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The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.

We report the implantation of patient-derived midbrain dopaminergic progenitor cells, differentiated in vitro from autologous induced pluripotent stem cells (iPSCs), in a patient with idiopathic Parkinson's disease. The patient-specific progenitor cells were produced under Good Manufacturing Practice conditions and characterized as having the phenotypic properties of substantia nigra pars compacta neurons; testing in a humanized mouse model (involving peripheral-blood mononuclear cells) indicated an absence of immunogenicity to these cells. The cells were implanted into the putamen (left hemisphere followed by right hemisphere, 6 months apart) of a patient with Parkinson's disease, without the need for immunosuppression. Positron-emission tomography with the use of fluorine-18-L-dihydroxyphenylalanine suggested graft survival. Clinical measures of symptoms of Parkinson's disease after surgery stabilized or improved at 18 to 24 months after implantation. (Funded by the National Institutes of Health and others.).

The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data.

Electrocorticography (ECoG) is becoming more prevalent due to improvements in fabrication and recording technology as well as its ease of implantation compared to intracortical electrophysiology, larger cortical coverage, and potential advantages for use in long term chronic implantation. Given the flexibility in the design of ECoG grids, which is only increasing, it remains an open question what geometry of the electrodes is optimal for an application. Conductive polymer, PEDOT:PSS, coated microelectrodes have an advantage that they can be made very small without losing low impedance. This makes them suitable for evaluating the required granularity of ECoG recording in humans and experimental animals. We used two-dimensional (2D) micro-ECoG grids to record intra-operatively in humans and during acute implantations in mouse with separation distance between neighboring electrodes (i.e., pitch) of 0.4 mm and 0.2/0.25 mm respectively. To assess the spatial properties of the signals, we used the average correlation between electrodes as a function of the pitch. In agreement with prior studies, we find a strong frequency dependence in the spatial scale of correlation. By applying independent component analysis (ICA), we find that the spatial pattern of correlation is largely due to contributions from multiple spatially extended, time-locked sources present at any given time. Our analysis indicates the presence of spatially structured activity down to the sub-millimeter spatial scale in ECoG despite the effects of volume conduction, justifying the use of dense micro-ECoG grids.

The physiologic processes underlying MRI contrast enhancement in glioblastoma patients remain poorly understood. MRIs of 148 glioblastoma subjects from The Cancer Imaging Archive were segmented using Iterative Probabilistic Voxel Labeling (IPVL). Three aspects of contrast enhancement (CE) were parametrized: the mean intensity of all CE voxels (CEi), the intensity heterogeneity in CE (CEh), and volumetric ratio of CE to necrosis (CEr). Associations between these parameters and patterns of gene expression were analyzed using DAVID functional enrichment analysis. Glioma CpG island methylator phenotype (G-CIMP) glioblastomas were poorly enhancing. Otherwise, no differences in CE parameters were found between proneural, neural, mesenchymal, and classical glioblastomas. High CEi was associated with expression of genes that mediate inflammatory responses. High CEh was associated with increased expression of genes that regulate remodeling of extracellular matrix (ECM) and endothelial permeability. High CEr was associated with increased expression of genes that mediate cellular response to stressful metabolic states, including hypoxia and starvation. Our results indicate that CE in glioblastoma is associated with distinct biological processes involved in inflammatory response and tissue hypoxia. Integrative analysis of these CE parameters may yield meaningful information pertaining to the biologic state of glioblastomas and guide future therapeutic paradigms.

BackgroundCerebrospinal fluid (CSF) leak is a well-recognized complication after surgical resection of vestibular schwannomas and is associated with a number of secondary complications, including readmission and meningitis.ObjectiveTo identify risk factors for and timing of 30-d readmission with CSF leak.MethodsPatients who had undergone surgical resection of a vestibular schwannoma from 1995 to 2010 were identified in the California Office of Statewide Health Planning and Development database. The most common admission diagnoses were identified by International Classification of Disease, ninth Revision, diagnosis codes, and predictors of readmission with CSF leak were determined using logistic regression.ResultsA total of 6820 patients were identified. CSF leak, though a relatively uncommon cause of admission after discharge (3.52% of all patients), was implicated in nearly half of 490 readmissions (48.98%). Significant independent predictors of readmission with CSF leak were male sex (odds ratio [OR] 1.72, 95% confidence interval [CI] 1.32-2.25), first admission at a teaching hospital (OR 3.32, 95% CI 1.06-10.39), CSF leak during first admission (OR 1.84, 95% CI 1.33-2.55), obesity during first admission (OR 2.10, 95% CI 1.20-3.66), and case volume of first admission hospital (OR of log case volume 0.82, 95% CI 0.70-0.95). Median time to readmission was 6 d from hospital discharge.ConclusionThis study has quantified CSF leak as an important contributor to nearly half of all readmissions following vestibular schwannoma surgery. We propose that surgeons should focus on technical factors that may reduce CSF leakage and take advantage of potential screening strategies for the detection of CSF leakage prior to first admission discharge.

Mass effect has demonstrated prognostic significance for glioblastoma, but is poorly quantified. Here we define and characterize a novel neuroimaging parameter, lateral ventricle displacement (LVd), which quantifies mass effect in glioblastoma patients. LVd is defined as the magnitude of displacement from the center of mass of the lateral ventricle volume in glioblastoma patients relative to that a normal reference brain. Pre-operative MR images from 214 glioblastoma patients from The Cancer Imaging Archive (TCIA) were segmented using iterative probabilistic voxel labeling (IPVL). LVd, contrast enhancing volumes (CEV) and FLAIR hyper-intensity volumes (FHV) were determined. Associations with patient survival and tumor genomics were investigated using data from The Cancer Genome Atlas (TCGA). Glioblastoma patients had significantly higher LVd relative to patients without brain tumors. The variance of LVd was not explained by tumor volume, as defined by CEV or FLAIR. LVd was robustly associated with glioblastoma survival in Cox models which accounted for both age and Karnofsky's Performance Scale (KPS) (p = 0.006). Glioblastomas with higher LVd demonstrated increased expression of genes associated with tumor proliferation and decreased expression of genes associated with tumor invasion. Our results suggest LVd is a quantitative measure of glioblastoma mass effect and a prognostic imaging biomarker.

BackgroundRNAs within extracellular vesicles (EVs) have potential as diagnostic biomarkers for patients with cancer and are identified in a variety of biofluids. Glioblastomas (GBMs) release EVs containing RNA into cerebrospinal fluid (CSF). Here we describe a multi-institutional study of RNA extracted from CSF-derived EVs of GBM patients to detect the presence of tumor-associated amplifications and mutations in epidermal growth factor receptor (EGFR).MethodsCSF and matching tumor tissue were obtained from patients undergoing resection of GBMs. We determined wild-type (wt)EGFR DNA copy number amplification, as well as wtEGFR and EGFR variant (v)III RNA expression in tumor samples. We also characterized wtEGFR and EGFRvIII RNA expression in CSF-derived EVs.ResultsEGFRvIII-positive tumors had significantly greater wtEGFR DNA amplification (P = 0.02) and RNA expression (P = 0.03), and EGFRvIII-positive CSF-derived EVs had significantly more wtEGFR RNA expression (P = 0.004). EGFRvIII was detected in CSF-derived EVs for 14 of the 23 EGFRvIII tissue-positive GBM patients. Conversely, only one of the 48 EGFRvIII tissue-negative patients had the EGFRvIII mutation detected in their CSF-derived EVs. These results yield a sensitivity of 61% and a specificity of 98% for the utility of CSF-derived EVs to detect an EGFRvIII-positive GBM.ConclusionOur results demonstrate CSF-derived EVs contain RNA signatures reflective of the underlying molecular genetic status of GBMs in terms of wtEGFR expression and EGFRvIII status. The high specificity of the CSF-derived EV diagnostic test gives us an accurate determination of positive EGFRvIII tumor status and is essentially a less invasive "liquid biopsy" that might direct mutation-specific therapies for GBMs.

To develop a cerebrospinal fluid (CSF) miRNA diagnostic biomarker for glioblastoma.Glioblastoma tissue and matched CSF from the same patient (obtained prior to tumor manipulation) were profiled by TaqMan OpenArray® Human MicroRNA Panel. CSF miRNA profiles from glioblastoma patients and controls were created from three discovery cohorts and confirmed in two validation cohorts.miRNA profiles from clinical CSF correlated with those found in glioblastoma tissues. Comparison of CSF miRNA profiles between glioblastoma patients and non-brain tumor patients yielded a tumor "signature" consisting of nine miRNAs. The "signature" correlated with glioblastoma tumor volume (p=0.008). When prospectively applied to cisternal CSF, the sensitivity and specificity of the 'signature' for glioblastoma detection were 67% and 80%, respectively. For lumbar CSF, the sensitivity and specificity of the signature were 28% and 95%, respectively. Comparable results were obtained from analyses of CSF extracellular vesicles (EVs) and crude CSF.We report a CSF miRNA signature as a "liquid biopsy" diagnostic platform for glioblastoma.

We examined the extracellular vesicle (EV) and RNA composition of pooled normal cerebrospinal fluid (CSF) samples and CSF from five major neurological disorders: Alzheimer's disease (AD), Parkinson's disease (PD), low-grade glioma (LGG), glioblastoma multiforme (GBM), and subarachnoid haemorrhage (SAH), representing neurodegenerative disease, cancer, and severe acute brain injury. We evaluated: (I) size and quantity of EVs by nanoparticle tracking analysis (NTA) and vesicle flow cytometry (VFC), (II) RNA yield and purity using four RNA isolation kits, (III) replication of RNA yields within and between laboratories, and (IV) composition of total and EV RNAs by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and RNA sequencing (RNASeq). The CSF contained ~106 EVs/μL by NTA and VFC. Brain tumour and SAH CSF contained more EVs and RNA relative to normal, AD, and PD. RT-qPCR and RNASeq identified disease-related populations of microRNAs and messenger RNAs (mRNAs) relative to normal CSF, in both total and EV fractions. This work presents relevant measures selected to inform the design of subsequent replicative CSF studies. The range of neurological diseases highlights variations in total and EV RNA content due to disease or collection site, revealing critical considerations guiding the selection of appropriate approaches and controls for CSF studies.

IntroductionThe subventricular zone (SVZ) has been implicated in the pathogenesis of glioblastoma. Whether molecular subtypes of glioblastoma arise from unique niches of the brain relative to the SVZ remains largely unknown. Here, we tested whether these subtypes of glioblastoma occupy distinct regions of the cerebrum and examined glioblastoma localization in relation to the SVZ.MethodsPre-operative MR images from 217 glioblastoma patients from The Cancer Imaging Archive were segmented automatically into contrast enhancing (CE) tumor volumes using Iterative Probabilistic Voxel Labeling (IPVL). Probabilistic maps of tumor location were generated for each subtype and distances were calculated from the centroid of CE tumor volumes to the SVZ. Glioblastomas that arose in a Genetically Modified Murine Model (GEMM) model were also analyzed with regard to SVZ distance and molecular subtype.ResultsClassical and mesenchymal glioblastomas were more diffusely distributed and located farther from the SVZ. In contrast, proneural and neural glioblastomas were more likely to be located in closer proximity to the SVZ. Moreover, in a GFAP-CreER; PtenloxP/loxP; Trp53loxP/loxP; Rb1loxP/loxP; Rbl1-/- GEMM model of glioblastoma where tumor can spontaneously arise in different regions of the cerebrum, tumors that arose near the SVZ were more likely to be of proneural subtype (p < 0.0001).ConclusionsGlioblastoma subtypes occupy different regions of the brain and vary in proximity to the SVZ. These findings harbor implications pertaining to the pathogenesis of glioblastoma subtypes.

BackgroundTumor specific genetic material can be detected in extracellular vesicles (EVs) isolated from blood, cerebrospinal fluid (CSF), and other biofluids of glioblastoma patients. As such, EVs have emerged as a promising platform for biomarker discovery. However, the optimal procedure to transport clinical EV samples remains poorly characterized.MethodsWe examined the stability of EVs isolated from CSF of glioblastoma patients that were stored under different conditions. EV recovery was determined by Nanoparticle tracking analysis, and qRT-PCR was performed to determine the levels of miRNAs.ResultsCSF EVs that were lyophilized and stored at room temperature (RT) for seven days exhibited a 37-43% reduction in EV number. This reduction was further associated with decreased abundance of representative miRNAs. In contrast, the EV number and morphology remained largely unchanged if CSF were stored at RT. Total RNA and representative miRNA levels were well-preserved under this condition for up to seven days. A single cycle of freezing and thawing did not significantly alter EV number, morphology, RNA content, or miRNA levels. However, incremental decreases in these parameters were observed after two cycles of freezing and thawing.ConclusionsThese results suggest that EVs in CSF are stable at RT for at least seven days. Repeated cycles of freezing/thawing should be avoided to minimize experimental artifacts.

IntroductionLevels of Alzheimer's disease (AD)-related proteins in plasma neuronal derived exosomes (NDEs) were quantified to identify biomarkers for prediction and staging of mild cognitive impairment (MCI) and AD.MethodsPlasma exosomes were extracted, precipitated, and enriched for neuronal source by anti-L1CAM antibody absorption. NDEs were characterized by size (Nanosight) and shape (TEM) and extracted NDE protein biomarkers were quantified by ELISAs. Plasma NDE cargo was injected into normal mice, and results were characterized by immunohistochemistry to determine pathogenic potential.ResultsPlasma NDE levels of P-T181-tau, P-S396-tau, and Aβ1-42 were significantly higher, whereas those of neurogranin (NRGN) and the repressor element 1-silencing transcription factor (REST) were significantly lower in AD and MCI converting to AD (ADC) patients compared to cognitively normal controls (CNC) subjects and stable MCI patients. Mice injected with plasma NDEs from ADC patients displayed increased P-tau (PHF-1 antibody)-positive cells in the CA1 region of the hippocampus compared to plasma NDEs from CNC and stable MCI patients.ConclusionsAbnormal plasma NDE levels of P-tau, Aβ1-42, NRGN, and REST accurately predict conversion of MCI to AD dementia. Plasma NDEs from demented patients seeded tau aggregation and induced AD-like neuropathology in normal mouse CNS.

IntroductionDiffusion Weighted Imaging (DWI), which is based on Echo Planar Imaging (EPI) protocols, is becoming increasingly important for neurosurgical applications. However, its use in this context is limited in part by significant spatial distortion inherent to EPI.MethodWe evaluated an efficient algorithm for EPI distortion correction (EPIC) across 814 DWI scans from 250 brain tumor patients and quantified the magnitude of geometric distortion for whole brain and multiple brain regions.ResultsEvaluation of the algorithm's performance revealed significantly higher mutual information between T1-weighted pre-contrast images and corrected b = 0 images than the uncorrected b = 0 images (p < 0.001). The distortion magnitude across all voxels revealed a median EPI distortion effect of 2.1 mm, ranging from 1.2 mm to 5.9 mm, the 5th and 95th percentile, respectively. Regions adjacent to bone-air interfaces, such as the orbitofrontal cortex, temporal poles, and brain stem, were the regions most severely affected by DWI distortion.ConclusionUsing EPIC to estimate the degree of distortion in 814 DWI brain tumor images enabled the creation of a topographic atlas of DWI distortion across the brain. The degree of displacement of tumors boundaries in uncorrected images is severe but can be corrected for using EPIC. Our results support the use of distortion correction to ensure accurate and careful application of DWI to neurosurgical practice.

Parkinson's disease (PD) is a neurodegenerativa disorder associated with loss of striatal dopamine, secondary to degeneration of midbrain dopamine (mDA) neurons in the substantia nigra, rendering cell transplantation a promising therapeutic strategy. To establish human induced pluripotent stem cell-based (hiPSC-based) autologous cell therapy, we report a platform of core techniques for the production of mDA progenitors as a safe and effective therapeutic product. First, by combining metabolism-regulating microRNAs with reprogramming factors, we developed a method to more efficiently generate clinical-grade iPSCs, as evidenced by genomic integrity and unbiased pluripotent potential. Second, we established a 'spotting'-based in vitro differentiation methodology to generate functional and healthy mDA cells in a scalable manner. Third, we developed a chemical method that safely eliminates undifferentiated cells from the final product. Dopaminergic cells thus express high levels of characteristic mDA markers, produce and secrete dopamine, and exhibit electrophysiological features typical of mDA cells. Transplantation of these cells into rodent models of PD robustly restores motor function and reinnervates host brain, while showing no evidence of tumor formation or redistribution of the implanted cells. We propose that this platform is suitable for the successful implementation of human personalized autologous cell therapy for PD., Introduction Parkinson's disease (PD), characterized by both motor and nonmotor system pathology, is a common neurodegenerative disorder affecting about 1% of the population over age 60. Its prevalence presents an [...]

Genomic heterogeneity is characteristic of glioblastoma (GBM). In many GBMs, the EGF receptor gene (EGFR) is amplified and may be truncated to generate a constitutively active form of the receptor called EGFRvIII. EGFR gene amplification and EGFRvIII are associated with GBM progression, even when only a small fraction of the tumor cells express EGFRvIII. In this study, we show that EGFRvIII-positive GBM cells express significantly increased levels of cellular urokinase receptor (uPAR) and release increased amounts of soluble uPAR (suPAR). When mice were xenografted with human EGFRvIII-expressing GBM cells, tumor-derived suPAR was detected in the plasma, and the level was significantly increased compared with that detected in plasma samples from control mice xenografted with EGFRvIII-negative GBM cells. suPAR also was increased in plasma from patients with EGFRvIII-positive GBMs. Purified suPAR was biologically active when added to cultures of EGFRvIII-negative GBM cells, activating cell signaling and promoting cell migration and invasion. suPAR did not significantly stimulate cell signaling or migration of EGFRvIII-positive cells, probably because cell signaling was already substantially activated in these cells. The activities of suPAR were replicated by conditioned medium (CM) from EGFRvIII-positive GBM cells. When the CM was preincubated with uPAR-neutralizing antibody or when uPAR gene expression was silenced in cells used to prepare CM, the activity of the CM was significantly attenuated. These results suggest that suPAR may function as an important paracrine signaling factor in EGFRvIII-positive GBMs, inducing an aggressive phenotype in tumor cells that are EGFRvIII-negative.

Analysis of extracellular vesicles (EVs) derived from plasma or cerebrospinal fluid (CSF) has emerged as a promising biomarker platform for therapeutic monitoring in glioblastoma patients. However, the contents of the various subpopulations of EVs in these clinical specimens remain poorly defined. Here we characterize the relative abundance of miRNA species in EVs derived from the serum and cerebrospinal fluid of glioblastoma patients. EVs were isolated from glioblastoma cell lines as well as the plasma and CSF of glioblastoma patients. The microvesicle subpopulation was isolated by pelleting at 10,000×g for 30 min after cellular debris was cleared by a 2000×g (20 min) spin. The exosome subpopulation was isolated by pelleting the microvesicle supernatant at 120,000×g (120 min). qRT-PCR was performed to examine the distribution of miR-21, miR-103, miR-24, and miR-125. Global miRNA profiling was performed in select glioblastoma CSF samples. In plasma and cell line derived EVs, the relative abundance of miRNAs in exosome and microvesicles were highly variable. In some specimens, the majority of the miRNA species were found in exosomes while in other, they were found in microvesicles. In contrast, CSF exosomes were enriched for miRNAs relative to CSF microvesicles. In CSF, there is an average of one molecule of miRNA per 150-25,000 EVs. Most EVs derived from clinical biofluids are devoid of miRNA content. The relative distribution of miRNA species in plasma exosomes or microvesicles is unpredictable. In contrast, CSF exosomes are the major EV compartment that harbor miRNAs.

We identified a synthetic lethality between PLK1 silencing and the expression of an oncogenic Epidermal Growth Factor Receptor, EGFRvIII. PLK1 promoted homologous recombination (HR), mitigating EGFRvIII induced oncogenic stress resulting from DNA damage accumulation. Accordingly, PLK1 inhibition enhanced the cytotoxic effects of the DNA damaging agent, temozolomide (TMZ). This effect was significantly more pronounced in an Ink4a/Arf(-/-) EGFRvIII glioblastoma model relative to an Ink4a/Arf(-/-) PDGF-β model. The tumoricidal and TMZ-sensitizing effects of BI2536 were uniformly observed across Ink4a/Arf(-/-) EGFRvIII glioblastoma clones that acquired independent resistance mechanisms to EGFR inhibitors, suggesting these resistant clones retain oncogenic stress that required PLK1 compensation. Although BI2536 significantly augmented the anti-neoplastic effect of EGFR inhibitors in the Ink4a/Arf(-/-) EGFRvIII model, durable response was not achieved until TMZ was added. Our results suggest that optimal therapeutic effect against glioblastomas requires a "multi-orthogonal" combination tailored to the molecular physiology associated with the target cancer genome.

Ten ongoing studies designed to test the possibility that extracellular RNAs may serve as biomarkers in human disease are described. These studies, funded by the NIH Common Fund Extracellular RNA Communication Program, examine diverse extracellular body fluids, including plasma, serum, urine and cerebrospinal fluid. The disorders studied include hepatic and gastric cancer, cardiovascular disease, chronic kidney disease, neurodegenerative disease, brain tumours, intracranial haemorrhage, multiple sclerosis and placental disorders. Progress to date and the plans for future studies are outlined.

The large diversity and volume of extracellular RNA (exRNA) data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a) selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b) retrieval of a data slice from the exRNA Atlas for integrative analysis and (c) interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data.

Extracellular RNAs (exRNAs) have been identified in all tested biofluids and have been associated with a variety of extracellular vesicles, ribonucleoprotein complexes and lipoprotein complexes. Much of the interest in exRNAs lies in the fact that they may serve as signalling molecules between cells, their potential to serve as biomarkers for prediction and diagnosis of disease and the possibility that exRNAs or the extracellular particles that carry them might be used for therapeutic purposes. Among the most significant bottlenecks to progress in this field is the lack of robust and standardized methods for collection and processing of biofluids, separation of different types of exRNA-containing particles and isolation and analysis of exRNAs. The Sample and Assay Standards Working Group of the Extracellular RNA Communication Consortium is a group of laboratories funded by the U.S. National Institutes of Health to develop such methods. In our first joint endeavour, we held a series of conference calls and in-person meetings to survey the methods used among our members, placed them in the context of the current literature and used our findings to identify areas in which the identification of robust methodologies would promote rapid advancements in the exRNA field.

Diffusion-weighted imaging (DWI) has been at the forefront of cancer imaging since the early 2000s. Before its application in clinical oncology, this powerful technique had already achieved widespread recognition due to its utility in the diagnosis of cerebral infarction. Following this initial success, the ability of DWI to detect inherent tissue contrast began to be exploited in the field of oncology. Although the initial oncologic applications for tumor detection and characterization, assessing treatment response, and predicting survival were primarily in the field of neurooncology, the scope of DWI has since broadened to include oncologic imaging of the prostate gland, breast, and liver. Despite its growing success and application, misconceptions about the underlying physical basis of the DWI signal exist among researchers and clinicians alike. In this review, we provide a detailed explanation of the biophysical basis of diffusion contrast, emphasizing the difference between hindered and restricted diffusion, and elucidating how diffusion parameters in tissue are derived from the measurements via the diffusion model. We describe one advanced DWI modeling technique, called restriction spectrum imaging (RSI). This technique offers a more direct in vivo measure of tumor cells, due to its ability to distinguish separable pools of water within tissue based on their intrinsic diffusion characteristics. Using RSI as an example, we then highlight the ability of advanced DWI techniques to address key clinical challenges in neurooncology, including improved tumor conspicuity, distinguishing actual response to therapy from pseudoresponse, and delineation of white matter tracts in regions of peritumoral edema. We also discuss how RSI, combined with new methods for correction of spatial distortions inherent in diffusion MRI scans, may enable more precise spatial targeting of lesions, with implications for radiation oncology and surgical planning. See all articles in this Cancer Research section, "Physics in Cancer Research."