Purpose: Proper fluoroscopic education and protocols may reduce the patient radiation dose but few prospective studies in urology have been performed. Using optically stimulated luminescent dosimeters we tested whether fluoroscopy time and/or entrance skin dose would decrease after educational and radiation reduction protocols.Materials and Methods: At default manufacturer settings fluoroscopy time and entrance skin dose were prospectively measured using optically stimulated luminescent dosimeters in patients undergoing ureteroscopy, retrograde pyelogram/ stent or percutaneous nephrolithotomy with access for stone disease. A validated radiation safety competency test was administered to urology faculty and residents before and after web based, hands-on fluoroscopy training. Default fluoroscopy settings were changed from continuous to intermittent pulse rate and from standard to half-dose output. Fluoroscopy time and entrance skin dose were then measured again.Results: The cohorts of 44 pre-protocol and 50 post-protocol patients with stones were similarly matched. The change in mean fluoroscopy time and entrance skin dose from pre-protocol to post-protocol was -0.6 minutes and -11.6 mGy (33%) for percutaneous nephrolithotomy (p = 0.62 and < 0.001), 0.5 minutes and -0.1 mGy (34%) for ureteroscopy (p = 0.42 and 0.31), and 0.1 minute and -0.1 mGy (29%) for retrograde pyelogram/stent (p = 0.85 and 0.49, respectively). Urologist post-training test scores increased 30% from pretraining scores (p = 0.1).Conclusions: Radiation safety training protocols improved clinical knowledge but did not significantly alter fluoroscopy time. Changing equipment default settings to intermittent pulse rate (12 frames per second) and half-dose lowered the entrance skin dose by 30% across all endourology patients but most significantly during percutaneous nephrolithotomy. To limit patient radiation exposure fluoroscopy default settings should be decreased before all endourology procedures and image equipment manufacturers should consider lowering standard default renal settings.

Purpose: New radiation dose reduction technologies are emerging constantly in the medical imaging field. The latest of these technologies, iterative reconstruction (IR) in CT, presents the ability to reduce dose significantly and hence provides great opportunity for CT protocol optimization. However, without effective analysis of image quality, the reduction in radiation exposure becomes irrelevant. This work explores the use of postmortem subjects as an image quality assessment medium for protocol optimizations in abdominal CT. Methods: Three female postmortem subjects were scanned using the Abdomen-Pelvis (AP) protocol at reduced minimum tube current and target noise index (SD) settings of 12.5, 17.5, 20.0, and 25.0. Images were reconstructed using two strengths of iterative reconstruction. Radiologists and radiology residents from several subspecialties were asked to evaluate 8 AP image sets including the current facility default scan protocol and 7 scans with the parameters varied as listed above. Images were viewed in the soft tissue window and scored on a 3-point scale as acceptable, borderline acceptable, and unacceptable for diagnosis. The facility default AP scan was identified to the reviewer while the 7 remaining AP scans were randomized and de-identified of acquisition and reconstruction details. The observers were also asked to comment on the subjective image quality criteria they used for scoring images. This included visibility of specific anatomical structures and tissue textures. Results: Radiologists scored images as acceptable or borderline acceptable for target noise index settings of up to 20. Due to the postmortem subjects’ close representation of living human anatomy, readers were able to evaluate images as they would those of actual patients. Conclusion: Postmortem subjects have already been proven useful for direct CT organ dose measurements. This work illustrates the validity of their use for the crucial evaluation of image quality during CT protocol optimization, especially when investigating the effects of new technologies.

PURPOSE:To develop a methodology that allows direct measurement of organ doses from computed tomographic (CT) examinations of postmortem subjects.MATERIALS AND METHODS:In this institutional review board approved study, the x-ray linear attenuation coefficients of various tissues were calculated from the mean CT numbers of images that were obtained in eight embalmed adult female cadavers and compared with the corresponding linear attenuation coefficients calculated from CT images obtained in eight living patients that were body mass index (BMI)-matched. Dosimetry was performed in three of the cadavers by accessing organs of interest and affixing partially sealed vinyl tubes inside them. Optically stimulated luminescent dosimeters (OSLDs) were inserted into the tubes and positioned within the organs of interest and on the skin. OSLDs were read with an InLight MicroStar (Landauer, Glenwood, Ill) reader, and readings were corrected for energy and scatter response. Fifteen tubes containing dosimeters were used, and imaging was repeated twice in each cadaver, for a total of five standard clinical protocols. Average dosimetry values were used for analysis.RESULTS:Differences in linear attenuation coefficients between living and embalmed cadaveric tissues were within 3% for the tissues investigated. Measured organ doses for a chest-abdomen-pelvis CT protocol were less than 32 mGy for all organs measured. Organs that were completely irradiated during a given examination received similar doses, whereas organs that were partially irradiated displayed a large variation in measured organ dose.CONCLUSION:The anatomic and radiation attenuation characteristics of cadavers are comparable to those of living human tissue. This methodology allows direct measurement of organ doses from clinical CT examinations.

Purpose:To determine the quantitative effect of adipose tissue shielding on organ dose measurements in computed tomography (CT) and model the effects with organ dose equations.Methods:The post‐mortem dose measurement methodology established in house was utilized to perform organ dose measurements on subjects of varying body habitus for a clinically standardized chest/abdomen/pelvis (CAP) protocol and chest protocol on a 320‐slice CT scanner. The outer effective diameter was calculated obtaining the anterior/posterior and lateral dimensions of the entire anatomy imaged at the middle of the scan range, while the inner effective diameter used the AP and Lat dimensions of the anatomy excluding adipose tissue. These parameters determined effective diameter using Effective Diameter= SQRT(AP *Lat). The subjects were matched by their inner effective diameter and the effective shielding radius was calculated by subtracting the inner effective diameter from the outer effective diameter and dividing by two. The relationship to organ specific CTDI‐to‐organ dose conversion factors was analyzed using linear regression analysis.Results:Of 7 subjects scanned with both the CAP and chest protocols, three were found to have the same inner effective diameters. The calculated CTDI‐to‐organ‐dose conversion factors relationship with the effective internal shielding radius was analyzed using a linear regression analysis. The R2 value for organs within the inner effective diameter space to include lungs, liver, stomach, small intestine, colon, uterus, and ovary ranged from 0.74 to 0.99, with an average of 0.91 for the CAP equations. While the R2 values for the chest scans for lungs, liver, and stomach ranged from 0.98 to 0.9991 with an average of 0.99, showing a good linear fit.Conclusion:The effective internal shielding radius shows a strong correlation when matching similar inner effective diameters to the CTDI‐to‐organ‐dose conversion factors.

Medical PhysicsVolume 42, Issue 6Part6 p. 3247-3248 Fifty-seventh annual meeting of the American association of physicists in medicine SU-E-I-28: Introduction and Investigation of Effective Diameter Ratios as a New Patient Size Metric for Use in CT R Lamoureux, R Lamoureux Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorL Sinclair, L Sinclair Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorA Mench, A Mench Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorI Lipnharski, I Lipnharski Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorC Carranza, C Carranza Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorB Cormack, B Cormack Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorS Bidari, S Bidari Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorL Rill, L Rill Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorM Arreola, M Arreola Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this author R Lamoureux, R Lamoureux Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorL Sinclair, L Sinclair Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorA Mench, A Mench Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorI Lipnharski, I Lipnharski Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorC Carranza, C Carranza Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorB Cormack, B Cormack Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorS Bidari, S Bidari Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorL Rill, L Rill Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this authorM Arreola, M Arreola Gainesville, FL Portland, OR Salem Health, Tualatin, OR University of Florida, Gainesville, FL University of Florida, Gainesville, FL UF Health, Gainesville, FL University of Florida, Gainesville, FL Univ Florida, Jacksonville Beach, FL University of Florida Health Science Center, Gainesville, FLSearch for more papers by this author First published: 29 June 2015 https://doi.org/10.1118/1.4924025Citations: 1About ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract Purpose: To introduce and investigate effective diameter ratios as a new patient metric for use in computed tomography protocol selection as a supplement to patient-specific size parameter data. Methods: The metrics of outer effective diameter and inner effective diameter were measured for 7 post-mortem subjects scanned with a standardized chest/abdomen/pelvis (CAP) protocol on a 320-slice MDCT scanner. The outer effective diameter was calculated by obtaining the anterior/posterior and lateral dimensions of the imaged anatomy at the middle of the scan range using Effective Diameter= SQRT(AP height*Lat Width). The inner effective diameter was calculated with the same equation using the AP and Lat dimensions of the anatomy excluding the adipose tissue. The ratio of outer to inner effective diameter was calculated for each subject. A relationship to BMI, weight, and CTDI conversion coefficients was investigated. Results: For the largest subject with BMI of 43.85 kg/m2 and weight of 255 lbs the diameter ratio was calculated as 1.33. For the second largest subject with BMI of 33.5 kg/m2 and weight of 192.4 lbs the diameter ratio was measured as 1.43, indicating a larger percentage of adipose tissue in the second largest subject's anatomical composition. For the smallest subject at BMI of 17.4 kg/m2 and weight of 86 lbs a similar tissue composition was indicated as a subject with BMI of 24.2 kg/m2 and weight of 136 lbs as they had the same diameter ratios of 1.11. Conclusion: The diameter ratio proves to contain information about anatomical composition that the BMI and weight alone do not. The utility of this metric is still being examined but could prove useful for determining MDCT techniques and for giving a more in depth detail of the composition of a patient's body habitus. Citing Literature Volume42, Issue6Part6June 2015Pages 3247-3248 RelatedInformation

PURPOSE:To generate empirical sets of equations that can be used to calculate patient-specific organ doses resulting from a group of computed tomographic (CT) studies by using data from direct dose measurements performed within a human body.MATERIALS AND METHODS:Organ dose measurements were obtained in eight postmortem female subjects. A chest-abdomen-pelvis protocol was used for this study. The relationships among measured organ doses, body mass index, effective diameter (D(eff)), and volume CT dose index (CTDI(vol)) were investigated. Organ dose equations were developed by means of linear regression from organ dose data, with CTDI(vol) and D(eff) as variables, by using Pearson correlation coefficients and P values to determine correlation strength of fit. Measured organ doses were compared with corresponding size-specific dose estimates (SSDEs).RESULTS:The central-section D(eff) presented similar correlations with organ doses to those from D(eff) measured at specific organ locations. The strongest correlations were observed between the central-section D(eff) and CTDI(vol)-normalized organ doses (R(2): 0.478-0.941). The average of measured organ doses for each subject resulted in an average difference of only 5% from SSDE-calculated doses; however, individual organ doses differed from +31% to -61% from the calculated SSDE.CONCLUSION:The organ dose equations developed represent a method for organ dose estimation from direct organ dose measurements that can estimate organ doses more accurately than the calculated SSDE, which provides a less-specific patient dose estimate.

You have accessJournal of UrologyImaging/Radiology: Uroradiology (I)1 Apr 20132008 CHANGING DEFAULT FLUOROSCOPY EQUIPMENT SETTINGS DECREASES ABSORBED DOSE IN ENDOUROLOGY PATIENTS Diana Kang, Lindsay Sinclair, Blake Evans, Octavia Devon, Benjamin Canales, Manuel Arreola, and Vincent Bird Diana KangDiana Kang Gainesville, FL More articles by this author , Lindsay SinclairLindsay Sinclair Gainesville, FL More articles by this author , Blake EvansBlake Evans Gainesville, FL More articles by this author , Octavia DevonOctavia Devon Madison, WI More articles by this author , Benjamin CanalesBenjamin Canales Gainesville, FL More articles by this author , Manuel ArreolaManuel Arreola Gainesville, FL More articles by this author , and Vincent BirdVincent Bird Gainesville, FL More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2013.02.2427AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Urologists use fluoroscopy to outline anatomy during treatment of kidney stones. With increased health awareness of the potential risks of radiation, several studies have documented proper fluoroscopic education and protocols can reduce patient absorbed radiation dose. These studies are limited by lack of actual radiation measurements and appropriate control groups. Using miniature optically-stimulated luminescent (OSL) dosimeters, we performed a prospective trial to measure fluoroscopy times and patient entrance skin radiation dose before and after implementation of surgeon education and radiation reduction protocols. METHODS From September 2010 to October 2012, prospective data were collected from patients undergoing ureteroscopy (URS), percutaneous nephrolithotomy (PCNL), or retrograde pyelogram/stent (RPG) procedures at a single academic institution practice. In the pre-protocol phase OSL dosimeters were placed directly over bladder and kidney skin locations to measure radiation entrance skin dose. Practitioners were blinded to results. Urology faculty and residents took a validated radiation safety quiz followed by online and hands-on training given by a board certified diagnostic radiological physicist (MA). Faculty and residents retook the quiz and changed the default fluoroscopy equipment settings to intermittent (vs. continuous) pulse rate and to half (vs. full) power dose. Fluoroscopic times and radiation doses were measured in the post-protocol phase and compared. RESULTS Post-training scores by urology faculty and residents increased by 29 +/− 4% from pre-test. A total of 44 procedures were measured in the pre-protocol phase. Mean fluoroscopy times and absorbed skin dose pre-protocol were: 11.5 minutes and 35.4 mGy for PCNL procedures; 1.95 minutes and 0.3 mGy for URS; and 2.2 minutes and 0.4 mGy for RPGs. Fifty procedures were measured during the post-protocol phase. Times and absorbed dose were: 10.9 minutes and 23.8 mGy for PCNL (32.8% reduction); 2.47 minutes and 0.2 mGy for URS (26.4% reduction); and 2.36 minutes and 0.2 mGy for RPG (49.8% reduction). A total 46.1% reduction in absorbed skin dose was seen in the post-protocol phase overall. CONCLUSIONS In this unique prospective study, radiation safety training protocols did not affect fluoroscopy times, perhaps due to observer bias or pre-existing radiation safety awareness. However, changing default equipment settings decreased measured dose by 46% and should be considered across specialties as a simple mean to limit patient radiation exposure. © 2013 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 189Issue 4SApril 2013Page: e825 Advertisement Copyright & Permissions© 2013 by American Urological Association Education and Research, Inc.MetricsAuthor Information Diana Kang Gainesville, FL More articles by this author Lindsay Sinclair Gainesville, FL More articles by this author Blake Evans Gainesville, FL More articles by this author Octavia Devon Madison, WI More articles by this author Benjamin Canales Gainesville, FL More articles by this author Manuel Arreola Gainesville, FL More articles by this author Vincent Bird Gainesville, FL More articles by this author Expand All Advertisement Advertisement PDF DownloadLoading ...

Purpose: To compare directly measured organ doses in cadaveric subjects with calculated size‐specific dose estimates (SSDE) for CT studies of the torso. Methods: : In 2011, the SSDE protocols were introduced by AAPM Task Group 204, which provides a library of conversion factors that can be applied directly to scanner‐generated CTDIvol for a CT exam of the torso to generate a patient‐specific dose estimate. However, the results of the SSDE formalism have not been compared to actual dose measurements. In this work, several cadaveric subjects of varying body habitus, were utilized to directly measure organ doses which Result from CT examinations. Optically‐stimulated luminescent dosimeters (OSLDs) were employed to measure dose within the following organs: thyroid, breasts, lungs, liver, stomach, small intestine, colon, ovary, uterus, and skin. Dose measurements were made for a standard Chest Abdomen Pelvis (CAP) protocol. After organ dose measurements were completed for each subject, the anterior‐posterior and lateral patient dimensions were measured on the central slice of the study to obtain the corresponding correction factor and SSDE from AAPM 204, which was then compared with the measured organ doses for each cadaver. Results: A total of four subjects were utilized for this study, with body mass indices (BMIs) ranging from 17.4–43.9. For the subject with a BMI of 17.4, the average organ dose from a CAP exam was 11.8 mGy. The corresponding SSDE for that subject was 12 mGy. Conclusion: It is observed with this data that the SSDE does accurately describe the average dose absorbed in the body. The SSDE can be effectively used as a patient dose descriptor in the clinic, while organ dose libraries and software that allow for organ dose calculation are still being developed.

Purpose: In the field of Computed Tomography (CT) dosimetry, there remains a need to accurately measure organ doses. Such measurements are only meaningful if they are performed under actual clinical scanning conditions, for this purpose, a cadaver can serve as the measurement subject that most closely mimics a living patient. Organ doses were measured in 7 adult female cadaveric subjects with varying body mass indices (BMIs) and for various CT protocols. Methods: A tube placement system allowed external access to internal organs, in which optically‐stimulated luminescent dosimeters (OSLDs) were placed and used to measure dose. Dosimeter placement and location was based on organ size and distribution. In order to determine organ doses of real patients, a correlation between various patient size parameters and the measured organ doses was explored. Only measurements that could be performed on a CT image or subject‐specific parameters or data which could otherwise be obtained for an actual patient were considered for this correlation. The size parameters that were examined included: body mass index (BMI), the AP and lateral dimensions of the patient, and patient perimeter. Results: The BMIs for the 7 subjects ranged from 16.6–43.9, spanning from underweight to extreme obesity. Overall average organ doses from a CAP exam for all subjects ranged from 11.8–24.4 mGy. Generally, organ doses were shown to increase with all size parameters examined. Conclusion: For the purpose of accuracy, the estimation of patient dose in CT must be based on actual physical measurements. A complete set of direct organ dose measurements for 7 adult female cadavers has been accomplished for common CT exams with this research. It has been shown before that patient size parameters can be indicative of patient dose. This work has shown further validation of this concept.

Purpose: To quantify average organ dose reduction resulting from use of adaptive iterative image reconstruction algorithm in Computed Tomography (CT). Methods: To determine the average organ dose reduction offered by the Adaptive Iterative Dose Reduction algorithm (AIDR3D) on a Toshiba Aquilion One 320‐slice CT scanner, organ doses were directly measured utilizing a method involving cadaveric subjects and optically‐stimulated luminescent dosimeters (OSLDs). Three female cadaveric subjects of various body habitus were scanned for the case of a clinically standardized Chest Abdomen Pelvis (CAP) protocol. Average organ doses were measured using OSLDs inserted into the breasts, lungs, liver, stomach, small intestine, colon, ovary, and uterus and placed on the skin of the cadavers. Measurements were first obtained for a standard non‐contrast CAP exam and then again, under identical scanning conditions, with the AIDR3D turned on. Measured doses were compared between the two scans for each of the organs. Results: Average organ dose reduction ranged from as low as 4% to as high as 66% for various organs. When averaged across all organs, the overall percent reduction amongst the three cadaveric subjects ranged from 18% to 46%. Significant dose reduction was noted for the lungs, breast and uterus in all three cadaveric subjects. The cadaveric subject with the lowest BMI level experienced the most prominent reduction in organ doses when compared to the subjects of higher BMI. Conclusions: As CT continues to be an indispensable tool in diagnostic radiology, future technological developments will remain focused on dose reduction methods. From this work it is clear that use of the AIDR 3D image reconstruction algorithm offers significant organ dose savings to patients. Based on recent literature and our own clinical experience, the dose savings do not come at the cost of degraded image quality.

Purpose: To quantify the breast dose delivered to female patients undergoing routine thoracic Computed Tomography (CT) exams and assess the dose savings provided by the use of bismuth shielding as well as iterative image reconstruction algorithms. Methods: Breast shields have been used at the University of Florida for three years with unanimous agreement by radiologists in terms of acceptable image quality and nonexistent artifacts. To assess the dose savings provided by both bismuth shields and adaptive iterative reconstruction algorithms (AIDR 3D), breast doses were directly measured on cadaveric subjects using optically‐stimulated luminescent dosimeters (OSLDs) implanted via tubes into the subjects. The cadavers were scanned with the clinically standardized Chest protocol on a Toshiba Aquilion One 320‐slice CT scanner. Next, they were scanned again, with all other parameters unchanged, using the bismuth shield and finally using the AIDR 3D algorithm. Average breast doses were measured for four female cadaveric subjects of various Body Mass Indices (BMIs). Breast doses were measured with the bismuth shield in place for two cadavers, while the AIDR 3D algorithm was investigated using the second pair of subjects. Tube current modulation was activated for all scans. Results: Average breast doses for all four cadaver subjects ranged from 7 to 24 mGy. Dose savings offered by the bismuth breast shield were 27% for the smaller cadaver and 18% for the larger cadaver. The set of subjects scanned with AIDR 3D turned on received an average breast dose savings of 26% and 21%, for the lower and higher BMI subjects, respectively. Conclusion: This research reveals that both bismuth shielding and iterative reconstruction algorithms are effective methods of reducing radiation dose to highly radiosensitive breast tissue. Neither of these methods has impacted clinical image quality negatively. Employing dose savings methods, however trivial or complex, benefits patients tremendously.

Purpose: The skeleton is of critical interest in internal radiation dosimetry. Accurate absorbed dose estimates to the hematopoietic tissues in the active (red) bone marrow and osteogenic tissues in the shallow active bone marrow are of primary importance in predicting the short‐term deterministic (myelotoxicity) and long‐term stochastic (leukemia and/or osteosarcomas induction) effects of radiation exposure. Presently, there are no international standards for skeletal reference models that are based upon a female subject. The purpose of this project is to complete the skeletal model for the ICRP reference adult female. Method and Materials: The development of this female skeletal reference model involves harvesting of major skeletal sites, as well as ex‐vivo CT imaging of the skeletal sites. The ex‐vivo CT scans provide image data for quantifying both trabecular spongiosa and cortical bone ratios within the bone site through manual image segmentation and constructing 3D anatomic models of the bone site for subsequent paired‐image radiation transport simulations. After review of each bone site's ex‐vivo CT scan, samples of spongiosa are strategically excised for imaging via microCT. Next, the microCT scans of each bone site's microstructure and ex‐vivo CT scans of each bone site's macrostructure are coupled and imported into the PIRT (Paired‐Image Radiation Transport) code. PIRT is able to track particle energy deposition both at the macroscopic scale and the microscopic scale simultaneously. Results: The end result of running these simulations will be absorbed dose estimates to the active bone marrow from the following sources: cortical bone surface and volume sources, trabecular bone surface and volume sources, and the trabecular active marrow itself. These will be compiled and available for use in estimating dose for the reference adult female. Conclusion: This reference skeletal model will be used to determine skeletal masses and accurate bone marrow dose estimates from radiation exposures.