Magnetic resonance imaging (MRI) has the potential to improve our understanding of diabetes and improve both diagnosis and monitoring of the disease. Although the spatial resolution of MRI is ...insufficient to directly image the endocrine pancreas in people, the increasing awareness that the exocrine pancreas is also involved in diabetes pathogenesis has spurred new MRI applications. These techniques build upon studies of exocrine pancreatic diseases, for which MRI has already developed into a routine clinical tool for diagnosis and monitoring of pancreatic cancer and pancreatitis. By adjusting the imaging contrast and carefully controlling image acquisition and processing, MRI can quantify a variety of tissue pathologies. This review introduces a number of quantitative MRI techniques that have been applied to study the diabetic pancreas, summarizes progress in validating and standardizing each technique, and discusses the need for image analyses that account for spatial heterogeneity in the pancreas.
Hybrid multiscale agent-based models (ABMs) are unique in their ability to simulate individual cell interactions and microenvironmental dynamics. Unfortunately, the high computational cost of ...modeling individual cells, the inherent stochasticity of cell dynamics, and numerous model parameters are fundamental limitations of applying such models to predict tumor dynamics. To overcome these challenges, we have developed a coarse-grained two-scale ABM (cgABM) with a reduced parameter space that allows for an accurate and efficient calibration using a set of time-resolved microscopy measurements of cancer cells grown with different initial conditions. The multiscale model consists of a reaction-diffusion type model capturing the spatio-temporal evolution of glucose and growth factors in the tumor microenvironment (at tissue scale), coupled with a lattice-free ABM to simulate individual cell dynamics (at cellular scale). The experimental data consists of BT474 human breast carcinoma cells initialized with different glucose concentrations and tumor cell confluences. The confluence of live and dead cells was measured every three hours over four days. Given this model, we perform a time-dependent global sensitivity analysis to identify the relative importance of the model parameters. The subsequent cgABM is calibrated within a Bayesian framework to the experimental data to estimate model parameters, which are then used to predict the temporal evolution of the living and dead cell populations. To this end, a moment-based Bayesian inference is proposed to account for the stochasticity of the cgABM while quantifying uncertainties due to limited temporal observational data. The cgABM reduces the computational time of ABM simulations by 93% to 97% while staying within a 3% difference in prediction compared to ABM. Additionally, the cgABM can reliably predict the temporal evolution of breast cancer cells observed by the microscopy data with an average error and standard deviation for live and dead cells being 7.61±2.01 and 5.78±1.13, respectively.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Studies of new therapies to preserve insulin secretion in early type 1 diabetes require several years to recruit eligible subjects and to see a treatment effect; thus, there is interest in ...alternative study designs to speed this process. Most people with longstanding type 1 diabetes no longer secrete insulin. However, studies from pancreata of those with longstanding T1D show that beta cells staining for insulin can persist for decades after diagnosis, and this is paralleled in work showing proinsulin secretion in individuals with longstanding disease; collectively this suggests that there is a reserve of alive but "sleeping" beta cells. Here, we designed a novel clinical trial platform to test whether a short course of therapy with an agent known to have effects in type 1 diabetes with residual endogenous insulin could transiently induce insulin secretion in those who no longer produce insulin. A therapy that transiently "wakes up" sleeping beta cells might be tested next in a fully powered trial in those with endogenous insulin secretion. In this three-arm non-randomized pilot study, we tested three therapies known to impact disease: two beta-cell supportive agents, liraglutide and verapamil, and an immunomodulatory agent, golimumab. The golimumab treated arm was not fully enrolled due to uncertainties about immunotherapy during the COVID-19 pandemic. Participants had mixed-meal tolerance test (MMTT)-stimulated C-peptide below the quantitation limit (<0.02 ng/mL) at enrollment and received 8 to 12 weeks of therapy. At the completion of therapy, none of the individuals achieved the primary outcome of MMTT-stimulated C-peptide ≥ 0.02 ng/mL. An exploratory outcome of the verapamil arm was MRI-assessed pancreas size, diffusion, and longitudinal relaxation time, which showed repeatability of these measures but no treatment effect. The liraglutide and golimumab arms were registered on clinicaltrials.gov under accession number NCT03632759 and the verapamil arm under accession number NCT05847413. Trail registration: Protocols are registered in ClinicalTrials.gov under accession numbers NCT03632759 and NCT05847413.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The ability to accurately predict response and then rigorously optimize a therapeutic regimen on a patient-specific basis, would transform oncology. Toward this end, we have developed an ...experimental-mathematical framework that integrates quantitative magnetic resonance imaging (MRI) data into a biophysical model to predict patient-specific treatment response of locally advanced breast cancer to neoadjuvant therapy. Diffusion-weighted and dynamic contrast-enhanced MRI data is collected prior to therapy, after 1 cycle of therapy, and at the completion of the first therapeutic regimen. The model is initialized and calibrated with the first 2 patient-specific MRI data sets to predict response at the third, which is then compared to patient outcomes (N = 18). The model's predictions for total cellularity, total volume, and the longest axis at the completion of the regimen are significant within expected measurement precision (P< 0.05) and strongly correlated with measured response (P < 0.01). Further, we use the model to investigate, in silico, a range of (practical) alternative treatment plans to achieve the greatest possible tumor control for each individual in a subgroup of patients (N = 13). The model identifies alternative dosing strategies predicted to achieve greater tumor control compared to the standard of care for 12 of 13 patients (P < 0.01). In summary, a predictive, mechanism-based mathematical model has demonstrated the ability to identify alternative treatment regimens that are forecasted to outperform the therapeutic regimens the patients clinically. This has important implications for clinical trial design with the opportunity to alter oncology care in the future.
Background
Quantitative diffusion‐weighted MRI (DW‐MRI) and dynamic contrast‐enhanced MRI (DCE‐MRI) have the potential to impact patient care by providing noninvasive biological information in breast ...cancer.
Purpose/Hypothesis
To quantify the repeatability, reproducibility, and accuracy of apparent diffusion coefficient (ADC) and T1‐mapping of the breast in community radiology practices.
Study Type
Prospective.
Subjects/Phantom
Ice‐water DW‐MRI and T1 gel phantoms were used to assess accuracy. Normal subjects (n = 3) and phantoms across three sites (one academic, two community) were used to assess reproducibility. Test–retest analysis at one site in normal subjects (n = 12) was used to assess repeatability.
Field Strength/Sequence
3T Siemens Skyra MRI quantitative DW‐MRI and T1‐mapping.
Assessment
Quantitative DW‐MRI and T1‐mapping parametric maps of phantoms and fibroglandular and adipose tissue of the breast.
Statistical Tests
Average values of breast tissue were quantified and Bland–Altman analysis was performed to assess the repeatability of the MRI techniques, while the Friedman test assessed reproducibility.
Results
ADC measurements were reproducible across sites, with an average difference of 1.6% in an ice‐water phantom and 7.0% in breast fibroglandular tissue. T1 measurements in gel phantoms had an average difference of 2.8% across three sites, whereas breast fibroglandular and adipose tissue had 8.4% and 7.5% average differences, respectively. In the repeatability study, we found no bias between first and second scanning sessions (P = 0.1). The difference between repeated measurements was independent of the mean for each MRI metric (P = 0.156, P = 0.862, P = 0.197 for ADC, T1 of fibroglandular tissue, and T1 of adipose tissue, respectively).
Data Conclusion
Community radiology practices can perform repeatable, reproducible, and accurate quantitative T1‐mapping and DW‐MRI. This has the potential to dramatically expand the number of sites that can participate in multisite clinical trials and increase clinical translation of quantitative MRI techniques for cancer response assessment.
Level of Evidence: 1
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2018;48:695–707.
This study harnessed the electronic medical record to assess pancreas volume in patients with type 1 diabetes (T1D) and matched controls to determine whether pancreas volume is altered in T1D and ...identify covariates that influence pancreas volume.
This study included 25 patients with T1D and 25 age-, sex-, and weight-matched controls from the Vanderbilt University Medical Center enterprise data warehouse. Measurements of pancreas volume were made from medical imaging studies using magnetic resonance imaging (MRI) or computed tomography (CT).
Patients with T1D had a pancreas volume 47% smaller than matched controls (41.16 ml vs. 77.77 ml, P < 0.0001) as well as pancreas volume normalized by subject body weight, body mass index, or body surface area (all P < 0.0001). Pancreatic volume was smaller with a longer duration of T1D across the patient population (N = 25, P = 0.04). Additionally, four individual patients receiving multiple imaging scans displayed progressive declines in pancreas volume over time (~ 6% of volume/year), whereas five controls scanned a year apart did not exhibit a decline in pancreas size (P = 0.03). The pancreas was uniformly smaller on the right and left side of the abdomen.
Pancreas volume declines with disease duration in patients with T1D, suggesting a protracted pathological process that may include the exocrine pancreas.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The purpose of this study was to determine whether advanced quantitative magnetic resonance imaging (MRI) can be deployed outside of large, research-oriented academic hospitals and into community ...care settings to predict eventual pathological complete response (pCR) to neoadjuvant therapy (NAT) in patients with locally advanced breast cancer.
Patients with stage II/III breast cancer (N = 28) were enrolled in a multicenter study performed in community radiology settings. Dynamic contrast-enhanced (DCE) and diffusion-weighted (DW)-MRI data were acquired at four time points during the course of NAT. Estimates of the vascular perfusion and permeability, as assessed by the volume transfer rate (K
) using the Patlak model, were generated from the DCE-MRI data while estimates of cell density, as assessed by the apparent diffusion coefficient (ADC), were calculated from DW-MRI data. Tumor volume was calculated using semi-automatic segmentation and combined with K
and ADC to yield bulk tumor blood flow and cellularity, respectively. The percent change in quantitative parameters at each MRI scan was calculated and compared to pathological response at the time of surgery. The predictive accuracy of each MRI parameter at different time points was quantified using receiver operating characteristic curves.
Tumor size and quantitative MRI parameters were similar at baseline between groups that achieved pCR (n = 8) and those that did not (n = 20). Patients achieving a pCR had a larger decline in volume and cellularity than those who did not achieve pCR after one cycle of NAT (p < 0.05). At the third and fourth MRI, changes in tumor volume, K
, ADC, cellularity, and bulk tumor flow from baseline (pre-treatment) were all significantly greater (p < 0.05) in the cohort who achieved pCR compared to those patients with non-pCR.
Quantitative analysis of DCE-MRI and DW-MRI can be implemented in the community care setting to accurately predict the response of breast cancer to NAT. Dissemination of quantitative MRI into the community setting allows for the incorporation of these parameters into the standard of care and increases the number of clinical community sites able to participate in novel drug trials that require quantitative MRI.
Background: Trastuzumab induces cell cycle arrest in HER2-overexpressing cells and demonstrates potential in radiosensitizing cancer cells. The purpose of this study is to quantify combination ...trastuzumab and radiotherapy to determine their synergy. Methods: In vitro, HER2+ cancer cells were treated with trastuzumab, radiation, or their combination, and imaged to evaluate treatment kinetics. In vivo, HER2+ tumor-bearing mice were treated with trastuzumab and radiation, and assessed longitudinally. An additional cohort was treated and sacrificed to quantify CD45, CD31, α-SMA, and hypoxia. Results: The interaction index revealed the additive effects of trastuzumab and radiation in vitro in HER2+ cell lines. Furthermore, the results revealed significant differences in tumor response when treated with radiation (p < 0.001); however, no difference was seen in the combination groups when trastuzumab was added to radiotherapy (p = 0.56). Histology revealed increases in CD45 staining in tumors receiving trastuzumab (p < 0.05), indicating potential increases in immune infiltration. Conclusions: The in vitro results showed the additive effect of combination trastuzumab and radiotherapy. The in vivo results showed the potential to achieve similar efficacy of radiotherapy with a reduced dose when combined with trastuzumab. If trastuzumab and low-dose radiotherapy induce greater tumor kill than a higher dose of radiotherapy, combination therapy can achieve a similar reduction in tumor burden.
Magnetic resonance imaging (MRI) has detected changes in pancreas volume and other characteristics in type 1 and type 2 diabetes. However, differences in MRI technology and approaches across ...locations currently limit the incorporation of pancreas imaging into multisite trials. The purpose of this study was to develop a standardized MRI protocol for pancreas imaging and to define the reproducibility of these measurements. Calibrated phantoms with known MRI properties were imaged at five sites with differing MRI hardware and software to develop a harmonized MRI imaging protocol. Subsequently, five healthy volunteers underwent MRI at four sites using the harmonized protocol to assess pancreas size, shape, apparent diffusion coefficient (ADC), longitudinal relaxation time (T1), magnetization transfer ratio (MTR), and pancreas and hepatic fat fraction. Following harmonization, pancreas size, surface area to volume ratio, diffusion, and longitudinal relaxation time were reproducible, with coefficients of variation less than 10%. In contrast, non-standardized image processing led to greater variation in MRI measurements. By using a standardized MRI image acquisition and processing protocol, quantitative MRI of the pancreas performed at multiple locations can be incorporated into clinical trials comparing pancreas imaging measures and metabolic state in individuals with type 1 or type 2 diabetes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Diabetes mellitus presents a global health challenge characterized by dysregulated glucose metabolism and insulin resistance. Pancreas dysfunction contributes to the development and progression of ...diabetes. Cross-sectional imaging modalities have provided new insight into the structural and functional alterations of the pancreas in individuals with diabetes. This review summarizes MRI and CT studies that characterize pancreas alterations in both type 1 and type 2 diabetes and discusses future applications of these techniques.
Key points
Cross-sectional imaging can detect alterations to the pancreas accompanying, and possibly presaging, the development of both type 1 diabetes (T1D) and type 2 diabetes (T2D).
The smaller pancreas found in individuals with diabetes implicates exocrine involvement in the disease, as it exceeds the 1–2% of the pancreas composed of hormone-producing endocrine tissue.
Pancreas fat content is associated with insulin resistance and is higher in individuals with T2D.
Quantitative MRI can detect changes in pancreas composition and microstructure in individuals with diabetes that display spatial heterogeneity throughout the gland.
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