Osteo-NeT: An Automated System for Predicting Knee Osteoarthritis from X-ray Images Using Transfer-Learning-Based Neural Networks Approach.

Knee osteoarthritis is a challenging problem affecting many adults around the world. There are currently no medications that cure knee osteoarthritis. The only way to control the progression of knee osteoarthritis is early detection. Currently, X-ray imaging is a central technique used for the prediction of osteoarthritis. However, the manual X-ray technique is prone to errors due to the lack of expertise of radiologists. Recent studies have described the use of automated systems based on machine learning for the effective prediction of osteoarthritis from X-ray images. However, most of these techniques still need to achieve higher predictive accuracy to detect osteoarthritis at an early stage. This paper suggests a method with higher predictive accuracy that can be employed in the real world for the early detection of knee osteoarthritis. In this paper, we suggest the use of transfer learning models based on sequential convolutional neural networks (CNNs), Visual Geometry Group 16 (VGG-16), and Residual Neural Network 50 (ResNet-50) for the early detection of osteoarthritis from knee X-ray images. In our analysis, we found that all the suggested models achieved a higher level of predictive accuracy, greater than 90%, in detecting osteoarthritis. However, the best-performing model was the pretrained VGG-16 model, which achieved a training accuracy of 99% and a testing accuracy of 92%.

Differential responses to 223Ra and Alpha-particles exposure in prostate cancer driven by mitotic catastrophe.

Introduction: Radium-223 (223Ra) has been shown to have an overall survival benefit in metastatic castration-resistant prostate cancer (mCRPC) involving bone. Despite its increased clinical usage, relatively little is known regarding the mechanism of action of 223Ra at the cellular level. Methods: We evaluated the effects of 223Ra irradiation in a panel of cell lines and then compared them with standard X-ray and external alpha-particle irradiation, with a particular focus on cell survival and DNA damage repair kinetics. Results: 223Ra exposures had very high, cell-type-dependent RBE50% ranging from 7 to 15. This was significantly greater than external alpha irradiations (RBE50% from 1.4 to 2.1). These differences were shown to be partially related to the volume of 223Ra solution added, independent of the alpha-particle dose rate, suggesting a radiation-independent mechanism of effect. Both external alpha particles and 223Ra exposure were associated with delayed DNA repair, with similar kinetics. Additionally, the greater treatment efficacy of 223Ra was associated with increased levels of residual DNA damage and cell death by mitotic catastrophe. Conclusions: These results suggest that 223Ra exposure may be associated with greater biological effects than would be expected by direct comparison with a similar dose of external alpha particles, highlighting important challenges for future therapeutic optimization.

Abiraterone In Vitro Is Superior to Enzalutamide in Response to Ionizing Radiation.

Abiraterone acetate and Enzalutamide are novel anti-androgens that are key treatments to improve both progression-free survival and overall survival in patients with metastatic castration-resistant prostate cancer. In this study, we aimed to determine whether combinations of AR inhibitors with radiation are additive or synergistic, and investigated the underlying mechanisms governing this. This study also aimed to compare and investigate a biological rationale for the selection of Abiraterone versus Enzalutamide in combination with radiotherapy as currently selection is based on consideration of side effect profiles and clinical experience. We report that AR suppression with Enzalutamide produces a synergistic effect only in AR-sensitive prostate models. In contrast, Abiraterone displays synergistic effects in combination with radiation regardless of AR status, alluding to potential alternative mechanisms of action. The underlying mechanisms governing this AR-based synergy are based on the reduction of key AR linked DNA repair pathways such as NHEJ and HR, with changes in HR potentially the result of changes in cell cycle distribution, with these reductions ultimately resulting in increased cell death. These changes were also shown to be conserved in combination with radiation, with AR suppression 24 hours before radiation leading to the most significant differences. Comparison between Abiraterone and Enzalutamide highlighted Abiraterone from a mechanistic standpoint as being superior to Abiraterone for all endpoints measured. Therefore, this provides a potential rationale for the selection of Abiraterone over Enzalutamide.

A novel tool for improving the interpretation of isotope bone scans in metastatic prostate cancer.

OBJECTIVES: The isotope bone scan (IBS) is the gold-standard imaging modality for detecting skeletal metastases as part of prostate cancer staging. However, its clinical utility for assessing skeletal metastatic burden is limited due to the need for subjective interpretation. We designed and tested a novel custom software tool, the Metastatic Bone Scan Tool (MetsBST), aimed at improving interpretation of IBSs, and compared its performance with that of an established software programme. METHODS: We used IBS images from 62 patients diagnosed with prostate cancer and suspected bone metastases to design and implement MetsBST in MATLAB by defining thresholds used to identify the texture and size of metastatic bone lesions. The results of MetsBST were compared with those of the commercially available automated Bone Scan Index (aBSI) with regression analysis. RESULTS: There was strong agreement between the MetsBST and aBSI results (R2 = 0.9189). In a subregional analysis, MetsBST quantified the extent of metastatic disease in multiple bone sites in patients receiving multimodality therapy (radium-223 and external beam radiotherapy) to illustrate the differences in bone metastatic response to different treatments. CONCLUSION: The results of MetsBST and the commercial software aBSI were highly consistent. MetsBST introduces novel clinical utility by its ability to differentiate between the responses of different bone metastases to multimodality therapies. ADVANCES IN KNOWLEDGE: MetsBST reduces the variability in assessment of tumour burden caused by subjective interpretation. Therefore, it is a useful aid to physicians reporting nuclear medicine scans, and may improve decision-making in the treatment of metastatic prostate cancer.