Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models

Model discovery approach enables noninvasive measurement of intra-tumoral fluid transport in dynamic MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to noninvasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that our method will contribute to the better understanding of cancer progression and therapeutic response.

Quantitative hemodynamic assessment of stenotic below-the-knee arteries using spatio-temporal bolus tracking on 4D-CT angiography

BACKGROUND

Peripheral arterial disease (PAD) is a chronic occlusive disease that restricts blood flow in the lower limbs, causing partial or complete blockages of the blood flow. While digital subtraction angiography (DSA) has traditionally been the preferred method for assessing blood flow in the lower limbs, advancements in wide beam Computed Tomography (CT), allowing successive acquisition at high frame rate, might enable hemodynamic measurements.

PURPOSE

To quantify the arterial blood flow in stenotic below-the-knee (BTK) arteries. To this end, we propose a novel method for contrast bolus tracking and assessment of quantitative hemodynamic parameters in stenotic arteries using 4D-CT.

METHODS

Fifty patients with suspected PAD underwent 4D-CT angiography in addition to the clinical run-off computed tomography angiography (CTA). From these dynamic acquisitions, the BTK arteries were segmented and the region of maximum blood flow was extracted. Time attenuation curves (TAC) were estimated using 2D spatio-temporal B-spline regression, enforcing both spatial and temporal smoothness. From these curves, quantitative hemodynamic parameters, describing the shape of the propagating contrast bolus were automatically extracted. We evaluated the robustness of the proposed TAC fitting method with respect to interphase delay and imaging noise and compared it to commonly used approaches. Finally, to illustrate the potential value of 4D-CT, we assessed the correlation between the obtained hemodynamic parameters and the presence of PAD.

RESULTS

280 out of 292 arteries were successfully segmented, with failures mainly due to a delayed contrast arrival. The proposed method led to physiologically plausible hemodynamic parameters and was significantly more robust compared to 1D temporal regression. A significant correlation between the presence of proximal stenoses and several hemodynamic parameters was found.

CONCLUSIONS

The proposed method based on spatio-temporal bolus tracking was shown to lead to stable and physiologically plausible estimation of quantitative hemodynamic parameters, even in the case of stenotic arteries. These parameters may provide valuable information in the evaluation of PAD and contribute to its diagnosis.

Model discovery approach enables non-invasive measurement of intra-tumoral fluid transport in dynamic MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to non-invasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that it will contribute to the better understanding of cancer progression and therapeutic response.

High Doses of Photons and Carbon Ions Comparably Increase Vascular Permeability in R3327-HI Prostate Tumors: A Dynamic Contrast-Enhanced MRI Study

Carbon- (12C-) ion radiotherapy exhibits enhanced biological effectiveness compared to photon radiotherapy, however, the contribution of its interaction with the vasculature remains debatable. The effect of high-dose 12C-ion and photon irradiation on vascular permeability in moderately differentiated rat prostate tumors was compared using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Syngeneic R3327-HI rat prostate tumors were irradiated with a single dose of either 18 or 37 Gy 12C ions, or 37 or 75 Gy 6-MV photons (sub-curative and curative dose levels, respectively). DCE-MRI was performed one day prior to and 3, 7, 14 and 21 days postirradiation. Voxel-based tumor concentration-time curves were clustered based on their curve shape and treatment response was assessed as the longitudinal changes in the relative abundance per cluster. Radiation-induced vascular damage and increased permeability occurred at day 7 postirradiation for all treatment groups except for the 75 Gy photon-irradiated group, where the onset of vascular damage was delayed until day 14. No differences between irradiation modalities were found. Therefore, early vascular damage cannot explain the higher effectiveness of 12C ions relative to photons in terms of local tumor control for this moderately differentiated prostate tumor and the applied single high doses.

Estimation of pharmacokinetic parameters from DCE-MRI by extracting long and short time-dependent features using an LSTM network

PURPOSE

T₁ -weighted dynamic contrast-enhanced Magnetic Resonance Imaging (DCE-MRI) is typically quantified by least squares (LS) fitting to a pharmacokinetic (PK) model to yield parameters of microvasculature and perfusion in normal and disease tissues. Such fitting is both time-consuming as well as subject to inaccuracy and instability in parameter estimates. Here, we propose a novel neural network approach to estimate the PK parameters by extracting long and short time-dependent features in DCE-MRI.

METHODS

A Long Short-Term Memory (LSTM) network, widely used for processing sequence data, was employed to map DCE-MRI time-series accompanied with an arterial input function to parameters of the extended Tofts model. Head and neck DCE-MRI from 103 patients were used for training and testing the LSTM model. Arterial input functions (AIFs) from 78 patients were used to generate synthetic DCE-MRI time-series for training, during which data augmentation was used to overcome the limited size of in vivo data. The model was tested on independent synthesized DCE data using AIFs from 25 patients. The LSTM performance was optimized for the numbers of layers and hidden state features. The performance of the LSTM was tested for different temporal resolution, total acquisition time, and contrast-to-noise ratio (CNR), and compared to the conventional LS fitting and a CNN-based method.

RESULTS

Compared to LS fitting, the LSTM model had comparable accuracy in PK parameter estimations from fully temporal-sampled DCE-MRI data (~3 s per frame), but much better accuracy for the data with temporally subsampling (4s or greater per frame), total acquisition time truncation by 48%-16%, or low CNR (5 and 10). The LSTM reduced normalized root mean squared error by 40.4%, 46.9%, and 53.0% for sampling intervals of 4s, 5s, and 6s, respectively, compared to LS fitting. Compared to the CNN model, the LSTM model reduced the error in the parameter estimates up to 55.2%. Also, the LSTM improved the inference time by ~ 14 times on CPU compared to LS fitting.

CONCLUSION

Our study suggests that the LSTM model could achieve improved robustness and computation speed for PK parameter estimation compared to LS fitting and the CNN based network, particularly for suboptimal data.

Impact of Single Dose Photons and Carbon Ions on Perfusion and Vascular Permeability: A Dynamic Contrast-Enhanced MRI Pilot Study in the Anaplastic Rat Prostate Tumor R3327-AT1

We collected initial quantitative information on the effects of high-dose carbon (¹²C) ions compared to photons on vascular damage in anaplastic rat prostate tumors, with the goal of elucidating differences in response to high-LET radiation, using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Syngeneic R3327-AT1 rat prostate tumors received a single dose of either 16 or 37 Gy ¹²C ions or 37 or 85 Gy 6 MV photons (iso-absorbed and iso-effective doses, respectively). The animals underwent DCE-MRI prior to, and on days 3, 7, 14 and 21 postirradiation. The extended Tofts model was used for pharmacokinetic analysis. At day 21, tumors were dissected and histologically examined. The results of this work showed the following: 1. ¹²C ions led to stronger vascular changes compared to photons, independent of dose; 2. Tumor growth was comparable for all radiation doses and modalities until day 21; 3. Nonirradiated, rapidly growing control tumors showed a decrease in all pharmacokinetic parameters (area under the curve, K_trans, v_e, v_p) over time; 4. ¹²C-ion-irradiated tumors showed an earlier increase in area under the curve and K_trans than photon-irradiated tumors; 5. ¹²C-ion irradiation resulted in more homogeneous parameter maps and histology compared to photons; and 6. ¹²C-ion irradiation led to an increased microvascular density and decreased proliferation activity in a largely dose-independent manner compared to photons. Postirradiation changes related to ¹²C ions and photons were detected using DCE-MRI, and correlated with histological parameters in an anaplastic experimental prostate tumor. In summary, this pilot study demonstrated that exposure to ¹²C ions increased the perfusion and/or permeability faster and led to larger changes in DCE-MRI parameters resulting in increased vessel density and presumably less hypoxia at the end of the observation period when compared to photons. Within this study no differences were found between curative and sub-curative doses in either modality.