RESUMEN
BACKGROUND: The integration of Artificial Intelligence (AI) technology in cancer care has gained unprecedented global attention over the past few decades. This has impacted the way that cancer care is practiced and delivered across settings. The purpose of this study was to explore the perspectives and experiences of healthcare professionals (HCPs) on cancer treatment and the need for AI. This study is a part of the INCISIVE European Union H2020 project's development of user requirements, which aims to fully explore the potential of AI-based cancer imaging technologies. METHODS: A mixed-methods research design was employed. HCPs participating in cancer care in the UK, Greece, Italy, Spain, Cyprus, and Serbia were first surveyed anonymously online. Twenty-seven HCPs then participated in semi-structured interviews. Appropriate statistical method was adopted to report the survey results by using SPSS. The interviews were audio recorded, verbatim transcribed, and then thematically analysed supported by NVIVO. RESULTS: The survey drew responses from 95 HCPs. The occurrence of diagnostic delay was reported by 56% (n = 28/50) for breast cancer, 64% (n = 27/42) for lung cancer, 76% (n = 34/45) for colorectal cancer and 42% (n = 16/38) for prostate cancer. A proportion of participants reported the occurrence of false positives in the accuracy of the current imaging techniques used: 64% (n = 32/50) reported this for breast cancer, 60% (n = 25/42) for lung cancer, 51% (n = 23/45) for colorectal cancer and 45% (n = 17/38) for prostate cancer. All participants agreed that the use of technology would enhance the care pathway for cancer patients. Despite the positive perspectives toward AI, certain limitations were also recorded. The majority (73%) of respondents (n = 69/95) reported they had never utilised technology in the care pathway which necessitates the need for education and training in the qualitative finding; compared to 27% (n = 26/95) who had and were still using it. Most, 89% of respondents (n = 85/95) said they would be opened to providing AI-based services in the future to improve medical imaging for cancer care. Interviews with HCPs revealed lack of widespread preparedness for AI in oncology, several barriers to introducing AI, and a need for education and training. Provision of AI training, increasing public awareness of AI, using evidence-based technology, and developing AI based interventions that will not replace HCPs were some of the recommendations. CONCLUSION: HCPs reported favourable opinions of AI-based cancer imaging technologies and noted a number of care pathway concerns where AI can be useful. For the future design and execution of the INCISIVE project and other comparable AI-based projects, the characteristics and recommendations offered in the current research can serve as a reference.
Asunto(s)
Neoplasias de la Mama , Neoplasias Colorrectales , Neoplasias Pulmonares , Neoplasias de la Próstata , Masculino , Humanos , Inteligencia Artificial , Diagnóstico Tardío , Atención a la SaludRESUMEN
OBJECTIVE: To analyze cases of ovarian leiomyomas and to discuss the proper surgical management. DESIGN: A case series and discussion. SETTING: General university hospital and healthcare center. PATIENT(S): Nine patients who were diagnosed with ovarian leiomyomas after surgery between 1993 and 2009. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): A preoperative diagnosis that was matched to the postoperative diagnosis and the type of surgery. RESULT(S): In all cases, ovarian leiomyoma was misdiagnosed preoperatively as pedunculated uterine myoma, ovarian fibroma, or even ovarian endometrioma. Seven (77.8%) of the nine patients underwent a salpingo-oophorectomy or an oophorectomy with or without hysterectomy, and only two (22.2%) patients were submitted to an ovary-preserving surgery (i.e., a cystectomy or ovarian wedge resection). CONCLUSION(S): Because of their extreme rarity, ovarian leiomyomas are seldom suspected intraoperatively or preoperatively. However, most of these tumors appear at reproductive age and have a benign nature, similar to uterine myomas. Therefore, surgeons should perform ovary-preserving management, especially in young patients.