Sarcopenia is a syndrome of progressive loss of skeletal muscle mass and strength resulting in physical disability reduced quality of life and death. Sarcopenia is common in the elderly and patients with cancer. Tumor combined with sarcopenia often occurs in the solid tumors such as gastrointestinal cancers head and neck cancers breast cancers and lung cancers. Due to frequent morbidity tumor combined with sarcopenia is highly correlated with adverse reaction of radiation therapy and chemotherapy and also with perioperative complications and diagnosis. Diagnostic methods for sarcopenia can be divided into non - imaging and imaging tests. At present studies on imaging evaluation and diagnosis of tumor - associated sarcopenia have been carried out extensively. Traditional diagnostic methods are cumbersome time-consuming and laborious. With the development of computer science in recent years the method of artificial intelligence driven by massive data computing power and algorithms can quickly and accurately accomplish imaging evaluation. This article reviews the specific imaging methods for the assessment of tumor-associated sarcopenia the advantages and disadvantages of AI - assisted assessment methods and the results of meta - studies. The aim is to clarify the important clinical value and application prospect of artificial intelligence method in evaluating tumor-associated sarcopenia provide a basis for further large-scale clinical studies and increase clinicians' attention to AI-related evaluation.