Deuterium MRS of early treatment-induced changes in tumour lactate in vitro.

Elevated production of lactate is a key characteristic of aberrant tumour cell metabolism and can be non-invasively measured as an early marker of tumour response using deuterium (2 H) MRS. Following treatment, changes in the 2 H-labelled lactate signal could identify tumour cell death or impaired metabolic function, which precede morphological changes conventionally used to assess tumour response. In this work, the association between apoptotic cell death, extracellular lactate concentration, and early treatment-induced changes in the 2 H-labelled lactate signal was established in an in vitro tumour model. Experiments were conducted at 7 T on acute myeloid leukaemia (AML) cells, which had been treated with 10 µg/mL of the chemotherapeutic agent cisplatin. At 24 and 48 h after cisplatin treatment the cells were supplied with 20 mM of [6,6'-2 H2 ]glucose and scanned over 2 h using a two-dimensional 2 H MR spectroscopic imaging sequence. The resulting signals from 2 H-labelled glucose, lactate, and water were quantified using a spectral fitting algorithm implemented on the Oxford Spectroscopy Analysis MATLAB toolbox. After scanning, the cells were processed for histological stains (terminal deoxynucleotidyl transferase UTP nick end labelling and haematoxylin and eosin) to assess apoptotic area fraction and cell morphology respectively, while a colorimetric assay was used to measure extracellular lactate concentrations in the supernatant. Significantly lower levels of 2 H-labelled lactate were observed in the 48 h treated cells compared with the untreated and 24 h treated cells, and these changes were significantly correlated with an increase in apoptotic fraction and a decrease in extracellular lactate. By establishing the biological processes associated with treatment-induced changes in the 2 H-labelled lactate signal, these findings suggest that 2 H MRS of lactate may be valuable in evaluating early tumour response.

VERDICT MRI validation in fresh and fixed prostate specimens using patient-specific moulds for histological and MR alignment.

The VERDICT framework for modelling diffusion MRI data aims to relate parameters from a biophysical model to histological features used for tumour grading in prostate cancer. Validation of the VERDICT model is necessary for clinical use. This study compared VERDICT parameters obtained ex vivo with histology in five specimens from radical prostatectomy. A patient-specific 3D-printed mould was used to investigate the effects of fixation on VERDICT parameters and to aid registration to histology. A rich diffusion data set was acquired in each ex vivo prostate before and after fixation. At both time points, data were best described by a two-compartment model: the model assumes that an anisotropic tensor compartment represents the extracellular space and a restricted sphere compartment models the intracellular space. The effect of fixation on model parameters associated with tissue microstructure was small. The patient-specific mould minimized tissue deformations and co-localized slices, so that rigid registration of MRI to histology images allowed region-based comparison with histology. The VERDICT estimate of the intracellular volume fraction corresponded to histological indicators of cellular fraction, including high values in tumour regions. The average sphere radius from VERDICT, representing the average cell size, was relatively uniform across samples. The primary diffusion direction from the extracellular compartment of the VERDICT model aligned with collagen fibre patterns in the stroma obtained by structure tensor analysis. This confirmed the biophysical relationship between ex vivo VERDICT parameters and tissue microstructure from histology.

The prognostic and predictive value of vascular response parameters measured by dynamic contrast-enhanced-CT, -MRI and -US in patients with metastatic renal cell carcinoma receiving sunitinib.

OBJECTIVES: To identify dynamic contrast-enhanced (DCE) imaging parameters from MRI, CT and US that are prognostic and predictive in patients with metastatic renal cell cancer (mRCC) receiving sunitinib. METHODS: Thirty-four patients were monitored by DCE imaging on day 0 and 14 of the first course of sunitinib treatment. Additional scans were performed with DCE-US only (day 7 or 28 and 2 weeks after the treatment break). Perfusion parameters that demonstrated a significant correlation (Spearman p < 0.05) with progression-free survival (PFS) and overall survival (OS) were investigated using Cox proportional hazard models/ratios (HR) and Kaplan-Meier survival analysis. RESULTS: A higher baseline and day 14 value for Ktrans (DCE-MRI) and a lower pre-treatment vascular heterogeneity (DCE-US) were significantly associated with a longer PFS (HR, 0.62, 0.37 and 5.5, respectively). A larger per cent decrease in blood volume on day 14 (DCE-US) predicted a longer OS (HR, 1.45). We did not find significant correlations between any of the DCE-CT parameters and PFS/OS, unless a cut-off analysis was used. CONCLUSIONS: DCE-MRI, -CT and ultrasound produce complementary parameters that reflect the prognosis of patients receiving sunitinib for mRCC. Blood volume measured by DCE-US was the only parameter whose change during early anti-angiogenic therapy predicted for OS and PFS. KEY POINTS: • DCE-CT, -MRI and ultrasound are complementary modalities for monitoring anti-angiogenic therapy. • The change in blood volume measured by DCE-US was predictive of OS/PFS. • Baseline vascular heterogeneity by DCE-US has the strongest prognostic value for PFS.

Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study.

The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.

Mapping water exchange rates in rat tumor xenografts using the late-stage uptake following bolus injections of contrast agent.

PURPOSE: To map the intra-to-extracellular water exchange rate constant in rat xenografts using a two-compartment model of relaxation with water exchange and a range of contrast agent concentrations and compare with histology. METHODS: MDA-MB-231 cells were xenografted into six nude rats. Three bolus injections of gadodiamide were administered. When uptake in the tumor demonstrated a steady-state, T1 data were acquired by spoiled gradient recalled acquisitions at four flip angles. A global fit of data to a two-compartment model incorporating exchange was performed, assuming a distribution volume of 20% of the rat. RESULTS: Voxels that did not reach steady-state and were excluded from parametric maps tended to be in large necrotic areas. TUNEL-negative (nonapoptotic) regions tended to have well-defined error bounds, with an average intra-to-extracellular exchange rate constant of 0.6 s(-1) . Apoptotic regions had higher exchange, but poorly determined upper bounds, with goodness of fit similar to that for a model assuming infinitely fast exchange. A lower bound of >3 s(-1) was used to establish voxels where the exchange rate constant was fast despite a large upper bound. CONCLUSION: Water exchange rates were higher in apoptotic regions, but examination of statistical errors was an important step in the mapping process.

Integrating low-cost sensor monitoring, satellite mapping, and geospatial artificial intelligence for intra-urban air pollution predictions.

There is a growing need to apply geospatial artificial intelligence analysis to disparate environmental datasets to find solutions that benefit frontline communities. One such critically needed solution is the prediction of health-relevant ambient ground-level air pollution concentrations. However, many challenges exist surrounding the size and representativeness of limited ground reference stations for model development, reconciling multi-source data, and interpretability of deep learning models. This research addresses these challenges by leveraging a strategically deployed, extensive low-cost sensor (LCS) network that was rigorously calibrated through an optimized neural network. A set of raster predictors with varying data quality and spatial scales was retrieved and processed, including gap-filled satellite aerosol optical depth products and airborne LiDAR-derived 3D urban form. We developed a multi-scale, attention-enhanced convolutional neural network model to reconcile the LCS measurements and multi-source predictors for estimating daily PM2.5 concentration at 30-m resolution. This model employs an advanced approach by using the geostatistical kriging method to generate a baseline pollution pattern and a multi-scale residual method to identify both regional patterns and localized events for high-frequency feature retention. We further used permutation tests to quantify the feature importance, which has rarely been done in DL applications in environmental science. Finally, we demonstrated one application of the model by investigating the air pollution inequality issue across and within various urbanization levels at the block group scale. Overall, this research demonstrates the potential of geospatial AI analysis to provide actionable solutions for addressing critical environmental issues.

Dynamic Contrast-enhanced CT to Evaluate Early Response in Neuroendocrine Liver Metastases Treated With Everolimus and Radiation.

BACKGROUND/AIM: The optimal method to evaluate response of neuroendocrine liver metastases (NELM) to radiation treatment (RT) is unknown; tumor perfusion parameters were evaluated by using dynamic contrast-enhanced computed tomography (DCE-CT) to correlate with efficacy in a prospective pilot study utilizing everolimus with radiotherapy for NELM. PATIENTS AND METHODS: Fourteen patients with progressive NELM received everolimus for 28 days prior to, concurrent with, and 14 days following radiation. Patients had a DCE-CT at baseline (t0), prior to radiation (t1) and 7 days after radiation (t2). Per lesion response was evaluated per standard response evaluation criteria (RECIST v1.1). Median statistics of the perfusion parameters were tabulated and included: blood flow (BF), blood volume (BV), and permeability (PS). Correlations between the parameters and the maximum percent change in size of the NELM at 12-months were explored. NELM not treated with radiation served as an internal control. RESULTS: Twenty-one treated NELM in 10 patients were evaluable. Compared to t0, BV increased at t1 (median 11%, range -15 to +37%, p=0.59), and then decreased significantly at t2 (median -8.4%, range -29 to +5.4%, p<0.03). A trend of increased BV in internal controls at each time point supports that the observed effect is due to radiation. Conventional objective response rate was 33%; no progression was seen within 12-months. CONCLUSION: Changes in DCE-CT were observed in patients receiving everolimus and radiation for NELM, with BV decreasing significantly following radiotherapy. Given the challenges in assessing response in NELM using traditional response evaluation criteria in any context, DCE-CT appears to be a promising modality.

Quantitative magnetization transfer studies of apoptotic cell death.

Magnetization transfer measurements were performed on samples of acute myeloid leukemia cells at early (36 h postcisplatin treatment) and late (48 h posttreatment) stages of apoptosis. Magnetization transfer ratio was calculated and a two-pool model was fitted to data at two powers and 16 offset frequencies of saturation pulse. No parameters changed significantly at early stages of apoptosis. At late stages, changes in magnetization transfer ratio were not significant, but quantitative model parameters showed a decrease in macromolecular proton fraction, M(0B), and an increase in the T(2) relaxation time of free water. Analysis also indicated an increase in the ratio R × M(0B)/R(1A), where R is the exchange rate between free water and macromolecular protons and R(1A) is the T(1) relaxation rate of free water. Changes in the magnetization transfer spectrum were largely attributable to differences in the free water pool and did not occur any earlier than changes in the average T(1) relaxation time, T(1obs).

Detection of apoptotic cell death in vitro in the presence of Gd-DTPA-BMA.

Due to variability in patient response to cancer therapy, there is a growing interest in monitoring patient progress during treatment. Apoptotic cell death is one early marker of tumor response to treatment. Using known extracellular concentrations of gadolinium diethylenetriamine pentaacetic acid bismethylamide (Gd-DTPA-BMA) to vary the exchange regime, T(1) and T(2) relaxation data for acute myeloid leukemia (AML) cell samples were obtained and then analyzed using a two-pool model of relaxation with exchange. Leukemia cells treated with cisplatin to induce apoptosis exhibited a statistically significant (P < 0.05) decrease in intracellular longitudinal relaxation time, T(1I), from 1030 ms to 940 ms, a decrease (P < 0.001) in the intracellular water fraction, M(0I), from 0.86 to 0.68 and a statistically significant increase (P < 0.01) in transmembrane water exchange rate, k(IE), from 1.4 s(-1) to 6.8 s(-1). The changes in MR parameters correlated with quantitative histology, such as cellular cross-sectional area and average nuclear area measurements. The results of this study emphasize the importance of accounting for water exchange in dynamic contrast-enhanced MRI (DCE-MRI) studies, particularly those that examine tumor response to therapies in which apoptotic changes occur.

Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings.

PURPOSE: To examine the usefulness of rich diffusion protocols with high b-values and varying diffusion time for probing microstructure in bone metastases. Analysis techniques including biophysical and mathematical models were compared with the clinical apparent diffusion coefficient (ADC). METHODS: Four patients were scanned using 13 b-values up to 3,000 s/mm2 and diffusion times ranging 18-52 ms. Data were fitted to mono-exponential ADC, intravoxel incoherent motion (IVIM), Kurtosis and Vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) models. Parameters from the models were compared using correlation plots. RESULTS: ADC and IVIM did not fit the data well, failing to capture the signal at high b-values. The Kurtosis model best explained the data in many voxels, but in voxels exhibiting a more time-dependent signal, the VERDICT model explained the data best. The ADC correlated significantly (p < 0.004) with the intracellular diffusion coefficient (r = 0.48), intracellular volume fraction (r = -0.21), and perfusion fraction (r = 0.46) parameters from VERDICT, suggesting that these factors all contribute to ADC contrast. The mean kurtosis correlated with the intracellular volume fraction parameter (r = 0.26) from VERDICT, consistent with the hypothesis that kurtosis relates to cellularity, but also correlated weakly with the intracellular diffusion coefficient (r = 0.18) and cell radius (r = 0.16) parameters, suggesting that it may be difficult to attribute physical meaning to kurtosis. CONCLUSION: Both Kurtosis and VERDICT explained the diffusion signal better than ADC and IVIM, primarily due to poor fitting at high b-values in the latter two models. The Kurtosis and VERDICT models captured information at high b using parameters (Kurtosis or intracellular volume fraction and radius) that do not have a simple relationship with ADC and that may provide additional microstructural information in bone metastases.

Water Exchange Rate Constant as a Biomarker of Treatment Efficacy in Patients With Brain Metastases Undergoing Stereotactic Radiosurgery.

PURPOSE: This study was designed to evaluate whether changes in metastatic brain tumors after stereotactic radiosurgery (SRS) can be seen with quantitative MRI early after treatment. METHODS AND MATERIALS: Using contrast-enhanced MRI, a 3-water-compartment tissue model consisting of intracellular (I), extracellular-extravascular (E), and vascular (V) compartments was used to assess the intra-extracellular water exchange rate constant (kIE), efflux rate constant (kep), and water compartment volume fractions (M0,I, M0,E, M0,V). In this prospective study, 19 patients were MRI-scanned before treatment and 1 week and 1 month after SRS. The change in model parameters between the pretreatment and 1-week posttreatment scans was correlated to the change in tumor volume between pretreatment and 1-month posttreatment scans. RESULTS: At 1 week kIE differentiated (P<.001) tumors that had partial response from tumors with stable and progressive disease, and a high correlation (R=-0.76, P<.001) was observed between early changes in the kIE and tumor volume change 1 month after treatment. Other model parameters had lower correlation (M0,E) or no correlation (kep, M0,V). CONCLUSIONS: This is the first study that measured kIE early after SRS, and it found that early changes in kIE (1 week after treatment) highly correlated with long-term tumor response and could predict the extent of tumor shrinkage at 1 month after SRS.

Apparatus for Histological Validation of In Vivo and Ex Vivo Magnetic Resonance Imaging of the Human Prostate.

This article describes apparatus to aid histological validation of magnetic resonance imaging studies of the human prostate. The apparatus includes a 3D-printed patient-specific mold that facilitates aligned in vivo and ex vivo imaging, in situ tissue fixation, and tissue sectioning with minimal organ deformation. The mold and a dedicated container include MRI-visible landmarks to enable consistent tissue positioning and minimize image registration complexity. The inclusion of high spatial resolution ex vivo imaging aids in registration of in vivo MRI and histopathology data.