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Your search keyword '"Biomathematical models"' showing total 3 results
Start Over Descriptor "Biomathematical models" Topic neuroimaging
3 results on '"Biomathematical models"'

1. Sex-specific impact of patterns of imageable tumor growth on survival of primary glioblastoma patients

Author

Paula Whitmire, Cassandra R. Rickertsen, Andrea Hawkins-Daarud, Eduardo Carrasco, Julia Lorence, Gustavo De Leon, Lee Curtin, Spencer Bayless, Kamala Clark-Swanson, Noah C. Peeri, Christina Corpuz, Christine Paula Lewis-de los Angeles, Bernard R. Bendok, Luis Gonzalez-Cuyar, Sujay Vora, Maciej M. Mrugala, Leland S. Hu, Lei Wang, Alyx Porter, Priya Kumthekar, Sandra K. Johnston, Kathleen M. Egan, Robert Gatenby, Peter Canoll, Joshua B. Rubin, and Kristin R. Swanson

Subjects
Glioblastoma, Neuroimaging, Sex differences, Biomathematical models, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Sex is recognized as a significant determinant of outcome among glioblastoma patients, but the relative prognostic importance of glioblastoma features has not been thoroughly explored for sex differences. Methods Combining multi-modal MR images, biomathematical models, and patient clinical information, this investigation assesses which pretreatment variables have a sex-specific impact on the survival of glioblastoma patients (299 males and 195 females). Results Among males, tumor (T1Gd) radius was a predictor of overall survival (HR = 1.027, p = 0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR = 1.011, p

Published
2020
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2. Sex-specific impact of patterns of imageable tumor growth on survival of primary glioblastoma patients.

Author

Whitmire, Paula, Rickertsen, Cassandra R., Hawkins-Daarud, Andrea, Carrasco, Eduardo, Lorence, Julia, De Leon, Gustavo, Curtin, Lee, Bayless, Spencer, Clark-Swanson, Kamala, Peeri, Noah C., Corpuz, Christina, Lewis-de los Angeles, Christine Paula, Bendok, Bernard R., Gonzalez-Cuyar, Luis, Vora, Sujay, Mrugala, Maciej M., Hu, Leland S., Wang, Lei, Porter, Alyx, and Kumthekar, Priya

Subjects
*TUMOR growth, *MAGNETIC resonance imaging, *GLIOBLASTOMA multiforme, *CELL proliferation, *OLIGODENDROGLIOMAS
Abstract

Background: Sex is recognized as a significant determinant of outcome among glioblastoma patients, but the relative prognostic importance of glioblastoma features has not been thoroughly explored for sex differences.Methods: Combining multi-modal MR images, biomathematical models, and patient clinical information, this investigation assesses which pretreatment variables have a sex-specific impact on the survival of glioblastoma patients (299 males and 195 females).Results: Among males, tumor (T1Gd) radius was a predictor of overall survival (HR = 1.027, p = 0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR = 1.011, p < 0.001). Female extreme survivors had significantly smaller tumors (T1Gd) (p = 0.010 t-test), but tumor size was not correlated with female overall survival (p = 0.955 CPH). Both male and female extreme survivors had significantly lower tumor cell net proliferation rates than other patients (M p = 0.004, F p = 0.001, t-test).Conclusion: Despite similar distributions of the MR imaging parameters between males and females, there was a sex-specific difference in how these parameters related to outcomes. [ABSTRACT FROM AUTHOR]

Published
2020
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3. Sex-specific impact of patterns of imageable tumor growth on survival of primary glioblastoma patients

Author

Peter Canoll, Alyx B. Porter, Priya Kumthekar, Maciej M. Mrugala, Sandra K. Johnston, Paula Whitmire, Lee Curtin, Eduardo Carrasco, Spencer Bayless, Andrea Hawkins-Daarud, Julia Lorence, Lei Wang, Bernard R. Bendok, Christine Paula Lewis-de los Angeles, Cassandra R. Rickertsen, Kristin R. Swanson, Robert A. Gatenby, Kathleen M. Egan, Sujay A. Vora, Leland S. Hu, Kamala Clark-Swanson, Christina Corpuz, Joshua B. Rubin, Noah C. Peeri, Luis F. Gonzalez-Cuyar, and Gustavo De Leon

Subjects
Male, Oncology, Cancer Research, 0302 clinical medicine, Surgical oncology, Clinical information, Child, Aged, 80 and over, Tumor size, Brain Neoplasms, Middle Aged, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Prognosis, Magnetic Resonance Imaging, Sex specific, Survival Rate, 030220 oncology & carcinogenesis, Female, Mr images, Research Article, Adult, medicine.medical_specialty, Adolescent, Neuroimaging, lcsh:RC254-282, 03 medical and health sciences, Young Adult, Sex Factors, Internal medicine, Image Interpretation, Computer-Assisted, Sex differences, Genetics, medicine, Overall survival, Humans, Tumor growth, Biomathematical models, Aged, Retrospective Studies, Primary Glioblastoma, business.industry, Models, Theoretical, medicine.disease, Mr imaging, Glioblastoma, business, 030217 neurology & neurosurgery, Follow-Up Studies
Abstract

BackgroundSex is recognized as a significant determinant of outcome among glioblastoma patients, but the relative prognostic importance of glioblastoma features has not been thoroughly explored for sex differences.MethodsCombining multi-modal MR images, biomathematical models, and patient clinical information, this investigation assesses which pretreatment variables have a sex-specific impact on the survival of glioblastoma patients. Pretreatment MR images of 494 glioblastoma patients (299 males and 195 females) were segmented to quantify tumor volumes. Cox proportional hazard (CPH) models and Student’s t-tests were used to assess which variables were associated with survival outcomes.ResultsAmong males, tumor (T1Gd) radius was a predictor of overall survival (HR=1.027, p=0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR=1.011, pConclusionDespite similar distributions of the MR imaging parameters between males and females, there was a sex-specific difference in how these parameters related to outcomes, which emphasizes the importance of considering sex as a biological factor when determining patient prognosis and treatment approach.

Published
2020
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