Ehsan Samei

Overview:

Dr. Ehsan Samei, PhD, DABR, FAAPM, FSPIE, FAIMBE, FIOMP, FACR is a Persian-American medical physicist. He is a tenured Professor of Radiology, Medical Physics, Biomedical Engineering, Physics, and Electrical and Computer Engineering at Duke University, where he also serves as the Chief Imaging Physicist for Duke University Health System, the director of the Carl E Ravin Advanced Imaging Laboratories, and the director of Center for Virtual Imaging Trials. He is certified by the American Board of Radiology, recognized as a Distinguished Investigator by the Academy of Radiology Research, and awarded Fellow by the American Association of Physicists in Medicine (AAPM), the International Society of Optics and Photonics (SPIE), the American Institute of Medical and Biomedical Engineering, International Organization of Medical Physics, and American College of Radiology. He was a founder or co-founder of the Duke Medical Physics Program, the Duke Imaging Physics Residency Program, the Duke Clinical Imaging Physics Group, the Center for Virtual Imaging Trials, and the Society of Directors of Academic Medical Physics Programs (SDAMPP). He has held senior leadership positions in the AAPM, SPIE, SDAMPP, and RSNA. 

Dr. Samei’s expertise include x-ray imaging, theoretical imaging models, simulation methods, and experimental techniques in medical image formation, analysis, assessment, and perception.  His current research includes methods to develop image quality and safety metrics that are clinically relevant and that can be used to design and utilize advanced imaging techniques towards optimum interpretive and quantitative performance. His research aims to bridge the gap between scientific scholarship and clinical practice, in the meaningful realization of translational research, and in clinical processes that are informed by scientific evidence. Those include advanced imaging performance characterization, procedural optimization, and radiomics in retrospective clinical dose and quality analytics. His most recent research interests have been virtual clinical trial across a broad spectrum of oncologic, pulmonary, cardiac, and vascular diseases, and developing  methodological advances that provide smart fusions of conventional, principle-informed and newer AI-based, data-informed approaches to scientific inquiry.

Dr. Samei has mentored over 100 trainees (graduate and postgraduate). He has over 1000 scientific publications including 300+ referred journal articles and 4 books. His laboratory of over 20 researchers has been supported continuously over years by 41 extramural grants, culminating in a NIH Program Project grant in 2021 to establish the national Center for Virtual Imaging Trials (CVIT), joining a small number of prominent Biomedical Technology Research Centers across the nation.

Positions:

Reed and Martha Rice Distinguished Professor of Radiology

Radiology
School of Medicine

Professor in Radiology

Radiology
School of Medicine

Professor in the Department of Physics

Physics
Trinity College of Arts & Sciences

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Professor of Biomedical Engineering

Biomedical Engineering
Pratt School of Engineering

Professor in the Department of Electrical and Computer Engineering

Electrical and Computer Engineering
Pratt School of Engineering

Education:

M.E. 1995

University of Michigan, Ann Arbor

Ph.D. 1997

University of Michigan, Ann Arbor

Grants:

3D Digital Breast Phantoms For Multimodality Research

Administered By
Radiology
Awarded By
National Institutes of Health
Role
Collaborator
Start Date
End Date

Information-Theoretic Based CAD in Mammography

Administered By
Radiology
Awarded By
National Institutes of Health
Role
Scientist
Start Date
End Date

Tomosynthesis for Improved Breast Cancer Detection

Administered By
Radiology
Awarded By
National Institutes of Health
Role
Co Investigator
Start Date
End Date

Resolution Requirements for Mammographic Displays

Administered By
Radiology
Awarded By
National Institutes of Health
Role
Principal Investigator
Start Date
End Date

3D Printing of Anatomically Realistic Phantoms for Optimization of Imaging Algorithms

Administered By
Radiology
Awarded By
National Institutes of Health
Role
Investigator
Start Date
End Date

Publications:

Oncology-specific radiation dose and image noise reference levels in adult abdominal-pelvic CT.

OBJECTIVES: To provide our oncology-specific adult abdominal-pelvic CT reference levels for image noise and radiation dose from a high-volume, oncologic, tertiary referral center. METHODS: The portal venous phase abdomen-pelvis acquisition was assessed for image noise and radiation dose in 13,320 contrast-enhanced CT examinations. Patient size (effective diameter) and radiation dose (CTDIvol) were recorded using a commercial software system, and image noise (Global Noise metric) was quantified using a custom processing system. The reference level and range for dose and noise were calculated for the full dataset, and for examinations grouped by CT scanner model. Dose and noise reference levels were also calculated for exams grouped by five different patient size categories. RESULTS: The noise reference level was 11.25 HU with a reference range of 10.25-12.25 HU. The dose reference level at a median effective diameter of 30.7 cm was 26.7 mGy with a reference range of 19.6-37.0 mGy. Dose increased with patient size; however, image noise remained approximately constant within the noise reference range. The doses were 2.1-2.5 times than the doses in the ACR DIR registry for corresponding patient sizes. The image noise was 0.63-0.75 times the previously published reference level in abdominal-pelvic CT examinations. CONCLUSIONS: Our oncology-specific abdominal-pelvic CT dose reference levels are higher than in the ACR dose index registry and our oncology-specific image noise reference levels are lower than previously proposed image noise reference levels. ADVANCES IN KNOWLEDGE: This study reports reference image noise and radiation dose levels appropriate for the indication of abdomen-pelvis CT examination for cancer diagnosis and staging. The difference in these reference levels from non-oncology-specific CT examinations highlight a need for indication-specific, dose index and image quality reference registries.
Authors
Ahmad, M; Liu, X; Morani, AC; Ganeshan, D; Anderson, MR; Samei, E; Jensen, CT
MLA Citation
Ahmad, Moiz, et al. “Oncology-specific radiation dose and image noise reference levels in adult abdominal-pelvic CT.Clin Imaging, vol. 93, Jan. 2023, pp. 52–59. Pubmed, doi:10.1016/j.clinimag.2022.10.016.
URI
https://scholars.duke.edu/individual/pub1556840
PMID
36375364
Source
pubmed
Published In
Clin Imaging
Volume
93
Published Date
Start Page
52
End Page
59
DOI
10.1016/j.clinimag.2022.10.016

Coronary Artery Calcium Evaluation Using New Generation Photon-counting Computed Tomography Yields Lower Radiation Dose Compared With Standard Computed Tomography.

<h4>Abstract</h4>Prospective head-to-head comparison of coronary calcium scores between standard computed tomography (CT) and photon-counting CT show no significant differences, while photon-counting CT administers substantially lower radiation dose.
Authors
Schwartz, FR; Daubert, MA; Molvin, L; Ramirez-Giraldo, JC; Samei, E; Marin, D; Tailor, TD
MLA Citation
Schwartz, Fides R., et al. “Coronary Artery Calcium Evaluation Using New Generation Photon-counting Computed Tomography Yields Lower Radiation Dose Compared With Standard Computed Tomography.Journal of Thoracic Imaging, vol. 38, no. 1, Jan. 2023, pp. 44–45. Epmc, doi:10.1097/rti.0000000000000685.
URI
https://scholars.duke.edu/individual/pub1558801
PMID
36490311
Source
epmc
Published In
Journal of Thoracic Imaging
Volume
38
Published Date
Start Page
44
End Page
45
DOI
10.1097/rti.0000000000000685

Evaluation and extension of in vivo detectability index to deep-learning and photon counting CT techniques

Authors
Ria, F; Jensen, C; Zarei, M; Liu, X; Schwartz, F; Abbey, C; Samei, E
URI
https://scholars.duke.edu/individual/pub1558609
Source
manual
Published Date

Optimization of imaging as a risk-versus-risk framework of quantitative balance between clinical and radiation risk: a task-based implementation for liver CT in a large demographic population

Authors
Ria, F; Lerebours, R; Zhang, A; Erkanli, A; Marin, D; Samei, E
URI
https://scholars.duke.edu/individual/pub1558608
Source
manual
Published Date

Emphysema quantifications with CT: Assessing the effects of acquisition protocols and imaging parameters using virtual imaging trials.

BACKGROUND: CT has notable potential to quantify the severity and progression of patients with emphysema. Such quantification should ideally reflect the true attributes and pathologies of subjects, not scanner parameters. To achieve such an objective, the effects of the scanner conditions need to be understood so the influence can be mitigated. RESEARCH QUESTION: How do CT imaging parameters affect the accuracy of emphysema-based quantifications and biomarkers? STUDY DESIGN AND METHODS: Twenty anthropomorphic digital phantoms were developed with diverse anatomical attributes and emphysema abnormalities informed by a real COPD cohort. The phantoms were input to a validated CT simulator (DukeSim), modeling a commercial scanner (Siemens Flash). Virtual images were acquired under various clinical conditions of dose levels, tube current modulations (TCM), and reconstruction techniques and kernels. The images were analyzed to evaluate the effects of imaging parameters on the accuracy of density-based quantifications (LAA-950 and Perc15) across varied subjects. Paired t-tests were performed to explore statistical differences between any two imaging conditions. RESULTS: The most accurate imaging condition corresponded to the highest acquired dose (100 mAs) and iterative reconstruction (SAFIRE) with the smooth kernel of I31, where the measurement errors (difference between measurement and ground truth) were 35±3 HU, -4±5%, and 26±10 HU (average±std), for the mean lung HU, LAA-950, and Perc15, respectively. Without TCM and at the I31 kernel, increase of dose (20 to 100 mAs) improved the lung mean absolute error (MAE) by 4.2±2.3 HU (average±std). TCM did not contribute to a systematic improvement of lung MAE. INTERPRETATION: The results highlight that while CT quantification is possible, its reliability is impacted by the choice of imaging parameters. The developed virtual imaging trial platform in this study enables comprehensive evaluation of CT methods in reliable quantifications, an effort that cannot be readily made with patient images or simplistic physical phantoms.
Authors
Abadi, E; Jadick, G; Lynch, DA; Segars, WP; Samei, E
MLA Citation
URI
https://scholars.duke.edu/individual/pub1559040
PMID
36462532
Source
pubmed
Published In
Chest
Published Date
DOI
10.1016/j.chest.2022.11.033