IP Library Granted Patent US 12,318,249
Granted Patent B2
US 12,318,249 · App. 18/586,358 · Granted Jun 3, 2025

Premature birth prediction

Inventor: Robert S Bunn (Highlands Ranch, CO)
Assignee: Ultrasound AI Inc.
A61B8/0866A61B8/06A61B8/0875A61B8/0883A61B8/467A61B8/488G06T7/0016G06T7/20G16H10/60G16H30/20G16H30/40G16H50/20G06T2207/10132G06T2207/20081G06T2207/30008G06T2207/30044G06T2207/30048G06T2207/30104
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Quick Facts
Patent No.
US 12,318,249
App. No.
18/586,358
Granted
Jun 3, 2025
Kind
B2
Abstract

Systems and methods of predicting future medical events are based on the processing of medical images. The prediction of premature birth and estimation of gestational age based on ultrasound images are presented as illustrative examples. The new abilities to estimate the probability of future medical events, before they otherwise could be predicted, provides new avenues for the development of preventative treatments.

Claims (32)

1. A medical prediction system configured to predict premature births, the medical prediction system comprising:

an image storage configured to store ultrasound images, the ultrasound images including a fetus;

image analysis logic configured to provide a quantitative prediction that the fetus will be born prematurely based on the ultrasound images, wherein the image analysis logic is configured to use a regression algorithm to provide the quantitative prediction, including an estimate that the fetus will be born prematurely within a time range and wherein the image analysis logic further comprises

first logic configured to estimate a gestational age of the fetus based on the ultrasound images, the gestational age being at a time the ultrasound images were generated,

second logic configured to estimate a time until birth of the fetus based on the ultrasound images, and

third logic configured to calculate an estimated gestational age of the fetus at birth;

a user interface configured to provide at least the prediction that the fetus will be born prematurely to a user; and

a microprocessor configured to execute at least a part of the image analysis logic.

2. The medical prediction system of claim 1 , further comprising an image generator configured to generate the ultrasound images.

3. The medical prediction system of claim 2 , wherein the image generator comprises a sound source, a sound detector and logic configured to generate the ultrasound images based on sound detected by the sound detector.

4. The medical prediction system of claim 2 , wherein the image generator is configured to adapt the generation of the ultrasound images based on an output of the image analysis logic.

5. The medical prediction system of claim 2 , wherein the image generator is configured to generate a sequence of images representative of motion of a fetus, the image sequence optionally including fetal blood flow, capillary profusion, and/or heart movement.

6. The medical prediction system of claim 2 , wherein the image generator is configured to direct a user to modify a position of a sound source configured to generate the ultrasound images.

7. The medical prediction system of claim 1 , further comprising a data input configured to receive clinical data regarding the fetus or a mother of the fetus, wherein an estimated time until birth of the fetus is based on the clinical data.

8. The medical prediction system of claim 7 , wherein the image analysis logic is further configured to predict that the fetus will be born prematurely based on clinical data received via the data input.

9. The medical prediction system of claim 8 , wherein the clinical data includes at least one of: mother genetics, mother weight, mother pregnancy history, mother blood glucose, mother heart function, mother kidney function, mother blood pressure, placenta condition, mother infections, mother nutrition, mother drug use, mother age, mother cervix or uterus characteristics.

10. The medical prediction system of claim 1 , further comprising feedback logic configured to guide acquisition of the ultrasound images based on a quality of the prediction that the fetus will be born prematurely or classification of the images acquired into subject matter classes.

11. The medical prediction system of claim 10 , wherein the feedback logic is configured to guide a positioning of the image generator so as to generate images more useful in the prediction that the fetus will be born prematurely.

12. The medical prediction system of claim 10 , wherein the feedback logic is configured to indicate a need to acquire additional ultrasound images useful in the prediction that the fetus will be born prematurely.

13. The medical prediction system of claim 1 , further comprising training logic configured to train the logic configured to estimate a time until birth of the fetus.

14. The medical prediction system of claim 13 , wherein the image analysis logic includes a machine learning system and the training logic is configured to pretrain the machine learning logic to recognize features in the ultrasound images.

15. The medical prediction system of claim 13 , wherein the image analysis logic includes a machine learning system and the training logic is configured to train the machine learning system to make the quantitative prediction that the fetus will be born prematurely.

16. The medical prediction system of claim 1 , wherein the ultrasound images including the fetus are generated over a period of time including at least three months.

17. The medical prediction system of claim 1 , wherein the ultrasound images include doppler information, or fluid, bone or tissue density information.

18. The medical prediction system of claim 1 , wherein the image analysis logic is configured to use a regression algorithm to output a range prediction to provide an estimate that the fetus will be born prematurely.

19. The medical prediction system of claim 1 , wherein the image analysis logic is configured to provide an estimate that the fetus will be born prematurely using a classification algorithm, the classification algorithm including at least two classifications of birth timing.

20. The medical prediction system of claim 1 , wherein the image analysis logic includes a neural network configured to receive the ultrasound images and to generate an output representative of the prediction that the fetus will be born prematurely.

21. The medical prediction system of claim 1 , wherein the image analysis logic includes a neural network configured to receive the ultrasound images and to generate an output indicative of a time until birth of the fetus.

22. The medical prediction system of claim 1 , wherein the quantitative prediction that the fetus will be born prematurely includes an estimate of a probability that the fetus will be born prematurely, the estimate being based on an ultrasound image, of the ultrasound images, of a cervix and/or amniotic fluid index.

23. The medical prediction system of claim 1 , wherein the quantitative prediction is based on an ultrasound image, of the ultrasound images, including an endometrium and/or a uterine wall.

24. The medical prediction system of claim 1 , wherein the user interface is configured to provide at least two of: the gestational age, the estimated time until birth and the gestational age of the fetus at birth.

25. The medical prediction system of claim 1 , wherein the image analysis logic includes a machine learning system and the training logic is configured to train the machine learning system to use both a regression algorithm and a classification algorithm to make the prediction that the fetus will be born prematurely.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 17, 2024
From: BUNN, ROBERT S
To: ULTRASOUND AI INC.
Reel/Frame 068616/0035 →
Continuity (6)
Continuation 17573246 · Jan 11, 2022
Continuation PCTUS2021038164 · Jun 20, 2021
Continuation 17352290 · Jun 19, 2021
Continuation 17352290 · Jun 19, 2021
Provisional Application 63041360 · Jun 19, 2020
Related Publication 20240315664A1 · Sep 26, 2024
References Cited (78)
US 8828981B2 · Creasy et al. · 2014 [cited by applicant]
US 10650929B1 · Beck et al. · 2020 [cited by applicant]
US 20040236193A1 · Sharf · 2004 [cited by applicant]
US 20060241510A1 · Halperin et al. · 2006 [cited by applicant]
US 20090093717A1 · Carneiro et al. · 2009 [cited by applicant]
US 20090169074A1 · Avinash et al. · 2009 [cited by applicant]
US 20100312115A1 · Dentinger · 2010 [cited by applicant]
US 20110248818A1 · Hashim-Waris · 2011 [cited by applicant]
US 20120135427A1 · Kypros et al. · 2012 [cited by applicant]
US 20140018678A1 · Donnelly et al. · 2014 [cited by applicant]
US 20140089004A1 · Frey et al. · 2014 [cited by applicant]
US 20150148657A1 · Shashar et al. · 2015 [cited by applicant]
US 20150342560A1 · Davey et al. · 2015 [cited by applicant]
US 20160071266A1 · Srivastava et al. · 2016 [cited by applicant]
US 20160228505A1 · Stossel et al. · 2016 [cited by applicant]
US 20170000683A1 · Samec et al. · 2017 [cited by applicant]
US 20170086785A1 · Bjaerum · 2017 [cited by applicant]
US 20170091402A1 · Salafia et al. · 2017 [cited by applicant]
US 20170216335A1 · Mangano · 2017 [cited by applicant]
US 20170357844A1 · Comaniciu et al. · 2017 [cited by applicant]
US 20180032666A1 · Sun et al. · 2018 [cited by applicant]
US 20180153504A1 · Herickhoff et al. · 2018 [cited by applicant]
US 20190008674A1 · Myers · 2019 [cited by examiner]
US 20190021698A1 · Raghvan et al. · 2019 [cited by applicant]
US 20190034590A1 · Oren et al. · 2019 [cited by applicant]
US 20190154704A1 · Davis et al. · 2019 [cited by applicant]
US 20190209116A1 · Sjostrand et al. · 2019 [cited by applicant]
US 20190246904A1 · Kim et al. · 2019 [cited by applicant]
US 20190251638A1 · Braz et al. · 2019 [cited by applicant]
US 20190367987A1 · Hamamah et al. · 2019 [cited by applicant]
US 20200005899A1 · Nicula et al. · 2020 [cited by applicant]
US 20200005901A1 · Cohen et al. · 2020 [cited by applicant]
US 20200022674A1 · Egorov · 2020 [cited by applicant]
US 20200069292A1 · Abolmaesumi et al. · 2020 [cited by applicant]
US 20200077947A1 · Shi et al. · 2020 [cited by applicant]
US 20200147006A1 · Charney et al. · 2020 [cited by applicant]
US 20200149110A1 · Targan et al. · 2020 [cited by applicant]
US 20200168310A1 · Westin et al. · 2020 [cited by applicant]
US 20200170614A1 · Kim et al. · 2020 [cited by applicant]
US 20210068905A1 · Quaid et al. · 2021 [cited by applicant]
US 20210090254A1 · Gong et al. · 2021 [cited by applicant]
US 20210118559A1 · Lefkofsky · 2021 [cited by applicant]
US 20210128115A1 · Mapiye et al. · 2021 [cited by applicant]
US 20210217166A1 · Graule et al. · 2021 [cited by applicant]
US 20210287513A1 · Mazar et al. · 2021 [cited by applicant]
US 20210307702A1 · Moon · 2021 [cited by applicant]
US 20220028551A1 · Jordan et al. · 2022 [cited by applicant]
US 20220067922A1 · Yu · 2022 [cited by applicant]
US 20220133260A1 · Bunn · 2022 [cited by applicant]
US 20220164635A1 · Johansen et al. · 2022 [cited by applicant]
US 20220192501A1 · Shuler · 2022 [cited by applicant]
US 20220328189A1 · Zhou et al. · 2022 [cited by applicant]
US 20220400963A1 · Bucklet et al. · 2022 [cited by applicant]
IN 201941040741A · 2021 [cited by applicant]
JP 2018140172A · 2018 [cited by applicant]
KR 1020200013161A · 2020 [cited by applicant]
WO 2020061590A1 · 2020 [cited by applicant]
Office Action Issued in related Chinese Patent Application No. 202180043378.8 issued Dec. 28, 2023, 27 pages. [cited by applicant]
PCT/US21/38164 International Search Report and Written Opinion, mailed Sep. 30, 2021. [cited by applicant]
PCT/US23/011845 International Search Report and Written Opinion, mailed Apr. 27, 2023. [cited by applicant]
PCT/US24/014349 International Search Report and Written Opinion, mailed May 7, 2024. [cited by applicant]
PCT/US24/019803 International Search Report and Written Opinion, mailed Jun. 17, 2024. [cited by applicant]
PCT/US24/014353 International Search Report and Written Opinion, mailed May 7, 2024. [cited by applicant]
PCT/US24/014356 International Search Report and Written Opinion, mailed May 9, 2024. [cited by applicant]
Kuo et al., “Automation of the kidney function prediction and classification through ultrasoundbased kidney imaging using deep learning.” In: npj Digital Medicine vol. 2, Article No. 29 (2019), [onlinel [retrieved on Ap… [cited by applicant]
CN 202180043378.8, Response to first office action issued Dec. 28, 2023, dated May 10, 2024. [cited by applicant]
CN 202180043378.8, Rejection Decision issued May 18, 2024. [cited by applicant]
CN 202180043378.8, Response to Rejection Decision iissued May 18, 2024, dated Aug. 19, 2024. [cited by applicant]
EP 21825348.2 EESR Issued Jun. 18, 2024. [cited by applicant]
Oelze et al., “Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound”, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Cont… [cited by applicant]
Suff Natalie et al: “The prediction of preterm delivery: What is new?”, Seminars in Fetal and Neonatal Medicine, Elsevier, GB, vol. 24, No. 1, Sep. 28, 2018 (Sep. 28, 2018), pp. 27-32, XP085591331, ISSN: 1744-165X, DOI:… [cited by applicant]
Pizzella Stephanie et al: “Evolving cervical imaging technologies to predict preterm birth”, Seminars in Immunopathology, Springer Berlin Heidelberg, Berlin/Heidelberg, vol. 42, No. 4, Jun. 10, 2020 (Jun. 10, 2020), pp.… [cited by applicant]
European Application No. EP 21825348.2, Response to EESR issued Jul. 5, 2024, filed Dec. 30, 2024. [cited by applicant]
Japanese Application No. JP 2022-574786, Response to Notice of Reasons for Refusal issued Sep. 3, 2024, filed Nov. 19, 2024. [cited by applicant]
Korean Application No. KR 10-2023-7000075; Response to Office Action issued Oct. 21, 2024, filed Dec. 23, 2024. [cited by applicant]
Japanese Application No. JP 2022-574786—Notice of Reasons for Refusal issued Feb. 4, 2025. [cited by applicant]
JP 2022-574786, Notice of Reasons for Refusal, Issued Sep. 3, 2024. [cited by applicant]
KR 10-2023-7000075, Office Action, Issued Oct. 21, 2024. [cited by applicant]
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