The puzzling Spitz tumours: is artificial intelligence the key to their understanding?

IF 3.9 2区医学 Q2 CELL BIOLOGY

Histopathology Pub Date : 2025-02-20 DOI:10.1111/his.15428

Laëtitia Launet, Adrián Colomer, Andrés Mosquera-Zamudio, Carlos Monteagudo, Valery Naranjo

{"title":"The puzzling Spitz tumours: is artificial intelligence the key to their understanding?","authors":"Laëtitia Launet, Adrián Colomer, Andrés Mosquera-Zamudio, Carlos Monteagudo, Valery Naranjo","doi":"10.1111/his.15428","DOIUrl":null,"url":null,"abstract":"<p><p>Since their first description in 1948, Spitz tumours remain one of the most challenging diagnostic entities in dermatopathology due to their complex histological features and ambiguous clinical behaviour. In recent years, artificial intelligence (AI) solutions have demonstrated significant potential across a wide range of medical applications, including computational pathology, for decision-making in diagnosis, along with promising advances in prognosis and tumour classification. However, the application of AI to Spitz tumours remains relatively underexplored, with few studies addressing this field. Yet in this evolving technological landscape, could AI provide the insights needed to help resolve the diagnostic uncertainties surrounding Spitz tumours? How could this technology be leveraged to bridge the gap between histopathological uncertainty and clinical accuracy? This review aims to provide an overview of the current state of AI applications in Spitz tumour analysis, identify existing research gaps, and propose future directions to optimize the use of AI in understanding and diagnosing these complex tumours.</p>","PeriodicalId":13219,"journal":{"name":"Histopathology","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Histopathology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/his.15428","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CELL BIOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Since their first description in 1948, Spitz tumours remain one of the most challenging diagnostic entities in dermatopathology due to their complex histological features and ambiguous clinical behaviour. In recent years, artificial intelligence (AI) solutions have demonstrated significant potential across a wide range of medical applications, including computational pathology, for decision-making in diagnosis, along with promising advances in prognosis and tumour classification. However, the application of AI to Spitz tumours remains relatively underexplored, with few studies addressing this field. Yet in this evolving technological landscape, could AI provide the insights needed to help resolve the diagnostic uncertainties surrounding Spitz tumours? How could this technology be leveraged to bridge the gap between histopathological uncertainty and clinical accuracy? This review aims to provide an overview of the current state of AI applications in Spitz tumour analysis, identify existing research gaps, and propose future directions to optimize the use of AI in understanding and diagnosing these complex tumours.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Histopathology 医学-病理学

CiteScore

10.20

自引率

4.70%

发文量

239

审稿时长

1 months

期刊介绍： Histopathology is an international journal intended to be of practical value to surgical and diagnostic histopathologists, and to investigators of human disease who employ histopathological methods. Our primary purpose is to publish advances in pathology, in particular those applicable to clinical practice and contributing to the better understanding of human disease.