ABSTRACT
Background Lung carcinoma is a leading cause of death worldwide. Histological subtype of lung adenocarcinoma is an important indicator of patient's outcome as it is helpful in surgical planning and guidance of prognosis. Objective To determine the diagnostic efficacy of computerized tomography-guided core needle biopsy (CNB) in identifying the histopathological subtype of lung adenocarcinoma. Methods and materials This is a retrospective, descriptive study including clinical data of 73 patients irrespective of their age and gender, who underwent computerized tomography-guided CNB for lung masses at the Department of Pathology, Aznostics - the Diagnostic Centre, Lahore, Pakistan from January 01, 2019 to June 30, 2023. Data collected was analyzed via Google Form (Google Inc., Mountainview, CA) and Statistical Package for Social Sciences (IBM SPSS Statistics for Windows, Version 24, released 2016; IBM Corp., Armonk, New York, United States) and was sent to statistician for descriptive analysis. Categorical data was used for calculating frequency and percentage, while continuous data was computed as mean and standard deviation. Results Seventy-three patients with adenocarcinoma underwent pulmonary biopsy. The mean age of included patients was 64.88 ± 11.39 year with a male predominance of 61.64%. Upper lobe was commonly affected by adenocarcinoma lung in 57.53% patients and 58.90% cases involved the right lung. The most common subtype was acinar with 51.65% followed by solid with 17.58% cases. Computerized tomography-guided CNB showed a diagnostic yield of 75.34% and identified histological subtypes of lung adenocarcinoma in 55 cases. Conclusion Computerized tomography-guided CNB is a useful, yet minimally invasive diagnostic tool to identify the histological subtype of lung adenocarcinoma. It not only helps in planning the surgical and adjuvant management of the patients, but also guides the patient-prognosis.
ABSTRACT
Background Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, enabling them to perform tasks. The advancements in AI have also improved virtual reality (VR), augmented reality (AR) and mixed reality (MR) experience allowing a greater opportunity for use in the field of medicine. Objective To evaluate the knowledge, attitude and practice of AI and types of realities among Pakistani healthcare professionals (HCPs). Materials and methods This was a prospective, nationwide study designed at the Department of Neurosurgery at Punjab Institute of Neurosciences (PINS), Lahore, was conducted between January 2024 to February 2024. More than 500 HCPs were approached, out of which 176 participated in this survey consensually. A pre-formed general questionnaire based on knowledge, attitude and practices of AI and types of realities was modified according to local conditions. Google Forms (Google Inc., USA) was used to conduct the one-time sign up response. Statistical Package for Social Sciences (IBM SPSS Statistics for Windows, Version 24, USA) was used to analyze submitted responses. Results About 69.9% respondents were male HCPs. Most of the respondents were from the fields of neurosurgery, medicine and general surgery, i.e., 10.80%, 10.20% and 4%, respectively. More than 90% HCPs used Internet and electronic devices daily. A majority of 62.50% respondents agreed that AI brings benefits for the patients, while at the same time, 45.50% agreed that they would not trust the assessment of AI more than that of HCPs. 61% HCPs feared that AI-based systems could be manipulated from the outside sources, like terrorists and hackers. Although 90% respondents knew the definition of AR and VR, a strikingly low 40% respondents could only identify the practical applications of these realities when asked in a mini-quiz. About 61.40% HCPs never used any AI-based application throughout their clinical practice, but Google Health was used by 29.50% respondents, followed by Remote Patient Monitoring AI application used by 3.4% individuals. Conclusion There is an evident under-utilization of AI and types of realities in clinical practice in Pakistan. Lack of awareness, paucity of resources and conventional clinical practices are the key reasons identified. Pakistan is on the path towards the point where the developed world is currently. There is a potential to move past the initial stages of AI implementation and into more advanced modes of adopting AI and types of realities.
