A novel approach to expedite emergency investigation for suspected cauda equina syndrome referrals from community and primary care services: A service evaluation.

INTRODUCTION: Although a rare spinal emergency, cauda equina syndrome (CES) can result in significant physical, emotional, and psychological sequalae. Introducing a CES pathway enhances diagnosis but may increase Radiology and Orthopaedic workload. To address this, one NHS hospital in England introduced a novel CES pathway. Utilising a criteria-led pathway, patients were referred directly from community/primary care, via the Emergency Department, for an emergency MRI scan. OBJECTIVE: To compare the outcomes of patients referred via an original and redesigned Community and Primary Care CES pathway. DESIGN: A retrospective service evaluation was undertaken of all emergency MRI scans investigating suspected CES via either pathway. METHODS: Two 3-month time periods were analysed; pre-(original) and post-implementation of the redesigned pathway; time to surgery was reviewed over two 12-month periods. RESULTS: Increased MRI scan utilisation was seen following the implementation of the redesigned pathway: original n = 50, redesigned n = 128, increasing Radiology workload. However, the redesigned pathway resulted in a reduction in time to MRI from 3h:01m to 1h:02m; reduction in time spent in ED 4h:55m to 3h:24m; reduction in time to surgery 18h:05m to 13h:38m; reduction in out-of-hour scanning from 10 to 2 patients during the evaluation period; and a reduction in on-call Orthopaedic involvement by 38%. CONCLUSION: All timed outcomes were improved with the implementation of this novel pathway. This suggests expediting MRI scans can result in substantial downstream benefits; albeit while increasing MRI scan utilisation. This pathway aligns with the emergency management of suspected CES under the new national CES pathway in England.

Metabolic Imaging Biomarkers of Response to Signaling Inhibition Therapy in Melanoma.

Dabrafenib therapy for metastatic melanoma focuses on blocking growth-promoting signals produced by a hyperactive BRAF protein. We report the metabolic differences of four human melanoma cell lines with diverse responses to dabrafenib therapy (30 mg/kg; oral): WM3918 < WM9838BR < WM983B < DB-1. Our goal was to determine if metabolic changes produced by the altered signaling pathway due to BRAF mutations differ in the melanoma models and whether these differences correlate with response to treatment. We assessed metabolic changes in isolated cells using high-resolution proton magnetic resonance spectroscopy (1H MRS) and supplementary biochemical assays. We also noninvasively studied mouse xenografts using proton and phosphorus (1H/31P) MRS. We found consistent changes in lactate and alanine, either in isolated cells or mouse xenografts, correlating with their relative dabrafenib responsiveness. In xenografts, we also observed that a more significant response to dabrafenib correlated with higher bioenergetics (i.e., increased ßNTP/Pi). Notably, our noninvasive assessment of the metabolic status of the human melanoma xenografts by 1H/31P MRS demonstrated early metabolite changes preceding therapy response (i.e., tumor shrinkage). Therefore, this noninvasive methodology could be translated to assess in vivo predictive metabolic biomarkers of response in melanoma patients under dabrafenib and probably other signaling inhibition therapies.

pH-dependent structural characteristics of lonidamine: 1H and 13C NMR study.

Lonidamine (LND) is an anti-cancer drug with great potential as a metabolic modulator of chemotherapy, radiotherapy, hyperthermia, and photodynamic therapy in cancer treatment. LND affects several important aspects of cancer cell metabolism: it inhibits Complex I and II of the electron transport chain (ETC) and pyruvate carriers (mitochondrial), and monocarboxylate transporters in the plasma membrane of the cell. Cancer cells are affected by changes in pH on the molecular level, and so are the drugs used to treat cancer, thus it is important to understand how pH affects their structures and LND is no exception. LND dissolves at a pH of 8.3 in tris-glycine buffer but has limited solubility at pH 7. To understand how pH affects the structure of LND, and its effect as a metabolic modulator on cancer therapy, we made up samples of LND at pH 2, pH 7, and pH 13, and analyzed these samples using 1H and 13C NMR. We looked for ionization sites to explain the behavior of LND in solution. Our results showed considerable chemical shifts between the extremes of our experimental pH range. LND was ionized at its indazole α-nitrogen, however, we did not directly observe the protonation of the carboxyl group oxygen that is expected at pH 2, which may be the result of a chemical-exchange phenomenon.

Impact of Arterial Input Function and Pharmacokinetic Models on DCE-MRI Biomarkers for Detection of Vascular Effect Induced by Stroma-Directed Drug in an Orthotopic Mouse Model of Pancreatic Cancer.

PURPOSE: We demonstrated earlier in mouse models of pancreatic ductal adenocarcinoma (PDA) that Ktrans derived from dynamic contrast-enhanced (DCE) MRI detected microvascular effect induced by PEGPH20, a hyaluronidase which removes stromal hyaluronan, leading to reduced interstitial fluid pressure in the tumor (Clinical Cancer Res (2019) 25: 2314-2322). How the choice of pharmacokinetic (PK) model and arterial input function (AIF) may impact DCE-derived markers for detecting such an effect is not known. PROCEDURES: Retrospective analyses of the DCE-MRI of the orthotopic PDA model are performed to examine the impact of individual versus group AIF combined with Tofts model (TM), extended-Tofts model (ETM), or shutter-speed model (SSM) on the ability to detect the microvascular changes induced by PEGPH20 treatment. RESULTS: Individual AIF exhibit a marked difference in peak gadolinium concentration. However, across all three PK models, kep values show a significant correlation between individual versus group-AIF (p < 0.01). Regardless individual or group AIF, when kep is obtained from fitting the DCE-MRI data using the SSM, kep shows a significant increase after PEGPH20 treatment (p < 0.05 compared to the baseline); %change of kep from baseline to post-treatment is also significantly different between PEGPH20 versus vehicle group (p < 0.05). In comparison, when kep is derived from the TM, only the use of individual AIF leads to a significant increase of kep after PEGPH20 treatment, whereas the %change of kep is not different between PEGPH20 versus vehicle group. Group AIF but not individual AIF allows detection of a significant increase of Vp (derived from the ETM) in PEGPH20 versus vehicle group (p < 0.05). Increase of Vp is consistent with a large increase of mean capillary lumen area estimated from immunostaining. CONCLUSION: Our results suggest that kep derived from SSM and Vp from ETM, both using group AIF, are optimal for the detection of microvascular changes induced by stroma-directed drug PEGPH20. These analyses provide insights in the choice of PK model and AIF for optimal DCE protocol design in mouse pancreatic cancer models.

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging.

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.

An Online Repository for Pre-Clinical Imaging Protocols (PIPs).

Providing method descriptions that are more detailed than currently available in typical peer reviewed journals has been identified as an actionable area for improvement. In the biochemical and cell biology space, this need has been met through the creation of new journals focused on detailed protocols and materials sourcing. However, this format is not well suited for capturing instrument validation, detailed imaging protocols, and extensive statistical analysis. Furthermore, the need for additional information must be counterbalanced by the additional time burden placed upon researchers who may be already overtasked. To address these competing issues, this white paper describes protocol templates for positron emission tomography (PET), X-ray computed tomography (CT), and magnetic resonance imaging (MRI) that can be leveraged by the broad community of quantitative imaging experts to write and self-publish protocols in protocols.io. Similar to the Structured Transparent Accessible Reproducible (STAR) or Journal of Visualized Experiments (JoVE) articles, authors are encouraged to publish peer reviewed papers and then to submit more detailed experimental protocols using this template to the online resource. Such protocols should be easy to use, readily accessible, readily searchable, considered open access, enable community feedback, editable, and citable by the author.

Evaluation of Apparent Diffusion Coefficient Repeatability and Reproducibility for Preclinical MRIs Using Standardized Procedures and a Diffusion-Weighted Imaging Phantom.

Relevant to co-clinical trials, the goal of this work was to assess repeatability, reproducibility, and bias of the apparent diffusion coefficient (ADC) for preclinical MRIs using standardized procedures for comparison to performance of clinical MRIs. A temperature-controlled phantom provided an absolute reference standard to measure spatial uniformity of these performance metrics. Seven institutions participated in the study, wherein diffusion-weighted imaging (DWI) data were acquired over multiple days on 10 preclinical scanners, from 3 vendors, at 6 field strengths. Centralized versus site-based analysis was compared to illustrate incremental variance due to processing workflow. At magnet isocenter, short-term (intra-exam) and long-term (multiday) repeatability were excellent at within-system coefficient of variance, wCV [±CI] = 0.73% [0.54%, 1.12%] and 1.26% [0.94%, 1.89%], respectively. The cross-system reproducibility coefficient, RDC [±CI] = 0.188 [0.129, 0.343] µm2/ms, corresponded to 17% [12%, 31%] relative to the reference standard. Absolute bias at isocenter was low (within 4%) for 8 of 10 systems, whereas two high-bias (>10%) scanners were primary contributors to the relatively high RDC. Significant additional variance (>2%) due to site-specific analysis was observed for 2 of 10 systems. Base-level technical bias, repeatability, reproducibility, and spatial uniformity patterns were consistent with human MRIs (scaled for bore size). Well-calibrated preclinical MRI systems are capable of highly repeatable and reproducible ADC measurements.

Dynamic Contrast-Enhanced MRI in the Abdomen of Mice with High Temporal and Spatial Resolution Using Stack-of-Stars Sampling and KWIC Reconstruction.

Application of quantitative dynamic contrast-enhanced (DCE) MRI in mouse models of abdominal cancer is challenging due to the effects of RF inhomogeneity, image corruption from rapid respiratory motion and the need for high spatial and temporal resolutions. Here we demonstrate a DCE protocol optimized for such applications. The method consists of three acquisitions: (1) actual flip-angle B1 mapping, (2) variable flip-angle T1 mapping and (3) acquisition of the DCE series using a motion-robust radial strategy with k-space weighted image contrast (KWIC) reconstruction. All three acquisitions employ spoiled radial imaging with stack-of-stars sampling (SoS) and golden-angle increments between the views. This scheme is shown to minimize artifacts due to respiratory motion while simultaneously facilitating view-sharing image reconstruction for the dynamic series. The method is demonstrated in a genetically engineered mouse model of pancreatic ductal adenocarcinoma and yielded mean perfusion parameters of Ktrans = 0.23 ± 0.14 min-1 and ve = 0.31 ± 0.17 (n = 22) over a wide range of tumor sizes. The SoS-sampled DCE method is shown to produce artifact-free images with good SNR leading to robust estimation of DCE parameters.

DWI Metrics Differentiating Benign Intraductal Papillary Mucinous Neoplasms from Invasive Pancreatic Cancer: A Study in GEM Models.

KPC (KrasG12D:Trp53R172H:Pdx1-Cre) and CKS (KrasG12D:Smad4L/L:Ptf1a-Cre) mice are genetically engineered mouse (GEM) models that capture features of human pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasms (IPMN), respectively. We compared these autochthonous tumors using quantitative imaging metrics from diffusion-weighted MRI (DW-MRI) and dynamic contrast enhanced (DCE)-MRI in reference to quantitative histological metrics including cell density, fibrosis, and microvasculature density. Our results revealed distinct DW-MRI metrics between the KPC vs. CKS model (mimicking human PDAC vs. IPMN lesion): the apparent diffusion coefficient (ADC) of CKS tumors is significantly higher than that of KPC, with little overlap (mean ± SD 2.24±0.2 vs. 1.66±0.2, p<10−10) despite intratumor and intertumor variability. Kurtosis index (KI) is also distinctively separated in the two models. DW imaging metrics are consistent with growth pattern, cell density, and the cystic nature of the CKS tumors. Coregistration of ex vivo ADC maps with H&E-stained sections allowed for regional comparison and showed a correlation between local cell density and ADC value. In conclusion, studies in GEM models demonstrate the potential utility of diffusion-weighted MRI metrics for distinguishing pancreatic cancer from benign pancreatic cysts such as IPMN.

Three-dimensional mapping of neurofibrillary tangle burden in the human medial temporal lobe.

Tau protein neurofibrillary tangles are closely linked to neuronal/synaptic loss and cognitive decline in Alzheimer's disease and related dementias. Our knowledge of the pattern of neurofibrillary tangle progression in the human brain, critical to the development of imaging biomarkers and interpretation of in vivo imaging studies in Alzheimer's disease, is based on conventional two-dimensional histology studies that only sample the brain sparsely. To address this limitation, ex vivo MRI and dense serial histological imaging in 18 human medial temporal lobe specimens (age 75.3 ± 11.4 years, range 45 to 93) were used to construct three-dimensional quantitative maps of neurofibrillary tangle burden in the medial temporal lobe at individual and group levels. Group-level maps were obtained in the space of an in vivo brain template, and neurofibrillary tangles were measured in specific anatomical regions defined in this template. Three-dimensional maps of neurofibrillary tangle burden revealed significant variation along the anterior-posterior axis. While early neurofibrillary tangle pathology is thought to be confined to the transentorhinal region, we found similar levels of burden in this region and other medial temporal lobe subregions, including amygdala, temporopolar cortex, and subiculum/cornu ammonis 1 hippocampal subfields. Overall, the three-dimensional maps of neurofibrillary tangle burden presented here provide more complete information about the distribution of this neurodegenerative pathology in the region of the cortex where it first emerges in Alzheimer's disease, and may help inform the field about the patterns of pathology spread, as well as support development and validation of neuroimaging biomarkers.

Adaptive convolutional neural networks for accelerating magnetic resonance imaging via k-space data interpolation.

Deep learning in k-space has demonstrated great potential for image reconstruction from undersampled k-space data in fast magnetic resonance imaging (MRI). However, existing deep learning-based image reconstruction methods typically apply weight-sharing convolutional neural networks (CNNs) to k-space data without taking into consideration the k-space data's spatial frequency properties, leading to ineffective learning of the image reconstruction models. Moreover, complementary information of spatially adjacent slices is often ignored in existing deep learning methods. To overcome such limitations, we have developed a deep learning algorithm, referred to as adaptive convolutional neural networks for k-space data interpolation (ACNN-k-Space), which adopts a residual Encoder-Decoder network architecture to interpolate the undersampled k-space data by integrating spatially contiguous slices as multi-channel input, along with k-space data from multiple coils if available. The network is enhanced by self-attention layers to adaptively focus on k-space data at different spatial frequencies and channels. We have evaluated our method on two public datasets and compared it with state-of-the-art existing methods. Ablation studies and experimental results demonstrate that our method effectively reconstructs images from undersampled k-space data and achieves significantly better image reconstruction performance than current state-of-the-art techniques. Source code of the method is available at https://gitlab.com/qgpmztmf/acnn-k-space.

Respiratory Motion Mitigation and Repeatability of Two Diffusion-Weighted MRI Methods Applied to a Murine Model of Spontaneous Pancreatic Cancer.

Respiratory motion and increased susceptibility effects at high magnetic fields pose challenges for quantitative diffusion-weighted MRI (DWI) of a mouse abdomen on preclinical MRI systems. We demonstrate the first application of radial k-space-sampled (RAD) DWI of a mouse abdomen using a genetically engineered mouse model of pancreatic ductal adenocarcinoma (PDAC) on a 4.7 T preclinical scanner equipped with moderate gradient capability. RAD DWI was compared with the echo-planar imaging (EPI)-based DWI method with similar voxel volumes and acquisition times over a wide range of b-values (0.64, 535, 1071, 1478, and 2141 mm2/s). The repeatability metrics are assessed in a rigorous test-retest study (n = 10 for each DWI protocol). The four-shot EPI DWI protocol leads to higher signal-to-noise ratio (SNR) in diffusion-weighted images with persisting ghosting artifacts, whereas the RAD DWI protocol produces relatively artifact-free images over all b-values examined. Despite different degrees of motion mitigation, both RAD DWI and EPI DWI allow parametric maps of apparent diffusion coefficients (ADC) to be produced, and the ADC of the PDAC tumor estimated by the two methods are 1.3 ± 0.24 and 1.5 ± 0.28 × 10-3 mm2/s, respectively (p = 0.075, n = 10), and those of a water phantom are 3.2 ± 0.29 and 2.8 ± 0.15 × 10-3 mm2/s, respectively (p = 0.001, n = 10). Bland-Altman plots and probability density function reveal good repeatability for both protocols, whose repeatability metrics do not differ significantly. In conclusion, RAD DWI enables a more effective respiratory motion mitigation but lower SNR, while the performance of EPI DWI is expected to improve with more advanced gradient hardware.

Heritability of fat distributions in male mice from the founder strains of the Diversity Outbred mouse population.

Specific fat distributions are risk factors for complex diseases, including coronary heart disease and obstructive sleep apnea. To demonstrate the utility of high-diversity mouse models for elucidating genetic associations, we describe the phenotyping and heritability of fat distributions within the five classical inbred and three wild-derived founder mouse strains of the Collaborative Cross and Diversity Outbred mice. Measurements of subcutaneous and internal fat volumes in the abdomen, thorax and neck, and fat volumes in the tongue and pericardium were obtained using magnetic resonance imaging in male mice from the A/J (n = 12), C57BL/6J (n = 17), 129S1/SvlmJ (n = 12), NOD/LtJ (n = 14), NZO/HILtJ (n = 12), CAST/EiJ (n = 14), PWK/PhJ (n = 12), and WSB/EiJ (n = 15) strains. Phenotypes were compared across strains using analysis of variance and heritability estimated as the proportion of phenotypic variability attributable to strain. Heritability ranged from 44 to 91% across traits, including >70% heritability of tongue fat. A majority of heritability estimates remained significant controlling for body weight, suggesting genetic influences independent of general obesity. Principal components analysis supports genetic influences on overall obesity and specific to increased pericardial and intra-neck fat. Thus, among the founder strains of the Collaborative Cross and Diversity Outbred mice, we observed significant heritability of subcutaneous and internal fat volumes in the neck, thorax and abdomen, pericardial fat volume and tongue fat volume, consistent with genetic architecture playing an important role in explaining trait variability. Findings pave the way for studies utilizing high-diversity mouse models to identify genes affecting fat distributions and, in turn, influencing risk for associated complex disorders.

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine.

The National Institutes of Health's (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.

Intervertebral Disc Degeneration Is Associated With Aberrant Endplate Remodeling and Reduced Small Molecule Transport.

The intervertebral disc is the largest avascular structure in the body, and cells within the disc rely on diffusive transport via vasculature located within the vertebral endplate to receive nutrients, eliminate waste products, and maintain disc health. However, the mechanisms by which small molecule transport into the disc occurs in vivo and how these parameters change with disc degeneration remain understudied. Here, we utilize an in vivo rabbit puncture disc degeneration model to study these interactions and provide evidence that remodeling of the endplate adjacent to the disc occurs concomitant with degeneration. Our results identify significant increases in endplate bone volume fraction, increases in microscale stiffness of the soft tissue interfaces between the disc and vertebral bone, and reductions in endplate vascularity and small molecule transport into the disc as a function of degenerative state. A neural network model identified changes in diffusion into the disc as the most significant predictor of disc degeneration. These findings support the critical role of trans-endplate transport in disease progression and will improve patient selection to direct appropriate surgical intervention and inform new therapeutic approaches to improve disc health. © 2020 American Society for Bone and Mineral Research. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.

Hyperpolarized Metabolic Imaging Detects Latent Hepatocellular Carcinoma Domains Surviving Locoregional Therapy.

BACKGROUND AND AIMS: Advances in cancer treatment have improved survival; however, local recurrence and metastatic disease-the principal causes of cancer mortality-have limited the ability to achieve durable remissions. Local recurrences arise from latent tumor cells that survive therapy and are often not detectable by conventional clinical imaging techniques. Local recurrence after transarterial embolization (TAE) of hepatocellular carcinoma (HCC) provides a compelling clinical correlate of this phenomenon. In response to TAE-induced ischemia, HCC cells adapt their growth program to effect a latent phenotype that precedes local recurrence. APPROACH AND RESULTS: In this study, we characterized and leveraged the metabolic reprogramming demonstrated by latent HCC cells in response to TAE-induced ischemia to enable their detection in vivo using dynamic nuclear polarization (DNP) magnetic resonance spectroscopic imaging (MRSI) of 13 carbon-labeled substrates. Under TAE-induced ischemia, latent HCC cells demonstrated reduced metabolism and developed a dependence on glycolytic flux to lactate. Despite the hypometabolic state of these cells, DNP-MRSI of 1-13 C-pyruvate and its downstream metabolites, 1-13 C-lactate and 1-13 C-alanine, predicted histological viability. CONCLUSIONS: These studies provide a paradigm for imaging latent, treatment-refractory cancer cells, suggesting that DNP-MRSI provides a technology for this application.

Characterization of hippocampal subfields using ex vivo MRI and histology data: Lessons for in vivo segmentation.

Hippocampal subfield segmentation on in vivo MRI is of great interest for cognition, aging, and disease research. Extant subfield segmentation protocols have been based on neuroanatomical references, but these references often give limited information on anatomical variability. Moreover, there is generally a mismatch between the orientation of the histological sections and the often anisotropic coronal sections on in vivo MRI. To address these issues, we provide a detailed description of hippocampal anatomy using a postmortem dataset containing nine specimens of subjects with and without dementia, which underwent a 9.4 T MRI and histological processing. Postmortem MRI matched the typical orientation of in vivo images and segmentations were generated in MRI space, based on the registered annotated histological sections. We focus on the following topics: the order of appearance of subfields, the location of subfields relative to macroanatomical features, the location of subfields in the uncus and tail and the composition of the dark band, a hypointense layer visible in T2-weighted MRI. Our main findings are that: (a) there is a consistent order of appearance of subfields in the hippocampal head, (b) the composition of subfields is not consistent in the anterior uncus, but more consistent in the posterior uncus, (c) the dark band consists only of the CA-stratum lacunosum moleculare, not the strata moleculare of the dentate gyrus, (d) the subiculum/CA1 border is located at the middle of the width of the hippocampus in the body in coronal plane, but moves in a medial direction from anterior to posterior, and (e) the variable location and composition of subfields in the hippocampal tail can be brought back to a body-like appearance when reslicing the MRI scan following the curvature of the tail. Our findings and this publicly available dataset will hopefully improve anatomical accuracy of future hippocampal subfield segmentation protocols.

Metabolic Detection of Bruton's Tyrosine Kinase Inhibition in Mantle Cell Lymphoma Cells.

Current methods to evaluate effects of kinase inhibitors in cancer are suboptimal. Analysis of changes in cancer metabolism in response to the inhibitors creates an opportunity for better understanding of the interplay between cell signaling and metabolism and, from the translational perspective, potential early evaluation of response to the inhibitors as well as treatment optimization. We performed genomic, metabolomic, and fluxomic analyses to evaluate the mechanism of action of the Bruton's tyrosine kinase (BTK) inhibitor ibrutinib (IBR) in mantle cell lymphoma (MCL) cells. Our comprehensive analysis of the data generated by these diverse technologies revealed that IBR profoundly affected key metabolic pathways in IBR-sensitive cells including glycolysis, pentose phosphate pathway, TCA cycle, and glutaminolysis while having much less effects on IBR-poorly responsive cells. Changes in 1H magnetic resonance spectroscopy (MRS)-detectable lactate and alanine concentrations emerged as promising biomarkers of response and resistance to IBR as demonstrated from experiments on various MCL cell lines. The metabolic network analysis on the 13C MRS and 13C LC/MS experimental data provided quantitative estimates of various intracellular fluxes and energy contributions. Glutaminolysis contributed over 50% of mitochondrial ATP production. Administration of the glutaminase inhibitor CB-839 induced growth suppression of the IBR-poorly responsive cells. IMPLICATIONS: Our study demonstrates application of the advanced metabolomic/fluxomic techniques for comprehensive, precise, and prompt evaluations of the effects of kinase inhibition in MCL cells and has strong translational implications by potentially permitting early evaluation of cancer patient response versus resistance to kinase inhibitors and on design of novel therapies for overcoming the resistance.

Murine MPDZ-linked hydrocephalus is caused by hyperpermeability of the choroid plexus.

Though congenital hydrocephalus is heritable, it has been linked only to eight genes, one of which is MPDZ Humans and mice that carry a truncated version of MPDZ incur severe hydrocephalus resulting in acute morbidity and lethality. We show by magnetic resonance imaging that contrast medium penetrates into the brain ventricles of mice carrying a Mpdz loss-of-function mutation, whereas none is detected in the ventricles of normal mice, implying that the permeability of the choroid plexus epithelial cell monolayer is abnormally high. Comparative proteomic analysis of the cerebrospinal fluid of normal and hydrocephalic mice revealed up to a 53-fold increase in protein concentration, suggesting that transcytosis through the choroid plexus epithelial cells of Mpdz KO mice is substantially higher than in normal mice. These conclusions are supported by ultrastructural evidence, and by immunohistochemistry and cytology data. Our results provide a straightforward and concise explanation for the pathophysiology of Mpdz-linked hydrocephalus.

Dynamic Contrast-enhanced MRI Detects Responses to Stroma-directed Therapy in Mouse Models of Pancreatic Ductal Adenocarcinoma.

PURPOSE: The dense stroma underlies the drug resistance of pancreatic ductal adenocarcinoma (PDA) and has motivated the development of stroma-directed drugs. Our objective is to test the concept that dynamic contrast-enhanced (DCE) MRI using FDA-approved contrast media, an imaging method sensitive to the tumor microenvironment, can detect early responses to stroma-directed drug. EXPERIMENTAL DESIGN: Imaging studies were performed in three mouse models exhibiting high desmoplastic reactions: the autochthonous PDA in genetically engineered mice (KPC), an orthotopic model in syngeneic mice, and a xenograft model of human PDA in athymic mice. An investigational drug, PEGPH20 (pegvorhyaluronidase alfa), which degrades hyaluronan (HA) in the stroma of PDA, was injected alone or in combination with gemcitabine. RESULTS: At 24 hours after a single injection of PEGPH20, Ktrans , a DCE-MRI-derived marker that measures how fast a unit volume of contrast media is transferred from capillaries to interstitial space, increased 56% and 50% from baseline in the orthotopic and xenograft tumors, respectively, compared with a 4% and 6% decrease in vehicle groups (both P < 0.05). Similarly, after three combined treatments, Ktrans in KPC mice increased 54%, whereas it decreased 4% in controls treated with gemcitabine alone (P < 0.05). Consistently, after a single injection of PEGPH20, tumor HA content assessed by IHC was reduced substantially in all three models while drug delivery (measured by paclitaxel accumulation in tumor) was increased by 2.6-fold. CONCLUSIONS: These data demonstrated a DCE-MRI marker, Ktrans , can detect early responses to stroma-directed drug and reveal the sustained effect of combination treatment (PEGPH20+ gemcitabine).