SBIR-STTR Award

Novel Algorithms for Reducing Radiation Dose of CT Perfusion
Award last edited on: 9/23/2022

Sponsored Program
STTR
Awarding Agency
NIH : NIMHD
Total Award Amount
$1,989,368
Award Phase
2
Solicitation Topic Code
100
Principal Investigator
Jeffry R ALGER

Company Information

Hura Imaging LLC

23120 Park Sorrento
Calabasas, CA 91302
   N/A
   bd@huraimaging.com
   www.huraimaging.com

Research Institution

University of Southern California

Phase I

Contract Number: 1R41EB024438-01A1
Start Date: 8/1/2017    Completed: 7/31/2018
Phase I year
2017
Phase I Amount
$265,898
X-ray computed tomography (CT) has been increasingly used in medical diagnosis, currently reaching more than 80 million CT scans every year in the US. The increasing use of CT has sparked concern over the effects of radiation dose on patients. It is estimated that every 2000 CT scans will cause one future cancer, i.e., 40,000 cases of future cancers from 80 million CT scans every year. CT brain perfusion (CTP) is a widely used imaging technique for the evaluation of hemodynamic changes in stroke and cerebrovascular disorders. However, CTP involves high radiation dose for patients as the CTP scan is repeated on the order of 40 times at the same anatomical location, in order to capture the full passage of the contrast bolus. This has been raised as a major concern by the FDA, especially when multiple successive CTPs are performed on the same patient, e.g. to monitor reperfusion following recanalization. Several techniques have been applied for radiation dose reduction in CTP scans, including reduction of tube current and tube voltage, as well as the use of novel noise reduction techniques such as iterative reconstruction (IR). However, the resultant radiation dose of existing CTP scans is still significantly higher than that of a standard head CT scan. The application of IR techniques in CTP is very limited due to the high complexity and computational burden for processing multiple CTP images that may impair clinical workflow. The overarching goal of the present STTR project is to develop and commercialize a novel CT imaging platform that reduces the radiation dose of existing CTP techniques by ~75% without compromising imaging speed or quality. This proprietary technology reduces the radiation dose of CTP scans by controlling the X-ray source to be on intermittently (instead of continuously) at pre-specified rotation angles (i.e., programmed pulsed X-ray). The dynamic CTP image series can then be reconstructed using algorithms that preserve high spatial and temporal resolutions as well as image quality comparable to those of standard CTP scans. During the proposed Phase 1 project, we plan to demonstrate a proof-of-concept of our technology by further developing, optimizing and evaluating the image reconstruction algorithm using both phantom and clinical CTP data. We will also collaborate with CT vendors to ensure the developed technology has a realistic pathway to commercialization.

Public Health Relevance Statement:
Relevance to Public Health More than 80 million CT scans are performed every year in the US, estimated to cause 40,000 cases of future cancers. This project will develop, evaluate and commercialize a novel CT imaging platform that reduces the radiation dose of existing CT perfusion techniques by ~75% without compromising imaging speed or quality.

NIH Spending Category:
Bioengineering; Biomedical Imaging; Brain Disorders; Cerebrovascular; Clinical Research; Neurosciences; Stroke

Project Terms:
acute stroke; Affect; Algorithms; Anatomy; Angiography; Back; Bolus Infusion; Brain; brain tissue; Cerebrovascular Disorders; Clinical; commercialization; Computer software; contrast imaging; Data; Decision Making; Detection; Diagnosis; Dose; Electromagnetics; Ensure; Evaluation; flexibility; Future; Goals; Head; Health; Heart; hemodynamics; High-LET Radiation; Image; image reconstruction; imaging platform; imaging system; Imaging Techniques; Impairment; Industry; Industry Standard; Infarction; innovation; ischemic lesion; Location; low-dose spiral CT; Magnetic Resonance Imaging; Malignant Neoplasms; Medical; Medical Imaging; Modernization; Monitor; new technology; Noise; novel; Organ; Pathway interactions; Patients; Pattern; Performance; Perfusion; perfusion imaging; Phase; Physiologic pulse; portability; Positioning Attribute; Protocols documentation; prototype; Public Health; Radiation; radiation effect; Radiation exposure; reconstruction; Reperfusion Therapy; Roentgen Rays; Rotation; Sampling; Scanning; Series; Slice; Small Business Technology Transfer Research; Societies; Source; Specific qualifier value; Speed; Stroke; System; Techniques; Technology; temporal measurement; Testing; Time; Tomography, Computed, Scanners; Tube; Vendor; voltage; X-Ray Computed Tomography

Phase II

Contract Number: 2R44EB024438-03
Start Date: 8/1/2017    Completed: 5/31/2022
Phase II year
2020
(last award dollars: 2021)
Phase II Amount
$1,723,470

X-ray computed tomography (CT) has been increasingly used in medical diagnosis, currently reaching more than 100 million CT scans every year in the US. The increasing use of CT has sparked concern over the effects of radiation dose on patients. It is estimated that every 2000 CT scans will cause one future cancer, i.e., 50,000 cases of future cancers from 100 million CT scans every year. CT brain perfusion (CTP) is a widely used imaging technique for the evaluation of hemodynamic changes in stroke and cerebrovascular disorders. However, CTP involves high radiation dose for patients as the CTP scan is repeated on the order of 40 times at the same anatomical location, in order to capture the full passage of the contrast bolus. Several techniques have been applied for radiation dose reduction in CTP scans, including reduction of tube current and tube voltage, as well as the use of noise reduction techniques such as iterative reconstruction (IR). However, the resultant radiation dose of existing CTP scans is still significantly higher than that of a standard head CT scan. The application of IR techniques in CTP is very limited due to the high complexity and computational burden for processing multiple CTP images that impairs clinical workflow. During the Phase 1 STTR project, we introduced a novel low dose CTP imaging method based on the k-space weighted image contrast (KWIC) reconstruction algorithm. We performed thorough evaluation in both a CTP phantom and clinical CTP datasets, and demonstrated that the KWIC algorithm is able to reduce the radiation dose of existing CTP techniques by 75% without affecting the image quality and accuracy of quantification (i.e., Milestone of Phase 1 STTR). However, the original KWIC algorithm requires rapid-switching pulsed X-ray at pre-specified rotation angles – a hardware capability yet to be implemented by commercial CT vendors. In order to address this limitation, we recently introduced a variant of the KWIC algorithm termed k-space weighted image average (KWIA) that preserves high spatial and temporal resolutions as well as image quality of low dose CTP data (~75% dose reduction) to be comparable to those of standard CTP scans. Most importantly, KWIA does not require modification of existing CT hardware and is computationally simple and fast, therefore has a low barrier for market penetration. The purpose of the Phase 2 STTR project is to further optimize and validate the KWIA algorithm for reducing radiation dose of CTP scans by ~75% while preserving the image quality and quantification accuracy in CTP phantom, clinical CTP data and animal studies. We will further develop innovative deep-learning (DL) based algorithms to address potential motion and other artifacts in KWIA, and commercialize the developed algorithms by collaborating with CT vendors. Public Health Relevance Statement Relevance to Public Health More than 100 million CT scans are performed every year in the US, estimated to cause 50,000 cases of future cancers. This project will develop, evaluate and commercialize novel CT imaging technologies that reduce the radiation dose of existing CT perfusion techniques by ~75% without compromising imaging speed or quality.