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Li, Baojun

https://orcid.org/0000-0001-6683-5535

Mayo Clinic

Boston University

Citations 2

AAPM Task Group Report 299: Quality control in multi‐energy computed tomography
Leng, Shuai, Boedeker, Kirsten , Burk, Laurel M., Dang, Hao , Li, Baojun , Madhav, Priti, Miller, Jessica R. , Nute, J, Giraldo, Juan Carlos Ramírez, Ruchala, Kenneth J., Tao, Shengzhen , Varchena, Vladimir, Vedantham, Srinivasan , Zeng, Rongping , Layman, Rick R. , Leng, Shuai , Duan, Xinhui , Jacobsen, Megan C. , Li, Ke , Little, Kevin J. , Ruchala, Ken, Zhang, Da

Medical Physics | July 29, 2024 | Volume: 51 | Issue: 10 | Pages: 7012-7037

10.1002/mp.17322 Get It

AbstractMulti‐energy computed tomography (MECT) offers the opportunity for advanced visualization, detection, and quantification of select elements (e.g., iodine) or materials (e.g., fat) beyond the capability of standard single‐energy computed tomography (CT). However, the use of MECT requires careful consideration as substantially different hardware and software approaches have been used by manufacturers, including different sets of user‐selected or hidden parameters that affect the performance and radiation dose of MECT. Another important consideration when designing MECT protocols is appreciation of the specific tasks being performed; for instance, differentiating between two different materials or quantifying a specific element. For a given task, it is imperative to consider both the radiation dose and task‐specific image quality requirements. Development of a quality control (QC) program is essential to ensure the accuracy and reproducibility of these MECT applications. Although standard QC procedures have been well established for conventional single‐energy CT, the substantial differences between single‐energy CT and MECT in terms of system implementations, imaging protocols, and clinical tasks warrant QC tests specific to MECT. This task group was therefore charged with developing a systematic QC program designed to meet the needs of MECT applications. In this report, we review the various MECT approaches that are commercially available, including information about hardware implementation, MECT image types, image reconstruction, and postprocessing techniques that are unique to MECT. We address the requirements for MECT phantoms, review representative commercial MECT phantoms, and offer guidance regarding homemade MECT phantoms. We discuss the development of MECT protocols, which must be designed carefully with proper consideration of MECT technology, imaging task, and radiation dose. We then outline specific recommended QC tests in terms of general image quality, radiation dose, differentiation and quantification tasks, and diagnostic and therapeutic applications.
Visualization and comparison of CT dose distribution between axial and helical acquisitions
Li, Xinhua, Yu, Lifeng , Li, Baojun , Marschall, Theodore A. , Liu, Bob , Yang, Kai , Li, Xinhua , Yu, Lifeng

Medical Physics | June 7, 2023 | Volume: 50 | Issue: 8 | Pages: 4797-4808

10.1002/mp.16530 Get It

AbstractBackgroundIt is challenging to assess the accuracy of volume CT Dose Index (CTDIvol) when the axial scan modes corresponding to a helical scan protocol are not available. An alternative approach was proposed to directly measure using helical acquisitions and relatively small differences (< 20%) from CTDIvol were observed.PurposeTo visually demonstrate the 3D dose distribution for both axial and helical CT acquisitions and quantitively compare and CTDIvol.Methods3D dose distribution within the standard CTDI phantoms (16 and 32 cm diameter) from a single CT projection, Dp(x,y,z) was first generated using Monte Carlo simulation (GEANT4) with 9×108 photons per combination of tube voltage (80–140 kV), collimation width (1–8 cm), and z‐axis location of the central ray of the x‐ray beam, with a spatial resolution of 1 mm3. These dose distributions from one single projection were analytically ensembled to simulate 3D dose volumes DA(x,y,z) and DH(x,y,z) for axial and helical scans, respectively, with different helical pitches (0.3–2) and scan lengths (100–150 mm). 2D planar dose distributions were obtained by integrating the inside 100 mm of the dose volumes. CTDIvol and were calculated using the planar dose data at corresponding pencil chamber locations and the percentage differences (PD) were reported.ResultsHigh spatial resolution 3D CT dose volumes were generated and visualized. PDs between and CTDIvol had strong dependency on scan length and peripheral chamber locations, with subtle dependency on collimation width and pitch. PDs were mostly within the range of ± 3% for a scan length of 150 mm with four peripheral chamber locations.ConclusionsWith a scan length covering the entire phantom length, directly measured from helical scans can serve as an alternative to CTDIvol only if all four peripheral locations were measured.