AI-assisted 3D analysis of grasping and reaching behavior of squirrel monkeys during recovery from cervical spinal cord injury.

We have previously demonstrated that machine learning-based video analysis, conducted via DeepLabCut, is more sensitive for detecting subtle deficits in hand grasping behavior than traditional end-point performance assessments. This superiority was observed in a nonhuman primate (NHP) model of cervical spinal cord injury, specifically a dorsal column lesion (DCL). The current study aims to further characterize the kinematic aspects of the deficits in hand reaching, grasping, and retrieving behavior from a 3D perspective following a DCL. Squirrel monkeys were trained to retrieve sugar pellets from eight wells, which were located either on a flat plate or a raised tube with varying well depths. This setup was designed to require coordinated finger movements during the task. Immediately after the DCL, the animals exhibited measurable behavioral deficits. These were characterized by significant increases in grasping speed squared and trial completion time, markedly widened movement trajectories of individual fingers, and abnormalities in inter-finger distance and orientation. Increased task difficulty was associated with more pronounced behavioral deficits. By three months post-DCL, video-based measurements indicated no significant recovery, even though global end-point performance had returned to baseline levels. Our findings demonstrate that deprivation of tactile information results in impaired dexterous hand behavior involving coordinated finger movements, and the impairment is sustained for 20 weeks. This spinal cord injury (SCI) model, along with DeepLapCut analysis, provides a valuable platform for separately evaluating sensory and motor functions and their contributions to dexterous hand behavior and may be used for evaluating therapeutic interventions using more sensitive behavioral outcome readouts.

Joint estimation of compartment-specific T2 relaxation and tumor microstructure using multi-TE IMPULSED MRI.

PURPOSE: This study aims to assess how T2 heterogeneity biases IMPULSED-derived metrics of tissue microstructure in solid tumors and evaluate the potential of estimating multi-compartmental T2 and microstructural parameters simultaneously. METHODS: This study quantifies the impact of T2 relaxation on IMPULSED-derived microstructural parameters using computer simulations and in vivo multi-TE IMPULSED MRI in five tumor models, including brain, breast, prostate, melanoma, and colon cancer. A comprehensive T2 + IMPULSED method was developed to fit multi-compartmental T2 and microstructural parameters simultaneously. A Bayesian model selection approach was carried out voxel-wisely to determine if the T2 heterogeneity needs to be included in IMPULSED MRI in cancer. RESULTS: Simulations suggest that T2 heterogeneity has a minor effect on the estimation of d in tissues with intermediate or high cell density, but significantly biases the estimation of v in $$ {v}_{in} $$ with low cell density. For the in vivo animal experiments, all IMPULSED metrics except v in $$ {v}_{in} $$ are statistically independent on TE. For B16 tumors, the IMPULSED-derived v in $$ {v}_{in} $$ exhibited a notable increase with longer TEs. For MDA-MB-231 tumors, IMPULSED-derived v in $$ {v}_{in} $$ showed a significant increase with increasing TEs. The T2 + IMPULSED-derived T 2 in $$ {T}_2^{in} $$ of all five tumor models are consistently smaller than T 2 ex $$ {T}_2^{ex} $$ . CONCLUSIONS: The findings from this study highlight two key observations: (i) TE has a negligible impact on IMPULSED-derived cell sizes, and (ii) the TE-dependence of IMPULSED-derived intracellular volume fractions used in T2 + IMPULSED modeling to estimate T 2 in $$ {T}_2^{in} $$ and T 2 ex $$ {T}_2^{ex} $$ . These insights contribute to the ongoing development and refinement of non-invasive MRI techniques for measuring cell sizes.

Radiofrequency-transparent local B0 shimming coils using float traps.

PURPOSE: Static field (B0) inhomogeneities present a major challenge in high-field MRI. Multicoil shimming using independent, local, direct-current (DC) shim coils has emerged as a powerful and flexible technique to address this issue. However, many-turn DC coils can lead to significant mutual coupling with radiofrequency (RF) coils, causing transmit field (B1 +) distortions and signal-to-noise ratio degradation. METHODS: We introduce an innovative RF-transparent DC coil that performs B0 shimming while minimizing RF performance impact. The design incorporates float traps to maintain high RF impedance, allowing flexible placement relative to the RF coil without compromising signal-to-noise ratio or affecting B1 +. We fabricated square-shaped DC coils with float traps for 3T MRI and compared them with conventional DC coils. To demonstrate high ΔB0/Amp efficiency, we conducted a B0 shimming experiment around a metal hip implant. RESULTS: Bench tests and MRI experimental results demonstrated that the RF-transparent DC coil effectively minimized RF interference, preserved signal-to-noise ratio, and maintained B1 +, even when placed near the RF receive coil. Additionally, the DC coil significantly improved B0 homogeneity near metal implants and substantially reduced image distortion. CONCLUSION: The RF-transparent DC coil offers a flexible, effective solution for managing B0 inhomogeneities, paving the way for integrating multiturn DC coils in clinical MRI settings without extensive hardware modifications.

Reductions in the white-gray functional connectome in preclinical Alzheimer's disease and their associations with amyloid and cognition.

BACKGROUND: The magnitudes and patterns of alterations of the white-gray matter (WM-GM) functional connectome in preclinical Alzheimer's disease (AD), and their associations with amyloid and cognition, remain unclear. METHODS: We compared regional WM-GM functional connectivity (FC) and network properties in subjects with preclinical AD (or AD dementia) and controls (total n = 344). Their associations with positron emission tomography AV45-measured amyloid beta (Aß) load and modified Preclinical Alzheimer Cognitive Composite (mPACC) scores were examined. RESULTS: Preclinical AD subjects showed lower FC in specific WM-GM pairs and reduced segregation of control, dorsal attention, and somatomotor networks. A major portion of the reduced FC and network segregations were linked to elevated Aß. Reduced FC of one WM-GM pair correlated with impaired mPACC. AD dementia exhibited broader reductions and stronger associations. DISCUSSION: The WM-GM functional connectome undergoes regional and systemic dysfunctions as early as in the preclinical stage, correlating with amyloid deposition and predicting cognitive impairment. HIGHLIGHTS: Preclinical Alzheimer's disease (AD) subjects showed lower functional connectivity in specific white-gray matter (WM-GM) pairs and reduced segregations of control, dorsal attention, and somatomotor networks. A major portion of the reduced connectivity and network segregations were linked to elevated amyloid beta load. Only one WM-GM pair's reduced connectivity was linearly correlated with impaired cognitive composite scores. AD dementia showed more extensive reductions in connectivity, network integration, and segregation, with stronger associations with amyloid elevation and cognitive impairment. The WM-GM functional connectome offers a distinct perspective for understanding changes in brain functional architecture throughout the AD continuum.

Layer-specific BOLD effects in gradient and spin-echo acquisitions in somatosensory cortex.

PURPOSE: Previous studies have shown varied BOLD signals with gradient echo (GE) across cortical depth. To interpret these variations, and understand the effects of vascular geometry and size, the magnitudes and layer distributions of GE and spin-echo (SE) BOLD functional MRI signals were compared in the somatosensory cortex of squirrel monkeys during tactile stimulation and in a resting state at high spatial resolution and high field. METHODS: A block-design stimulation was used to identify tactile-evoked activation signals in somatosensory Areas 3b and 1. Layer-specific connectivities were calculated using resting-state data. Signal power spectra were compared by depth and pulse sequence. The measured ratios of transverse relaxation rate changes were compared with Anderson and Weiss's model. RESULTS: SE signals showed a 26% lower percentage signal change during tactile stimulation compared with GE, along with a slower time course. SE signals remained consistent but weaker in lower layers, whereas GE signals decreased with cortical depth. This pattern extended to resting-state power spectra. Resting-state functional connectivity indicated larger connectivity between the top layers of Area 3b and Area 1 for GE, with minimal changes for SE. Comparisons with theory suggest vessel diameters ranging from 19.4 to 9 microns are responsible for BOLD effects across cortical layers at 9.4 T. CONCLUSION: These results provide further evidence that at high field, SE BOLD signals are relatively free of contributions from sources other than microvascular changes in response to neural activity, whereas GE signals, even in the superficial layers, are not dominated by very large vessels.

White matter engagement in brain networks assessed by integration of functional and structural connectivity.

Current models of brain networks may potentially be improved by integrating our knowledge of structural connections, within and between circuits, with metrics of functional interactions between network nodes. The former may be obtained from diffusion MRI of white matter (WM), while the latter may be derived by measuring correlations between resting state BOLD signals from pairs of gray matter (GM) regions. From inspection of diffusion MRI data, it is clear that each WM voxel within a 3D image array may be traversed by multiple WM structural tracts, each of which connects a pair of GM nodes. We hypothesized that by appropriately weighting and then integrating the functional connectivity of each such connected pair, the overall engagement of any WM voxel in brain functions could be evaluated. This model introduces a structural constraint to earlier studies of WM engagement and addresses some limitations of previous efforts to relate structure and function. Using concepts derived from graph theory, we obtained spatial maps of WM engagement which highlight WM regions critical for efficient communications across the brain. The distributions of WM engagement are highly reproducible across subjects and depict a notable interdependence between the distribution of GM activities and the detailed organization of WM. Additionally, we provide evidence that the engagement varies over time and shows significant differences between genders. These findings suggest the potential of WM engagement as a measure of the integrity of normal brain functions and as a biomarker for neurological and cognitive disorders.

Identification of functional white matter networks in BOLD fMRI.

White matter signals in resting state blood oxygen level dependent functional magnetic resonance (BOLD-fMRI) have been largely discounted, yet there is growing evidence that these signals are indicative of brain activity. Understanding how these white matter signals capture function can provide insight into brain physiology. Moreover, functional signals could potentially be used as early markers for neurological changes, such as in Alzheimer's Disease. To investigate white matter brain networks, we leveraged the OASIS-3 dataset to extract white matter signals from resting state BOLD-FMRI data on 711 subjects. The imaging was longitudinal with a total of 2,026 images. Hierarchical clustering was performed to investigate clusters of voxel-level correlations on the timeseries data. The stability of clusters was measured with the average Dice coefficients on two different cross fold validations. The first validated the stability between scans, and the second validated the stability between populations. Functional clusters at hierarchical levels 4, 9, 13, 18, and 24 had local maximum stability, suggesting better clustered white matter. In comparison with JHU-DTI-SS Type-I Atlas defined regions, clusters at lower hierarchical levels identified well-defined anatomical lobes. At higher hierarchical levels, functional clusters mapped motor and memory functional regions, identifying 50.00%, 20.00%, 27.27%, and 35.14% of the frontal, occipital, parietal, and temporal lobe regions respectively.

Restriction-induced time-dependent transcytolemmal water exchange: Revisiting the Kӓrger exchange model.

The Kӓrger model and its derivatives have been widely used to incorporate transcytolemmal water exchange rate, an essential characteristic of living cells, into analyses of diffusion MRI (dMRI) signals from tissues. The Kӓrger model consists of two homogeneous exchanging components coupled by an exchange rate constant and assumes measurements are made with sufficiently long diffusion time and slow water exchange. Despite successful applications, it remains unclear whether these assumptions are generally valid for practical dMRI sequences and biological tissues. In particular, barrier-induced restrictions to diffusion produce inhomogeneous magnetization distributions in relatively large-sized compartments such as cancer cells, violating the above assumptions. The effects of this inhomogeneity are usually overlooked. We performed computer simulations to quantify how restriction effects, which in images produce edge enhancements at compartment boundaries, influence different variants of the Kӓrger-model. The results show that the edge enhancement effect will produce larger, time-dependent estimates of exchange rates in e.g., tumors with relatively large cell sizes (>10 µm), resulting in overestimations of water exchange as previously reported. Moreover, stronger diffusion gradients, longer diffusion gradient durations, and larger cell sizes, all cause more pronounced edge enhancement effects. This helps us to better understand the feasibility of the Kärger model in estimating water exchange in different tissue types and provides useful guidance on signal acquisition methods that may mitigate the edge enhancement effect. This work also indicates the need to correct the overestimated transcytolemmal water exchange rates obtained assuming the Kärger-model.

Functional correlation tensors in brain white matter and the effects of normal aging.

Resting state correlations between blood oxygenation level dependent (BOLD) MRI signals from voxels in white matter (WM) are demonstrably anisotropic, so that functional correlation tensors (FCT) may be used to quantify the underlying microstructure of BOLD effects in WM tracts. However, the overall spatial distribution of FCTs and their metrics in specific populations has not yet been established, and the factors that affect their precise arrangements remain unclear. Changes in WM occur with normal aging, and these may be expected to affect FCTs. We hypothesized that FCTs exhibit a characteristic spatial pattern and may show systematic changes with aging or other factors. Here we report our analyses of the FCT characteristics of fMRI images of a large cohort of 461 cognitively normal subjects (190 females, 271 males) sourced from the Open Access Series of Imaging Studies (OASIS), with age distributions of 42 y/o - 95 y/o. Group averages and statistics of FCT indices, including axial functional correlations, radial functional correlations, mean functional correlations and fractional anisotropy, were quantified in WM bundles defined by the JHU ICBM-DTI-81 WM atlas. In addition, their variations with normal aging were examined. The results revealed a dimorphic distribution of changes in FCT metrics with age, with decreases of the functional correlations in some regions and increases in others. Supplementary analysis revealed that females exhibited significant age effects on a greater number of WM areas, but the interaction between age and sex was not significant. The findings demonstrate the reproducibility of the spatial distribution of FCT metrics and reveal subtle regional changes with age.

Modelling white matter microstructure using diffusion OGSE MRI: Model and analysis choices.

Alterations in white matter (WM) microstructure of the central nervous system have been shown to be pathophysiological presentations of various neurodegenerative disorders. Current methods for measuring such WM features require ex vivo tissue samples analyzed using electron microscopy. Magnetic Resonance Imaging (MRI) diffusion-weighted pulse sequences provide a non-invasive tool for estimating such microstructural features in vivo. The current project investigated the use of two methods of analysis, including the ROI-based (Region of Interest, RBA) and voxel-based analysis (VBA), as well as four mathematical models of WM microstructure, including the ActiveAx Frequency-Independent Extra-Axonal Diffusion (AAI), ActiveAx Frequency-Dependent Extra-Axonal Diffusion (AAD), AxCaliber Frequency-Independent Extra-Axonal Diffusion (ACI), and AxCaliber Frequency-Dependent Extra-Axonal Diffusion (ACD) models. Two mice samples imaged at 7 T and 15.2 T were analyzed. Both the AAI and AAD models provide a single value for each of the fit parameters, including mean effective axon diameter AxD¯, packing fraction fin, intra-cellular and Din and extra-cellular Dex diffusion coefficients, as well as the frequency dependence of Dex, ßex for the AAD model. The ACI and ACD models provide this, in addition to a distribution of axon diameters for a chosen ROI. VBA extends this, providing a parameter value for each voxel within the selected ROI, at the cost of increased computational load and analysis time. Overall, RBA-ACD and VBA-AAD were found to be optimal for parameter fitting to physically relevant values in a reasonable time frame. A full comparison of each combination of RBA and VBA with AAI, AAD, ACI, and ACD is provided to give the reader sufficient information to make an informed decision of which model is best for their own experiments.

Targeting soluble amyloid-beta oligomers with a novel nanobody.

The classical amyloid cascade hypothesis postulates that the aggregation of amyloid plaques and the accumulation of intracellular hyperphosphorylated Tau tangles, together, lead to profound neuronal death. However, emerging research has demonstrated that soluble amyloid-ß oligomers (SAßOs) accumulate early, prior to amyloid plaque formation. SAßOs induce memory impairment and disrupt cognitive function independent of amyloid-ß plaques, and even in the absence of plaque formation. This work describes the development and characterization of a novel anti-SAßO (E3) nanobody generated from an alpaca immunized with SAßO. In-vitro assays and in-vivo studies using 5XFAD mice indicate that the fluorescein (FAM)-labeled E3 nanobody recognizes both SAßOs and amyloid-ß plaques. The E3 nanobody traverses across the blood-brain barrier and binds to amyloid species in the brain of 5XFAD mice. Imaging of mouse brains reveals that SAßO and amyloid-ß plaques are not only different in size, shape, and morphology, but also have a distinct spatial distribution in the brain. SAßOs are associated with neurons, while amyloid plaques reside in the extracellular matrix. The results of this study demonstrate that the SAßO nanobody can serve as a diagnostic agent with potential theragnostic applications in Alzheimer's disease.

Characteristic BOLD signals are detectable in white matter of the spinal cord at rest and after a stimulus.

We report the reliable detection of reproducible patterns of blood-oxygenation-level-dependent (BOLD) MRI signals within the white matter (WM) of the spinal cord during a task and in a resting state. Previous functional MRI studies have shown that BOLD signals are robustly detectable not only in gray matter (GM) in the brain but also in cerebral WM as well as the GM within the spinal cord, but similar signals in WM of the spinal cord have been overlooked. In this study, we detected BOLD signals in the WM of the spinal cord in squirrel monkeys and studied their relationships with the locations and functions of ascending and descending WM tracts. Tactile sensory stimulus -evoked BOLD signal changes were detected in the ascending tracts of the spinal cord using a general-linear model. Power spectral analysis confirmed that the amplitude at the fundamental frequency of the response to a periodic stimulus was significantly higher in the ascending tracts than the descending ones. Independent component analysis of resting-state signals identified coherent fluctuations from eight WM hubs which correspond closely to the known anatomical locations of the major WM tracts. Resting-state analyses showed that the WM hubs exhibited correlated signal fluctuations across spinal cord segments in reproducible patterns that correspond well with the known neurobiological functions of WM tracts in the spinal cord. Overall, these findings provide evidence of a functional organization of intraspinal WM tracts and confirm that they produce hemodynamic responses similar to GM both at baseline and under stimulus conditions.

TARGETING SOLUBLE AMYLOID-BETA OLIGOMERS WITH A NOVEL NANOBODY.

The classical amyloid cascade hypothesis postulates that the aggregation of amyloid plaques and the accumulation of intracellular hyperphosphorylated Tau tangles, together, lead to profound neuronal death. However, emerging research has demonstrated that soluble amyloid-ß oligomers (SAßOs) accumulate early, prior to amyloid plaque formation. SAßOs induce memory impairment and disrupt cognitive function independent of amyloid-ß plaques, and even in the absence of plaque formation. This work describes the development and characterization of a novel anti-SAßO (E3) nanobody generated from an alpaca immunized with SAßO. In-vitro assays and in-vivo studies using 5XFAD mice indicate that the fluorescein (FAM)-labeled E3 nanobody recognizes both SAßOs and amyloid-ß plaques. The E3 nanobody traverses across the blood-brain barrier and binds to amyloid species in the brain of 5XFAD mice. Imaging of mouse brains reveals that SAßO and amyloid-ß plaques are not only different in size, shape, and morphology, but also have a distinct spatial distribution in the brain. SAßOs are associated with neurons, while amyloid plaques reside in the extracellular matrix. The results of this study demonstrate that the SAßO nanobody can serve as a diagnostic agent with potential theragnostic applications in Alzheimer's disease.

Quantification of mediation effects of white matter functional characteristics on cognitive decline in aging.

Cognitive decline with aging involves multifactorial processes, including changes in brain structure and function. This study focuses on the role of white matter functional characteristics, as reflected in blood oxygenation level-dependent signals, in age-related cognitive deterioration. Building on previous research confirming the reproducibility and age-dependence of blood oxygenation level-dependent signals acquired via functional magnetic resonance imaging, we here employ mediation analysis to test if aging affects cognition through white matter blood oxygenation level-dependent signal changes, impacting various cognitive domains and specific white matter regions. We used independent component analysis of resting-state blood oxygenation level-dependent signals to segment white matter into coherent hubs, offering a data-driven view of white matter's functional architecture. Through correlation analysis, we constructed a graph network and derived metrics to quantitatively assess regional functional properties based on resting-state blood oxygenation level-dependent fluctuations. Our analysis identified significant mediators in the age-cognition relationship, indicating that aging differentially influences cognitive functions by altering the functional characteristics of distinct white matter regions. These findings enhance our understanding of the neurobiological basis of cognitive aging, highlighting the critical role of white matter in maintaining cognitive integrity and proposing new approaches to assess interventions targeting cognitive decline in older populations.

Identification of functional white matter networks in BOLD fMRI.

White matter signals in resting state blood oxygen level dependent functional magnetic resonance (BOLD-fMRI) have been largely discounted, yet there is growing evidence that these signals are indicative of brain activity. Understanding how these white matter signals capture function can provide insight into brain physiology. Moreover, functional signals could potentially be used as early markers for neurological changes, such as in Alzheimer's Disease. To investigate white matter brain networks, we leveraged the OASIS-3 dataset to extract white matter signals from resting state BOLD-FMRI data on 711 subjects. The imaging was longitudinal with a total of 2,026 images. Hierarchical clustering was performed to investigate clusters of voxel-level correlations on the timeseries data. The stability of clusters was measured with the average Dice coefficients on two different cross fold validations. The first validated the stability between scans, and the second validated the stability between subject populations. Functional clusters at hierarchical levels 4, 9, 13, 18, and 24 had local maximum stability, suggesting better clustered white matter. In comparison with JHU-DTI-SS Type-I Atlas defined regions, clusters at lower hierarchical levels identified well defined anatomical lobes. At higher hierarchical levels, functional clusters mapped motor and memory functional regions, identifying 50.00%, 20.00%, 27.27%, and 35.14% of the frontal, occipital, parietal, and temporal lobe regions respectively.

Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord.

Diffusion MRI of the spinal cord (SC) is susceptible to geometric distortion caused by field inhomogeneities, and prone to misalignment across time series and signal dropout caused by biological motion. Several modifications of image acquisition and image processing techniques have been introduced to overcome these artifacts, but their specific benefits are largely unproven and warrant further investigations. We aim to evaluate two specific aspects of image acquisition and processing that address image quality in diffusion studies of the spinal cord: susceptibility corrections to reduce geometric distortions, and cardiac triggering to minimize motion artifacts. First, we evaluate 4 distortion preprocessing strategies on 7 datasets of the cervical and lumbar SC and find that while distortion correction techniques increase geometric similarity to structural images, they are largely driven by the high-contrast cerebrospinal fluid, and do not consistently improve the geometry within the cord nor improve white-to-gray matter contrast. We recommend at a minimum to perform bulk-motion correction in preprocessing and posit that improvements/adaptations are needed for spinal cord distortion preprocessing algorithms, which are currently optimized and designed for brain imaging. Second, we design experiments to evaluate the impact of removing cardiac triggering. We show that when triggering is foregone, images are qualitatively similar to triggered sequences, do not have increased prevalence of artifacts, and result in similar diffusion tensor indices with similar reproducibility to triggered acquisitions. When triggering is removed, much shorter acquisitions are possible, which are also qualitatively and quantitatively similar to triggered sequences. We suggest that removing cardiac triggering for cervical SC diffusion can be a reasonable option to save time with minimal sacrifice to image quality.

The missing third dimension-Functional correlations of BOLD signals incorporating white matter.

Correlations between magnetic resonance imaging (MRI) blood oxygenation level-dependent (BOLD) signals from pairs of gray matter areas are used to infer their functional connectivity, but they are unable to describe how white matter is engaged in brain networks. Recently, evidence that BOLD signals in white matter are robustly detectable and are modulated by neural activities has accumulated. We introduce a three-way correlation between BOLD signals from pairs of gray matter volumes (nodes) and white matter bundles (edges) to define the communication connectivity through each white matter bundle. Using MRI images from publicly available databases, we show, for example, that the three-way connectivity is influenced by age. By integrating functional MRI signals from white matter as a third component in network analyses, more comprehensive descriptions of brain function may be obtained.

Assessing White Matter Engagement in Brain Networks through Functional and Structural Connectivity Mapping.

Understanding the intricate interplay between gray matter (GM) and white matter (WM) is crucial for deciphering the complex activities of the brain. While diffusion tensor imaging (DTI) has advanced the mapping of these structural pathways, the relationship between structural connectivity (SC) and functional connectivity (FC) remains inadequately understood. This study addresses the need for a more integrative approach by mapping the importance of the inter-GM functional link to its structural counterparts in WM. This mapping yields a spatial distribution of engagement that is not only highly reproducible but also aligns with direct structural, functional, and bioenergetic measures within WM, illustrating a notable interdependence between the function of GM and the characteristics of WM. Additionally, our research has uncovered a set of unique engagement modes through a clustering analysis of window-wise engagement maps, highlighting the dyanmic nature of the engagement. The engagement along with their temporal variations revealed significant differences across genders and age groups. These findings suggest the potential of WM engagement as a biomarker for neurological and cognitive conditions, offering a more nuanced understanding of individualized brain activity and connectivity patterns.

Tumor therapy by targeting extracellular hydroxyapatite using novel drugs: A paradigm shift.

BACKGROUND: It has been shown that tumor microenvironment (TME) hydroxyapatite (HAP) is typically associated with many malignancies and plays a role in tumor progression and growth. Additionally, acidosis in the TME has been reported to play a key role in selecting for a more aggressive tumor phenotype, drug resistance and desensitization to immunotherapy for many types of cancers. TME-HAP is an attractive target for tumor detection and treatment development since HAP is generally absent from normal soft tissue. We provide strong evidence that dissolution of hydroxyapatite (HAP) within the tumor microenvironment (TME-HAP) using a novel therapeutic can be used to kill cancer cells both in vitro and in vivo with minimal adverse effects. METHODS: We developed an injectable cation exchange nano particulate sulfonated polystyrene solution (NSPS) that we engineered to dissolve TME-HAP, inducing localized acute alkalosis and inhibition of tumor growth and glucose metabolism. This was evaluated in cell culture using 4T1, MDA-MB-231 triple negative breast cancer cells, MCF10 normal breast cells, and H292 lung cancer cells, and in vivo using orthotopic mouse models of cancer that contained detectable microenvironment HAP including breast (MMTV-Neu, 4T1, and MDA-MB-231), prostate (PC3) and colon (HCA7) cancer using 18 F-NaF for HAP and 18 F-FDG for glucose metabolism with PET imaging. On the other hand, H292 lung tumor cells that lacked detectable microenvironment HAP and MCF10a normal breast cells that do not produce HAP served as negative controls. Tumor microenvironment pH levels following injection of NSPS were evaluated via Chemical Exchange Saturation (CEST) MRI and via ex vivo methods. RESULTS: Within 24 h of adding the small concentration of 1X of NSPS (~7 µM), we observed significant tumor cell death (~ 10%, p < 0.05) in 4T1 and MDA-MB-231 cell cultures that contain HAP but ⟨2% in H292 and MCF10a cells that lack detectable HAP and in controls. Using CEST MRI, we found extracellular pH (pHe) in the 4T1 breast tumors, located in the mammary fat pad, to increase by nearly 10% from baseline before gradually receding back to baseline during the first hour post NSPS administration. in the tumors that contained TME-HAP in mouse models, MMTV-Neu, 4T1, and MDA-MB-231, PC3, and HCA7, there was a significant reduction (p<0.05) in 18 F-Na Fuptake post NSPS treatment as expected; 18 F- uptake in the tumor = 3.8 ± 0.5 %ID/g (percent of the injected dose per gram) at baseline compared to 1.8 ±0.5 %ID/g following one-time treatment with 100 mg/kg NSPS. Of similar importance, is that 18 F-FDG uptake in the tumors was reduced by more than 75% compared to baseline within 24 h of treatment with one-time NSPS which persisted for at least one week. Additionally, tumor growth was significantly slower (p < 0.05) in the mice treated with one-time NSPS. Toxicity showed no evidence of any adverse effects, a finding attributed to the absence of HAP in normal soft tissue and to our therapeutic NSPS having limited penetration to access HAP within skeletal bone. CONCLUSION: Dissolution of TME-HAP using our novel NSPS has the potential to provide a new treatment paradigm to enhance the management of cancer patients with poor prognosis.