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Browsing by Subject "Cerebellar neoplasms"
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Item A 41-year-old woman with von Hippel-Lindau and a cerebellar lesion(Wiley, 2010-03) Martin, Sarah E.; Al-Khatib, Sohaib M.; Turner, Michael S.; Douglas-Akinwande, Annette C.; Hattab, Eyas M.; Pathology and Laboratory Medicine, School of MedicineA 41-year-old woman with a 12-year history of von Hippel-Lindau disease presented with progressive quadriparesis and difficulty swallowing. MRI revealed a well-circumscribed, partially cystic cerebellar neoplasm, consistent with hemangioblastoma. The tumor was resected and the diagnosis of hemangioblastoma confirmed. Embedded within the hemangioblastoma was a small focus of metastatic renal cell carcinoma (RCC). RCC metastatic to a CNS hemangioblastoma is the second most common type of tumor-to-tumor metastasis, which may be due to a number of factors. Proper immunostaining panels are required to clearly identify these cases since both tumor may have similar histology.Item Radiomic Phenotypes Distinguish Atypical Teratoid/Rhabdoid Tumors from Medulloblastoma(American Society of Neuroradiology, 2021) Zhang, M.; Wong, S. W.; Lummus, S.; Han, M.; Radmanesh, A.; Ahmadian, S. S.; Prolo, L. M.; Lai, H.; Eghbal, A.; Oztekin, O.; Cheshier, S. H.; Fisher, P. G.; Ho, C. Y.; Vogel, H.; Vitanza, N. A.; Lober, R. M.; Grant, G. A.; Jaju, A.; Yeom, K. W.; Radiology and Imaging Sciences, School of MedicineBackground and purpose: Atypical teratoid/rhabdoid tumors and medulloblastomas have similar imaging and histologic features but distinctly different outcomes. We hypothesized that they could be distinguished by MR imaging-based radiomic phenotypes. Materials and methods: We retrospectively assembled T2-weighted and gadolinium-enhanced T1-weighted images of 48 posterior fossa atypical teratoid/rhabdoid tumors and 96 match-paired medulloblastomas from 7 institutions. Using a holdout test set, we measured the performance of 6 candidate classifier models using 6 imaging features derived by sparse regression of 900 T2WI and 900 T1WI Imaging Biomarker Standardization Initiative-based radiomics features. Results: From the originally extracted 1800 total Imaging Biomarker Standardization Initiative-based features, sparse regression consistently reduced the feature set to 1 from T1WI and 5 from T2WI. Among classifier models, logistic regression performed with the highest AUC of 0.86, with sensitivity, specificity, accuracy, and F1 scores of 0.80, 0.82, 0.81, and 0.85, respectively. The top 3 important Imaging Biomarker Standardization Initiative features, by decreasing order of relative contribution, included voxel intensity at the 90th percentile, inverse difference moment normalized, and kurtosis-all from T2WI. Conclusions: Six quantitative signatures of image intensity, texture, and morphology distinguish atypical teratoid/rhabdoid tumors from medulloblastomas with high prediction performance across different machine learning strategies. Use of this technique for preoperative diagnosis of atypical teratoid/rhabdoid tumors could significantly inform therapeutic strategies and patient care discussions.