The impact of anthropometric patient‐phantom matching on organ dose: A hybrid phantom study for fluoroscopy guided interventions

Abstract

Purpose: To investigate the benefits and limitations of patient-phantom matching for determining organ dose during fluoroscopy guided interventions. Methods: In this study, 27 CT datasets representing patients of different sizes and genders were contoured and converted into patient-specific computational models. Each model was matched, based on height and weight, to computational phantoms selected from the UF hybrid patientdependent series. In order to investigate the influence of phantom type on patient organ dose, Monte Carlo methods were used to simulate two cardiac projections ͑PA/left lateral͒ and two abdominal projections ͑RAO/LPO͒. Organ dose conversion coefficients were then calculated for each patientspecific and patient-dependent phantom and also for a reference stylized and reference hybrid phantom. The coefficients were subsequently analyzed for any correlation between patientspecificity and the accuracy of the dose estimate. Accuracy was quantified by calculating an absolute percent difference using the patient-specific dose conversion coefficients as the reference. Results: Patient-phantom matching was shown most beneficial for estimating the dose to heavy patients. In these cases, the improvement over using a reference stylized phantom ranged from approximately 50% to 120% for abdominal projections and for a reference hybrid phantom from 20% to 60% for all projections. For lighter individuals, patient-phantom matching was clearly superior to using a reference stylized phantom, but not significantly better than using a reference hybrid phantom for certain fields and projections. Conclusions:The results indicate two sources of error when patients are matched with phantoms: Anatomical error, which is inherent due to differences in organ size and location, and error attributed to differences in the total soft tissue attenuation. For small patients, differences in soft tissue attenuation are minimal and are exceeded by inherent anatomical differences. For large patients, difference in soft tissue attenuation can be large. In these cases, patient-phantom matching proves most effective as differences in soft tissue attenuation are mitigated. With increasing obesity rates, overweight patients will continue to make up a growing fraction of all patients undergoing medical imaging. Thus, having phantoms that better represent this population represents a considerable improvement over previous methods. In response to this study, additional phantoms representing heavier weight percentiles will be added to the UFHADM and UFHADF patient-dependent series.

Construction of patient‐specific computational models for organ dose estimation in radiological imaging

“…A potential alternative for person‐specific organ dose estimation is to use a library of computational models where habitus‐specific phantoms could serve as alternative models covering various anthropometric and anatomical characteristics of patients . Several habitus‐dependent phantom series have been developed to perform patient‐specific dose estimation by matching anthropometric characteristics of patients, such as gender, age, height, and body weight . Stepusin et al suggested to match patient's data to a computational phantom from a predefined library using height and weight matching for patient‐specific CT dosimetry.…”

Assessment of different patient‐to‐phantom matching criteria applied in Monte Carlo–based computed tomography dosimetry

“…For this study, 52 patient CT image sets were obtained and segmented using 3D‐DOCTOR™ (Able Software Corporation, Lexington, MA, USA). Of these patients, 13 were adult females (previously segmented), 13 were adult males (previously segmented), 13 were pediatric females, and 13 were pediatric males . Eight organs of interest (bladder, heart wall, kidney, liver, lung, pancreas, spleen, and stomach) and homogeneous bone were manually segmented and imported into 3D‐modeling software Rhinoceros™ (Robert McNeel & Associates, Seattle, WA, USA).…”

Skin dose mapping for fluoroscopically guided interventions

“…In a previous study by the authors, patientphantom matching was shown effective for increasing the accuracy of organ dose estimation for larger than average patients. 24 Organ size and location, however, played a large role in limiting the effectiveness for smaller than average patients. For skin dose mapping, the primary factor affecting dose is the calculation of the source-to-skin distance.…”

“…The patient-specific phantoms were created previously during the organ dose study by contouring CT datasets retrieved under IRB approval from the PACS system at Shands Jacksonville Medical Center. 24 The major axis represented the patient's lateral width, and the semiminor axis represented the patient's posterior/anterior width as measured for a supine patient. In total, six measurements were needed to create the phantoms and are illustrated in Fig.…”

“…The selection process mirrored that followed in our previous organ dose study. 24 Finally, PSD was calculated using the uniquely created contour phantom which matched the patient as described previously. Accuracy was then quantified for each phantom type by calculating a percent-difference using the patient-specific dose as the true value.…”