thesis research
|
|
Thesis / Doctoral Project / Dissertation Proposal |
|
|
|
Student Information:
I. Title:
Estimation of Peak Skin Dose and Its Relation to the Size Specific Dose Estimate
II. Problem or Hypothesis:
The CT Dose Index (CTDIvol) was originally designed as an index of dose associated with various CT diagnostic procedures not as a direct dosimetry method for individual patient dose assessments. There is no current method for calculating peak skin dose (PSD) using the key metrics provided from the radiation dose structure report of a CT scanner. Every CT study is required to output the kVp and mAs that were used, the dose length product and CT dose index volume which will all be shown on the CT console, but there is no direct method to go straight to the PSD. This project will test the hypothesis that the SSDE has a sufficiently strong linear relationship with PSD to allow direct calculation of the PSD directly from the SSDE.
III. Review of Related Literature:
The highest radiation dose accruing at a single site on a patient’s skin is referred to as the peak skin dose (PSD) which is related to the Computed Tomography dose index (CTDIvol) that is displayed on the console of CT scanners. However, the CT Dose Index was originally designed as an index not as a direct dosimetry method for patient dose assessment. More recently, modifications to original CTDI concept have attempted to convert it into to patient dosimetry method, but have with mixed results in terms of accuracy. Nonetheless, CTDI-based dosimetry is the current worldwide standard for estimation of patient dose in CT. Therefore, CTDIvol is often used to enable medical physicists to compare the dose output between different CT scanners.
Fearon, Thomas (2011) explained that current estimation of radiation dose from CT scans on patients has relied on the measurement of Computed Tomography Dose Index (CTDI) in standard cylindrical phantoms, and calculations based on mathematical representations of “standard man.” The purpose of this study was to investigate the feasibility of adapting a radiation treatment planning system (RTPS) to provide patient-specific CT dosimetry. A radiation treatment planning system was modified to calculate patient-specific CT dose distributions, which can be represented by dose at specific points within an organ of interest, as well as organ dose-volume (after image segmentation) for a GE Light Speed Ultra Plus CT scanner. Digital representations of the phantoms (virtual phantom) were acquired with the GE CT scanner in axial mode. Thermoluminescent dosimeter (TLDs) measurements in pediatric anthropomorphic phantoms were utilized to validate the dose at specific points within organs of interest relative to RTPS calculations and Monte Carlo simulations of the same virtual phantoms. Congruence of the calculated and measured point doses for the same physical anthropomorphic phantom geometry was used to verify the feasibility of the method. The advantage of the RTPS is the significant reduction in computation time, yielding dose estimates within 10%–20% of measured values.
De las Heras (2013) elaborated on the concept of CT scanners and their critical implementation in diagnostic imaging. His method was based on estimating the peak skin dose delivered by CT scanners by measuring the PSD values related to the volume CT dose index (CTDIvol), a parameter that is displayed on the console of modern CT scanners. He obtained the PSD measurement estimates in CT units by placing radio-chromic film on the surface of a CTDI head phantom, and different x-ray tube currents were then used to irradiate the phantom. The PSD and the CTDIvol were independently measured and later related to the CTDIvol value that was displayed on the console. They found that there was a relationship between the measured PSD and the associated CTDIvol displayed on the console, and the measured PSD values varied among all scanners when the routine head scan parameters were used. This work showed the widely used CTDIvol could be used to accurately estimate an actual radiation dose delivered to the skin of a patient. Also, the method and the analysis provided valuable information to patients, radiological technologists, medical physicists, and physicians to relate the displayed CTDIvol to an actual measured dose delivered to the skin of a patient.
Jones, A. Kyle (2021) recently developed a new method to estimate the peak skin dose from CTDIvol. The objective of this study was to validate the methodology during CT-guided ablation procedures. Radio-chromic film was calibrated and used to measure PSD as well. Real patients, rather than phantoms, were used in the study. CTDIvol stratified by axial and helical scanning was used to calculate an estimate of PSD, and both calculated PSD and total CTDIvol were compared to measured PSD. The calculated PSD were significantly different from the measured PSD, but the measured PSD were not significantly different from total CTDIvol which prove that the CTDI can help in measuring the patient dose. Considering that CTDIvol was reported on the console of all CT scanners, is not stratified by axial and helical scanning modes, and is immediately available to the operator during CT-guided interventional procedures.
Each of the methodologies mentioned above represents a reasonably accurate approach for computing the patient dose from CT procedures. Reassuringly, estimation of the dose to either phantoms or actual patients yielded comparable doses. However, all the methodologies used to obtaine the PSD measurement were based on the same experimental approach. They estimated in CT units by placing a radio-chromic film on the surface of a CTDI phantom. This research project will use a completely different approach -- it will make patient dose estimates by means of Nanodots dosimeters. Nanodots have optically stimulated luminescence (OSL) technology which is a single point radiation monitoring dosimeter. It is a useful tool in measuring the patient dose, and it is an ideal solution in multiple settings, including diagnostic radiology, nuclear medicine, interventional procedures and radiation oncology. These dosimeters have the technical advantage that they can be placed anywhere on the body or phantom and the nondestructive readout supports reanalysis and electronic data archiving.
IV. Procedure or Method:
The CTDIvol displayed by the scanner will be validated to the true CTDIvol following the ACR testing guidelines. A correction factor will be used to correct any inaccuracies in the displayed value. This correction will also be applied to the DLP displayed by the scanner.
Peak skin dose and its relation will be measured by various phantoms such as NEMA phantoms, 16 cm CTDI and 32 cm CTDI phantoms. The phantoms will be aligned at the isocenter of the scanner with the chamber in the center hole of the phantom. The longitudinal axis of the chamber and cylindrical phantom will be aligned parallel to the longitudinal axis of the CT gantry. With using those different phantoms, the dosimeter will be placed serially in center hole ad peripheral hole. Those measurements are combined to produce the weighted CTDI, so a 100-mm-long cylindrical (pencil) chamber, approximately 9 mm in diameter, inserted into either the center or a peripheral hole of a phantom as shown in figure 1, and with the pencil chamber located at the center (in the z-dimension) of the phantom and also at the center of the CT gantry, a single axial CT scan is made. An ionization chamber can only produce an accurate dose estimate if its entire sensitive volume is irradiated by the x-ray beam. Therefore, for the partially irradiated 100-mm CT pencil chamber, the nominal beam width which is the total collimated x-ray beam width as indicated on the CT console, is used to correct the chamber reading for the partial volume exposure. The 100-mm chamber length is useful for x-ray beams of thin slices such as 5 mm to thicker beam collimations such as 40 mm. The correction for partial volume is essential and is calculated using the correction for partial volume is essential and is calculated using which B can be either the total collimated beam width, in mm, for a single axial scan or the width of an individual CT detector (T) number of active detectors (n)
Then the CTDI will be calculated as CTDI100 = (1/3) x CTDIcenter + (2/3) x CTDIperiphery. Combining the center and peripheral measurements using a 1/3 and 2/3 weighting scheme provides a good estimate of the average dose to the phantom at the central CT slice along z, giving rise to the weighted CTDI, CTDIw. The CTDI100, which is the amount of radiation delivered to one slice of the body over a long CT scan and it is also known as CTDI weighted. The scanner scans the entire volume in a helical trajectory. Thus, there isn't really a true 'slice', as the z-position of the scanner is different at each angle. Also, the spacing between successive revolutions of the CT tube represents the pitch of the scan. In fact, the wider the helix, the less dose the patient will receive because the same portion of tissue is being irradiated at fewer angles, so the larger the pitch the lower the dose. Therefore, CTDIvol represent the dose for a specific scan protocol which considers gaps and overlaps between the radiation dose profile from consecutive rotations of the x-ray source and it can be calculated; CTDIvol = (1/pitch) x CTDIw. The CTDIw represents the average radiation dose over the x and y direction whereas CTDIvol represents the average radiation dose over the x, y and z directions.
Nanodot dosimeters will be placed on the LAT and AP locations as shown in figure 2, the dose to the skin will be measured at these locations. Then, the phantoms will be scanned over the scan length for a fixed value of the tube current. The measurement will be repeated several times using various scanning techniques (with varying energy, current). Size conversion factors used will be based on the dimension of the phantom being scanned used. These K-factors with the CTDIvol can produce size specific dose estimates (SSDEs), and since the CT dose index will be provided at the CT scanner too, the size specific dose estimate for the phantoms will be calculated. Also testing if the correlation between the size specific dose estimate and the measurement of the peak skin dose match will be done, and if such a relationship exists, trying to find that factor will be the aim.
Finally, in null hypothesis significance testing, the p-value is the probability of obtaining test results at least as extreme as the results observed under the assumption that the null hypothesis is correct. Since reporting the p-values of statistical tests is common practice in academic publication of many quantitative fields, then calculating the p-value will be done and looking for very small p-value will be the hope. Because small p-value (p-value <0.05) means that such an extreme observed outcome would be very unlikely under the null hypothesis and regression analyses and correlation coefficients are statically significant.
Phantom
Phantom
Figure1: a 100-mm-long cylindrical (pencil) chamber, approximately 9 mm in diameter, inserted into either the center or a peripheral hole of a phantom.
1
CT TABLE
3
2
Figure2: a phantom in the middle of the CT scan and 1 is the AP location, 2 is the LAT location and 3 is the PA location.
V. Selected Bibliography:
|
Andersson, J., Bednarek, D. R., Bolch, W., Boltz, T., Bosmans, H., Gislason-Lee, A. J., ... & Zamora, D. (2021). Estimation of patient skin dose in fluoroscopy: summary of a joint report by AAPM TG357 and EFOMP. Medical physics (Lancaster). da Silva, E. H., Baffa, O., Elias, J., & Buls, N. (2021). Conversion factor for size specific dose estimation of head CT scans based on age, for individuals from 0 up to 18 years old. Physics in Medicine & Biology, 66(8), 085011. Fleury, A. S., Durand, R. E., Cahill, A. M., Zhu, X., Meyers, K. E., & Otero, H. J. (2021). Validation of computed tomography angiography as a complementary test in the assessment of renal artery stenosis: a comparison with digital subtraction angiography. Pediatric Radiology, 1-14. Greffier, J., Hamard, A., Berny, L., Snene, F., Perolat, R., Larbi, A., ... & Beregi, J. P. (2021). A retrospective comparison of organ dose and effective dose in percutaneous vertebroplasty performed under CT guidance or using a fixed C-arm with a flat-panel detector. Physica Medica, 88, 235-241. Jauhari, A., Anam, C., Ali, M. H., Rae, W. I. D., Akbari, S., & Meilinda, T. (2021). The effect on CT size-specific dose estimates of mis-positioning patientsfrom the iso-centre. European Journal of Molecular & Clinical Medicine, 8(3), 155-164. Jones, A. K., Kisiel, M. E., Rong, X. J., & Tam, A. L. (2021). Validation of a method for estimating peak skin dose from CT‐guided procedures. Journal of applied clinical medical physics. Loose, R. W., Vano, E., Mildenberger, P., Tsapaki, V., Caramella, D., Sjöberg, J., ... & Damilakis, J. (2021). Radiation dose management systems—requirements and recommendations for users from the ESR EuroSafe Imaging initiative. European Radiology, 31(4), 2106-2114. Mohamed, A. I. A. (2021). Estimation of Effective Dose for Pediatric Patients During Computed Tomography Examinations (Doctoral dissertation, Sudan University of Science and Technology). Okamoto, H., Kito, S., Tohyama, N., Yonai, S., Kawamorita, R., Nakamura, M., ... & Shioyama, Y. (2021). Radiation protection in radiological imaging: a survey of imaging modalities used in Japanese institutions for verifying applicator placements in high-dose-rate brachytherapy. Journal of Radiation Research, 62(1), 58-66. Saeed, M. K. (2021). Comparison of estimated and calculated fetal radiation dose for a pregnant woman who underwent computed tomography and conventional X-ray examinations based on a phantom study. Radiological Physics and Technology, 14(1), 25-33. Steuwe, A., Weber, M., Bethge, O. T., Rademacher, C., Boschheidgen, M., Sawicki, L. M., … & Aissa, J. (2021). Influence of a novel deep-learning based reconstruction software on the objective and subjective image quality in low-dose abdominal computed tomography. The British Journal of Radiology, 94(1117), 20200677. Sundell, V. M., Kortesniemi, M., Siiskonen, T., Kosunen, A., Rosendahl, S., & Büermann, L. (2021). Patient-Specific Dose Estimates In Dynamic Computed Tomography Myocardial Perfusion Examination. Radiation Protection Dosimetry, 193(1), 24-36. Tabari, A., Li, X., Yang, K., Liu, B., Gee, M. S., & Westra, S. J. (2021). Patient-level dose monitoring in computed tomography: tracking cumulative dose from multiple multi-sequence exams with tube current modulation in children. Pediatric Radiology, 1-9. Thierry-Chef, I., Ferro, G., Le Cornet, L., Dabin, J., Istad, T. S., Jahnen, A., ... & Simon, S. L. (2021). Dose estimation for the european epidemiological study on pediatric computed tomography (EPI-CT). Radiation Research, 196(1), 74-99. De las Heras, H., Minniti, R., Wilson, S., Mitchell, C., Skopec, M., Brunner, C. C., & Chakrabarti, K. (2013). Experimental estimates of peak skin dose and its relationship to the CT dose index using the CTDI head phantom. Radiation protection dosimetry, 157(4), 536-542.
|
V. Use of Human Subjects:
Does your research involve the use of human subjects? No
|
No |
If yes, you must obtain approval from the appropriate University Institutional Review Board before your proposal can be submitted to the Graduate School. Submit a copy of the IRB Approval Memo for your research along with this form.
|
IRB Number: |
VII. Student Signature:
Abdullatif Abdullah October, 29th 2021
Signature Date
VIII. Faculty Approvals:
COMMITTEE ROLE: |
MEMBER NAME: (typed) |
SIGNATURE: |
DATE: |
|
Thesis Advisor |
Matthew Williams |
|
11/5/2021 |
|
Committee Member |
Stanley Thomas Fricke |
|
11/14/2021 |
|
Committee Member |
|
|
|
|
Committee Member |
|
|
|
|
Committee Member |
|
|
|
Directorof Graduate Studies |
|
|
|
|
Completed form should be returned to: |
BGE students should return the form to: |
|
Graduate School of Arts & Sciences |
Biomedical Graduate Education Office |
|
Car Barn 207, 3520 Prospect Street, NW gradstudentservices@georgetown.edu |
SE109 Medical Dental Building bgestudentservices@georgetown.edu |
5