasis on whole-body bone scan: contribution of SPECT/CT

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Linqi Zhang ◽  
Qiao He ◽  
Tao Zhou ◽  
Bing Zhang ◽  
Wei Li ◽  
...  
Keyword(s):  
Bone Metastasis ◽  
Bone Scan ◽  
Whole Body ◽  
Body Bone

scholarly journals A Lightweight Convolutional Neural Network Architecture Applied for Bone Metastasis Classification in Nuclear Medicine: A Case Study on Prostate Cancer Patients

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 493
Author(s):  
Charis Ntakolia ◽  
Dimitrios E. Diamantis ◽  
Nikolaos Papandrianos ◽  
Serafeim Moustakidis ◽  
Elpiniki I. Papageorgiou
Keyword(s):  
Neural Network ◽  
Prostate Cancer ◽  
Bone Metastasis ◽  
Convolutional Neural Network ◽  
Network Architecture ◽  
Cancer Metastasis ◽  
State Of The Art ◽  
Metastatic Cancer ◽  
Whole Body ◽  
Free Parameters

Bone metastasis is among the most frequent in diseases to patients suffering from metastatic cancer, such as breast or prostate cancer. A popular diagnostic method is bone scintigraphy where the whole body of the patient is scanned. However, hot spots that are presented in the scanned image can be misleading, making the accurate and reliable diagnosis of bone metastasis a challenge. Artificial intelligence can play a crucial role as a decision support tool to alleviate the burden of generating manual annotations on images and therefore prevent oversights by medical experts. So far, several state-of-the-art convolutional neural networks (CNN) have been employed to address bone metastasis diagnosis as a binary or multiclass classification problem achieving adequate accuracy (higher than 90%). However, due to their increased complexity (number of layers and free parameters), these networks are severely dependent on the number of available training images that are typically limited within the medical domain. Our study was dedicated to the use of a new deep learning architecture that overcomes the computational burden by using a convolutional neural network with a significantly lower number of floating-point operations (FLOPs) and free parameters. The proposed lightweight look-behind fully convolutional neural network was implemented and compared with several well-known powerful CNNs, such as ResNet50, VGG16, Inception V3, Xception, and MobileNet on an imaging dataset of moderate size (778 images from male subjects with prostate cancer). The results prove the superiority of the proposed methodology over the current state-of-the-art on identifying bone metastasis. The proposed methodology demonstrates a unique potential to revolutionize image-based diagnostics enabling new possibilities for enhanced cancer metastasis monitoring and treatment.

scholarly journals Evaluation of Tumor Viability for Primary and Bone Metastases in Metastatic Castration-Resistant Prostate Cancer Using Whole-Body Magnetic Resonance Imaging

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Hiromichi Iwamura ◽  
Yasuhiro Kaiho ◽  
Jun Ito ◽  
Go Anan ◽  
Nozomi Satani ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Prostate Cancer ◽  
Bone Metastasis ◽  
Needle Biopsy ◽  
Bone Scan ◽  
Whole Body ◽  
Castration Resistant Prostate Cancer ◽  
Resonance Imaging ◽  
Castration Resistant ◽  
Body Magnetic Resonance Imaging

In contrast to bone scan and computed tomography (CT), which depend on osteoblastic response to detect bone metastasis, whole-body magnetic resonance imaging (WB-MRI) may be able to directly detect viable tumors. A 75-year-old male who had progressive metastatic prostate cancer during primary androgen deprivation therapy was referred to our hospital. Although bone scan and CT showed multiple bone metastases, WB-MRI suggested nonviable bone metastasis and viable tumor of the primary lesion. Prostate needle biopsy demonstrated viable prostate cancer cells from 10 of 12 cores. In contrast, CT-guided needle biopsy from bone metastasis of the lumbar vertebra revealed no malignant cells. Based on these findings, we reasoned that viable tumor cells inducing disease progression may primarily exist in the primary lesions and not in the metastatic lesions, and combined prostate radiotherapy and systemic hormonal therapy resulted in successful clinical response and disease control. The use of WB-MRI to detect viable disease lesions may enable us to design optimal treatment strategies for patients with metastatic castration-resistant prostate cancer.

scholarly journals Comparison of Different Image Enhancement Methods for Effective Whole-Body Bone Scan Image

2019 ◽  
Vol 7 (3) ◽  
pp. 55
Author(s):  
Sulieman Mohammed Salih Zobly
Keyword(s):  
Image Enhancement ◽  
Bone Scan ◽  
Whole Body ◽  
Body Bone

scholarly journals Hyoid Bone Metastasis in Patients With Lung Adenocarcinoma: A Case Report

2020 ◽  
pp. 014556132091698
Author(s):  
Hong-Yang Zhang ◽  
Shan Shan Li ◽  
Xing Guo ◽  
Ning Zhao
Keyword(s):  
Bone Metastasis ◽  
Bone Mass ◽  
Lung Adenocarcinoma ◽  
Hyoid Bone ◽  
Metastatic Lesion ◽  
Whole Body ◽  
Initial Symptom ◽  
Pathologic Analysis ◽  
Full Consideration ◽  
Body Bone

Objective: Hyoid bone metastasis from lung adenocarcinoma is exceedingly rare. This study aims to provide an experience to clinicians in the differential diagnosis of hyoid tumors and discusses its possible source. Methods and Results: We report a 68-year-old male patient having hyoid bone metastasis from lung adenocarcinoma. The initial symptom of the hyoid bone metastasis was neck pain exacerbated by swallowing. The hyoid bone mass was resected based on comprehensive analysis including whole-body bone imaging and pathologic analysis of the hyoid bone mass. The adenocarcinoma of hyoid was identified as a metastatic lesion of lung adenocarcinoma. The patient recovered well and the anterior cervical pain was significantly alleviated after surgery and the patient underwent corresponding chemotherapy. Conclusion: In patients with hyoid metastasis of lung adenocarcinoma, surgical resection may reduce the pain in anterior cervical after full consideration of physical condition.

Comparison of 18F-Fluciclovine PET/CT and 99mTc-MDP bone scan in detection of bone metastasis in prostate cancer

2019 ◽  
Vol 40 (9) ◽  
pp. 940-946 ◽  
Author(s):  
Bo Chen ◽  
Peng Wei ◽  
Homer A. Macapinlac ◽  
Yang Lu
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Bone Scan ◽  
Pet Ct

scholarly journals Does whole-body bone SPECT/CT provide additional diagnostic information over [18F]-FCH PET/CT for the detection of bone metastases in the setting of prostate cancer biochemical recurrence?

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Nicolas de Leiris ◽  
Julien Leenhardt ◽  
Bastien Boussat ◽  
Christopher Montemagno ◽  
Alexandre Seiller ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastases ◽  
Biochemical Recurrence ◽  
Diagnostic Information ◽  
Whole Body ◽  
Additional Diagnostic Information ◽  
Pet Ct ◽  
Bone Spect ◽  
Body Bone

scholarly journals Total-Body 68Ga-PSMA-11 PET/CT for Bone Metastasis Detection in Prostate Cancer Patients: Potential Impact on Bone Scan Guidelines

2019 ◽  
Vol 61 (3) ◽  
pp. 405-411 ◽  
Author(s):  
Kelsey L. Pomykala ◽  
Johannes Czernin ◽  
Tristan R. Grogan ◽  
Wesley R. Armstrong ◽  
John Williams ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Cancer Patients ◽  
Bone Scan ◽  
Pet Ct ◽  
Potential Impact ◽  
Total Body
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