1. Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation
- Author
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Daniel S. Marcus, Pamela LaMontagne, Tammie L.S. Benzinger, Jingxia Liu, Maria Rosana Ponisio, Sonika Dahiya, Parinaz Massoumzadeh, Michelle M. Miller-Thomas, Gengsheng Chen, Jonathan McConathy, Gloria J. Guzmán Pérez-Carrillo, Yong Wang, Qing Wang, Amber Salter, Mikhail Milchenko, Joshua S. Shimony, and Keith M. Rich
- Subjects
Stereotactic biopsy ,Biopsy ,Perfusion scanning ,Diagnostic Radiology ,030218 nuclear medicine & medical imaging ,0302 clinical medicine ,Adenocarcinomas ,Edema ,Medicine and Health Sciences ,Brain Mapping ,Multidisciplinary ,medicine.diagnostic_test ,Brain Neoplasms ,Radiology and Imaging ,Physics ,Classical Mechanics ,Glioma ,Middle Aged ,Magnetic Resonance Imaging ,3. Good health ,Oncology ,Physical Sciences ,Medicine ,Female ,medicine.symptom ,Perfusion ,Research Article ,Adult ,Imaging Techniques ,Science ,Brain Morphometry ,Surgical and Invasive Medical Procedures ,Neuroimaging ,Fluid Mechanics ,Research and Analysis Methods ,Continuum Mechanics ,Carcinomas ,03 medical and health sciences ,Malignant Tumors ,Text mining ,Diagnostic Medicine ,Cancer Detection and Diagnosis ,medicine ,Humans ,Effective diffusion coefficient ,business.industry ,Cancers and Neoplasms ,Biology and Life Sciences ,Fluid Dynamics ,Diffusion Magnetic Resonance Imaging ,Neoplasm Grading ,Nuclear medicine ,business ,030217 neurology & neurosurgery ,Neuroscience ,Diffusion MRI - Abstract
ObjectivesPrimary brain tumors are composed of tumor cells, neural/glial tissues, edema, and vasculature tissue. Conventional MRI has a limited ability to evaluate heterogeneous tumor pathologies. We developed a novel diffusion MRI-based method-Heterogeneity Diffusion Imaging (HDI)-to simultaneously detect and characterize multiple tumor pathologies and capillary blood perfusion using a single diffusion MRI scan.MethodsSeven adult patients with primary brain tumors underwent standard-of-care MRI protocols and HDI protocol before planned surgical resection and/or stereotactic biopsy. Twelve tumor sampling sites were identified using a neuronavigational system and recorded for imaging data quantification. Metrics from both protocols were compared between World Health Organization (WHO) II and III tumor groups. Cerebral blood volume (CBV) derived from dynamic susceptibility contrast (DSC) perfusion imaging was also compared with the HDI-derived perfusion fraction.ResultsThe conventional apparent diffusion coefficient did not identify differences between WHO II and III tumor groups. HDI-derived slow hindered diffusion fraction was significantly elevated in the WHO III group as compared with the WHO II group. There was a non-significantly increasing trend of HDI-derived tumor cellularity fraction in the WHO III group, and both HDI-derived perfusion fraction and DSC-derived CBV were found to be significantly higher in the WHO III group. Both HDI-derived perfusion fraction and slow hindered diffusion fraction strongly correlated with DSC-derived CBV. Neither HDI-derived cellularity fraction nor HDI-derived fast hindered diffusion fraction correlated with DSC-derived CBV.ConclusionsConventional apparent diffusion coefficient, which measures averaged pathology properties of brain tumors, has compromised accuracy and specificity. HDI holds great promise to accurately separate and quantify the tumor cell fraction, the tumor cell packing density, edema, and capillary blood perfusion, thereby leading to an improved microenvironment characterization of primary brain tumors. Larger studies will further establish HDI's clinical value and use for facilitating biopsy planning, treatment evaluation, and noninvasive tumor grading.
- Published
- 2019