Local and Global Function Model of the Liver

Current Insights into Molecular Mechanisms and Potential Biomarkers for Treating Radiation-Induced Liver Damage

Highly conformal delivery of radiation therapy (RT) has revolutionized the treatment landscape for primary and metastatic liver cancers, yet concerns persist regarding radiation-induced liver disease (RILD). Despite advancements, RILD remains a major dose-limiting factor due to the potential damage to normal liver tissues by therapeutic radiation. The toxicity to normal liver tissues is associated with a multitude of physiological and pathological consequences. RILD unfolds as multifaceted processes, intricately linking various responses, such as DNA damage, oxidative stress, inflammation, cellular senescence, fibrosis, and immune reactions, through multiple signaling pathways. The DNA damage caused by ionizing radiation (IR) is a major contributor to the pathogenesis of RILD. Moreover, current treatment options for RILD are limited, with no established biomarker for early detection. RILD diagnosis often occurs at advanced stages, highlighting the critical need for early biomarkers to adjust treatment strategies and prevent liver failure. This review provides an outline of the diverse molecular and cellular mechanisms responsible for the development of RILD and points out all of the available biomarkers for early detection with the aim of helping clinicians decide on advance treatment strategies from a single literature recourse.

Time variation of high-risk groups for liver function deteriorations within fluctuating long-term liver function after hepatic radiotherapy in patients with hepatocellular carcinoma

PURPOSE

The purpose of this study is to find essential risk factors associated with liver function (LF) deteriorations within fluctuating long-term LF and their time-varying effects in patients with hepatocellular carcinoma (HCC) receiving hepatic radiotherapy and to identify high-risk groups for adverse LF deteriorations and their changes over time in facilitating the prevention of hepatic decompensation and the improvement of survival.

MATERIALS AND METHODS

A total of 133 HCC patients treated by hepatic radiotherapy were enrolled. A study design was conducted to convert posttreatment long-term LF with fluctuating levels over time to recurrent LF events using defined upgrades in a grading scale. The hazard ratios (HR) of pretreatment biochemical, demographic, clinical, and dosimetric factors in developing posttreatment LF events were estimated using the Cox model. Methodologies of the counting process approach, robust variance estimation, goodness-of-fit testing based on the Schoenfeld residuals, and time-dependent covariates in survival analysis were employed to handle the correlation within subjects and evaluate the time-varying effects during long-term follow-up.

RESULTS

Baseline LF score before radiotherapy and gender were significant factors. Initial HR in developing LF events was 1.17 (95% CI 1.11-1.23; P < 0.001) for each increase of baseline LF score and kept almost constant over time (HR, 1.00; 95% CI 1.00-1.01; P = 0.065). However, no difference was observed regarding initial hazards for gender (HR, 1.00; 95% CI 0.64-1.56; P = 0.994), but the hazard for women got higher monthly over time compared with men (HR, 1.04; 95% CI 1.01-1.07; P = 0.006).

CONCLUSIONS

High-risk groups for adverse LF deteriorations after hepatic radiotherapy may change over time. Patients with poor baseline LF are vulnerable from the beginning. Women require prevention strategies and careful monitoring for deteriorations at a later stage.

Efficacy of a Second Course of Radiation for Patients With Metachronous Hepatocellular Carcinoma

PURPOSE

Liver-directed radiation therapy is an effective treatment for hepatocellular carcinoma (HCC), but metachronous lesions develop outside the irradiated field in >50% of patients. We hypothesized that irradiation of these new lesions would produce an outcome like that of patients receiving a first course (C1) of treatment.

METHODS AND MATERIALS

We included patients with HCC who received a second course (C2) of radiation therapy >1 month after C1. Toxicity was defined as Child-Pugh score increase ≥2 within 6 months posttreatment (binary model) and as the change in albumin-bilirubin during the year after treatment (longitudinal model). Overall survival (OS) and local failure (LF) were captured at the patient and lesion level, respectively; both were summarized with Kaplan-Meier estimates. Predictors of toxicity and OS were assessed using generalized linear mixed and Cox regression models, respectively.

RESULTS

Of 340 patients with HCC, 47 underwent irradiation for metachronous HCC, receiving similar prescription dose in C1/C2. Median follow-up was 17 months after C1 and 15 months after C2. Twenty-two percent of patients experienced toxicity after C1, and 25% experienced toxicity after C2. Worse baseline albumin-bilirubin predicted toxicity in both binary (odds ratio, 2.40; 95% CI, 1.46-3.94; P = .0005) and longitudinal models (P < .005). Two-year LF rate was 11.2% after C1 and 8.3% after C2; tumor dose (hazard ratio [HR], 0.982; 95% CI, 0.969-0.995; P = .007) and tumor size (HR, 1.135; 95% CI, 1.068-1.206; P < .005) predicted LF. Two-year OS was 46.0% after C1 and 42.6% after C2; tumor dose (HR, 0.986; 95% CI, 0.979-0.992; P < .005) and tumor size (HR, 1.049; 95% CI, 1.010-1.088; P = .0124) predicted OS. Reirradiation was not associated with toxicity (P > .7), LF (P = .79), or OS (P = .39).

CONCLUSIONS

In this largest series in the Western hemisphere, we demonstrate that irradiation for metachronous HCC offers low rates of LF with acceptable toxicity and OS like that of patients receiving a C1. These findings support judicious selection of patients for reirradiation in metachronous HCC.

Evolution of Response-Based Radiotherapy for Hepatocellular Cancer

ABSTRACT

Stereotactic body radiation therapy has emerged as a safe and effective treatment modality for properly selected hepatocellular cancer (HCC) patients with normal liver function. However, many HCC patients have reduced baseline liver function due to underlying cirrhosis or prior liver-directed therapies. Therefore, because of the increased risk of hepatotoxicity, the use of stereotactic body radiation therapy for patients with reduced liver function has been approached with caution. Individualized, response-based radiotherapy incorporates models, imaging tools, and biomarkers that determine the dose-response relationship of the liver before, during, and after treatment and has been useful in reducing the likelihood of liver damage without sacrificing tumor control. This review discusses the evolution of response-based radiotherapy for HCC and highlights areas for further investigation.

Prognostic Analysis of Single Large Hepatocellular Carcinoma Following Radical Resection: A Single-Center Study

Objective

To investigate the survival and independent prognostic factors for single large hepatocellular carcinoma (SLHCC) after surgical resection.

Methods

Patients with SLHCC who underwent radical resection from January 2013 to December 2017 were retrospectively analyzed. The Kaplan-Meier method was used to analyze the overall survival (OS) rate and recurrence-free survival (RFS) rates. Cox forward stepwise regression was performed to analyze the independent prognostic factors.

Results

A total of 485 cases were included. The average age was 51.2±11.2 years, 88.9% had a history of hepatitis B virus infection, and most patients had normal liver function. The average tumor diameter was 8.8±3.0 cm. The 1-, 3-, and 5-year OS and RFS rates were 76.8%, 56.7%, and 45.7%, and 61.0%, 46.2%, and 34.7%, respectively. Multivariate analysis showed that liver cirrhosis (HR=1.456, P=0.004), total bilirubin (TB) ≥17.1 μmol/L (HR=1.437, P=0.011), glutamyl transferase (GGT) >60 U/L (HR=1.438, P=0.020), lactate dehydrogenase (LDH) >225 U/L (HR=1.442, P=0.007), blood loss ≥400 mL (HR=1.339, P=0.027), microvascular invasion (MVI) (HR=1.492, P=0.004), satellite lesions (HR=1.859, P<0.0001) and Edmondson-Steiner grade III+IV (HR=1.740, P=0.018) were independent risk factors for reduced OS in SLHCC patients. Sex (HR=1.763, P=0.003), liver cirrhosis (HR=1.382, P=0.007), GGT >60 U/L (HR=1.512, P=0.003), LDH >225 U/L (HR=1.480, P=0.002), MVI (HR=1.545, P=0.001), and satellite lesions (HR=1.564, P=0.001) were independent risk factors for reduced RFS. OS and RFS nomograms were constructed using risk factors with C-index values of 0.692 (95% CI: 0.659-0.724) and 0.659 (95% CI: 0.623-0.693), respectively. The Hosmer-Leme test demonstrated the good fit of both nomograms.

Conclusion

Surgical resection is the standard and effective treatment for SLHCC patients. Sex, liver cirrhosis, TB≥17.1 μmol/L, GGT>60 U/L, LDH>225 U/L, blood loss≥400 mL, MVI, Edmondson-Steiner grade III+IV, and satellite lesions were found to be independent prognostic factors in SLHCC patients following radical resection. The OS and RFS nomograms accurately predicted the prognosis of SLHCC patients.

Proton Beam Therapy and Photon-Based Magnetic Resonance Image-Guided Radiation Therapy: The Next Frontiers of Radiation Therapy for Hepatocellular Carcinoma

External beam radiation therapy (EBRT) has increasingly been utilized in the treatment of hepatocellular carcinoma (HCC) due to technological advances with positive clinical outcomes. Innovations in EBRT include improved image guidance, motion management, treatment planning, and highly conformal techniques such as intensity-modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT). Moreover, proton beam therapy (PBT) and magnetic resonance image-guided radiation therapy (MRgRT) have expanded the capabilities of EBRT. PBT offers the advantage of minimizing low- and moderate-dose radiation to the surrounding normal tissue, thereby preserving uninvolved liver and allowing for dose escalation. MRgRT provides the advantage of improved soft tissue delineation compared to computerized tomography (CT) guidance. Additionally, MRgRT with online adaptive therapy is particularly useful for addressing motion not otherwise managed and reducing high-dose radiation to the normal tissue such as the stomach and bowel. PBT and online adaptive MRgRT are emerging technological advancements in EBRT that may provide a significant clinical benefit for patients with HCC.

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.

Evaluation of Pretreatment Magnetic Resonance Elastography for the Prediction of Radiation-Induced Liver Disease

Purpose

Magnetic resonance (MR) elastography (E) is a noninvasive technique for quantifying liver stiffness (LS) for fibrosis. This study evaluates whether LS is associated with risk of developing radiation-induced liver disease (RILD) in patients receiving liver-directed radiation therapy (RT).

Methods and Materials

Based on prior studies, LS ≤3 kPa was considered normal and LS >3.0 kPa as representing fibrosis. RILD was defined as an increase in Child-Pugh (CP) score of ≥2 from baseline within 1 year of RT. Univariate and multivariate Cox models were used to assess correlation.

Results

One hundred two patients, 51 with primary liver tumors and 51 with liver metastases, were identified with sufficient follow-up. In univariate models, pre-RT LS >3.0 kPa (hazard ratio [HR] 4.9; 95% confidence interval [CI], 1.6-14; P = .004), body mass index (BMI), clinical cirrhosis, CP score, albumin-bilirubin (ALBI) grade 2, primary liver tumor, and mean liver dose were significantly associated with risk of post-RT RILD. In a multivariate analysis, LS >3.0 and mean liver dose both were significantly associated with RILD risk.

Conclusions

Elevated pre-RT LS is associated with an increased risk of RILD in patients receiving liver-directed RT.

Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function

Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.

Volumetric prediction of breathing and slow drifting motion in the abdomen using radial MRI and multi-temporal resolution modeling

Abdominal organ motions introduce geometric uncertainties to radiotherapy. This study investigates a multi-temporal resolution 3D motion prediction scheme that accounts for both breathing and slow drifting motion in the abdomen in support of MRI-guided radiotherapy. Ten-minute MRI scans were acquired for 8 patients using a volumetric golden-angle stack-of-stars sequence. The first five-minutes was used for patient-specific motion modeling. Fast breathing motion was modeled from high temporal resolution radial k-space samples, which served as a navigator signal to sort k-space data into different bins for high spatial resolution reconstruction of breathing motion states. Slow drifting motion was modeled from a lower temporal resolution image time series which was reconstructed by sequentially combining a large number of breathing-corrected k-space samples. Principal components analysis (PCA) was performed on deformation fields between different motion states. Gaussian kernel regression and linear extrapolation were used to predict PCA coefficients of future motion states for breathing motion (340 ms ahead of acquisition) and slow drifting motion (8.5 s ahead of acquisition) respectively. k-space data from the remaining five-minutes was used to compare ground truth motions states obtained from retrospective reconstruction/deformation with predictions. Median distances between predicted and ground truth centroid positions of gross tumor volume (GTV) and organs at risk (OARs) were less than 1 mm on average. 95- percentile Hausdorff distances between predicted and ground truth GTV contours of various breathing motions states were 2 mm on average, which was smaller than the imaging resolution and 95-percentile Hausdorff distances between predicted and ground truth OAR contours of different slow drifting motion states were less than 0.2 mm. These results suggest that multi-temporal resolution motion models are capable of volumetric predictions of breathing and slow drifting motion with sufficient accuracy and temporal resolution for MRI-based tracking, and thus have potential for supporting MRI-guided abdominal radiotherapy.

Impact of adjuvant radiotherapy on biological and clinical parameters in right-sided breast cancer

PURPOSE

In patients with right-sided breast cancer (BC) the liver might be partially irradiated during adjuvant radiotherapy (RT). Thus, we performed a prospective observational study to evaluate the dose delivered to the liver, and its potential biological impact.

PATIENTS AND METHODS

We enrolled 34 patients with right-sided BC treated with adjuvant RT. The RT schedules were either the Canadian (42.5Gy in 16 fx) or standard fractionated (50Gy in 25 fx) regimen respectively with 9 (26.5%) and 25 (73.5%) patients each, ± a boost of 10-16Gy. Each patient had a complete blood count and liver enzymes analysis, before starting and during the last week of treatment.

RESULTS

A significant decrease in white blood cells and thrombocytes counts was observed during RT. We observed a significant correlation between certain hepatic parameters and the volume of the irradiated liver and/or the mean liver dose. A significant correlation between the volume of the right lung and the liver mean dose was found (P=0.008). In the bivariate analysis, a significant correlation between fatigue and the white blood cell count's evolution was observed (P<0.025).

CONCLUSION

With the standard RT technique, incidental irradiation of the liver was documented in a large number of patients, and some significant hepatic parameters alterations were observed, without an apparent clinical impact, but this study cannot exclude them. The liver mean dose was correlated with the right lung volume suggesting that deep inspiration breath hold (DIBH) techniques may represent a way to decrease the liver dose. These findings need to be evaluated in further larger studies.

Modeling intra-fractional abdominal configuration changes using breathing motion-corrected radial MRI

Abdominal organ motions introduce geometric uncertainties to gastrointestinal radiotherapy. This study investigated slow drifting motion induced by changes of internal anatomic organ arrangements using a 3D radial MRI sequence with a scan length of 20 min. Breathing motion and cyclic GI motion were first removed through multi-temporal resolution image reconstruction. Slow drifting motion analysis was performed using an image time series consisting of 72 image volumes with a temporal sampling rate of 17 s. B-spline deformable registration was performed to align image volumes of the time series to a reference volume. The resulting deformation fields were used for motion velocity evaluation and patient-specific motion model construction through principal component analysis (PCA). Geometric uncertainties introduced by slow drifting motion were assessed by Hausdorff distances between unions of organs at risk (OARs) at different motion states and reference OAR contours as well as probabilistic distributions of OARs predicted using the PCA model. Thirteen examinations from 11 patients were included in this study. The averaged motion velocities ranged from 0.8 to 1.9 mm min^-1, 0.7 to 1.6 mm min^-1, 0.6 to 2.0 mm min^-1and 0.7 to 1.4 mm min^-1for the small bowel, colon, duodenum and stomach respectively; the averaged Hausdorff distances were 5.6 mm, 5.3 mm, 5.1 mm and 4.6 mm. On average, a margin larger than 4.5 mm was needed to cover a space with OAR occupancy probability higher than 55%. Temporal variations of geometric uncertainties were evaluated by comparing across four 5 min sub-scans extracted from the full scan. Standard deviations of Hausdorff distances across sub-scans were less than 1 mm for most examinations, indicating stability of relative margin estimates from separate time windows. These results suggested slow drifting motion of GI organs is significant and geometric uncertainties introduced by such motion should be accounted for during radiotherapy planning and delivery.

Gastrointestinal 4D MRI with respiratory motion correction

PURPOSE

Gastrointestinal motion patterns such as peristalsis and segmental contractions can alter the shape and position of the stomach and intestines with respect to other irradiated organs during radiation therapy. Unfortunately, these deformations are concealed by conventional four-dimensional (4D)-MRI techniques, which were developed to visualize respiratory motion by binning acquired data into respiratory motion states without considering the phases of GI motion. We present a method to reconstruct breathing-compensated images showing the phases of periodic gastric motion and study the effect of this motion on regional anatomical structures.

METHODS

Sixty-seven DCE-MRI examinations were performed on patients undergoing MRI simulation for hepatocellular carcinoma using a golden-angle stack-of-stars sequence that collected 2000 radial spokes over 5 min. The collected data were reconstructed using a method with integrated respiratory motion correction into a time series of 3D image volumes without visible breathing motion. From this series, a gastric motion signal was extracted by temporal filtering of time-intensity curves in the stomach. Using this motion signal, breathing-corrected back-projection images were sorted according to the gastric phase and reconstructed into 21 gastric motion state images showing the phases of gastric motion.

RESULTS

Reconstructed image volumes showed gastric motion states clearly with no visible breathing motion or related artifacts. The mean frequency of the gastric motion signal was 3 cycles/min with a standard deviation of 0.27 cycles/min.

CONCLUSIONS

Periodic gastrointestinal motion can be visualized without confounding respiratory motion using the presented GI 4D MRI technique. GI 4D MRIs may help define internal target volumes for treatment planning, aid in planning organ at risk volume definition, or support motion model development for gastrointestinal motion tracking algorithms for real-time MR-guided radiation therapy.

Abdominal synthetic CT generation from MR Dixon images using a U-net trained with 'semi-synthetic' CT data

Magnetic resonance imaging (MRI) is gaining popularity in guiding radiation treatment for intrahepatic cancers due to its superior soft tissue contrast and potential of monitoring individual motion and liver function. This study investigates a deep learning-based method that generates synthetic CT volumes from T1-weighted MR Dixon images in support of MRI-based intrahepatic radiotherapy treatment planning. Training deep neutral networks for this purpose has been challenged by mismatches between CT and MR images due to motion and different organ filling status. This work proposes to resolve such challenge by generating 'semi-synthetic' CT images from rigidly aligned CT and MR image pairs. Contrasts within skeletal elements of the 'semi-synthetic' CT images were determined from CT images, while contrasts of soft tissue and air volumes were determined from voxel-wise intensity classification results on MR images. The resulting 'semi-synthetic' CT images were paired with their corresponding MR images and used to train a simple U-net model without adversarial components. MR and CT scans of 46 patients were investigated and the proposed method was evaluated for 31 patients with clinical radiotherapy plans, using 3-fold cross validation. The averaged mean absolute errors between synthetic CT and CT images across patients were 24.10 HU for liver, 28.62 HU for spleen, 47.05 HU for kidneys, 29.79 HU for spinal cord, 105.68 HU for lungs and 110.09 HU for vertebral bodies. VMAT and IMRT plans were optimized using CT-derived electron densities, and doses were recalculated using corresponding synthetic CT-derived density grids. Resulting dose differences to planning target volumes and various organs at risk were small, with the average difference less than 0.15 Gy for all dose metrics evaluated. The similarities in both image intensity and radiation dose distributions between CT and synthetic CT volumes demonstrate the accuracy of the method and its potential in supporting MRI-only radiotherapy treatment planning.

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.

Role and future of MRI in radiation oncology

Technical innovations and developments in areas such as disease localization, dose calculation algorithms, motion management and dose delivery technologies have revolutionized radiation therapy resulting in improved patient care with superior outcomes. A consequence of the ability to design and accurately deliver complex radiation fields is the need for improved target visualization through imaging. While CT imaging has been the standard of care for more than three decades, the superior soft tissue contrast afforded by MR has resulted in the adoption of this technology in radiation therapy. With the development of real time MR imaging techniques, the problem of real time motion management is enticing. Currently, the integration of an MR imaging and megavoltage radiation therapy treatment delivery system (MR-linac or MRL) is a reality that has the potential to provide improved target localization and real time motion management during treatment. Higher magnetic field strengths provide improved image quality potentially providing the backbone for future work related to image texture analysis-a field known as Radiomics-thereby providing meaningful information on the selection of future patients for radiation dose escalation, motion-managed treatment techniques and ultimately better patient care. On-going advances in MRL technologies promise improved real time soft tissue visualization, treatment margin reductions, beam optimization, inhomogeneity corrected dose calculation, fast multileaf collimators and volumetric arc radiation therapy. This review article provides rationale, advantages and disadvantages as well as ideas for future research in MRI related to radiation therapy mainly in adoption of MRL.

Abdominal DCE-MRI reconstruction with deformable motion correction for liver perfusion quantification

PURPOSE

Abdominal dynamic contrast-enhanced (DCE) MRI suffers from motion-induced artifacts that can blur images and distort contrast-agent uptake curves. For liver perfusion analysis, image reconstruction with rigid-body motion correction (RMC) can restore distorted portal-venous input functions (PVIF) to higher peak amplitudes. However, RMC cannot correct for liver deformation during breathing. We present a reconstruction algorithm with deformable motion correction (DMC) that enables correction of breathing-induced deformation in the whole abdomen.

METHODS

Raw data from a golden-angle stack-of-stars gradient-echo sequence were collected for 54 DCE-MRI examinations of 31 patients. For each examination, a respiratory motion signal was extracted from the data and used to reconstruct 21 breathing states from inhale to exhale. The states were aligned with deformable image registration to the end-exhale state. Resulting deformation fields were used to correct back-projection images before reconstruction with view sharing. Images with DMC were compared to uncorrected images and images with RMC.

RESULTS

DMC significantly increased the PVIF peak amplitude compared to uncorrected images (P << 0.01, mean increase: 8%) but not compared to RMC. The increased PVIF peak amplitude significantly decreased estimated portal-venous perfusion in the liver (P << 0.01, mean decrease: 8 ml/(100 ml·min)). DMC also removed artifacts in perfusion maps at the liver edge and reduced blurring of liver tumors for some patients.

CONCLUSIONS

DCE-MRI reconstruction with DMC can restore motion-distorted uptake curves in the abdomen and remove motion artifacts from reconstructed images and parameter maps but does not significantly improve perfusion quantification in the liver compared to RMC.

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.

Implementing Radiation Dose-Volume Liver Response in Biomechanical Deformable Image Registration

PURPOSE

Understanding anatomic and functional changes in the liver resulting from radiation therapy is fundamental to the improvement of normal tissue complication probability models needed to advance personalized medicine. The ability to link pretreatment and posttreatment imaging is often compromised by significant dose-dependent volumetric changes within the liver that are currently not accounted for in deformable image registration (DIR) techniques. This study investigated using delivered dose, in combination with other patient factors, to biomechanically model longitudinal changes in liver anatomy for follow-up care and re-treatment planning.

METHODS AND MATERIALS

Population models describing the relationship between dose and hepatic volume response were produced using retrospective data from 33 patients treated with focal radiation therapy. A DIR technique was improved by implementing additional boundary conditions associated with the dose-volume response in series with a previously developed biomechanical DIR algorithm. Evaluation of this DIR technique was performed on computed tomography imaging from 7 patients by comparing the model-predicted volumetric change within the liver with the observed change, tracking vessel bifurcations within the liver through the deformation process, and then determining target registration error between the predicted and identified posttreatment bifurcation points.

RESULTS

Evaluation of the proposed DIR technique showed that all lobes were volumetrically deformed to within the respective contour variability of each lobe. The average target registration error achieved was 7.3 mm (2.8 mm left-right and anterior-posterior and 5.1 mm superior-inferior), with the superior-inferior component within the average limiting slice thickness (6.0 mm). This represented a significant improvement (P<.01, Wilcoxon test) over the application of the previously published biomechanical DIR algorithm (10.9 mm).

CONCLUSIONS

This study demonstrates the feasibility of implementing dose-driven volumetric response in deformable registration, enabling improved accuracy of modeling liver anatomy changes, which could allow for improved dose accumulation, particularly for patients who require additional liver radiation therapy.

Optimizing global liver function in radiation therapy treatment planning

Liver stereotactic body radiation therapy (SBRT) patients differ in both pre-treatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pre-treatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose ([Formula: see text]) (conventional '[Formula: see text] model'), the so-called perfusion-weighted [Formula: see text] ([Formula: see text]) (proposed 'fEUD model'), and post-treatment global liver function (GLF) (proposed 'GLF model'), predicted by a new liver-perfusion-based dose-response model. The resulting [Formula: see text], fEUD, and GLF plans delivering the same target [Formula: see text] are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to [Formula: see text] more liver function than the fEUD ([Formula: see text]) plan does in 2D cases, and up to [Formula: see text] in 3D cases. The GLF and fEUD plans worsen in [Formula: see text] of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and often achieves better GLF than [Formula: see text] model optimization does, the GLF model directly optimizes a more clinically relevant metric and can further improve fEUD plan quality.