Healthy VolunteersNCT04657042
4D-MRI for Precision Medicine
An observational study of Healthy Volunteers and Liver Cancer, run by University of Virginia at 1 site in United States.
Trial summary
The purpose of this study is to develop new ways to make medical images of the lungs and liver of adults using a technique called four-dimensional magnetic resonance imaging (4D-MRI). This technique produces three-dimensional movies of the inside of the chest and abdomen while the patient is breathing. Read more about this study
- Who is it for?
- Ages 18 to 82 yearsHealthy volunteers can take part
- Conditions the study is for
- Healthy Volunteers, Liver Cancer, Lung Cancer
- What is being tested?
- Magnetic Resonance Imaging
- How many people
- 100 participants
- Where
- 1 siteUnited States
- Study dates
- 5 Nov 2020to 31 Dec 2030
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 82 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Up to 30 lung cancer patients, 30 liver cancer patients, and 40 healthy human volunteers will receive MRI examinations at the University of Virginia to directly measure respiratory motion in the thorax and abdomen. All subject populations will include roughly equal male and female representations. The subject populations will have minority and ethnic representation typical of the local population area that includes the University of Virginia. No specific racial or ethnic group will be excluded. All subjects must have the ability to understand the requirements of the study and must provide informed consent with a personal signature. No persons from vulnerable populations will be included in this study.
Who may be able to join
None listed.
Who cannot join
- Any condition for which a MRI procedure is contraindicated including presence of metallic material in the body, such as pacemakers, non- MRI compatible surgical clips, shrapnel, etc.
- Subjects who have difficulty lying flat on their back for extended periods of time
- Patients with any serious/poorly controlled medical or psychological conditions that would complicate protocol compliance
- Too large to adequately fit in the magnet bore or RF coils
- Claustrophobia
- Females who are pregnant or lactating
- Presence of active or chronic infection
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
University of Virginia
Charlottesville, Virginia, 22908
Roselove Nunoo-Asare, MA, 5402955399, rnunoo.asare@gmail.com
About this study
Official title: Toward Precision Radiotherapy: Physiological Modeling of Respiratory Motion Based on Ultra-quality 4D-MRI
The purpose of this study is to develop new ways to make medical images of the lungs and liver of adults using a technique called four-dimensional magnetic resonance imaging (4D-MRI). This technique produces three-dimensional movies of the inside of the chest and abdomen while the patient is breathing. (The fourth dimension is time!)
This new way of medical imaging is being developed to help cancer patients undergoing radiation therapy. Radiation therapy is used to treat cancerous tumors. For radiation therapy to be effective, the precise size, shape, and location of the tumor within the body must be known. A particular difficulty for radiation treatment of lung and liver cancer is that the tumor moves during treatment because the patient is breathing. Therefore, tumor motion must also be incorporated into the treatment plan. This study aims to improve radiation treatment planning through better targeting and dose estimation based on 4D-MRI. Before this new imaging method can be used for radiation treatment planning, it must be tested in living, breathing volunteers.
Read the detailed description
Radiotherapy for cancer has been a forerunner of personalized medicine, developing individualized treatments based on patient-specific anatomical information. Despite many advances in radiotherapy over the past decade, which have effectively enhanced local or loco-regional tumor control for many patients, there remains substantial room for improvement. The challenges for radiotherapy to further widen the therapeutic window in the era of precision medicine are mainly two-fold: (a) further improve radiation dose conformity to the defined target volume, and (b) adapt novel biological strategies for personalized treatment. Four-dimensional (4D) imaging and deformable image registration (DIR) are key tools in modern radiotherapy, playing critical roles in many recent advances, including 4D radiotherapy, adaptive radiotherapy, and treatment assessment. However, current 4D imaging and DIR technologies are facing significant challenges as the requirement for precision increases.
The current standard of 4D imaging in radiotherapy is 4D-CT. However, it has two major limitations preventing it from precision radiotherapy applications: (a) low soft-tissue contrast. 4D-CT is therefore not ideal for abdominal applications; (b) motion artifacts caused by irregular breathing. 4D-CT motion artifacts have been shown to cause errors in various radiotherapy applications, including motion measurement, target volume delineation, dose calculation, DIR, and lung ventilation calculation. 4D-MRI is an emerging 4D imaging technology for radiotherapy. It has superior soft-tissue contrast to 4D-CT and is therefore superb for abdominal imaging. Despite many recent advances in 4D-MRI, current 4D-MRI implementations have inadequate image quality for precision radiotherapy application due to at least one of the following deficiencies: low temporal and/or spatial resolutions, long image acquisition time, and suboptimal contrast in the lungs. Resulting 4D-MRI images lack sufficient anatomical details for clinical applications, which can adversely affect the performance of DIR. Current DIR techniques focus on morphological similarity but not on the physiological plausibility of the deformation. Studies have shown that an increased morphological similarity of the aligned data does not always imply increased registration accuracy. Therefore, more sophisticated approaches are desirable.
The investigators will take a systematic approach to address the aforementioned limitations of 4D imaging and deformable image registration (DIR) based on the development and cross-fertilization of two major techniques: ultra-quality 4D-MRI and physiological-based hybrid DIR. There are two parts of this research, comprising three main objectives:
Part 1. Technical development in healthy subjects: The investigators will extend their existing pulse sequence strategy for ultra-quality 3D MRI to enable ultra-quality 4D-MRI. Compared to 4D-CT and current 4D-MRI techniques, the proposed ultra-quality 4D-MRI technique offers the following advantages: (a) high spatial resolution (1.5 mm isotropic) with rich image features (e.g. vessel trees) in the whole torso; (b) high temporal pseudo-resolution (>20 phases/cycle); and (c) (nearly) free of motion artifacts.
- Objective 1: Develop an MRI pulse sequence and image reconstruction pipeline that generates images meeting these three design goals.
Part 2. Evaluation of 4D-MRI in a patient study: 4D-MRI will be compared with existing DIR and 4D-CT methods. There will be two classes of comparisons, each formulated as a separate objective:
- Objective 2: Compare motion modelling based on 4D-MRI with deformable image registration (DIR) in healthy volunteers and cancer patients. An improved motion modeling method will be developed that is tailored for the ultra-quality 4D-MRI applications. The investigators hypothesize that a new motion modeling method based on 4D-MRI will outperform current DIR algorithms for respiratory motion estimation. This hypothesis will be tested by comparing the new method to five DIR algorithms which include a mix of commercial software and publicly available algorithms.
- Objective 3: Compare 4D-MRI with 4D-CT in lung and liver cancer patients. The overall hypothesis of this objective is that the ultra-quality 4D-MRI provides better image quality than 4D-CT for motion management of radiotherapy in the lungs and the liver, especially in patients with irregular breathing.
- Conditions
- Healthy Volunteers, Liver Cancer, Lung Cancer
- Being tested
- Magnetic Resonance Imaging
- Medical subject headings
- Liver Neoplasms, Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Magnetic Resonance ImagingDiagnostic test
Four-dimensional MRI of torso
| Study group | Role | What they receive |
|---|---|---|
| Healthy | Healthy volunteers from the local community Receives: Diagnostic Test: Magnetic Resonance Imaging | |
| Liver cancer | Patients undergoing radiotherapy for liver cancer Receives: Diagnostic Test: Magnetic Resonance Imaging | |
| Lung cancer | Patients undergoing radiotherapy for lung cancer Receives: Diagnostic Test: Magnetic Resonance Imaging |
What is being measured
The primary outcome is the main question the study is designed to answer.
Image quality metrics in healthy volunteers
General 4D-MRI image quality will be assessed based on signal-to-noise ratio, number of distinct images per breathing cycle, total necessary imaging time, and image quality index.
Measured: single imaging session, lasting up to 2 hours
Image quality metrics in cancer patients
We hypothesize that our ultra-quality 4D-MRI methodology will outperform 4D-CT for motion management of radiotherapy in the lungs and the liver. We will test this hypothesis by comparing image quality based on tumor volume consistency, number of trackable landmarks, motion measurement accuracy, and image quality index.
Measured: single imaging session, lasting up to 2 hours
DVF errors in healthy volunteers and cancer patients
We hypothesize that our motion modeling method based on 4D-MRI will outperform current DIR algorithms for respiratory motion estimation. We will test this hypothesis by comparing our method to five existing DIR algorithms, based on the magnitude error (Em) and the angular error (Ea) of the calculated deformation vector field (DVF).
Measured: single imaging session, lasting up to 2 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Dec 2020
- Study start5 Nov 2020
- Primary completion31 Dec 2026 (estimated)
- Study completion31 Dec 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Healthy VolunteersStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Virginia
- Sponsor type
- University, hospital or other
- Collaborators
- Duke University, The Hong Kong Polytechnic University
- Responsible party
- Principal investigator, G. Wilson Miller, MD, University of Virginia
- Investigators
- G. Wilson Miller, PhD, Principal investigator, Univsersity of Virginia
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04657042
- Sponsor's protocol ID
- HSR20040
- Status last verified
- Apr 2026
- First submitted
- 23 Nov 2020
- Last updated
- 6 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Data acquired from cancer patients using the optimized 4D-MRI protocol will be used to construct digital phantoms for use by the radiotherapy research community to improve radiotherapy planning methods.
Study at a glance
From the registry record, last updated by the sponsor on 6 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Toward Precision Radiotherapy: Physiological Modeling of Respiratory Motion Based on Ultra-quality 4D-MRI
- ClinicalTrials.gov ID
- NCT04657042
- Acronym / sponsor ID
- HSR20040
- Conditions
- Healthy Volunteers, Liver Cancer, Lung Cancer
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- University of VirginiaUniversity, hospital or other
- Collaborators
- Duke University, The Hong Kong Polytechnic University
- Study start
- 5 Nov 2020 (actual)
- Primary completion
- 31 Dec 2026 (estimated)
- Study completion
- 31 Dec 2030 (estimated)
- First posted
- 8 Dec 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The purpose of this study is to develop new ways to make medical images of the lungs and liver of adults using a technique called four-dimensional magnetic resonance imaging (4D-MRI). This technique produces three-dimensional movies of the inside of the chest and abdomen while the patient is breathing. (The fourth dimension is time!)
This new way of medical imaging is being developed to help cancer patients undergoing radiation therapy. Radiation therapy is used to treat cancerous tumors. For radiation therapy to be effective, the precise size, shape, and location of the tumor within the body must be known. A particular difficulty for radiation treatment of lung and liver cancer is that the tumor moves during treatment because the patient is breathing. Therefore, tumor motion must also be incorporated into the treatment plan. This study aims to improve radiation treatment planning through better targeting and dose estimation based on 4D-MRI. Before this new imaging method can be used for radiation treatment planning, it must be tested in living, breathing volunteers.
Detailed description
Radiotherapy for cancer has been a forerunner of personalized medicine, developing individualized treatments based on patient-specific anatomical information. Despite many advances in radiotherapy over the past decade, which have effectively enhanced local or loco-regional tumor control for many patients, there remains substantial room for improvement. The challenges for radiotherapy to further widen the therapeutic window in the era of precision medicine are mainly two-fold: (a) further improve radiation dose conformity to the defined target volume, and (b) adapt novel biological strategies for personalized treatment. Four-dimensional (4D) imaging and deformable image registration (DIR) are key tools in modern radiotherapy, playing critical roles in many recent advances, including 4D radiotherapy, adaptive radiotherapy, and treatment assessment. However, current 4D imaging and DIR technologies are facing significant challenges as the requirement for precision increases.
The current standard of 4D imaging in radiotherapy is 4D-CT. However, it has two major limitations preventing it from precision radiotherapy applications: (a) low soft-tissue contrast. 4D-CT is therefore not ideal for abdominal applications; (b) motion artifacts caused by irregular breathing. 4D-CT motion artifacts have been shown to cause errors in various radiotherapy applications, including motion measurement, target volume delineation, dose calculation, DIR, and lung ventilation calculation. 4D-MRI is an emerging 4D imaging technology for radiotherapy. It has superior soft-tissue contrast to 4D-CT and is therefore superb for abdominal imaging. Despite many recent advances in 4D-MRI, current 4D-MRI implementations have inadequate image quality for precision radiotherapy application due to at least one of the following deficiencies: low temporal and/or spatial resolutions, long image acquisition time, and suboptimal contrast in the lungs. Resulting 4D-MRI images lack sufficient anatomical details for clinical applications, which can adversely affect the performance of DIR. Current DIR techniques focus on morphological similarity but not on the physiological plausibility of the deformation. Studies have shown that an increased morphological similarity of the aligned data does not always imply increased registration accuracy. Therefore, more sophisticated approaches are desirable.
The investigators will take a systematic approach to address the aforementioned limitations of 4D imaging and deformable image registration (DIR) based on the development and cross-fertilization of two major techniques: ultra-quality 4D-MRI and physiological-based hybrid DIR. There are two parts of this research, comprising three main objectives:
Part 1. Technical development in healthy subjects: The investigators will extend their existing pulse sequence strategy for ultra-quality 3D MRI to enable ultra-quality 4D-MRI. Compared to 4D-CT and current 4D-MRI techniques, the proposed ultra-quality 4D-MRI technique offers the following advantages: (a) high spatial resolution (1.5 mm isotropic) with rich image features (e.g. vessel trees) in the whole torso; (b) high temporal pseudo-resolution (>20 phases/cycle); and (c) (nearly) free of motion artifacts.
- Objective 1: Develop an MRI pulse sequence and image reconstruction pipeline that generates images meeting these three design goals.
Part 2. Evaluation of 4D-MRI in a patient study: 4D-MRI will be compared with existing DIR and 4D-CT methods. There will be two classes of comparisons, each formulated as a separate objective:
- Objective 2: Compare motion modelling based on 4D-MRI with deformable image registration (DIR) in healthy volunteers and cancer patients. An improved motion modeling method will be developed that is tailored for the ultra-quality 4D-MRI applications. The investigators hypothesize that a new motion modeling method based on 4D-MRI will outperform current DIR algorithms for respiratory motion estimation. This hypothesis will be tested by comparing the new method to five DIR algorithms which include a mix of commercial software and publicly available algorithms.
- Objective 3: Compare 4D-MRI with 4D-CT in lung and liver cancer patients. The overall hypothesis of this objective is that the ultra-quality 4D-MRI provides better image quality than 4D-CT for motion management of radiotherapy in the lungs and the liver, especially in patients with irregular breathing.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Healthy | – | Diagnostic Test: Magnetic Resonance ImagingHealthy volunteers from the local community |
| Liver cancer | – | Diagnostic Test: Magnetic Resonance ImagingPatients undergoing radiotherapy for liver cancer |
| Lung cancer | – | Diagnostic Test: Magnetic Resonance ImagingPatients undergoing radiotherapy for lung cancer |
Who may qualify
- Ages
- 18 to 82 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Up to 30 lung cancer patients, 30 liver cancer patients, and 40 healthy human volunteers will receive MRI examinations at the University of Virginia to directly measure respiratory motion in the thorax and abdomen. All subject populations will include roughly equal male and female representations. The subject populations will have minority and ethnic representation typical of the local population area that includes the University of Virginia. No specific racial or ethnic group will be excluded. All subjects must have the ability to understand the requirements of the study and must provide informed consent with a personal signature. No persons from vulnerable populations will be included in this study.
Key inclusion criteria (0 listed)
Key exclusion criteria (7 listed)
- Any condition for which a MRI procedure is contraindicated including presence of metallic material in the body, such as pacemakers, non- MRI compatible surgical clips, shrapnel, etc.
- Subjects who have difficulty lying flat on their back for extended periods of time
- Patients with any serious/poorly controlled medical or psychological conditions that would complicate protocol compliance
- Too large to adequately fit in the magnet bore or RF coils
- Claustrophobia
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Magnetic Resonance ImagingFour-dimensional MRI of torso | Diagnostic test | Healthy, Liver cancer, Lung cancer |
Primary outcome
Image quality metrics in healthy volunteers
Time frame: single imaging session, lasting up to 2 hours
General 4D-MRI image quality will be assessed based on signal-to-noise ratio, number of distinct images per breathing cycle, total necessary imaging time, and image quality index.
Image quality metrics in cancer patients
Time frame: single imaging session, lasting up to 2 hours
We hypothesize that our ultra-quality 4D-MRI methodology will outperform 4D-CT for motion management of radiotherapy in the lungs and the liver. We will test this hypothesis by comparing image quality based on tumor volume consistency, number of trackable landmarks, motion measurement accuracy, and image quality index.
DVF errors in healthy volunteers and cancer patients
Time frame: single imaging session, lasting up to 2 hours
We hypothesize that our motion modeling method based on 4D-MRI will outperform current DIR algorithms for respiratory motion estimation. We will test this hypothesis by comparing our method to five existing DIR algorithms, based on the magnitude error (Em) and the angular error (Ea) of the calculated deformation vector field (DVF).
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 May 2026.
- Individual participant dataSharing planned: Yes. Data acquired from cancer patients using the optimized 4D-MRI protocol will be used to construct digital phantoms for use by the radiotherapy research community to improve radiotherapy planning methods.
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Irritability
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
G. Wilson Miller, PhD principal investigator
Univsersity of Virginia
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Healthy Volunteers and Liver Cancer, run by University of Virginia at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 0 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 6 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Roselove N Nunoo-Asare, MA (4342436074, RNN3B@VIRGINIA.EDU), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Image quality metrics in healthy volunteers (time frame: single imaging session, lasting up to 2 hours). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 May 2026.