Performance of tumor growth kinetics as an imaging biomarker for response assessment in colorectal liver metastases: correlation with FDG PET

In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment

Angiogenesis is a crucial step in tumour progression, as this process allows tumours to recruit new blood vessels and obtain oxygen and nutrients to sustain growth. Therefore, inhibiting angiogenesis remains a viable strategy for cancer therapy. However, anti-angiogenic therapy has not proved to be effective in reducing tumour growth across a wide range of tumours, and no reliable predictive biomarkers have been found to determine the efficacy of anti-angiogenic treatment. Using our previously established computational model of tumour-bearing mice, we sought to determine whether tumour growth kinetic parameters could be used to predict the outcome of anti-angiogenic treatment. A model trained with datasets from six in vivo mice studies was used to generate a randomized in silico tumour-bearing mouse population. We analysed tumour growth in untreated mice (control) and mice treated with an anti-angiogenic agent and determined the Kaplan–Meier survival estimates based on simulated tumour volume data. We found that the ratio between two kinetic parameters, k₀ and k₁, which characterize the tumour's exponential and linear growth rates, as well as k₁ alone, can be used as prognostic biomarkers of the population survival outcome. Our work demonstrates a robust, quantitative approach for identifying tumour growth kinetic parameters as prognostic biomarkers and serves as a template that can be used to identify other biomarkers for anti-angiogenic treatment.

Carcinoembryonic antigen reduction after medical treatment in patients with metastatic colorectal cancer: a systematic review and meta-analysis

PURPOSE

The introduction of new drugs and multimodal treatments for the management of patients with metastatic colorectal cancer (mCRC) has reduced the importance of time-to-event endpoints and reported the attention on the response-related endpoints. Furthermore, the prognostic role of the surgical scores before the resection of metastases has not been confirmed for multimodal treatments. The purpose of this research is to perform a meta-analysis of the studies that evaluated the relationship between carcinoembryonic antigen (CEA) response and outcome in patients with mCRC receiving systemic chemotherapy.

METHODS

A systematic review of the literature on two databases and a selection of studies that evaluated the relationship between CEA response and outcome were performed according to predefined criteria. After, three meta-analyses were carried out on the selected studies, each for each outcome variable.

RESULTS

Nineteen studies have been selected. Fourteen studies (1475 patients) have documented a close association between radiological response and CEA response (odds ratio (OR), 9.03; confidence intervals (CIs), 5.14-15.87; I² statistic (I²), 72%). Four studies have reported a longer progression-free survival for patients with a CEA response (hazard ratio (HR), 0.73; CIs, 0.64-0.83; I², 23%). Finally, 10 studies (13 study cohorts) have shown a strong relationship between CEA response and overall survival (OS) (HR, 0. 62; CIs, 0.55-0.70; I², 35%).

CONCLUSIONS

CEA response merits further investigation as a surrogate endpoint of clinical trials of first-line medical therapy of patients with mCRC, and should be studied as a prognostic factor for those patients who are candidates for multimodal treatment strategies.

18F-fludeoxyglucose positron emission tomography for diagnosis of HCC: implications for therapeutic strategy in curative and non-curative approaches

Hepatocellular carcinoma (HCC) is a global health issue with increasing incidence and high mortality rate. Depending on the tumor load and extent of underlying liver cirrhosis, aggressive surgical treatment by hepatectomy or liver transplantation (LT) may lead to cure, whereas different modalities of liver-directed locoregional or systemic tumor treatments are currently available for a noncurative approach. Apart from tumor burden and grade of liver dysfunction, assessment of prognostic relevant biological tumor aggressiveness is vitally important for establishing a promising multimodal therapeutic strategy and improving the individual treatment-related risk/benefit ratio. In recent years, an increasing body of clinical evidence has been presented that ¹⁸F-fludeoxyglucose (¹⁸F-FDG) positron emission tomography (PET), which is a standard nuclear imaging device in oncology, may serve as a powerful surrogate for tumor invasiveness and prognosis in HCC patients and, thereby, impact individual decision making on most appropriate therapy concept. This review describes the currently available data on the prognostic value of ¹⁸F-FDG PET in patients with early and advanced HCC stages and the resulting implications for treatment strategy.

Hybrid PET/MR Kernelised Expectation Maximisation Reconstruction for Improved Image-Derived Estimation of the Input Function from the Aorta of Rabbits

Positron emission tomography (PET) provides simple noninvasive imaging biomarkers for multiple human diseases which can be used to produce quantitative information from single static images or to monitor dynamic processes. Such kinetic studies often require the tracer input function (IF) to be measured but, in contrast to direct blood sampling, the image-derived input function (IDIF) provides a noninvasive alternative technique to estimate the IF. Accurate estimation can, in general, be challenging due to the partial volume effect (PVE), which is particularly important in preclinical work on small animals. The recently proposed hybrid kernelised ordered subsets expectation maximisation (HKEM) method has been shown to improve accuracy and contrast across a range of different datasets and count levels and can be used on PET/MR or PET/CT data. In this work, we apply the method with the purpose of providing accurate estimates of the aorta IDIF for rabbit PET studies. In addition, we proposed a method for the extraction of the aorta region of interest (ROI) using the MR and the HKEM image, to minimise the PVE within the rabbit aortic region-a method which can be directly transferred to the clinical setting. A realistic simulation study was performed with ten independent noise realisations while two, real data, rabbit datasets, acquired with the Biograph Siemens mMR PET/MR scanner, were also considered. For reference and comparison, the data were reconstructed using OSEM, OSEM with Gaussian postfilter and KEM, as well as HKEM. The results across the simulated datasets and different time frames show reduced PVE and accurate IDIF values for the proposed method, with 5% average bias (0.8% minimum and 16% maximum bias). Consistent results were obtained with the real datasets. The results of this study demonstrate that HKEM can be used to accurately estimate the IDIF in preclinical PET/MR studies, such as rabbit mMR data, as well as in clinical human studies. The proposed algorithm is made available as part of an open software library, and it can be used equally successfully on human or animal data acquired from a variety of PET/MR or PET/CT scanners.

Fluorine-18-fluorodeoxyglucose positron emission tomography as an objective substitute for CT morphologic response criteria in patients undergoing chemotherapy for colorectal liver metastases

PURPOSE

The computed tomography (CT) morphologic response of colorectal liver metastases (CLM) after chemotherapy is reportedly correlated with pathologic response and survival outcomes of patients undergoing surgery. However, they are rather subjective criteria and not evaluable without adequate quality of contrast-enhanced CT images. This study sought the potential use of fluorine-18-fluorodeoxyglucose (FDG) positron emission tomography (PET) as an objective substitute for predicting pathological viability of CLM after chemotherapy.

METHODS

Predictive ability of tumor viability of ≤10% was compared between FDG-PET/CT and contrast-enhanced CT in 34 patients who underwent curative surgical resection for CLM after chemotherapy. The CT morphology and response were defined according to the reported criteria (Chun YS, JAMA 2009).

RESULTS

The mean standard uptake value (SUV-mean) in CLM was significantly lower in patients with group 1 and group 2 CT morphology (median, 2.53 and 3.00, respectively) than in group 3 (median, 3.32). The tumor SUV-mean showed moderate correlation with the tumor pathologic viability (r = 0.660, P < 0.0001). A receiver operating characteristic curve analysis revealed that both the tumor SUV-mean (area under the curve [AUC], 0.916; the cut-off value, 3.00) and the CT morphology (AUC, 0.882) have excellent predictive power for ≤10% of tumor viability, while degree of tumor shrinkage showed lower predictive power (AUC, 0.692).

CONCLUSIONS

FDG-PET shows significant correlation with pathologic viability of CLM after chemotherapy and may offer additional objective information for estimating tumor viability when the CT morphologic response is not evaluable.

Advanced imaging to predict response to chemotherapy in colorectal liver metastases - a systematic review

BACKGROUND

The assessment of colorectal liver metastases (CRLM) after treatment with chemotherapy is challenging due to morphological and/or functional change without changes in size. The aim of this review was to assess the value of FDG-PET, FDG-PET-CT, CT and MRI in predicting response to chemotherapy in CRLM.

METHODS

A systematic review was undertaken based on PRISMA statement. PubMed and Embase were searched up to October 2016 for studies on the accuracy of PET, PET-CT, CT and MRI in predicting RECIST or metabolic response to chemotherapy and/or survival in patients with CRLM. Articles evaluating the assessment of response after chemotherapy were excluded.

RESULTS

Sixteen studies met the inclusion criteria and were included for further analysis. Study results were available for 6 studies for FDG-PET(-CT), 6 studies for CT and 9 studies for MRI. Generally, features predicting RECIST or metabolic response often predicted shorter survival. The ADC (apparent diffusion coefficient, on MRI) seems to be the most promising predictor of response and survival. In CT-related studies, few attenuation-related parameters and texture features show promising results. In FDG-PET(-CT), findings were ambiguous.

CONCLUSION

Radiological data on the prediction of response to chemotherapy for CRLM is relatively sparse and heterogeneous. Despite that, a promising parameter might be ADC. Second, there seems to be a seemingly counterintuitive correlation between parameters that predict a good response and also predict poor survival.

Mechanistic modeling quantifies the influence of tumor growth kinetics on the response to anti-angiogenic treatment

Tumors exploit angiogenesis, the formation of new blood vessels from pre-existing vasculature, in order to obtain nutrients required for continued growth and proliferation. Targeting factors that regulate angiogenesis, including the potent promoter vascular endothelial growth factor (VEGF), is therefore an attractive strategy for inhibiting tumor growth. Computational modeling can be used to identify tumor-specific properties that influence the response to anti-angiogenic strategies. Here, we build on our previous systems biology model of VEGF transport and kinetics in tumor-bearing mice to include a tumor compartment whose volume depends on the “angiogenic signal” produced when VEGF binds to its receptors on tumor endothelial cells. We trained and validated the model using published in vivo measurements of xenograft tumor volume, producing a model that accurately predicts the tumor’s response to anti-angiogenic treatment. We applied the model to investigate how tumor growth kinetics influence the response to anti-angiogenic treatment targeting VEGF. Based on multivariate regression analysis, we found that certain intrinsic kinetic parameters that characterize the growth of tumors could successfully predict response to anti-VEGF treatment, the reduction in tumor volume. Lastly, we use the trained model to predict the response to anti-VEGF therapy for tumors expressing different levels of VEGF receptors. The model predicts that certain tumors are more sensitive to treatment than others, and the response to treatment shows a nonlinear dependence on the VEGF receptor expression. Overall, this model is a useful tool for predicting how tumors will respond to anti-VEGF treatment, and it complements pre-clinical in vivo mouse studies.

One hallmark of cancer is angiogenesis, the formation of new blood capillaries from pre-existing vessels. Angiogenesis promotes tumor growth by enabling the tumor to obtain oxygen and nutrients from the surrounding microenvironment. Cancer drugs that inhibit angiogenesis ("anti-angiogenic therapies") have focused on inhibiting proteins that promote the growth of new blood vessels. The response to anti-angiogenic therapy is highly variable, and some tumors do not respond at all. Therefore, identifying a biomarker that predicts how specific tumors will respond would be extremely valuable. This work uses a computational model of tumor-bearing mice to investigate the response to anti-angiogenic treatment that targets the potent promoter of angiogenesis, vascular endothelial growth factor (VEGF), and how the response is influenced by tumor growth kinetics. We show that certain properties of tumor growth can be used to predict how much the tumor volume will be reduced upon administration of an anti-VEGF drug. This work identifies tumor growth parameters that may be reliable biomarkers for predicting how tumors will respond to anti-VEGF therapy. Our computational model generates novel, testable hypotheses and nicely complements pre-clinical studies of anti-angiogenic therapeutics.