Personalized Pancreatic Tumor Growth Prediction via Group Learning

Tumor growth prediction, a highly challenging task, has long been viewed as a mathematical modeling problem, where the tumor growth pattern is personalized based on imaging and clinical data of a target patient. Though mathematical models yield promising results, their prediction accuracy may be limited by the absence of population trend data and personalized clinical characteristics. In this paper, we propose a statistical group learning approach to predict the tumor growth pattern that incorporates both the population trend and personalized data, in order to discover high-level features from multimodal imaging data. A deep convolutional neural network approach is developed to model the voxel-wise spatio-temporal tumor progression. The deep features are combined with the time intervals and the clinical factors to feed a process of feature selection. Our predictive model is pretrained on a group data set and personalized on the target patient data to estimate the future spatio-temporal progression of the patient's tumor. Multimodal imaging data at multiple time points are used in the learning, personalization and inference stages. Our method achieves a Dice coefficient of 86.8% +- 3.6% and RVD of 7.9% +- 5.4% on a pancreatic tumor data set, outperforming the DSC of 84.4% +- 4.0% and RVD 13.9% +- 9.8% obtained by a previous state-of-the-art model-based method

First-in-Human Phase I Study to Evaluate the Brain-Penetrant PI3K/mTOR Inhibitor GDC-0084 in Patients with Progressive or Recurrent High-Grade Glioma.

PurposeGDC-0084 is an oral, brain-penetrant small-molecule inhibitor of PI3K and mTOR. A first-in-human, phase I study was conducted in patients with recurrent high-grade glioma.Patients and methodsGDC-0084 was administered orally, once daily, to evaluate safety, pharmacokinetics (PK), and activity. Fluorodeoxyglucose-PET (FDG-PET) was performed to measure metabolic responses.ResultsForty-seven heavily pretreated patients enrolled in eight cohorts (2-65 mg). Dose-limiting toxicities included 1 case of grade 2 bradycardia and grade 3 myocardial ischemia (15 mg), grade 3 stomatitis (45 mg), and 2 cases of grade 3 mucosal inflammation (65 mg); the MTD was 45 mg/day. GDC-0084 demonstrated linear and dose-proportional PK, with a half-life (∼19 hours) supportive of once-daily dosing. At 45 mg/day, steady-state concentrations exceeded preclinical target concentrations producing antitumor activity in xenograft models. FDG-PET in 7 of 27 patients (26%) showed metabolic partial response. At doses ≥45 mg/day, a trend toward decreased median standardized uptake value in normal brain was observed, suggesting central nervous system penetration of drug. In two resection specimens, GDC-0084 was detected at similar levels in tumor and brain tissue, with a brain tissue/tumor-to-plasma ratio of >1 and >0.5 for total and free drug, respectively. Best overall response was stable disease in 19 patients (40%) and progressive disease in 26 patients (55%); 2 patients (4%) were nonevaluable.ConclusionsGDC-0084 demonstrated classic PI3K/mTOR-inhibitor related toxicities. FDG-PET and concentration data from brain tumor tissue suggest that GDC-0084 crossed the blood-brain barrier

Dynamic Contrast Enhanced Computed Tomography Measurement of Perfusion in Hepatic Cancer

ABSTRACT In recent years, the incidence and mortality rate for hepatocellular carcinoma (HCC) have increased due to the emergence of hepatitis B, C and other diseases that cause cirrhosis. The progression from cirrhosis to HCC is characterized by abnormal vascularization and by a shift from a venous to an arterial blood supply. A knowledge of HCC vascularity which is manifested as alterations in liver blood flow may distinguish among different stages of liver disease and can be used to monitor response to treatment. Unfortunately, conventional diagnostic imaging techniques lack the ability to accurately quantify HCC vascularity. The purpose of this thesis was to validate and assess the diagnostic capabilities of dynamic contrast enhanced computed tomography (DCE-CT) and perfusion software designed to measure hepatic perfusion. Chapter 2 described a study designed to evaluate the accuracy and precision of hepatic perfusion measurement. The results showed a strong correlation between hepatic artery blood flow measurement with DCE-CT and radioactive microspheres under steady state in a rabbit model for HCC (VX2 carcinoma). Using repeated measurements and Monte Carlo simulations, DCE-CT perfusion measurements were found to be precise; with the highest precision in the tumor rim. In Chapter 3, we used fluorine-18 fluoro-2-deoxy-D-glucose (FDG) positron emission tomography and DCE-CT perfusion to determined an inverse correlation between glucose utilization and tumor blood flow; with an R of 0.727 (P \u3c 0.05). This suggests a limited supply of oxygen (possibly hypoxia) and that the tumor cells were surviving via anaerobic glycolysis. in In Chapter 4, hepatic perfusion data showed that thalidomide caused a reduction of tumor perfusion in the responder group during the first 8 days after therapy, P \u3c 0.05; while perfusion in the partial responder and control group remained unchanged, P \u3e 0.05. These changes were attributed to vascular remodeling and maturation resulting in a more functional network of endothelial tubes lined with pericytes. The results of this thesis demonstrate the accuracy and precision of DCE-CT hepatic perfusion measurements. It also showed that DCE-CT perfusion has the potential to enhance the functional imaging ability of hybrid PET/CT scanners and evaluate the efficacy of anti-angiogenesis therapy

Focal Spot, Spring 2004

https://digitalcommons.wustl.edu/focal_spot_archives/1096/thumbnail.jp

Molecular Imaging

The present book gives an exceptional overview of molecular imaging. Practical approach represents the red thread through the whole book, covering at the same time detailed background information that goes very deep into molecular as well as cellular level. Ideas how molecular imaging will develop in the near future present a special delicacy. This should be of special interest as the contributors are members of leading research groups from all over the world

Imaging of preclinical endometrial cancer models for monitoring tumor progression and response to targeted therapy

Endometrial cancer is the most common gynecologic malignancy in industrialized countries. Most patients are cured by surgery; however, about 15% of the patients develop recurrence with limited treatment options. Patient-derived tumor xenograft (PDX) mouse models represent useful tools for preclinical evaluation of new therapies and biomarker identification. Preclinical imaging by magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), single-photon emission computed tomography (SPECT) and optical imaging during disease progression enables visualization and quantification of functional tumor characteristics, which may serve as imaging biomarkers guiding targeted therapies. A critical question, however, is whether the in vivo model systems mimic the disease setting in patients to such an extent that the imaging biomarkers may be translatable to the clinic. The primary objective of this review is to give an overview of current and novel preclinical imaging methods relevant for endometrial cancer animal models. Furthermore, we highlight how these advanced imaging methods depict pathogenic mechanisms important for tumor progression that represent potential targets for treatment in endometrial cancer.publishedVersio

Nuclear Imaging and Therapy:Towards a Personalized Approach in HCC and NET

This thesis explores new applications of nuclear imaging and therapy in patients with hepatocellular carcinoma (HCC) and neuroendocrine tumors (NET). These diseases are often detected late, making curative therapy not always possible. Developments in positron emission tomography (PET) and radionuclide therapy have led to new nuclear agents. The aim of this thesis is to provide insight into several new applications of current and new tracers in the diagnosis and treatment of HCC and NET.One of the investigated tracers is 18F-DOPA, which is currently used for NET tumors that are negative on 68Ga-labeled somatostatin analog (SSA) PET scans. Our study confirms the equivalent detection of 18F-DOPA in tumor detection compared to 68Ga-SSAs. Selective internal radiation therapy (SIRT) uses yttrium-90 radioactive resin spheres that are intravascularly injected into the liver. Higher than usual dosages (>120 Gy) appear to lead to better results in tumor reduction and the effects not only seem to be greater but also longer lasting.Furthermore, we demonstrated that 11C-Choline and 18F-FDG together find more tumors that are relevant for clinical decision-making in patients suspected of HCC recurrence. The thesis also offers two prospective study protocols, namely a comparison of 68Ga-DOTA-TOC with the new somatostatin tracer 18F-SiTATE in NET and a comparison of ablation with SIRT as a bridge strategy in liver transplantation. These results suggest that broader use of 18F-DOPA in PET diagnosis of NET is possible and that higher tumor-targeted dosages in SIRT can lead to better treatment