Advanced perfusion quantification methods for dynamic PET and MRI data modelling

The functionality of tissues is guaranteed by the capillaries, which supply the microvascular network providing a considerable surface area for exchanges between blood and tissues. Microcirculation is affected by any pathological condition and any change in the blood supply can be used as a biomarker for the diagnosis of lesions and the optimization of the treatment. Nowadays, a number of techniques for the study of perfusion in vivo and in vitro are available. Among the several imaging modalities developed for the study of microcirculation, the analysis of the tissue kinetics of intravenously injected contrast agents or tracers is the most widely used technique. Tissue kinetics can be studied using different modalities: the positive enhancement of the signal in the computed tomography and in the ultrasound dynamic contrast enhancement imaging; T1-weighted MRI or the negative enhancement of T2* weighted MRI signal for the dynamic susceptibility contrast imaging or, finally, the uptake of radiolabelled tracers in dynamic PET imaging. Here we will focus on the perfusion quantification of dynamic PET and MRI data. The kinetics of the contrast agent (or the tracer) can be analysed visually, to define qualitative criteria but, traditionally, quantitative physiological parameters are extracted with the implementation of mathematical models. Serial measurements of the concentration of the tracer (or of the contrast agent) in the tissue of interest, together with the knowledge of an arterial input function, are necessary for the calculation of blood flow or perfusion rates from the wash-in and/or wash-out kinetic rate constants. The results depend on the acquisition conditions (type of imaging device, imaging mode, frequency and total duration of the acquisition), the type of contrast agent or tracer used, the data pre-processing (motion correction, attenuation correction, correction of the signal into concentration) and the data analysis method. As for the MRI, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a non-invasive imaging technique that can be used to measure properties of tissue microvasculature. It is sensitive to differences in blood volume and vascular permeability that can be associated with tumour angiogenesis. DCE-MRI has been investigated for a range of clinical oncologic applications (breast, prostate, cervix, liver, lung, and rectum) including cancer detection, diagnosis, staging, and assessment of treatment response. Tumour microvascular measurements by DCE-MRI have been found to correlate with prognostic factors (such as tumour grade, microvessel density, and vascular endothelial growth factor expression) and with recurrence and survival outcomes. Furthermore, DCE-MRI changes measured during treatment have been shown to correlate with outcome, suggesting a role as a predictive marker. The accuracy of DCE-MRI relies on the ability to model the pharmacokinetics of an injected contrast agent using the signal intensity changes on sequential magnetic resonance images. DCE-MRI data are usually quantified with the application of the pharmacokinetic two-compartment Tofts model (also known as the standard model), which represents the system with the plasma and tissue (extravascular extracellular space) compartments and with the contrast reagent exchange rates between them. This model assumes a negligible contribution from the vascular space and considers the system in, what-is-known as, the fast exchange limit, assuming infinitely fast transcytolemmal water exchange kinetics. In general, the number, as well as any assumption about the compartments, depends on the properties of the contrast agent used (mainly gadolinium) together with the tissue physiology or pathology studied. For this reason, the choice of the model is crucial in the analysis of DCE-MRI data. The value of PET in clinical oncology has been demonstrated with studies in a variety of cancers including colorectal carcinomas, lung tumours, head and neck tumours, primary and metastatic brain tumours, breast carcinoma, lymphoma, melanoma, bone cancers, and other soft-tissue cancers. PET studies of tumours can be performed for several reasons including the quantification of tumour perfusion, the evaluation of tumour metabolism, the tracing of radiolabelled cytostatic agents. In particular, the kinetic analysis of PET imaging has showed, in the past few years, an increasing value in tumour diagnosis, as well as in tumour therapy, through providing additional indicative parameters. Many authors have showed the benefit of kinetic analysis of anticancer drugs after labelling with radionuclide in measuring the specific therapeutic effect bringing to light the feasibility of applying the kinetic analysis to the dynamic acquisition. Quantification methods can involve visual analysis together with compartmental modelling and can be applied to a wide range of different tracers. The increased glycolysis in the most malignancies makes 18F-FDG-PET the most common diagnostic method used in tumour imaging. But, PET metabolic alteration in the target tissue can depend by many other factors. For example, most types of cancer are characterized by increased choline transport and by the overexpression of choline kinase in highly proliferating cells in response to enhanced demand of phosphatidylcholine (prostate, breast, lung, ovarian and colon cancers). This effect can be diagnosed with choline-based tracers as the 18Ffluoromethylcholine (18F-FCH), or the even more stable 18F-D4-Choline. Cellular proliferation is also imaged with 18F-fluorothymidine (FLT), which is trapped within the cytosol after being mono phosphorylated by thymidine kinase-1 (TK1), a principal enzyme in the salvage pathway of DNA synthesis. 18F-FLT has been found to be useful for noninvasive assessment of the proliferation rate of several types of cancer and showed high reproducibility and accuracy in breast and lung cancer tumours. The aim of this thesis is the perfusion quantification of dynamic PET and MRI data of patients with lung, brain, liver, prostate and breast lesions with the application of advanced models. This study covers a wide range of imaging methods and applications, presenting a novel combination of MRI-based perfusion measures with PET kinetic modelling parameters in oncology. It assesses the applicability and stability of perfusion quantification methods, which are not currently used in the routine clinical practice. The main achievements of this work include: 1) the assessment of the stability of perfusion quantification of D4-Choline and 18F-FLT dynamic PET data in lung and liver lesions, respectively (first applications in the literature); 2) the development of a model selection in the analysis of DCE-MRI data of primary brain tumours (first application of the extended shutter speed model); 3) the multiparametric analysis of PET and MRI derived perfusion measurements of primary brain tumour and breast cancer together with the integration of immuohistochemical markers in the prediction of breast cancer subtype (analysis of data acquired on the hybrid PET/MRI scanner). The thesis is structured as follows: - Chapter 1 is an introductive chapter on cancer biology. Basic concepts, including the causes of cancer, cancer hallmarks, available cancer treatments, are described in this first chapter. Furthermore, there are basic concepts of brain, breast, prostate and lung cancers (which are the lesions that have been analysed in this work). - Chapter 2 is about Positron Emission Tomography. After a brief introduction on the basics of PET imaging, together with data acquisition and reconstruction methods, the chapter focuses on PET in the clinical settings. In particular, it shows the quantification techniques of static and dynamic PET data and my results of the application of graphical methods, spectral analysis and compartmental models on dynamic 18F-FDG, 18F-FLT and 18F-D4- Choline PET data of patients with breast, lung cancer and hepatocellular carcinoma. - Chapter 3 is about Magnetic Resonance Imaging. After a brief introduction on the basics of MRI, the chapter focuses on the quantification of perfusion weighted MRI data. In particular, it shows the pharmacokinetic models for the quantification of dynamic contrast enhanced MRI data and my results of the application of the Tofts, the extended Tofts, the shutter speed and the extended shutter speed models on a dataset of patients with brain glioma. - Chapter 4 introduces the multiparametric imaging techniques, in particular the combined PET/CT and the hybrid PET/MRI systems. The last part of the chapter shows the applications of perfusion quantification techniques on a multiparametric study of breast tumour patients, who simultaneously underwent DCE-MRI and 18F-FDG PET on a hybrid PET/MRI scanner. Then the results of a predictive study on the same dataset of breast tumour patients integrated with immunohistochemical markers. Furthermore, the results of a multiparametric study on DCE-MRI and 18F-FCM brain data acquired both on a PET/CT scanner and on an MR scanner, separately. Finally, it will show the application of kinetic analysis in a radiomic study of patients with prostate cancer

Cylindrical illumination with angular coupling for whole-prostate photoacoustic tomography

Current diagnosis of prostate cancer relies on histological analysis of tissue samples acquired by biopsy, which could benefit from real-time identification of suspicious lesions. Photoacoustic tomography has the potential to provide real-time targets for prostate biopsy guidance with chemical selectivity, but light delivered from the rectal cavity has been unable to penetrate to the anterior prostate. To overcome this barrier, a urethral device with cylindrical illumination is developed for whole-prostate imaging, and its performance as a function of angular light coupling is evaluated with a prostate-mimicking phantom

Analysis of contrast-enhanced medical images.

Early detection of human organ diseases is of great importance for the accurate diagnosis and institution of appropriate therapies. This can potentially prevent progression to end-stage disease by detecting precursors that evaluate organ functionality. In addition, it also assists the clinicians for therapy evaluation, tracking diseases progression, and surgery operations. Advances in functional and contrast-enhanced (CE) medical images enabled accurate noninvasive evaluation of organ functionality due to their ability to provide superior anatomical and functional information about the tissue-of-interest. The main objective of this dissertation is to develop a computer-aided diagnostic (CAD) system for analyzing complex data from CE magnetic resonance imaging (MRI). The developed CAD system has been tested in three case studies: (i) early detection of acute renal transplant rejection, (ii) evaluation of myocardial perfusion in patients with ischemic heart disease after heart attack; and (iii), early detection of prostate cancer. However, developing a noninvasive CAD system for the analysis of CE medical images is subject to multiple challenges, including, but are not limited to, image noise and inhomogeneity, nonlinear signal intensity changes of the images over the time course of data acquisition, appearances and shape changes (deformations) of the organ-of-interest during data acquisition, determination of the best features (indexes) that describe the perfusion of a contrast agent (CA) into the tissue. To address these challenges, this dissertation focuses on building new mathematical models and learning techniques that facilitate accurate analysis of CAs perfusion in living organs and include: (i) accurate mathematical models for the segmentation of the object-of-interest, which integrate object shape and appearance features in terms of pixel/voxel-wise image intensities and their spatial interactions; (ii) motion correction techniques that combine both global and local models, which exploit geometric features, rather than image intensities to avoid problems associated with nonlinear intensity variations of the CE images; (iii) fusion of multiple features using the genetic algorithm. The proposed techniques have been integrated into CAD systems that have been tested in, but not limited to, three clinical studies. First, a noninvasive CAD system is proposed for the early and accurate diagnosis of acute renal transplant rejection using dynamic contrast-enhanced MRI (DCE-MRI). Acute rejection–the immunological response of the human immune system to a foreign kidney–is the most sever cause of renal dysfunction among other diagnostic possibilities, including acute tubular necrosis and immune drug toxicity. In the U.S., approximately 17,736 renal transplants are performed annually, and given the limited number of donors, transplanted kidney salvage is an important medical concern. Thus far, biopsy remains the gold standard for the assessment of renal transplant dysfunction, but only as the last resort because of its invasive nature, high cost, and potential morbidity rates. The diagnostic results of the proposed CAD system, based on the analysis of 50 independent in-vivo cases were 96% with a 95% confidence interval. These results clearly demonstrate the promise of the proposed image-based diagnostic CAD system as a supplement to the current technologies, such as nuclear imaging and ultrasonography, to determine the type of kidney dysfunction. Second, a comprehensive CAD system is developed for the characterization of myocardial perfusion and clinical status in heart failure and novel myoregeneration therapy using cardiac first-pass MRI (FP-MRI). Heart failure is considered the most important cause of morbidity and mortality in cardiovascular disease, which affects approximately 6 million U.S. patients annually. Ischemic heart disease is considered the most common underlying cause of heart failure. Therefore, the detection of the heart failure in its earliest forms is essential to prevent its relentless progression to premature death. While current medical studies focus on detecting pathological tissue and assessing contractile function of the diseased heart, this dissertation address the key issue of the effects of the myoregeneration therapy on the associated blood nutrient supply. Quantitative and qualitative assessment in a cohort of 24 perfusion data sets demonstrated the ability of the proposed framework to reveal regional perfusion improvements with therapy, and transmural perfusion differences across the myocardial wall; thus, it can aid in follow-up on treatment for patients undergoing the myoregeneration therapy. Finally, an image-based CAD system for early detection of prostate cancer using DCE-MRI is introduced. Prostate cancer is the most frequently diagnosed malignancy among men and remains the second leading cause of cancer-related death in the USA with more than 238,000 new cases and a mortality rate of about 30,000 in 2013. Therefore, early diagnosis of prostate cancer can improve the effectiveness of treatment and increase the patient’s chance of survival. Currently, needle biopsy is the gold standard for the diagnosis of prostate cancer. However, it is an invasive procedure with high costs and potential morbidity rates. Additionally, it has a higher possibility of producing false positive diagnosis due to relatively small needle biopsy samples. Application of the proposed CAD yield promising results in a cohort of 30 patients that would, in the near future, represent a supplement of the current technologies to determine prostate cancer type. The developed techniques have been compared to the state-of-the-art methods and demonstrated higher accuracy as shown in this dissertation. The proposed models (higher-order spatial interaction models, shape models, motion correction models, and perfusion analysis models) can be used in many of today’s CAD applications for early detection of a variety of diseases and medical conditions, and are expected to notably amplify the accuracy of CAD decisions based on the automated analysis of CE images

A novel in vivo tumor oxygen profiling assay: Combining functional and molecular imaging with multivariate mathematical modeling

Purpose: The objective of this study is to develop and test a novel high spatio-temporal in vivo assay to quantify tumor oxygenation and hypoxia. The assay implements a biophysical model of oxygen transport to fuse parameters acquired from in vivo functional and molecular imaging modalities. ^ Introduction: Tumor hypoxia plays an important role in carcinogenesis. It triggers pathological angiogenesis to supply more oxygen to the tumor cells and promotes cancer cell metastasis. Preclinical and clinical evidence show that anti-angiogenic treatment is capable of normalizing the tumor vasculature both structurally and functionally. The resulting normalized vasculature provides a more efficient and uniform microcirculation that enhances oxygen and drug delivery to the tumor cells and improves second-line treatments such as traditional radiation or chemotherapy. Early studies using the overall or average tumor hypoxia as a prognostic biomarker of anti-angiogenic therapy efficacy was ambivalent; however, recent studies have discovered that the etiology of hypoxia and its heterogeneity could be used as reliable prognostic biomarkers. The capability to longitudinally map tumor hypoxia with high spatial and temporal resolution has the potential to enhance fundamental cancer research and ultimately cancer patient care. ^ Method: A novel methodology to identify and characterize tumor hypoxia by fusing the physiological hemodynamic parametric maps obtained from functional and molecular imaging modalities and technique using a modified Krogh model of oxygen transport (MPO2) was developed. First, simulations studies were performed to validate this technique. Microscopy data of tumor and brain tissue (control) provided both the vasculature and rheology data. A Green\u27s function algorithm was used to solve the ordinary differential equation and calculate the oxygen profile at a microscopic scale (15 μm) (GPO2), which was used as a reference. From this data, simulated physiological maps (perfusion, fractional plasma volume, fractional interstitial volume) and hemoglobin status (oxygen saturation, hemoglobin concentration) was used as input to MPO2 and used to calculate pO2 levels as a function of scanner spatial resolution and noise. Second, MPO2 was compared to pO2 measurements in xenograft breast tumors using OxyLite oxygen sensor as a Gold Standard, where DCE-CT and PCT-S images were acquired to obtain hemodynamic images. Finally, the vascular physiology measurements obtained from an anti-angiogenic therapeutic study in pancreatic tumors was applied to MPO2 and compared to therapeutic response. ^ Results: The simulation results using Green\u27s function pO2 as standard showed that the MPO2 model performance was dependent on the spatial resolution (voxel size) of the images. Sensitivity and error analysis of this model were also investigated in this study. These oxygen transport simulations results suggest the oxygen saturation and hemoglobin concentration were two key factors in tissue oxygenation, and concomitant with blood perfusion and tumor metabolic rate. Comparisons of the pO2 profile obtained from MPO2 and OxyLite probe in MCF7 tumor model demonstrated a significant correlation and approached a slope of one (after accounting for a few outliers). Simulation studies implementing the physiological data obtained from the anti-angiogenic therapeutic study in pancreatic tumors using the MPO2 model agreed with the experimental findings that blood perfusion is a valuable prognostic biomarker in therapeutic efficacy. This model also predicted the oxygenation improvement difference from two vascular renormalization modes (topological normalization and geometrical normalization). ^ Conclusion: The results from the simulation and in vivo studies demonstrated the feasibility of this novel hypoxia assay. Simulation results of the pancreatic tumors provide an example of the impact the MPO2 model in conjunction with imaging can provide when evaluating the therapeutic significance of various normalization modes in anti-angiogenic therapy, and suggests potential approaches to further improve anti-angiogenic therapy efficacy

A Novel Anthropomorphic Flow Phantom for the Quantitative Evaluation of Prostate DCE-MRI Acquisition Techniques

A novel anthropomorphic flow phantom device has been developed which can be used for quantitatively assessing the ability of MRI scanners to accurately measure signal / concentration time-intensity curves (CTCs) associated with dynamic contrast-enhanced (DCE) MRI. Modelling of the complex pharmacokinetics of contrast agents as they perfuse through the tumour capillary network has shown great promise for cancer diagnosis and therapy monitoring. However, clinical adoption has been hindered by methodological problems, resulting in a lack of consensus regarding the most appropriate acquisition and modelling methodology to use and a consequent wide discrepancy in published data. A heretofore overlooked source of such discrepancy may arise from measurement errors of tumour CTCs deriving from the imaging pulse sequence itself, while the effects on the fidelity of CTC measurement of using rapidly-accelerated sequences such as parallel imaging and compressed sensing remain unknown. The present work aimed to investigate these features by developing a test device in which „ground truth‟ CTCs were generated and presented to the MRI scanner for measurement, thereby allowing for an assessment of the DCE-MRI protocol to accurately measure this curve-shape. The device comprised of a 4-pump flow system wherein CTCs derived from prior patient prostate data were produced in measurement chambers placed within the imaged volume. The ground truth was determined as the mean of repeat measurements using an MRI-independent, custom-built optical imaging system. In DCE-MRI experiments, significant discrepancies between the ground truth and measured CTCs were found for both tumorous and healthy tissue-mimicking curve shapes. Pharmacokinetic modelling revealed errors in measured Ktrans, ve and kep values of up to 42%, 31%, and 50% respectively, following a simple variation of the parallel imaging factor and number of signal averages in the acquisition protocol The device allows for the quantitative assessment and standardisation of DCE-MRI protocols (both existing and emerging)

Combined ultrasound and photoacoustic imaging of metal objects

Methods of combined ultrasound and photoacoustic imaging are provided. In some embodiments, the methods may be used to determine the location or positioning of a metal object in a sample. In other embodiments, the methods may be used to determine the composition of a sample surrounding a metal object. Other methods are also provided.Board of Regents, University of Texas Syste

A review of imaging techniques for systems biology

This paper presents a review of imaging techniques and of their utility in system biology. During the last decade systems biology has matured into a distinct field and imaging has been increasingly used to enable the interplay of experimental and theoretical biology. In this review, we describe and compare the roles of microscopy, ultrasound, CT (Computed Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), and molecular probes such as quantum dots and nanoshells in systems biology. As a unified application area among these different imaging techniques, examples in cancer targeting are highlighted

Hyperthermia and smart drug delivery systems for solid tumor therapy

Chemotherapy is a cornerstone of cancer therapy. Irrespective of the administered drug, it is crucial that adequate drug amounts reach all cancer cells. To achieve this, drugs first need to be absorbed, then enter the blood circulation, diffuse into the tumor interstitial space and finally reach the tumor cells. Next to chemoresistance, one of the most important factors for effective chemotherapy is adequate tumor drug uptake and penetration. Unfortunately, most chemotherapeutic agents do not have favorable properties. These compounds are cleared rapidly, distribute throughout all tissues in the body, with only low tumor drug uptake that is heterogeneously distributed within the tumor. Moreover, the typical microenvironment of solid cancers provides additional hurdles for drug delivery, such as heterogeneous vascular density and perfusion, high interstitial fluid pressure, and abundant stroma. The hope was that nanotechnology will solve most, if not all, of these drug delivery barriers. However, in spite of advances and decades of nanoparticle development, results are unsatisfactory. One promising recent development are nanoparticles which can be steered, and release content triggered by internal or external signals. Here we discuss these so-called smart drug delivery systems in cancer therapy with emphasis on mild hyperthermia as a trigger signal for drug delivery

Ultrasound Biomicroscopy in Small Animal Research: Applications in Molecular and Preclinical Imaging

Ultrasound biomicroscopy (UBM) is a noninvasive multimodality technique that allows high-resolution imaging in mice. It is affordable, widely available, and portable. When it is coupled to Doppler ultrasound with color and power Doppler, it can be used to quantify blood flow and to image microcirculation as well as the response of tumor blood supply to cancer therapy. Target contrast ultrasound combines ultrasound with novel molecular targeted contrast agent to assess biological processes at molecular level. UBM is useful to investigate the growth and differentiation of tumors as well as to detect early molecular expression of cancer-related biomarkers in vivo and to monitor the effects of cancer therapies. It can be also used to visualize the embryological development of mice in uterus or to examine their cardiovascular development. The availability of real-time imaging of mice anatomy allows performing aspiration procedures under ultrasound guidance as well as the microinjection of cells, viruses, or other agents into precise locations. This paper will describe some basic principles of high-resolution imaging equipment, and the most important applications in molecular and preclinical imaging in small animal research