Intractable Trigeminal Neuralgia Secondary to Osteoma of the Clivus: A Case Report and Literature Review

Skull base osteomas (SBOs) are benign tumors that are frequently detected on radiographic images by coincidence. They are known for being slow-growing tumors and rarely symptomatic. The therapeutic approach for SBOs can differ substantially. Depending on the symptoms, size, and location of the tumor, this can range from serial observation to vigorous surgical extirpation. Clival osteoma is extremely rare. We report a case of clival osteoma, causing intractable trigeminal neuralgia due to the pressure effect on the trigeminal nerve at Meckel's cave. We also provide a review of pertinent literature. A 37-year-old woman presented with intractable trigeminal neuralgia. Cranial magnetic resonance imaging (MRI) demonstrated a large, lobulated, extra-axial lesion involving the right cerebellopontine angle and epicentering the clivus. Pathologically, the specimen was proven to be osteoma. The patient reported complete symptom resolution over a 4-year follow-up period. To the best of the authors' knowledge, this is the first clinical case of intractable trigeminal neuralgia due to clival osteoma.

Angioscopic evaluation of vascular healing at 1 and 12 months after drug-coated stent implantation

Background Polymer- and carrier-free Biolimus-A9-coated stent (DCS) is expected better vascular healing compared with conventional durable polymer drug-eluting stents (DES). Moreover, DCS had been demonstrated in clinical trials to allow one-month short dual antiplatelet therapy, which might achieve sufficient healing at only 1 month after implantation. However, the process of vascular healing after DCS implantation has not been elucidated by angioscopic observation. Purpose To evaluate the process of vascular healing at 1 month and 12 months after DCS implantation. Methods This study included 57 patients treated with DCS or durable polymer everolimus-eluting stents (EES) in our hospital from April 2017 to April 2019. Firstly, the angioscopic findings of DCS at 1 month (n=16) and 12 months (n=14) after implantation were respectively compared with EES at 12 months after implantation (EES-12, n=35) as a standard healing status of DES. Secondary, angioscopic findings of DCS at 1 month and 12 months after implantation were compared among the serially observed eight patients. Neointimal coverage (NIC) grade, yellow colour grade, and the presence of thrombus were evaluated. NIC grade was classified as grade 0 (no neointimal coverage), grade 1 (struts were bulged into lumen but covered), grade 2 (struts were embedded in the neointima but visible), or grade 3 (struts were fully embedded and invisible). Yellow colour grade was classified as grade 0 (white), grade 1 (light yellow), grade 2 (yellow), or grade 3 (intensive yellow). Results At 1 month after DCS implantation, dominant NIC grade was lower (0.3±0.5 vs. 1.5±0.7, p<0.001) and the frequency of thrombus was higher (38% vs. 6%, p=0.008) than EES-12. On the other hands, at 12 months after DCS implantation, dominant NIC grade was higher (2.1±0.6 vs. 1.5±0.7, p=0.013) and the frequency of thrombus was not different (7% vs. 6%, p=1.000) in comparison with EES-12. By serial observation of DCS, dominant NIC grade was higher at 12 months than at 1 month (2.3±0.5 vs. 0.4±0.5, p<0.001), while yellow colour grade (1.0±0.5 vs. 1.5±1.2, p=0.227) and the frequency of thrombus adhesion (0% vs. 38%, p=0.200) were not different. Conclusion Compared with EES-12, vascular healing of DCS was inferior at 1 month but superior at 12 months. Figure 1 Funding Acknowledgement Type of funding source: None

Quadratic Polynomial Regression Using Serial Observation Processing: Implementation within DART

It is well known that the ensemble-based variants of the Kalman filter may be thought of as producing a state estimate that is consistent with linear regression. Here, it is shown how quadratic polynomial regression can be performed within a serial data assimilation framework. The addition of quadratic polynomial regression to the Data Assimilation Research Testbed (DART) is also discussed and its performance is illustrated using a hierarchy of models from simple scalar systems to a GCM.