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Objective: The internet and social media have become primary sources of health information, with men frequently turning to these platforms before seeking professional help. Chat generative pretrained transformer (ChatGPT), an artificial intelligence model developed by OpenAI, has gained popularity as a natural language processing program. The present study evaluated the accuracy and reproducibility of ChatGPT's responses to andrology-related questions. Methods: The study analyzed frequently asked andrology questions from health forums, hospital websites, and social media platforms like YouTube and Instagram. Questions were categorized into topics like male hypogonadism, erectile dysfunction, etc. The European Association of Urology (EAU) guideline recommendations were also included. These questions were input into ChatGPT, and responses were evaluated by 3 experienced urologists who scored them on a scale of 1 to 4. Results: Out of 136 evaluated questions, 108 met the criteria. Of these, 87.9% received correct and adequate answers, 9.3% were correct but insufficient, and 3 responses contained both correct and incorrect information. No question was answered completely wrong. The highest correct answer rates were for disorders of ejaculation, penile curvature, and male hypogonadism. The EAU guideline-based questions achieved a correctness rate of 86.3%. The reproducibility of the answers was over 90%. Conclusion: The study found that ChatGPT provided accurate and reliable answers to over 80% of andrology-related questions. While limitations exist, such as potential outdated data and inability to understand emotional aspects, ChatGPT's potential in the health-care sector is promising. Collaborating with health-care professionals during artificial intelligence model development could enhance its reliability. [ABSTRACT FROM AUTHOR]

Objective: A newly developed GafchromicTM EBT4 film model was released recently. According to the vendor‐stated specifications, this new model maintains major features of its more recent predecessor, EBT3, but has a great improvement in the signal‐to‐noise ratio (SNR). The purpose of this study was to fully characterize the EBT4 model by testing its dose response dependence on beam energy using clinical photon and electron beams and validating its improvement in SNR. Methods: In the beam energy dependence experiments, 6 MV and 15 MV photon beams, 6 MeV, 12 MeV and 20 MeV electron beams, 120 kVp and two 250 kVp x‐ray beams (with different half‐layer values) were selected, representing different clinical beam energies and radiation types. In the noise and SNR analyses, only the 6 MV photon beam was selected as the representative to compare between EBT4 and EBT3 models. Results: The energy dependence test results showed that there was a slight difference (<2% at most dose levels) in the dose response among the clinical MV photons and MeV electrons. However, a large deviation (>10%) in the dose response was found for the 120 kVp x‐ray beam. For the two 250 kVp x‐ray beams, the difference in the dose response was moderate (<5%), but not negligible. The noise and SNR results showed a reduced noise and strengthened SNR in EBT4. Conclusion: We conclude that the EBT4 film has a minimal energy dependence for MV photon and MeV electron beams but has a notable energy dependence for kilovoltage x‐ray beams, and the vendor‐stated features of the reduced noise and improved SNR in EBT4 are validated. [ABSTRACT FROM AUTHOR]

Background and Aim: Gallium-68 (68Ga)-Prostate Membrane Specific Antigen Positron Emission Tomography/Computed Tomography (68Ga-PSMA PET/CT) is an emerging diagnostic modality which is gaining importance in individualized prostate cancer (PCa) management era. This study aimed to investigate the diagnostic accuracy of 68Ga-PSMA PET/CT on primary LN staging before radical prostatectomy (RP) in intermediate and high risk PCa.Materials and Methods: The retrospectively documented 49 patients with intermediate and high risk non-metastatic PCa who had 68Ga-PSMA PET/CT before RP were enrolled into this study. The histopathology of dissected LNs was used as reference standard to evaluate the accuracy of 68Ga-PSMA PET/CT on primary LN staging, both in per-patient (n = 49) and in per-node (n = 454) analyses. The diagnostic accuracy was investigated using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), and by area under the curve (AUC) provided using receiver operating curve (ROC) analysis.Results: Median age was 64 (48-79) years and, median and mean PSA values were 10 (1.31-138) ng/ml and 16.2 (±19.8) ng/ml, respectively. 22 (44.9%) and 27 (55.1%) of patients had intermediate and high risk PCa, respectively. A total of 5 (10.2%) patients had histopathologically proven LN metastasis and 3 (60%) of them was detected in 68Ga-PSMA PET/CT. In per patient analysis, the sensitivity, specifity, PPV and NPV of 68Ga-PSMA PET/CT on primary LN staging were 0.60, 0.96, 0.60 and 0.96, respectively. Among overall 454 LNs, 16 (3.5 %) of them were reported as metastatic in histopathology and, 13 (2.9%) of these metastatic LNs were detected in 68Ga-PSMA PET/CT. In per-node analysis, the sensitivity, specificity, PPV and NPV of 68Ga-PSMA PET/CT on primary LN staging were 0.82, 0.99, 0.87 and 0.99, respectively. The ROC analyses found AUCs for primary LN staging as 0.777 (95%CI:0.508-1.0) in per patient analysis and, as 0.904 (95%CI:0.790 - 1.0) in per node analysis, respectively.Conclusion: The use of 68Ga-PSMA PET/CT has promising diagnostic accuracy on primary LN staging before RP in intermediate and high risk PCa. However, the efforts should be taken to increase sensitivity of 68Ga-PSMA PET/CT in individualized treatment era. [ABSTRACT FROM AUTHOR]

Background and Aim: Gallium-68 (68Ga)-Prostate Membrane Specific Antigen Positron Emission Tomography/Computed Tomography (68Ga-PSMA PET/CT) is an emerging diagnostic modality which is gaining importance in individualized prostate cancer (PCa) management era. This study aimed to investigate the diagnostic accuracy of 68 Ga-PSMA PET/CT on primary LN staging before radical prostatectomy (RP) in intermediate and high risk PCa., Materials and Methods: The retrospectively documented 49 patients with intermediate and high risk non-metastatic PCa who had 68 Ga-PSMA PET/CT before RP were enrolled into this study. The histopathology of dissected LNs was used as reference standard to evaluate the accuracy of 68 Ga-PSMA PET/CT on primary LN staging, both in per-patient (n = 49) and in per-node (n = 454) analyses. The diagnostic accuracy was investigated using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), and by area under the curve (AUC) provided using receiver operating curve (ROC) analysis., Results: Median age was 64 (48-79) years and, median and mean PSA values were 10 (1.31-138) ng/ml and 16.2 (±19.8) ng/ml, respectively. 22 (44.9%) and 27 (55.1%) of patients had intermediate and high risk PCa, respectively. A total of 5 (10.2%) patients had histopathologically proven LN metastasis and 3 (60%) of them was detected in 68 Ga-PSMA PET/CT. In per patient analysis, the sensitivity, specifity, PPV and NPV of 68 Ga-PSMA PET/CT on primary LN staging were 0.60, 0.96, 0.60 and 0.96, respectively. Among overall 454 LNs, 16 (3.5 %) of them were reported as metastatic in histopathology and, 13 (2.9%) of these metastatic LNs were detected in 68 Ga-PSMA PET/CT. In per-node analysis, the sensitivity, specificity, PPV and NPV of 68 Ga-PSMA PET/CT on primary LN staging were 0.82, 0.99, 0.87 and 0.99, respectively. The ROC analyses found AUCs for primary LN staging as 0.777 (95%CI:0.508-1.0) in per patient analysis and, as 0.904 (95%CI:0.790 - 1.0) in per node analysis, respectively., Conclusion: The use of 68 Ga-PSMA PET/CT has promising diagnostic accuracy on primary LN staging before RP in intermediate and high risk PCa. However, the efforts should be taken to increase sensitivity of 68 Ga-PSMA PET/CT in individualized treatment era., Competing Interests: Conflict of interest All authors declare that they have no conflict of interest, (Copyright © 2021 Elsevier Inc. All rights reserved.)