目的:探討嗅溝腦膜瘤的影像學表現與病理組織學之間的相關關系及其鑒別診斷。方法:對11例經手術及病理證實為嗅溝腦膜瘤的患者進行回顧性分析。男5例,女6例,年齡29～59歲,平均48歲。行CT檢查3例,MRI檢查8例,均為增強掃描。分析CT、MRI影像特征,并與手術、病理結果對照。結果:瘤灶起源于顱前窩嗅溝,多數密度或信號均勻,邊界清楚,均勻增強;少數不均勻增強,大部分病例出現腦膜尾征,少數伴鈣化、壞死、囊變。鄰近顱骨受累時引起骨質增生或受侵。結論:起源于嗅溝的腦膜瘤均具有典型的影像學表現特征。嗅溝骨質及其腦膜影像改變的顯示,對瘤灶起源具有重要的定位、定性診斷價值。MRI優于CT,但CT對鈣化和骨質改變顯示優于MRI。
目的 探討膝關節盤狀半月板的診斷標準，雙膝盤狀半月板的MRI分型及損傷特點。 方法 通過對2009年11月－2013年3月，13 936膝大樣本量的MRI檢查的盤狀半月板流行病學研究，篩查出雙膝關節盤狀半月板956膝，并對診斷為盤狀半月板的全部患者行冠狀位髁間棘層面半月板寬度與脛骨平臺寬度之比（板面比）、矢狀位“領結樣”改變層面中半月板后角最厚層面的厚度（半月板后角厚度）及矢狀位“領結樣”改變層數測量并分析；根據盤狀半月板MRI表現分為板型、楔型、肥角型；分析雙膝盤狀半月板分型，比較雙膝盤狀半月板損傷率與總體損傷率的差別。 結果 956膝盤狀半月板中伴撕裂392膝，損傷率為41.0%；篩查出45例90膝雙膝盤狀半月板，外側44例，內側1例，其中板型58膝、楔型32膝，無肥角型，伴盤狀半月板撕裂23膝，損傷率為25.5%；雙膝盤狀半月板的損傷率低于盤狀半月板總體平均值。 結論 板面比≥0.20、半月板后角厚度≥4.40 mm、矢狀位連續“領結樣”改變層數≥3層為盤狀半月板的MRI診斷標準；雙膝盤狀半月板多見于外側，分型中未見肥角型，損傷率較總體損傷率低。
With the rapid development of artificial intelligence technology, researchers have applied it to the diagnosis of various tumors in the urinary system in recent years, and have obtained many valuable research results. The article sorted the research status of artificial intelligence technology in the fields of renal tumors, bladder tumors and prostate tumors from three aspects: the number of papers, image data, and clinical tasks. The purpose is to summarize and analyze the research status and find new valuable research ideas in the future. The results show that the artificial intelligence model based on medical data such as digital imaging and pathological images is effective in completing basic diagnosis of urinary system tumors, image segmentation of tumor infiltration areas or specific organs, gene mutation prediction and prognostic effect prediction, but most of the models for the requirement of clinical application still need to be improved. On the one hand, it is necessary to further improve the detection, classification, segmentation and other performance of the core algorithm. On the other hand, it is necessary to integrate more standardized medical databases to effectively improve the diagnostic accuracy of artificial intelligence models and make it play greater clinical value.