Shutter-speed dynamic contrast-enhanced MRI: Is it fit for purpose?

Simultaneous estimation of the cellular water exchange rate, intracellular volume fraction, and longitudinal relaxation rate in cancer cells

The purpose of the current study was to investigate the feasibility of simultaneously estimating the cellular water efflux rate ( k ie ), intracellular longitudinal relaxation rate ( R 10 i ), and intracellular volume fraction ( v i ) of a cell suspension using multiple samples with different gadolinium concentrations. Numerical simulation studies were conducted to assess the uncertainty in the estimation of k ie , R 10 i , and v i from saturation recovery data using single (SC) or multiple concentrations (MC) of gadolinium-based contrast agent (GBCA). In vitro experiments with 4 T1 murine breast cancer and SCCVII squamous cell cancer models were conducted at 11 T to compare parameter estimation using the SC protocol with that using the MC protocol. The cell lines were challenged with a Na⁺ /K⁺ -ATPase inhibitor, digoxin, to assess the treatment response in terms of k ie , R 10 i , and v i . Data analysis was conducted using the two-compartment exchange model for parameter estimation. The simulation study data demonstrate that the MC method, compared with the SC method, reduces the uncertainty of the estimated k ie by decreasing the interquartile ranges from 27.3% ± 3.7% to 18.8% ± 5.1% and the median differences from ground truth from 15.0% ± 6.3% to 7.2% ± 4.2%, while estimating R 10 i and v i simultaneously. In the cell studies, the MC method demonstrated reduced uncertainty in overall parameter estimation compared with the SC approach. MC method-measured parameter changes in cells treated with digoxin increased R 10 i by 11.7% (p = 0.218) and k ie by 5.9% (p = 0.234) for 4 T1 cells, respectively, and decreased R 10 i by 28.8% (p = 0.226) and k ie by 1.6% (p = 0.751) for SCCVII cells, respectively. v i did not change noticeably by the treatment. The results of this study substantiate the feasibility of using saturation recovery data of multiple samples with different GBCA concentrations for simultaneous measurement of the cellular water efflux rate, intracellular volume fraction, and intracellular longitudinal relaxation rate in cancer cells.

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 K^trans 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, k_ep values show a significant correlation between individual versus group-AIF (p < 0.01). Regardless individual or group AIF, when k_ep is obtained from fitting the DCE-MRI data using the SSM, k_ep shows a significant increase after PEGPH20 treatment (p < 0.05 compared to the baseline); %change of k_ep from baseline to post-treatment is also significantly different between PEGPH20 versus vehicle group (p < 0.05). In comparison, when k_ep is derived from the TM, only the use of individual AIF leads to a significant increase of k_ep after PEGPH20 treatment, whereas the %change of k_ep is not different between PEGPH20 versus vehicle group. Group AIF but not individual AIF allows detection of a significant increase of V_p (derived from the ETM) in PEGPH20 versus vehicle group (p < 0.05). Increase of V_p is consistent with a large increase of mean capillary lumen area estimated from immunostaining.

CONCLUSION

Our results suggest that k_ep derived from SSM and V_p 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.

Evaluation of cellular water exchange in a mouse glioma model using dynamic contrast-enhanced MRI with two flip angles

This manuscript aims to evaluate the robustness and significance of the water efflux rate constant (k_io) parameter estimated using the two flip-angle Dynamic Contrast-Enhanced (DCE) MRI approach with a murine glioblastoma model at 7 T. The repeatability of contrast kinetic parameters and k_io measurement was assessed by a test-retest experiment (n = 7). The association of k_io with cellular metabolism was investigated through DCE-MRI and FDG-PET experiments (n = 7). Tumor response to a combination therapy of bevacizumab and fluorouracil (5FU) monitored by contrast kinetic parameters and k_io (n = 10). Test-retest experiments demonstrated compartmental volume fractions (v_e and v_p) remained consistent between scans while the vascular functional measures (F_p and PS) and k_io showed noticeable changes, most likely due to physiological changes of the tumor. The standardized uptake value (SUV) of tumors has a linear correlation with k_io (R² = 0.547), a positive correlation with F_p (R² = 0.504), and weak correlations with v_e (R² = 0.150), v_p (R² = 0.077), PS (R² = 0.117), K^trans (R² = 0.088) and whole tumor volume (R² = 0.174). In the treatment study, the k_io of the treated group was significantly lower than the control group one day after bevacizumab treatment and decreased significantly after 5FU treatment compared to the baseline. This study results support the feasibility of measuring k_io using the two flip-angle DCE-MRI approach in cancer imaging.

Metabolic activity diffusion imaging (MADI): I. Metabolic, cytometric modeling and simulations

Evidence mounts that the steady-state cellular water efflux (unidirectional) first-order rate constant (k_io [s^-1 ]) magnitude reflects the ongoing, cellular metabolic rate of the cytolemmal Na⁺ , K⁺ -ATPase (NKA), ^c MR_NKA (pmol [ATP consumed by NKA]/s/cell), perhaps biology's most vital enzyme. Optimal ¹ H₂ O MR k_io determinations require paramagnetic contrast agents (CAs) in model systems. However, results suggest that the homeostatic metabolic k_io biomarker magnitude in vivo is often too large to be reached with allowable or possible CA living tissue distributions. Thus, we seek a noninvasive (CA-free) method to determine k_io in vivo. Because membrane water permeability has long been considered important in tissue water diffusion, we turn to the well-known diffusion-weighted MRI (DWI) modality. To analyze the diffusion tensor magnitude, we use a parsimoniously primitive model featuring Monte Carlo simulations of water diffusion in virtual ensembles comprising water-filled and -immersed randomly sized/shaped contracted Voronoi cells. We find this requires two additional, cytometric properties: the mean cell volume (V [pL]) and the cell number density (ρ [cells/μL]), important biomarkers in their own right. We call this approach metabolic activity diffusion imaging (MADI). We simulate water molecule displacements and transverse MR signal decays covering the entirety of b-space from pure water (ρ = V = 0; k_io undefined; diffusion coefficient, D₀ ) to zero diffusion. The MADI model confirms that, in compartmented spaces with semipermeable boundaries, diffusion cannot be described as Gaussian: the nanoscopic D (D_n ) is diffusion time-dependent, a manifestation of the "diffusion dispersion". When the "well-mixed" (steady-state) condition is reached, diffusion becomes limited, mainly by the probabilities of (1) encountering (ρ, V), and (2) permeating (k_io ) cytoplasmic membranes, and less so by D_n magnitudes. Importantly, for spaces with large area/volume (A/V; claustrophobia) ratios, this can happen in less than a millisecond. The model matches literature experimental data well, with implications for DWI interpretations.

A comprehensive evaluation and impact of normalization of generalized tracer kinetic model parameters to characterize blood-brain-barrier permeability in normal-appearing and tumor tissue regions of patients with glioma

RATIONALE AND OBJECTIVES

To comprehensively evaluate robustness and variations of DCE-MRI derived generalized-tracer-kinetic-model (GTKM) parameters in healthy and tumor tissues and impact of normalization in mitigating these variations on application to glioma.

MATERIALS (PATIENTS) AND METHODS

A retrospective study included pre-operative 31 high-grade-glioma(HGG), 22 low-grade-glioma(LGG) and 33 follow-up data from 10 patients a prospective study with 4 HGG subjects. Voxel-wise GTKM was fitted to DCE-MRI data to estimate K^trans, v_e, v_b. Simulations were used to evaluate noise sensitivity. Variation of parameters with-respect-to arterial-input-function (AIF) variation and data length were studied. Normalization of parameters with-respect-to mean values in gray-matter (GM) and white-matter (WM) regions (GM-Type-2, WM-Type-2) and mean curves (GM-Type-1, WM-Type-1) were also evaluated. Co-efficient-of-variation(CoV), relative-percentage-error (RPE), Box-Whisker plots, bar graphs and t-test were used for comparison.

RESULTS

GTKM was fitted well in all tissue regions. K^trans and v_e in contrast-enhancing (CE) has shown improved noise sensitivity in longer data. v_b was reliable in all tissues. Mean AIF and C(t) peaks showed ~38% and ~35% variations. During simulation, normalizations have mitigated variations due to changes in AIF amplitude in K^trans and v_b.. v_e was less sensitive to normalizations. CoV of K^trans and v_b has reduced ~70% after GM-Type-1 normalization and ~80% after GM-Type-2 normalization, respectively. GM-Type-1 (p = 0.003) and GM-Type-2 (p = 0.006) normalizations have significantly improved differentiation of HGG and LGG using K^trans.

CONCLUSION

K^trans and v_b can be reliably estimated in normal-appearing brain tissues and can be used for normalization of corresponding parameters in tumor tissues for mitigating inter-subject variability due to errors in AIF. Normalized K^trans and v_b provided improved differentiation of HGG and LGG.

Measurement of cellular-interstitial water exchange time in tumors based on diffusion-time-dependent diffusional kurtosis imaging

PURPOSE

To assess the feasibility of using diffusion-time-dependent diffusional kurtosis imaging (tDKI) to measure cellular-interstitial water exchange time (τex ) in tumors, both in animals and in humans.

METHODS

Preclinical tDKI studies at 7 T were performed with the GL261 glioma model and the 4T1 mammary tumor model injected into the mouse brain. Clinical studies were performed at 3 T with women who had biopsy-proven invasive ductal carcinoma. tDKI measurement was conducted using a diffusion-weighted STEAM pulse sequence with multiple diffusion times (20-800 ms) at a fixed echo time, while keeping the b-values the same (0-3000 s/mm2 ) by adjusting the diffusion gradient strength. The tDKI data at each diffusion time t were used for a weighted linear least-squares fit method to estimate the diffusion-time-dependent diffusivity, D(t), and diffusional kurtosis, K(t).

RESULTS

Both preclinical and clinical studies showed that, when diffusion time t ≥ 200 ms, D(t) did not have a noticeable change while K(t) decreased monotonically with increasing diffusion time in tumors and t ≥ 100 ms for the cortical ribbon of the mouse brain. The estimated τex averaged median and interquartile range (IQR) of GL261 and 4T1 tumors were 93 (IQR = 89) ms and 68 (78) ms, respectively. For the cortical ribbon, the estimated τex averaged median and IQR were 41 (34) ms for C57BL/6 and 30 (17) ms for BALB/c. For invasive ductal carcinoma, the estimated τex median and IQR of the two breast cancers were 70 (94) and 106 (92) ms.

CONCLUSION

The results of this proof-of-concept study substantiate the feasibility of using tDKI to measure cellular-interstitial water exchange time without using an exogenous contrast agent.

Shutter-Speed DCE-MRI Analyses of Human Glioblastoma Multiforme (GBM) Data

BACKGROUND

The shutter-speed model dynamic contrast-enhanced (SSM-DCE) MRI pharmacokinetic analysis adds a metabolic dimension to DCE-MRI. This is of particular interest in cancers, since abnormal metabolic activity might happen.

PURPOSE

To develop a DCE-MRI SSM analysis framework for glioblastoma multiforme (GBM) cases considering the heterogeneous tissue found in GBM.

STUDY TYPE

Prospective.

SUBJECTS

Ten GBM patients.

FIELD STRENGTH/SEQUENCE

3T MRI with DCE-MRI.

ASSESSMENTS

The corrected Akaike information criterion (AIC_c ) was used to automatically separate DCE-MRI data into proper SSM versions based on the contrast agent (CA) extravasation in each pixel. The supra-intensive parameters, including the vascular water efflux rate constant (k_bo ), the cellular efflux rate constant (k_io ), and the CA vascular efflux rate constant (k_pe ), together with intravascular and extravascular-extracellular water mole fractions (p_b and p_o , respectively) were determined. Further error analyses were also performed to eliminate unreliable estimations on k_io and k_bo .

STATISTICAL TESTS

Student's t-test.

RESULTS

For tumor pixels of all subjects, 88% show lower AIC_c with SSM than with the Tofts model. Compared to normal-appearing white matter (NAWM), tumor tissue showed significantly larger p_b (0.045 vs. 0.011, P < 0.001) and higher k_pe (3.0 × 10^-2 s^-1 vs. 6.1 × 10^-4 s^-1 , P < 0.001). In the contrast, significant k_bo reduction was observed from NAWM to GBM tumor tissue (2.8 s^-1 vs. 1.0 s^-1 , P < 0.001). In addition, k_bo is four orders and two orders of magnitude greater than k_pe in the NAWM and GBM tumor, respectively. These results indicate that CA and water molecule have different transmembrane pathways. The mean tumor k_io of all subjects was 0.57 s^-1 .

DATA CONCLUSION

We demonstrate the feasibility of applying SSM models in GBM cases. Within the proposed SSM analysis framework, k_io and k_bo could be estimated, which might be useful biomarkers for GBM diagnosis and survival prediction in future.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 1 J. Magn. Reson. Imaging 2020;52:850-863.

Measuring water exchange across the blood-brain barrier using MRI

The blood-brain barrier (BBB) regulates the transfer of solutes and essential nutrients into the brain. Growing evidence supports BBB dysfunction in a range of acute and chronic brain diseases, justifying the need for novel research and clinical tools that can non-invasively detect, characterize, and quantify BBB dysfunction in-vivo. Many approaches already exist for measuring BBB dysfunction in man using positron emission tomography and magnetic resonance imaging (e.g. dynamic contrast-enhanced MRI measurements of gadolinium leakage). This review paper focusses on MRI measurements of water exchange across the BBB, which occurs through a wide range of pathways, and is likely to be a highly sensitive marker of BBB dysfunction. Key mathematical models and acquisition methods are discussed for the two main approaches: those that utilize contrast agents to enhance relaxation rate differences between the intravascular and extravascular compartments and so enhance the sensitivity of MRI signals to BBB water exchange, and those that utilize the dynamic properties of arterial spin labelling to first isolate signal from intravascular spins and then estimate the impact of water exchange on the evolving signal. Data from studies in healthy and pathological brain tissue are discussed, in addition to validation studies in rodents.

Advances in Diffusion and Perfusion MRI for Quantitative Cancer Imaging

PURPOSE OF REVIEW

This article is to review recent technical developments and their clinical applications in cancer imaging quantitative measurement of cellular and vascular properties of the tumors.

RECENT FINDINGS

Rapid development of fast Magnetic Resonance Imaging (MRI) technologies over last decade brought new opportunities in quantitative MRI methods to measure both cellular and vascular properties of tumors simultaneously.

SUMMARY

Diffusion MRI (dMRI) and dynamic contrast enhanced (DCE)-MRI have become widely used to assess the tissue structural and vascular properties, respectively. However, the ultimate potential of these advanced imaging modalities has not been fully exploited. The dependency of dMRI on the diffusion weighting gradient strength and diffusion time can be utilized to measure tumor perfusion, cellular structure, and cellular membrane permeability. Similarly, DCE-MRI can be used to measure vascular and cellular membrane permeability along with cellular compartment volume fractions. To facilitate the understanding of these potentially important methods for quantitative cancer imaging, we discuss the basic concepts and recent developments, as well as future directions for further development.

Estimation of cellular-interstitial water exchange in dynamic contrast enhanced MRI using two flip angles

PURPOSE

To investigate the feasibility of using multiple flip angles in dynamic contrast enhanced (DCE) MRI to reduce the uncertainty in estimation of intracellular water lifetime (τ_i ).

METHODS

Numerical simulation studies were conducted to assess the uncertainty in estimation of τ_i using dynamic contrast enhanced MRI with one or two flip angles. In vivo experiments with a murine brain tumor model were conducted at 7T using two flip angles. The in vivo data were used to compare τ_i estimation using the single-flip-angle (SFA) protocol with that using the double-flip-angle (DFA) protocol. Data analysis was conducted using the two-compartment exchange model combined with the three-site-two-exchange model for water exchange.

RESULTS

In the numerical simulation studies with a range of contrast kinetic parameters and signal-to-noise ratio = 20, the median bias of τ_i estimation decreased from 72 ms with SFA to 65 ms with DFA, and the corresponding median inter-quartile range reduced from 523 ms to 156 ms. In the in vivo studies, τ_i estimation with SFA was not successful in most voxels in the tumors, as the estimated τ_i values reached the upper limit of the parameter range (2 s). In contrast, the estimated τ_i values with DFA were mostly between 0.2 and 1.5 s and homogeneously distributed spatially across the tumor. The τ_i estimation with DFA was less sensitive to arterial input function scaling but more sensitive to pre-contrast T₁ than the other contrast kinetic parameters.

CONCLUSION

This study results demonstrate the feasibility of using multiple flip angles to encode the post-contrast time-intensity curve with different weighting of water exchange effect to reduce the uncertainty in τ_i estimation.

Reliability of dynamic contrast-enhanced magnetic resonance imaging data in primary brain tumours: a comparison of Tofts and shutter speed models

Purpose

The purpose of this study is to investigate the robustness of pharmacokinetic modelling of DCE-MRI brain tumour data and to ascertain reliable perfusion parameters through a model selection process and a stability test.

Methods

DCE-MRI data of 14 patients with primary brain tumours were analysed using the Tofts model (TM), the extended Tofts model (ETM), the shutter speed model (SSM) and the extended shutter speed model (ESSM). A no-effect model (NEM) was implemented to assess overfitting of data by the other models. For each lesion, the Akaike Information Criteria (AIC) was used to build a 3D model selection map. The variability of each pharmacokinetic parameter extracted from this map was assessed with a noise propagation procedure, resulting in voxel-wise distributions of the coefficient of variation (CV).

Results

The model selection map over all patients showed NEM had the best fit in 35.5% of voxels, followed by ETM (32%), TM (28.2%), SSM (4.3%) and ESSM (< 0.1%). In analysing the reliability of K^trans, when considering regions with a CV < 20%, ≈ 25% of voxels were found to be stable across all patients. The remaining 75% of voxels were considered unreliable.

Conclusions

The majority of studies quantifying DCE-MRI data in brain tumours only consider a single model and whole tumour statistics for the output parameters. Appropriate model selection, considering tissue biology and its effects on blood brain barrier permeability and exchange conditions, together with an analysis on the reliability and stability of the calculated parameters, is critical in processing robust brain tumour DCE-MRI data.

NMR shutter-speed elucidates apparent population inversion of 1 H2 O signals due to active transmembrane water cycling

Purpose

The desire to quantitatively discriminate the extra‐ and intracellular tissue ¹H₂O MR signals has gone hand‐in‐hand with the continual, historic increase in MRI instrument magnetic field strength [B₀]. However, recent studies have indicated extremely valuable, novel metabolic information can be readily accessible at ultra–low B₀. The two signals can be distinguished, and the homeostatic activity of the cell membrane sodium/potassium pump (Na⁺,K⁺,ATPase) detected. The mechanism allowing ¹H₂O MRI to do this is the newly discovered active transmembrane water cycling (AWC) phenomenon, which we found using paramagnetic extracellular contrast agents at clinical B₀ values. AWC is important because Na⁺,K⁺,ATPase can be considered biology’s most vital enzyme, and its in vivo steady‐state activity has not before been measurable, let alone amenable to mapping with high spatial resolution. Recent reports indicate AWC correlates with neuronal firing rate, with malignant tumor metastatic potential, and inversely with cellular reducing equivalent fraction. We wish to systematize the ways AWC can be precisely measured.

Methods

We present a theoretical longitudinal relaxation analysis of considerable scope: it spans the low‐ and high–field situations.

Results

We show the NMR shutter‐speed organizing principle is pivotal in understanding how trans–membrane steady–state water exchange kinetics are manifest throughout the range. Our findings illuminate an aspect, apparent population inversion, which is crucial in understanding ultra‐low field results.

Conclusions

Without an appreciation of apparent population inversion, significant misinterpretations of future data are likely. These could have unfortunate diagnostic consequences.