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.

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.

Background: The impact of certain comorbidities on mechanical thrombectomy (MT) outcomes remains largely unexplored. Diabetes mellitus (DM) and admission hyperglycemia have been associated with poor clinical outcomes for patients treated with MT. In this study, we sought to investigate the effects of DM and admission hyperglycemia on MT outcomes. Methods: Following PRISMA guidelines, a systematic literature search was conducted in Medline, Embase, Scopus, and Web of Science databases. Data regarding successful recanalization (modified Thrombolysis in Cerebral Infarction [mTICI] ≥2b), functional independence (modified Rankin Scale [mRS] 0–2), excellent outcomes (mRS 0–1), symptomatic intracranial hemorrhage (sICH), and mortality were extracted from the included studies. The pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were calculated using random effects model. Results: Twenty-one studies comprising 9708 patients were included. A total of 2311 patients (24%) had a history of DM, and 2026 patients (21%) had admission hyperglycemia. Admission hyperglycemia was associated with significantly lower odds of mTICI ≥2b (OR = 0.7, 95% CI = 0.55–0.89), mRS 0–2 (OR = 0.47, 95% CI = 0.41–0.53), and mRS 0–1 (OR = 0.43, 95% CI = 0.34–0.55) as compared to normoglycemic state. Patients with hyperglycemia had significantly higher rates of sICH (OR = 2.05, 95% CI = 1.66–2.54) and mortality (OR = 1.99, 95% CI = 1.58–2.52) than normoglycemic patients. Diabetes mellitus was associated with significantly high rates of mortality (OR = 1.74, 95% CI = 1.31–2.3) and lower rates of mRS 0–2 (OR = 0.60, 95% CI = 0.48–0.76) in sensitivity analyses. Conclusion: Our results indicate that admission blood glucose levels and DM can negatively affect MT outcomes. Further research should focus on optimizing MT outcomes for these patients.

Treatment with ¹⁷⁷Lu-prostate-specific membrane antigen (PSMA)–617 (¹⁷⁷Lu-vipivotide tetraxetan [Pluvicto]) prolongs both progression-free and overall survival in advanced PSMA-positive metastatic castration-resistant prostate cancer. Data examining specifically neurologic symptoms after ¹⁷⁷Lu-PSMA-617 treatment are scarce. In this study, we aimed to review the neurologic findings in a large cohort of metastatic castration-resistant prostate cancer patients undergoing ¹⁷⁷Lu-PSMA-617 therapy. Methods: The clinical records and imaging data of patients who received their initial dose of ¹⁷⁷Lu-PSMA-617 between March 2022 and November 2022 were retrospectively reviewed. All patients presenting for medical evaluation, regardless of specific specialty appointments, with new or worsening neurologic symptoms were included in the study. Results: A total of 185 patients underwent ¹⁷⁷Lu-PSMA-617 therapy. The median age was 70 y (range, 58–90 y). The mean follow-up time was 12.04 ± 2.87 mo. Fifty-five new or worsening neurologic symptoms were observed in 50 patients (27%, 50/185). Of these, 27 (11.9%, 27/185) reported altered taste. Eleven patients (6%, 11/185) experienced dizziness with no other clear etiology; 2 of these patients were admitted to the emergency department (ED). Paresthesia symptoms were reported in 6 patients (3.2%, 6/185). Five patients (2.7%, 5/185) reported headaches, 3 of these patients were admitted to the ED because of the severity of the symptoms. Two patients (1.08%, 2/185) presented with extremity weakness. Two patients (1.08%, 2/185) had an ischemic stroke and were admitted to the ED. One patient (0.05%, 1/185) exhibited gait disturbances. In total, 7 patients (3.78%, 7/185) were admitted to the ED because of neurologic symptoms. None of the patients discontinued or failed to complete the ¹⁷⁷Lu-PSMA-617 therapy because of neurologic symptoms. Conclusion: After ¹⁷⁷Lu-PSMA-617 treatment, the most common neurologic symptoms were dysgeusia and dizziness. In this study, our follow-up period and population size might not have been sufficient to detect delayed or uncommon neurologic symptoms. In patients without neurologic symptoms or central nervous system metastases before treatment, we found the development of severe neurologic problems to be rare and unlikely to require discontinuation of treatment. Visual Abstract