The use of advanced imaging in guiding the further investigation and treatment of primary prostate cancer

Identification and Localization of Indolent and Aggressive Prostate Cancers Using Multilevel Bi-LSTM

Identifying indolent and aggressive prostate cancers is a critical problem for optimal treatment. The existing approaches of prostate cancer detection are facing challenges as the techniques rely on ground truth labels with limited accuracy, and histological similarity, and do not consider the disease pathology characteristics, and indefinite differences in appearance between the cancerous and healthy tissue lead to many false positive and false negative interpretations. Hence, this research introduces a comprehensive framework designed to achieve accurate identification and localization of prostate cancers, irrespective of their aggressiveness. This is accomplished through the utilization of a sophisticated multilevel bidirectional long short-term memory (Bi-LSTM) model. The pre-processed images are subjected to multilevel feature map-based U-Net segmentation, bolstered by ResNet-101 and a channel-based attention module that improves the performance. Subsequently, segmented images undergo feature extraction, encompassing various feature types, including statistical features, a global hybrid-based feature map, and a ResNet-101 feature map that enhances the detection accuracy. The extracted features are fed to the multilevel Bi-LSTM model, further optimized through channel and spatial attention mechanisms that offer the effective localization and recognition of complex structures of cancer. Further, the framework represents a promising approach for enhancing the diagnosis and localization of prostate cancers, encompassing both indolent and aggressive cases. Rigorous testing on a distinct dataset demonstrates the model's effectiveness, with performance evaluated through key metrics which are reported as 96.72%, 96.17%, and 96.17% for accuracy, sensitivity, and specificity respectively utilizing the dataset 1. For dataset 2, the model achieves the accuracy, sensitivity, and specificity values of 94.41%, 93.10%, and 94.96% respectively. These results surpass the efficiency of alternative methods.

Bone Metastasis in Prostate Cancer: Bone Scan Versus PET Imaging

Prostate cancer is the second most common cause of malignancy among men, with bone metastasis being a significant source of morbidity and mortality in advanced cases. Detecting and treating bone metastasis at an early stage is crucial to improve the quality of life and survival of prostate cancer patients. This objective strongly relies on imaging studies. While CT and MRI have their specific utilities, they also possess certain drawbacks. Bone scintigraphy, although cost-effective and widely available, presents high false-positive rates. The emergence of PET/CT and PET/MRI, with their ability to overcome the limitations of standard imaging methods, offers promising alternatives for the detection of bone metastasis. Various radiotracers targeting cell division activity or cancer-specific membrane proteins, as well as bone seeking agents, have been developed and tested. The use of positron-emitting isotopes such as fluorine-18 and gallium-68 for labeling allows for a reduced radiation dose and unaffected biological properties. Furthermore, the integration of artificial intelligence (AI) and radiomics techniques in medical imaging has shown significant advancements in reducing interobserver variability, improving accuracy, and saving time. This article provides an overview of the advantages and limitations of bone scan using SPECT and SPECT/CT and PET imaging methods with different radiopharmaceuticals and highlights recent developments in hybrid scanners, AI, and radiomics for the identification of prostate cancer bone metastasis using molecular imaging.

New Iron Metabolic Pathways and Chelation Targeting Strategies Affecting the Treatment of All Types and Stages of Cancer

There is new and increasing evidence from in vitro, in vivo and clinical studies implicating the pivotal role of iron and associated metabolic pathways in the initiation, progression and development of cancer and in cancer metastasis. New metabolic and toxicity mechanisms and pathways, as well as genomic, transcription and other factors, have been linked to cancer and many are related to iron. Accordingly, a number of new targets for iron chelators have been identified and characterized in new anticancer strategies, in addition to the classical restriction of/reduction in iron supply, the inhibition of transferrin iron delivery, the inhibition of ribonucleotide reductase in DNA synthesis and high antioxidant potential. The new targets include the removal of excess iron from iron-laden macrophages, which affects anticancer activity; the modulation of ferroptosis; ferritin iron removal and the control of hyperferritinemia; the inhibition of hypoxia related to the role of hypoxia-inducible factor (HIF); modulation of the function of new molecular species such as STEAP4 metalloreductase and the metastasis suppressor N-MYC downstream-regulated gene-1 (NDRG1); modulation of the metabolic pathways of oxidative stress damage affecting mitochondrial function, etc. Many of these new, but also previously known associated iron metabolic pathways appear to affect all stages of cancer, as well as metastasis and drug resistance. Iron-chelating drugs and especially deferiprone (L1), has been shown in many recent studies to fulfill the role of multi-target anticancer drug linked to the above and also other iron targets, and has been proposed for phase II trials in cancer patients. In contrast, lipophilic chelators and their iron complexes are proposed for the induction of ferroptosis in some refractory or recurring tumors in drug resistance and metastasis where effective treatments are absent. There is a need to readdress cancer therapy and include therapeutic strategies targeting multifactorial processes, including the application of multi-targeting drugs involving iron chelators and iron-chelator complexes. New therapeutic protocols including drug combinations with L1 and other chelating drugs could increase anticancer activity, decrease drug resistance and metastasis, improve treatments, reduce toxicity and increase overall survival in cancer patients.