IP Library › Granted Patent US 12,229,957
Granted Patent B2
US 12,229,957 · App. 18/307,316 · Granted Feb 18, 2025

Systems and methods for diagnostics for management of cardiovascular disease patients

Inventors: Andrew J. Buckler (Boston, MA); Kjell Johnson (Ann Arbor, MI); Xiaonan Ma (South Hamilton, MA); Keith A. Moulton (Amesbury, MA); David S. Paik (Moon Bay, CA)
Assignee: ELUCID BIOIMAGING INC.
G06T7/0012G06F18/211G06F18/2148G06F18/24G06N3/08G06N20/00G06T3/00G06T5/73G06T7/11G06V10/25G06V10/764G06V20/69G06T2207/10048G06T2207/10081G06T2207/10088G06T2207/10101G06T2207/10104G06T2207/10108G06T2207/10132G06T2207/20081G06T2207/30096G06T2207/30104
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,229,957
App. No.
18/307,316
Filed
Apr 26, 2023
Granted
Feb 18, 2025
Kind
B2
Examiner
HUYNH, VAN D
Art Unit
2665
USPC
382/128
Abstract

Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.

Claims (14)

1. A system for implementing artificial intelligence, the system comprising:

a processor configured to:

receive imaging data of Computed Tomography (CT), Magnetic resonance (MR), Ultrasound (US), or Positron Emission Tomography (PET) of a patient;

determine, based on the received imaging date, a first set of quantities of anatomic descriptors, plaque descriptors or both as spatial distributions of biological properties, wherein the spatial distribution of biological properties are based on one or more transformations, wherein the one or more transformations include unwrapping the received imaging data;

determine, based on the first set of quantities, a second set of quantities that identify, characterize or both vascular disease burden as a medical condition; and

output the identification or characterization of the vascular disease burden.

2. The system of claim 1 wherein the quantities are lipid core, fibrosis, calcification, hemorrhage, permeability, thrombosis, ulceration, remodeling ratio, percent stenosis, percent dilation, wall thickness or any combination thereof.

3. The system of claim 1 wherein the processor is further configured to receive a patient's clinical history, a patient's symptoms, one or more diagnostic tests, or any combination thereof; and use any of the received patient's clinical history, received patient's symptoms, or received one or more diagnostic tests to determine the first set, the second set or both.

4. The system of claim 1 wherein the processor is further configured to receive one or more user inputs to adjust the first set, the second set, the vascular disease burden or any combination thereof.

5. The system of claim 1 wherein the processor is further configured to cause the one or more outputs to be transmitted to a display and, displayed using graphics and text.

6. The system of claim 1 wherein the processor utilizes one or more deep-learning algorithms.

7. The system of claim 1 wherein the second set of quantities, identify, characterize or both risk assessment or stratification of disease as a medical condition based on the first set of quantities.

8. The system of claim 1 wherein the second set of quantities, identify, characterize or both predicting a course of disease as a medical condition based on the first set of quantities, wherein the course of disease comprises adverse event outcomes.

9. The system of claim 1 wherein the second set of quantities, identify, characterize or both indicate a potential effectiveness of one treatment over another in individual patient based on the first set of quantities.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 27, 2023
From: BUCKLER, ANDREW J.; JOHNSON, KJELL; MA, XIAONAN; MOULTON, KEITH A.; PAIK, DAVID S.
To: ELUCID BIOIMAGING INC.
Reel/Frame 063459/0643 →
Continuity (11)
Continuation 17328414 · May 24, 2021
Continuation 16203418 · Nov 28, 2018
Continuation In Part 14959732 · Dec 4, 2015
Provisional Application 62771448 · Nov 26, 2018
Provisional Application 62676975 · May 27, 2018
Provisional Application 62219860 · Sep 17, 2015
Provisional Application 62205295 · Aug 14, 2015
Provisional Application 62205313 · Aug 14, 2015
Provisional Application 62205305 · Aug 14, 2015
Provisional Application 62205322 · Aug 14, 2015
Related Publication 20230326166A1 · Oct 12, 2023
References Cited (344)
US 6108635A · Herren et al. · 2000 [cited by applicant]
US 7127095B2 · Fakhri et al. · 2006 [cited by applicant]
US 7519211B2 · Fakhri et al. · 2009 [cited by applicant]
US 8157742B2 · Taylor · 2012 [cited by applicant]
US 8175355B2 · Fakhri et al. · 2012 [cited by applicant]
US 8249815B2 · Taylor · 2012 [cited by applicant]
US 8311747B2 · Taylor · 2012 [cited by applicant]
US 8311748B2 · Taylor et al. · 2012 [cited by applicant]
US 8311750B2 · Taylor · 2012 [cited by applicant]
US 8315812B2 · Taylor · 2012 [cited by applicant]
US 8315813B2 · Taylor et al. · 2012 [cited by applicant]
US 8315814B2 · Taylor et al. · 2012 [cited by applicant]
US 8321150B2 · Taylor · 2012 [cited by applicant]
US 8374689B2 · Gopinathan et al. · 2013 [cited by applicant]
US 8386188B2 · Taylor et al. · 2013 [cited by applicant]
US 8496594B2 · Taylor et al. · 2013 [cited by applicant]
US 8523779B2 · Taylor et al. · 2013 [cited by applicant]
US 8548778B1 · Hart et al. · 2013 [cited by applicant]
US 8553832B2 · Camus et al. · 2013 [cited by applicant]
US 8554490B2 · Tang et al. · 2013 [cited by applicant]
US 8594950B2 · Taylor · 2013 [cited by applicant]
US 8606530B2 · Taylor · 2013 [cited by applicant]
US 8630812B2 · Taylor · 2014 [cited by applicant]
US 8706457B2 · Hart et al. · 2014 [cited by applicant]
US 8734356B2 · Taylor · 2014 [cited by applicant]
US 8734357B2 · Taylor · 2014 [cited by applicant]
US 8768669B1 · Hart et al. · 2014 [cited by applicant]
US 8768670B1 · Hart et al. · 2014 [cited by applicant]
US 8812245B2 · Taylor · 2014 [cited by applicant]
US 8812246B2 · Taylor · 2014 [cited by applicant]
US 8824752B1 · Fonte et al. · 2014 [cited by applicant]
US 8825151B2 · Gopinathan et al. · 2014 [cited by applicant]
US 8831314B1 · Fonte et al. · 2014 [cited by applicant]
US 8831315B1 · Fonte et al. · 2014 [cited by applicant]
US 8855984B2 · Hart et al. · 2014 [cited by applicant]
US 8861820B2 · Fonte et al. · 2014 [cited by applicant]
US 8914264B1 · Hart et al. · 2014 [cited by applicant]
US 8970578B2 · Voros et al. · 2015 [cited by applicant]
US 8977339B1 · Wu et al. · 2015 [cited by applicant]
US 8983155B2 · McIntyre · 2015 [cited by examiner]
US 9002690B2 · Hart et al. · 2015 [cited by applicant]
US 9008405B2 · Fonte et al. · 2015 [cited by applicant]
US 9042613B2 · Spilker et al. · 2015 [cited by applicant]
US 9043190B2 · Grady et al. · 2015 [cited by applicant]
US 9063634B2 · Hart et al. · 2015 [cited by applicant]
US 9063635B2 · Hart et al. · 2015 [cited by applicant]
US 9078564B2 · Taylor · 2015 [cited by applicant]
US 9081882B2 · Taylor · 2015 [cited by applicant]
US 9087147B1 · Fonte · 2015 [cited by applicant]
US 9119540B2 · Sharma et al. · 2015 [cited by applicant]
US 9149197B2 · Taylor · 2015 [cited by applicant]
US 9152757B2 · Taylor · 2015 [cited by applicant]
US 9155512B2 · Choi et al. · 2015 [cited by applicant]
US 9167974B2 · Taylor · 2015 [cited by applicant]
US 9168012B2 · Hart et al. · 2015 [cited by applicant]
US 9189600B2 · Spilker et al. · 2015 [cited by applicant]
US 9195801B1 · Sankaran et al. · 2015 [cited by applicant]
US 9202010B2 · Taylor et al. · 2015 [cited by applicant]
US 9220418B2 · Choi et al. · 2015 [cited by applicant]
US 9220419B2 · Choi et al. · 2015 [cited by applicant]
US 9226672B2 · Taylor · 2016 [cited by applicant]
US 9235679B2 · Taylor · 2016 [cited by applicant]
US 9239905B1 · Sankaran et al. · 2016 [cited by applicant]
US 9247918B2 · Sharma et al. · 2016 [cited by applicant]
US 9262581B2 · Kim et al. · 2016 [cited by applicant]
US 9265473B2 · Mittal et al. · 2016 [cited by applicant]
US 9268902B2 · Taylor et al. · 2016 [cited by applicant]
US 9271657B2 · Taylor · 2016 [cited by applicant]
US 9280639B2 · Sankaran et al. · 2016 [cited by applicant]
US 9292659B1 · Grady et al. · 2016 [cited by applicant]
US 9320487B2 · Mittal et al. · 2016 [cited by applicant]
US 9336354B1 · Sankaran et al. · 2016 [cited by applicant]
US 9339200B2 · Fonte · 2016 [cited by applicant]
US 9349178B1 · Itu et al. · 2016 [cited by applicant]
US 9386933B2 · Grady et al. · 2016 [cited by applicant]
US 9390224B2 · Choi et al. · 2016 [cited by applicant]
US 9390232B2 · Taylor et al. · 2016 [cited by applicant]
US 9405886B2 · Taylor et al. · 2016 [cited by applicant]
US 9424395B2 · Sankaran et al. · 2016 [cited by applicant]
US 9449145B2 · Sankaran et al. · 2016 [cited by applicant]
US 9449146B2 · Spilker et al. · 2016 [cited by applicant]
US 9449147B2 · Taylor · 2016 [cited by applicant]
US 9471999B2 · Ishi et al. · 2016 [cited by applicant]
US 9501622B2 · Sankaran et al. · 2016 [cited by applicant]
US 9517040B2 · Hart et al. · 2016 [cited by applicant]
US 9538925B2 · Sharma et al. · 2017 [cited by applicant]
US 9572495B2 · Schmitt et al. · 2017 [cited by applicant]
US 9585623B2 · Fonte et al. · 2017 [cited by applicant]
US 9585723B2 · Taylor · 2017 [cited by applicant]
US 9595089B2 · Itu et al. · 2017 [cited by applicant]
US 9607386B2 · Grady et al. · 2017 [cited by applicant]
US 9649171B2 · Sankaran et al. · 2017 [cited by applicant]
US 9613186B2 · Fonte · 2017 [cited by applicant]
US 9629563B2 · Sharma et al. · 2017 [cited by applicant]
US 9633454B2 · Lauritsch et al. · 2017 [cited by applicant]
US 9668700B2 · Taylor · 2017 [cited by applicant]
US 9672615B2 · Fonte et al. · 2017 [cited by applicant]
US 9675301B2 · Fonte et al. · 2017 [cited by applicant]
US 9679374B2 · Choi et al. · 2017 [cited by applicant]
US 9697330B2 · Taylor · 2017 [cited by applicant]
US 9700219B2 · Sharma et al. · 2017 [cited by applicant]
US 9706925B2 · Taylor · 2017 [cited by applicant]
US 9607130B2 · Grady et al. · 2017 [cited by applicant]
US 9737276B2 · Mittal et al. · 2017 [cited by applicant]
US 9743835B2 · Taylor · 2017 [cited by applicant]
US 9747525B2 · Sauer et al. · 2017 [cited by applicant]
US 9754082B2 · Taylor et al. · 2017 [cited by applicant]
US 9757073B2 · Goshen et al. · 2017 [cited by applicant]
US 9761048B2 · Igarashi · 2017 [cited by applicant]
US 9770303B2 · Choi et al. · 2017 [cited by applicant]
US 9773219B2 · Sankaran et al. · 2017 [cited by applicant]
US 9785746B2 · Fonte et al. · 2017 [cited by applicant]
US 9785748B2 · Koo et al. · 2017 [cited by applicant]
US 9786068B2 · Ishi et al. · 2017 [cited by applicant]
US 9788807B2 · Schmitt et al. · 2017 [cited by applicant]
US 9801689B2 · Taylor · 2017 [cited by applicant]
US 9805168B2 · Sankaran et al. · 2017 [cited by applicant]
US 9805463B2 · Choi et al. · 2017 [cited by applicant]
US 9594876B2 · Sankaran et al. · 2017 [cited by applicant]
US 9836840B2 · Fonte et al. · 2017 [cited by applicant]
US 9839399B2 · Fonte et al. · 2017 [cited by applicant]
US 9839483B2 · Sankaran et al. · 2017 [cited by applicant]
US 9839484B2 · Taylor · 2017 [cited by applicant]
US 9842401B2 · Prevrhal et al. · 2017 [cited by applicant]
US 9855105B2 · Taylor · 2018 [cited by applicant]
US 9858387B2 · Lavi et al. · 2018 [cited by applicant]
US 9861284B2 · Taylor · 2018 [cited by applicant]
US 9864840B2 · Grady et al. · 2018 [cited by applicant]
US 9877657B2 · Igarashi · 2018 [cited by applicant]
US 9888968B2 · Sauer et al. · 2018 [cited by applicant]
US 9888971B2 · Taylor · 2018 [cited by applicant]
US 9891044B2 · Tu et al. · 2018 [cited by applicant]
US 9913616B2 · Fonte et al. · 2018 [cited by applicant]
US 9918690B2 · Itu et al. · 2018 [cited by applicant]
US 9924869B2 · Kim et al. · 2018 [cited by applicant]
US 9928593B2 · Ooga et al. · 2018 [cited by applicant]
US 9940736B2 · Ishi et al. · 2018 [cited by applicant]
US 9943233B2 · Lavi et al. · 2018 [cited by applicant]
US 9949650B2 · Edic et al. · 2018 [cited by applicant]
US 9965891B2 · Grady et al. · 2018 [cited by applicant]
US 9974454B2 · Sharma et al. · 2018 [cited by applicant]
US 9974508B2 · Kassab et al. · 2018 [cited by applicant]
US 9974616B2 · Grady et al. · 2018 [cited by applicant]
US 9977869B2 · Lavi et al. · 2018 [cited by applicant]
US 9984465B1 · Ma et al. · 2018 [cited by applicant]
US 9993303B2 · Sankaran et al. · 2018 [cited by applicant]
US 9999361B2 · Sharma et al. · 2018 [cited by applicant]
US 10002419B2 · Rapaka et al. · 2018 [cited by applicant]
US 10007762B2 · Grady et al. · 2018 [cited by applicant]
US 10010255B2 · Fonte et al. · 2018 [cited by applicant]
US 10034614B2 · Edic et al. · 2018 [cited by applicant]
US 10052031B2 · Sharma et al. · 2018 [cited by applicant]
US 10052032B2 · Grass et al. · 2018 [cited by applicant]
US 10052158B2 · Taylor · 2018 [cited by applicant]
US 10080613B2 · Taylor · 2018 [cited by applicant]
US 10080614B2 · Taylor · 2018 [cited by applicant]
US 10092247B2 · Taylor · 2018 [cited by applicant]
US 10092360B2 · Taylor · 2018 [cited by applicant]
US 10096104B2 · Choi et al. · 2018 [cited by applicant]
US 10170206B2 · Koo et al. · 2019 [cited by applicant]
US 10398386B2 · Grady et al. · 2019 [cited by applicant]
US 10433740B2 · Fonte et al. · 2019 [cited by applicant]
US 10456094B2 · Fonte et al. · 2019 [cited by applicant]
US 10517677B2 · Sankaran et al. · 2019 [cited by applicant]
US 10561324B2 · Fonte et al. · 2020 [cited by applicant]
US 10692608B2 · Koo et al. · 2020 [cited by applicant]
US 10966619B2 · Fonte et al. · 2021 [cited by applicant]
US 11013425B2 · Fonte et al. · 2021 [cited by applicant]
US 11382569B2 · Grady et al. · 2022 [cited by applicant]
US 11398029B2 · Grady et al. · 2022 [cited by applicant]
US 11399729B2 · Fonte et al. · 2022 [cited by applicant]
US 11482339B2 · Koo et al. · 2022 [cited by applicant]
US 11576626B2 · Fonte et al. · 2023 [cited by applicant]
US 20010047137A1 · Moreno · 2001 [cited by examiner]
US 20020103776A1 · Bella et al. · 2002 [cited by applicant]
US 20030082105A1 · Fischman · 2003 [cited by examiner]
US 20030105638A1 · Taira · 2003 [cited by applicant]
US 20050043614A1 · Huizenga · 2005 [cited by examiner]
US 20050118632A1 · Chen · 2005 [cited by applicant]
US 20050260615A1 · Palenchar · 2005 [cited by applicant]
US 20050262031A1 · Saidi et al. · 2005 [cited by applicant]
US 20060242288A1 · Masurkar · 2006 [cited by applicant]
US 20070130206A1 · Zhou et al. · 2007 [cited by applicant]
US 20070208516A1 · Kutsyy et al. · 2007 [cited by applicant]
US 20070260141A1 · Margolis · 2007 [cited by examiner]
US 20080027695A1 · Balgi et al. · 2008 [cited by applicant]
US 20080085294A1 · Freyman · 2008 [cited by examiner]
US 20080180541A1 · Yonemitsu · 2008 [cited by applicant]
US 20080188762A1 · John · 2008 [cited by applicant]
US 20080201280A1 · Martin et al. · 2008 [cited by applicant]
US 20080294038A1 · Weese et al. · 2008 [cited by applicant]
US 20090036770A1 · Tearney · 2009 [cited by examiner]
US 20090171871A1 · Zhang et al. · 2009 [cited by applicant]
US 20090258925A1 · Wahlestdt · 2009 [cited by applicant]
US 20090259459A1 · Ceusters et al. · 2009 [cited by applicant]
US 20090324126A1 · Zitnick · 2009 [cited by applicant]
US 20100041981A1 · Kassab · 2010 [cited by applicant]
US 20100070448A1 · Omoigui · 2010 [cited by applicant]
US 20100088264A1 · Teverovskiy et al. · 2010 [cited by applicant]
US 20100137711A1 · Hamilton · 2010 [cited by examiner]
US 20100262545A1 · Herlitz · 2010 [cited by applicant]
US 20110026798A1 · Madabhushi · 2011 [cited by examiner]
US 20110027181A1 · Amodei et al. · 2011 [cited by applicant]
US 20110299746A1 · Kobayashi · 2011 [cited by examiner]
US 20120232853A1 · Voigt et al. · 2012 [cited by applicant]
US 20120278060A1 · Cancedda · 2012 [cited by applicant]
US 20130022252A1 · Chen · 2013 [cited by examiner]
US 20130246034A1 · Sharma et al. · 2013 [cited by applicant]
US 20130275094A1 · Ortoleva · 2013 [cited by applicant]
US 20140126770A1 · Odessky et al. · 2014 [cited by applicant]
US 20140172780A1 · Senart et al. · 2014 [cited by applicant]
US 20140276121A1 · Kassab · 2014 [cited by applicant]
US 20150154275A1 · Senart et al. · 2015 [cited by applicant]
US 20150234921A1 · Li · 2015 [cited by applicant]
US 20150324527A1 · Siegel et al. · 2015 [cited by applicant]
US 20150324962A1 · Itu · 2015 [cited by applicant]
US 20160203599A1 · Gillies et al. · 2016 [cited by applicant]
US 20160306944A1 · Grady · 2016 [cited by applicant]
US 20160310018A1 · Fonte · 2016 [cited by applicant]
US 20160314580A1 · Lloyd · 2016 [cited by examiner]
US 20160326588A1 · Beier · 2016 [cited by applicant]
US 20160364630A1 · Reicher et al. · 2016 [cited by applicant]
US 20170046839A1 · Paik · 2017 [cited by examiner]
US 20170319278A1 · Trayanova · 2017 [cited by examiner]
US 20170358079A1 · Gillies · 2017 [cited by applicant]
US 20180253591A1 · Madabhushi · 2018 [cited by applicant]
US 20190244347A1 · Buckler et al. · 2019 [cited by applicant]
CN 1952981 · 2007 [cited by applicant]
CN 106682060 · 2017 [cited by applicant]
CN 107730489 · 2018 [cited by applicant]
JP A2006181025 · 2006 [cited by applicant]
JP A2018011958 · 2018 [cited by applicant]
JP 2018504969 · 2018 [cited by applicant]
KR 102080021635 · 2018 [cited by applicant]
WO WO2014002095 · 2014 [cited by applicant]
WO WO2015058151 · 2015 [cited by applicant]
WO WO2017150497 · 2017 [cited by applicant]
WO WO2019016309 · 2019 [cited by applicant]
Castellano et al. “Texture analysis of medical images,” Clinical Radiology, Dec. 1, 2004 (Dec. 1, 2004) vol. 59. [cited by applicant]
Choi et al. “Multiscale image segmentation using wavelet-domain hidden Markov models” IEEE Trans Image Process, Sep. 1, 2001 (Sep. 1, 2001), vol. 10. [cited by applicant]
Reedy et al. “Confidence guided enhancing brain tumor segmentation in multi-parametric MRI” Proceedings of the 12 [cited by applicant]
Khan et al., “Robust atlas-based brain segmentation using multi-structure confidence-weighted registration” Proceedings of the 12th International Conference on Medical Image Computing, Sep. 20, 2009. [cited by applicant]
Ariff et al. “Carotid Artery Hemodynamics: Observing Patient-specific Changes with Amlodipine and Lisinopril by Using MRI Imaging Computation Fluid Dynamics.” Radiol. 257.3(2010): 662-669. [cited by applicant]
Bourque et al. “Usefulness of Cardiovascular Magnetic Resonance Imaging of the Superficial Femoral Artery for Screening Patients with Diabetes Mellitus for Artherosclerosis.” Am. J. Cardiol. 110.1(2012):50-56. [cited by applicant]
Buckler et al. “A Collaborative Enterprise for Multi-Stakeholder Participation in the Advancement of Quantitative Imaging.” Radiol. 258.3(2011):906-914. [cited by applicant]
Buckler et al. “Data Sets for the Qualification of CT as a Quantitative Imaging Biomarker in Lung Cancer.” Optics Exp.18.14(2010):16. [cited by applicant]
Buckler et al. “Data Sets for the Qualification of Volumetric CT as a Quantitative Imaging Biomarker in Lung Cancer.” Optics Exp. 18.14(2010):15267-15282. [cited by applicant]
Buckler et al. “Quantitative Imaging Test Approval and Biomarker Qualification: Interrelated but Distinct Activities.” Radiol. 259.3(2011):875-884. [cited by applicant]
Buckler et al. “Standardization of Quantitative Imaging: The Time is Right and 18F-FDG PET/CT is a Good Place to Start.” J. Nuclear Med. 52.2(2011):171-172. [cited by applicant]
Buckler et al. “The Use of Volumetric CT as an Imaging Biomarker in Lung Cancer.” Academic Radiol. 17.1(2010):100-106. [cited by applicant]
Buckler et al. “Volumetric CT in Lung Cancer: An Example for the Qualification of Imaging as a Biomarker.” Academic Radiol. 17.1(2010):107-115. [cited by applicant]
Buyse et al. “The Validation of Surrogate Endpoints in Meta-Analysis of Randomized Experiments.” Biostat. 1 (2000):1-1. [cited by applicant]
Chan et al. “Active Contours without Edges.” IEEE Trans. Image Process. 10.2(2001):266-277. [cited by applicant]
De Weert et al. “In Vivo Characterization and Quantification of Atherosclerotic Carotid Plaque Components with Multidetector Computed Tomography and Histopathlogical Correlation.” Arterioscler. Thromb. Vase. Biol. 26.10… [cited by applicant]
Fleming. “Surrogate Endpoints and FDA's Accelerated Approval Process.” Health Affairs. 24.1{2005):67-78. [cited by applicant]
Freedman et al. “Statistical Validation of Intermediate Endpoints for Chronic Diseases.” Stat. Med. 11(1992):167-178. [cited by applicant]
Fuleihan et al. “Reproducibility of DXA Absorptiometry: A Model for Bone Loss Estimates.” J. Bone Miner. Res. 10.74 (1995):1004-1014. [cited by applicant]
Horie et al. “Assessment of Carotid Plaque Stability Based on Dynamic Enhancement Pattern in Plaque Components with Multidetector CT Angiography.” Stroke. 43.2{2012):393-398. [cited by applicant]
Hrace et al. “Human Common Carotid Wall Shear Stress as a Function of Age and Gender: A 12-year Follow-up Study.” AGE. 34.6(2012):1553-1562. [cited by applicant]
Jaffe, “Measures of Response: RECIST, WHO, and New Alternatives.” J.Clin. Oncol. 24.20(2006):3245-3251. [cited by applicant]
Katz, “Biomarkers and Surrogate Markers: An FDA Perspective.” NeuroRx. 1.2(2004):189-195. [cited by applicant]
Kerwin et al. “MRI of Carotid Artherosclerosis.” Am. J. Roentgenol. 200.3(2013):W304-W313. [cited by applicant]
Kim et al. “A Curve Evolution-based variational approach to Simultaneous Image Restoration and Segmentation.” EEE Int. Conf. Image Proc. (2002):1-109. [cited by applicant]
Lathia et al. “The Value, Qualification, and Regulatory Use of Surrogate End Points in Drug Development.” Clin Pharmacol. Therapeutics. 86.1(2009):32-43. [cited by applicant]
Mozley et al. “Change in Lung Tumor Volume as a Biomarker of Treatment Response: A Critical Review of the Evidence.” Ann. Oncol. 21.9(2010):1751-1755. [cited by applicant]
Phinikaridou et al. “Regions of Low Endothelial Shear Stress Colocalize with Positive Vascular Remodeling and Atherosclerotic Plaque Disruption: An in vivo Magnetic Resonance Imaging Study.” Circ. Cardiovasc. Imaging. 6… [cited by applicant]
Prentice, “Surrogate Endpoints in Clinical Trials: Definition and Operational Criteria.” Stat. Med. 9(1989):431-440. [cited by applicant]
Sargent et al. “Validation of Novel Imaging Methodologies for Use as Cancer Clinical Trial End-points.” Eur. J. Dis. 45 ('2009):290-299. [cited by applicant]
Sui et al. “Assessment of Wall Shear Stress in the Common Carotid Artery of Healthy Subjects Using 3.0-Tesla Magentic Resonance.” Acta Radiologica. 49.4(2008):442-449. [cited by applicant]
Sten Kate et al. “Noninvasive Imaging of the Vulnerable Atherosclerotic Plaque.” Current Problems Cardiol. 35.11(2010):556-591. [cited by applicant]
Van Klavern et al. “Management of Lung Nodules Detected by Volume CT Scanning.” New Engl. J. Med. 361 (2009):23. [cited by applicant]
Varma et al. “Coronary Vessel Wall Contrast Enhancement Imaging as a Potential Direct Marker of Coronary Involvement: Integration of Findings from CAD and SLE Patients.” JACC Cardiovasc. Imaging. 7.8(2014):762-770. [cited by applicant]
Wintermark et al. “Carotid Plaque CT Imaging in Stroke and Non-Stroke Patients.” Ann. Neurol. 64.2(2008):149-157. [cited by applicant]
Wintermark et al. “High-Resolution CT Imaging of Carotid Artery Atherosclerotic Plaques.” Am. J. Neuroradiol. 29.5 (2008):875-882. [cited by applicant]
Wong et al. “Imaging in Drug Discovery, Preclinical, and Early Clinical Development.” J. Nuclear Med. 49.6 (2008):26N-28N. [cited by applicant]
Woodcock et al. “The FDA Critical Path Initiative and its Influence on New Drug Development.” Annu. Rev. Med. 59 (2008):1-12. [cited by applicant]
Zavodni et al. “Carotid Artery Plaque Morphology and Composition in Relation to Incident Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis (MESA).” Radiol. 271.2 (2014):361-389. [cited by applicant]
Zhao et al. “Evaluating Variability in Tumor Measurements from Same-Day Repeat CT Scans of Patients with Non-Small Cell Lung Cancer.” Radiol. 252.1(2009):263-272. [cited by applicant]
Aerts,H. J.W.L., et al., Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun, 2014. 5. [cited by applicant]
Ahmadi, A., et al., Association of Coronary Stenosis and Plaque Morphology With Fractional Flow Reserve and Outcomes. JAMA Cardiol, 2016.1(3): p. 350-7. [cited by applicant]
Ahmadi, A., et al., Lesion-Specific and Vessel-Related Determinants of Fractional Flow Reserve Beyond Coronary Artery Stenosis. JACC Cardiovasc Imaging, 2018. 11(4): p. 521-530. [cited by applicant]
Albuquerque, L C , et al., Intraplaque hemorrhage assessed by high-resolution magnetic resonance imaging and C-reactive protein in carotid atherosclerosis. Journal of Vascular Surgery, 2007.46(6): p. 1130-1137. [cited by applicant]
Alimohammadi, M., et al., Development of a Patient-Specific Multi-Scale Model to Understand Atherosclerosis and Calcification Locations: Comparison with In vivo Data in an Aortic Dissection Front Physiol, 2016. 7: p. 23. [cited by applicant]
Aoki, T., et al., Peripheral Lung Adenocarcinoma: Correlation of Thin-Section CT Findings with Histologic Prognostic Factors and Survival 1. Radiology, 2001.220(3): p. 803-809. [cited by applicant]
Atkinson,A.J., et al., Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework. Clinical Pharmacology & Therapeutics, 2001. 69(3): p. 89-95. [cited by applicant]
Bittencourt, M.S., et al., Prognostic Value of Nonobstructive and Obstructive Coronary Artery Disease Detected by Coronary Computed Tomography Angiography to Identify Cardiovascular Events. Circulation: Cardiovascular I… [cited by applicant]
Buckler,A., et al, A Novel Knowledge Representation Framework for the Statistical Validation of Quantitative Imaging Biomarkers. Journal of Digital Imaging, 2013. 26(4): p. 614-629. [cited by applicant]
Buckler, A.J., et al., Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers. Journal of digital imaging : the official journal of the Society for Computer Applicat… [cited by applicant]
Buckler, A.J., et al., Quantitative imaging test approval and biomarker qualification: interrelated but distinct activities. Radiology, 2011.259(3): p. 875-84. [cited by applicant]
Cai, J., et al., In vivo quantitative measurement of intact fibrous cap and lipid-rich necrotic core size in atherosclerotic carotid plaque: comparison of high-resolution, contrast-enhanced magnetic resonance imaging an… [cited by applicant]
Chan, T.F. and L.A. Vese, Active contours without edges. IEEE Trans Image Process,2001. 10(2): p. 266-77. [cited by applicant]
Coenen, A., et al., Diagnostic accuracy of a machine-learning approach to coronary computed tomographic angiography-based fractional flow reserve: result from the Machine consortium. Circulation: Cardiovascular Imaging,… [cited by applicant]
De Bono, B., et al., The Open Physiology workflow: modeling processes over physiology circuit boards of interoperable tissue units Front Physiol, 2015. 6: p. 24. [cited by applicant]
De Graaf, M., et al., Automatic quantification and characterization of coronary atherosclerosis with computed tomography coronary angiography: cross-correlation with intravascular ultrasound virtual histology. Int J Car… [cited by applicant]
DeMarco, J.K. and J. Huston, Imaging of high-risk carotid artery plaques: current status and future directions Neurosurgical Focus, 2014. 36(1): p. E1. [cited by applicant]
Diaz-Zamudio, M., et al., Automated Quantitative Plaque Burden from Coronary CT Angiography Noninvasively Predicts Hemodynamic Significance by using Fractional Flow Reserve in Intermediate Coronary Lesions. Radiology, 2… [cited by applicant]
Dong, L., et al., Carotid Artery Atherosclerosis: Effect of Intensive Lipid Therapy on the Vasa Vasorum—Evaluation by Using Dynamic Contrast-enhanced MR Imaging. Radiology, 2011.260(1): p. 224-231. [cited by applicant]
Fiilardi,V., Carotid artery stenosis near a bifurcation investigated by fluid dynamic analyses. The Neuroradiology Journal, 2013. 26(4): p. 439-453. [cited by applicant]
Fleming,T.R. and D.L. DeMets, Surrogate end points in clinical trials:are we being misled? Ann Intern Med, 1996. 125 (7): p. 605-13. [cited by applicant]
Freimuth, R.R.,et al., Life sciences domain analysis model. J Am Med Inform Assoc,2012. 19(6): p. 1095-102. [cited by applicant]
Fujimoto,S.,et al., A novel method for non-invasive plaque morphology analysis by coronary computed tomography angiography. Int J Cardiovasc Imaging, 2014. 30(7): p. 1373-1382. [cited by applicant]
Gaston A. Rodriguez-Granillo, Patricia Carrascosa, Nico Bruining, and a.H.M.G.-G. Ron Waksman, Defining the non-vulnerable and vulnerable patients with computed tomography coronary angiography: evaluation of atheroscler… [cited by applicant]
Gevaert, O., et al., Non-small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data—methods and preliminary results Radiology, 2012 264(2): p. 387-396. [cited by applicant]
Ghazalpour, A., et al., Thematic review series: The pathogenesis of atherosclerosis. Toward a biological network for atherosclerosis J Lipid Res, 2004 45(10): p. 1793-805. [cited by applicant]
Gupta, A., et al., Carotid Plaque MRI and Stroke Risk A Systematic Review and Meta-analysis. Stroke, 2013.44(11): p. 3071-3077. [cited by applicant]
Gupta, A., et al., Detection of Symptomatic Carotid Plaque Using Source Data from MR and CT Angiography: A Correlative Study Cerebrovasc Dis, 2015. 39(3-4): p. 151-61. [cited by applicant]
Gupta, A., et al., Intraplaque high-intensity signal on 3D time-of-flight MR angiography is strongly associated with symptomatic carotid artery stenosis. American Journal of Neuroradiology, 2014. 35(3): p. 557-561. [cited by applicant]
Hecht, H.S., Coronary artery calcium scanning: past, present, and future. JACC Cardiovasc Imaging, 2015. 8: p. 579-596. [cited by applicant]
Hecht,H.S., J. Narula, and W.F. Fearon, Fractional Flow Reserve and Coronary Computed Tomographic Angiography, A Review and Critical Analysis. Circ Res, 2016.119(2): p. 300-16. [cited by applicant]
Helft, G., et al., Progression and regression of atherosclerotic lesions: monitoring with serial noninvasive magnetic resonance imaging Circulation, 2002. 105(8): p. 993-8. [cited by applicant]
Inoue, K., et al., Serial Coronary CT Angiography-Verified Changes in Plaque Characteristics as an End Point: Evaluation of Effect of Statin Intervention. JACC: Cardiovascular Imaging, 2010. 3(7): p. 691-698. [cited by applicant]
Krizhevsky, A.I. Sutskever, and G.E. Hinton. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems 2012. [cited by applicant]
Lobatto, ME., et al., Multimodal Clinical Imaging To Longitudinally Assess a Nanomedical Anti-Inflammatory Treatment in Experimental Atherosclerosis. Molecular Pharmaceutics, 2010. 7(6): p. 2020-2029. [cited by applicant]
Ma,X.,et al Volumes Learned: It Takes More Than Size to “Size Up” Pulmonary Lesions. Acad Radiol, 2016. 23(9): p. 1190-8. [cited by applicant]
Melander, O., et al., Novel and conventional biomarkers for prediction of incident cardiovascular events in the community. JAMA: the journal of the American Medical Association, 2009. 302(1): p. 49-57. [cited by applicant]
Miao, C., et al., The Association of Pericardial Fat with Coronary Artery Plaque Index at MR Imaging: The Multi-Ethnic Study of Atherosclerosis (MESA). Radiology, 2011.261(1): p. 109-115. [cited by applicant]
Mono, M.L., et al., Plaque Characteristics of Asymptomatic Carotid Stenosis and Risk of Stroke. Cerebrovascular Diseases, 2012. 34(5-6): p. 343-350. [cited by applicant]
Narula, J., et al., Histopathologic characteristics of atherosclerotic coronary disease and implications of the findings for the invasive and noninvasive detection of vulnerable plaques. Journal of the American College … [cited by applicant]
Naylor, A.R., Identifying the high-risk carotid plaque. The Journal of Cardiovascular Surgery, 2014. 55(2): p. 11-20. [cited by applicant]
Perera ,R. and P. Nand, Recent Advances in Natural Language Generation: A Survey and Classification of the Empirical Literature. vol. 36.2017. 1-31. [cited by applicant]
Prentice, R.L., Surrogate endpoints in clinical trials: definition and operational criteria. Statistics in medicine, 1989. 8 (4): p. 431-440. [cited by applicant]
Prescott, J., Quantitative Imaging Biomarkers: The Application of Advanced Image Processing and Analysis to Clinical and Preclinical Decision Making Journal of Digital Imaging, 2013. 26(1): p. 97-108. [cited by applicant]
Reddy et al. “Confidence guided enhancing brain tumor segmentation in multi-parametric MRI” Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009, he… [cited by applicant]
Saba, L., et al., Carotid Artery Plaque Characterization Using CT Multienergy Imaging American Journal of Neuroradiology, 2013 34(4): p. 855-859. [cited by applicant]
Sadot, A., et al., Toward verified biological models. IEEE/ACM Trans Comput Biol Bioinform, 2008. 5(2): p. 223-34. [cited by applicant]
Sargent, D., et al., Validation of novel imaging methodologies for use as cancer clinical trial end-points. European Journal of Cancer, 2009.45(2): p. 290-299. [cited by applicant]
Stary, H.C., et al., A definition of advanced types of atherosclerotic lesions and a histological classification of atherosclerosis A report from the Committee on Vascular Lesions of the Council on Arteriosclerosis, Ame… [cited by applicant]
Stary, H.C., Natural history and histological classification of atherosclerotic lesions: an update. Arterioscler Thromb Vasc Biol, 2000.20(5): p. 1177-8. [cited by applicant]
Van't Klooster ,R., et al., Visualization of Local Changes in Vessel Wall Morphology and Plaque Progression in Serial Carotid Artery Magnetic Resonance Imaging. Stroke, 2014. 45(8): p. e160-e163. [cited by applicant]
Virmani, R., et al., Pathology of the Vulnerable Plaque. JACC,2006.47(8): p. C13-8. [cited by applicant]
Voros, S., et al., Coronary Atherosclerosis Imaging by Coronary CT Angiography. JACC Cardiovasc Imaging, 2011.4 (5): p. 537-48. [cited by applicant]
William B. Kerr et al. “A Methodology and Metric for Quantitative Analysis and Parameter Optimization of Unsupervised, Multi-Region Image Segmentation”, Proceeding of the 8th IASTED International Conference on Signal an… [cited by applicant]
Majd Zreik et al. “Automatic Detection and Characterization of Coronary Artery Plaque and Stenosis using a Recurrent Convolutional Neural Network in Coronary CT Angiography”, arxiv.org, Cornell University Library, 201 O… [cited by applicant]
Wei Jun et al.: “Computerized detection of noncalcified plaques in coronary CT angiography: Evaluation of topologicals soft gradient prescreening method and luminal analysis”, Medical Physics., vol. 41, No. 8 Part 1, Ju… [cited by applicant]
Filipovic et al. Hemodynamic Flow Modeling Through an Abdominal Aorta Aneurysm Using Data Mining Tools, IEEE Transactions on Information Technology in Biomedicine, vol. 15, No. 2, Mar. 2011, pp. 189-194. [cited by applicant]
Bishop, Christopher M., Pattern Recognition and Machine Learning, Springer Science 2006, pp. 1-758. [cited by applicant]
Notice of Allowance for U.S. Appl. No. 18/309,903 dated Mar. 7, 2024. [cited by applicant]
Office Action for U.S. Appl. No. 18/545,542 dated Mar. 15, 2024. [cited by applicant]
Notice of Allowance from U.S. Appl. No. 18/415,137 dated Aug. 9, 2024. [cited by applicant]
Office Action from U.S. Appl. No. 18/415,125 dated Apr. 30, 2024. [cited by applicant]
Notice of Allowance from U.S. Appl. No. 18/415,125 dated Jul. 18, 2024. [cited by applicant]
Notice of Allowance from U.S. Appl. No. 18/504,795 dated Jun. 20, 2024. [cited by applicant]
Notice of Allowance from U.S. Appl. No. 18/504,811 dated Jul. 8, 2024. [cited by applicant]
Notice of Allowance from U.S. Appl. No. 18/545,563 dated May 31, 2024. [cited by applicant]
Cited By (11)
US 12,396,695 US 12,440,180 US 12,499,539 US 12,531,162 US 12,555,228 US 12,558,048 US 12,562,256 US 12,589,032 US 12,599,352 US 12,670,587 US 12,714,382