The Effects of Mismatch between SPECT and CT Images on Quantitative Activity Estimation – A Simulation Study

Abstract Background: Quantitative activity estimation is essential in targeted radionuclide therapy dosimetry. Misregistration between SPECT and CT images at the same imaging time point due to patient movement degrades accuracy. This work aims to study the mismatch effects between CT and SPECT data on attenuation correction (AC), volume-of-interest (VOI) delineation and registration for activity estimation.Methods: Nine 4D XCAT phantoms were generated at 1, 24, and 144 hrs post In-111 Zevalin injection, varying in activity distributions, body and organ sizes. Realistic noisy SPECT projections were generated by an analytical projection and reconstructed with quantitative OS-EM method. CT images were shifted from -5 to 5 voxels as well as according to clinical reference corresponding to SPECT images at each time point. For AC effect, mismatched CT images were used for AC in SPECT reconstruction while VOIs were mapped out from matched CTs. For VOI effect, target organs were mapped out using mismatched CTs with matched CTs for AC. For registration effect, non-rigid registrations were performed on sequential mismatched CTs to align corresponding SPECT images, with no AC and VOI mismatch. Bi-exponential curve fitting was performed to obtain time-integrated activity (TIA). Organ activity errors (%OAE) and TIA errors (%TIAE) were calculated.Results: According to clinical reference, %OAE was larger for organs near ribs for AC effect, e.g., -2.58%±0.81% for liver. For VOI effect, %OAE was larger for small and low uptake organs, e.g., -11.94%±10.34% for spleen. %OAE was proportional to mismatch magnitude, e.g., 4.77%±1.41%, 12.01%±3.97% and 42.81%±6.38% for 1-, 2-, and 5-voxel mismatch for lungs. For registration effect, %TIAE were larger when mismatch existed in more numbers of SPECT/CT images, while no substantial difference was observed when using mismatched CT at different time points for registration reference. %TIAE was highest for VOI, followed by registration and AC, e.g., 37.61%±5.08%, 14.25%±7.07% and 1.13%±0.90% respectively for kidneys.Conclusions: The mismatch between CT and SPECT images poses a significant impact on accuracy of quantitative activity estimation in dosimetry, attributed particularly from VOI delineation errors. It is recommended to perform registration between emission and transmission images at the same time point to ensure dosimetric accuracy.

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A New Framework for the Accurate FE Model of Bone Tissue Based on CT Images

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.44-47.1612 ◽

2010 ◽

Vol 44-47 ◽

pp. 1612-1616

Author(s):

Xiao Hui Huang ◽

Guo Qun Zhao ◽

Wen Guang Liu ◽

Pei Lai Liu

Keyword(s):

Bone Tissue ◽

Material Property ◽

Geometric Model ◽

Automatic Segmentation ◽

Region Of Interest ◽

Ct Images ◽

Fe Model ◽

Volume Of Interest ◽

Smooth Operator ◽

New Framework

The frameworks for finite element (FE) model of bone tissue available in pervious literatures, to some extent, are expert-oriented and give rise to a considerable deviation in geometric model and assignment of material property. The objective of this study is to develop a new framework to reconstruct accurate individual bone FE model based on CT images rapidly and conveniently. In image-processing, automatic segmentation of the region of interest (ROIs) improves the efficiency. The idea of enclosed volume of interest (VOI) overcomes the drawback of geometric ambiguity in Marching Cube (MC) method. Geometric model is easily obtained by a STL translator and smooth operator in home-made program. In the material property assignment, two templates for hexahedron and tetrahedron FE models, respectively, are put forth to smoothing an abrupt change of material property in the region from cortical to cancellous. K-mean algorithm is introduced to cluster material properties to improve partition performance. Finally, the new framework is demonstrated by the implementation of a femoral FE model.

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The impact of 3D volume of interest definition on accuracy and precision of activity estimation in quantitative SPECT and planar processing methods

Physics in Medicine and Biology ◽

10.1088/0031-9155/55/12/017 ◽

2010 ◽

Vol 55 (12) ◽

pp. 3535-3544 ◽

Cited By ~ 19

Author(s):

Bin He ◽

Eric C Frey

Keyword(s):

Quantitative Spect ◽

Processing Methods ◽

Volume Of Interest ◽

Accuracy And Precision ◽

3D Volume ◽

The Impact ◽

Activity Estimation

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MRI-only brain radiotherapy: Assessing the dosimetric accuracy of synthetic CT images generated using a deep learning approach

Radiotherapy and Oncology ◽

10.1016/j.radonc.2019.03.026 ◽

2019 ◽

Vol 136 ◽

pp. 56-63 ◽

Cited By ~ 23

Author(s):

Samaneh Kazemifar ◽

Sarah McGuire ◽

Robert Timmerman ◽

Zabi Wardak ◽

Dan Nguyen ◽

...

Keyword(s):

Deep Learning ◽

Ct Images ◽

Learning Approach ◽

Brain Radiotherapy ◽

Dosimetric Accuracy ◽

Synthetic Ct

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Using neighborhood gray tone difference matrix texture features on dual time point PET/CT images to differentiate malignant from benign FDG-avid solitary pulmonary nodules

Cancer Imaging ◽

10.1186/s40644-019-0243-3 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Song Chen ◽

Stephanie Harmon ◽

Timothy Perk ◽

Xuena Li ◽

Meijie Chen ◽

...

Keyword(s):

Pulmonary Nodules ◽

Texture Features ◽

Ct Images ◽

Solitary Pulmonary Nodules ◽

Difference Matrix ◽

Pet Ct ◽

Gray Tone ◽

Dual Time Point ◽

Time Point

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MRI-based Treatment Planning with Electron Density Information Mapped from CT Images: A Preliminary Study

Technology in Cancer Research & Treatment ◽

10.1177/153303460800700501 ◽

2008 ◽

Vol 7 (5) ◽

pp. 341-347 ◽

Cited By ~ 23

Author(s):

C. Wang ◽

M. Chao ◽

L. Lee ◽

L. Xing

Keyword(s):

Electron Density ◽

Radiation Treatment ◽

Dose Calculation ◽

Ct Images ◽

Planar Imaging ◽

Mr Images ◽

Dosimetric Accuracy ◽

Tissue Contrast ◽

Preliminary Study ◽

Ct Data

Nowadays magnetic resonance imaging (MRI) has been profoundly used in radiotherapy (RT) planning to aid the contouring of targets and critical organs in brain and intracranial cases, which is attributable to its excellent soft tissue contrast and multi-planar imaging capability. However, the lack of electron density information in MRI, together with the image distortion issues, precludes its use as the sole image set for RT planning and dose calculation. The purpose of this preliminary study is to probe the feasibility and evaluate an MRI-based radiation dose calculation process by providing MR images the necessary electron density (ED) information from a patient's readily available diagnostic/staging computed tomography (CT) images using an image registration model. To evaluate the dosimetric accuracy of the proposed approach, three brain and three intracranial cases were selected retrospectively for this study. For each patient, the MR images were registered to the CT images, and the ED information was then mapped onto the MR images by in-house developed software generating a modified set of MR images. Another set of MR images with voxel values assigned with the density of water was also generated. The original intensity modulated radiation treatment (IMRT) plan was then applied to the two sets of MR images and the doses were calculated. The dose distributions from the MRI-based calculations were compared to that of the original CT-based calculation. In all cases, the MRI-based calculations with mapped ED yielded dose values very close (within 2%) to that of the CT-based calculations. The MRI-based calculations with voxel values assigned with water density indicated a dosimetric error of 3–5%, depending on the treatment site. The present approach offers a means of utilizing MR images for accurate dose calculation and affords a potential to eliminate the redundant simulation CT by planning a patient's treatment with only simulation MRI and any available diagnostic/staging CT data.

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