Bone Metastases.

ABSTRACT: Bone metastases occur frequently in common malignancies such as breast and prostate cancer. They are responsible for considerable morbidity and skeletal-related events. Fortunately, there are now several systemic, focal, and targeted therapies that can improve quality and length of life, including radionuclide therapies. It is therefore important that bone metastases can be detected as early as possible and that treatment can be accurately and sensitively monitored. Several bone-specific and tumor-specific single-photon emission computed tomography and positron emission tomography molecular imaging agents are available, for detection and monitoring response to systemic therapeutics, as well as theranostic agents to confirm target expression and predict response to radionuclide therapies.

Theranostics and artificial intelligence: new frontiers in personalized medicine.

The field of theranostics is rapidly advancing, driven by the goals of enhancing patient care. Recent breakthroughs in artificial intelligence (AI) and its innovative theranostic applications have marked a critical step forward in nuclear medicine, leading to a significant paradigm shift in precision oncology. For instance, AI-assisted tumor characterization, including automated image interpretation, tumor segmentation, feature identification, and prediction of high-risk lesions, improves diagnostic processes, offering a precise and detailed evaluation. With a comprehensive assessment tailored to an individual's unique clinical profile, AI algorithms promise to enhance patient risk classification, thereby benefiting the alignment of patient needs with the most appropriate treatment plans. By uncovering potential factors unseeable to the human eye, such as intrinsic variations in tumor radiosensitivity or molecular profile, AI software has the potential to revolutionize the prediction of response heterogeneity. For accurate and efficient dosimetry calculations, AI technology offers significant advantages by providing customized phantoms and streamlining complex mathematical algorithms, making personalized dosimetry feasible and accessible in busy clinical settings. AI tools have the potential to be leveraged to predict and mitigate treatment-related adverse events, allowing early interventions. Additionally, generative AI can be utilized to find new targets for developing novel radiopharmaceuticals and facilitate drug discovery. However, while there is immense potential and notable interest in the role of AI in theranostics, these technologies do not lack limitations and challenges. There remains still much to be explored and understood. In this study, we investigate the current applications of AI in theranostics and seek to broaden the horizons for future research and innovation.

Performance of ChatGPT-4 and Bard chatbots in responding to common patient questions on prostate cancer 177Lu-PSMA-617 therapy.

Background: Many patients use artificial intelligence (AI) chatbots as a rapid source of health information. This raises important questions about the reliability and effectiveness of AI chatbots in delivering accurate and understandable information. Purpose: To evaluate and compare the accuracy, conciseness, and readability of responses from OpenAI ChatGPT-4 and Google Bard to patient inquiries concerning the novel 177Lu-PSMA-617 therapy for prostate cancer. Materials and methods: Two experts listed the 12 most commonly asked questions by patients on 177Lu-PSMA-617 therapy. These twelve questions were prompted to OpenAI ChatGPT-4 and Google Bard. AI-generated responses were distributed using an online survey platform (Qualtrics) and blindly rated by eight experts. The performances of the AI chatbots were evaluated and compared across three domains: accuracy, conciseness, and readability. Additionally, potential safety concerns associated with AI-generated answers were also examined. The Mann-Whitney U and chi-square tests were utilized to compare the performances of AI chatbots. Results: Eight experts participated in the survey, evaluating 12 AI-generated responses across the three domains of accuracy, conciseness, and readability, resulting in 96 assessments (12 responses x 8 experts) for each domain per chatbot. ChatGPT-4 provided more accurate answers than Bard (2.95 ± 0.671 vs 2.73 ± 0.732, p=0.027). Bard's responses had better readability than ChatGPT-4 (2.79 ± 0.408 vs 2.94 ± 0.243, p=0.003). Both ChatGPT-4 and Bard achieved comparable conciseness scores (3.14 ± 0.659 vs 3.11 ± 0.679, p=0.798). Experts categorized the AI-generated responses as incorrect or partially correct at a rate of 16.6% for ChatGPT-4 and 29.1% for Bard. Bard's answers contained significantly more misleading information than those of ChatGPT-4 (p = 0.039). Conclusion: AI chatbots have gained significant attention, and their performance is continuously improving. Nonetheless, these technologies still need further improvements to be considered reliable and credible sources for patients seeking medical information on 177Lu-PSMA-617 therapy.

Salivary toxicity from PSMA-targeted radiopharmaceuticals: What we have learned and where we are going.

Clinical trials of prostate-specific membrane antigen (PSMA) targeted radiopharmaceuticals have shown encouraging results. Some agents, like lutetium-177 [177Lu]Lu-PSMA-617 ([177Lu]Lu-PSMA-617), are already approved for late line treatment of metastatic castration-resistant prostate cancer (mCRPC). Projections are for continued growth of this treatment modality; [177Lu]Lu-PSMA-617 is being studied both in earlier stages of disease and in combination with other anti-cancer therapies. Further, the drug development pipeline is deep with variations of PSMA-targeting radionuclides, including higher energy alpha particles conjugated to PSMA-honing vectors. It is safe to assume that an increasing number of patients will be exposed to PSMA-targeted radiopharmaceuticals during the course of their cancer treatment. In this setting, it is important to better understand and mitigate the most commonly encountered toxicities. One particularly vexing side effect is xerostomia. In this review, we discuss the scope of the problem, inventories to better characterize and monitor this troublesome side effect, and approaches to preserve salivary function and effectively palliate symptoms. This article aims to serve as a useful reference for prescribers of PSMA-targeted radiopharmaceuticals, while also commenting on areas of missing data and opportunities for future research.