Optimizing global liver function in radiation therapy treatment planning

Analysis and prediction of liver volume change maps derived from computational tomography scans acquired pre- and post-radiation therapy

External beam radiation therapy (EBRT) of liver cancers can cause local liver atrophy as a result of tissue damage or hypertrophy as a result of liver regeneration. Predicting those volumetric changes would enable new strategies for liver function preservation during treatment planning. However, understanding of the spatial dose/volume relationship is still limited. This study leverages the use of deep learning-based segmentation and biomechanical deformable image registration (DIR) to analyze and predict this relationship. Pre- and Post-EBRT imaging data were collected for 100 patients treated for hepatocellular carcinomas, cholangiocarcinoma or CRC with intensity-modulated radiotherapy (IMRT) with prescription doses ranging from 50 to 100 Gy delivered in 10-28 fractions. For each patient, DIR between the portal and venous (PV) phase of a diagnostic computed tomography (CT) scan acquired before radiation therapy (RT) planning, and a PV phase of a diagnostic CT scan acquired after the end of RT (on average 147 ± 36 d) was performed to calculate Jacobian maps representing volume changes in the liver. These volume change maps were used: (i): to analyze the dose/volume relationship in the whole liver and individual Couinaud's segments; and (ii): to investigate the use of deep-learning to predict a Jacobian map solely based on the pre-RT diagnostic CT and planned dose distribution. Moderate correlations between mean equivalent dose in 2 Gy fractions (EQD2) and volume change was observed for all liver sub-regions analyzed individually with Pearson correlationrranging from -0.36 to -067. The predicted volume change maps showed a significantly stronger voxel-wise correlation with the DIR-based volume change maps than when considering the original EQD2 distribution (0.63 ± 0.24 versus 0.55 ± 23, respectively), demonstrating the ability of the proposed approach to establish complex relationships between planned dose and liver volume response months after treatment, which represents a promising prediction tool for the development of future adaptive and personalized liver radiation therapy strategies.

The Effect of Stereotactic Body Radiation Therapy for Hepatocellular Cancer on Regional Hepatic Liver Function

PURPOSE

To investigate direct radiation dose-related and inflammation-mediated regional hepatic function losses after stereotactic body radiation therapy (SBRT) in patients with hepatocellular carcinoma (HCC) and poor liver function.

METHODS AND MATERIALS

Twenty-four patients with HCC enrolled on an IRB-approved adaptive SBRT trial had liver dynamic gadoxetic acid-enhanced magnetic resonance imaging and blood sample collections before and 1 month after SBRT. Gadoxetic acid uptake rate (k1) maps were quantified for regional hepatic function and coregistered to both 2-Gy equivalent dose and physical dose distributions. Regional k1 loss patterns from before to after SBRT were analyzed for effects of dose and patient using a mixed-effects model and logistic function and were associated with pretherapy liver-function albumin-bilirubin scores. Plasma levels of tumor necrosis factor α receptor 1 (TNFR1), an inflammation marker, were correlated with mean k1 losses in the lowest dose regions by Spearman rank correlation.

RESULTS

The whole group had a k1 loss rate of 0.4%/Gy (2-Gy equivalent dose); however, there was a significant random effect of patient in the mixed-effect model (P < .05). Patients with poor and good liver functions lost 50% of k1 values at 12.5 and 57.2 Gy and 33% and 16% of k1 values at the lowest dose regions (<5 Gy), respectively. The k1 losses at the lowest dose regions of individual patients were significantly correlated with their TNFR1 levels after SBRT (P < .02).

CONCLUSIONS

The findings suggest that regional hepatic function losses after SBRT in patients with HCC include both direct radiation dose-dependent and inflammation-mediated effects, which could influence how to manage these patients to preserve their liver function after SBRT.

Role of Functional MRI in Liver SBRT: Current Use and Future Directions

Stereotactic body radiation therapy (SBRT) is an emerging treatment for liver cancers whereby large doses of radiation can be delivered precisely to target lesions in 3-5 fractions. The target dose is limited by the dose that can be safely delivered to the non-tumour liver, which depends on the baseline liver functional reserve. Current liver SBRT guidelines assume uniform liver function in the non-tumour liver. However, the assumption of uniform liver function is false in liver disease due to the presence of cirrhosis, damage due to previous chemo- or ablative therapies or irradiation, and fatty liver disease. Anatomical information from magnetic resonance imaging (MRI) is increasingly being used for SBRT planning. While its current use is limited to the identification of target location and size, functional MRI techniques also offer the ability to quantify and spatially map liver tissue microstructure and function. This review summarises and discusses the advantages offered by functional MRI methods for SBRT treatment planning and the potential for adaptive SBRT workflows.

Gadoxetic Acid Uptake Rate as a Measure of Global and Regional Liver Function as Compared to Indocyanine Green Retention, Albumin-Bilirubin Score, and Portal Venous Perfusion

Purpose

Global and regional liver function assessments are important for defining the magnitude and spatial distribution of dose to preserve functional liver parenchyma and reduce incidence of hepatotoxicity from radiation therapy for intrahepatic cancer treatment. This individualized liver function-guided radiation therapy strategy is critical for patients with heterogeneous and poor liver function, often observed in cirrhotic patients treated for hepatocellular carcinoma. This study aimed to validate k₁ as a measure of global and regional function through comparison with 2 well-regarded global function measures: indocyanine green retention (ICGR) and albumin-bilirubin (ALBI).

Methods and Materials

Seventy-nine dynamic gadoxetic acid enhanced magnetic resonance imaging scans were acquired in 40 patients with hepatocellular carcinoma in institutional review board approved prospective protocols. Portal venous perfusion (k_pv) was quantified from gadoxetic acid enhanced magnetic resonance imaging using a dual-input 2-compartment model, and gadoxetic acid uptake rate (k₁) was fitted using a linearized single-input 2-compartment model chosen for robust k₁ estimation. Four image-derived measures of global liver function were tested: (1) mean k₁ multiplied by liver volume (k₁V_L) (functional volume), (2) mean k₁ multiplied by blood distribution volume (k₁V_dis)_, (3) mean k_pv, and (4) liver volume (V_L). The measure's correlation with corresponding ICGR and ALBI tests was assessed using linear regression. Voxel-wise similarity between k₁ and k_pv was compared using Spearman ranked correlation.

Results

Significant correlations (P < .05) with ICGR and ALBI were found for k₁V_L, k₁V_dis, and V_L (in order of strength), but not for mean k_pv. The mean ranked correlation coefficient between k₁ and k_pv maps was 0.09. k₁ and k_pv maps were predominantly mismatched in patients with poor liver function.

Conclusions

The metric combining function and liver volume (k₁V_L) was a stronger measure of global liver function compared with perfusion or liver volume alone, especially in patients with poor liver function. Gadoxetic acid uptake rate is promising for both global and regional liver function.

GAN and dual-input two-compartment model-based training of a neural network for robust quantification of contrast uptake rate in gadoxetic acid-enhanced MRI

PURPOSE

Gadoxetic acid uptake rate (k₁ ) obtained from dynamic, contrast-enhanced (DCE) magnetic resonance imaging (MRI) is a promising measure of regional liver function. Clinical exams are typically poorly temporally characterized, as seen in a low temporal resolution (LTR) compared to high temporal resolution (HTR) experimental acquisitions. Meanwhile, clinical demands incentivize shortening these exams. This study develops a neural network-based approach to quantitation of k₁ , for increased robustness over current models such as the linearized single-input, two-compartment (LSITC) model.

METHODS

Thirty Liver HTR DCE MRI exams were acquired in 22 patients with at least 16 min of postcontrast data sampled at least every 13 s. A simple neural network (NN) with four hidden layers was trained on voxel-wise LTR data to predict k₁ . Low temporal resolution data were created by subsampling HTR data to contain six time points, replicating the characteristics of clinical LTR data. Both the total length and the placement of points in the training data were varied considerably to encourage robustness to variation. A generative adversarial network (GAN) was used to generate arterial and portal venous inputs for use in data augmentation based on the dual-input, two-compartment, pharmacokinetic model of gadoxetic acid in the liver. The performance of the NN was compared to direct application of LSITC on both LTR and HTR data. The error was assessed when subsampling lengths from 16 to 4 min, enabling assessment of robustness to acquisition length.

RESULTS

For acquisition lengths of 16 min NRMSE (Normalized Root-Mean-Squared Error) in k₁ was 0.60, 1.77, and 1.21, for LSITC applied to HTR data, LSITC applied to LTR data, and GAN-augmented NN applied to LTR data, respectively. As the acquisition length was shortened, errors greatly increased for LSITC approaches by several folds. For acquisitions shorter than 12 min the GAN-augmented NN approach outperformed the LSITC approach to a statistically significant extent, even with HTR data.

CONCLUSIONS

The study indicates that data length is significant for LSITC analysis as applied to DCE data for standard temporal sampling, and that machine learning methods, such as the implemented NN, have potential for much greater resilience to shortened acquisition time than directly fitting to the LSITC model.

Functional Adaptation in Radiation Therapy

The promise of adaptive therapy to improve outcomes in radiation oncology has been an area of interest and research in the community for many years. One of the sources of data that can be used to drive adaptive therapy is functional information about the tumor or normal tissues. This avenue of adaptation includes many potential sources of data including global markers and functional imaging. Global markers can be assessments derived from blood measurements, patient functional testing, and circulating tumor material and functional imaging data comprises spatial physiological information from various imaging studies such as positron emission tomography, magnetic resonance imaging, and single photon emission computed tomography. The goal of functional adaptation is to use these functional data to adapt radiation therapy to improve patient outcomes. While functional adaptation holds a lot of promise, there are challenges such as quantifying and minimizing uncertainties, streamlining clinical implementation, determining the ideal way to incorporate information within treatment plan optimization, and proving the clinical benefit through trials. This paper will discuss the types of functional information currently being used for adaptation, highlight several areas where functional adaptation has been studied, and introduce some of the barriers to more widespread clinical implementation.

Modeling of Normal Tissue Complications Using Imaging and Biomarkers After Radiation Therapy for Hepatocellular Carcinoma

PURPOSE

To develop normal tissue complications (NTCP) models for hepatocellular cancer (HCC) patients who undergo liver radiation therapy (RT) and to evaluate the potential role of functional imaging and measurement of blood-based circulating biological markers before and during RT to improve the performance of these models.

METHODS AND MATERIALS

The data from 192 HCC patients who had undergone RT from 2005 to 2014 were evaluated. Of the 192 patients, 146 had received stereotactic body RT (SBRT) and 46 had received conventional RT to a median physical tumor dose of 49.8 Gy and 50.4 Gy, respectively. The physical doses were converted into 2-Gy equivalents for analysis. Two approaches were investigated for modeling NTCP: (1) a generalized Lyman-Kutcher-Burman model; and (2) a generalization of the parallel architecture model. Three clinical endpoints were considered: the change in albumin-bilirubin (ALBI), change in Child-Pugh (C-P) score, and grade ≥3 liver enzymatic changes. Local dynamic contrast-enhanced magnetic resonance imaging portal venous perfusion information was used as an imaging biomarker for local liver function. Four candidate inflammatory cytokines were considered as biological markers. The imaging findings and cytokine levels were incorporated into NTCP modeling, and their role was evaluated using goodness-of-fit metrics.

RESULTS

Using dosimetric information only, the Lyman-Kutcher-Burman model for the ALBI/C-P change had a steeper response curve compared with grade ≥3 enzymatic changes. Incorporating portal venous perfusion imaging information into the parallel architecture model to represent functional reserve resulted in relatively steeper dose-response curves compared with dose-only models. A larger loss of perfusion function was needed for enzymatic changes compared with ALBI/C-P changes. Increased transforming growth factor-β1 and eotaxin expression increased the trend of expected risk in both NTCP modeling approaches but did not reach statistical significance.

CONCLUSIONS

The incorporation of imaging findings and biological markers into NTCP modeling of liver toxicity improved the estimates of expected NTCP risk compared with using dose-only models. In addition, such generalized NTCP models should contribute to a better understanding of the normal tissue response in HCC SBRT patients and facilitate personalized treatment.

Radiation-Induced Liver Disease and Modern Radiotherapy

Modern radiotherapy techniques have enabled high focal doses of radiation to be delivered to patients with primary and secondary malignancies of the liver. The current clinical practice of radiation oncology has benefitted from decades of research that have informed how to achieve excellent local control and survival outcomes with minimal toxicities. Still, one of the most devastating consequences of radiation to the liver remains a challenge: radiation-induced liver disease (RILD). Here, we will review the current understanding of classic and nonclassic RILD from a clinical perspective, the evaluation and management of patients who are at risk of developing RILD, methods to reduce the likelihood of RILD using modern radiation techniques, and the diagnosis and treatment of radiation-related liver toxicities.

Quantification of liver function by linearization of a two-compartment model of gadoxetic acid uptake using dynamic contrast-enhanced magnetic resonance imaging

Dynamic gadoxetic acid-enhanced magnetic resonance imaging (MRI) allows the investigation of liver function through the observation of the perfusion and uptake of contrast agent in the parenchyma. Voxel-by-voxel quantification of the contrast uptake rate (k₁ ) from dynamic gadoxetic acid-enhanced MRI through the standard dual-input, two-compartment model could be susceptible to overfitting of variance in the data. The aim of this study was to develop a linearized, but more robust, model. To evaluate the estimated k₁ values using this linearized analysis, high-temporal-resolution gadoxetic acid-enhanced MRI scans were obtained in 13 examinations, and k₁ maps were created using both models. Comparison of liver k₁ values estimated from the two methods produced a median correlation coefficient of 0.91 across the 12 scans that could be used. Temporally sparse clinical MRI data with gadoxetic acid uptake were also employed to create k₁ maps of 27 examinations using the linearized model. Of 20 scans, the created k₁ maps were compared with overall liver function as measured by indocyanine green (ICG) retention, and yielded a correlation coefficient of 0.72. In the 27 k₁ maps created via the linearized model, the mean liver k₁ value was 3.93 ± 1.79 mL/100 mL/min, consistent with previous studies. The results indicate that the linearized model provides a simple and robust method for the assessment of the rate of contrast uptake that can be applied to both high-temporal-resolution dynamic contrast-enhanced MRI and typical clinical multiphase MRI data, and that correlates well with the results of both two-compartment analysis and independent whole liver function measurements.

Integration of PET/MR Hybrid Imaging into Radiation Therapy Treatment

Hybrid PET/MR imaging is in early development for treatment planning. This article briefly reviews research and clinical applications of PET/MR imaging in radiation oncology. With improvements in workflow, more specific tracers, and fast and robust acquisition protocols, PET/MR imaging will play an increasingly important role in better target delineation for treatment planning and have clear advantages in the evaluation of tumor response and in a better understanding of tumor heterogeneity. With advances in treatment delivery and the potential of integrating PET/MR imaging with research on radiomics for radiation oncology, quantitative and physiologic information could lead to more precise and personalized RT.