The relationship of pathology, represented by the rise of telepathology in the late 1960s, has evolved into the era of artificial intelligence assisted digital pathology.This field includes the application of digitized specimens to visualize, share, and conclude pathology information in a digital space.Radiomics, the extraction of quantitative features from radiological images, has been an effective technique in neuropathology and intraoperative diagnosis.Ongoing technological advancements, these methods offer enhanced diagnostic accuracy and expedited treatment decisions.However, evaluating their accuracies and reproducibility relative to traditional methods remains controversial.By and large, a group of specific techniques used for diagnosis, prognosis, and prediction of intracranial lesions.Digital pathology enables pathologists to assess radiologic images concurrently with frozen section slides, promoting real-time collaboration and informed decision-making regardless of geographical barriers.Our study investigates the reproducibility of digital pathology, AI, and radiomics in neuropathology and intraoperative diagnosis.By analyzing case studies, literature, and data analysis, this research sheds light on factors impacting the reliability of these techniques.Ultimately, this study aims to emphasize potential benefits and limitations of these technologies, mentioning their aspects to clinical practice.
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Edis et al. (2024) studied this question.
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