Citations

Abstract With mean survival from glioblastoma multiforme (GBM) barely edging over 15 months, it become imperative to develop novel tools informing on both progression and treatment efficacy. As the aggressive growth of GBM outstrips available resources, regions of hypoxia develop. Hypoxia can be clinically assessed through [18F]-flouromisonidazole (FMISO) PET. However, PET imaging suffers from low resolution and reconstruction artifact. We present the comparative and predictive results of a multi-stage model utilizing the mathematical biology of cancer and the physics of PET imaging. Our mathematical model of GBM characterizes cancer cells into the interacting phenotypes of normoxic, hypoxic, and necrotic cells supported by vasculature. The pharmacokinetic activity of FMISO is induced in the simulated tissue then acquired and reconstructed by an analytic simulator of the PET process. This multi-stage process creates a patient-specific virtual PET images with characteristic of the clinical PET scan. Extending previous work, we model the full three-dimensional dynamics of tumor progression, pharmacokinetic activity, and FMISO PET for the tumor kinetics of six GBM patients. Virtual and clinical FMISO PET images are compared. Overall hypoxic burden and spatial distribution show strong correspondence between virtual and clinical FMISO PET images for all six patients. Simulated FMISO PET dynamics, with tumor kinetics derived from routine clinical MRI scans, provide a unique and evolving tool giving insight into the biological connections between magnetic resonance and molecular imaging. Citation Format: Joshua Jacobs, Andrea Hawkins-Darrud, Robert Harrison, Sandra Johnston, Paul Kinahan, Kristin Swanson. Correlating magnetic resonance and molecular imaging using three dimensional untreated virtual control. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A10.

Abstract Purpose: Investigate the utility of patient-specific spatial predictions of tumor cell density from a bio-mathematical model. Introduction: Glioblastomas (GBMs) are the most malignant of all primary brain tumors. While it is known there is always a non-detectable portion of the tumor, current techniques of monitoring GBM progression, imaging and initial histological assessment, are not able to reliably estimate the tumor invasion past the enhancing region on T2-Weighted (T2W) imaging. Over the last two decades, a large effort has been made to create a simple patient-specific mathematical model of gliomas. The resulting model, referred to as the Proliferation-Invasion (PI) model, is based on two key parameters, the net growth rate, ρ, and the dispersal coefficient, D. In this model, the ratio of D/ρ is related to degree of invasion and the product D*ρ, is related to the speed of growth. The intuitive understanding provided by this model has been able to provide patient-specific understanding of disease kinetics enabling prediction of outcomes following surgical resection, radiation and the development of a prognostic response metric. Previous literature utilizing this model has been based on the assumption that what is seen on the pretreatment T1-Weighted contrast-enhanced (T1Gd) and T2W, images correspond to an 80% and 16% tumor cell density threshold respectively. This assumption allows for an estimate of D/ρ from a single time point of imaging. While these values were based on extensive experience, for ethical and technical reasons, they have never been rigorously investigated histologically. Recent technological advances have made it possible for surgeons to use an MRI to guide the acquisition of tissue making it possible to know with a good degree of accuracy where on the MR image the histological specimen comes from. Methods: Model Calibration : To estimate D/ρ for each patient, we assume abnormalities on the T1Gd and T2W images correspond to an 80% and 16% tumor cell density threshold respectively. We then utilize a Bayesian calibration approach based on adaptive grid refinement while holding the velocity constant to find the most likely value of D/ρ to match the observed radial measurements. Three-Dimensional Density Maps : Given a gray/white segmentation and an estimate for D/ρ, we can build a tumor cell density prediction in the patient's anatomy using the Eikonal equations and the modified Fast Marching Method (FMM) algorithm presented by Konukoglu et al. Patient Cohort : Eighteen patients were recruited with clinically suspected GBM undergoing preoperative stereotactic MRI for surgical resection with IRB approval Barrow Neurological Institute and Mayo Clinic in Arizona. Surgical Biopsy : Pre-operative conventional MRI, including T1Gd and T2W, was utilized to guide stereotactic biopsies. An average of 5–6 tissue specimens were acquired from each tumor by using stereotactic surgical localization, following the smallest possible diameter craniotomies to minimize brain shift. Histological Analysis : 4 μm tissue sections were stained with hematoxylin and eosin (H&E) for neuropathology review. H&E slides were reviewed by a neuropathologist. The percent tumor nuclei in the field was estimated. Results and Conclusion: Our analysis showed that the intuitive ordering of diffuse to nodular tumor profiles from the PI model is consistent with the histologic data. Further, utilizing the histologic data, limitations to a universal threshold cutoff of the T2/FLAIR region are specified and a better threshold cutoff value is suggested. We hope that this paper will lead to more studies of this kind resulting in more accurate ways to predict the spatial distribution of GBM tumor cells from medical imaging. Such advances could revolutionize surgical procedures and radiation therapy and may enable additional insights into tumor kinetic differences meaningful for treatment. Citation Format: Andrea Hawkins-Daarud, Lauren DeGirolamo, Joshua Jacobs, Kamala Clark-Swanson, Jennifer M. Eschbacher, Kris A. Smith, Peter Nakaji, Leslie C. Baxter, John P. Karis, Teresa Wu, J. Ross Mitchell, Jing Li, Leland Hu, Kristin R. Swanson. Histologic evidence for a bio-mathematical model of glioblastoma invasion. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A08.

Abstract Background: It is documented that inequities in research participation by minority and underrepresented populations limits the progression of personalized medicine for cancer treatment for these groups. A lack of understanding essential information during the consent process and poor physician-patient communication have been noted as two overarching barriers to patients participating in translational, clinical and biospecimen research. To address these major patient barriers, we developed a plain language research literacy support (RLS) tool to improve the consent process and facilitate dialogue between physicians/research staff and patients. We describe the tool's iterative development process and testing of the developed culturally appropriate RLS tool. Methods: We tested the tool among: 1) patient participants ≥18 years of age, who were able to read and speak English from communities associated with five academic centers in the Midwest and Northeast United States; and 2) eligible recruiters who were employed at an academic center and actively recruiting patients into research. The development process for the RLS tool consisted of two phases: cognitive and beta testing. During cognitive testing, we solicited feedback from patient and recruiter participants about the content and format of the tool including low literacy language, pictures and recommendations for additional content. The tool consisted of concept cards to provide information to assist patients in making an informed decision about participating in research. During beta testing, a condensed version of the tool was tested to assess acceptability and change in knowledge about research participation. Results: Participants included 155 patients (52: cognitive testing phase; 103: beta testing phase) and 20 recruiter participants. Patient participants were mostly females (71%). Self-identified race of patients included: Whites (43%), African Americans (32%), Native Americans (20%), and other (6%). In addition, 23% of patient participants self-identified as Hispanic. During the cognitive testing phase, patient participants reported that the information was clearly laid out and the tool explained the different steps in the recruitment and enrollment process. Patient participants indicated they had learned new information related to randomization, standard of care, coded-information, and biobanking. Although some patient participants acknowledged the cards contained a great deal of information, most reported that the information was essential. Several participants suggested cards be tailored for the Native American population. Recruiters indicated that the cards provided useful information and would assist patients and research staff. During beta testing phase, 98% of participants agreed the information on the cards helped them understand clinical research. After reviewing the cards, 49% of patient participants reported that they would be very likely to participate in research and 32% reported being somewhat likely to participate in research. The majority (61%) of participants indicated that if invited to participate in a research study, they would prefer that the cards would be mailed to them in advance while 34% wanted to review the cards at their medical appointment. Half of the participants preferred accessing the cards on a computer if administered in a video format. Conclusion: The RLS tool was well received among patient and recruiter participants, making it a potentially valuable resource for enrollment of minority and underrepresented patients into health research. The next step will be to test the RLS tool for effectiveness in a randomized controlled trial. Citation Format: Erika E. de la Riva, Rodney Haring, Elisa M. Rodriguez, Evelyn Gonzalez, Mira Katz, Nikia Clark, Whitney Ann E. Henry, Rosa O. Ortiz, Barret J. Zimmermann, Marla L. Clayman, Deborah O. Erwin, Judith S. Kaur, Melissa A. Simon. Development and beta testing of a culturally appropriate research literacy support tool to increase research participation among minority and underrepresented populations. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr A11.

PurposeTo compare algorithms performing material decomposition and classification in dual‐energy CT, it is desirable to know the ground truth of the lesion to be analyzed in real patient data. In this work, we developed and validated a framework to insert digital lesions of arbitrary chemical composition into patient projection data acquired on a dual‐source, dual‐energy CT system.MethodsA model that takes into account beam‐hardening effects was developed to predict the CT number of objects with known chemical composition. The model utilizes information about the x‐ray energy spectra, the patient/phantom attenuation, and the x‐ray detector energy response. The beam‐hardening model was validated on samples of iodine (I) and calcium (Ca) for a second‐generation dual‐source, dual‐energy CT scanner for all tube potentials available and a wide range of patient sizes. The seven most prevalent mineral components of renal stones were modeled and digital stones were created with CT numbers computed for each patient/phantom size and x‐ray energy spectra using the developed beam‐hardening model. Each digital stone was inserted in the dual‐energy projection data of a water phantom scanned on a dual‐source scanner and reconstructed with the routine algorithms in use in our practice. The geometry of the forward projection for dual‐energy data was validated by comparing CT number accuracy and high‐contrast resolution of simulated dual‐energy CT data of the ACR phantom with experimentally acquired data.ResultsThe beam‐hardening model and forward projection method accurately predicted the CT number of I and Ca over a wide range of tube potentials and phantom sizes. The images reconstructed after the insertion of digital kidney stones were consistent with the images reconstructed from the scanner, and the CT number ratios for different kidney stone types were consistent with data in the literature. A sample application of the proposed tool was also demonstrated.ConclusionA framework was developed and validated for the creation of digital objects of known mineral composition, and for inserting the digital objects into projection data from a commercial dual‐source, dual‐energy CT scanner. Among other applications, it will allow a systematic investigation of the impact of scan and reconstruction parameters on kidney stone dual‐energy properties under rigorously controlled conditions.

243 Background: Cbz/pred extends survival in mCRPC patients (pts) following docetaxel and first-line studies comparing Cbz to docetaxel are ongoing. Mito/pred also has anti-tumor activity in mCRPC and a non-overlapping mechanism of action and toxicity profile with Cbz. A multicenter phase I trial was initiated through the DOD PCCTC to establish the maximally tolerated dose (MTD) of the combination of Cbz, Mito, and Pred. Methods: Chemotherapy (chemo)-naive pts with mCRPC were enrolled in an accelerated titration design. The primary objective was to determine the MTD of CAMP; secondary objectives included assessing PSA and objective response rates and duration of response. Starting dose of Cbz was 25 mg/m2 (the currently approved single-agent dose) and Mito 4 mg/m2, administered on day 1 of a 21-day cycle. Mito was escalated by 2 mg/m2 per dose level. Pred 5 mg BID and pegfilgrastim were administered with each cycle. Results: 9 pts were enrolled (dose level I, N = 1; dose level II, N = 1; dose level III, N = 3; dose level IV N = 4). The median age was 67 (range 55-81) and the median baseline PSA was 82.3 (range 20.4-791.2). There were 2 DLTs observed at dose level IV (Cbz 25 mg/m2 + mito 10 mg/m2), both grade 4 sepsis. The most common grade 3 adverse events were hematologic (neutropenia, n = 5; febrile neutropenia, n = 2, thrombocytopenia, n = 2). 6 of 9 pts remain on study (range 2.2 - 10.5+ months). Maximal PSA declines from baseline > 50% have been observed in 4/7 (57%) evaluable pts to date. 2 of 4 pts with measurable disease have experienced partial responses and a third has had a minor response after 4 cycles of chemo. The median progression-free survival and duration of response have not been reached. Conclusions: The approved single-agent dosage of Mito (12 mg/m2) could not be safely reached in combination with Cbz 25 mg/m2. Pre-planned evaluation of an alternate dosing strategy combining Mito with Cbz 20 mg/m2, which has demonstrated activity in mCRPC and potentially less hematologic toxicity, is underway. Preliminary efficacy data are encouraging but additional follow-up and further study of the treatment combination is required. Clinical trial information: NCT01594918.