Allison B. Weisbrod

Patient Specific Tumor Growth Prediction Using Multimodal Images

Personalized tumor growth model is valuable in tumor staging and therapy planning. In this paper, we present a patient specific tumor growth model based on longitudinal multimodal imaging data including dual-phase CT and FDG-PET. The proposed Reaction-Advection-Diffusion model is capable of integrating cancerous cell proliferation, infiltration, metabolic rate and extracellular matrix biomechanical response. To bridge the model with multimodal imaging data, we introduce Intracellular Volume Fraction (ICVF) measured from dual-phase CT and Standardized Uptake Value (SUV) measured from FDG-PET into the model. The patient specific model parameters are estimated by fitting the model to the observation, which leads to an inverse problem formalized as a coupled Partial Differential Equations (PDE)-constrained optimization problem. The optimality system is derived and solved by the Finite Difference Method. The model was evaluated by comparing the predicted tumors with the observed tumors in terms of average surface distance (ASD), root mean square difference (RMSD) of the ICVF map, average ICVF difference (AICVFD) of tumor surface and tumor relative volume difference (RVD) on six patients with pathologically confirmed pancreatic neuroendocrine tumors. The ASD between the predicted tumor and the reference tumor was 2.4±0.5mm, the RMSD was 4.3±0.4%, the AICVFD was 2.6±0.6%, and the RVD was 7.7±1.3%.

Assessment of Tumor Growth in Pancreatic Neuroendocrine Tumors in von Hippel Lindau Syndrome

BACKGROUND The incidence of pancreatic neuroendocrine tumors (PNETs) is increasing, but only a subset of these heterogeneous tumors will progress to malignant disease, which is associated with a poor prognosis. Currently, there are limited data on the natural history of these tumors and it is difficult to determine which patients require surgical intervention because the risk of metastatic disease cannot be accurately determined. STUDY DESIGN We conducted a prospective study of 87 patients with von Hippel Lindau syndrome-associated solid pancreatic lesions to determine the natural history of these tumors with biochemical testing, follow-up anatomic and functional imaging, and advanced imaging analysis, with a median follow-up of 4 years. RESULTS Approximately 20% of consecutive tumor measurements during follow-up were decreased in size and 20% showed no change. This included 2 of 4 surgically proven malignant tumors, which had a net decrease in tumor size over time. Tumor volume, as derived from greatest diameter and volumetric measurements, showed good correlation to pathology tumor measurement of surgically resected tumors (Spearman rank correlation ρ = 0.72, p = 0.0011, and ρ = 0.83, p < 0.0001, respectively). Tumor density measurement had an inverse relationship with tumor size (Spearman rank correlation -0.22, p = 0.0047). A tumor density cutoff of 200 was 75% specific for malignant tumors. CONCLUSIONS Pancreatic neuroendocrine tumors demonstrate a nonlinear growth pattern, which includes periods of no growth and apparent decrease in size by imaging. These growth patterns are variable and are not associated with tumor grade and malignancy. Tumor density, as measured in this cohort, may offer a specific diagnostic tool for malignant disease.

Association of Type-O Blood with Neuroendocrine Tumors in Multiple Endocrine Neoplasia Type 1

CONTEXT The ABO blood type system describes the expression of human blood group antigens found on both erythrocytes and normal tissue throughout the body. We recently reported an association between O blood type and the manifestation of pancreatic neuroendocrine tumors in a cohort of patients with Von Hippel-Lindau syndrome. OBJECTIVE The aim of the study was to determine whether there is an association of ABO blood type with the development of neuroendocrine tumors in patients with multiple endocrine neoplasia, type 1 (MEN-1). DESIGN A retrospective analysis of 105 patients with MEN-1 was performed. Demographic, clinical, and biochemical data were analyzed by ABO blood type. Fishers exact test was used to determine association between ABO blood type and manifestation of neuroendocrine tumor. RESULTS Demographic and clinical characteristics were similar amongst blood type cohorts. We found an association between O blood type and the manifestation of a primary neuroendocrine tumor of the gastrointestinal tract, lung, pancreas, and thymus in patients with MEN-1 (P = 0.01). Sixteen of 17 (94%) metastatic tumors had type-O blood, compared to 32 of 43 (74%) with a benign tumor who had non-O blood type. CONCLUSIONS Our findings suggest an association between O blood type and the manifestation of a primary neuroendocrine tumor in patients with MEN-1. Prospective clinical studies are warranted to see whether patient blood type status may be a useful addition to current screening and surveillance practices.

Clinical Utility of Functional Imaging with 18F-FDOPA in Von Hippel-Lindau Syndrome

CONTEXT Von Hippel-Lindau (VHL) syndrome is an inherited cancer syndrome in which patients are at risk of developing multiple tumors in different organs. 6-L-¹⁸F-fluorodihydroxyphenylalanine (¹⁸F-FDOPA) positron emission tomography (PET) is a relatively new metabolic imaging tracer proposed for the use of localizing sites of neuroendocrine tumors. There are limited data on the clinical utility of using ¹⁸F-FDOPA PET for identifying neuroendocrine tumors in a high-risk population such as VHL. OBJECTIVE The aim of this prospective study was to evaluate the clinical utility of ¹⁸F-FDOPA PET in patients with VHL-related tumors. DESIGN Radiological findings were prospectively collected from four imaging modalities: computed tomography, magnetic resonance imaging (MRI), ¹⁸F-fluorodeoxyglucose PET, and ¹⁸F-FDOPA PET. ¹⁸F-FDOPA PET findings were compared with those from other imaging modalities, as well as with clinical and laboratory data, and pathology findings if patients underwent an operation. RESULTS In 52 patients with VHL, 390 lesions were identified by computed tomography (n = 139), MRI (n = 117), ¹⁸F-fluorodeoxyglucose PET (n = 94), and ¹⁸F-FDOPA PET (n = 40). ¹⁸F-FDOPA PET identified 20 pancreatic and 20 extrapancreatic tumors, including lesions in the adrenal gland (n = 11), kidney (n = 3), liver (n = 4), lung (n = 1), and cervical paraganglioma (n = 1). These tumor sites were not seen by conventional imaging studies in 9.6% of patients and 4.4% of lesions. Seven of eight patients who had an ¹⁸F-FDOPA PET-positive lesion underwent resection, and pathology showed a neuroendocrine tumor. Four of 10 patients with positive adrenal uptake had elevated catecholamine levels, and six of 10 patients had a discrete mass on axial imaging. CONCLUSIONS ¹⁸F-FDOPA PET is a useful complementary imaging study to detect neuroendocrine tumors in patients with VHL undergoing surveillance, especially in those suspected to have adrenal pheochromocytoma or unusual ectopic locations.

Prospective Evaluation of the Clinical Utility of 18-Fluorodeoxyglucose PET CT Scanning in Patients with Von Hippel-Lindau–Associated Pancreatic Lesions

BACKGROUND The natural history of pancreatic neuroendocrine neoplasms (PNENs) in patients with Von Hippel-Lindau (VHL) disease is poorly defined. Management of patients with PNENs is challenging because there are no reliable preoperative criteria to detect malignant lesions, and the majority of resected tumors are found to be benign. The aim of this study was to determine whether 18-fluorodeoxyglucose-positron emission tomography ((18)FDG-PET) uptake predicts growth and detects malignant VHL-associated PNENs. STUDY DESIGN We performed a prospective study of 197 patients with VHL-associated pancreatic lesions. Clinical and imaging characteristics were analyzed to study the associations between FDG-PET uptake, tumor growth, and the development of metastatic disease. RESULTS One hundred nine of 197 patients had solid pancreatic lesions and underwent both CT and (18)FDG-PET scanning, which identified 165 and 144 lesions, respectively. Metastatic disease was detected by (18)FDG-PET in 3 patients in whom it was not detected by CT scan and suggested non-neoplastic disease in 3 patients. Maximum standardized uptake values (SUV) on (18)FDG-PET correlated with tumor size on CT (r = 0.47, p < 0.0001), and an increase in SUVmax was associated with tumor growth (r = 0.36, p = 0.0062). No association was seen between (18)FDG-PET uptake and age, VHL genotype, or serum chromogranin A levels. CONCLUSIONS Scanning with FDG-PET identifies metastatic disease not detected by CT scan and avoids resection of non-PNEN lesions that have no malignant potential in patients with VHL-associated PNENs. It should be considered as a valuable functional imaging modality in the clinical management of patients with VHL-associated PNENs.

Multimodal Image Driven Patient Specific Tumor Growth Modeling

Personalized tumor growth model using clinical imaging data is valuable in tumor staging and therapy planning. In this paper, we build a patient specific tumor growth model based on longitudinal dual phase CT and FDG-PET. We propose a reaction-advection-diffusion model integrating cancerous cell proliferation, infiltration, metabolic rate and extracellular matrix biomechanical response. We then develop a scheme to bridge our model with multimodal radiologic images through intracellular volume fraction (ICVF) and Standardized Uptake Value (SUV). The model was evaluated by comparing the predicted tumors with the observed tumors in terms of average surface distance (ASD), root mean square difference (RMSD) of the ICVF map, the average ICVF difference (AICVFD) of tumor surface and the tumor relative volume difference (RVD) on six patients with pathologically confirmed pancreatic neuroendocrine tumors. The ASD between the predicted tumor and the reference tumor was 2.5 +/- 0.7 mm, the RMSD was 4.3 +/- 0.6%, the AICVFD was 2.6 +/- 0.8%, and the RVD was 7.7 +/- 1.9%.

Tumor growth modeling based on dual phase CT and FDG-PET

In this paper, we presented a method to deal with tumor growth prediction using multimodality non-invasive clinical imaging data. We developed a reaction-diffusion tumor growth model that (1) relates cell metabolic rate and tumor growth, and (2) is driven by clinical imaging data. The metabolic rate was incorporated into the model through cell proliferation rate of the model via energy conservation law. FDG-PET scan was employed to provide non-invasive measurement of the metabolic rate. To bridge the gap between the model prediction and the clinical observation, we introduced intracellular volume fraction (ICVF) using dual phase CT scans to link them. The patient specific model parameters were estimated by minimizing the deviation between the predicted ICVF and the measured ICVF with deformation corrected. The experiment was conducted on two pancreatic neuroendocrine tumors. The average surface distance between the predicted tumor and the reference tumor was 2.1 mm and 2.7 mm, respectively, and the mean square difference of the ICVF map was 5.4% and 3.8%, respectively.