Post-gadolinium 3-dimensional spatial, surface, and structural characteristics of glioblastomas differentiate pseudoprogression from true tumor progression.

PURPOSE: Pseudoprogression is often indistinguishable from true tumor progression on conventional 2-dimensional (2D) MRI in glioblastoma multiforme (GBM) patients. The aim of this study was to determine the association between post-gadolinium 3-dimensional (3D) characteristics and clinical state in GBM patients. METHODS: Standardized 3D brain MRI studies were performed, and contrast enhancing portions of each tumor were segmented and analyzed, blinded to clinical state, using principal component analysis (PCA), medial axis transformation (MAT), and coverage analysis. Associations between the 3D characteristics of the post-gadolinium enhanced regions and the clinical status of patients were performed. RESULTS: A total of 15 GBM patients [male: 11 (73%); median age (range): 62 years (36-72)] with a median disease duration of 6 months (range 2-24 months) were studied cross-sectionally with 6 (40%) patients identified with tumor progression. Post-gadolinium features corresponding to the group with progressive disease exhibited a more spherical and symmetric shape relative to their stable counterparts (p = 0.005). The predictive value of a more uniformly full post-gadolinium enhanced shell to clinical progression was determined with a sensitivity of 66.7% (95% CI 29.9-92.5), specificity of 100% (54.1-100), and PPV of 100% (p = 0.028, 2-tailed Fisher's exact test). There did not appear to be an association between the thickness of the contrast enhanced shell to clinical state. CONCLUSIONS: The application of 3D technology with post-gadolinium imaging data may inform healthcare providers with new insights into disease states based on spatial, surface, and structural patterns.

Three-Dimensional Lesion Phenotyping and Physiologic Characterization Inform Remyelination Ability in Multiple Sclerosis.

BACKGROUND AND PURPOSE: Multiple sclerosis (MS) clinical management is based upon lesion characterization from 2-dimensional (2D) magnetic resonance imaging (MRI) views. Such views fail to convey the lesion-phenotype (ie, shape and surface texture) complexity, underlying metabolic alterations, and remyelination potential. We utilized a 3-dimensional (3D) lesion phenotyping approach coupled with imaging to study physiologic profiles within and around MS lesions and their impacts on lesion phenotypes. METHODS: Lesions were identified in 3T T2 -FLAIR images and segmented using geodesic active contouring. A calibrated fMRI sequence permitted measurement of cerebral blood flow (CBF), blood-oxygen-level-dependent signal (BOLD), and cerebral metabolic rate of oxygen (CMRO2 ). These metrics were measured within lesions and surrounding tissue in concentric layers exact to the 3D-lesion shape. BOLD slope was calculated as BOLD changes from a lesion to its surrounding perimeters. White matter integrity was measured using diffusion kurtosis imaging. Associations between these metrics and 3D-lesion phenotypes were studied. RESULTS: One hundred nine lesions from 23 MS patients were analyzed. We identified a noninvasive biomarker, BOLD slope, to metabolically characterize lesions. Positive BOLD slope lesions were metabolically active with higher CMRO2 and CBF compared to negative BOLD slope or inactive lesions. Metabolically active lesions with more intact white matter integrity had more symmetrical shapes and more complex surface textures compared to inactive lesions with less intact white matter integrity. CONCLUSION: The association of lesion phenotypes with their metabolic signatures suggests the prospect for translation of such data to clinical management by providing information related to metabolic activity, lesion age, and risk for disease reactivation and self-repair. Our findings also provide a platform for disease surveillance and outcome quantification involving myelin repair therapeutics.

Multiple Sclerosis in the Contemporary Age: Understanding the Millennial Patient with Multiple Sclerosis to Create Next-Generation Care.

The average age of onset of multiple sclerosis (MS) is between 20 and 40 years of age. Therefore, most new patients diagnosed with MS within the next 10 to 15 years will be from the millennial generation, representing those born between 1982 and 2000. Certain preferences and trends of this contemporary generation will present new challenges to the MS physician and effective MS care. By first understanding these challenges, relevant and successful solutions can be created to craft a system of care that best benefits the millennial patient with MS.

Precision medicine for multiple sclerosis promotes preventative medicine.

Multiple sclerosis (MS) is a chronic, lifelong disease, currently without a cure that is responsible for significant neurological injury in young adults. Precision medicine for MS aims to provide a more exacting and refined approach toward management by providing recommendations based on disease subtype, clinical status, existing radiological data, para-clinical data, and other biological markers. To achieve better outcomes, the three stages of care-diagnosis, treatment, and management-should be optimized. However, as the temporal profile of disease behavior is highly variable in MS, and unlike outcomes from other chronic conditions (i.e., hypertension, diabetes mellitus, etc.), should precision medicine for MS be one that focuses more on disease prevention and lifestyle modifications beyond recommendations for the use of disease-modifying therapies? As scientific advancements continue within the field of neuroimmunology, and until reliable biomarkers that predict disease outcomes are available, success may be better achieved by focusing on modifiable factors to reduce future disability.