During the medical rescue after Wenchuan earthquake, the Department of Appliances and Materials of West China Hospital took prompt action to ensure the regular operation of hospital devices and facilities. Meanwhile, owing to its specialized superiority of material and appliance purchase as well as the optimized processes for material and appliance supply, the hospital ensured the effective supply of disaster relief materials and efficiently managed the consumption of donated materials. From May 12 to 30, a total of 2 200 000 pieces of medical materials (total value RMB 3 770 000 Yuan) and 220 sets of medical appliance (total value RMB 9 000 000 Yuan) were purchased as part of the immediate medical rescue response to the earthquake.
Theory of risk control was introduced to medical instruments quality control management in West China Hospital. A quality control system for the whole life cycle management of instruments has been established, which includes evaluation before instrument purchase, policy and management of bidding, operation training, safe maintenance, maintenance management and waste disposal. Medical instrument quality system was introduced to provide information for medical instrument risk control and quality management in a large, general Chinese hospital.
目的 評價選擇性介入治療在原發性肝癌（HCC）門脈高壓癥中的應用價值。 方法 2008年11月－2011年3月，收治65例臨床明確診斷的HCC伴門脈高壓癥患者，選擇性使用肝動脈化學療法（化療）栓塞術、脾栓塞術、門靜脈化療栓塞術、門靜脈支架、胃冠狀靜脈栓塞術等介入術式，術后通過觀察臨床指標、定期復查影像檢查等了解病變轉歸，隨訪生存期并評價療效。 結果 65例HCC患者均合并不同程度門靜脈高壓，其中門靜脈癌栓46例中有37例顯示肝動脈-門靜脈分流，通過肝動脈及門靜脈化療栓塞術進行主瘤體及癌栓治療。11例行門靜脈支架置入術，支架置入后門靜脈壓較術前明顯下降（P＜0.01），支架中位通暢時間為5.8個月。39例行胃冠狀靜脈和（或）胃短靜脈栓塞術，術后有4例再次發生門脈高壓性出血，再出血率10.26%。18例行脾動脈栓塞術，術后3個月血小板較術前顯著升高（P＜0.01）。隨訪術后3、6、12及24個月的生存率分別為90.77%、69.23%、35.38%及13.85%。 結論 選擇性聯合使用各種介入術式是治療HCC及其相關性門脈高壓癥的一種有效方法，可有效預防高危風險，延長患者生存期。
In colorectal cancer histopathology, the collaborative perception of microscopic and salient lesions is critical for effective diagnosis and improved patient prognosis. However, existing deep learning methods struggle to simultaneously capture microscopic glandular disorganization and salient tissue lesions. To address this limitation, a colorectal cancer diagnosis network based on dynamic gland-aware and tissue soft-clustering (DGTSNet) is proposed. The method employs dynamic gland-aware convolution to explicitly perceive gland boundaries and dynamically adjust sampling offsets, while incorporating a continuous-domain constraint to prevent out-of-bound sampling, thereby enhancing the perception of microscopic glandular disorders. Meanwhile, a tissue soft-clustering module is utilized to adaptively generate clustering prototypes and guide pixels toward relevant prototype centroids according to semantic similarity, suppressing irrelevant background interference and enhancing responses to significant tissue lesions. Finally, a cascaded sparse coupling module is introduced to collaboratively modulate cross-semantic feature representations along both the spatial and channel dimensions, while constructing differentiable masks to suppress low-contribution semantics, thereby achieving collaborative coupling of cross-semantic features. Experimental results demonstrated that the proposed method achieved superior performance on the Chaoyang, Kather-5K, and EBHI datasets, as well as a real-world clinical validation cohort, outperforming multiple baseline models. The study shows that the proposed method can effectively enhance the joint perception of microscopic glandular disorders and significant tissue lesions, providing an effective solution for colorectal cancer diagnosis.