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1.
J Pathol Inform ; 15: 100378, 2024 Dec.
Article in English | MEDLINE | ID: mdl-38868487

ABSTRACT

Background: Prostate cancer ranks as the most frequently diagnosed cancer in men in the USA, with significant mortality rates. Early detection is pivotal for optimal patient outcomes, providing increased treatment options and potentially less invasive interventions. There remain significant challenges in prostate cancer histopathology, including the potential for missed diagnoses due to pathologist variability and subjective interpretations. Methods: To address these challenges, this study investigates the ability of artificial intelligence (AI) to enhance diagnostic accuracy. The Galen™ Prostate AI algorithm was validated on a cohort of Puerto Rican men to demonstrate its efficacy in cancer detection and Gleason grading. Subsequently, the AI algorithm was integrated into routine clinical practice during a 3-year period at a CLIA certified precision pathology laboratory. Results: The Galen™ Prostate AI algorithm showed a 96.7% (95% CI 95.6-97.8) specificity and a 96.6% (95% CI 93.3-98.8) sensitivity for prostate cancer detection and 82.1% specificity (95% CI 73.9-88.5) and 81.1% sensitivity (95% CI 73.7-87.2) for distinction of Gleason Grade Group 1 from Grade Group 2+. The subsequent AI integration into routine clinical use examined prostate cancer diagnoses on >122,000 slides and 9200 cases over 3 years and had an overall AI Impact ™ factor of 1.8%. Conclusions: The potential of AI to be a powerful, reliable, and effective diagnostic tool for pathologists is highlighted, while the AI Impact™ in a real-world setting demonstrates the ability of AI to standardize prostate cancer diagnosis at a high level of performance across pathologists.

2.
Gynecol Oncol Rep ; 48: 101236, 2023 Aug.
Article in English | MEDLINE | ID: mdl-37576355

ABSTRACT

The Human Papillomavirus (HPV) causes cervical cancer, the fourth most common cause of death in women in the United States (US). Several major screening clinical trials have demonstrated that high risk HPV (HR-HPV) DNA primary screen is more sensitive at determining the risk of cervical intraepithelial neoplasia level 3 or higher (CIN ≥ 3) than cytology alone and is similar to co-testing. In this cross-sectional study, we characterized a Hispanic population of 18,052 women ages 21-70 years with HR-HPV DNA testing and cytology to determine the prevalence of HR-HPV in the population and determine the likelihood of high grade squamous intraepithelial lesion (HSIL). We also compared cytology, HR-HPV DNA testing, and co-testing strategies to determine sensitivity, specificity, positive predictive value, and negative predictive value for HSIL in cervical biopsies. Results show that HR-HPV had a slightly higher sensitivity (94.2% vs 92.3%) compared to cytology for all high-grade disease (CIN2/3).

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