Metastasis to the skull frequently occurs in patients with lung, breast and prostate cancer. However, skull metastases from hepatocellular carcinoma (HCC) have been rarely reported. We review the literature on skull metastasis from HCC and report a case of a 46-year-old male, who was diagnosed as HCC and was operated on by trans-arterial embolization and lobectomy in Oct. 2004. He complained of a painless mass over the left frontal region for two months. Radiograph of the skull revealed an osteolytic mass about 4-5 cm in size over the left frontal region. A cranial computerized tomography demonstrated a destructive lesion with soft tissue mass over the left frontal region. A left frontal craniectomy was performed and tumor was totally removed. The histological diagnosis was cranial metastasis from HCC. Postoperative recovery was uneventful without any neurological deficits. Because of improved and advancing treatment for HCC, survival time for HCC has been lengthened and distant metastases will thus be found to increase. Early diagnosis is essential to treat the primary disease. Skull metastases from HCC should be considered as a differential diagnosis in patients with scalp subcutaneous mass and osteolytic defect on X-ray skull films.
With the proliferation of paid mobile learning applications (m-learning apps), understanding how to assess their success has become an important issue for academics and practitioners. Based on the information systems (IS) success models and the value-based adoption model, this study developed and validated a multidimensional model for assessing paid m-learning app success. The proposed model describes the interrelationships among seven paid m-learning app success variables: system quality, information quality, perceived enjoyment, perceived fee, user satisfaction, intention to reuse, and learning effectiveness. Data collected from 160 paid m-learning app users were tested against the research model using structural equation modeling (SEM). The empirical findings provide evidence that learning effectiveness is affected by user satisfaction and intention to reuse, which, in turn, are determined by system quality, information quality, perceived enjoyment, and perceived fee. The findings of this study provide several important theoretical and practical implications for the development, implementation, and promotion of paid m-learning apps.
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