Charles Jillings, CEO of Utilico, energized by strong economic momentum across Latin America. Watch the video here.
London South East prides itself on its community spirit, and in order to keep the chat section problem free, we ask all members to follow these simple rules. In these rules, we refer to ourselves as "we", "us", "our". The user of the website is referred to as "you" and "your".
By posting on our share chat boards you are agreeing to the following:
The IP address of all posts is recorded to aid in enforcing these conditions. As a user you agree to any information you have entered being stored in a database. You agree that we have the right to remove, edit, move or close any topic or board at any time should we see fit. You agree that we have the right to remove any post without notice. You agree that we have the right to suspend your account without notice.
Please note some users may not behave properly and may post content that is misleading, untrue or offensive.
It is not possible for us to fully monitor all content all of the time but where we have actually received notice of any content that is potentially misleading, untrue, offensive, unlawful, infringes third party rights or is potentially in breach of these terms and conditions, then we will review such content, decide whether to remove it from this website and act accordingly.
Premium Members are members that have a premium subscription with London South East. You can subscribe here.
London South East does not endorse such members, and posts should not be construed as advice and represent the opinions of the authors, not those of London South East Ltd, or its affiliates.
Looks like a buying signal to me ...
The key point is who imaging biometrics is working with on these projects!
The grant in collaboration with BNI includes working with major scanner vendors (GE, Siemens, and Philips) to harmonise the way perfusion MRI data is collected and post-processed. The involvement of the major scanner vendors is exciting and very positive, and the Company looks forward to their continued collaboration and support.
QIN Reference Listing:
Published Manuscripts
Schmainda KM, Zhang Z, Prah M, Snyder BS, Gilbert MR, Sorensen AG, Barboriak DP, & Boxerman JL. (2015). “Dynamic susceptibility contrast MRI measures of relative cerebral blood volume as a prognostic marker for overall survival in recurrent glioblastoma: results from the ACRIN 6677/RTOG 0625 multi-center trial.” Neuro-Oncology,17(8):1148-56. PMID: 25646027.
Prah MA, Stufflebeam SM, Paulson ES, Kalpathy-Cramer J, Gerstner ER, Batchelor TT, Barboriak DP, Rosen BR, Schmainda KM. “Repeatability of standardized and normalized relative CBV in patients with newly diagnosed glioblastoma.” Am J Neuroradiol 36(9):1654-61 (2015). PMID: 26066626.
Jafari-Khouzani K, Emblem KE, Kalpathy-Cramer J, Bjornerud A, Vangel M, Gerstner E, Schmainda KM, Paynabar K, Wu O, Wen PY, Batchelor T, Rosen B, Stufflebeam SM. “Repeatability of cerebral perfusion using dynamic susceptibility contrast MRI on glioblastoma patients.” Translational Oncology 8(3):137-46 (2015). PMID: 26055170.
Boxerman JL, Schmainda KM, Zhang Z, Barboriak DP. “Dynamic susceptibility contrast MRI measures of relative cerebral blood volume continue to show promise as an early response marker in the setting of bevacizumab treatment.” Neuro Oncol 17(11):1538-9 (2015). PMID: 26361983.
Mickevicius NJ, Carle AB, Bluemel T, Santarriaga S, Schloemer F, Shumate D, Connelly J, Schmainda KM, LaViolette PS. “Location of brain tumor intersecting white matter tracts predicts patient prognosis.” J Neurooncol 125(2):393-400 (2015). PMID 26376654.
Renu D, Aggarwal P, Bhat V, Cherukuri SC, Livi C, Rosenberg M, Tata P, Al-Gizawiy M, Schmainda KM, Mirza SP. Molecular Subtypes in Glioblastoma Multiforme: Integrated Analysis using Agilent GeneSpring® Multi-Omics Software. Agilent Technologies, Inc. 2015; 5991-5505EN.
Nguyen HS, Milback N, HUrrell SL, Cochran E, Connelly J, Bovi JA, Schultz CJ, Mueller WM, Rand SD, Schmainda KM, LaViolette PS. “Progressing bevacizumab-induced diffusion restriction is associated with coagulative necrosis surrounded by viable tummor and decreased overall survival in patients with recurrent glioblastoma.” AJNR Am J Neuorradiology 37(12):2201-2208 (2016). PMID: 27492073.
McGarry SD, Hurrell SL, Kaczmarowski AL, Cochran EJ, Connelly J, Rand SD, Schmainda KM, LaViolette PS. “Magnetic resonance imaging-based radiomic profiles predict patient prognosis in newly diagnosed glioblastoma before therapy.” Tomography 2(3):223-228 (2016). PMID: 27774518.
Paulson ES, Prah DE, Schmainda KM. “Spiral perfusion imaging with consecutive echoes (SPICE) for the simultaneous mapping of DSC- and DCE-MRI parameters in brain tumor patients: theory and initial feasibility. Tomography 2(4):297-307 (2016). PMID: 28090589.
The overall goal of this U01 project (CA176110) is to develop and validate both standard and novel perfusion-weighted MRI (PWI) and diffusion-weighted MRI (DWI) biomarkers for evaluation of brain tumors and their response to therapies. Two PWI methods will be characterized for clinical trials. The first more wide-spread DSC (dynamic susceptibility contrast) approach provides tumor rCBV (relative cerebral blood volume) measurements obtained after a pre-load of contrast agent and corrected for confounding contrast agent leakage effects. The second approach, while less-proven has high-potential to become the most comprehensive perfusion solution. It consists of using a spiral perfusion imaging method with consecutive echoes (SPICE), which enables the simultaneous collection of both DSC (dynamic susceptibility contrast) and DCE (dynamic contrast enhanced) perfusion data using only a single dose of contrast agent and incorporates comprehensive correction for leakage effects. In addition, the team will continue to explore the potential of DWI methods for the evaluation of treatment response, specifically by computing changes in the apparent diffusion coefficient (ADC) across time and creating functional diffusion maps (fDM) within non-contrast-agent-enhancing regions.
While both PWI and DWI have demonstrated great promise for treatment monitoring, studies defining their test-retest repeatability, necessary for use of these techniques in clinical trials, are lacking, and thus represent the focus of Aim 1. In addition, early results suggest that hybrid PWI/DWI maps will likely provide the most complete assessment of treatment response, a hypothesis that will be tested in Aim 2. Finally, in order to make the optimized PWI/DWI technology and workflow available in a robust and cost-effective manner for clinical trials and standard practice, Aim 3 involves the development of a commercial integrated image analysis platform for use in large-scale multi-center clinical trials. This aim is being accomplished in collaboration with Imaging Biometrics LLC, co-investigators on the U01.
Point 7 of the update from January doesn’t get much discussion which I find odd as it goes into detail about the FIRST grant we received (yes we have 2) here it is
7. The Company is fulfilling the work outlined in its two funded grants collaborating with MCW and the Barrow Neurological Institute ("BNI"). Both grants are "industrial-academic partnerships", aimed at commercialising technologies and incorporating them into routine clinical use, and each grant is entering into the second year of its five-year term. The grant in collaboration with MCW is the second such award as part of the Quantitative Imaging Network ("QIN"). The QIN is an initiative sponsored by the US National Cancer Institute ("NCI") promoting research, development, and clinical validation of quantitative imaging tools and methods for the measurement or prediction of tumour response to therapies in clinical trial settings, with the overall goal of facilitating clinical decision making. The grant in collaboration with BNI includes working with major scanner vendors (GE, Siemens, and Philips) to harmonise the way perfusion MRI data is collected and post-processed. The involvement of the major scanner vendors is exciting and very positive, and the Company looks forward to their continued collaboration and support.
Here’s a link to Kathleen Schmainda overall goals of this project
https://imaging.cancer.gov/programs_resources/specialized_initiatives/qin/qinsites/medical_college_of_wisconsin.htm
The Quantitative Imaging Network (QIN) promotes research, development and clinical validation of quantitative imaging tools and methods for the measurement or prediction of tumor response to therapies in clinical trial settings, with the overall goal of facilitating clinical decision making. Projects include the development and adaptation/implementation of quantitative imaging methods, imaging protocols, and software solutions/tools (used with existing commercial imaging platforms and instrumentation) and application of these methods in current and planned clinical therapy trials. The research projects focus on image-derived quantitative measurements of responses to drugs and/or radiation therapy during clinical trials or standard of care. To achieve the goals of the QIN, multidisciplinary teams which include oncologists as well as clinical and basic imaging scientists are required. The involvement of industrial partners in the development and adaptation/implementation of quantitative imaging methods to aid cancer therapies are encouraged.