Prediction of liver function by using magnetic resonance-based portal venous perfusion imaging

Differential hepatic avoidance radiation therapy: Proof of concept in hepatocellular carcinoma patients

PURPOSE

To evaluate the feasibility of a novel planning concept that differentially redistributes RT dose away from functional liver regions as defined by (99m)Tc-sulphur colloid (SC) uptake on patient SPECT/CT images.

MATERIALS AND METHODS

Ten HCC patients with different Child-Turcotte-Pugh scores (A5-B9) underwent SC SPECT/CT scans in treatment position prior to RT that were registered to planning CT scans. Proton pencil beam scanning (PBS) therapy plans were optimized to deliver 37.5-60.0Gy (RBE) over 5-15 fractions using single field uniform dose technique robust to range and setup uncertainty. Photon volumetrically modulated arc therapy (VMAT) plans were optimized to the same prescribed dose and minimum target coverage. For both treatment modalities, differential hepatic avoidance RT (DHART) plans were generated to decrease dose to functional liver volumes (FLV) defined by a range of thresholds relative to maximum SC uptake (43-90%) in the tumor-subtracted liver. Radiation dose was redistributed away from regions of increased SC uptake in each FLV by linearly scaling mean dose objectives during PBS or VMAT optimization. DHART planning feasibility was assessed by a significantly negative Spearman's rank correlation (RS) between dose difference and SC uptake. Patient, tumor, and treatment planning characteristics were tested for association to DHART planning feasibility using non-parametric Kruskal-Wallis ANOVA.

RESULTS

Compared to conventional plans, DHART plans achieved a 3% FLV dose reduction for every 10% SC uptake increase. DHART planning was feasible in the majority of patients with 60% of patients having RS<-0.5 (p<0.01, range -1.0 to 0.2) and was particularly effective in 30% of patients (RS<-0.9). Mean dose to FLV was reduced by up to 20% in these patients. Only fractionation regimen was associated with DHART planning feasibility: 15 fraction courses were more feasible than 5-6 fraction courses (RS<-0.93 vs. RS>-0.60, p<0.02).

CONCLUSION

Differential avoidance of functional liver regions defined on sulphur colloid SPECT/CT is achievable with either photon VMAT or proton PBS therapy. Further investigation with phantom studies and in a larger cohort of patients may validate the utility of DHART planning for HCC radiotherapy.

4DCT Simulation With Synchronized Contrast Injection in Liver SBRT Patients

BACKGROUND/PURPOSE

Delivering stereotactic body radiotherapy for liver metastases remains a challenge because of respiratory motion and poor visibility without intravenous contrast. The purpose of this article is to describe a novel and simple computed tomography (CT) simulation process of integrating timed intravenous contrast that could overcome the uncertainty of target delineation.

METHODS AND RESULTS

The simulation involves two 4-dimensional CT (4DCT) scans. The first scan only encompasses the immediate region of the tumor and surrounding tissue, which reduces the 4DCT scan time so that it can be optimally timed with intravenous contrast injection. The second 4DCT scan covers a larger volume and is used as the primary CT data set for dose calculation, as well as patient setup verification on the treatment unit. The combination of the two 4DCT scans allows us to optimally visualize liver metastases over all phases of the breathing cycle while simultaneously acquiring a long enough 4DCT data set that is suitable for planning and patient setup verification.

CONCLUSION

This simulation technique allows for a better target definition when treating liver metastases, without being invasive.

Dynamic contrast-enhanced magnetic resonance imaging: applications in oncology

Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) allows functional characterisation of tissue perfusion characteristics and acts as a biomarker for tumour angiogenesis. It involves serial acquisition of MRI images before and after injection of contrast, as such, tissue perfusion and permeability can be assessed based on the signal enhancement kinetics. The ability to evaluate whole tumour volumes in a non-invasive manner makes DCE MRI especially attractive for potential oncological applications. Here we provide an overview of the current research involving DCE MRI as a biomarker for the diagnosis and characterisation of malignancies, prediction of the therapeutic response and survival outcomes, as well as radiation therapy planning.

Arterial perfusion imaging-defined subvolume of intrahepatic cancer

PURPOSE

To assess whether an increase in a subvolume of intrahepatic tumor with elevated arterial perfusion during radiation therapy (RT) predicts tumor progression after RT.

METHODS AND MATERIALS

Twenty patients with unresectable intrahepatic cancers undergoing RT were enrolled in a prospective, institutional review board-approved study. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was performed before RT (pre-RT), after delivering ∼60% of the planned dose (mid-RT) and 1 month after completion of RT to quantify hepatic arterial perfusion. The arterial perfusions of the tumors at pre-RT were clustered into low-normal and elevated perfusion by a fuzzy clustering-based method, and the tumor subvolumes with elevated arterial perfusion were extracted from the hepatic arterial perfusion images. The percentage changes in the tumor subvolumes and means of arterial perfusion over the tumors from pre-RT to mid-RT were evaluated for predicting tumor progression post-RT.

RESULTS

Of the 24 tumors, 6 tumors in 5 patients progressed 5 to 21 months after RT completion. Neither tumor volumes nor means of tumor arterial perfusion at pre-RT were predictive of treatment outcome. The mean arterial perfusion over the tumors increased significantly at mid-RT in progressive tumors compared with the responsive tumors (P=.006). From pre-RT to mid-RT, the responsive tumors had a decrease in the tumor subvolumes with elevated arterial perfusion (median, -14%; range, -75% to 65%), whereas the progressive tumors had an increase of the subvolumes (median, 57%; range, -7% to 165%) (P=.003). Receiver operating characteristic analysis of the percentage change in the subvolume for predicting tumor progression post-RT had an area under the curve of 0.90.

CONCLUSION

The increase in the subvolume of the intrahepatic tumor with elevated arterial perfusion during RT has the potential to be a predictor for tumor progression post-RT. The tumor subvolume could be a radiation boost candidate for response-driven adaptive RT.

Predictive models for regional hepatic function based on 99mTc-IDA SPECT and local radiation dose for physiologic adaptive radiation therapy

PURPOSE

High-dose radiation therapy (RT) for intrahepatic cancer is limited by the development of liver injury. This study investigated whether regional hepatic function assessed before and during the course of RT using 99mTc-labeled iminodiacetic acid (IDA) single photon emission computed tomography (SPECT) could predict regional liver function reserve after RT.

METHODS AND MATERIALS

Fourteen patients treated with RT for intrahepatic cancers underwent dynamic 99mTc-IDA SPECT scans before RT, during, and 1 month after completion of RT. Indocyanine green (ICG) tests, a measure of overall liver function, were performed within 1 day of each scan. Three-dimensional volumetric hepatic extraction fraction (HEF) images of the liver were estimated by deconvolution analysis. After coregistration of the CT/SPECT and the treatment planning CT, HEF dose-response functions during and after RT were generated. The volumetric mean of the HEFs in the whole liver was correlated with ICG clearance time. Three models, dose, priori, and adaptive models, were developed using multivariate linear regression to assess whether the regional HEFs measured before and during RT helped predict regional hepatic function after RT.

RESULTS

The mean of the volumetric liver HEFs was significantly correlated with ICG clearance half-life time (r=-0.80, P<.0001), for all time points. Linear correlations between local doses and regional HEFs 1 month after RT were significant in 12 patients. In the priori model, regional HEF after RT was predicted by the planned dose and regional HEF assessed before RT (R=0.71, P<.0001). In the adaptive model, regional HEF after RT was predicted by regional HEF reassessed during RT and the remaining planned local dose (R=0.83, P<.0001).

CONCLUSIONS

99mTc-IDA SPECT obtained during RT could be used to assess regional hepatic function and helped predict post-RT regional liver function reserve. This could support individualized adaptive radiation treatment strategies to maximize tumor control and minimize the risk of liver damage.

GPU-accelerated voxelwise hepatic perfusion quantification

Voxelwise quantification of hepatic perfusion parameters from dynamic contrast enhanced (DCE) imaging greatly contributes to assessment of liver function in response to radiation therapy. However, the efficiency of the estimation of hepatic perfusion parameters voxel-by-voxel in the whole liver using a dual-input single-compartment model requires substantial improvement for routine clinical applications. In this paper, we utilize the parallel computation power of a graphics processing unit (GPU) to accelerate the computation, while maintaining the same accuracy as the conventional method. Using compute unified device architecture-GPU, the hepatic perfusion computations over multiple voxels are run across the GPU blocks concurrently but independently. At each voxel, nonlinear least-squares fitting the time series of the liver DCE data to the compartmental model is distributed to multiple threads in a block, and the computations of different time points are performed simultaneously and synchronically. An efficient fast Fourier transform in a block is also developed for the convolution computation in the model. The GPU computations of the voxel-by-voxel hepatic perfusion images are compared with ones by the CPU using the simulated DCE data and the experimental DCE MR images from patients. The computation speed is improved by 30 times using a NVIDIA Tesla C2050 GPU compared to a 2.67 GHz Intel Xeon CPU processor. To obtain liver perfusion maps with 626 400 voxels in a patient's liver, it takes 0.9 min with the GPU-accelerated voxelwise computation, compared to 110 min with the CPU, while both methods result in perfusion parameters differences less than 10(-6). The method will be useful for generating liver perfusion images in clinical settings.